The New York City Community Health Survey (CHS) is a telephone survey conducted annually by the DOHMH, Division of Epidemiology, Bureau of Epidemiology Services. CHS provides robust data on the health of New Yorkers, including neighborhood, borough, and citywide estimates on a broad range of chronic diseases and behavioral risk factors. The data are analyzed and disseminated to influence health program decisions, and increase the understanding of the relationship between health behavior and health status. For more information see EpiQuery, https://a816-health.nyc.gov/hdi/epiquery/visualizations?PageType=ps&PopulationSource=CHS

The dataset contains state-wise National Family Health Survey (NFHS) compiled data on various family planning, childbirth, population, medical, health and other parameters which provide statistical indicators data on family profile and health status in India. There are 100+ indicators covered in the survey which broadly fall in the following categories: Health and Wellness, Maternal and Child Health, Family Planning and Reproductive Health, Disease Screening and Prevention, Social and Economic Factors, General Healthcare and Treatment

The different types of health data contained in the dataset include Anaemia among women and children, blood sugar levels and hypertension among men and women, tobacco and alcohol consumption among adults, delivery care and child feeding practices of women, quality of family planning services, screening of cancer among women, marriage and family, maternity care, nutritional status of women, child vaccinations and vitamin A supplementation, treatment of childhood diseases, etc.

Within these categories of health data, the dataset contains indicators data such as births attended by skilled health care professionals and caesarean section, number of children with under and heavy weight, stunted growth, their different vaccations status, male and female sterilization, consumption of iron folic acid among mothers, mother who had antenatal, postnatal, neonatal services, women who are obese and at the risk of weight to hip ratio, educational status among women and children, sanitation, birth and sex ratio, etc.

All of the data is compiled from the NFHS 4th and 5th survey reports. The The NFHS is a collaborative project of the International Institute for Population Sciences(IIPS), aimed at providing health data to strengthen India's health policies and programmes.

There are 100+ indicators covered in the survey which broadly fall in the following categories: Health and Wellness, Maternal and Child Health, Family Planning and Reproductive Health, Disease Screening and Prevention, Social and Economic Factors, General Healthcare and Treatment

The 2023 Jordan Population and Family Health Survey (JPFHS) is the eighth Population and Family Health Survey conducted in Jordan, following those conducted in 1990, 1997, 2002, 2007, 2009, 2012, and 2017–18. It was implemented by the Department of Statistics (DoS) at the request of the Ministry of Health (MoH).

The primary objective of the 2023 JPFHS is to provide up-to-date estimates of key demographic and health indicators. Specifically, the 2023 JPFHS:
• Collected data at the national level that allowed calculation of key demographic indicators
• Explored the direct and indirect factors that determine levels of and trends in fertility and childhood mortality
• Measured contraceptive knowledge and practice
• Collected data on key aspects of family health, including immunisation coverage among children, prevalence and treatment of diarrhoea and other diseases among children under age 5, and maternity care indicators such as antenatal visits and assistance at delivery
• Obtained data on child feeding practices, including breastfeeding, and conducted anthropometric measurements to assess the nutritional status of children under age 5 and women age 15–49
• Conducted haemoglobin testing with eligible children age 6–59 months and women age 15–49 to gather information on the prevalence of anaemia
• Collected data on women’s and men’s knowledge and attitudes regarding sexually transmitted infections and HIV/AIDS
• Obtained data on women’s experience of emotional, physical, and sexual violence
• Gathered data on disability among household members

The information collected through the 2023 JPFHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population. The survey also provides indicators relevant to the Sustainable Development Goals (SDGs) for Jordan.

Between July of 2010 and May of 2013, the Government of India conducted the Annual Health Survey in the Empowered Action Group states of north India. The purpose of the survey was to study the impact of reforms to maternal and child health services in the nine high-fertility, high-mortality states that comprise the EAG.

The AHS consists of a three-round panel that interviewed over 4 million households in each round, as well as a one-time Clinical, Anthropometric, and Bio-Chemical Survey. These data were released to the public in 2015 as a set of .csv files. Between December of 2019 and May of 2021, a team of researchers from The University of Texas at Austin assembled the publicly available microdata, constructed the necessary identifiers, cleaned the data, and released user-friendly versions of the constituent datasets on the University of Michigan’s Inter-university Consortium for Political and Social Research.

