# OMAS Public Analytic Data Variable Descriptions

## 1 Introduction

This document is intended to provide clarity on how the GRC created the variables produced in its recoding of the variables provided by RTI. Some additional details about the origin of these variables are provided here to give context about the meaning of the recoded variables. If a variable is ends with “_IMP”, then it has been imputed by RTI. A full codebook for the variables provided by RTI can be found on the OMAS Website.

Responses indicating that a respondent didn’t know the answer to a question or refused to answer a question were recoded to NA for all variables. In some cases, a variable derived from a question where a respondent did not provide an answer might still have a non-missing response - these recoding rules are described for each such variable.

Recoded variables that are indicators for respondent characteristics are coded so that a value of “1” indicates the respondent has that characteristic and a value of “0” indicates that the respondent does not have that characteristic.

## 2 Adult Variable Descriptions

### 2.1 Access to Care

#### 2.1.1 ac_avoid

Years: 2017, 2019, 2021
Description: Indicator for delaying or avoiding health care they felt they needed in the past 12 months
Coding Details: This is derived from question AVOID_CARE (“During the past 12 months, did you delay or avoid getting care that you felt you needed?”).

#### 2.1.2 ac_avoid_avail

Years: 2019, 2021
Description: Indicator for delaying or avoiding health care in the past 12 months because the provider was not available when needed
Coding Details: This is derived from question AVOID_CAREc (“Did you delay or avoid getting care over the past 12 months because the provider was not available when you needed to go?”). This variable is only populated for respondents who delayed or avoided health care they felt they needed in the past 12 months (ac_avoid).

#### 2.1.3 ac_avoid_cost

Years: 2019, 2021
Description: Indicator for delaying or avoiding health care in the past 12 months because of the cost
Coding Details: This is derived from question AVOID_CAREa (“Did you delay or avoid getting care over the past 12 months because you thought it would cost too much?”). This variable is only populated for respondents who delayed or avoided health care they felt they needed in the past 12 months (ac_avoid).

#### 2.1.4 ac_avoid_cvd

Years: 2021
Description: Indicator for delaying or avoiding health care in the past 12 months because of the COVID-19 pandemic
Coding Details: This is derived from question WHY_AVOIDe (“Did you delay or avoid getting medical care because you did not want to visits a provider’s office because of COVID-19?”). This variable is only populated for respondents who delayed or avoided health care they felt they needed in the past 12 months (ac_avoid).

#### 2.1.5 ac_avoid_find

Years: 2019, 2021
Description: Indicator for delaying or avoiding health care in the past 12 months because they could not find a provider
Coding Details: This is derived from question AVOID_CAREd (“Did you delay or avoid getting care over the past 12 months because you could not find a provider?”). This variable is only populated for respondents who delayed or avoided health care they felt they needed in the past 12 months (ac_avoid).

#### 2.1.6 ac_avoid_trnsp

Years: 2019, 2021
Description: Indicator for delaying or avoiding health care in the past 12 months because they did not have transportation
Coding Details: This is derived from question AVOID_CAREb (“Did you delay or avoid getting care over the past 12 months because you did not have transportation to or from appointments?”). This variable is only populated for respondents who delayed or avoided health care they felt they needed in the past 12 months (ac_avoid).

#### 2.1.7 ac_harder

Years: 2010, 2012, 2015, 2019
Description: Indicator for finding it harder to get medical care now than three years ago
Coding Details: This variable indicates that a respondent answered “Harder” to question F69 (2010, 2012, 2015) or question F69_NEW (2019) (“Compared with three years ago, is getting the medical care you need becoming easier, harder, or has it stayed the same?”). The 2019 version of the question differs in that it includes an additional option for not needing medical care.

#### 2.1.8 ac_uslsrc_fac

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for having a usual source of medical care
Coding Details: This variable is derived from question F67 (prior to 2021: “Is there one place that you usually go to when you are sick or need advice about your health?”; 2021 on: “When you are sick or need advice about your health, do you usually receive care at one place, more than one place, or no place at all?”).

##### Variable Levels

- Does Not have a Usual Source of Care
- Has a Usual Source of Care

#### 2.1.9 ac_uslsrc_not_ed

Years: 2019, 2021, 2023
Description: Indicator for having a usual source of medical care that is not an emergency department
Coding Details: This variable indicates that a respondent’s value for ac_uslsrc_place (a factor for usual source of care) is not “Hospital ER” or “No Usual Source of Care”.

#### 2.1.10 ac_uslsrc_place

Years: 2019, 2021, 2023
Description: Factor for place of usual source of medical care
Coding Details: This variable is derived using questions F67 (prior to 2021: “Is there one place that you usually go to when you are sick or need advice about your health?”; 2021 on: “When you are sick or need advice about your health, do you usually receive care at one place, more than one place, or no place at all?”) and F67_2 (“Is the place where you usually receive care or advice about your health a doctor’s office or health center, including by phone or video call, a hospital emergency room, an urgent care center, including by phone or video call, a clinic in a pharmacy or grocery store, or some other place?”).

##### Variable Levels

- No Usual Source of Care
- Doctor’s Office or Health Center
- Hospital ER
- Urgent Care Center
- Clinic in a Pharmacy or Grocery Store
- Some Other Place

### 2.2 Chronic Conditions

#### 2.2.1 cc_any

Years: 2012, 2015, 2017, 2019, 2023
Description: Indicator for ever being diagnosed with a chronic condition
Coding Details: This variable is derived from questions asking respondents if they have ever been diagnosed with the following chronic conditions: hypertension (D41), asthma (D44), congestive heart failure (D41D), a stroke (D41C), high cholesterol (D42), coronary heart disease (D41B), and a heart attack (D41A). If the respondent answered “Yes” to any of these questions, then this variable is coded as 1. If they did not answer “Yes” to any of these questions and answered “No” to at least one, then it is coded as 0.

#### 2.2.2 cc_any_hrt_fac

Years: 2012, 2015, 2017, 2019, 2023
Description: Factor for ever being diagnosed with a heart attack, coronary heart disease, or congestive heart failure
Coding Details: This variable is derived from cc_any_hrt (an indicator for ever having a heart attack, coronary heart disease, or congestive heart failure).

##### Variable Levels

- Never Diagnosed with Any Heart Disease
- Ever Diagnosed with Any Heart Disease

#### 2.2.3 cc_asth_fac

Years: 2019, 2023
Description: Factor for ever being diagnosed with asthma
Coding Details: This variable is derived from cc_asth (an indicator for ever being diagnosed with asthma).

##### Variable Levels

- Never Diagnosed with Asthma
- Ever Diagnosed with Asthma

#### 2.2.4 cc_cncr_fac

Years: 2023
Description: Factor for ever being diagnosed with cancer
Coding Details: This variable is derived from cc_cncr (an indicator for ever being diagnosed with cancer).

##### Variable Levels

- Never Diagnosed with Cancer
- Ever Diagnosed with Cancer

#### 2.2.5 cc_cong_hrt_fac

Years: 2012, 2015, 2017, 2019, 2023
Description: Factor for ever being diagnosed with congestive heart failure
Coding Details: This variable is derived from cc_cong_hrt (an indicator for ever being diagnosed with congestive heart failure).

##### Variable Levels

- Never Diagnosed with Congestive Heart Failure
- Ever Diagnosed with Congestive Heart Failure

#### 2.2.6 cc_copd_fac

Years: 2023
Description: Factor for ever being diagnosed with with COPD
Coding Details: This variable is derived from cc_copd (an indicator for ever being diagnosed with COPD).

##### Variable Levels

- Never Diagnosed with COPD
- Ever Diagnosed with COPD

#### 2.2.7 cc_cor_hrt_fac

Years: 2012, 2015, 2017, 2019, 2023
Description: Factor for ever being diagnosed with coronary heart disease
Coding Details: This variable is derived from cc_cor_hrt (an indicator for ever being diagnosed with coronary heart disease).

##### Variable Levels

- Never Diagnosed with Coronary Heart Disease
- Ever Diagnosed with Coronary Heart Disease

#### 2.2.8 cc_dbts21

Years: 2021, 2023
Description: Factor for ever being diagnosed with diabetes or borderline diabetes
Coding Details: This variable categorizes diabetes status into three categories based on question D43 (“Has a doctor or other health professional ever told you that you had diabetes?”). In 2021, an third answer option for “Borderline Diabetes” was added.

##### Variable Levels

- Ever Diagnosed with Diabetes
- Never Diagnosed with Diabetes
- Ever Diagnosed with Borderline Diabetes

#### 2.2.9 cc_dbts21_preg

Years: 2021, 2023
Description: Factor for ever being diagnosed with diabetes or borderline diabetes and relation to pregnancy among women 44 years old and younger
Coding Details: This variable categories diabetes status into categories based on cc_dbts21 (factor for ever being diagnosed with diabetes or borderline diabetes) and question D43B (“Was your diabetes/borderline diabetes only during a time associated with a pregnancy?”). This variable is only populated for female respondents who are 44 years old or younger.

##### Variable Levels

- Never Diagnosed with Diabetes
  - Level Details: cc_dbts21 = “No”
- Diagnosed with Diabetes Only During Pregnancy
  - Level Details: cc_dbts21 in (“Ever Diagnosed with Diabetes”, “Ever Diagnosed with Borderline”) and D43B = “Yes”
- Ever Diagnosed with Diabetes Outside of Pregnancy
  - Level Details: cc_dbts21 in (“Ever Diagnosed with Diabetes”, “Ever Diagnosed with Borderline”) and D43B = “No”

#### 2.2.10 cc_dbts_fac

Years: 2012, 2015, 2017, 2019
Description: Factor for ever being diagnosed with diabetes
Coding Details: This variable is derived from cc_dbts (an indicator for ever being diagnosed with diabetes).

##### Variable Levels

- Never Diagnosed with Diabetes
- Ever Diagnosed with Diabetes

#### 2.2.11 cc_hchol_fac

Years: 2019, 2023
Description: Factor for ever being diagnosed with high cholesterol
Coding Details: This variable is derived from cc_hchol (an indicator for ever being diagnosed with high cholesterol).

##### Variable Levels

- Never Diagnosed with High Cholesterol
- Ever Diagnosed with High Cholesterol

#### 2.2.12 cc_hrt_atk_fac

Years: 2012, 2015, 2017, 2019, 2023
Description: Factor for ever being diagnosed with a heart attack
Coding Details: This variable is derived from cc_hrt_atk (an indicator for ever being diagnosed with heart attack).

##### Variable Levels

- Never Diagnosed with Heart Attack
- Ever Diagnosed with Heart Attack

#### 2.2.13 cc_hyper_fac

Years: 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for ever being diagnosed with high blood pressure or hypertension
Coding Details: This variable is derived from cc_hyper (an indicator for ever being diagnosed with high blood pressure or hypertension).

##### Variable Levels

- Never Diagnosed with Hypertension
- Ever Diagnosed with Hypertension

#### 2.2.14 cc_stroke_fac

Years: 2012, 2019, 2023
Description: Factor for ever being diagnosed with a stroke
Coding Details: This variable is derived from cc_stroke (an indicator for ever being diagnosed with a stroke).

##### Variable Levels

- Never Diagnosed with Stroke
- Ever Diagnosed with Stroke

### 2.3 Community Problems

#### 2.3.1 cp_crime

Years: 2023
Description: Factor for how big of a problem crime is in their community
Coding Details: This variable is derived from question CM_PRB02 (“How big a problem to do you think the following issues are in your community? Crime.”)

##### Variable Levels

- Very or Moderately Big Problem
- Small Problem or Not a Problem at All
- Don’t Know or Missing

#### 2.3.2 cp_drug

Years: 2023
Description: Factor for how big of a problem drug addiction is in their community
Coding Details: This variable is derived from question CM_PRB03 (“How big a problem to do you think the following issues are in your community? Drug Addiction.”)

##### Variable Levels

- Very or Moderately Big Problem
- Small Problem or Not a Problem at All
- Don’t Know or Missing

#### 2.3.3 cp_food

Years: 2023
Description: Factor for how big of a problem paying for food is in their community
Coding Details: This variable is derived from question CM_PRB05 (“How big a problem to do you think the following issues are in your community? Paying for food.”)

##### Variable Levels

- Very or Moderately Big Problem
- Small Problem or Not a Problem at All
- Don’t Know or Missing

#### 2.3.4 cp_house

Years: 2023
Description: Factor for how big of a problem paying for housing is in their community
Coding Details: This variable is derived from question CM_PRB06 (“How big a problem to do you think the following issues are in your community? Paying for housing.”)

##### Variable Levels

- Very or Moderately Big Problem
- Small Problem or Not a Problem at All
- Don’t Know or Missing

#### 2.3.5 cp_jobs

Years: 2023
Description: Factor for how big of a problem lack of jobs is in their community
Coding Details: This variable is derived from question CM_PRB04 (“How big a problem to do you think the following issues are in your community? Lack of jobs.”)

##### Variable Levels

- Very or Moderately Big Problem
- Small Problem or Not a Problem at All
- Don’t Know or Missing

#### 2.3.6 cp_transp

Years: 2023
Description: Factor for how big of a problem transportation is in their community
Coding Details: This variable is derived from question CM_PRB01 (“How big a problem to do you think the following issues are in your community? Access to transportation.”)

##### Variable Levels

- Very or Moderately Big Problem
- Small Problem or Not a Problem at All
- Don’t Know or Missing

### 2.4 Demographics

#### 2.4.1 dem_age

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor categorizing by age
Coding Details: This variable is derived from S14_IMP (“How old were you on your last birthday?”).

##### Variable Levels

- 19-24
- 25-34
- 35-44
- 45-54
- 55-64
- 65-74
- 75+

#### 2.4.2 dem_age_cont

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Numeric age in years, topcoded at 75
Coding Details: This variable is derviced from S14_IMP (“How old were you on your last birthday?”) and is topcoded at 75 (i.e., all respondents 75+ are coded as being 75).

#### 2.4.3 dem_educ

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for education with six levels
Coding Details: This variable is derived from EDUC_IMP (“What is the highest level of school you have completed or the highest degree received?”).

##### Variable Levels

- Up to High School but No Diploma
  - Level Details: EDUC_IMP = 1,2,3 (2010) or 1 (2012 to 2021) or 1,2 (2023 on)
- High School Graduate or Equivalent
  - Level Details: EDUC_IMP = 4 (2010) or 2 (2012 to 2021) or 3,4 (2023 on)
- Some College
  - Level Details: EDUC_IMP = 5 (2010) or 3 (2012 to 2021) or 5 (2023 on)
- Associate Degree
  - Level Details: EDUC_IMP = 6 (2010) or 4 (2012 to 2021) or 6 (2023 on)
- 4-Year College Graduate
  - Level Details: 2010: EDUC_IMP = 7 (2010) or 5 (2012 to 2021) or 7 (2023 on)
- Advanced Degree
  - Level Details: EDUC_IMP = 8 (2010) or 6 (2012 to 2021) or 8 (2023 on)

#### 2.4.4 dem_educ_3lev

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for education with three levels
Coding Details: This variable is derived from dem_educ (a factor for education with six levels).

##### Variable Levels

- High School Degree or Less
  - Level Details: dem_educ = “Up to High School but No Diploma”,“High School Graduate or Equivalent”
- Some College
  - Level Details: dem_educ = “Some College” , “Associate Degree”
- 4-Year College or More
  - Level Details: dem_educ = “4-Year College Graduate”,“Advanced Degree”

#### 2.4.5 dem_educ_4lev

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for education with four levels
Coding Details: This variable is derived from dem_educ (a factor for education with six levels).

##### Variable Levels

- Up to High School but No Diploma
  - Level Details: dem_educ = “Up to High School but No Diploma”
- High School Graduate or Equivalent
  - Level Details: dem_educ =“High School Graduate or Equivalent”
- Some College
  - Level Details: dem_educ = “Some College” , “Associate Degree”
- 4-year college or more
  - Level Details: dem_educ = “4-Year College Graduate”,“Advanced Degree”

#### 2.4.6 dem_famtype

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for family type
Coding Details: This variable is derived from FAM_TYPE (2010) or FAM_TYPE_IMP (all other years).

##### Variable Levels

- 1 Adult and No Kids
- 1 Adult and 1+ Kids
- 2+ Adults and No Kids
- 2+ Adults and 1+ Kids

#### 2.4.7 dem_live_alone

Years: 2021, 2023
Description: Factor for living alone
Coding Details: This variable is derived using the sum of NUM_ADULTS_IMP (“How many members of your household, including yourself, are 19 years of age or older?”) and S12_IMP (“How many children 18 years of age or younger live in your household, whether they are family members or not?”).

##### Variable Levels

- Living Alone
- Living with One or More Person

#### 2.4.8 dem_live_sitch

Years: 2010, 2012, 2019
Description: Factor for living situation
Coding Details: This variable is derived from question CELL1 (2010), HOME2 (2012), or F3 (2019). A respondent is categorized in “Other” if they answered that their current living quarters were “Occupied without payment of cash rent” (2010, 2012) or answered that they currently “Stay with friends or family without paying rent”, “Live in a shelter or some other temporary housing”, or “Are currently homeless” (2019).

##### Variable Levels

- Own or Pay a Mortgage on Home
- Pay Rent
- Other

#### 2.4.9 dem_marital

Years: 2010, 2012, 2015, 2017, 2019, 2021
Description: Factor for marital status with five levels
Coding Details: This variable is derived from H76, which asks for a respondent’s marital status.

##### Variable Levels

- Married
- Divorced or Separated
- Widowed
- Never Married
- Unmarried Couple

#### 2.4.10 dem_marital23

Years: 2023
Description: Factor for marital status with four levels
Coding Details: This variable is derived from MRD_IMP (“What is your current marital status?”).

##### Variable Levels

- Married
  - Level Details: MRD_IMP = 1
- Divorced or Separated
  - Level Details: MRD_IMP = 3,4
- Widowed
  - Level Details: MRD_IMP = 2
- Never Married
  - Level Details: MRD_IMP = 5

#### 2.4.11 dem_married

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for marital status with two levels
Coding Details: This variable is derived from dem_marital (up to 2021) or dem_marital23 (2023 on).

