The National Health Interview Survey (NHIS) is the principal source of information on the health of the civilian noninstitutionalized population of the United States and is one of the major data collection programs of the National Center for Health Statistics (NCHS) which is part of the Centers for Disease Control and Prevention (CDC). The National Health Survey Act of 1956 provided for a continuing survey and special studies to secure accurate and current statistical information on the amount, distribution, and effects of illness and disability in the United States and the services rendered for or because of such conditions. The survey referred to in the Act, now called the National Health Interview Survey, was initiated in July 1957. Since 1960, the survey has been conducted by NCHS, which was formed when the National Health Survey and the National Vital Statistics Division were combined. NHIS data are used widely throughout the Department of Health and Human Services (DHHS) to monitor trends in illness and disability and to track progress toward achieving national health objectives. The data are also used by the public health research community for epidemiologic and policy analysis of such timely issues as characterizing those with various health problems, determining barriers to accessing and using appropriate health care, and evaluating Federal health programs. The NHIS also has a central role in the ongoing integration of household surveys in DHHS. The designs of two major DHHS national household surveys have been or are linked to the NHIS. The National Survey of Family Growth used the NHIS sampling frame in its first five cycles and the Medical Expenditure Panel Survey currently uses half of the NHIS sampling frame. Other linkage includes linking NHIS data to death certificates in the National Death Index (NDI). While the NHIS has been conducted continuously since 1957, the content of the survey has been updated about every 10-15 years. In 1996, a substantially revised NHIS questionnaire began field testing. This revised questionnaire, described in detail below, was implemented in 1997 and has improved the ability of the NHIS to provide important health information.

2019–present. The National Health Interview Survey (NHIS) is a nationally representative household health survey of the U.S. civilian noninstitutionalized population. The NHIS data are used to monitor trends in illness and disability, track progress toward achieving national health objectives, for epidemiologic and policy analysis of various health problems, determining barriers to accessing and using appropriate health care, and evaluating Federal health programs. NHIS is conducted continuously throughout the year by the National Center for Health Statistics (NCHS). Public-use data files on adults and children with corresponding imputed income data files, and survey paradata are released annually. The NHIS data website (https://www.cdc.gov/nchs/nhis/documentation/index.html) features the most up-to-date public-use data files and documentation for downloading including questionnaire, codebooks, CSV and ASCII data files, programs and sample code, and in-depth survey description. Most of the NHIS data are included in the public use files. NHIS is protected by Federal confidentiality laws that state the data collected by NCHS may be used only for statistical reporting and analysis. Some NHIS variables have been suppressed or edited in the public use files to protect confidentiality. Analysts interested in using data that has been suppressed or edited may apply for access through the NCHS Research Data Center at https://www.cdc.gov/rdc/. In 2019, NHIS launched a redesigned content and structure that differs from its previous questionnaire designs. NHIS has been conducted continuously since 1957.

The National Health Survey of Spain 2017 (ENSE 2017), carried out by the Ministry of Health, Consumption and Social Welfare with the collaboration of the National Institute of Statistics, collects health information related to the population residing in Spain in 23,860 households. It is a five-yearly survey that allows knowing numerous aspects of the health of citizens at a national and regional level, and planning and evaluating actions in health matters. It consists of 3 questionnaires, household, adult and minor, which address 4 large areas: sociodemographic, health status, use of health services and health determinants.