The documentation, code, and data shared here describes how the final datasets were constructed from the original files released by the Government of India’s Ministry of Health and Family Welfare, what information the final datasets contain, how to use the panel structure of the data, and how to link the different datasets together. It also discusses some of the limitations of the data.

The original files released by the Government of India can be accessed here: https://zenodo.org/record/6062984#.YiZTG0ntwdU

The National Family Health Survey (NFHS) is a large-scale, multi-round survey conducted in a representative sample of households throughout India. The survey is conducted by the Ministry of Health and Family Welfare, in collaboration with the International Institute for Population Sciences (IIPS) and other partner organizations. The NFHS is conducted periodically and provides important information on a wide range of health and social indicators, such as fertility, infant and child mortality, maternal and child health, nutrition, family planning, HIV/AIDS, and other health-related issues. The survey is designed to provide reliable data at the national, state, and district levels, and the results are widely used by policymakers, researchers, and program managers to inform policy and programs related to health and development.

The Irish Health Survey (IHS) is the Irish version of the European Health Interview Survey (EHIS). This survey fulfils the need for public health policies to obtain reliable data on health status, health care usage and health determinants. It allows for health comparisons to be made across Europe. The statistical population is all individuals aged 15 years or older in the state with a total of 10,323 respondents. The principal variables are the Minimum European Health Module (MEHM), which is comprised of general self-perceived health, self-reported longstanding illnesses and longstanding health problems, and self-reported long-standing limitations in activities people usually do because of health problems. --> --> External Link--> --> -->

The Health Survey for England series was designed to monitor trends in the nation's health; estimating the proportion of people in England who have specified health conditions, and the prevalence of risk factors and behaviours associated with these conditions. The surveys provide regular information that cannot be obtained from other sources. The surveys have been carried out since 1994 by the Joint Health Surveys Unit of NatCen Social Research and the Research Department of Epidemiology and Public Health at UCL. Each survey in the series includes core questions, e.g. about alcohol and smoking, and measurements (such as blood pressure, height and weight, and analysis of blood and saliva samples), and modules of questions on topics that vary from year to year. The trend tables show data for available years between 1993 and 2016 for adults (defined as age 16 and over) and for children. The survey samples cover the population living in private households in England. In 2016 the sample contained 8,011 adults and 2,056 children and 5,049 adults and 1,117 children had a nurse visit. We would very much like your feedback about whether some proposed changes to the publications would be helpful and if the publications meet your needs. This will help us shape the design of future publications to ensure they remain informative and useful. Please answer our reader feedback survey on Citizen Space which is open until 18 June 2018.

Abstract

The Service Delivery Indicators (SDI) are a set of health and education indicators that examine the effort and ability of staff and the availability of key inputs and resources that contribute to a functioning school or health facility. The indicators are standardized, allowing comparison between and within countries over time.

The Health SDIs include healthcare provider effort, knowledge and ability, and the availability of key inputs (for example, basic equipment, medicines and infrastructure, such as toilets and electricity). The indicators provide a snapshot of the health facility and assess the availability of key resources for providing high quality care.

The Sierra Leone SDI Health survey team visited a sample of 536 health facilities across Sierra Leone between January and April 2018. The survey team collected rosters covering 5,055 workers for absenteeism and assessed 829 health workers for competence using patient case simulations.

Geographic coverage

National

Analysis unit

Health facilities and healthcare providers

Universe

All health facilities providing primary-level care

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling strategy for SDI surveys is designed towards attaining indicators that are accurate and representative at the national level, as this allows for proper cross-country (i.e. international benchmarking) and across time comparisons, when applicable. In addition, other levels of representativeness are sought to allow for further disaggregation (rural/urban areas, public/private facilities, subregions, etc.) during the analysis stage.

The sampling strategy for SDI surveys follows a multistage sampling approach. The main units of analysis are facilities (schools and health centers) and providers (health and education workers: teachers, doctors, nurses, facility managers, etc.). The multi-stage sampling approach makes sampling procedures more practical by dividing the selection of large populations of sampling units in a step-by-step fashion. After defining the sampling frame and categorizing it by stratum, a first stage selection of sampling units is carried out independently within each stratum. Often, the primary sampling units (PSU) for this stage are cluster locations (e.g. districts, communities, counties, neighborhoods, etc.) which are randomly drawn within each stratum with a probability proportional to the size (PPS) of the cluster (measured by the location’s number of facilities, providers or pupils). Once locations are selected, a second stage takes place by randomly selecting facilities within location (either with equal probability or with PPS) as secondary sampling units. At a third stage, a fixed number of health and education workers and pupils are randomly selected within facilities to provide information for the different questionnaire modules.