##### Variable Levels

- Unmarried
- Married

#### 2.4.12 dem_parent_hshld

Years: 2019, 2021, 2023
Description: Indicator for being a parent of any child in their household
Coding Details: This variable is derived from S13a (“Are you a parent of the child living in your household?) and S13b_IMP (”How many of the children living in your household are family members?).

#### 2.4.13 dem_raceeth

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for race/ethnicity with four levels
Coding Details: This variable is derived from RACE5_A_IMP (2012, 2021) or RACE4_A_IMP (all other years). The “White or Other, non-Hispanic” category includes multiracial, non-Hispanic, individuals.

##### Variable Levels

- White or Other, non-Hispanic
- Black, non-Hispanic
- Hispanic
- Asian, non-Hispanic

#### 2.4.14 dem_raceeth_5lev

Years: 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for race/ethnicity with five levels
Coding Details: This variable is derived from RACE5_A_REC_IMP (2012) or RACE5_A_IMP (all other years). The “Other, non-Hispanic” category includes multiracial, non-Hispanic, individuals.

##### Variable Levels

- White, non-Hispanic
- Black, non-Hispanic
- Hispanic
- Asian, non-Hispanic
- Other, non-Hispanic

#### 2.4.15 dem_sex

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for sex
Coding Details: This variable is derived from S15_IMP (“What is your sex?”).

##### Variable Levels

- Male
- Female

#### 2.4.16 dem_usaf_ever

Years: 2010, 2015, 2017, 2019, 2021, 2023
Description: Indicator for ever serving in the United States Armed Forces
Coding Details: This variable is derived from question H78 (“Have you ever served in the United States Armed Forces?)).

#### 2.4.17 dem_usaf_fac

Years: 2021, 2023
Description: Factor for service in the United States Armed Forces
Coding Details: This variable is derived from questions H78 (“Have you ever served in the United States Armed Forces?) and ML_NOW (”Are you currently serving in the United States Armed Forces?“).

##### Variable Levels

- Never Served
  - Level Details: H78 = “No”
- Currently Serving
  - Level Details: H78 = “Yes” and ML_NOW = “Yes”
- Formerly Served
  - Level Details: H78 = “Yes” and ML_NOW = “No”

### 2.5 Disability

#### 2.5.1 disab_acs

Years: 2019, 2021, 2023
Description: ACS Disability Indicator (Indicator for having serious difficulty with at least one Activity of Daily Living (ADL))
Coding Details: This variable indicates serious difficulty with at least one daily task addressed in questions CDC_1 to CDC_6 (2019) or CDC_1_IMP to CDC_6_IMP (2021 on): hearing, seeing, walking, dressing/bathing, concentrating/remembering/making decisions, and doing errands alone. This is based on the American Community Survey’s definition of adult disability.

#### 2.5.2 disab_comm_dif

Years: 2023
Description: Factor for level of difficulty communicating using their usual language
Coding Details: This variable is derived from question COM_SS (“Using your usual language, do you have difficulty communicating, for example understanding or being understood?”).

##### Variable Levels

- No Difficulty
- Some Difficulty
- A Lot of Difficulty
- Cannot Communicate at All

#### 2.5.3 disab_comm_onst

Years: 2023
Description: Indicator for difficulty communicating using their usual language beginning before age 22 among those with difficulty communicating using their usual language
Coding Details: This variable is derived from questions COM_SS (“Using your usual language, do you have difficulty communicating, for example understanding or being understood?”) and AG_ONST_CM (“Did this difficulty communicating begin before age 22?”). All respondents who have difficulty communicating (disab_comm_dif) and are younger than 22 (dem_age_cont) are assigned a value of 1 automatically.

#### 2.5.4 disab_dif_dress

Years: 2019, 2021, 2023
Description: Indicator for having serious difficulty dressing or bathing
Coding Details: This variable is derived from question CDC_4 (2019; “Do you have difficulty dressing or bathing?”) or CDC_4_IMP (2021 on).

#### 2.5.5 disab_dif_errand

Years: 2019, 2021, 2023
Description: Indicator for having difficulty doing errands alone
Coding Details: This variable is derived from question CDC_6 (2019; “Because of a physical, mental, or emotional condition, do you have difficulty doing errands alone, such as visiting a doctor’s office or shopping?”) or CDC_6_IMP (2021 on).

#### 2.5.6 disab_dif_hear

Years: 2019, 2021, 2023
Description: Indicator for having serious difficulty hearing
Coding Details: This variable is derived from question CDC_1 (2019; “Are you deaf or do you have serious difficulty hearing?”) or CDC_1_IMP (2021 on).

#### 2.5.7 disab_dif_memory

Years: 2019, 2021, 2023
Description: Indicator for having serious difficulty concentrating, remembering, or making decisions
Coding Details: This variable is derived from question CDC_5 (2019; “Because of a physical, mental, or emotional condition, do you have serious difficulty concentrating, remembering, or making decisions?”) or CDC_5_IMP (2021 on).

#### 2.5.8 disab_dif_see

Years: 2019, 2021, 2023
Description: Indicator for having serious difficulty seeing (even with glasses)
Coding Details: This variable is derived from question CDC_2 (2019; “Are you blind, or do you have serious difficulty seeing, even when wearing glasses?”) or CDC_2_IMP (2021 on).

#### 2.5.9 disab_dif_walk

Years: 2019, 2021, 2023
Description: Indicator for having serious difficulty walking or climbing stairs
Coding Details: This variable is derived from question CDC_3 ( 2019; “Do you have serious difficulty walking or climbing stairs?”) or CDC_3_IMP (2021 on).

#### 2.5.10 disab_dvlp

Years: 2015, 2017, 2019, 2021, 2023
Description: Indicator for having a developmental disability
Coding Details: This variable is derived from question ADULT_DD (2015, 2017, 2019; “Do you have a developmental disability?”) or ADULT_DD_IMP (all other years).

#### 2.5.11 disab_onst_dress

Years: 2019, 2021, 2023
Description: Indicator for serious difficulty dressing or bathing beginning before age 22 among those with serious difficulty dressing or bathing
Coding Details: This variable is derived from questions CDC_4_IMP (“Do you have difficulty dressing or bathing?”) and AG_ONST_4 (“Did this serious difficulty with dressing or bathing begin before age 22?”). All respondents who have serious difficulty dressing or bathing (disab_dif_dress) and are younger than 22 (dem_age_cont) are assigned a value of 1 automatically.

#### 2.5.12 disab_onst_errand

Years: 2019, 2021, 2023
Description: Indicator for difficulty doing errands alone beginning before age 22 among those with difficulty doing errands alone
Coding Details: This variable is derived from questions CDC_6_IMP (“Because of a physical, mental, or emotional condition, do you have difficulty doing errands alone, such as visiting a doctor’s office or shopping?”) and AG_ONST_6 (“Did this difficulty doing errands alone begin before age 22?”). All respondents who have difficulty doing errands alone (disab_dif_errand) and are younger than 22 (dem_age_cont) are assigned a value of 1 automatically.

#### 2.5.13 disab_onst_walk

Years: 2019, 2021, 2023
Description: Indicator for serious difficulty walking or climbing stairs beginning before age 22 among those with serious difficulty walking or climbing stairs
Coding Details: This variable is derived from questions CDC_3_IMP (“Do you have serious difficulty walking or climbing stairs?”) and AG_ONST_3 (“Did this serious difficulty with walking or climbing stairs begin before age 22?”). All respondents who have serious difficulty walking or climbing stairs (disab_dif_walk) and are younger than 22 (dem_age_cont) are assigned a value of 1 automatically.

### 2.6 Financial Stress

#### 2.6.1 fs_debt_dif

Years: 2023
Description: Indicator for having difficulty paying debt in the past 12 months
Coding Details: This variable is derived from question PY_DBT (“During the past 12 months, at any point did you have difficulty paying any debt that you have?”).

#### 2.6.2 fs_debt_harder

Years: 2017, 2019
Description: Indicator for finding it harder to pay off debt in past 12 months
Coding Details: This variable is derived from question DEBT_12MO (“In the past 12 months, has it gotten easier, harder, or stayed the same to pay off any debt that you had?”).

#### 2.6.3 fs_food_dif

Years: 2023
Description: Indicator for having difficulty paying for food for family or household in the past 12 months
Coding Details: This variable is derived from question PY_FD (“During the past 12 months, at any point did you have difficulty paying for food for your family or household?”).

#### 2.6.4 fs_food_ebt

Years: 2023
Description: Indicator for having used EBT/Food Stamps in the past thirty days
Coding Details: This variable is derived from question FD_EBT (“During the past 30 days, have you used an EBT or Food Stamp benefit card?”).

#### 2.6.5 fs_food_out

Years: 2019, 2023
Description: Indicator for having food run out before getting money to buy more in the past 12 months
Coding Details: This variable is derived from question FOOD_OUT (“At any time in the past 12 months, have you run out of food before you got money to buy more?”).

#### 2.6.6 fs_food_worry

Years: 2019, 2023
Description: Indicator for having worried food will run out before getting money to buy more in the past 12 months
Coding Details: This variable is derived from question FOOD_WORRY (“At any time in the past 12 months, have you worried whether food would run out before you got money to buy more?”).

#### 2.6.7 fs_med_bills

Years: 2017, 2019, 2021, 2023
Description: Indicator for having a problem paying medical bills in the past 12 months
Coding Details: This variable is derived from question F70 (“During the past 12 months, were there times when you had problems paying or you were unable to pay for medical bills for yourself or anyone else in the family or household?”).

#### 2.6.8 fs_rent_4lev

Years: 2017, 2019, 2021
Description: Factor for how hard it was to pay rent or mortgage in past 12 months
Coding Details: This variable is derived from question RENT_12MO (“In the past 12 months, has it gotten easier, harder, or stayed the same to pay your rent or mortgage?”).

##### Variable Levels

- Easier
- Harder
- Stayed the Same
- Did Not have a Rent or Mortgage Payment

#### 2.6.9 fs_rent_dif

Years: 2023
Description: Indicator for having difficulty paying rent or mortgage in the past 12 months
Coding Details: This variable is derived from question PY_RNT (“During the past 12 months, at any point did you have difficulty paying your rent or mortgage?”).

#### 2.6.10 fs_rent_harder

Years: 2017, 2019, 2021
Description: Indicator for it being harder to pay rent or mortgage in past 12 months
Coding Details: This variable is derived from question RENT_12MO (“In the past 12 months, has it gotten easier, harder, or stayed the same to pay your rent or mortgage?”).

#### 2.6.11 fs_rent_move

Years: 2023
Description: Indicator for having been forced to move in the past 12 months due to not being able to pay rent among those who had difficulty paying rent or mortgage in that time period
Coding Details: This variable is derived from question FRC_MV_RNT (“During the past 12 months, were you forced to move because you couldn’t pay your rent or mortgage?”) which was only asked of respondents who had difficulty paying their rent or mortgage in the past 12 months as indicated by fs_rent_dif.

#### 2.6.12 fs_trnsp_dif

Years: 2023
Description: Indicator for having difficulty accessing reliable transportation in the past 12 months
Coding Details: This variable is derived from question PY_TRNSP (“During the past 12 months, at any point did you have difficulty accessing reliable transportation?”).

#### 2.6.13 fs_usual_dif

Years: 2023
Description: Indicator for household finding it somewhat or very difficult to pay for usual household expenses in the past 12 months
Coding Details: This variables indicates that a respondent answered “Very difficult” or “Somewhat difficult” to question Q1_NEW (“During the past 12 months, how difficult has it been for your household to pay for usual household expenses, such as food, rent or mortgage, medical expenses, and so on?”).

### 2.7 Geography

#### 2.7.1 geo_aaa

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Area Agency on Aging
Coding Details: This variable is derived from question S9 (2010, 2012; “In what county in the state of Ohio do you live?”) or S9_IMP (all other years).

#### 2.7.2 geo_adamh

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Alcohol, Drug, and Mental Health (ADAMH) board
Coding Details: This variable is derived from question S9 (2010, 2012; “In what county in the state of Ohio do you live?”) or S9_IMP (all other years).

#### 2.7.3 geo_county

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Ohio county of residence
Coding Details: This variable is derived from question S9 (2010, 2012; “In what county in the state of Ohio do you live?”) or S9_IMP (all other years).

#### 2.7.4 geo_county_type

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for type of Ohio county of residence
Coding Details: This variable is derived from REGION (2010, 2012, 2015) or S9_TYPE_IMP (all other years).

##### Variable Levels

- Rural Appalachian
- Metropolitan
- Rural Non-Appalachian
- Suburban

#### 2.7.5 geo_fips

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: FIPS for Ohio county of residence
Coding Details: This variable is derived from question S9 (2010, 2012; “In what county in the state of Ohio do you live?”) or S9_IMP (all other years).

#### 2.7.6 geo_mivi_fac

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for residence in a county that is part of the Maternal and Infant Vitality Initiative
Coding Details: This variable is derived from question S9 (2010, 2012; “In what county in the state of Ohio do you live?”) or S9_IMP (all other years). Counties in the Maternal and Infant Vitality Initiative (MIVI) include Butler, Cuyahoga, Franklin, Hamilton, Lorain, Lucas, Mahoning, Montgomery, Stark, and Summit.

##### Variable Levels

- MIVI
- Non-MIVI

### 2.8 Health Status

#### 2.8.1 hs_5lev

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for self-rated overall health with five levels
Coding Details: This variable is derived from question D30 (2010; “In general, would you say your health is excellent, very good, good, fair, or poor?”) or D30_IMP (all other years).

##### Variable Levels

- Poor Self-rated Health
- Fair Self-rated Health
- Good Self-rated Health
- Very Good Self-rated Health
- Excellent Self-rated Health

#### 2.8.2 hs_bmi

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for BMI categories
Coding Details: This variable is derived from BMI_A_CAT which is based on questions D30A_VALUE (weight in pounds), D30B_F (height - feet), and D30B_I (height - inches).

##### Variable Levels

- Underweight
  - Level Details: Respondent’s BMI < 18.5
- Healthy
  - Level Details: Respondent’s BMI in [18.5,25.0)
- Overweight
  - Level Details: Respondent’s BMI in [25.0,30)
- Obese
  - Level Details: Respondent’s BMI > 30

#### 2.8.3 hs_dntl_fp_fac

Years: 2021, 2023
Description: Factor for fair or poor self-rated dental health
Coding Details: This variable is derived from question D30_D (“Thinking about your teeth and gums, would you say your dental health is excellent, very good, good, fair, or poor?”).

##### Variable Levels

- Self-rated Dental Health Excellent/Very Good/Good
- Self-rated Dental Health Fair/Poor

#### 2.8.4 hs_fallcare

Years: 2015, 2019
Description: Indicator for a fall that resulted in a visit to a health professional in the past 12 months among those who had been injured due to a fall during that time period
Coding Details: This variable is derived from question D33B (“Did this injury due to a fall result in a visit to a doctor, nurse, other health professional, a clinic, or hospital?”) which was only asked if they answered “Yes” to question D33 (“Within the past 12 months, have you been injured due to a fall?”).

#### 2.8.5 hs_fp_fac

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for fair or poor self-rated overall health
Coding Details: This variable is derived from question D30 (2010; “In general, would you say your health is excellent, very good, good, fair, or poor?”) or D30_IMP (all other years).

##### Variable Levels

- Self-rated Health Excellent/Very Good/Good
- Self-rated Health Fair/Poor

#### 2.8.6 hs_injuredfall

Years: 2015, 2019
Description: Indicator for injury due to a fall in the past 12 months
Coding Details: This variable is derived from question D33 (“Within the past 12 months, have you been injured due to a fall?”).

#### 2.8.7 hs_insulin

Years: 2019
Description: Indicator for taking insulin among those ever diagnosed with diabetes
Coding Details: This variable is derived from question D43C (“Are you now taking insulin?”). D43C was only asked if a respondent answered “Yes” to question D43 (“Has a doctor, nurse, or other health professional ever told you that you had diabetes or sugar diabetes?”).

#### 2.8.8 hs_mh_5lev

Years: 2023
Description: Factor for self-rated mental health
Coding Details: This variable is derived from question MTL_HLTH (“In general, would you say your mental health is excellent, very good, good, fair, or poor?”).

##### Variable Levels

- Poor Self-rated Mental Health
- Fair Self-rated Mental Health
- Good Self-rated Mental Health
- Very Good Self-rated Mental Health
- Excellent Self-rated Mental Health

#### 2.8.9 hs_mh_fp_fac

Years: 2023
Description: Factor for fair or poor self-rated mental health
Coding Details: This variable is derived from question MTL_HLTH (“In general, would you say your mental health is excellent, very good, good, fair, or poor?”).

##### Variable Levels

- Self-rated Mental Health Excellent/Very Good/Good
- Self-rated Mental Health Fair/Poor

#### 2.8.10 hs_mhi_cat

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for days in past 30 where mental health prevented work or activities
Coding Details: This variable categorizes by question D30I (up to 2019; “…for how many days, during the past 30 days did a mental health condition or emotional problem keep you from doing your work or other usual activities?”) or D30I_IMP (2021 on).

##### Variable Levels

- 0 Days
- 1-6 Days
- 7-13 Days
- 14-31 Days

#### 2.8.11 hs_mhi_fac

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for having 14 or more days in the past 30 where mental health prevented work or activities
Coding Details: This variable categorizes by whether a respondent answered 14 or more days to question D30I (up to 2019; “…for how many days, during the past 30 days did a mental health condition or emotional problem keep you from doing your work or other usual activities”) or had a value of 14 or more days for D30I_IMP (2021 on).

##### Variable Levels

- Less Than 14 Days of Mental Distress Out of the Last 30 Days
- 14+ Days of Mental Distress Out of the Last 30 Days

#### 2.8.12 hs_preg_12mo_fac

Years: 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for pregnant in the last 12 months among women under 45 years of age
Coding Details: This variable is derived question E65 (“During the past 12 months were you pregnant at any time?”). This variable only contains a value for female respondents under the age of 45.

