Abstract

The District Level Household and facility Survey (DLHS) is a household survey at the district level and in DLHS-3, the survey covered 611 districts in India. The total number of households representing a district varies from 1000 to 1500 households. The DLHS-3 is designed to provide information on family planning, maternal and child health, reproductive health of ever married women and adolescent girls, utilization of maternal and child healthcare services at the district level for India. In addition, DLHS-3 also provides information on new-born care, post-natal care within 48 hours, role of ASHA in enhancing the reproductive and child health care and coverage of Janani Suraksha Yojana (JSY). An important component of DLHS-3 is the integration of Facility Survey of health institution (Sub centre, Primary Health Centre, Community Health Centre and District Hospital) accessible to the sampled villages. The focus of DLHS-3 is to provide health care and utilization indicators at the district level for the enhancement of the activities under National Rural Health Mission (NRHM).

Documentation

You can access the data at the International Institute for Population Sciences.\

Methodology

Survey design and sample size

The survey as well as the preparation of reports was carried out in two separate phases. Approximately 50 percent of the districts from each state and union territory were covered in each phase. The survey for phase I was carried out from May to November, 1998 and for phase II it was carried out from to October, 1999. In the first phase of the RHS, 50 percent of the total districts in India as existing in 1995 were selected for the survey. Systematic random sampling was adopted for the selection of the districts for phase1. For selection purposes, districts within the state were arranged alphabetically, and starting at random from either first or second district, alternative districts were selected. The second phase covered all the remaining districts of the country.

In each of the selected districts, 50 Primary Sampling Units (PSUs), i.e. either villages or urban wards were selected adopting probability proportional to size (PPS) sampling. The village/ ward level population as per the 1991 census was used for this purpose. The sample size for DLHS-DLHS was fixed at 1000 households with 20 households from each PSU. In order to take care of non-response due to various reasons, 10 percent over sampling was done. In other words, 22 households from each PSU were selected. The selection of the households in a PSU was done after listing of all the households in the PSUs. For the selection of households circular systematic random sampling was adopted. In the first phase the work of drawing sample of PSUs was entrusted to the Institute of Research in Medical Statistics (IRMS), New Delhi and in the second phase IIPS did the sampling of PSUs in all the districts.

House listing

House listing involved the preparation of a location map of each PSU and layout sketch of the structures and recording details of the households in the village/census enumeration block. An independent team comprising of one lister and one mapper carried out the houselisting exercise.

Complete listing was carried out in villages with population up to 1500. In the case of larger villages, with more than 1500 population, the village was divided into two or more segments of equal size, one segment was selected at random for listing and in the selected segment complete listing was carried out. In the urban wards with population exceeding 1500 one census enumeration block was selected at random.

** ****Questionnaires**

Two types of questionnaires were used in the survey: the household questionnaire and the woman’s questionnaire. IIPS in consultation with MoHFW and World Bank decided the overall contents of the questionnaires. These questionnaires were discussed and finalized in training-cum-workshop organized at IIPS during the third week of May 1998. Representatives of Regional Agencies, MoHFW, IIPS and World Bank participated in this workshop. IIPS carried out pre-testing of these questionnaires in Maharashtra. Questionnaires were also pre-tested in different languages by regional agencies. Though the overall contents of questionnaire for both the phases were the same, there were some changes in the second phase. The changes were mainly regarding ordering and phrasing of the questions. The household questionnaire was used to list all the eligible women in the selected households (de jure) and to collect information on marriages and births among the usual residents. In the first phase the reference period for the recording of marriages and births was from 1st January 1995 to survey date and in the second phase it was from 1st January 1996 to survey date. For all the marriages reported in the survey, age at marriage of boy/ girl of that household who got marri

