Interactive Biannual Early Release Estimates provide health statistics based on data from the 2019-2021 National Health Interview Survey (NHIS) for selected health topics for adults aged 18 years and over. All estimates are unadjusted percentages based on preliminary data files and are released prior to final data editing and final weighting to provide access to the most recent information from the NHIS. Estimates can be grouped by demographic characteristics (such as age, race and Hispanic origin, or sex). Estimates based on 2019-2020 NHIS quarterly data are available in Interactive Quarterly Early Release Estimates. Estimates based on the 1997–2018 NHIS can be found in Previous Early Release Reports on Key Health Indicators.

Data source description - Adults: NHIS monitors the health of the U.S. population by collecting and analyzing data on a broad range of health topics. Interviews are conducted continuously throughout the year, and are initiated in-person, with telephone follow-up. NHIS focuses on the health of children and adults in the United States. One adult household member is randomly selected to be the subject of a detailed health interview. If children are present, one child is also randomly selected. Adults answer on their own behalf, while a knowledgeable adult answers on behalf of the selected child. NHIS topics featured include adult life satisfaction, anxiety, depression, mental health conditions, mental health care, and social and emotional support.

Data source description - Teenagers: NHIS-Teen was a web-based health survey of teenagers between the ages of 12 to 17. Answers from teenagers helped paint a picture of the health of teenagers living in the United States. NHIS-Teen covered questions on a variety of health topics, including doctor visits, mental health, and social and emotional support. Data were collected between July 2021 and December 2023. 

For additional information, please see: https://www.cdc.gov/mental-health/about-data/mental-health-data-sources.html" target ="_blank">Mental Health Data Sources.

Interactive Biannual Early Release Estimates provide health statistics based on data from the 2019-2021 National Health Interview Survey (NHIS) for selected health topics for adults aged 18 years and over. All estimates are unadjusted percentages based on preliminary data files and are released prior to final data editing and final weighting to provide access to the most recent information from the NHIS. Estimates can be grouped by demographic characteristics (such as age, race and Hispanic origin, or sex). Estimates based on 2019-2020 NHIS quarterly data are available in Interactive Quarterly Early Release Estimates. Estimates based on the 1997–2018 NHIS can be found in Previous Early Release Reports on Key Health Indicators.

The National Health Interview Survey (NHIS)—Teen was a follow-back survey of Sample Children ages 12-17 years old (herein teen) for whom a parent completed the National Health Interview Survey (NHIS) and also provided permission for the teen to participate. NHIS—Teen is a self-administered survey that teens completed themselves either on the web or paper (mailed). Recruitment for NHIS—Teen occurred July 2021—December 2023 during the NHIS Sample Child interview. Teens with permission received an invitation to go online and complete a questionnaire about their own health. Mailed paper questionnaires were sent to nonrespondents. Questions were included to test concordance with parent-reported responses, address time-sensitive data needs, assess public health attitudes or behaviors, and contribute to developmental work to understand differences between parent and self-reported measures of health.

The majority of NHIS—Teen survey content focused on the health behaviors, social and emotional wellbeing, and healthcare experiences of teens. Detailed sociodemographic characteristics (e.g. health insurance coverage type, family income) as reported by the parent in the NHIS Sample Child interview can be linked to NHIS—Teen. NHIS—Teen was a pilot survey with data collection concluding in March 2024. There are currently no plans to field additional iterations.

Interactive Summary Health Statistics for Adults provide annual estimates of selected health topics for adults aged 18 years and over based on final data from the National Health Interview Survey.

In 2020, the National Center for Health Statistics (NCHS) partnered with the Census Bureau on an experimental data system called the Household Pulse Survey. This survey was designed to complement the ability of the federal statistical system to rapidly respond and provide relevant information about how emergent issues are impacting American households. Beginning in Phase 4.0 (on January 9, 2024), questions on social support, loneliness, and social isolation were added to the survey. These questions have been included on other nationally representative surveys. Briefly, the question on social support was included on the National Health Interview Survey (NHIS) from July 2020-December 2021 and was added to the 2024 NHIS. The question on loneliness was added to the 2024 NHIS. The questions on social isolation are adapted from the Berkman-Syme Social Network Index and were included on an earlier cycle of the National Health and Nutrition Examination Survey. For more information, please visit: https://www.cdc.gov/nchs/covid19/pulse/lack-socialconnection.htm