##### Variable Levels

- Not Pregnant in the Last 12 Months
- Pregnant in the Last 12 Months

#### 2.8.13 hs_preg_now

Years: 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for currently being pregnant among women under 45 years of age
Coding Details: This variable is derived from question E65A (“Are you currently pregnant?”). This variable only contains a value for female respondents under the age of 45.

### 2.9 Healthcare Visits

#### 2.9.1 hcv_audio

Years: 2023
Description: Indicator for having a health care visit by audio call without video in the past twelve months
Coding Details: This variable is derived from UTLZ02_IMP (“During the past 12 months, did you see a doctor or other healthcare provider by audio-only call without video?”).

#### 2.9.2 hcv_er_3more

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for whether a respondent had 3 or more ER visits in the past 12 months
Coding Details: This variable is derived from E62_CAT_IMP (2021) or question E62 (all other years; “During the past 12 months, how many times were you a patient in a hospital emergency room?”). Note that starting in 2023, E62 was changed from open ended to categorical.

#### 2.9.3 hcv_er_num

Years: 2010, 2012, 2015, 2017, 2019, 2021
Description: Factor for number of ER visits in the past 12 months (prior to 2023)
Coding Details: This variable is derived from question E62 (up to 2019; “During the past 12 months, how many times were you a patient in a hospital emergency room?”) or E62_CAT_IMP (2021).

##### Variable Levels

- 0 Visits
- 1 Visit
- 2 Visits
- 3 or More Visits

#### 2.9.4 hcv_er_num23

Years: 2023
Description: Factor for number of ER visits in the past 12 months (beginning in 2023)
Coding Details: This variable is derived from question E62 (“During the past 12 months, how many times were you a patient in a hospital emergency room?”). In 2023, question E62 was changed from open-ended to categorical with four options.

##### Variable Levels

- 0 Visits
- 1 to 2 Visits
- 3 to 6 Visits
- 7 or More Visits

#### 2.9.5 hcv_in_person

Years: 2023
Description: Indicator for having an in-person health care visit in the past twelve months
Coding Details: This variable is derived from UTLZ01_IMP (“During the past 12 months, did you see a doctor or other healthcare provider in person?”).

#### 2.9.6 hcv_no_routine

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for last routine doctor’s visits being more than a year ago
Coding Details: This variable derived from question E59ADAYS (up to 2015) or E59A (2017 on; “About how long has it been since you last visited a doctor for a routine check-up?”).

#### 2.9.7 hcv_no_visit

Years: 2010, 2012, 2015, 2017, 2019, 2021
Description: Indicator for last seeeing a doctor (excluding overnight stays, ER visits, home visits, and telephone calls) more than a year ago
Coding Details: This variable is derived from question E59DAYS (up to 2015) or E59 (2017, 2019, 2021; “Not including overnight hospital stays, visits to hospital emergency rooms, home visits, or telephone calls, about how long has it been since you last saw a doctor or other health care professional about your own health?”).

#### 2.9.8 hcv_none

Years: 2023
Description: Indicator for having no health care visits in the past twelve months
Coding Details: This variable is derived from hcv_in_person, hcv_audio, and hcv_video.

#### 2.9.9 hcv_tele_4lev

Years: 2023
Description: Factor for number of telehealth visits in the past 12 months
Coding Details: This variable is derived from TLHLTH_IMP (“During the past 12 months, how many times have you had a telehealth visit with a doctor, nurse, or other healthcare provider?”). If a respondent did not have an audio or video health visit in the past 12 months, as indicated by hcv_audio and hcv_video.

##### Variable Levels

- 0 Times
- 1 to 2 Times
- 3 to 6 Times
- 7 or More Times

#### 2.9.10 hcv_tele_any

Years: 2023
Description: Indicator for one or more telehealth visits in the past 12 months
Coding Details: This variable is derived from hcv_tele_4lev.

#### 2.9.11 hcv_video

Years: 2023
Description: Indicator for having a health care visit by video call with audio ing the past twelve months
Coding Details: This variable is derived from UTLZ03_IMP (“During the past 12 months, did you see a doctor or other healthcare provider by video call with audio?”).

### 2.10 Income

#### 2.10.1 inc_4lev

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for family income as percentage of the federal poverty line with four levels
Coding Details: This variable is derived from inc_7lev.

##### Variable Levels

- Up to 138% FPL
- 138% up to 250% FPL
- 250% up to 400% FPL
- 400% or more FPL

#### 2.10.2 inc_7lev

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for family income as percentage of the federal poverty line
Coding Details: This variable categorizes respondents by their household’s income as a percentage of the FPL. It is based on H84_A3_IMP (2017) or inc_cont (all other years).

##### Variable Levels

- 0 up to 75% FPL
- 75 up to 100% FPL
- 100 up to 138% FPL
- 138 up to 206% FPL
- 206 up to 250% FPL
- 250 up to 400% FPL
- 400% or more FPL

#### 2.10.3 inc_cont

Years: 2010, 2012, 2015, 2019, 2021, 2023
Description: Numeric value of family income as a percentage of the federal poverty line
Coding Details: This variable is calculated based on questions H84_A1 (“How many family members, including yourself, are supported by the family’s total income?”), H84_A1_NUM (“How many other family members who do not live in your home are also supported by the family’s total income?”), and H84_A3 (“What is your best estimate of your households total XXXX annual income before taxes and deductions?”) where XXXX is the appropriate four digit year. In all years other than 2010 and 2017, this variable is provided as FPL_PCT.

### 2.11 Insurance

#### 2.11.1 ins_dental

Years: 2021, 2023
Description: Factor for having insurance that covers dental bills
Coding Details: This variable is derived from question B4_DENTAL (“Do you currently have any type of insurance that covers dental bills?”). Respondents who are indicated by recoded variable ins_none as being uninsured are categorized as not having dental insurance.

##### Variable Levels

- Dental Insurance Coverage
- No Dental Insurance Coverage

#### 2.11.2 ins_esi

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for having employer-sponsored health insurance
Coding Details: This variable is derived from I_TYPE_A (2010) or I_TYPE_A_IMP (2012 on) which categorize by insurance type.

#### 2.11.3 ins_esi_elig_fac

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for eligibility for employer sponsored health insurance
Coding Details: This variable categorizes by whether a respondent is eligible for ESI where eligibility is identified as having ESI according to recoded variable ins_esi or being eligible for their employer or union health plan according to G72B_V2 (2021) or the question G72B (all other years; “…are you currently eligible to participate in your employer or union health plan?”). A respondent is considered to be ineligible for ESI if they do not currently have ESI and did not work last week (wrk_fac), their employer doesn’t offer ESI (ins_esi_offer), or their employer offers ESI.

##### Variable Levels

- Not Eligible for ESI
- Eligible for ESI

#### 2.11.4 ins_esi_lng

Years: 2021, 2023
Description: Factor for length of ESI coverage among those with ESI
Coding Details: This variable is derived from question ESI_LNG (2023; “How long have you been covered by your current health insurance through a current or former employer or labor union?”) or B4AC (2021; “Approximately how long have you been covered by your current health insurance plan from your or someone else’s work?”). This variable is NA for all respondents who are not covered by ESI ( ins_esi).

##### Variable Levels

- Less than 3 Months
- 3 to 12 Months
- 1 to 2 Years
- More than 2 Years

#### 2.11.5 ins_esi_np_cost

Years: 2017, 2019, 2021, 2023
Description: Indicator for not participating in ESI because it costs too much among those who are eligible for ESI but do not participate
Coding Details: This variable is derived from question G72c_1 (“Was the reason for you not participating in your employer or labor union health insurance because it costs too much?”). This variable is only populated for respondents who do not currently have employer sponsored insurance (ESI) according to ins_esi but are currently eligible for ESI according to ins_esi_elig_fac.

#### 2.11.6 ins_esi_np_need

Years: 2019, 2021, 2023
Description: Indicator for not participating in ESI due to not needing it among those who are eligible for ESI but do not participate
Coding Details: This variable is derived from question G72c_3 (“Was the reason for you not participating in your employer or labor union health insurance because you do not need it?”). This variable is only populated for respondents who do not currently have employer sponsored insurance (ESI) according to ins_esi but are currently eligible for ESI according to ins_esi_elig_fac.

#### 2.11.7 ins_esi_np_othins

Years: 2017, 2019, 2021, 2023
Description: Indicator for not participating in ESI due to having other insurance among those who are eligible for ESI but do not participate
Coding Details: This variable is derived from question G72c_2 (“Was the reason for you not participating in your employer or labor union health insurance because you have other insurance?”). This variable is only populated for respondents who do not currently have employer sponsored insurance (ESI) according to ins_esi but are currently eligible for ESI according to ins_esi_elig_fac.

#### 2.11.8 ins_esi_offer

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for employer or union offering health insurance among those currently working
Coding Details: This variable is either derived from question G72 (“Does your employer or union offer health insurance to any of its employees?”) or an indicator that a respondent has insurance through their employer or through both their employer and someone else’s employer according to recoded variable ins_esi_type. Additionally, this variable is NA for anyone is not working according to recoded variable wrk_fac.

#### 2.11.9 ins_esi_type

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for type of ESI insurance with four levels
Coding Details: This variable is derived from question B4AA (“Is your insurance through your work or are you receiving insurance as a dependent through someone else’s work?”). Respondents are assigned a value of “Does not have ESI” if they do not have ESI according to recoded variable ins_esi.

##### Variable Levels

- ESI through Employer
- ESI through Someone Else’s Employer
- ESI through both Employer and Someone Else’s Employer
- Does not have ESI

#### 2.11.10 ins_exchange

Years: 2021, 2023
Description: Indicator for having insurance through the health insurance exchange (ie: healthcare.gov)
Coding Details: This variable is derived from INS_EXCHANGE_A_IMP which is based on question B4I (2021) or EXCHNG (2023; “Are you currently covered by health insurance from healthcare.gov (sometimes called the health insurance”exchange” or marketplace)?“).

#### 2.11.11 ins_fac

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for insurance status
Coding Details: This variable is derived from INSRD_A_IMP.

##### Variable Levels

- Insured
- Uninsured

#### 2.11.12 ins_mcd

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for having insurance through Medicaid
Coding Details: This variable is derived from I_TYPE_A (2010) or I_TYPE_A_IMP (2012 on) which categorize by insurance type.

#### 2.11.13 ins_mcd_lng

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for having Medicaid for less than a year
Coding Details: This variable is derived from B18DAYS (2010, 2012; “How long have you been covered by your current primary health insurance plan?”), B4C2DAYS (2015; “How long have you been covered by ?”), B4C2_IMP (2017, 2019, 2021; “How long have you been covered by Medicaid?”), MDCD_LNG_IMP (2023 on; ABS sample) or MDLST_LNG_IMP (2023 on; Medicaid list sample). It is only populated for those with Medicaid coverage according to [ins_mcd][#ADULT:ins_mcd].

#### 2.11.14 ins_mcr_only

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for having insurance through Medicare only
Coding Details: This variable is derived from I_TYPE_A (2010) or I_TYPE_A_IMP (2012 on) which categorize by insurance type.

#### 2.11.15 ins_none

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for being uninsured
Coding Details: This variable is derived from I_TYPE_A (2010) or I_TYPE_A_IMP (2012 on) which categorize by insurance type.

#### 2.11.16 ins_none_jobloss

Years: 2021, 2023
Description: Indicator for losing insurance due to job loss among those who are uninsured and lost their coverage in the last two years
Coding Details: This variable is derived from question C2B (“Did you lose your insurance because of a job loss or layoff that you or a family member experienced?”) and is only populated for respondents who are uninsured according to ins_none and lost their coverage in the last two years as denoted by ins_none_lng.

#### 2.11.17 ins_none_lng

Years: 2021, 2023
Description: Factor for length of time since being insured among those who are uninsured
Coding Details: This variable is derived from question C1_NEW (“When were you last covered by any type of health insurance?”) and is NA for all respondents who are not denoted as uninsured by ins_none.

##### Variable Levels

- Less than 3 Months
- 3 to 12 Months
- 1 to 2 Years
- More than 2 Years

#### 2.11.18 ins_none_prev_esi

Years: 2021, 2023
Description: Indicator for most recent insurance being ESI among those who are uninsured and lost their coverage in the last two years
Coding Details: This variable is derived from question C4 (“The last time you had health insurance, were you covered by insurance obtained through a current or former employer or labor union?”). Respondents are assigned a value of 0 if they are denoted by ins_none_prev_mcd as being uninsured and their most recent insurance coverage being Medicaid. This variable is only populated for respondents who are uninsured according to ins_none and lost their coverage in the last two years as denoted by ins_none_lng.

#### 2.11.19 ins_none_prev_mcd

Years: 2021, 2023
Description: Indicator for most recent insurance being Medicaid among those who are uninsured and lost their coverage in the last two years
Coding Details: This variable is derived from question C3 (“The last time you had health insurance, were you covered by Medicaid, the state of Ohio health insurance for those with lower income?”) and is only populated for respondents who are uninsured according to ins_none and lost their coverage in the last two years as denoted by ins_none_lng.

#### 2.11.20 ins_prev

Years: 2012, 2015, 2017, 2019, 2021
Description: Indicator for having coverage by a different insurance plan just prior to current plan in the past 12 months among those currently insured
Coding Details: This variable is derived from question B19 (“Before you became covered with your current health insurance plans, were you covered by another plan within the past 12 months?”).

#### 2.11.21 ins_prev_esi

Years: 2010, 2012, 2015, 2017, 2019, 2021
Description: Indicator for having employer-sponsored health insurance just prior to current insurance plan and in the past 12 months
Coding Details: This variable is derived from question B21 (“Just prior to current health insurance coverage, were you covered by a health insurance plan obtained through an employer or union?”). It has a value of 0 for insured respondents who were not covered by a different plan just prior to their current plan, in the past 12 months, according to ins_prev and is NA for all uninsured respondents according to ins_none.

#### 2.11.22 ins_prev_mcd

Years: 2012, 2015, 2017, 2019, 2021
Description: Indicator for having Medicaid just prior to current insurance plan and in the past 12 months among those currently insured with non-Medicaid coverage
Coding Details: This variable is derived from question B20 (“Just prior to your current health insurance coverage were you covered by Medicaid, the state of Ohio government health care program?”). It has a value of 0 for insured respondents who were not covered by a different plan just prior to their current plan, in the past 12 months, according to ins_prev. It is NA for all uninsured respondents according to ins_none and respondents currently covered by Medicaid according to ins_mcd.

#### 2.11.23 ins_prev_oth

Years: 2010, 2012, 2015, 2017, 2019, 2021
Description: Indicator for having a type of insurance plan just prior to current insurance plan and in the past 12 months that was not private, employer-sponsored, or Medicaid among those currently insured
Coding Details: This variable is derived from question B24 (“Just prior to your current health insurance coverage, were you covered by any health insurance plan?”). It has a value of 0 for insured respondents who were not covered by a different plan just prior to their current plan, in the past 12 months, according to ins_prev and is NA for all uninsured respondents according to ins_none.

#### 2.11.24 ins_prev_prvt

Years: 2010, 2012, 2015, 2017, 2019, 2021
Description: Indicator for having private insurance just prior to current insurance plan and in the past 12 months
Coding Details: This variable is derived from question B22 (“Just prior to your current health insurance coverage, were you covered by any other insurance that your family paid for completely?”). It has a value of 0 for insured respondent who were not covered by a different plan just prior to their current plan, in the past 12 months, according to ins_prev and is NA for all uninsured respondents according to ins_none.

#### 2.11.25 ins_prvt

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for having private insurance
Coding Details: This variable is an Indicator for whether a respondent has health insurance categorized as “Directly Purchased”, “Insured Type Unknown”, or “Other” by I_TYPE_A (2010) or “Other Directly Purchased” or “Other” by I_TYPE_A_IMP (2012 on).

#### 2.11.26 ins_type

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for current insurance type with five levels
Coding Details: This variable is derived from I_TYPE_A (2010) or I_TYPE_A_IMP (2012 on) which categorize by insurance type.

##### Variable Levels

- Employer-Sponsored
  - Level Details: I_TYPE_A = “Job-Based Coverage”
- Medicaid
  - Level Details: I_TYPE_A = “Medicaid and Medicare”, “Medicaid, No Medicare”
- Medicare Only
  - Level Details: I_TYPE_A = “Medicare, No Medicaid”
- Other Insured
  - Level Details: I_TYPE_A = “Directly Purchased”, “Other”, “Insurance Type Unknown”
- Uninsured
  - Level Details: I_TYPE_A = “Uninsured”

#### 2.11.27 ins_type_4lev

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for current insurance type with four levels
Coding Details: This variable is derived from I_TYPE_A (2010) or I_TYPE_A_IMP (2012 on) which categorize by insurance type.

##### Variable Levels

- Employer-Sponsored
  - Level Details: I_TYPE_A = “Job-Based Coverage”
- Medicaid
  - Level Details: I_TYPE_A = “Medicaid and Medicare”, “Medicaid, No Medicare”
- Other Insured
  - Level Details: I_TYPE_A = “Medicare, No Medicaid”, “Directly Purchased”, “Other”, “Insurance Type Unknown”
- Uninsured
  - Level Details: I_TYPE_A = “Uninsured”

#### 2.11.28 ins_type_6lev

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for current insurance type with six levels
Coding Details: This variable is derived from I_TYPE_A (2010) or I_TYPE_A_IMP (2012 on) which categorize by insurance type.

##### Variable Levels

- Employer-Sponsored
  - Level Details: I_TYPE_A = “Job-Based Coverage”
- Medicaid Only
  - Level Details: I_TYPE_A = “Medicaid, No Medicare”
- Dual, Medicaid and Medicare
  - Level Details: I_TYPE_A = “Medicaid and Medicare”
- Medicare Only
  - Level Details: I_TYPE_A = “Medicare, No Medicaid”
- Other Insured
  - Level Details: I_TYPE_A = “Directly Purchased”, “Other”, “Insurance Type Unknown”
- Uninsured
  - Level Details: I_TYPE_A = “Uninsured”

#### 2.11.29 ins_vision

Years: 2023
Description: Factor for having insurance that covers eyeglassess, lenses, or vision care bills
Coding Details: This variable is derived from question B4_VISION (“Do you currently have any type of insurance that covers eyeglasses, lenses, or vision care bills?”). Respondents who are indicated by ins_none as being uninsured are categorized as not having vision insurance.