The purpose of the National Health Interview Survey (NHIS) is to obtain information about the amount and distribution of illness, its effects in terms of disability and chronic impairments, and the kinds of health services people receive. Implementation of a redesigned NHIS, consisting of a basic module, a periodic module, and a topical module, began in 1997 (see NATIONAL HEALTH INTERVIEW SURVEY, 1997 [ICPSR 2954]). The 2006 NHIS contains the Household, Family, Person, Sample Adult, and Sample Child files from the basic module. Each record in Part 1, Household Level, contains data on type of living quarters, number of families in the household responding and not responding, and the month and year of the interview for each sampling unit. Part 2, Family Level, is made up of reconstructed variables from the person-level data of the basic module and includes information on sex, age, race, marital status, Hispanic origin, education, veteran status, family income, family size, major activities, health status, activity limits, and employment status, along with industry and occupation. As part of the basic module, Part 3, Personl Level, provides information on all family members with respect to health status, limitation of daily activities, cognitive impairment, and health conditions. Also included are data on years at current residence, region variables, height, weight, bed days, doctor visits, hospital stays, and health care access and utilization. A randomly-selected adult in each family was interviewed for Part 4, Sample Adult, regarding respiratory conditions, use of nasal spray, renal conditions, AIDS, joint symptoms, health status, limitation of daily activities, and behaviors such as smoking, alcohol consumption, and physical activity in addition to questions regarding stroke, diabetes, arthritis, and weight control. Part 5, Sample Child, provides information from an adult in the household on medical conditions of one child in the household, such as respiratory problems, seizures, allergies, and use of special equipment like hearing aids, braces, or wheelchairs. Also included are variables regarding child behavior, the use of mental health services, and Attention Deficit Hyperactivity Disorder (ADHD), as well as responses to the SDQ, the Strengths and Difficulties questionnaire on child mental health. The 2006 data contain the Child Mental Health Brief (CMB), Child Mental Health Services (CMS) and Child Influenza Immunization (CFI) sections. Part 6, Injury/Poison Episode, is an episode-based file that contains information about the external cause and nature of the injury or poisoning episode and what the person was doing at the time of the injury or poisoning episode, in addition to the date and place of occurrence. Part 7, Injury/Poison Episode Verbatim, contains edited narrative text descriptions of the injury or poisoning, provided by the respondent. Imputed income files for 2006 are now available through the NCHS Web site . (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR -- https://doi.org/10.3886/ICPSR20681.v3. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.

The National Health and Nutrition Examination Survey (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. An ongoing annual survey combines interviews and physical examinations. The NHANES interview includes demographic, socioeconomic, dietary, and health-related questions. The examination component consists of medical, dental, and physiological measurements, as well as laboratory tests administered by highly trained medical personnel.

Ancillary studies include the NHANES National Youth Fitness Survey (NNYFS) and NHANES Epidemiologic Followup Study (NHEFS). NNYFS was conducted in 2012 to evaluate the physical activity and fitness of children aged 3 to 15 years old through interviews and fitness tests. NHEFS is a longitudinal survey of adults aged 25 to 74 years old in the NHANES I (1971-1975) cohort who completed a medical examination. Data was collected in follow-up rounds in 1982-1984, 1986, 1987, and 1992 through subject and proxy interviews and vital record search. Available data files include vital and tracing status, demographic information, interview data on health status, health care facility inpatient data, and mortality data.

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 Public Health Agency of Sweden annually conducts a national public health survey, Health on Equal Terms, including a sample of 20 000 people aged 16-84 years. The survey, which was conducted for the first time in 2004, is an on going collaboration between the The Public Health Agency of Sweden and county councils/regions in Sweden and is carried out with help from Statistics Sweden (SCB). All studies, since 2004, can be found under the tab Related studies.

The survey is voluntary and done with the purpose to investigate the health in the population and to show changes in the population's health over time as a follow up of the national health politics.

The sample is randomly drawn from the Statistics Sweden's population register and includes 20 000 people aged 16-84 years. The personal data is confidential and protected by law and those working with this survey are obliged to practice professional secrecy. Individual answers can not be identified in the results.

The study participants are since 2007 given the opportunity to answer the survey on the web. Since 2012, the web survey is also in English, and since 2014 also in Finnish.

The questionnaire includes about 85 questions. Each county council has its own introduction letter and the questions has been prepared in collaboration with representatives from a number of different community medicine units. The origin and quality of the questions are described in the report "Objective and background of the questions in the national public health survey". Most questions recur each year, but questions can in particular cases be replaced by other questions of good quality and national relevance.

The questions in the national public health survey cover physical and mental health, consumption of pharmaceuticals, contact with healthcare services, dental health, living habits, financial conditions, work and occupation, work environment, safety and social relationships. Data regarding education is collected from the education register, and data of income, economic support, sickness benefits and pensions from the income an taxation register.

Purpose:

The aim is to investigate the health in the population and to show changes in the population's health over time as a follow up of the national health politics.