ObjectiveThis study aimed to examine the association between smoking and epilepsy in a nationwide cross-sectional analysis of US adults.MethodsData from the National Health Interview Survey (NHIS) conducted between 2021 and 2022 were utilized, encompassing 57,088 participants aged 18–85 years with documented tobacco usage and self-reported epilepsy. Logistic regression models were employed to evaluate the relationship between smoking and epilepsy. The assessment of tobacco usage encompassed smoking status, cigarette smoking, pipe-filled tobacco smoking, and smokeless tobacco usage.ResultsThe overall prevalence of self-reported epilepsy in the sample was 1.76%, with smokers constituting 46.03% of cases. Individuals with epilepsy exhibited higher smoking rates compared to those without epilepsy. In the multivariate logistic regression model, smoking demonstrated a significant association with self-reported epilepsy (OR = 1.26, 95% CI: 1.07–1.47, P = 0.005). Subsequent stratified analyses showed consistent associations between smoking and self-reported epilepsy in all sex and ethnic subgroups.ConclusionsOur findings suggest that smoking is independently associated with self-reported epilepsy among US adults. Further investigation into the biological mechanisms underlying this association is warranted, contingent upon the validation of these results in an external population.

NOTE: On October 19, 2021, estimates for 2016–2018 by health insurance status were revised to correct errors. Changes are highlighted and tagged at https://www.cdc.gov/nchs/data/hus/2019/012-508.pdf

Data on health conditions among children under age 18, by selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time.

SOURCE: NCHS, National Health Interview Survey, Family Core and Sample Child questionnaires. For more information on the National Health Interview Survey, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus19-appendix-508.pdf.

NOTE: On October 19, 2021, estimates for 2016–2018 by health insurance status were revised to correct errors. Changes are highlighted and tagged at https://www.cdc.gov/nchs/data/hus/2019/012-508.pdf Data on health conditions among children under age 18, by selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time. SOURCE: NCHS, National Health Interview Survey, Family Core and Sample Child questionnaires. For more information on the National Health Interview Survey, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus19-appendix-508.pdf.

Analysis of ‘Loss of Work Due to Illness from COVID-19’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/aff30812-e69e-42c9-9724-88083a583fac on 26 January 2022.

--- Dataset description provided by original source is as follows ---

The Research and Development Survey (RANDS) is a platform designed for conducting survey question evaluation and statistical research. RANDS is an ongoing series of surveys from probability-sampled commercial survey panels used for methodological research at the National Center for Health Statistics (NCHS). RANDS estimates are generated using an experimental approach that differs from the survey design approaches generally used by NCHS, including possible biases from different response patterns and sampling frames as well as increased variability from lower sample sizes. Use of the RANDS platform allows NCHS to produce more timely data than would be possible using traditional data collection methods. RANDS is not designed to replace NCHS’ higher quality, core data collections. Below are experimental estimates of loss of work due to illness with coronavirus for three rounds of RANDS during COVID-19. Data collection for the three rounds of RANDS during COVID-19 occurred between June 9, 2020 and July 6, 2020, August 3, 2020 and August 20, 2020, and May 17, 2021 and June 30, 2021. Information needed to interpret these estimates can be found in the Technical Notes. RANDS during COVID-19 included a question about the inability to work due to being sick or having a family member sick with COVID-19. The National Health Interview Survey, conducted by NCHS, is the source for high-quality data to monitor work-loss days and work limitations in the United States. For example, in 2018, 42.7% of adults aged 18 and over missed at least 1 day of work in the previous year due to illness or injury and 9.3% of adults aged 18 to 69 were limited in their ability to work or unable to work due to physical, mental, or emotional problems. The experimental estimates on this page are derived from RANDS during COVID-19 and show the percentage of U.S. adults who did not work for pay at a job or business, at any point, in the previous week because either they or someone in their family was sick with COVID-19. Technical Notes: https://www.cdc.gov/nchs/covid19/rands/work.htm#limitations