##### Variable Levels

- Vision Insurance Coverage
- No Vision Insurance Coverage

### 2.12 Intimate Partner Violence

#### 2.12.1 ipv

Years: 2019
Description: Factor for intimate partner violence status
Coding Details: This variable is derived from questions R2N_THREAT (“Has an intimate partner ever threatened you with physical violence? This includes threatening to hit, slap, push, kick or physically hurt you in any way.”), R2N_USED (“Has an intimate partner ever used physical violence against you? This includes hitting, slapping, pushing, kicking, or hurting you in any way.”), and R3NEWDAY (“When was the last time an intimate partner threated or used physical violence against you?”).

##### Variable Levels

- During past year
  - Level Details: (R3NEWDAY in [0,365]) or (R3NEWDAY = “DK”,“RF” and R2N_THREAT/R2N_USED = “Yes”)
- More than 1 year ago
  - Level Details: R3NEWDAY > 365 and R3NEWDAY < 50000
- Never
  - Level Details: (R3NEWDAY = “DK”,“RF” or R3NEWDAY >= 50000) and (R2N_THREAT = “No” or R2N_USED = “No”)

### 2.13 Loneliness and Isolation

#### 2.13.1 iso_3lev

Years: 2019, 2021, 2023
Description: Factor for level of loneliness with three levels
Coding Details: This variable is derived from questions IS_UCLA1, IS_UCLA2, and IS_UCLA3 (“How often do you feel that you lack companionship?”, “How often do you feel left out?”, and “How often do you feel isolated from others?”, respectively) where, for each question, 0 = “NA”, “DK”, “RF”, 1 = “Hardly ever”, 2 = “Some of the time”, and 3 = “Often”.

##### Variable Levels

- Not Lonely
  - Level Details: IS_UCLA1 + IS_UCLA2 + IS_UCLA3 < 4
- Moderately Lonely
  - Level Details: IS_UCLA1 + IS_UCLA2 + IS_UCLA3 = 4,5
- Lonely
  - Level Details: IS_UCLA1 + IS_UCLA2 + IS_UCLA3 > 5

#### 2.13.2 iso_comp_fac

Years: 2019, 2021, 2023
Description: Factor for loneliness status
Coding Details: This variable categorizes by whether the sum of a respondent’s answers to questions IS_UCLA1, IS_UCLA2, and IS_UCLA3 is greater than or equal to 6 (“How often do you feel that you lack companionship?”, “How often do you feel left out?”, and “How often do you feel isolated from others?”, respectively) where, for each question, 0 = “NA”, “DK”, “RF”, 1 = “Hardly ever”, 2 = “Some of the time”, and 3 = “Often”. If a respondent’s values for all three questions are one of “NA”, “DK”, or “RF”, their value is set to “NA”.

##### Variable Levels

- Not Lonely
- Lonely

#### 2.13.3 iso_mhi

Years: 2019, 2021, 2023
Description: Indicator for having MHI and experiencing loneliness
Coding Details: This variable indicates that a respondent has a mental health impairment (MHI) according to the variable hs_mhi_fac and experiences loneliness according to the variable iso_comp_fac.

### 2.14 Medicaid Eligibility

#### 2.14.1 mcd_elig

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for potential Medicaid eligibility status with three levels
Coding Details: This variable is derived from ins_mcd and mcd_ptn_elig.

##### Variable Levels

- Medicaid-Enrolled
- Potentially Medicaid Eligible
- Not Potentially Medicaid Eligible

#### 2.14.2 mcd_elig_4lev

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for groupings within being potentially Medicaid eligible
Coding Details: This variable is derived froms ins_mcd, mcd_ptn_elig, mcd_ptn_elig_othins , and mcd_ptn_elig_unins.

##### Variable Levels

- Medicaid-Enrolled
- Potentially Medicaid Eligible and Uninsured
- Potentially Medicaid Eligible with Other Insurance
- Not Potentially Medicaid Eligible

#### 2.14.3 mcd_ptn_elig

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for being potentially Medicaid eligible
Coding Details: This variable indicates whether a respondent is potentially eligible for Medicaid because their household family income is no more than 138% of the FPL or because they either are pregnant (prior to 2023) or have been pregnant in the last 12 months (2023 on) and their household family income is between 139% and 200% of the FPL (206% was used for 2017 because only categorical FPL was available). This variable is derived froms inc_cont (numeric value of family income as a percentage of the federal poverty line, hs_preg_12mo_fac (an indicator for being pregnant in the past 12 months), and hs_preg_now (an indicator for currently being pregnant). We use the cut off of 206% FPL for a respondent who is pregnant in 2017, despite the cutoff being 200% in Ohio, since as we are not able to calculate continuous FPL for 2017.

#### 2.14.4 mcd_ptn_elig_othins

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for potentially Medicaid eligible and currently on another kind of insurance
Coding Details: This variable is derived from ins_none (an indicator for being uninsured), ins_mcd (an indicator for being on Medicaid), and mcd_ptn_elig (an indicator for being potentially Medicaid eligible).

#### 2.14.5 mcd_ptn_elig_unins

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for being potentially Medicaid eligible and currently uninsured
Coding Details: This variable is derived from ins_none (an indicator for being uninsured) and mcd_ptn_elig (an indicator for being potentially Medicaid eligible).

### 2.15 PHQ-4 Screener

#### 2.15.1 phq_anxiety

Years: 2023
Description: Factor for PHQ-4 anxiety subscale
Coding Details: This variable categorizes respondent based on their total score on the PHQ-4 anxiety subscale presented in questions PHQ1 and PHQ2 (“Over the last two weeks, how often have you been bothered by feeling nervous, anxious, or on edge?” and “…by not being able to stop or control worrying?”, respectively) where, for each question, “Not at all” = 0, “Several days” = 1, “More than half of the days” =2, and “Nearly every day” = 3. This variable was defined using guidance from “An Ultra-Brief Screening Scale Anxiety and Depression: The PHQ-4” (Kroenke et al., 2009).

##### Variable Levels

- Positive
  - Level Details: Score from 3-6
- Negative
  - Level Details: Score from 0-2

#### 2.15.2 phq_depression

Years: 2023
Description: Factor for PHQ-4 depression subscale
Coding Details: This variable categorizes respondent based on their total score on the PHQ-4 depression subscale presented in questions PHQ3 and PHQ4 (“Over the last two weeks, how often have you been bothered by feeling down, depressed, or hopeless?”, and “…by having little interest or pleasure in doing things?”, respectively) where, for each question, “Not at all” = 0, “Several days” = 1, “More than half of the days” =2, and “Nearly every day” = 3. This variable was defined using guidance from “An Ultra-Brief Screening Scale Anxiety and Depression: The PHQ-4” (Kroenke et al., 2009).

##### Variable Levels

- Positive
  - Level Details: Score from 3-6
- Negative
  - Level Details: Score from 0-2

#### 2.15.3 phq_dual

Years: 2023
Description: Indicator for screening positive for both anxiety and depression
Coding Details: This variable indicates that a respondent screened positive for anxiety on the PHQ-4 anxiety subscale (phq_anxiety) and for depression on the PHQ-4 depression subscale (phq_depression).

#### 2.15.4 phq_overall

Years: 2023
Description: Factor for PHQ-4 screening tool
Coding Details: This variable categorizes respondent based on their total score on the PHQ-4 screening tool for anxiety and depression presented in questions PHQ1, PHQ2, PHQ3, and PHQ4 (“Over the last two weeks, how often have you been bothered by feeling nervous, anxious, or on edge?”, “…by not being able to stop or control worrying?”, “…by feeling down, depressed, or hopeless?”, and “…by having little interest or pleasure in doing things?”, respectively) where, for each question, “Not at all” = 0, “Several days” = 1, “More than half of the days” =2, and “Nearly every day” = 3. This variable was defined using guidance from “An Ultra-Brief Screening Scale Anxiety and Depression: The PHQ-4” (Kroenke et al., 2009).

##### Variable Levels

- Normal
  - Level Details: Score from 0-2
- Mild
  - Level Details: Score from 3-5
- Moderate
  - Level Details: Score from 6-8
- Severe
  - Level Details: Score from 9-12

### 2.16 Substance Use

#### 2.16.1 su_alc

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for drinking alcohol in the past 30 days
Coding Details: This variable is derived from question D46 (“During the past 30 days, on how many days did you have at least one drink of an alcoholic beverage such as beer, wine, a malt beverage or liquor?”).

#### 2.16.2 su_alc_binge

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for binge drinking alcohol in the past 30 days
Coding Details: This variable is derived from question D46A (“During the past 30 days, considering all types of alcoholic beverages, on how many days, if any, did you have _ or more drinks on an occasion?”, where the blank is filled with a 5 for men and a 4 for women). This variable has a value of 0 for anyone who did not drink in the past 30 days according to su_alc.

#### 2.16.3 su_chew

Years: 2019
Description: Indicator for use of chewing tobacco, snuff, or snus every day or some days
Coding Details: This variable is derived from question D45D (“Do you currently use chewing tobacco, snuff, or snus every day, some days, or not at all?”).

#### 2.16.4 su_ecig_3lev

Years: 2019, 2021, 2023
Description: Factor for e-cigarette and vape use
Coding Details: This variable is derived from questions D45E (“Have you ever used an electronic cigarette or vaping product, even one time?”) and D45F (“Do you now use e-cigarettes or vaping products every day, some days, rarely, or not at all?”).

##### Variable Levels

- Never
  - Level Details: D45E = “No”
- Every Day or Some Days
  - Level Details: D45E = “Yes” and D45F = “Every day”, “Some days”
- Rarely or Former
  - Level Details: D45E = “Yes” and D45F = “Rarely”, “Not at all”

#### 2.16.5 su_mrj

Years: 2019, 2021
Description: Indicator for marijuana or cannabis use in the past 30 days
Coding Details: This variable is derived from question D46B (“During the past 30 days, on how many days did you use marijuana or cannabis?”).

#### 2.16.6 su_mrj_thc

Years: 2023
Description: Indicator for having used marijuana, cannabis, or any THC products in the past 30 days
Coding Details: This variable is derived from question MRJ_FREQ (2023 on; “During the past thirty days, have you used marijuana, cannabis, or any form of THC every day, some days, rarely, or not at all?”). Respondents who are indicated to have never used marijuana by recoded variable su_mrj_thc_evr where assigned a value of 0.

#### 2.16.7 su_mrj_thc_evr

Years: 2023
Description: Indicator for having ever used marijuana, cannabis, or any THC products
Coding Details: This variable is derived from question MRJ_EV (“Have you ever, even once, used marijuana, cannabis, or any form of THC product such as edibles, oils, and food products?”).

#### 2.16.8 su_pain_misuse

Years: 2012, 2015, 2019
Description: Indicator for ever using a prescription pain reliever in any way not directed by a doctor
Coding Details: This variable is derived from question D46C (2012, 2015) or D46C_1 (2019) (“Have you ever, even once, used any prescription pain reliever in any way a doctor did not direct you to use them?”).

#### 2.16.9 su_pain_notrx

Years: 2023
Description: Indicator for using a prescription pain reliver that was not prescribed in the past twelve months
Coding Details: This variable is derived from question PRESC_4 (“During the past twelve months, have you used a prescription pain reliever that was not prescribed for you by a doctor?”) .

#### 2.16.10 su_pain_rx

Years: 2023
Description: Indicator for having been prescribed a pain reliever by a doctor in the past twelve months
Coding Details: This variable is derived from question PRESC_1 (“During the past twelve months, have you been prescribed a pain reliever by a doctor?”) .

#### 2.16.11 su_pain_rx_abuse

Years: 2023
Description: Indicator for abusing prescription pain relief in the past 12 months
Coding Details: This variable is derived from question PRESC_3 (“During the past twelve months, have you used a prescription pain reliever in greater amounts, more often, or longer than a doctor told you to take it?”). This variable is 0 for all respondents who were not prescribed a pain reliever by a doctor in the past twelve months according to recoded variable su_pain_rx and for all respondents who were prescrived a pain reliver but did not misuse prescription pain relief in the past 12 months according to recoded variable su_pain_rx_misuse.

#### 2.16.12 su_pain_rx_misuse

Years: 2023
Description: Indicator for misusing prescription pain relief in the past 12 months
Coding Details: This variable is derived from question PRESC_2 (“During the past twelve months, have you used a prescription pain reliever in any way a doctor did not direct you to use it?”). It has a value of 0 for all respondents who were not prescribed a pain reliever by a doctor in the past twelve months according to recoded variable su_pain_rx.

#### 2.16.13 su_smoke

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for current smoker
Coding Details: This variable is derived from questions D45 (“Have you smoked at least 100 cigarettes in your entire life?”) and D45A (“Do you smoke cigarettes every day, some days, or not at all?”).

### 2.17 Survey

#### 2.17.1 stratum

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Survey stratum
Coding Details: This variable is STRATA (2015, 2017, 2019) or STRATUM (all other years).

#### 2.17.2 wt

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Survey weight
Coding Details: This variable is WT_A_BLEND (2019) or WT_A (all other years).

### 2.18 Unmet Needs

#### 2.18.1 umt_alc_drg

Years: 2019
Description: Indicator for having an unmet need for alcohol or drug treatment in the past 12 months
Coding Details: This variable is derived from question F68B_4 (“During the past 12 months, was there a time when you needed any of the following, but could not get it at that time: Alcohol or other drug treatment, not counting cigarettes?”).

#### 2.18.2 umt_alc_drg_3lev

Years: 2021, 2023
Description: Factor for need and reciept of alcohol and drug treatment in the past 12 months
Coding Details: This variable is derived from question F68_4_1 (2021; “During the past 12 months, was there a time when you needed alcohol or other drug treatment, not counting cigarettes?”) or ND_DRG_IMP (2023 on; “During the past 12 months, was there a time when you needed treatment for your use of alcohol or other drugs, not including nicotine products?”) and follow-up question F68_4_2 (2021; “Were you able to get the alcohol or other drug treatment that you needed?”) or UNMT_DRG_IMP (2023 on; “Were you able to get the treatment you needed for your use of alcohol or other drugs, not including nicotine products?”). In 2023 on, a gate was added to this series of questions and this variable was set to “Did not need care” for all respondents with the value “No” for ND_DRG_EVR_IMP (“Have you ever needed treatment for your use of alcohol or other drugs, not including nicotine products?”).

##### Variable Levels

- Did Not Need Care
  - Level Details: (F68B_4_1 or ND_DRG = “No”) or ND_DRG_EVR = “No”
- Received Needed Care
  - Level Details: F68B_4_1or ND_DRG= “Yes” and F68B_4_02 or UNMT_DRG = “Yes”
- Did Not Receive Needed Care
  - Level Details: F68B_4_1 or ND_DRG = “Yes” and F68B_4_2 or UNMT_DRG = “No”

#### 2.18.3 umt_alc_drg_cost

Years: 2023
Description: Indicator for not getting needed alcohol or drug treatment because it would cost too much among those who had an unmet need for alcohol or drug treatment in the past 12 months
Coding Details: This variable is derived from question UM_DRG_RS01 (“Why did you not get the treatment you needed for your use of alcohol or other drugs, not including nicotine products, during the past 12 months? I thought it would cost too much”). It is populated for all respondents who are indicated by umt_alc_drg_need as having an unmet need for alcohol or drug treatment in the past 12 months.

#### 2.18.4 umt_alc_drg_ever

Years: 2023
Description: Indicator for having ever needed treatment for use of alcohol or other drugs, not including nicotine products
Coding Details: This variable is derived from ND_DRG_EVR_IMP (“Have you ever needed treatment for your use of alcohol or other drugs, not including nicotine products?”).

#### 2.18.5 umt_alc_drg_ins

Years: 2023
Description: Indicator for not getting needed alcohol or drug treatment because they could not find a provider who would accept their insurance among those who had an unmet need for alcohol or drug treatment in the past 12 months
Coding Details: This variable is derived from question UM_DRG_RS04 (“Why did you not get the treatment you needed for your use of alcohol or other drugs, not including nicotine products, during the past 12 months? I could not find a provider who would accept my insurance”). This variable is populated for all respondents who are indicated by umt_alc_drg_need as having an unmet need for alcohol or drug treatment in the past 12 months.

#### 2.18.6 umt_alc_drg_need

Years: 2021, 2023
Description: Indicator for having an unmet need for alcohol or drug treatment among those who needed care in the past 12 months
Coding Details: This variable is derived from questions F68B_4_1 (2021; “During the past 12 months, was there a time when you needed alcohol or other drug treatment, not counting cigarettes?”) or ND_DRG_IMP (2023 on; “During the past 12 months, was there a time when you needed treatment for your use of alcohol or other drugs, not including nicotine products?”) and F68B_4_2 (2021; “Were you able to get the alcohol or other drug treatment that you needed?”) or question UNMT_DRG (2023 on; “Were you able to get the treatment you needed for your use of alcohol or other drugs, not including nicotine products?”).

#### 2.18.7 umt_alc_drg_trans

Years: 2023
Description: Indicator for not getting needed alcohol or drug treatment because they did not have transportation among those who had an unmet need for alcohol or drug treatment in the past 12 months
Coding Details: This variable is derived from question UM_DRG_RS02 (“Why did you not get the treatment you needed for your use of alcohol or other drugs, not including nicotine products, during the past 12 months? I did not have transportation to or from appointments”). This variable is populated for all respondents who are indicated by umt_alc_drg_need as having an unmet need for alcohol or drug treatment in the past 12 months.