The District Level Household and Facility Survey (DLHS-3) is a nationwide survey covering 601 districts from 34 states and union territories of India. This is the third round of the district level household survey which was conducted during December 2007 to December 2008. Data was collected from 7,20,320 households from 28 States and 6 Union Territories of India during 2007-08. From these households, 6,43,944 ever-married women aged 15-49 years and 1,66,620 unmarried women aged 15-24 years were interviewed. The DLHS-3 is designed to provide information on family planning, maternal and child health, reproductive health of ever married women and adolescent girls, utilization of maternal and child healthcare services at the district level for India. In addition, DLHS-3 also provides information on new-born care, post-natal care within 48 hours, role of ASHA in enhancing the reproductive and child health care and coverage of Janani Suraksha Yojana (JSY). An important component of DLHS-3 is the integration of Facility Survey of health institution (Sub centre, Primary Health Centre, Community Health Centre and District Hospital) accessible to the sampled villages. The focus of DLHS-3 is to provide health care and utilization indicators at the district level for the enhancement of the activities under National Rural Health Mission (NRHM). It contains data on Child feeding practices, Child Immunization and Vitamin A suplimentation, Family Planning (currently marriedmage 15 to 49), Knowledge of HIV-AIDs and RTI-STI among ever married women (15 to 49 age), Knowledge of HIV-AIDs unmarried women (15 to 24age), Marriage and fertility (Jan2004 to 2007-08, Maternal Health, Population and household characteristics, Standard of Living Index, Treatment of childhood disease (children under 3 years based on last surviving children), Village Indicator, Women facilitated or motivated by ASHA and Facility Indicators.

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 District Level Household and Facility Survey (DLHS-4) is a nationwide survey which was conducted during 2012-13. The ever-married womens questionnaire contained information on womens characteristics, maternal care, immunization and childcare, contraception and fertility preferences, reproductive health including knowledge about HIV/AIDS. The village questionnaire contained information on availability of health, education and other facilities in the village, and whether the facilities are accessible throughout the year. The health facility questionnaire contained information on human resources, infrastructure, and services. For the first time, a population-linked facility survey has been conducted in DLHS-4. All Community Health Centres (CHCs), District Hospitals and Sub Divisional Hospitals were covered. Further, all Sub-Health Centres and Primary Health Centres (PHCs) which serve the population of the selected PSUs were also covered.It contains district wise data on population and household profile, percentage of households having electricity, improved source of drinking water, having access to improved toilet facility, use clean fuel for cooking, mean age of marriage for girls and boys and percentage of currently married women married below age 18 years and 21 years, characteristics of women, fertility, current use of family planning methods, Unmet need for family planning, quality of family planning services, antenatal care, delivery care, percentage of women who received JSY benefits, percentage of women who had any pregnancy complication, any delivery complication, any post-delivery complication, problem of vaginal discharge and menstrual related problems, percentage of pregnancy resulted in live birth, still birth, induced abortion and spontaneous abortion, child immunization, child feeding practices, birth weight, awareness about Diarrhoea, awareness about ARI, treatment of childhood diseases, awareness of RTI/STI and HIV/AIDS, utilization of government health services, birth registration, personal habits, reported prevalence of morbidity, reported prevalence of chronic illness during last one year, Anaemia status by Haemoglobin level, blood sugar level and hypertension.

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 Core Welfare Indicators Questionnaire (CWIQ) currently constitutes one of the largest socio-economic household survey databases on Tanzania. Since 2003 EDI has interviewed roughly 20,000 households in 35 different districts. For 9 districts repeat surveys have been organised to track changes over time.

Rationale: Absence of district level survey data does not rhyme with the devolution of power to districts. Tanzania is undergoing a decentralisation process whereby each of its roughly 128 districts is becoming an increasingly important policy actor. A district taking on this challenge needs accurate information to monitor and develop its own policies. Much relevant information is currently not available as national statistics are not representative at district level and many of the routine data collection mechanisms are still under development. CWIQ then provides an attractive, one-stop survey-based method to collect basic development indicators. Furthermore, the survey results can be disseminated - through Swahili briefs and posters - to a district's population; thus increasing the extent to which people are able to hold their local governments accountable. Exciting new ground is being broken on such population-wide dissemination by the Prime Minister's Office.