--- Original source retains full ownership of the source dataset ---

The Research and Development Survey (RANDS) is a platform designed for conducting survey question evaluation and statistical research. RANDS is an ongoing series of surveys from probability-sampled commercial survey panels used for methodological research at the National Center for Health Statistics (NCHS). RANDS estimates are generated using an experimental approach that differs from the survey design approaches generally used by NCHS, including possible biases from different response patterns and sampling frames as well as increased variability from lower sample sizes. Use of the RANDS platform allows NCHS to produce more timely data than would be possible using traditional data collection methods. RANDS is not designed to replace NCHS’ higher quality, core data collections. Below are experimental estimates of telemedicine access and use for three rounds of RANDS during COVID-19. Data collection for the three rounds of RANDS during COVID-19 occurred between June 9, 2020 and July 6, 2020, August 3, 2020 and August 20, 2020, and May 17, 2021 and June 30, 2021. Information needed to interpret these estimates can be found in the Technical Notes. RANDS during COVID-19 included questions about whether providers offered telemedicine (including video and telephone appointments) in the last 2 months—both during and before the pandemic—and about the use of telemedicine in the last 2 months during the pandemic. As a result of the coronavirus pandemic, many local and state governments discouraged people from leaving their homes for nonessential reasons. Although health care is considered an essential activity, telemedicine offers an opportunity for care without the potential or perceived risks of leaving the home. The National Health Interview Survey, conducted by NCHS, added telemedicine questions to its sample adult questionnaire in July 2020. The Household Pulse Survey (https://www.cdc.gov/nchs/covid19/pulse/telemedicine-use.htm), an online survey conducted in response to the COVID-19 pandemic by the Census Bureau in partnership with other federal agencies including NCHS, also reports estimates of telemedicine use during the pandemic (beginning in Phase 3.1, which started on April 14, 2021). The Household Pulse Survey reports telemedicine use in the last 4 weeks among adults and among households with at least one child under age 18 years. The experimental estimates on this page are derived from RANDS during COVID-19 and show the percentage of U.S. adults who have a usual place of care and a provider that offered telemedicine in the past 2 months, who used telemedicine in the past 2 months, or who have a usual place of care and a provider that offered telemedicine prior to the coronavirus pandemic. Technical Notes: https://www.cdc.gov/nchs/covid19/rands/telemedicine.htm#limitations

Analysis of ‘Access and Use of Telemedicine During COVID-19’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/62ae3836-5b7b-4d97-b8e7-7e853aa39df0 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

The Research and Development Survey (RANDS) is a platform designed for conducting survey question evaluation and statistical research. RANDS is an ongoing series of surveys from probability-sampled commercial survey panels used for methodological research at the National Center for Health Statistics (NCHS). RANDS estimates are generated using an experimental approach that differs from the survey design approaches generally used by NCHS, including possible biases from different response patterns and sampling frames as well as increased variability from lower sample sizes. Use of the RANDS platform allows NCHS to produce more timely data than would be possible using traditional data collection methods. RANDS is not designed to replace NCHS’ higher quality, core data collections. Below are experimental estimates of telemedicine access and use for three rounds of RANDS during COVID-19. Data collection for the three rounds of RANDS during COVID-19 occurred between June 9, 2020 and July 6, 2020, August 3, 2020 and August 20, 2020, and May 17, 2021 and June 30, 2021. Information needed to interpret these estimates can be found in the Technical Notes. RANDS during COVID-19 included questions about whether providers offered telemedicine (including video and telephone appointments) in the last 2 months—both during and before the pandemic—and about the use of telemedicine in the last 2 months during the pandemic. As a result of the coronavirus pandemic, many local and state governments discouraged people from leaving their homes for nonessential reasons. Although health care is considered an essential activity, telemedicine offers an opportunity for care without the potential or perceived risks of leaving the home. The National Health Interview Survey, conducted by NCHS, added telemedicine questions to its sample adult questionnaire in July 2020. The Household Pulse Survey (https://www.cdc.gov/nchs/covid19/pulse/telemedicine-use.htm), an online survey conducted in response to the COVID-19 pandemic by the Census Bureau in partnership with other federal agencies including NCHS, also reports estimates of telemedicine use during the pandemic (beginning in Phase 3.1, which started on April 14, 2021). The Household Pulse Survey reports telemedicine use in the last 4 weeks among adults and among households with at least one child under age 18 years. The experimental estimates on this page are derived from RANDS during COVID-19 and show the percentage of U.S. adults who have a usual place of care and a provider that offered telemedicine in the past 2 months, who used telemedicine in the past 2 months, or who have a usual place of care and a provider that offered telemedicine prior to the coronavirus pandemic. Technical Notes: https://www.cdc.gov/nchs/covid19/rands/telemedicine.htm#limitations