#### 2.18.8 umt_alc_drg_unavl

Years: 2023
Description: Indicator for not getting needed alcohol or drug treatment because the provider was unavailable when they needed it among those who had an unmet need for alcohol or drug treatment in the past 12 months
Coding Details: This variable is derived from question UM_DRG_RS03 (“Why did you not get the treatment you needed for your use of alcohol or other drugs, not including nicotine products, during the past 12 months? The provider was not available when I needed to go”). This variable is populated for all respondents who are indicated by umt_alc_drg_need as having an unmet need for alcohol or drug treatment in the past 12 months.

#### 2.18.9 umt_alc_drg_want

Years: 2023
Description: Indicator for not getting needed alcohol or drug treatment because they did not want it among those who had an unmet need for alcohol or drug treatment in the past 12 months
Coding Details: This variable is derived from question UM_DRG_RS05 (“Why did you not get the treatment you needed for your use of alcohol or other drugs, not including nicotine products, during the past 12 months? Another reason not listed.”). This variable is populated for all respondents who are indicated by umt_alc_drg_need as having an unmet need for alcohol or drug treatment in the past 12 months.

#### 2.18.10 umt_dent

Years: 2010, 2012, 2015, 2017, 2019
Description: Indicator for having an unmet dental care need in the past 12 months
Coding Details: This variable is derived from question F68 (“During the past 12 months, was there a time when you needed any of the following, but could not get it at that time: Dental care?”).

#### 2.18.11 umt_dent_3lev

Years: 2021, 2023
Description: Factor for need and receipt of dental care in the past 12 months
Coding Details: This variable is derived from questions F68_1 (“During the past 12 months, was there a time when you needed dental care?”) and F68_2 (“Were you able to get the dental care that you needed?”). Note that F68_1 and F68_2 were renamed ND_DNTL_IMP and UNMT_DNTL_IMP, respectively, beginning in 2023.

##### Variable Levels

- Did Not Need Care
  - Level Details: F68_1 = “No”
- Received Needed Care
  - Level Details: F68_1 = “Yes” and F68_2 = “Yes”
- Did Not Receive Needed Care
  - Level Details: F68_1 = “Yes” and F68_2 = “No”

#### 2.18.12 umt_dent_cost

Years: 2023
Description: Indicator for not getting needed dental care because it would cost too much among those who had an unmet need for dental care in the past 12 months
Coding Details: This variable is derived from question UM_DNTL_RS01 (“Why did you not get the dental care you needed during the past 12 months? I thought it would cost too much”). This variable is populated for all respondents who are indicated by umt_dent_need as having an unmet need for dental care in the past 12 months.

#### 2.18.13 umt_dent_ins

Years: 2023
Description: Indicator for not getting needed dental care because they could not find provider who would accept their insurance among those who had an unmet need for dental care in the past 12 months
Coding Details: This variable is derived from question UM_DNTL_RS04 (“Why did you not get the dental care you needed during the past 12 months? I could not find a provider who would accept my insurance”). This variable is populated for all respondents who are indicated by umt_dent_need as having an unmet need for dental care in the past 12 months.

#### 2.18.14 umt_dent_need

Years: 2021, 2023
Description: Indicator for having an unmet dental care need among those who needed dental care in the past 12 months
Coding Details: This variable is derived from questions F68_1 (“During the past 12 months, was there a time when you needed dental care?”) and F68_2 (“Were you able to get the dental care that you needed?”). Note that these questions were renamed ND_DNTL_IMP and UNMT_DNTL_IMP beginning in 2023.

#### 2.18.15 umt_dent_trans

Years: 2023
Description: Indicator for not getting needed dental care because they did not have transportation among those who had an unmet need for dental care in the past 12 months
Coding Details: This variable is derived from question UM_DNTL_RS02 (“Why did you not get the dental care you needed during the past 12 months? I did not have transportation to or from appointments”). This variable is populated for all respondents who are indicated by umt_dent_need as having an unmet need for dental care in the past 12 months.

#### 2.18.16 umt_dent_unavl

Years: 2023
Description: Indicator for not getting needed dental care because the provider was unavailable when they needed it among those who had an unmet need for dental care in the past 12 months
Coding Details: This variable is derived from question UM_DNTL_RS03 (“Why did you not get the dental care you needed during the past 12 months? The provider was not available when I needed to go”). This variable is populated for all respondents who are indicated by umt_dent_need as having an unmet need for dental care in the past 12 months.

#### 2.18.17 umt_fill_rx

Years: 2023
Description: Indicator for there being a time when they were not able to fill a prescription in the past 12 months
Coding Details: This variable is derived from UNMT_PRS_IMP (“During the past 12 months, was there a time when you were not able to fill a prescription?”).

#### 2.18.18 umt_fill_rx_cost

Years: 2023
Description: Indicator for not filling needed prescription because it would cost too much among those who were not able to fill a needed prescription in the past 12 months
Coding Details: This variable is derived from question UM_PRS_RS01 (“Thinking about the most recent time you were not able to fill a prescription, why were you not able to fill it? I thought it would cost too much”). This variable is populated for all respondents who are indicated by umt_fill_rx as having a time when they were not able to fill a prescription in the past 12 months.

#### 2.18.19 umt_fill_rx_cvg

Years: 2023
Description: Indicator for not filling needed prescription because their insurance would not cover the prescriptions among those who were not able to fill a needed prescription in the past 12 months
Coding Details: This variable is derived from question UM_PRS_RS06 (“Thinking about the most recent time you were not able to fill a prescription, why were you not able to fill it? My Isnurance would not cover the prescription”). This variable is populated for all respondents who are indicated by umt_fill_rx as having a time when they were not able to fill a prescription in the past 12 months.

#### 2.18.20 umt_fill_rx_ins

Years: 2023
Description: Indicator for not filling needed prescription because they could not find provider who would accept their insurance among those who were not able to fill a needed prescription in the past 12 months
Coding Details: This variable is derived from question UM_PRS_RS04 (“Thinking about the most recent time you were not able to fill a prescription, why were you not able to fill it? I could not find a provider who would accept my insurance”). This variable is populated for all respondents who are indicated by umt_fill_rx as having a time when they were not able to fill a prescription in the past 12 months.

#### 2.18.21 umt_fill_rx_refill

Years: 2023
Description: Indicator for not filling needed prescription because they ran out of refills among those who were not able to fill a needed prescription in the past 12 months
Coding Details: This variable is derived from question UM_PRS_RS05 (“Thinking about the most recent time you were not able to fill a prescription, why were you not able to fill it? I ran out of refils”). This variable is populated for all respondents who are indicated by umt_fill_rx as having a time when they were not able to fill a prescription in the past 12 months.

#### 2.18.22 umt_fill_rx_trans

Years: 2023
Description: Indicator for not filling needed prescription because they did not have transportation among those who were not able to fill a needed prescription in the past 12 months
Coding Details: This variable is derived from question UM_PRS_RS02 (“Thinking about the most recent time you were not able to fill a prescription, why were you not able to fill it? I did not have transportation to or from appointments”). This variable is populated for all respondents who are indicated by umt_fill_rx as having a time when they were not able to fill a prescription in the past 12 months.

#### 2.18.23 umt_fill_rx_unavl

Years: 2023
Description: Indicator for not filling needed prescription because the provider was unavailable when they needed it among those who were not able to fill a needed prescription in the past 12 months
Coding Details: This variable is derived from question UM_PRS_RS03 (“Thinking about the most recent time you were not able to fill a prescription, why were you not able to fill it? The provider was not available when I needed to go”). This variable is populated for all respondents who are indicated by umt_fill_rx as having a time when they were not able to fill a prescription in the past 12 months.

#### 2.18.24 umt_mtl

Years: 2012, 2015, 2017, 2019
Description: Indicator for having an unmet mental health care need in the past 12 months
Coding Details: This variable is derived from question F68B_3 (“During the past 12 months, was there a time when you needed any of the following, but could not get it at that time: Mental or emotional health care or counseling services?”)

#### 2.18.25 umt_mtl_3lev

Years: 2021, 2023
Description: Factor for need and care receipt of mental health care in the past 12 months
Coding Details: This variable is derived from questions F68B_3_1 (“During the past 12 months, was there a time when you needed mental or emotional health care or counseling services?”) and F68B_3_2 (“Were you able to get the mental or emotional health care or counseling services that you needed?”). Note that these questions were renamed as ND_MTL_IMP and UNMT_MTL_IMP, respectively, beginning in 2023.

##### Variable Levels

- Did Not Need Care
  - Level Details: F68B_3_1= “No”
- Received Needed Care
  - Level Details: F68B_3_2 = “Yes” and F68B_3_2 = “Yes”
- Did Not Receive Needed Care
  - Level Details: F68B_3_2 = “Yes” and F68B_3_2 = “No”

#### 2.18.26 umt_mtl_cost

Years: 2023
Description: Indicator for not getting needed mental health care because it would cost too much among those who had an unmet need for mental health care in the past 12 months
Coding Details: This variable is derived from question UM_MTL_RS01 (“Why did you not get the mental or emotional health care or counseling services you needed during the past 12 months? I thought it would cost too much”). This variable is populated for all respondents who are indicated by umt_mtl_need as having an unmet need for mental health care in the past 12 months.

#### 2.18.27 umt_mtl_find

Years: 2023
Description: Indicator for not getting needed mental health care because they could not find a provider among those who had an unmet need for mental health care in the past 12 months
Coding Details: This variable indicates that a respondent said that they did not get treatment because they couldn’t find a provider in their open end response to question UM_MTL_RS05 (“Why did you not get the mental or emotional health care or counseling services you needed during the past 12 months? Another reason not specifed”). This variable is populated for all respondents who are indicated by umt_mtl_need as having an unmet need for mental health care in the past 12 months.

#### 2.18.28 umt_mtl_ins

Years: 2023
Description: Indicator for not getting needed mental health care because they could not find provider who would accept their insurance among those who had an unmet need formental health care in the past 12 months
Coding Details: This variable is derived from question UM_MTL_RS04 (“Why did you not get the mental or emotional health care or counseling services you needed during the past 12 months? I could not find a provider who would accept my insurance”). This variable is populated for all respondents who are indicated by umt_mtl_need as having an unmet need for mental health care in the past 12 months.

#### 2.18.29 umt_mtl_need

Years: 2021, 2023
Description: Indicator for having an unmet mental health care need among those who needed mental health care in the past 12 months
Coding Details: This variable is derived from questions F68B_3_1 (“During the past 12 months, was there a time when you needed mental or emotional health care or counseling services?”) and F68B_3_2 (“Were you able to get the mental or emotional health care or counseling services that you needed?”). Note that these questions were renamed ND_MTL_IMP and UNMT_MTL_IMP, respectively, beginning in 2023.

#### 2.18.30 umt_mtl_trans

Years: 2023
Description: Indicator for not getting needed mental health care because they did not have transportation among those who had an unmet need for mental health care in the past 12 months
Coding Details: This variable is derived from question UM_MTL_RS02 (“Why did you not get the mental or emotional health care or counseling services you needed during the past 12 months? I did not have transportation to or from appointments”). This variable is populated for all respondents who are indicated by umt_mtl_need as having an unmet need for mental health care in the past 12 months.

#### 2.18.31 umt_mtl_unavl

Years: 2023
Description: Indicator for not getting needed mental health care because the provider was unavailable when they needed it among those who had an unmet need for mental health care in the past 12 months
Coding Details: This variable is derived from question UM_MTL_RS03 (“Why did you not get the mental or emotional health care or counseling services you needed during the past 12 months? The provider was not available when I needed to go”). This variable is populated for all respondents who are indicated by umt_mtl_need as having an unmet need for mental health care in the past 12 months.

#### 2.18.32 umt_mtl_want

Years: 2023
Description: Indicator for not getting needed mental health care because they didn’t want it among those who had an unmet need for mental health care in the past 12 months
Coding Details: This variable indicates that a respondent said that they did not get treatment because they didn’t want it in their open end response to question UM_MTL_RS05 (“Why did you not get the mental or emotional health care or counseling services you needed during the past 12 months? Another reason not specifed”). This variable is populated for all respondents who are indicated by umt_mtl_need as having an unmet need for mental health care in the past 12 months.

#### 2.18.33 umt_need_any

Years: 2019
Description: Indicator for not receiving som kind of needed health care in the past 12 months
Coding Details: This variable is derived from questions F68, F68B_3, F68B_4, and F68C_new, which respectively asked if, during the past 12 months, there was a time the respondent needed but could not receive dental care, mental or emotional health care or counseling services, alcohol or other drug treatment (not counting cigarettes), or any other health care (such as medical exam or medical supplies).

#### 2.18.34 umt_oth

Years: 2010, 2012, 2015, 2017, 2019
Description: Indicator for having unmet medical needs other than dental, mental health, or drug/alcohol treatment care (e.g., a medical exam or medical supplies) in the past 12 months
Coding Details: This variable is derived from question F68C (up to 2017) or F68C_NEW (2019; “During the past 12 months, was there a time when you needed any of the following, but could not get it at that time: Any other health care, such as a medical exam, or medical supplies?”)

#### 2.18.35 umt_oth_3lev

Years: 2021
Description: Factor for need and receipt of care for medical needs other than dental, mental health, or drug/alcohol treatment care (e.g., a medical exam or medical supplies) in the past 12 months
Coding Details: This variable is derived from questions F68C_NEW_1 (“During the past 12 months, was there a time when you needed any other health care, such as a medical exam or medical supplies?”) and F68C_NEW_2 (“Were you able to get the other health care that you needed?”).

##### Variable Levels

- Did Not Need Care
  - Level Details: F68C_NEW_1= “No”
- Received Needed Care
  - Level Details: F68C_NEW_2 = “Yes” and F68C_NEW_2 = “Yes”
- Did Not Receive Needed Care
  - Level Details: F68C_NEW_2 = “Yes” and F68C_NEW_2 = “No”

#### 2.18.36 umt_oth_need

Years: 2021
Description: Indicator for having other unmet medical needs among those who needed care
Coding Details: This variable is derived from questions F68C_NEW_1 (“During the past 12 months, was there a time when you needed any other health care, such as a medical exam or medical supplies?”) and F68C_NEW_2 (“Were you able to get the other health care that you needed?”).

#### 2.18.37 umt_rx_cost

Years: 2010, 2012, 2015
Description: Indicator for having an unmet prescription need in the past 12 months
Coding Details: This variable is derived from question F68B (“During the past 12 months, have you not filled a prescription because of the cost? This includes refills.”)

#### 2.18.38 umt_vsn

Years: 2010, 2012, 2015, 2017
Description: Indicator for having an unmet vision need
Coding Details: This variable indicates that a respondent answered that during the past 12 months there was time when they vision care or eye glasses but could not get it at that time (“Yes” to question F68B_4).

This variable is derived from question F68B_2 (“During the past 12 months, was there a time when you needed any of the following, but could not get it at that time: Vision care or eye glasses?”)

#### 2.18.39 umt_vsn_3lev

Years: 2021, 2023
Description: Factor for need and receipt of vision care in the past 12 months
Coding Details: This variable is derived from questions F68B_2_1 (“During the past 12 months, was there a time when you needed vision care or eyeglasses?”) and F68B_2_2 (“Were you able to get the vision care or eyeglasses that you needed?”). Note that these questions were renamed ND_VS_IMP and UNMT_VS_IMP, respectively, beginning in 2023.

##### Variable Levels

- Did Not Need Care
  - Level Details: F68B_2_1= “No”
- Received Needed Care
  - Level Details: F68B_2_2 = “Yes” and F68B_2_2 = “Yes”
- Did Not Receive Needed Care
  - Level Details: F68B_2_2 = “Yes” and F68B_2_2 = “No”

#### 2.18.40 umt_vsn_cost

Years: 2023
Description: Indicator for not getting needed vision care because it would cost too much among those who had an unmet need for vision care in the past 12 months
Coding Details: This variable is derived from question UM_VS_RS01 (“Why did you not get the vision care, eyeglasses, or lenses you needed during the past 12 months? I thought it would cost too much”). This variable is populated for all respondents who are indicated by umt_vsn_need as having an unmet vision need in the past 12 months.

#### 2.18.41 umt_vsn_ins

Years: 2023
Description: Indicator for not getting needed vision care because they could not find provider who would accept their insurance among those who had an unmet vision care in the past 12 months
Coding Details: This variable is derived from question UM_VS_RS04 (“Why did you not get the vision care, eyeglasses, or lenses you needed during the past 12 months? I could not find a provider who would accept my insurance”). This variable is populated for all respondents who are indicated by umt_vsn_need as having an unmet vision need in the past 12 months.

#### 2.18.42 umt_vsn_need

Years: 2021, 2023
Description: Indicator for having an unmet vision need among those who needed care in the past 12 months
Coding Details: This variable is derived from questions F68B_2_1 (“During the past 12 months, was there a time when you needed vision care or eyeglasses?”) and F68C_2_2 (“Were you able to get the vision care or eyeglasses that you needed?”). Note that these questions were renamed ND_VS_IMP and UNMT_VS_IMP, respectively, beginning in 2023.

#### 2.18.43 umt_vsn_trans

Years: 2023
Description: Indicator for not getting needed vision care because they did not have transportation among those who had an unmet need for vision care in the past 12 months
Coding Details: This variable is derived from question UM_VS_RS02 (“Why did you not get the vision care, eyeglasses, or lenses you needed during the past 12 months? I did not have transportation to or from appointments”). During the past 12 months, //have you/has PERSON FROM S1// not filled a prescription because of the cost? This includes refills.

#### 2.18.44 umt_vsn_unavl

Years: 2023
Description: Indicator for not getting needed vision care because the provider was unavailable when they needed it among those who had an unmet need for vision care in the past 12 months
Coding Details: This variable is derived from question UM_VS_RS03 (“Why did you not get the vision care, eyeglasses, or lenses you needed during the past 12 months? The provider was not available when I needed to go”). During the past 12 months, //have you/has PERSON FROM S1// not filled a prescription because of the cost? This includes refills.