Methodology: The data are collected through a small 10-page questionnaire, called the Core Welfare Indicators Questionnaire (CWIQ). The questionnaire and data software constitute an off-the-shelf survey package developed by the World Bank to produce standardised monitoring indicators of welfare. The questionnaire is purposively concise and is designed to collect information on household demographics, employment, education, health and nutrition as well as utilisation and satisfaction with social services. Questionnaires are scannable, with interviewers shading bubbles and writing numbers later recognised by the scanning software. The data system is fully automated allowing the results to roll out within weeks of the fieldwork.

Funding: projects are typically funded by organisations that care about making decentralisation work in Tanzania. CWIQ is a method to promote evidence-based policy formulation and debate in the district and a tool for the population to hold their local governments accountable. With funding from the RNE (Royal Netherlands Embassy) and SNV (Stichting Nederlands Vrijwilligers), CWIQ surveys were implemented between 2003-2005 in 16 districts. In 2006/07 PMO-RALG (Prime Minister's Office - Regional Administration and Local Government) commissioned EDI to cover a further 28 districts. In 9 of these districts this constituted a repeat survey and thus a unique opportunity arises to monitor changes that occurred in the district over this time period.

Dissemination: EDI disseminated the results of CWIQ on posters and briefs to district level stakeholders (councillors, district officials, NGOs, CBOs, Advocacy Groups, MPs, 'interested citizens', etc.), with the aim at district level, to: (i) promote evidence-based policy debate, (ii) promote evidence-based policy formulation, (iii) provide tools for district level M&E and (iv) increase accountability of LGA to citizens.

Public Domain: Currently in the public domain are (i) all CWIQ reports - note that Shinyanga 2004 and Kagera 2003 reports are organised into one region-wide report (ii) Swahili and English briefs for 5 pilot dissemination districts funded by the Prime Minister's Office - and (iii) raw data for all CWIQs conducted between 2003 and 2007.

Geographic coverage

Five rural districts of Kagera: Ngara, Biharamulo, Muleba, Bukoba Rural and Karagwe.

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

Data from the 2002 Population and Housing Census was used to select 15 households in 30 Enumeration areas in each rural district of the Kagera region. This brings the total number of households to 450 per district or 2,250 at rural regional level. Selection of households did not include refugee camps. Households were further stratified into rural and peri-urban areas and given statistical weights reflecting the number of households they represent.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Due to logistical constraints the completed questionnaires could not be scanned and automatically analysed through CWIQ software. This meant that the lay-out of the questionnaire had to be redesigned slightly to allow easy manual data entry. In order to avoid any problems with coding, missing variables, outliers etc. and to keep continuous thorough checks throughout the data analysis process, all tables and figures were manually produced and assessed for consistency with the data.

Abstract

The World Bank has launched a quick-deploying high-frequency phone-monitoring survey of households to generate near real-time insights on the socio-economic impact of COVID-19 on households which hence to be used to support evidence-based response to the crisis. At a moment when all conventional modes of data collection have had to be suspended, a phone-based rapid data collection/tracking tool can generate large payoffs by helping identify affected populations across the vast archipelago as the contagion spreads, identify with a high degree of granularity the mechanisms of socio-economic impact, identify gaps in public policy response as the Government responds, generating insight that could be useful in scaling up or redirecting resources as necessary as the affected population copes and eventually regains economic footing.

Analysis unit

Household-level; Individual-level: household primary breadwinners, respondent, student, primary caregivers, and under-5 years old kids