--- Original source retains full ownership of the source dataset ---

The Research and Development Survey (RANDS) is a platform designed for conducting survey question evaluation and statistical research. RANDS is an ongoing series of surveys from probability-sampled commercial survey panels used for methodological research at the National Center for Health Statistics (NCHS). RANDS estimates are generated using an experimental approach that differs from the survey design approaches generally used by NCHS, including possible biases from different response patterns and sampling frames as well as increased variability from lower sample sizes. Use of the RANDS platform allows NCHS to produce more timely data than would be possible using traditional data collection methods. RANDS is not designed to replace NCHS’ higher quality, core data collections. Below are experimental estimates of loss of work due to illness with coronavirus for three rounds of RANDS during COVID-19. Data collection for the three rounds of RANDS during COVID-19 occurred between June 9, 2020 and July 6, 2020, August 3, 2020 and August 20, 2020, and May 17, 2021 and June 30, 2021. Information needed to interpret these estimates can be found in the Technical Notes. RANDS during COVID-19 included a question about the inability to work due to being sick or having a family member sick with COVID-19. The National Health Interview Survey, conducted by NCHS, is the source for high-quality data to monitor work-loss days and work limitations in the United States. For example, in 2018, 42.7% of adults aged 18 and over missed at least 1 day of work in the previous year due to illness or injury and 9.3% of adults aged 18 to 69 were limited in their ability to work or unable to work due to physical, mental, or emotional problems. The experimental estimates on this page are derived from RANDS during COVID-19 and show the percentage of U.S. adults who did not work for pay at a job or business, at any point, in the previous week because either they or someone in their family was sick with COVID-19. Technical Notes: https://www.cdc.gov/nchs/covid19/rands/work.htm#limitations

The Research and Development Survey (RANDS) is a platform designed for conducting survey question evaluation and statistical research. RANDS is an ongoing series of surveys from probability-sampled commercial survey panels used for methodological research at the National Center for Health Statistics (NCHS). RANDS estimates are generated using an experimental approach that differs from the survey design approaches generally used by NCHS, including possible biases from different response patterns and sampling frames as well as increased variability from lower sample sizes. Use of the RANDS platform allows NCHS to produce more timely data than would be possible using traditional data collection methods. RANDS is not designed to replace NCHS’ higher quality, core data collections. Below are experimental estimates of reduced access to healthcare for three rounds of RANDS during COVID-19. Data collection for the three rounds of RANDS during COVID-19 occurred between June 9, 2020 and July 6, 2020, August 3, 2020 and August 20, 2020, and May 17, 2021 and June 30, 2021. Information needed to interpret these estimates can be found in the Technical Notes. RANDS during COVID-19 included questions about unmet care in the last 2 months during the coronavirus pandemic. Unmet needs for health care are often the result of cost-related barriers. The National Health Interview Survey, conducted by NCHS, is the source for high-quality data to monitor cost-related health care access problems in the United States. For example, in 2018, 7.3% of persons of all ages reported delaying medical care due to cost and 4.8% reported needing medical care but not getting it due to cost in the past year. However, cost is not the only reason someone might delay or not receive needed medical care. As a result of the coronavirus pandemic, people also may not get needed medical care due to cancelled appointments, cutbacks in transportation options, fear of going to the emergency room, or an altruistic desire to not be a burden on the health care system, among other reasons. The Household Pulse Survey (https://www.cdc.gov/nchs/covid19/pulse/reduced-access-to-care.htm), an online survey conducted in response to the COVID-19 pandemic by the Census Bureau in partnership with other federal agencies including NCHS, also reports estimates of reduced access to care during the pandemic (beginning in Phase 1, which started on April 23, 2020). The Household Pulse Survey reports the percentage of adults who delayed medical care in the last 4 weeks or who needed medical care at any time in the last 4 weeks for something other than coronavirus but did not get it because of the pandemic. The experimental estimates on this page are derived from RANDS during COVID-19 and show the percentage of U.S. adults who were unable to receive medical care (including urgent care, surgery, screening tests, ongoing treatment, regular checkups, prescriptions, dental care, vision care, and hearing care) in the last 2 months. Technical Notes: https://www.cdc.gov/nchs/covid19/rands/reduced-access-to-care.htm#limitations