### 2.19 Vaccines

#### 2.19.1 vac_ever_cvd

Years: 2023
Description: Indicator for having ever received a shot or vaccine for COVID-19
Coding Details: This variables is derived from question VACRC_EVR3 (“Have you ever had a shot or vaccine for COVID-19?”).

#### 2.19.2 vac_ever_pna

Years: 2023
Description: Indicator for having ever received a shot or vaccine for pneumonia among those who are 65 or older
Coding Details: This variables is derived from question VACRC_EVR1 (“Have you ever had a shot or vaccine for Pneumonia?”) and is NA for respondents who are less than 65 years old according to dem_age_cont.

#### 2.19.3 vac_ever_shingles

Years: 2023
Description: Indicator for having ever received a shot or vaccine for shingles among those who are 50 or older
Coding Details: This variables is derived from question VACRC_EVR2 (“Have you ever had a shot or vaccine for Shingles?”) and is NA for all respondents who are younger than 50 according to dem_age_cont.

#### 2.19.4 vac_flu

Years: 2023
Description: Indicator for having received a shot or vaccine for the flu in the past 12 months
Coding Details: This variables is derived from question VACRC_FLU (“During the past 12 months, have you had a shot or vaccine for the flu?”).

#### 2.19.5 vac_hes_cvd

Years: 2023
Description: Indicator for being very or somewhat hesitant to receive a COVID-19 shot or vaccine
Coding Details: This variable is derived from question VAC_HES4 (“Currently, how hesitant are you to receive vaccines for the COVID-19?”).

#### 2.19.6 vac_hes_flu

Years: 2023
Description: Indicator for being very or somewhat hesitant to receive a flu shot or vaccine
Coding Details: This variable is derived from question VAC_HES1 (“Currently, how hesitant are you to receive vaccines for the flu?”).

#### 2.19.7 vac_hes_pna

Years: 2023
Description: Indicator for being very or somewhat hesitant to receive a pneumonia shot or vaccine among those who are 65 or older
Coding Details: This variable is derived from question VAC_HES2 (“Currently, how hesitant are you to receive vaccines for the pneumonia?”) and is NA for respondents who are less than 65 years old according to dem_age_cont.

#### 2.19.8 vac_hes_shingles

Years: 2023
Description: Indicator for being very or somewhat hesitant to receive a shingles shot or vaccine among those who are 50 or older
Coding Details: This variable is derived from question VAC_HES3 (“Currently, how hesitant are you to receive vaccines for the shingles?”) and is NA for respondents who are less than 50 years old according to dem_age_cont.

### 2.20 Work and Employment

#### 2.20.1 wrk_4lev

Years: 2019, 2021, 2023
Description: Factor for work and job-seeking status
Coding Details: This variable is derived from questions G71_IMP (“Last week did you have a job?”) and G76 (“In the last month have you looked for work?”).

##### Variable Levels

- Working
  - Level Details: G71_IMP = “Yes”
- Not Working and Looking for Work
  - Level Details: G71_IMP = “No” and G76 = “Yes”
- Not Working and Not Looking for Work
  - Level Details: G71_IMP = “No” and G76 = “No”
- Not Working and Unknown if Looking for Work
  - Level Details: G71_IMP = “No” and G76 = “DK”,“RF”

#### 2.20.2 wrk_fac

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for working status
Coding Details: This variable is derived from question G71 (“Last week, did you have a job?”).

##### Variable Levels

- Working
- Not Working

#### 2.20.3 wrk_hours

Years: 2023
Description: Factor for number of hours worked last week
Coding Details: This variable is derived from question G71a (“Thinking about just last week, how many hours did you work?”). It is NA for all respondents who did not work last week according to wrk_fac.

##### Variable Levels

- 0-10 hours
- 11-20 hours
- 21-30 hours
- 31-40 hours
- More than 40 hours

#### 2.20.4 wrk_lost

Years: 2023
Description: Indicator for having lost their job in the past twelve months
Coding Details: This variable is derived from question LS_JB (“During the past 12 months, did you lose a job? By ‘lose a job’, we mean getting fired, let go, or laid off, meaning that you no longer work in that job.”).

#### 2.20.5 wrk_lost_cvd

Years: 2021
Description: Indicator that respondent lost a job since March 2020
Coding Details: This variable is derived from question G70 (“Since March of 2020, have you lost a job?”).

#### 2.20.6 wrk_lost_fam_cvd

Years: 2021
Description: Indicator that a family member lost a job since March 2020
Coding Details: This variable is derived from question G70A (“Since March of 2020, has a family member you live with lost a job?”).

#### 2.20.7 wrk_lv

Years: 2023
Description: Indicator for having chosen to leave a job in the past twelve months
Coding Details: This variable is derived from question LV_JB (“During the past 12 months, did you choose to leave a job? By ‘leave a job’, we mean quitting or voluntarily deciding to no longer work in that job.”)

#### 2.20.8 wrk_lv_benefits

Years: 2023
Description: Indicator for having left job because the benefits weren’t good in the past twelve months among those who chose to leave a job during that time period
Coding Details: This variable is derived from question WHY_LV_JB06 (“Did you choose to leave that job because the benefits, such as health insurance, weren’t good?”). It is NA for respondents who did not chose to leave a job in the past 12 months according to wrk_lv.

#### 2.20.9 wrk_lv_childcare

Years: 2023
Description: Indicator for having left job because of childcare issues in the past twelve months among those who chose to leave a job during that time period
Coding Details: This variable is derived from question WHY_LV_JB04 (“Did you choose to leave that job because of childcare issues?”). It is NA for those who did not chose to leave a job in the past 12 months according to wrk_lv.

#### 2.20.10 wrk_lv_flex

Years: 2023
Description: Indicator for having left job because there was not enough flexibility in work schedule or hours in the past twelve months among those who chose to leave a job during that time period
Coding Details: This variable is derived from question WHY_LV_JB05 (“Did you choose to leave that job because there was not enough flexibility in work schedule or hours?”). It is NA for those who did not chose to leave a job in the past 12 months according to wrk_lv.

#### 2.20.11 wrk_lv_opp

Years: 2023
Description: Indicator for having left job because not enough opportunities for advancement in the past twelve months among those who chose to leave a job during that time period
Coding Details: This variable is derived from question WHY_LV_JB02 (“Did you choose to leave that job because there were not enough opportunities for advancement?”). It is NA for those who did not chose to leave a job in the past 12 months according to wrk_lv.

#### 2.20.12 wrk_lv_pay

Years: 2023
Description: Indicator for having left job because the pay was too low in the past twelve months among those who chose to leave a job during that time period
Coding Details: This variable is derived from question WHY_LV_JB01 (“Did you choose to leave that job because the pay was too low?”). It is NA for those who did not chose to leave a job in the past 12 months according to wrk_lv.

#### 2.20.13 wrk_lv_respect

Years: 2023
Description: Indicator for having left job because they felt disrespected at work in the past twelve months among those who chose to leave a job during that time period
Coding Details: This variable is derived from question WHY_LV_JB03 (“Did you choose to leave that job because you felt disrespected at work?”). It is NA for those who did not chose to leave a job in the past 12 months according to wrk_lv.

#### 2.20.14 wrk_lv_transp

Years: 2023
Description: Indicator for having left job because of transportation issues in the past twelve months among those who chose to leave a job during that time period
Coding Details: This variable is derived from question WHY_LV_JB07 (“Did you choose to leave that job because of transportation issues?”). It is NA for those who did not chose to leave a job in the past 12 months according to wrk_lv.

#### 2.20.15 wrk_mcd_fx

Years: 2023
Description: Factor for how having Medicaid coverage affects ability to work among those who have Medicaid and are currently working
Coding Details: This variable is derived from question MCD_WRK (“Does having Medicaid coverage affect your ability to work?”). It is only populated for respondents who have Medicaid (ins_mcd) and are working (wrk_fac).

##### Variable Levels

- Makes it Easier
- Has No Effect
- Makes it Harder

#### 2.20.16 wrk_mcd_look_fx

Years: 2023
Description: Factor for how having Medicaid coverage affects ability to look for work among those who have Medicaid and are currently not working
Coding Details: This variable is derived from question MCD_LK_WRK (“Does having Medicaid coverage affect your ability to look for work?”). It is only populated for respondents who have Medicaid (ins_mcd) and are working (wrk_fac).

##### Variable Levels

- Makes it Easier
- Has No Effect
- Makes it Harder

#### 2.20.17 wrk_no_caretaker

Years: 2019, 2021, 2023
Description: Indicator for not working due to being a caretaker for a family member
Coding Details: This variable is derived from question G77B (2021) or NTWK_RS_2 (2023 on; “Are you not working because you are caring for a child/adult family member?”). It is NA for all respondents who were working last week according to wrk_fac.

#### 2.20.18 wrk_no_find

Years: 2019, 2021, 2023
Description: Indicator for not working due to being unable to find work
Coding Details: This variable is derived from question G77A (2021) or NTWK_RS_1 (2023 on; “Are you not working because you could not find work?”). It is NA for all respondents who were working last week according to wrk_fac.

#### 2.20.19 wrk_no_health

Years: 2019, 2021, 2023
Description: Indicator for not working due to at least one physical or mental health condition
Coding Details: This variable is derived from question G77C (2021) or NTWK_RS_3 (2023 on; “Are you not working because you have at least one physical or mental health limitation?”). It is NA for all respondents who were working last week according to wrk_fac.

#### 2.20.20 wrk_no_retired

Years: 2019, 2021, 2023
Description: Indicator for not working due to being retired among those not working and 55 or older
Coding Details: This variable is derived from question G71RET_IMP (2019), G77RET_IMP (2021), or NTWK_RS_1 (2023 on; “Are you not working because you are retired?”). This variable is NA for all respondents under 55 years old (G71RET was only asked to respondents 55 or older in 2021) and if a respondent is working according to wrk_fac (a factor for working status last week).

#### 2.20.21 wrk_no_train

Years: 2019, 2021, 2023
Description: Indicator for not working due to being in school or a job training program
Coding Details: This variable is derived from question G77E (2021) or NTWK_RS_4 (2023 on; “Are you not working because you are in a job training program or in school?”). It is NA for all respondents who were working last week according to wrk_fac.

#### 2.20.22 wrk_no_trans

Years: 2023
Description: Indicator for being unemployed due to a lack of reliable transportation
Coding Details: This variable is derived from question NTWK_RS_6 (“Are you not working because you do not have reliable transportation?”). It is NA for all respondents who were working last week according to wrk_fac.

#### 2.20.23 wrk_retired_fac

Years: 2019, 2021, 2023
Description: Factor for being retired among those 55 years or older
Coding Details: This variable is derived from question G71RET_IMP (2019), G77RET_IMP (2021), or NTWK_RS_1 (2023 on; “Are you not working because you are retired?”). This variable is 0 if a respondent is not working according to wrk_fac (a factor for working status last week). This variable is NA for all respondents who are less than 55 years old because question G77RET was restricted to individuals 55 years of age or older beginning in 2021.

##### Variable Levels

- Not Retired
- Retired

#### 2.20.24 wrk_self_employ

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for being self-employed among those who are currently working
Coding Details: This variable is derived from question G71A (2010, 2012, 2015; “Do you work for the government, private industry, or self-employed?”) or G71A_NEW (all other years; “Are you self-employed at all? This may be in addition to your main job.”). This variable is missing for all respondents who are not working according to wrk_fac.

#### 2.20.25 wrk_tenure

Years: 2019, 2021, 2023
Description: Factor for length of employment at current job among those who worked last week
Coding Details: This variable is derived from question G71F (“How long have you had your current job?”).

##### Variable Levels

- Less than 3 Months
- 3 to 6 Months
- 6 Months to 1 Year
- 1 Year or Longer

## 3 Child Variable Descriptions

### 3.1 Access to Care

#### 3.1.1 ac_avoid_cost

Years: 2019, 2021
Description: Indicator that needed health care was delayed or avoided due to cost in the past 12 months
Coding Details: This variable is derived from question AVOID_CARE_C (“During the past 12 months, did you delay or avoid getting care that you felt <child’s name> needed because of the cost?”).

#### 3.1.2 ac_uslsrc_fac

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for having a usual source of medical care
Coding Details: This variable is derived from question N136 (prior to 2021: “Is there one place that you usually go to when <child’s name> is sick or need advice about their health?”; 2021 on: “When <child’s name> is sick or needs advice about their health, do they usually receive care at one place, more than one place, or no place at all?”).

##### Variable Levels

- Does Not have a Usual Source of Care
- Has a Usual Source of Care

#### 3.1.3 ac_uslsrc_not_ed

Years: 2019, 2021, 2023
Description: Indicator for having a usual source of medical care that is not an emergency department
Coding Details: This variable indicates that a child’s value for ac_uslsrc_place (a factor for place of usual source of care) is not “Hospital ER” or “No Usual Source of Care”.

#### 3.1.4 ac_uslsrc_place

Years: 2019, 2021, 2023
Description: Factor for place of usual source of medical care
Coding Details: This variable is derived from questions N136 (prior to 2021: “Is there one place that you usually go to when <child’s name> is sick or need advice about their health?”; 2021 on: “When <child’s name> is sick or needs advice about their health, do they usually receive care at one place, more than one place, or no place at all?”) and N136A (“Is the place where <child’s name> usually receives care or advice about their health a doctor’s office or health center, including by phone or video call, a hospital emergency room, an urgent care center, including by phone or video call, a clinic in a pharmacy or grocery store, or some other place?”).

##### Variable Levels

- No Usual Source of Care
- Doctor’s Office or Health Center
- Hospital ER
- Urgent Care Center
- Clinic in a Pharmacy or Grocery Store
- Some Other Place

### 3.2 Adverse Childhood Experiences (ACEs)

#### 3.2.1 aces_10_race

Years: 2019, 2021, 2023
Description: Indicator for being treated or judged unfairly because of race or ethnic group
Coding Details: This variable is derived from question ACE_10 (“Has <child’s name> ever been treated or judged unfairly because of their race or ethnic group?”).

#### 3.2.2 aces_3_divorce

Years: 2019, 2021, 2023
Description: Indicator for divorce or separation of a parent or guardian
Coding Details: This variable is derived from question ACE_3 (“To the best of your knowledge, has <child’s name> ever experienced parents or guardians going through a divorce or separation?”).

#### 3.2.3 aces_3ormore

Years: 2019, 2021, 2023
Description: Indicator for count of 3 or more ACES
Coding Details: This variable indicates that a child has experienced three or more Adverse Childhood Experiences (ACEs) as recorded by aces_sum (a count of the number of ACEs a child has had).

#### 3.2.4 aces_4_death

Years: 2019, 2021, 2023
Description: Indicator for parent or guardian death
Coding Details: This variable is derived from question ACE_4 (“Has <child’s name> ever experienced the death of a parent or guardian?”).

#### 3.2.5 aces_4ormore

Years: 2019, 2021, 2023
Description: Indicator for having 4 or more ACES
Coding Details: This variable indicates that a child has experienced four or more Adverse Childhood Experiences (ACEs) according to aces_sum.

#### 3.2.6 aces_5_jail

Years: 2019, 2021, 2023
Description: Indicator for parent or guardian serving time in jail after child was born
Coding Details: This variable is derived from question ACE_5 (“Has <child’s name> ever experienced a parent or guardian serving time in jail after <child’s name> was born?”).

#### 3.2.7 aces_6_hit

Years: 2019, 2021, 2023
Description: Indicator for having seen or heard parents or adults slap, hit, kick, or punch one another in the home
Coding Details: This variable is derived from question ACE_6 (“Has <child’s name> ever seen or heard parents or adults slap, hit, kick, punch one another in the home?”).

#### 3.2.8 aces_7_neigh

Years: 2019, 2021, 2023
Description: Indicator for being a victim of violence or witnessing violence in the neighborhood
Coding Details: This variable is derived from question ACE_7 (“Has <child’s name> ever been the victim of violence or witnessed violence in their neighborhood?”).

#### 3.2.9 aces_8_mh

Years: 2019, 2021, 2023
Description: Indicator for ever living with anyone who was mentally ill, suicidal, or severly depressed
Coding Details: This variable is derived from question ACE_8 (“Has <child’s name> ever lived with anyone who was mentally ill, suicidal, or severely depressed?”).

#### 3.2.10 aces_9_alcdrg

Years: 2019, 2021, 2023
Description: Indicator for ever living with anyone who had a problem with alcohol or drugs
Coding Details: This variable is derived from question ACE_9 (“Has <child’s name> ever lived with anyone who had a problem with alcohol or drugs?”).

#### 3.2.11 aces_cat

Years: 2019, 2021, 2023
Description: Factor for number of ACEs
Coding Details: This variable categorizes a child by the number of Adverse Childhood Experiences (ACEs) they have experienced according to aces_sum.

##### Variable Levels

- 0 ACEs
- 1-3 ACEs
- 4+ ACEs

#### 3.2.12 aces_sum

Years: 2019, 2021, 2023
Description: Count of number of ACEs
Coding Details: This variable is a count of the number of Adverse Childhood Experiences (ACEs) that a child has experienced based on questions ACE_3 to ACE_10, which consider the following ACEs: whether the child’s parent or guardian divorced or separated, died, or served time in jail after the child was born, whether the child has seen or heard parents or adults slap, hit, kick, punch one another in the home or was a victim of violence or witnessed violence in neighborhood, whether the child has lived with anyone who was mentally ill, suicidal, or severely depressed or had a problem with alcohol or drugs, and whether the child has ever been treated or judged unfairly because of their race or ethnic group.

### 3.3 Chronic Conditions

#### 3.3.1 cc_asth

Years: 2012, 2019, 2021
Description: Indicator for ever being diagnosed with asthma
Coding Details: This variable is derived from question LAS1A (“Has a doctor or other health professional ever told you that <child’s name> has asthma?”).

#### 3.3.2 cc_asth_now

Years: 2012
Description: Indicator for currently having asthma
Coding Details: This variable us derived from questions LAS1A (“Has a doctor or other health professional ever told you that <child’s name> has asthma?”) and LAS1B (“Does <child’s name> currently have asthma?”).