Detailed information about the specific sampling process is available in the associated SDI Country Report included as part of the documentation that accompany these datasets.

Mode of data collection

Face-to-face [f2f]

Research instrument

The SDI Health Survey Questionnaire consists of four modules:

Module 1: General Information - Administered to the health facility manager to collect information on equipment, medicines, infrastructure and other facets of the health facility.

Module 2: Provider Absence - A roster of healthcare providers is collected and absence measured.

Module 3: Clinical Vignettes – A selection of providers are given clinical vignettes to measure knowledge of common medical conditions.

Module 4: Facility finances – Information on facility revenue and expenditures is collected from the health facility manager.

Weights: Weights for facilities, absentee-related analyses and clinical vignette analyses.

Cleaning operations

Quality control was performed in Stata.

NFHS-5 (2019-21)

The National Family & Health Survey (NFHS) is a survey in India that attempts to collect information on health conditions, nutrition, family planning, domestic violence, and a host of other factors through conducting surveys on a random ("representative") sample of Indian households in all states. The fifth NFHS was conducted through 2019-21, and the reports were released to the public in 2021 and can be found at this link. The original data was released as PDFs; this Kaggle dataset was created by extracting the tabular data from PDFs into JSONs.

What kind of information is collected in this survey?

Here's a non-comprehensive list of some indicators collected by this survey:

1. Female population age 6 years and above who ever attended school (%)
2. Women age 20-24 years married before age 18 years (%)
3. Institutional births in public facility (%)
4. Children with diarrhoea in the 2 weeks preceding the survey who received oral rehydration salts (ORS) (%)
5. Blood sugar level - high or very high (>140 mg/dl) or taking medicine to control blood sugar level (%)
6. Women age 15 years and above who use any kind of tobacco (%)

Major news outlets in India analysed the results of the study too - here are some interesting articles that show what sorts of "stories" or insights you van look for in this data:

• 50% women, kids in 14 states and UTs are anaemic: National Family Health Survey
• Latest Family Health Survey Proves Prohibition Has Not Worked In Bihar, Alcohol Consumption Is Rife
• Sex Ratio In India Was Estimated As 1,020 By National Family Health Survey During 2019 to 2021, Says MoS Health Dr Bharati Pravin Pawar
• A close reading of the NFHS-5, the health of India
• What the latest NFHS data says about the New Welfarism
• More hospital births, but limited gains in childhood nutrition: National Family Health Survey-5

Note: I used a Python script to parse the data automatically. I tried my best to make sure the data was parsed correctly, but there is a possibility that some data in JSON might not be 100% accurate - there is no way I could have manually verified all 704 PDF files and their outputs, so I randomly sampled and verified a couple of files, all of which looked okay. If you want to see the scripts used to parse this PDFs, please visit my GitHub repo.

Dataset cover photo by Naveed Ahmed on Unsplash.com

Abstract

The primary objective of the 2017 Indonesia Dmographic and Health Survey (IDHS) is to provide up-to-date estimates of basic demographic and health indicators. The IDHS provides a comprehensive overview of population and maternal and child health issues in Indonesia. More specifically, the IDHS was designed to: - provide data on fertility, family planning, maternal and child health, and awareness of HIV/AIDS and sexually transmitted infections (STIs) to help program managers, policy makers, and researchers to evaluate and improve existing programs; - measure trends in fertility and contraceptive prevalence rates, and analyze factors that affect such changes, such as residence, education, breastfeeding practices, and knowledge, use, and availability of contraceptive methods; - evaluate the achievement of goals previously set by national health programs, with special focus on maternal and child health; - assess married men’s knowledge of utilization of health services for their family’s health and participation in the health care of their families; - participate in creating an international database to allow cross-country comparisons in the areas of fertility, family planning, and health.