The Research and Development Survey (RANDS) is a platform designed for conducting survey question evaluation and statistical research. RANDS is an ongoing series of surveys from probability-sampled commercial survey panels used for methodological research at the National Center for Health Statistics (NCHS). RANDS estimates are generated using an experimental approach that differs from the survey design approaches generally used by NCHS, including possible biases from different response patterns and sampling frames as well as increased variability from lower sample sizes. Use of the RANDS platform allows NCHS to produce more timely data than would be possible using traditional data collection methods. RANDS is not designed to replace NCHS’ higher quality, core data collections. Below are experimental estimates of loss of work due to illness with coronavirus for three rounds of RANDS during COVID-19. Data collection for the three rounds of RANDS during COVID-19 occurred between June 9, 2020 and July 6, 2020, August 3, 2020 and August 20, 2020, and May 17, 2021 and June 30, 2021. Information needed to interpret these estimates can be found in the Technical Notes. RANDS during COVID-19 included a question about the inability to work due to being sick or having a family member sick with COVID-19. The National Health Interview Survey, conducted by NCHS, is the source for high-quality data to monitor work-loss days and work limitations in the United States. For example, in 2018, 42.7% of adults aged 18 and over missed at least 1 day of work in the previous year due to illness or injury and 9.3% of adults aged 18 to 69 were limited in their ability to work or unable to work due to physical, mental, or emotional problems. The experimental estimates on this page are derived from RANDS during COVID-19 and show the percentage of U.S. adults who did not work for pay at a job or business, at any point, in the previous week because either they or someone in their family was sick with COVID-19. Technical Notes: https://www.cdc.gov/nchs/covid19/rands/work.htm#limitations

Abstract

The National Family Health Survey 2019-21 (NFHS-5), the fifth in the NFHS series, provides information on population, health, and nutrition for India, each state/union territory (UT), and for 707 districts.

The primary objective of the 2019-21 round of National Family Health Surveys is to provide essential data on health and family welfare, as well as data on emerging issues in these areas, such as levels of fertility, infant and child mortality, maternal and child health, and other health and family welfare indicators by background characteristics at the national and state levels. Similar to NFHS-4, NFHS-5 also provides information on several emerging issues including perinatal mortality, high-risk sexual behaviour, safe injections, tuberculosis, noncommunicable diseases, and the use of emergency contraception.

The information collected through NFHS-5 is intended to assist policymakers and programme managers in setting benchmarks and examining progress over time in India’s health sector. Besides providing evidence on the effectiveness of ongoing programmes, NFHS-5 data will help to identify the need for new programmes in specific health areas.

The clinical, anthropometric, and biochemical (CAB) component of NFHS-5 is designed to provide vital estimates of the prevalence of malnutrition, anaemia, hypertension, high blood glucose levels, and waist and hip circumference, Vitamin D3, HbA1c, and malaria parasites through a series of biomarker tests and measurements.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15 to 54

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-54, and all children aged 0-5 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

A uniform sample design, which is representative at the national, state/union territory, and district level, was adopted in each round of the survey. Each district is stratified into urban and rural areas. Each rural stratum is sub-stratified into smaller substrata which are created considering the village population and the percentage of the population belonging to scheduled castes and scheduled tribes (SC/ST). Within each explicit rural sampling stratum, a sample of villages was selected as Primary Sampling Units (PSUs); before the PSU selection, PSUs were sorted according to the literacy rate of women age 6+ years. Within each urban sampling stratum, a sample of Census Enumeration Blocks (CEBs) was selected as PSUs. Before the PSU selection, PSUs were sorted according to the percentage of SC/ST population. In the second stage of selection, a fixed number of 22 households per cluster was selected with an equal probability systematic selection from a newly created list of households in the selected PSUs. The list of households was created as a result of the mapping and household listing operation conducted in each selected PSU before the household selection in the second stage. In all, 30,456 Primary Sampling Units (PSUs) were selected across the country in NFHS-5 drawn from 707 districts as on March 31st 2017, of which fieldwork was completed in 30,198 PSUs.