The dataset consists of 20 variables and 6795 observations from 6795 respondents who were surveyed during the National Health and Nutrition Examination Survey 2009-2010 in order to assess the health and nutritional status of adults and children in the United States.

The purpose of this study was to collect extensive information on the sexual experiences and other social, demographic, attitudinal, and health-related characteristics of adults in the United States. The survey collected information on sexual practices with spouses/cohabitants and other sexual partners and collected background information about the partners. Major areas of investigation include sexual experiences such as number of sexual partners in given time periods, frequency of particular practices, and timing of various sexual events. The data cover childhood and adolescence, as well as adulthood. Other topics in the survey relate to sexual victimization, marriage and cohabitation, and fertility. Respondents were also queried about their physical health, including history of sexually transmitted diseases. Respondents' attitudes toward premarital sex, the appeal of particular practices such as oral sex, and levels of satisfaction with particular sexual relationships were also studied. Demographic items include race, education, political and religious affiliation, income, and occupation.

Abstract

The primary objective of the Cambodia National Health Survey is to provide the Ministry of Health with reliable, population-based, nationally representative data or infant/child mortality, fertility, and related health service indicators.

A secondary objective was to provide the ADB-financed Basic Helath Services Project (BHSP) and the World Bank finaced Cambodia Disease Control and Health Development Project (CDCP) with baseline information about their respective Project areas, against which project impact could later be assessed.

Geographic coverage

National coverage

Analysis unit

Household Women age 15-49 Children under age 5

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design and Selection The NHS sample was designed to provide estimates of kwy health indicators including infant/ child mortality rates and fertility rates for the country as a whole, for urban and rural residence, and for the two project catchment areas (the Basic Health Services Project and the Cambodia Disease Control and Health Development Project). In addition, the design allows for estimates of most key variables (but not for the vaccination coverage of children, fertility rates, or mortality rates) for 14 Provinces. In the other Provinces, the sample size is not sufficiently large to allow for province-level estimates. In order to provide sufficient cases to meet the survey objectives, the number of households selected in the NHS sample from each Province was disproportional to the size of the population in the Province. The above arrangements imply stratification into 40 strata, with 40 different sampling fractions. These strata are 20 Provinces, each divided into an urban and a rural sector. As a result, the NHS sample is self-weighting within strata; weights are only necessary when making estimates across more than one stratum.

For a more complete description of the NHS sample design, see Appendix A of the survey final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The NHS involved two types of questionnaires: a household questionnaire and an individual questionnaire. The household questionnaire was administered to all selected households; the individual questionnaire was administered to all women aged 15-49 identified in the household questionnaire as either usual residents of the household or visitors who stayed there on the night before the day of interview. These questionnaires were developed to measure the desired indicators identified by the MOH and Technical Steering Committee. Wording and structure of the questionnaires, where applicable, was based on the model survey instruments Macro International has used in similar surveys worldwide.

The household questionnaire consisted of three parts: 1) a household schedule giving demographic details of all usual household members and overnight visitors; 2) a series of questions relating to the utilization of health services for any household members who had been ill or injured in the past 30 days; and 3) questions about wall and roof materials of the home and household possessions, which in turn were used to compose a measure of overall household socio-economic status.

The individual questionnaire administered to women aged 15-49 gathered detailed information about the woman's reproductive history, and maternal and child health related knowledge and practices. Questions specific to child health practices were limited to children born after January 1993. (i.e., children under age 5)

The questionnaire was developed in English, translated into Khmer, then back translated and corrected. Following this, a three day pretest covering 100 households was conducted in Phnom Penh and rural Kandal Province by twenty interviewers after initial two week training. The questionnaires were finalized following the pretest.

Cleaning operations

Data Processing was conducted by NIPH with technical assistance form Macro International. The NIPH central office collected questionnaires form supervisors as soon as a cluster was completed. Office editors reviewed questionnaires for consistency and completeness. The data from the questionnaires were then entered and edited on microcomputers using the Integrated System for Survey Analysis (ISSA), a software package developed especially for such surveys by Macro International. During the machine entry, all questionnaires were reentered for verification. Entry and editing of data began one week after the fieldwork started and was completed by the beginning of August 1998. To provide feedback for the field teams, quality tables were produced every two weeks during the fieldwork. These tables were designed to identify major systematic errors in data collection (e.g. age displacement). The fieldwork coordinators reviewed these tables and, if they found a problem, notified and advised all teams of the steps to be taken to avoid this problem in the future.