Geographic coverage

National coverage

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2017 IDHS sample covered 1,970 census blocks in urban and rural areas and was expected to obtain responses from 49,250 households. The sampled households were expected to identify about 59,100 women age 15-49 and 24,625 never-married men age 15-24 eligible for individual interview. Eight households were selected in each selected census block to yield 14,193 married men age 15-54 to be interviewed with the Married Man's Questionnaire. The sample frame of the 2017 IDHS is the Master Sample of Census Blocks from the 2010 Population Census. The frame for the household sample selection is the updated list of ordinary households in the selected census blocks. This list does not include institutional households, such as orphanages, police/military barracks, and prisons, or special households (boarding houses with a minimum of 10 people).

The sampling design of the 2017 IDHS used two-stage stratified sampling: Stage 1: Several census blocks were selected with systematic sampling proportional to size, where size is the number of households listed in the 2010 Population Census. In the implicit stratification, the census blocks were stratified by urban and rural areas and ordered by wealth index category.

Stage 2: In each selected census block, 25 ordinary households were selected with systematic sampling from the updated household listing. Eight households were selected systematically to obtain a sample of married men.

For further details on sample design, see Appendix B of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2017 IDHS used four questionnaires: the Household Questionnaire, Woman’s Questionnaire, Married Man’s Questionnaire, and Never Married Man’s Questionnaire. Because of the change in survey coverage from ever-married women age 15-49 in the 2007 IDHS to all women age 15-49, the Woman’s Questionnaire had questions added for never married women age 15-24. These questions were part of the 2007 Indonesia Young Adult Reproductive Survey Questionnaire. The Household Questionnaire and the Woman’s Questionnaire are largely based on standard DHS phase 7 questionnaires (2015 version). The model questionnaires were adapted for use in Indonesia. Not all questions in the DHS model were included in the IDHS. Response categories were modified to reflect the local situation.

Cleaning operations

All completed questionnaires, along with the control forms, were returned to the BPS central office in Jakarta for data processing. The questionnaires were logged and edited, and all open-ended questions were coded. Responses were entered in the computer twice for verification, and they were corrected for computer-identified errors. Data processing activities were carried out by a team of 34 editors, 112 data entry operators, 33 compare officers, 19 secondary data editors, and 2 data entry supervisors. The questionnaires were entered twice and the entries were compared to detect and correct keying errors. A computer package program called Census and Survey Processing System (CSPro), which was specifically designed to process DHS-type survey data, was used in the processing of the 2017 IDHS.

Response rate

Of the 49,261 eligible households, 48,216 households were found by the interviewer teams. Among these households, 47,963 households were successfully interviewed, a response rate of almost 100%.

In the interviewed households, 50,730 women were identified as eligible for individual interview and, from these, completed interviews were conducted with 49,627 women, yielding a response rate of 98%. From the selected household sample of married men, 10,440 married men were identified as eligible for interview, of which 10,009 were successfully interviewed, yielding a response rate of 96%. The lower response rate for men was due to the more frequent and longer absence of men from the household. In general, response rates in rural areas were higher than those in urban areas.

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 result from mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding 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 2017 Indonesia Demographic and Health Survey (2017 IDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2017 IDHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling error is a measure of the variability among 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 percent 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 2017 IDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2017 IDHS is a STATA program. This program used the Taylor linearization method for variance estimation 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 C of the survey final report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar year - Reporting of age at death in days - Reporting of age at death in months

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

The Annual Health Survey (AHS), conducted by the Government of India between July 2010 and May 2013, investigates maternal and child health in nine states: Assam, Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttarakhand, and Uttar Pradesh. These states constitute about 70 percent of neonatal deaths in India and about one-in-five neonatal deaths globally. The AHS consists of a three-round panel that interviewed over 4 million households in each round, as well as a one-time Clinical, Anthropometric, and Bio-Chemical Survey (CAB). The data were originally released to the public in 2015 as a set of 45 .csv files. The .csv files are included in a restricted-use zipped package as part of the ICPSR release (see dataset 21). The survey focused on topics such as household composition, caste, fertility, family planning, pre- and post-natal care, breastfeeding, infant mortality, illness, disease, disability, and health care practices. Demographic information includes sex, age, education, occupation, marital status, household size, and religion. The CAB files contain biometric data including but not limited to height, weight, blood pressure, hemoglobin, pulse, and blood glucose. Potential data users should note that the public-use and restricted-use versions of the datasets are the same except for the masking of day component variables for certain dates in the public-use versions of the files (please see the Description of Variables section for full details). Therefore, only researchers with a limited set of research questions that require full birth, marriage, and death dates will need to apply for the restricted-use versions of the data files. Additionally, because the final data files are very large and potentially very time consuming to analyze on personal computers, researchers have the option to download ten-percent samples of each file (see datasets 3, 4, 7, 8, 11, 12, 15, 16, 19, and 20). These samples contain the same variables as the original files but only ten percent of the records. The samples were determined by taking a randomly selected ten percent of households in each district. P.I. codebooks were not produced for these samples. Please note that the ten-percent samples for each dataset were selected independently, so it is not advised to merge across datasets within the AHS using these samples, as the match rates will be very low.