For further details on sample design, see Section 1.2 of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four survey schedules/questionnaires: Household, Woman, Man, and Biomarker were canvassed in 18 local languages using Computer Assisted Personal Interviewing (CAPI).

Cleaning operations

Electronic data collected in the 2019-21 National Family Health Survey were received on a daily basis via the SyncCloud system at the International Institute for Population Sciences, where the data were stored on a password-protected computer. Secondary editing of the data, which required resolution of computer-identified inconsistencies and coding of open-ended questions, was conducted in the field by the Field Agencies and at the Field Agencies central office, and IIPS checked the secondary edits before the dataset was finalized.

Field-check tables were produced by IIPS and the Field Agencies on a regular basis to identify certain types of errors that might have occurred in eliciting information and recording question responses. Information from the field-check tables on the performance of each fieldwork team and individual investigator was promptly shared with the Field Agencies during the fieldwork so that the performance of the teams could be improved, if required.

Response rate

A total of 664,972 households were selected for the sample, of which 653,144 were occupied. Among the occupied households, 636,699 were successfully interviewed, for a response rate of 98 percent.

In the interviewed households, 747,176 eligible women age 15-49 were identified for individual women’s interviews. Interviews were completed with 724,115 women, for a response rate of 97 percent. In all, there were 111,179 eligible men age 15-54 in households selected for the state module. Interviews were completed with 101,839 men, for a response rate of 92 percent.

The Research and Development Survey (RANDS) is a platform designed for conducting survey question evaluation and statistical research. RANDS is an ongoing series of surveys from probability-sampled commercial survey panels used for methodological research at the National Center for Health Statistics (NCHS). RANDS estimates are generated using an experimental approach that differs from the survey design approaches generally used by NCHS, including possible biases from different response patterns and sampling frames as well as increased variability from lower sample sizes. Use of the RANDS platform allows NCHS to produce more timely data than would be possible using traditional data collection methods. RANDS is not designed to replace NCHS’ higher quality, core data collections. Below are experimental estimates of reduced access to healthcare for three rounds of RANDS during COVID-19. Data collection for the three rounds of RANDS during COVID-19 occurred between June 9, 2020 and July 6, 2020, August 3, 2020 and August 20, 2020, and May 17, 2021 and June 30, 2021. Information needed to interpret these estimates can be found in the Technical Notes. RANDS during COVID-19 included questions about unmet care in the last 2 months during the coronavirus pandemic. Unmet needs for health care are often the result of cost-related barriers. The National Health Interview Survey, conducted by NCHS, is the source for high-quality data to monitor cost-related health care access problems in the United States. For example, in 2018, 7.3% of persons of all ages reported delaying medical care due to cost and 4.8% reported needing medical care but not getting it due to cost in the past year. However, cost is not the only reason someone might delay or not receive needed medical care. As a result of the coronavirus pandemic, people also may not get needed medical care due to cancelled appointments, cutbacks in transportation options, fear of going to the emergency room, or an altruistic desire to not be a burden on the health care system, among other reasons. The Household Pulse Survey (https://www.cdc.gov/nchs/covid19/pulse/reduced-access-to-care.htm), an online survey conducted in response to the COVID-19 pandemic by the Census Bureau in partnership with other federal agencies including NCHS, also reports estimates of reduced access to care during the pandemic (beginning in Phase 1, which started on April 23, 2020). The Household Pulse Survey reports the percentage of adults who delayed medical care in the last 4 weeks or who needed medical care at any time in the last 4 weeks for something other than coronavirus but did not get it because of the pandemic. The experimental estimates on this page are derived from RANDS during COVID-19 and show the percentage of U.S. adults who were unable to receive medical care (including urgent care, surgery, screening tests, ongoing treatment, regular checkups, prescriptions, dental care, vision care, and hearing care) in the last 2 months. Technical Notes: https://www.cdc.gov/nchs/covid19/rands/reduced-access-to-care.htm#limitations

Browse the English in-person and web interview questionnaires for the 2021 National Survey on Drug Use and Health (NSDUH). The documents provide the exact questions given to respondents in their full context, along with the skip patterns that determined whether a person was asked a question or not. There is also information on which sections were interviewer administered when conducted in-person, and a section that summarizes changes made to the questionnaire for 2021.

