The U.S. Census Bureau, in collaboration with five federal agencies, launched the Household Pulse Survey to produce data on the social and economic impacts of Covid-19 on American households. The Household Pulse Survey was designed to gauge the impact of the pandemic on employment status, consumer spending, food security, housing, education disruptions, and dimensions of physical and mental wellness. The survey was designed to meet the goal of accurate and timely weekly estimates. It was conducted by an internet questionnaire, with invitations to participate sent by email and text message. The sample frame is the Census Bureau Master Address File Data. Housing units linked to one or more email addresses or cell phone numbers were randomly selected to participate, and one respondent from each housing unit was selected to respond for him or herself. Estimates are weighted to adjust for nonresponse and to match Census Bureau estimates of the population by age, sex, race and ethnicity, and educational attainment. All estimates shown meet the NCHS Data Presentation Standards for Proportions,

Overview

The Associated Press is sharing data from the COVID Impact Survey, which provides statistics about physical health, mental health, economic security and social dynamics related to the coronavirus pandemic in the United States.

Conducted by NORC at the University of Chicago for the Data Foundation, the probability-based survey provides estimates for the United States as a whole, as well as in 10 states (California, Colorado, Florida, Louisiana, Minnesota, Missouri, Montana, New York, Oregon and Texas) and eight metropolitan areas (Atlanta, Baltimore, Birmingham, Chicago, Cleveland, Columbus, Phoenix and Pittsburgh).

The survey is designed to allow for an ongoing gauge of public perception, health and economic status to see what is shifting during the pandemic. When multiple sets of data are available, it will allow for the tracking of how issues ranging from COVID-19 symptoms to economic status change over time.

The survey is focused on three core areas of research:

• Physical Health: Symptoms related to COVID-19, relevant existing conditions and health insurance coverage.
• Economic and Financial Health: Employment, food security, and government cash assistance.
• Social and Mental Health: Communication with friends and family, anxiety and volunteerism. (Questions based on those used on the U.S. Census Bureau’s Current Population Survey.) ## Using this Data - IMPORTANT This is survey data and must be properly weighted during analysis: DO NOT REPORT THIS DATA AS RAW OR AGGREGATE NUMBERS!!

Instead, use our queries linked below or statistical software such as R or SPSS to weight the data.

Queries

If you'd like to create a table to see how people nationally or in your state or city feel about a topic in the survey, use the survey questionnaire and codebook to match a question (the variable label) to a variable name. For instance, "How often have you felt lonely in the past 7 days?" is variable "soc5c".

Nationally: Go to this query and enter soc5c as the variable. Hit the blue Run Query button in the upper right hand corner.

Local or State: To find figures for that response in a specific state, go to this query and type in a state name and soc5c as the variable, and then hit the blue Run Query button in the upper right hand corner.

The resulting sentence you could write out of these queries is: "People in some states are less likely to report loneliness than others. For example, 66% of Louisianans report feeling lonely on none of the last seven days, compared with 52% of Californians. Nationally, 60% of people said they hadn't felt lonely."

Margin of Error

The margin of error for the national and regional surveys is found in the attached methods statement. You will need the margin of error to determine if the comparisons are statistically significant. If the difference is:

• At least twice the margin of error, you can report there is a clear difference.
• At least as large as the margin of error, you can report there is a slight or apparent difference.
• Less than or equal to the margin of error, you can report that the respondents are divided or there is no difference. ## A Note on Timing Survey results will generally be posted under embargo on Tuesday evenings. The data is available for release at 1 p.m. ET Thursdays.

About the Data

The survey data will be provided under embargo in both comma-delimited and statistical formats.

Each set of survey data will be numbered and have the date the embargo lifts in front of it in the format of: 01_April_30_covid_impact_survey. The survey has been organized by the Data Foundation, a non-profit non-partisan think tank, and is sponsored by the Federal Reserve Bank of Minneapolis and the Packard Foundation. It is conducted by NORC at the University of Chicago, a non-partisan research organization. (NORC is not an abbreviation, it part of the organization's formal name.)

Data for the national estimates are collected using the AmeriSpeak Panel, NORC’s probability-based panel designed to be representative of the U.S. household population. Interviews are conducted with adults age 18 and over representing the 50 states and the District of Columbia. Panel members are randomly drawn from AmeriSpeak with a target of achieving 2,000 interviews in each survey. Invited panel members may complete the survey online or by telephone with an NORC telephone interviewer.

Once all the study data have been made final, an iterative raking process is used to adjust for any survey nonresponse as well as any noncoverage or under and oversampling resulting from the study specific sample design. Raking variables include age, gender, census division, race/ethnicity, education, and county groupings based on county level counts of the number of COVID-19 deaths. Demographic weighting variables were obtained from the 2020 Current Population Survey. The count of COVID-19 deaths by county was obtained from USA Facts. The weighted data reflect the U.S. population of adults age 18 and over.

Data for the regional estimates are collected using a multi-mode address-based (ABS) approach that allows residents of each area to complete the interview via web or with an NORC telephone interviewer. All sampled households are mailed a postcard inviting them to complete the survey either online using a unique PIN or via telephone by calling a toll-free number. Interviews are conducted with adults age 18 and over with a target of achieving 400 interviews in each region in each survey.Additional details on the survey methodology and the survey questionnaire are attached below or can be found at https://www.covid-impact.org.

Attribution

Results should be credited to the COVID Impact Survey, conducted by NORC at the University of Chicago for the Data Foundation.

AP Data Distributions

​To learn more about AP's data journalism capabilities for publishers, corporations and financial institutions, go here or email kromano@ap.org.