Response rate

A total of 7,654 women were identified as eligible to be interviewed. Questionnaires were completed for 7,630 of those women, a response rate of 99.7 precent. There is a little difference between the household and individual response rates in urban and rural areas. The same is true for the two project areas.

Sampling error estimates

The estimate from a sample survey is affected by two types of errors: 1) nonsampling errors, and 2) sampling errors. Nonsampling errors are the results of mistake made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the National Health Survey (NHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling error, on the other hand, can be evaluated statistically. The sample of respondents selected in the NHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these 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 nor 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 reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistics will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible sample 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 NHS sample is the result of a multi-stage stratified design and consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the NHS is the ISSA Sampling Error Module. This module used the Taylor linearization method of variance estimation for survey estimates that are means of proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

For details of sampling error estimations information see Appendix B of the final survey report.

Data appraisal

Data Quality Tables - Household age distribution - Births by calendar year - Reporting of age at death in days - Reporting of age at death in months

Note: See detailed tables in APPENDIX C of the survey report.

analyze the national health interview survey (nhis) with r the national health interview survey (nhis) is a household survey about health status and utilization. each annual data set can be used to examine the disease burden and access to care that individuals and families are currently experiencing across the country. check out the wikipedia article (ohh hayy i wrote that) for more detail about its current and potential uses. if you're cooking up a health-related analysis that doesn't need medical expenditures or monthly health insurance coverage, look at nhis before the medical expenditure panel survey (it's sample is twice as big). the centers for disease control and prevention (cdc) has been keeping nhis real since 1957, and the scripts below automate the download, importation, and analysis of every file back to 1963. what happened in 1997, you ask? scientists cloned dolly the sheep, clinton started his second term, and the national health interview survey underwent its most recent major questionnaire re-design. here's how all the moving parts work: a person-level file (personsx) that merges onto other files using unique household (hhx), family (fmx), and person (fpx) identifiers. [note to data historians: prior to 2004, person number was (px) and unique within each household.] this file includes the complex sample survey variables needed to construct a taylor-series linearization design, and should be used if your analysis doesn't require variables from the sample adult or sample c hild files. this survey setup generalizes to the noninstitutional, non-active duty military population. a family-level file that merges onto other files using unique household (hhx) and family (fmx) identifiers. a household-level file that merges onto other files using the unique household (hhx) identifier. a sample adult file that includes questions asked of only one adult within each household (selected at random) - a subset of the main person-level file. hhx, fmx, and fpx identifiers will merge with each of the files above, but since not every adult gets asked thes e questions, this file contains its own set of weights: wtfa_sa instead of wtfa. you can merge on whatever other variables you need from the three files above, but if your analysis requires any variables from the sample adult questionnaire, you can't use records in the person-level file that aren't also in the sample adult file (a big sample size cut). this survey setup generalizes to the noninstitutional, non-active duty military adult population. a sample child file that includes questions asked of only one child within each household (if available, and also selected at random) - another subset of the main person-level file. same deal as the sample adult description, except use wtfa_sc instead of wtfa oh yeah and this one generalizes to the child population. five imputed income files. if you want income and/or poverty variables incorporated into any part of your analysis, you'll need these puppies. the replication example below uses these, but if that's impenetrable, post in the comments describing where you get stuck. some injury stuff and other miscellanea that varies by year. if anyone uses this, please share your experience. if you use anything more than the personsx file alone, you'll need to merge some tables together. make sure you understand the difference between setting the parameter all = TRUE versus all = FALSE -- not everyone in the personsx file has a record in the samadult and sam child files. this new github repository contains four scripts: 1963-2011 - download all microdata.R loop through every year and download every file hosted on the cdc's nhis ftp site import each file into r with SAScii save each file as an r d ata file (.rda) download all the documentation into the year-specific directory 2011 personsx - analyze.R load the r data file (.rda) created by the download script (above) set up a taylor-series linearization survey design outlined on page 6 of this survey document perform a smattering of analysis examples 2011 personsx plus samadult with multiple imputation - analyze.R load the personsx and samadult r data files (.rda) created by the download script (above) merge the personsx and samadult files, highlighting how to conduct analyses that need both create tandem survey designs for both personsx-only and merg ed personsx-samadult files perform just a touch of analysis examples load and loop through the five imputed income files, tack them onto the personsx-samadult file conduct a poverty recode or two analyze the multiply-imputed survey design object, just like mom used to analyze replicate cdc tecdoc - 2000 multiple imputation.R download and import the nhis 2000 personsx and imputed income files, using SAScii and this imputed income sas importation script (no longer hosted on the cdc's nhis ftp site). loop through each of the five imputed income files, merging each to the personsx file and performing the same set of...