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.

The Health Survey for England (HSE) monitors trends in the nation’s health and care. It provides information about adults aged 16 and over, and children aged 0 to 15, living in private households in England. The survey consists of an interview, followed by a visit from a nurse who takes some measurements and blood and saliva samples. Interviews for children aged 0 to 12 were carried out with a parent; children aged 13 to 15 were interviewed directly. Children aged 8 to 15 filled in a self-completion booklet about their drinking and smoking behaviour and young adults, aged between 16 and 17 completed these questions directly into a computer. A total of 8,205 adults (aged 16 and over) and 2,095 children (aged 0 to 15) were interviewed in the 2019 survey. 4,947 adults and 1,169 children had a nurse visit. Each survey in the series includes core questions, and measurements such as blood pressure, height and weight measurements and analysis of blood and saliva samples. In addition, there are modules of questions on specific topics that vary from year to year. The Main Findings follow this page via the link at the bottom. Detailed reports and a link to the supporting Excel tables can be found further down this page and include: • Overweight and obesity in adults and children • Eating Disorders • Adults' health-related behaviours (includes smoking and alcohol consumption) • Children’s health (includes smoking and alcohol consumption) • Providing care to family and friends • Adults' health (includes diabetes, hypertension, and high cholesterol) • Use of health care services

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

The Health Survey for England (HSE) is part of a programme of surveys commissioned by the Health and Social Care Information Centre. It has been carried out since 1994 by the Joint Health Surveys Unit of NatCen Social Research and the Research Department of Epidemiology and Public Health at UCL (University College London). The study provides regular information that cannot be obtained from other sources on a range of aspects concerning the public's health and many of the factors that affect health. The series of Health Surveys for England was designed to monitor trends in the nation's health, to estimate the proportion of people in England who have specified health conditions, and to estimate the prevalence of certain risk factors and combinations of risk factors associated with these conditions. The survey is also used to monitor progress towards selected health targets. Each survey in the series includes core questions and measurements (such as blood pressure, anthropometric measurements and analysis of blood and saliva samples), as well as modules of questions on specific issues that vary from year to year. In some years, the core sample has also been augmented by an additional boosted sample from a specific population subgroup, such as minority ethnic groups, older people or children; there was no boost in 2012. This is the 22nd annual Health Survey for England. All surveys have covered the adult population aged 16 and over living in private households in England. Since 1995, the surveys have included children who live in households selected for the survey; children aged 2-15 were included from 1995, and infants under two years old were added in 2001. Those living in institutions were outside the scope of the survey. This should be borne in mind when considering survey findings, since the institutional population is likely to be older and less healthy than those living in private households. The HSE in 2012 provided a representative sample of the population at both national and regional level. 9,024 addresses were randomly selected in 564 postcode sectors, issued over twelve months from January to December 2012. Where an address was found to have multiple dwelling units, a random selection was made and a single dwelling unit was included. Where there were multiple households at a dwelling unit, again one was selected at random. All adults and children in selected households were eligible for inclusion in the survey. Where there were three or more children aged 0-15 in a household, two of the children were selected at random to limit the respondent burden for parents. A nurse visit was arranged for all participants who consented. A total of 8,291 adults and 2,043 children were interviewed. A household response rate of 64 per cent was achieved. 5,470 adults and 1,203 children had a nurse visit. It should be noted that, as in 2011, there was no child boost sample in 2012. Thus the scope for analyses of some data for children may be limited by relatively small sample sizes.

The New York City Community Mental Health Survey (CMHS) was a one-time telephone survey conducted by the DOHMH. The CMHS was conducted in conjunction with the annual 2012 Community health Survey (CHS). The CMHS provides robust data on the mental health of New Yorkers, including neighborhood, borough, and citywide estimates. The data are analyzed and disseminated to influence mental health program decisions, and increase the understanding of the mental health among New Yorkers.