Abstract

The 2021-22 Cambodia Demographic and Health Survey (2021-22 CDHS) was implemented by the National Institute of Statistics (NIS) in collaboration with the Ministry of Health (MoH). Data collection took place from September 15, 2021, to February 15, 2022.

The primary objective of the 2021-22 CDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the survey collected information on fertility, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and children, maternal and child health, adult and childhood mortality, women’s empowerment, domestic violence, awareness and behavior regarding HIV/AIDS and other sexually transmitted infections (STIs), and other health-related issues such as smoking.

The information collected through the 2021-22 CDHS is intended to assist policymakers and program managers in evaluating and designing programs and strategies for improving the health of Cambodia’s population. The survey also provides data on indicators relevant to the Sustainable Development Goals (SDGs) for Cambodia.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15 to 49

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-49, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four questionnaires were used in the 2021-22 CDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Cambodia. In addition, a self-administered Fieldworker Questionnaire collected information about the survey’s fieldworkers.

Cleaning operations

The processing of the 2021-22 CDHS data began as soon as the fieldwork started. When data collection was completed in each cluster, the electronic data files were transferred via the IFSS to the NIS central office in Phnom Penh. The data files were registered and checked for inconsistencies, incompleteness, and outliers. Errors and inconsistencies were communicated to the field teams for review and correction. Secondary editing, done by NIS data processors, was carried out in the central office and included resolving inconsistencies and coding open-ended questions. The paper Biomarker Questionnaires were collected by field coordinators and then compared with the electronic data files to assess whether any inconsistencies arose during data entry. Data processing and editing were carried out using the CSPro software package. The concurrent data collection and processing offered an advantage because it maximized the likelihood of the data being error-free. Timely generation of field check tables allowed for effective monitoring. The secondary editing of the data was completed in March 2022.

Response rate

A total of 21,270 households were selected for the CDHS sample, of which 20,967 were found to be occupied. Of the occupied households, 20,806 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 19,845 women age 15-49 were identified as eligible for individual interviews. Interviews were completed with 19,496 women, yielding a response rate of 98%. In the subsample of households selected for the male survey, 9,079 men age 15-49 were identified as eligible for individual interviews and 8,825 were successfully interviewed, yielding a response rate of 97%.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are errors that were made during data collection and data processing such as failure to locate and interview the correct household, misunderstanding of the questions by either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2021-22 Cambodia Demographic and Health Survey (CDHS) to minimize this type of error, nonsampling errors are impossible to eliminate completely and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2021-22 CDHS is only one of many possible samples that could have been selected from the same population, using exactly the same design. Each of those samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2021-22 CDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2021-22 CDHS was an SAS program. This program used the Taylor linearization method for estimate variances for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables

• Household age distribution
• Age distribution of eligible and interviewed women
• Age distribution of eligible and interviewed men
• Age displacement at age 14/15
• Age displacement at age 49/50
• Pregnancy outcomes by years preceding the survey
• Completeness of reporting
• Height and weight data completeness and quality for children
• Height measurements from random subsample of measured children
• Interference in height and weight measurements of children
• Interference in height and weight measurements of women
• Heaping in anthropometric measurements for children (digit preference)
• Observation of handwashing facility
• School attendance by single-year age
• Vaccination cards photographed
• Number of enumeration areas completed by month and province
• Sibship size and sex ratio of siblings
• Pregnancy-related mortality trends
• Pregnancy-related mortality

See details of the data quality tables in Appendix C of the final report.

IntroductionEmerging evidence suggests that a COVID-19 infection with a high initial severity may be associated with development of long-COVID conditions such as chronic pain. At the population level, it is unknown if severity of a COVID-19 infection might be a new risk factor for chronic pain above and beyond the traditional slate of pre-established risk factors. The purpose of this study is to examine whether COVID-19 severity of infection may be a new risk factor for chronic pain.MethodsUsing data from the 2021 National Health Interview Survey (n = 15,335), this study examined the adjusted odds of experiencing high frequency levels of pain in the past 3 months for those who reported no/mild symptoms from a COVID-19 infection, and those reporting moderate/severe symptoms from COVID-19, compared to those never infected. A 1:1:1 propensity score matched analysis was also performed to examine the odds of pain.ResultsPrevalence of pain was higher in the moderate/severe symptom group compared to the no infection group (25.48% vs 19.44%, p