### 3.4 Demographics

#### 3.4.1 dem_age

Years: 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor categorizing by age
Coding Details: This variable is derived from I90A_IMP (“How old was <child’s name> on their last birthday?”).

##### Variable Levels

- 0-5
- 6-11
- 12-18

#### 3.4.2 dem_age_cont

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Numeric age in years
Coding Details: This variable is derived from I90A_IMP (“How old was <child’s name> on their last birthday?”).

#### 3.4.3 dem_female

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for female sex
Coding Details: This variable is derived from P148_IMP (“What is <child’s name>’s sex?”). This variable is the inverse of dem_male.

#### 3.4.4 dem_male

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for male sex
Coding Details: This variable is derived from P148_IMP (“What is <child’s name>’s sex?”). This variable is the inverse of dem_female.

#### 3.4.5 dem_parents_work

Years: 2010, 2012, 2015, 2017, 2019, 2021
Description: Indicator for at least one parent having a job last week
Coding Details: If the respondent is not the child’s parent based on question I90B (“What is your relationship to <child’s name>?”), this variable is derived from question P151 (“Are either of <child’s name> parents employed?”). If the respondent is the child’s parent, then this variable is derived from question G71 (“Last week, did you have a job?”) and, if “No” to G71, question P151.

#### 3.4.6 dem_raceeth

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for race/ethnicity with 4 levels
Coding Details: This variable is derived from RACE5_C_IMP (2012, 2021) or RACE4_C_IMP (all other years).

##### Variable Levels

- White or Other, non-Hispanic
- Black, non-Hispanic
- Hispanic
- Asian, non-Hispanic

#### 3.4.7 dem_raceeth_5lev

Years: 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for race/ethnicity
Coding Details: This variable is derived from RACE5_C_IMP (2012, 2021) or RACE4_C_IMP (all other years).

##### Variable Levels

- White, non-Hispanic
- Black, non-Hispanic
- Hispanic
- Asian, non-Hispanic
- Other, non-Hispanic

#### 3.4.8 dem_sex

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for sex
Coding Details: This variable is derived from P148_IMP (“What is <child’s name>’s sex?”).

##### Variable Levels

- Male
- Female

### 3.5 Disability

#### 3.5.1 disab_dif_hear

Years: 2023
Description: Indicator that the child is deaf or has serious difficulty hearing
Coding Details: This variable is derived from CDC_1_CH (“Is <child’s name> deaf or do they have serious difficulty hearing?”)

#### 3.5.2 disab_dif_see

Years: 2023
Description: Indicator that child is blind or has serious difficulty seeing
Coding Details: This variable is derived from question CDC_2_CH (“Is <child’s name> blind or do they have serious difficulty seeing, even when wearing glasses?”)

#### 3.5.3 disab_dvlp_fac

Years: 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for a developmental disability
Coding Details: This variable is derived from question L126H_2 (through 2021) (“Does <child’s name> currently have a developmental disability?”) or CHILD_DD (2023) (“Does <child’s name> have a developmental disability?).

##### Variable Levels

- Does Not Have a Developmental Disability
- Has a Developmental Disability

### 3.6 Geography

#### 3.6.1 geo_aaa

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Area Agency on Aging
Coding Details: This variable is derived from question S9 (2010, 2012; “In what county in the state of Ohio do you live?”) or S9_IMP (all other years).

#### 3.6.2 geo_adamh

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Alcohol, Drug, and Mental Health (ADAMH) board
Coding Details: This variable is derived from question S9 (2010, 2012; “In what county in the state of Ohio do you live?”) or S9_IMP (all other years).

#### 3.6.3 geo_county

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Ohio county of residence
Coding Details: This variable is derived from question S9 (2010, 2012; “In what county in the state of Ohio do you live?”) or S9_IMP (2015, 2017, 2019, 2021).

#### 3.6.4 geo_county_type

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for type of Ohio county of residence
Coding Details: This variable is derived from REGION (2010, 2012, 2015) or S9_TYPE_IMP (2017 on).

##### Variable Levels

- Rural Appalachian
- Metropolitan
- Rural Non-Appalachian
- Suburban

#### 3.6.5 geo_fips

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: FIPS for Ohio county of residence
Coding Details: This variable is derived from question S9 (2010, 2012; “In what county in the state of Ohio do you live?”) or S9_IMP (2015, 2017, 2019, 2021).

#### 3.6.6 geo_mivi_fac

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for residence in a Maternal and Infant Vitality Initiative county
Coding Details: This variable is derived from question S9 (2010, 2012; “In what county in the state of Ohio do you live?”) or S9_IMP (all other years). Counties in the Maternal and Infant Vitality Initiative (MIVI) include Butler, Cuyahoga, Franklin, Hamilton, Lorain, Lucas, Mahoning, Montgomery, Stark, and Summit.

##### Variable Levels

- MIVI
- Non-MIVI

### 3.7 Health Behavior

#### 3.7.1 hb_device

Years: 2019, 2021
Description: Factor for screen time on average weekday
Coding Details: This variable is derived from question DEVICE_USE (“On an average weekday, about how much screen time does <child’s name> usually have?”) where “screen time” is the time that the child spends with cell phones, tablets, television, computers, video games, and other electronic devices for things other than schoolwork.

##### Variable Levels

- None
- Less than 1 Hour
- 1 to 2 Hours
- 3 to 4 Hours
- 5 to 6 Hours
- 7 or More Hours

#### 3.7.2 hb_juice

Years: 2015, 2017, 2019
Description: Indicator for drinking at least one glass of juice yesterday
Coding Details: This variable is derived from question SUGAR_1 (“Considering the food <child’s name> ate yesterday, including meals and snacks, how many glasses or boxes of 100% fruit juice, such as orange or apple juice, did <child’s name> drink?”).

#### 3.7.3 hb_soda

Years: 2015, 2017, 2019
Description: Indicator for drinking at least one non-diet soda yesterday
Coding Details: This variable is derived from question SUGAR_2 (“Yesterday, how many glasses or cans of soda or pop, such as Coke, or other sweetened drinks, such as fruit punch or sports drinks, did <child’s name> drink? Do not count diet drinks.”).

### 3.8 Health Status

#### 3.8.1 hs_bmi

Years: 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for BMI categories
Coding Details: This variable is derived from BMI_C_CAT2 which is based on questions PL125AP (weight in pounds), PL125AP_F (height - feet), and PL125AP_I (height - inches). This variable is only populated for children 6 years of age and older.

##### Variable Levels

- Underweight
  - Level Details: Child’s BMI percentile < 5
- Healthy
  - Level Details: Child’s BMI percentile in [5,85)
- Overweight
  - Level Details: Child’s BMI percentile in [85,95)
- Obese
  - Level Details: Child’s BMI percentile > 95

#### 3.8.2 hs_dntl_fp_fac

Years: 2021, 2023
Description: Factor for self-rated fair or poor dental health
Coding Details: This variable is derived from question D30_D (“Thinking about <child’s name>’s teeth and gums, would you say <child’s name>’s dental health is excellent, very good, good, fair, or poor?”).

##### Variable Levels

- Self-rated Dental Health Excellent/Very Good/Good
- Self-rated Dental Health Fair/Poor

#### 3.8.3 hs_fp_fac

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for fair or poor overall health
Coding Details: This variable is derived from question L125 (2010; “In general, how would you describe <child’s name>’s health? Would you say their health is excellent, very good, good, fair, or poor?”) or L125_IMP (2012 on).

##### Variable Levels

- Self-rated Health Excellent/Very Good/Good
- Self-rated Health Fair/Poor

#### 3.8.4 hs_mhi_12up

Years: 2019, 2021
Description: Indicator for having 14 or more days in the past 30 where mental health prevented school or usual activities among children 12 years and up
Coding Details: This variable indicates a value of 14 or more for LAS12B (“Now, thinking about <child’s name>’s mental health, which includes stress, depression, and problems with emotions or substance use, for how many days, during the past 30 days did a mental health condition or emotional problem keep <child’s name> from participating in school, social relationships with friends, or other usual activities?”). This question was only asked for children 12 years old or older.

#### 3.8.5 hs_mhi_12up_cat

Years: 2019, 2021
Description: Factor for number of days in the past 30 where mental health prevented school or usual activities among children 12 years and up
Coding Details: This variable is derived from LAS12B (“Now, thinking about <child’s name>’s mental health, which includes stress, depression, and problems with emotions or substance use, for how many days, during the past 30 days did a mental health condition or emotional problem keep <child’s name> from participating in school, social relationships with friends, or other usual activities?”). This question was only asked for children 12 years old or older.

##### Variable Levels

- 0 Days
- 1-6 Days
- 7-13 Days
- 14-31 Days

#### 3.8.6 hs_mhi_6to11

Years: 2019, 2021
Description: Indicator for having 14 or more days in the past 30 where mental health prevented school or usual activities among children 6 to 11 years older
Coding Details: This variable indicates a value of 14 or more days to question LAS12A (“Now, thinking about <child’s name>’s mental health, which includes stress, depression, and problems with emotions, for how many days, during the past 30 days, did a mental health condition or emotional problem keep <child’s name> from participating in school, social relationships with friends, or other usual activities?”). This question was only asked for children between 6 and 11 years old.

#### 3.8.7 hs_mhi_6to11_cat

Years: 2019, 2021
Description: Indicator for the number of days in the past 30 where mental health prevented school or usual activities among children 6 to 11 years older
Coding Details: This variable is derived from question LAS12A (“Now, thinking about <child’s name>’s mental health, which includes stress, depression, and problems with emotions, for how many days, during the past 30 days, did a mental health condition or emotional problem keep <child’s name> from participating in school, social relationships with friends, or other usual activities?”). This question was only asked for children between 6 and 11 years old.

##### Variable Levels

- 0 Days
- 1-6 Days
- 7-13 Days
- 14-31 Days

#### 3.8.8 hs_mhi_cat

Years: 2019, 2021, 2023
Description: Number of days in the past 30 days that mental health problems kept the child from their usual activities among children 6 years or older
Coding Details: This variable categorizes by LAS12B_IMP (2023 on; “Now, thinking about <child’s name>’s mental health, which includes stress, depression, and problems with emotions or substance use, for how many days, during the past 30 days did a mental health condition or emotional problem keep <child’s name> from participating in school, social relationships with friends, or other usual activities?”). Prior to 2023, this variable pools hs_mhi_12up_cat and hs_mhi_6to11_cat.

##### Variable Levels

- 0 Days
- 1-6 Days
- 7-13 Days
- 14-31 Days

#### 3.8.9 hs_mhi_fac

Years: 2019, 2021, 2023
Description: Factor for having 14 or more days in the past 30 where mental health prevented school or usual activities for all children 6 years or older
Coding Details: This variable is derived from question LAS12B (2023 on; “Now, thinking about <child’s name>’s mental health, which includes stress, depression, and problems with emotions or substance use, for how many days, during the past 30 days did a mental health condition or emotional problem keep <child’s name> from participating in school, social relationships with friends, or other usual activities?”). Prior to 2023, this question was split for children aged 6 to 11 (LAS12A) and children 12 or older (LAS12B). This variable is defined for all children 6 years old or older.

##### Variable Levels

- Less Than 14 Days of Mental Distress Out of the Last 30 Days
- 14+ Days of Mental Distress Out of the Last 30 Days

#### 3.8.10 hs_mntl_dstr_fac

Years: 2019, 2021, 2023
Description: Factor for having 7 or more days in the past 30 where mental health prevented school or usual activities for all children 6 years or older
Coding Details: This variable is derived from question LAS12B (2023 on; “Now, thinking about <child’s name>’s mental health, which includes stress, depression, and problems with emotions or substance use, for how many days, during the past 30 days did a mental health condition or emotional problem keep <child’s name> from participating in school, social relationships with friends, or other usual activities?”). Prior to 2023, this question was split for children aged 6 to 11 (LAS12A) and children 12 or older (LAS12B). This variable is defined for all children 6 years old or older.

##### Variable Levels

- Less Than 7 Days of Mental Distress Out of the Last 30 Days
- 7+ Days of Mental Distress Out of the Last 30 Days

#### 3.8.11 hs_need_meds

Years: 2010, 2012, 2015, 2017, 2019, 2021
Description: Indicator for currently needing or using prescribed medication other than vitamins
Coding Details: This variable is derived from question L126A (2010, 2012, 2015; “Does <child’s name> currently need or use medicine prescribed by a doctor, other than vitamins?”) or question L126A_NEW (2017, 2019, 2021; “Because of a physical, mental, or emotional condition lasting 6 months or more, does <child’s name> currently need or use medicine prescribed by a doctor or other health care professional, other than vitamins?”).

#### 3.8.12 hs_need_meds23

Years: 2023
Description: Indicator for currently needing prescription medication due to a condition lasting 12 months or more
Coding Details: This variable is derived from DIS12_MED_IMP (“Because of a physical, mental, or emotional condition lasting 12 months or more, does <child’s name> currently need or use medicine prescribed by a doctor or other health care professional, other than vitamins?”).

### 3.9 Healthcare Visits

#### 3.9.1 hcv_audio

Years: 2023
Description: Indicator for having a health care visit by audio call without video in the past twelve months
Coding Details: This variable is derived from question UTLZ_CHLD_2 (“During the past 12 months, did <child’s name> see a doctor or other healthcare provider by audio-only call without video?”).

#### 3.9.2 hcv_dental

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for dental visit in the last year
Coding Details: This variable is derived from question M135 (“About how long has it been since <child’s name> last visited a dentist?”).

#### 3.9.3 hcv_doc_visit

Years: 2010, 2012, 2015, 2017, 2019, 2021
Description: Indicator for doctor’s visit in the last year (excluding overnight hospital stays, emergency room visits, home visits, or telephone calls)
Coding Details: This variable is derived from question M131 (“Not including overnight hospital stays, visits to hospital emergency rooms, home visits, or telephone calls, about how long has it been since <child’s name> last saw a doctor or other health care professional about health?”).

#### 3.9.4 hcv_in_person

Years: 2023
Description: Indicator for having an in-person health care visit ing the past twelve months
Coding Details: This variable is derived from question UTLZ_CHLD_1 (“During the past 12 months, did <child’s name> see a doctor or other healthcare provider in person?”).

#### 3.9.5 hcv_none

Years: 2023
Description: Indicator for having no health care visits in the past twelve months
Coding Details: This variable is derived from hcv_in_person, hcv_audio, and hcv_video.

#### 3.9.6 hcv_tele_4lev

Years: 2023
Description: Factor for the number of telehealth visits in the past 12 months
Coding Details: This variable is derived from question M131C_TELE (“During the past 12 months, how many times has <child’s name> had a telehealth visit with a doctor, nurse, or other healthcare provider?”). If a child did not have an audio or video health visit in the past 12 months, as indicated by hcv_audio and hcv_video, they are assigned a value of “0 times”.

##### Variable Levels

- 0 Times
- 1 to 2 Times
- 3 to 6 Times
- 7 or More Times

#### 3.9.7 hcv_tele_any

Years: 2023
Description: Indicator for one or more telehealth visits in the past 12 months
Coding Details: This variable is derived from hcv_tele_4lev.

#### 3.9.8 hcv_tele_num

Years: 2023
Description: Factor for the number of telehealth visits in the past 12 months with three levels
Coding Details: This variable is derived from question M131C_TELE (“Telehealth is defined as having a health care or counseling visit without going to a healthcare office using a phone, smartphone, or computer. Considering the past 12 months, how often has <child’s name> had a telehealth visit with a doctor, nurse, or other health care provider?”).

##### Variable Levels

- 0 Times
- 1 to 2 Times
- 3 or More Times

#### 3.9.9 hcv_tele_num21

Years: 2021
Description: Factor for number of telehealth visits in past year
Coding Details: This variable is derived from question M131C_TELE (“Telehealth is defined as having a health care or counseling visit without going to a healthcare office using a phone, smartphone, or computer. Considering the past 12 months, how often has <child’s name> had a telehealth visit with a doctor, nurse, or other health care provider?”).

##### Variable Levels

- Never
- 1 or 2 Times
- 3 or 4 Times
- 5 or More Times

#### 3.9.10 hcv_thrpy

Years: 2010, 2012, 2015, 2017, 2019, 2021
Description: Indicator for currently needs or gets special therapy
Coding Details: This variable is derived from question L126J (2010, 2012, 2015; “Does <child’s name> need or get special therapy, such as physical, occupational or speech therapy?”) or question L126J_NEW (2017, 2019, 2021; “Because of a physical, mental, or emotional condition lasting 6 months or more, does <child’s name> need or get special therapy, such as physical, occupational or speech therapy?”).

#### 3.9.11 hcv_thrpy23

Years: 2023
Description: Indicator for currently needing or getting special therapy, such as physical, occupational, or speech therapy, due to a condition lasting 12 months or more
Coding Details: This variable is derived from DIS12_THRP_IMP (“Because of a physical, mental, or emotional condition lasting 12 months or more, does <child’s name> currently need or get special therapy, such as physical, occupational, or speech therapy?”).

#### 3.9.12 hcv_trtcoun

Years: 2010, 2012, 2015, 2017, 2019, 2021
Description: Indicator for currently receiving treatment or counseling for an emotional, developmental, or behavioral problem
Coding Details: This variable is derived from question L126M (2010, 2012, 2015; “Does <child’s name> have any kind of emotional, developmental or behavioral problem for which needs or gets treatment or counseling?”) or question L126M_NEW (2017, 2019, 2021; “Because of a physical, mental, or emotional condition lasting 6 months or more, does <child’s name> have any kind of emotional, developmental or behavioral problem for which they get/need treatment or counseling?”).

#### 3.9.13 hcv_trtcoun23

Years: 2023
Description: Indicator for currently receiving treatment or counseling for an emotional, developmental, or behavioral problem due to a condition lasting 12 months or more
Coding Details: This variable is derived from DIS12_CNS_IMP (“Because of a physical, mental, or emotional condition lasting 12 months or more, does <child’s name> have any kind of emotional, developmental or behavioral problem for which they get/need treatment or counseling?”).