BackgroundLittle is known about whether people who use both tobacco and cannabis (co-use) are more or less likely to have mental health disorders than single substance users or non-users. We aimed to examine associations between use of tobacco and/or cannabis with anxiety and depression.MethodsWe analyzed data from the COVID-19 Citizen Science Study, a digital cohort study, collected via online surveys during 2020–2022 from a convenience sample of 53,843 US adults (≥ 18 years old) nationwide. Past 30-day use of tobacco and cannabis was self-reported at baseline and categorized into four exclusive patterns: tobacco-only use, cannabis-only use, co-use of both substances, and non-use. Anxiety and depression were repeatedly measured in monthly surveys. To account for multiple assessments of mental health outcomes within a participant, we used Generalized Estimating Equations to examine associations between the patterns of tobacco and cannabis use with each outcome.ResultsIn the total sample (mean age 51.0 years old, 67.9% female), 4.9% reported tobacco-only use, 6.9% cannabis-only use, 1.6% co-use, and 86.6% non-use. Proportions of reporting anxiety and depression were highest for the co-use group (26.5% and 28.3%, respectively) and lowest for the non-use group (10.6% and 11.2%, respectively). Compared to non-use, the adjusted odds of mental health disorders were highest for co-use (Anxiety: OR = 1.89, 95%CI = 1.64–2.18; Depression: OR = 1.77, 95%CI = 1.46–2.16), followed by cannabis-only use, and tobacco-only use. Compared to tobacco-only use, co-use (OR = 1.35, 95%CI = 1.08–1.69) and cannabis-only use (OR = 1.17, 95%CI = 1.00–1.37) were associated with higher adjusted odds for anxiety, but not for depression. Daily use (vs. non-daily use) of cigarettes, e-cigarettes, and cannabis were associated with higher adjusted odds for anxiety and depression.ConclusionsUse of tobacco and/or cannabis, particularly co-use of both substances, were associated with poor mental health. Integrating mental health support with tobacco and cannabis cessation may address this co-morbidity.

National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) was designed to assess the prevalence of alcohol use disorders (AUD) and their associated disabilities in the general population. The survey is the largest ever comorbidity study of multiple mental health disorders among U.S. adults, including alcohol and other substance use disorders, personality disorders, and anxiety and mood disorders. NESARC is designed to be a longitudinal survey with the first wave fielded in 2001–2002. The second wave of interviews was completed in 2004–2005 and used the same sample of respondents. NESARC is a nationwide household survey with a probability sample representative of US adults. The final sample for Wave 1 was 43,093 respondents; Wave 2 was 34,653 of the Wave 1 respondents. Data are not publicly available; however, researchers may request specific analyses via Census.

The dataset contains self-report inventory, the Symptom Checklist-90 (SCL-90) was used to investigate the mental health status of 548 medical personnel dealing with the new coronavirus pneumonia in eight provinces and cities of China. Some factors that were assessed include somatization, obsessive-compulsive, anxiety, phobic anxiety, psychoticism, and personal factors affecting the mental health status of medical personnel. Data is accessible to people who have an OPEN ICPSR account.

The Generations study is a five-year study designed to examine health and well-being across three generations of lesbians, gay men, and bisexuals (LGB). The study explored identity, stress, health outcomes, and health care and services utilization among LGBs in three generations of adults who came of age during different historical contexts. This collection includes baseline, wave 1, and wave 2 data collected as part of the Generations study. The study aimed to assess whether younger cohorts of LGBs differed from older cohorts in how they viewed their LGB identity and experienced stress related to prejudice and everyday forms of discrimination, as well as whether patterns of resilience differed between different LGB cohorts. Additionally, the study sought to examine how differences in stress experience affected mental health and well-being, including depressive and anxiety symptoms, substance and alcohol use, suicide ideation and behavior, and how younger LGBs utilized LGB-oriented social and health services, relative to older cohorts. In wave 2, respondents were re-interviewed approximately one year after completion of the baseline (wave 1) survey. Only respondents who participated in the original sample of participants were surveyed at wave 2 (i.e., the enhancement oversample was not included in the longitudinal design of this study). In wave 3, respondents were re-interviewed approximately one year after the completion of the wave 2 survey. Demographic variables collected as part of this study include questions related to age, education, race, ethnicity, sexual identity, gender identity, income, employment, and religiosity.

Intercorrelations among mitigation change measures.

Correlations of changes in mitigation behaviors with potential associates.

Mortality rate has been age-adjusted to the 2000 U.S. standard population. ICD-10 codes used to identify suicides are X60-X84, Y87.0, and U03. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Suicide is a leading cause of preventable death in Los Angeles County, affecting individuals of all ages and races and ethnicities. While there is a strong association between suicide and health conditions, such as mood and anxiety disorders or substance use disorders, suicide is rarely caused by a single circumstance and is more often due to a combination of individual, relational, and environmental factors. Individual factors can include history of mental illness, previous suicide attempts, adverse childhood events, or financial hardship. Relational factors include experiences of bullying, loss of relationships, or social isolation. Environmental factors include lack of access to healthcare, community violence, or social stigma associated with seeking help for a mental illness.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

Comparison of positive anxiety screens between study population (years 2013–2014) and NHANES population (years 1999–2004).

The analysis for depression was adjusted for the area of study, current location, family relationships, source of tuition, and age; the analysis for anxiety was adjusted for the area of study, family relationships, source of tuition, and age. The frequency of US social media use, frequency of exercise in the past two weeks, and amount of knowledge about common mental disorders were not significantly associated with either the risk of depression or the risk of anxiety and were removed from the table for abbreviation purposes.