The Australian National Health Survey (NHS), conducted every three years by the Australian Bureau of Statistics (ABS), provides a nationally representative profile of Australians' health and wellbeing. The 2017-18 survey collected self-reported data on health, demographics, and lifestyle factors from both adults and children, offering valuable insights into the nation's health status and behaviors through a comprehensive sampling design.

Abstract

Objectives: To provide a broad set of information about health characteristics of population necessary for the formulation, monitoring and evaluation of policies related to health sector.

Reference Period: Month

Periodicity of Data Collection: Every 5 years

Geographic coverage

Whole country

Analysis unit

Individuals

Universe

Population groups: Persons who are members of households

Total population covered: It is a sample survey covering 80,000 households throughout Brazil or 0,11% of the total population

Economic activities: Na

Sectors covered: All sectors

Labor force status: Employed persons, unemployed persons, persons outside labour force

Status in Employment: Employees, employers, own-account workers, contributing family workers

Establishments: No (National Health Survey only collects data in households)

Other limitations: According to the methodology, employment data is collected only for people aged 14 years and over

Classifications: Sex, age, level of education, type of living arrangements, status in employment, occupation, economic activity, type of disability

Cross-classification: Disability variable can be cross-classified by all variables

Kind of data

Sample survey data [ssd]

Frequency of data collection

Periodicity of Data collection: Every 5 years

The purpose of the Health Interview Survey is to obtain information about the amount and distribution of illness, its effects in terms of disability and chronic impairments, and the kinds of health services people receive. There are five types of records in this core survey, each in a separate data file. The Person File (Part 1) includes information on sex, age, race, marital status, Hispanic origin, education, veteran status, family income, family size, major activities, health status, activity limits, employment status, and industry and occupation. These variables are found in the Conditions, Doctor Visits, and Hospital Episodes Files as well. The Person File also supplies data on height, weight, bed days, doctor visits, hospital stays, years at residence, and region variables. The variables in the Household File (Part 2) include type of living quarters, size of family, number of families in the household, presence of a telephone, number of unrelated individuals, and region. The Conditions File (Part 3) contains information for each reported health condition, with specifics on injury and accident reports. The Hospital Episodes File (Part 4) provides information on medical conditions, hospital episodes, type of service, type of hospital ownership, date of admission and discharge, number of nights in hospital, and operations performed. The Doctor Visits File (Part 5) documents doctor visits within the time period and identifies acute or chronic conditions. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR -- https://doi.org/10.3886/ICPSR08338.v3. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.

European Public Health Survey

These data are the part of the two National Health Surveys in the Republic of Serbia, conducted in 2006 and 2013, funded by the Ministry of Health. The survey was conducted in accordance with the methodology and instruments of the European Health Interview Survey wave 2. Both surveys were conducted as cross sectional studies. Population presented in the research included adults, aged 19 and more. The researches excluded people living on the territory of Kosovo and Metohija, as well as people with residence addresses in Special institutions (retirement homes, prisons, psychiatric clinics). Data on basic characteristics of the interviewees, health condition of the interviewees, using hospital and non-hospital health care services and prevention check-ups and unachieved need for health care was obtained through a face-to-face interview carried out at home, while information at the level of the household was obtained by means of a household questionnaire. The questions were validated instruments based on the standard questionnaires from similar types of surveys.