#### 3.9.14 hcv_video

Years: 2023
Description: Indicator for having a health care visit by video call with audio in the past twelve months
Coding Details: This variable is derived from question UTLZ_CHLD_3 (“During the past 12 months, did <child’s name> see a doctor or other healthcare provider by video call with audio?”).

#### 3.9.15 hcv_wellchild

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for a well-child visit in the last year
Coding Details: This variable is derived from question M130 (“During the past 12 months did <child’s name> receive a well-child checkup, that is a general checkup when not sick or injured?”) where “well-child” was replaced with “well-baby” when appropriate based on the child’s age. If the child did not have a doctor’s visit in the last 12 months, as indicated by hcv_doc_visit (prior to 2023) and hcv_none (2023 on), then this indicator is set to 0. If the child does not have a value for the hcv_doc_visit or hcv_none, this indicator is set to NA.

### 3.10 Income

#### 3.10.1 inc_4lev

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for family income as percentage of the federal poverty line with four levels
Coding Details: This variable is derived from inc_7lev.

##### Variable Levels

- Up to 138% FPL
- 138% up to 250% FPL
- 250% up to 400% FPL
- 400% or more FPL

#### 3.10.2 inc_7lev

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for family income as percentage of the federal poverty line
Coding Details: This variable categorizes child by their household’s income as a percentage of the FPL. It is based on H84_A3_IMP (2017) or inc_cont (all other years).

##### Variable Levels

- 0 up to 75% FPL
- 75 up to 100% FPL
- 100 up to 138% FPL
- 138 up to 206% FPL
- 206 up to 250% FPL
- 250 up to 400% FPL
- 400% or more FPL

#### 3.10.3 inc_cont

Years: 2010, 2012, 2015, 2019, 2021, 2023
Description: Numeric value of family income as a percentage of the federal poverty line
Coding Details: This variable is calculated based on questions H84_A1 (“How many family members, including yourself, are supported by the family’s total income?”), H84_A1_NUM (“How many other family members who do not live in your home are also supported by the family’s total income?”), and H84_A3 (“What is your best estimate of your households total XXXX annual income before taxes and deductions?”) where XXXX is the appropriate four digit year. In all years other than 2010 and 2017, this variable is provided as FPL_PCT.

### 3.11 Insurance

#### 3.11.1 ins_dental

Years: 2021, 2023
Description: Indicator for having dental insurance
Coding Details: This variable is derived from question N067 (“Does <child’s name> have any insurance that covers dental bills?”)

#### 3.11.2 ins_esi

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for having employer-sponsored health insurance
Coding Details: This variable is derived from I_TYPE_C (2010) or I_TYPE_C_IMP (2012 on) which categorize by insurance type.

#### 3.11.3 ins_exchange

Years: 2021, 2023
Description: Indicator for having insurance through the health insurance exchange (ie: healthcare.gov)
Coding Details: This variable is derived from INS_EXCHANGE_C_IMP which is based on question J1002J (2021) or EXCHNG_CH (2023; “Is <child’s name> currently covered by health insurance from healthcare.gov, sometimes called the health insurance”exchange” or marketplace?).

#### 3.11.4 ins_mcd

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for having insurance through Medicaid
Coding Details: This variable is derived from I_TYPE_C (2010) or I_TYPE_C_IMP (2012 on) which categorize by insurance type.

#### 3.11.5 ins_none

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for being uninsured
Coding Details: This variable is derived from I_TYPE_C (2010) or I_TYPE_C_IMP (2012 on) which categorize by insurance type.

#### 3.11.6 ins_prvt

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for having private insurance
Coding Details: This variable is derived from I_TYPE_C (2010) or I_TYPE_C_IMP (2012 on) and indicates a child’s insurance is “Directly Purchased”, “Other”, or “Insurance Type Unknown”.

#### 3.11.7 ins_type

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for insurance type
Coding Details: This variable is derived from I_TYPE_C (2010) or I_TYPE_C_IMP (2012 on) which categorize by insurance type.

##### Variable Levels

- Employer-Sponsored
  - Level Details: I_TYPE_C = “Job-Based Coverage”
- Medicaid
  - Level Details: I_TYPE_C = “Medicaid and Medicare”, “Medicaid, No Medicare”
- Other Insured
  - Level Details: I_TYPE_C = “Medicare, No Medicaid”,“Directly Purchased”, “Other”, “Insurance Type Unknown”
- Uninsured
  - Level Details: I_TYPE_C = “Uninsured”

### 3.12 Medicaid Eligibility

#### 3.12.1 mcd_elig

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for potential Medicaid eligibility status with three levels
Coding Details: This variable is derived from ins_mcd and mcd_ptn_elig.

##### Variable Levels

- Medicaid-Enrolled
- Potentially Medicaid Eligible
- Not Potentially Medicaid Eligible

#### 3.12.2 mcd_elig_4lev

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Factor for groupings within being potentially Medicaid eligible
Coding Details: This variable is derived froms ins_mcd, mcd_ptn_elig, mcd_ptn_elig_othins , and mcd_ptn_elig_unins.

##### Variable Levels

- Medicaid-Enrolled
- Potentially Medicaid Eligible and Uninsured
- Potentially Medicaid Eligible with Other Insurance
- Not Potentially Medicaid Eligible

#### 3.12.3 mcd_ptn_elig

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for being potentially Medicaid eligible
Coding Details: This variable indicates that a child is potentially Medicaid eligible because their household’s income is less than or equal to 206% of the FPL. It is derived using inc_7lev.

#### 3.12.4 mcd_ptn_elig_othins

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for being potentially Medicaid eligible and currently on another kind of insurance
Coding Details: This variable is derived from mcd_ptn_elig, ins_none, and ins_mcd.

#### 3.12.5 mcd_ptn_elig_unins

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Indicator for being potentially Medicaid eligible and currently uninsured
Coding Details: This variable is derived from mcd_ptn_elig and ins_none.

### 3.13 Survey

#### 3.13.1 stratum

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Survey stratum
Coding Details: This variable is STRATA (2015, 2017, 2019) or STRATUM (all other years).

#### 3.13.2 wt

Years: 2010, 2012, 2015, 2017, 2019, 2021, 2023
Description: Survey weight
Coding Details: This variable is WT_A_BLEND (2019) or WT_A (all other years).

### 3.14 Unmet Needs

#### 3.14.1 umt_dent

Years: 2010, 2012, 2015, 2017, 2019
Description: Indicator for having an unmet dental care need in the past 12 months
Coding Details: This variable is derived from question O139 (“During the past 12 months, was there a time when <child’s name> needed dental care but could not get it at that time?”).

#### 3.14.2 umt_dent_3lev

Years: 2021, 2023
Description: Factor for need and receipt of dental care in the past 12 months
Coding Details: This variable is derived from questions O139_1 (“During the past 12 months, was there a time when <child’s name> needed dental care?”) and O139_2 (“Was <child’s name> able to get the dental care that they needed?”).

##### Variable Levels

- Did Not Need Care
  - Level Details: O139_1 = “No”
- Received Needed Care
  - Level Details: O139_1 = “Yes” and O139_2 = “Yes”
- Did Not Receive Needed Care
  - Level Details: O139_1 = “Yes” and O139_2 = “No”

#### 3.14.3 umt_dent_cost

Years: 2023
Description: Indicator that for an unmet dental care need due to concerns about cost among those who had an unmet need for dental care in the past 12 months
Coding Details: This variable is derived from question UM_DT_RS_C1 (“Did <child’s name> not get the dental care they needed during the past 12 months because you thought it would cost too much?”). This variable is populated for all children who had an unmet dental care need according to umt_dent_need.

#### 3.14.4 umt_dent_ins

Years: 2023
Description: Indicator that for an unmet dental care need because their guardian could not locate a provider who accepted the child’s insurance among those who had an unmet need for dental care in the past 12 months
Coding Details: This variable indicates that the adult respondent answered “Yes” to question UM_DT_RS_C4 (“Did <child’s name> not get the dental care they needed during the past 12 months because you could not find a provider who would accept <child’s name>’s insurance?”). This variable is populated for all children who had an unmet dental care need according to umt_dent_need.

#### 3.14.5 umt_dent_need

Years: 2021, 2023
Description: Indicator for having an unmet dental care need among those who needed care in the past 12 months
Coding Details: This variable is derived from questions O139_1 (“During the past 12 months, was there a time when <child’s name> needed dental care?”) and O139_2 (“Was <child’s name> able to get the dental care that they needed?”).

#### 3.14.6 umt_dent_trans

Years: 2023
Description: Indicator that for an unmet dental care need due to lack of transportation among those who had an unmet need for dental care in the past 12 months
Coding Details: This variable is derived from question UM_DT_RS_C2 (“Did <child’s name> not get the dental care they needed during the past 12 months because <child’s name> did not have transportation to or from appointments?”). This variable is populated for all children who had an unmet dental care need according to umt_dent_need.

#### 3.14.7 umt_dent_unavl

Years: 2023
Description: Indicator that for an unmet dental care need due to insufficient provider availability among those who had an unmet need for dental care in the past 12 months
Coding Details: This variable is derived from question UM_DT_RS_C3 (“Did <child’s name> not get the dental care they needed during the past 12 months because the provider was not available when <child’s name> needed to go?”). This variable is populated for all children who had an unmet dental care need according to umt_dent_need.

#### 3.14.8 umt_mtl_3lev

Years: 2021, 2023
Description: Factor for need and receipt of mental health care in the past 12 months
Coding Details: This variable is derived from questions O139_MH_1 (“During the past 12 months, was there a time when <child’s name> needed mental or emotional health care or counseling services?”) and O139_MH_2 (“Was <child’s name> able to get the mental or emotional health care or counseling services that they needed?”).

##### Variable Levels

- Did Not Need Care
  - Level Details: O139_MH_1= “No”
- Received Needed Care
  - Level Details: O139_MH_2 = “Yes” and O139_MH_2 = “Yes”
- Did Not Receive Needed Care
  - Level Details: O139_MH_2 = “Yes” and O139_MH_2 = “No”

#### 3.14.9 umt_mtl_cost

Years: 2023
Description: Indicator that for an unmet mental health care need due to concerns about cost among those who had an unmet need for mental healthcare in the past 12 months
Coding Details: This variable is derived from question UM_MT_RS_C1 (Did <child’s name> not get the mental or emotional health care or counseling services they needed during the past 12 months because you thought it would cost too much?). This variable is populated for all children who had an unmet need for mental health care in the past 12 months according to umt_mtl_need.

#### 3.14.10 umt_mtl_ins

Years: 2023
Description: Indicator that for an unmet mental health care need because their guardian could not locate a provider who accepted the child’s insurance among those who had an unmet need for mental healthcare in the past 12 months
Coding Details: This variable indicates that the adult respondent answered “Yes” to question UM_MT_RS_C4 (Did <child’s name> not get the mental or emotional health care or counseling services they needed during the past 12 months because you could not find a provider who would accept <child’s name>’s insurance?). This variable is populated for all children who had an unmet need for mental health care in the past 12 months according to umt_mtl_need.

#### 3.14.11 umt_mtl_need

Years: 2021, 2023
Description: Indicator for having an unmet mental health care need among those who needed care in the past 12 months
Coding Details: This variable is derived from questions O139_MH_1 (“During the past 12 months, was there a time when <child’s name> needed mental or emotional health care or counseling services?”) and O139_MH_2 (“Was <child’s name> able to get the mental or emotional health care or counseling services that they needed?”).

#### 3.14.12 umt_mtl_trans

Years: 2023
Description: Indicator that for an unmet mental health care need due to lack of transportation among those who had an unmet need for mental healthcare in the past 12 months
Coding Details: This variable indicates that the adult respondent answered “Yes” to question UM_MT_RS_C2 (Did <child’s name> not get the mental or emotional health care or counseling services they needed during the past 12 months because <child’s name> did not have transportation to or from appointments?). This variable is populated for all children who had an unmet need for mental health care in the past 12 months according to umt_mtl_need.

#### 3.14.13 umt_mtl_unavl

Years: 2023
Description: Indicator that for an unmet mental health care need due to insufficient provider availability among those who had an unmet need for mental healthcare in the past 12 months
Coding Details: This variable indicates that the adult respondent answered “Yes” to question UM_MT_RS_C3 (Did <child’s name> not get the mental or emotional health care or counseling services they needed during the past 12 months because the provider was not available when <child’s name> needed to go?). This variable is populated for all children who had an unmet need for mental health care in the past 12 months according to umt_mtl_need.

#### 3.14.14 umt_rx_cost

Years: 2010, 2012, 2015
Description: Indicator for not having a prescription filled due to cost in the past 12 months
Coding Details: This variable is derived from question O140 (“During the past 12 months, has <child’s name> not had a prescription filled because of the cost? This includes refills.”).

#### 3.14.15 umt_vsn

Years: 2012, 2015
Description: Indicator for having an unmet vision or eye care need in the past 12 months
Coding Details: This variable is derived from question O139B (“During the past 12 months, was there a time when <child’s name> needed vision or eye care but could not get it at that time?”).

### 3.15 Vaccines

#### 3.15.1 vac_ever_chkpox

Years: 2023
Description: Indicator for ever receiving a vaccine for Chickenpox
Coding Details: This variable is derived from question VACRC_C_EVR1 (“Has <child’s name> ever had a shot or vaccine for chickenpox, that is, Varicella?”).

#### 3.15.2 vac_ever_cvd

Years: 2023
Description: Indicator for ever receiving a vaccine for COVID-19
Coding Details: This variable is derived from question VACRC_C_EVR6 (“Has <child’s name> ever had a shot or vaccine for COVID-19?”).

#### 3.15.3 vac_ever_dtap

Years: 2023
Description: Indicator for ever receiving a vaccine for Tetanus, Diphtheria, and Pertussis
Coding Details: This variable is derived from question VACRC_C_EVR4 (“Has <child’s name> ever had a shot or vaccine for DTaP or Tdap, that is, Tetanus, Diphtheria, Pertussis?”).

#### 3.15.4 vac_ever_hpv

Years: 2023
Description: Indicator for ever receiving a vaccine for HPV
Coding Details: This variable is derived from question VACRC_C_EVR5 (“Has <child’s name> ever had a shot or vaccine for HPV, that is, Human Papillomavirus?”).

#### 3.15.5 vac_ever_mmr

Years: 2023
Description: Indicator for ever receiving a vaccine for Measles, Mumps, and Rubella
Coding Details: This variable indicates that the adult respondent answered “Yes” to question VACRC_C_EVR2 (“Has <child’s name> ever had a shot or vaccine for MMR, that is, Measles, Mumps, Rubella?”).

#### 3.15.6 vac_ever_polio

Years: 2023
Description: Indicator for ever receiving a vaccine for Polio
Coding Details: This variable is derived from question VACRC_C_EVR3 (“Has <child’s name> ever had a shot or vaccine for Polio?”).

#### 3.15.7 vac_flu

Years: 2023
Description: Indicator for the child having received a flu vaccine in the past 12 months
Coding Details: This variable is derived from question VACRC_C_FLU (“During the past 12 months, has <child’s name> had a shot or vaccine for the flu?”).

#### 3.15.8 vac_hes_chkpox

Years: 2023
Description: Indicator for adult respondent being very or somewhat hesitant to have children in their household receive a vaccine for chicken pox
Coding Details: This variable is derived from question VAC_C_HES2 (“Currently, how hesitant are you about the children in your household receiving the vaccine for Chickenpox, that is, Varicella? Very hesitant, somewhat hesitant, not that hesitant, or not at all hesitant?”).

#### 3.15.9 vac_hes_cvd

Years: 2023
Description: Indicator for adult respondent being very or somewhat hesitant to have children in their household receive a vaccine for COVID-19
Coding Details: This variable is derived from question VAC_C_HES7 (“Currently, how hesitant are you about the children in your household receiving the vaccine for COVID-19? Very hesitant, somewhat hesitant, not that hesitant, or not at all hesitant?”).

#### 3.15.10 vac_hes_dtap

Years: 2023
Description: Indicator for adult respondent being very or somewhat hesitant to have children in their household receive a vaccine for diphtheria, tetanus, and pertussis
Coding Details: This variable is derived from question VAC_C_HES5 (“Currently, how hesitant are you about the children in your household receiving the vaccine for DTaP/Tdap, that is, Tetanus, Diphtheria, Pertussis? Very hesitant, somewhat hesitant, not that hesitant, or not at all hesitant?”).

#### 3.15.11 vac_hes_flu

Years: 2023
Description: Indicator for adult respondent being very or somewhat hesitant to have children in their household receive a vaccine for influenza
Coding Details: This variable is derived from question VAC_C_HES1 (“Currently, how hesitant are you about the children in your household receiving the vaccine for Flu? Very hesitant, somewhat hesitant, not that hesitant, or not at all hesitant?”).

#### 3.15.12 vac_hes_hpv

Years: 2023
Description: Indicator for adult respondent being very or somewhat hesitant to have children in their household receive a vaccine for HPV
Coding Details: This variable is derived from question VAC_C_HES6 (“Currently, how hesitant are you about the children in your household receiving the vaccine for HPV, that is, Human Papillomavirus? Very hesitant, somewhat hesitant, not that hesitant, or not at all hesitant?”).

#### 3.15.13 vac_hes_mmr

Years: 2023
Description: Indicator for adult respondent being very or somewhat hesitant to have children in their household receive a vaccine for measles, mumps, and rubella
Coding Details: This variable is derived from question VAC_C_HES3 (“Currently, how hesitant are you about the children in your household receiving the vaccine for MMR, that is, Measles, Mumps, Rubella? Very hesitant, somewhat hesitant, not that hesitant, or not at all hesitant?”).

#### 3.15.14 vac_hes_polio

Years: 2023
Description: Indicator for adult respondent being very or somewhat hesitant to have children in their household receive a vaccine for polio
Coding Details: This variable is derived from question VAC_C_HES4 (“Currently, how hesitant are you about the children in your household receiving the vaccine for Polio? Very hesitant, somewhat hesitant, not that hesitant, or not at all hesitant?”).

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