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.

Abstract

The National Family Health Survey (NFHS) is a large-scale, multi-round survey conducted in a representative sample of households throughout India. Four rounds of the survey have been conducted in 1992-93, 1998-99, 2005-06, and 2015-16. The fifth round of the survey (2019-2020) is currently in the field. All of the surveys are part of the Demographic and Health Surveys (DHS) Program. The surveys provide information on population, health, and nutrition at the national and state level. Since 2015-16, the surveys have also provided information at the district level. Some of the major topics included in NFHS-4 (2015-16) are fertility, infant and child mortality, family planning, maternal and reproductive health, child vaccinations, prevalence and treatment of childhood diseases, nutrition, women’s empowerment, domestic violence, marriage, sexual activity, employment, anemia, anthropometry, HIV/AIDS knowledge and testing, tobacco and alcohol use, biomarker tests (anthropometry, anemia, HIV, blood pressure, and blood glucose), and water, sanitation, and hygiene. The primary objective of the NFHS surveys is to provide essential data on health and family welfare, as well as emerging issues in these areas. The information collected through the NFHS surveys is intended to assist policymakers and program managers in setting benchmarks and examining progress over time in India’s health sector. The Ministry of Health and Family Welfare (MOHFW), Government of India, designated the International Institute for Population Sciences (IIPS), Mumbai, as the agency responsible for providing coordination and technical guidance for all of the surveys. IIPS has collaborated with a large number of field agencies for survey implementation. The Demographic and Health Surveys Program has provided technical assistance for all of the surveys.

Documentation

You can access the data through the DHS website. Data files are available in the following five formats:

• Hierarchical CSPro file
• Flat files: ASCII data with syntax, Stata, SPSS, SAS

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All datasets are distributed in archived ZIP files that include the data file and its associated documentation. The DHS Program is authorized to distribute, at no cost, unrestricted survey data files for legitimate academic research. Registration is required to access the data.

Additional information about the surveys is available on the India page on the DHS Program website. This page provides a list of surveys and reports, plus Country Quickstats for India, and it is the gateway to accessing more information about the India surveys and datasets.

Methodology

2015-16 National Family Health Survey (NFHS-4): Fieldwork for NFHS-4 was conducted in two phases, from January 2015 to December 2016. The fieldwork was conducted by 14 field agencies, including three Population Research Centers. Laboratory testing for HIV was done by seven laboratories throughout India. NFHS-4 collected information from a nationally representative sample of 601,509 households, 699,686 women age 15-49, and 112,122 men age 15-54. The survey covered all 29 states, 7 Union Territories, and 640 districts in India.

Funding for the survey was provided by the Ministry of Health and Family Welfare, Government of India; the United States Agency for International Development (USAID); UKAID/DFID; the Bill & Melinda Gates Foundation; UNICEF; the United Nations Population Fund (UNFPA); and the MacArthur Foundation. Technical Assistance for NFHS-4 was provided by Macro International, Maryland, USA.

2005-06 National Family Health Survey (NFHS-3): Fieldwork for NFHS-3 was conducted in two phases, from November 2005 to August 2006. The fieldwork was conducted by 18 field agencies, including six Population Research Centers. Laboratory testing for HIV was done by the SRL Ranbaxy laboratory in Mumbai. NFHS-3 collected information from a nationally representative sample of 109,041 households, 124,385 women age 15-49, and 74,369 men age 15-54. The survey covered all 29 states. Only the Union Territories were not included.

Funding for the survey was provided by the United States Agency for International Development (USAID); United Kingdom Department for International Development (DFID); the Bill & Melinda Gates Foundation; UNICEF; the United Nations Population Fund (UNFPA); and the Government of India. Technical assistance for NFHS-3 was provided by Macro International, Maryland, USA.

1998-99 National Family Health Survey (NFHS-2): Fieldwork for NFHS-2 was conducted in two phases, from November 1998 to December 1999. The fieldwork was conducted by 13 field agencies, including five Population Research Centers. NFHS-2 collected information from a nationally representative sample of 91,196 households and 89,188 ever-married women age 15-49. Male interviews were not included in the survey. The survey cover

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.

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