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

Data from the Integrated Health Interview Survey. These data are archived to facilitate replication of Abowd and Schmutte (2017) "Revisiting the Economics of Privacy."http://digitalcommons.ilr.cornell.edu/ldi/22/

The purpose of the National Health Interview Survey (NHIS) is to obtain information about the amount and distribution of illness, its effects in terms of disability and chronic impairments, and the kinds of health services people receive. The variables in the Household Record file (Part 1) include type of living quarters, size of family, number of families in the household, presence of a telephone, number of unrelated individuals, and region. The Person Record file (Part 2) includes information on sex, age, race, marital status, Hispanic origin, education, veteran status, family income, family size, major activities, health status, activity limits, employment status, and industry and occupation. These variables are found in the Condition, Doctor Visit, and Hospital Record files as well. The Person Record also supplies data on height, weight, bed days, doctor visits, hospital stays, years at residence, and region variables. The Condition Record file (Part 3) contains information for each reported health condition, with specifics on injury and accident reports. The Doctor Visit Record file (Part 4) documents doctor visits within the time period and identifies acute or chronic conditions. The Hospital Record file (Part 5) provides information on medical conditions, hospital episodes, type of service, type of hospital ownership, date of admission and discharge, number of nights in hospital, and operations performed. (Source: downloaded from ICPSR 7/13/10)

• to provide annual data about the nation’s health;
• to estimate the proportion of people in England with specified health conditions;
• to estimate the prevalence of certain risk factors associated with these conditions;
• to examine differences between population subgroups in their likelihood of having specific conditions or risk factors;
• to assess the frequency with which particular combinations of risk factors are found, and which groups these combinations most commonly occur;
• to monitor progress towards selected health targets
• since 1995, to measure the height of children at different ages, replacing the National Study of Health and Growth;
• since 1995, monitor the prevalence of overweight and obesity in children.

The survey includes a number of core questions every year but also focuses on different health issues at each wave. Topics are revisited at appropriate intervals in order to monitor change.

Further information about the series may be found on the NHS Digital Health Survey for England; health, social care and lifestyles webpage, the NatCen Social Research NatCen Health Survey for England webpage and the University College London Health and Social Surveys Research Group UCL Health Survey for England webpage.

Changes to the HSE from 2015:
Users should note that from 2015 survey onwards, only the individual data file is available under standard End User Licence (EUL). The household data file is now only included in the Special Licence (SL) version, released from 2015 onwards. In addition, the SL individual file contains all the variables included in the HSE EUL dataset, plus others, including variables removed from the EUL version after the NHS Digital disclosure review. The SL HSE is subject to more restrictive access conditions than the EUL version (see Access information). Users are advised to obtain the EUL version to see if it meets their needs before considering an application for the SL version.

COVID-19 and the HSE:
Due to the COVID-19 pandemic, the HSE 2020 survey was stopped in March 2020 and never re-started. There was no publication that year. The survey resumed in 2021, albeit with an amended methodology. The full HSE resumed in 2022, with an extended fieldwork period. Due to this, the decision was taken not to progress with the 2023 survey, to maximise the 2022 survey response and enable more robust reporting of data. See the NHS Digital Health Survey for England - Health, social care and lifestyles webpage for more details.

The HSE 2007 was designed to provide data at both national and regional level about the population living in private households in England. The sample comprised two components; the core (general population) sample and a boost sample of children aged 2-15. The core sample was designed to be representative of the population living in private households in England and should be used for analyses at the national level.

For the HSE core sample, all adults aged 16 years or older at each household were selected for the interview (up to a maximum of ten adults). However, a limit of two was placed on the number of interviews carried out with children aged 0-15. For households with three or more children, interviewers selected two children at random. At boost addresses interviewers screened for households containing at least one child aged 2-15 years. For households which included eligible children, up to two were selected by the interviewer for inclusion in the survey. Interviewing was conducted throughout the year to take account of seasonal differences.

For the second edition (April 2010), three new children's Body Mass Index (BMI) variables have been added to the individual data file (bmicat1, bmicat2, bmicat3). The original variables (bmicut1, bmicut2, bmicut3) are unreliable and should not be used. Further information is available in the documentation and on the Information Centre for Health and Social Care Health Survey for England web page.