Sampling procedure

The sampling frame of the Indonesia high-frequency phone-based monitoring of socio-economic impacts of COVID-19 on households was the list of households enumerated in three recent World Bank surveys, namely Urban Survey (US), Rural Poverty Survey (RPS), and Digital Economy Household Survey (DEHS). The US was conducted in 2018 with 3,527 sampled households living in the urban areas of 10 cities and 2 districts in 6 provinces. The RPS was conducted in 2019 with the sample size of 2,404 households living in rural areas of 12 districts in 6 provinces. The DEHS was conducted in 2020 with 3,107 sampled households, of which 2,079 households lived in urban areas and 1,028 households lived in rural areas in 26 districts and 31 cities within 27 provinces. Overall, the sampled households drawn from the three surveys across 40 districts and 35 cities in 27 provinces (out of 34 provinces). For the final sampling frame, six survey areas of the DEHS which were overlapped with the survey areas in the UPS were dropped from the sampling frame. This was done in order to avoid potential bias later on when calculating the weights (detailed below). The UPS was chosen to be kept since it had much larger samples (2,016 households) than that of the DEHS (265 households). Three stages of sampling strategies were applied. For the first stage, districts (as primary sampling unit (PSU)) were selected based on probability proportional to size (PPS) systematic sampling in each stratum, with the probability of selection was proportional to the estimated number of households based on the National Household Survey of Socio-economic (SUSENAS) 2019 data. Prior to the selection, districts were sorted by provincial code.

In the second stage, villages (as secondary sampling unit (SSU)) were selected systematically in each district, with probability of selection was proportional to the estimated number of households based on the Village Potential Census (PODES) 2018 data. Prior to the selection, villages were sorted by sub-district code. In the third stage, the number of households was selected systematically in each selected village. Prior to the selection, all households were sorted by implicit stratification, that is gender and education level of the head of households. If the primary selected households could not be contacted or refused to participate in the survey, these households were replaced by households from the same area where the non-response households were located and with the same gender and level of education of households’ head, in order to maintain the same distribution and representativeness of sampled households as in the initial design.

In the Round 8 survey where we focused on early nutrition knowledge and early child development, we introduced an additional respondent who is the primary caregiver of under 5 years old in the household. We prioritized the mother as the target of caregiver respondents. In households with multiple caregivers, one is randomly selected. Furthermore, only the under 5 children who were taken care of by the selected respondent will be listed in the early child development module.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaire in English is provided for download under the Documentation section.

Response rate

The HiFy survey was initially designed as a 5-round panel survey. By end of the fifth round, it is expected that the survey can maintain around 3,000 panel households. Based on the experience of phone-based, panel survey conducted previously in other study in Indonesia, the response rates were expected to be around 60 percent to 80 percent. However, learned from other similar surveys globally, response rates of phone-based survey, moreover phone-based panel survey, are generally below 50 percent. Meanwhile, in the case of the HiFy, information on some of households’ phone numbers was from about 2 years prior the survey with a potential risk that the targeted respondents might not be contactable through that provided numbers (already inactive or the targeted respondents had changed their phone numbers). With these considerations, the estimated response rate of the first survey was set at 60 percent, while the response rates of the following rounds were expected to be 80 percent. Having these assumptions and target, the first round of the survey was expected to target 5,100 households, with 8,500 households in the lists. The actual sample of households in the first round was 4,338 households or 85 percent of the 5,100 target households. However, the response rates in the following rounds are higher than expected, making the sampled households successfully interviewed in Round 2 were 4,119 (95% of Round 1 samples), and in Rounds 3, 4, 5, 6, 7, and 8 were 4,067 (94%), 3,953 (91%), 3,686 (85%), 3,471 (80%), 3,435 (79%), 3,383 (78%) respectively. The number of balanced panel households up to Rounds 3, 4, 5, 6, 7, and 8 are 3,981 (92%), 3,794 (87%), 3,601 (83%), 3,320 (77%), 3,116 (72%), and 2,856 (66%) respectively.

BackgroundWith India preparing for the next decennial Census in 2021, we compared the disability estimates and data collection methodology between the Census 2011 and the most recent population-level survey for India and its states, to highlight the issues to be addressed to improve robustness of the disability estimates in the upcoming Census.MethodsData from the Census 2011 and from two complementary nationally representative household surveys that covered all Indian states with the same methodology and survey instruments–the District-Level Household Survey-4 (DLHS-4, 2012–2013) and the Annual Health Surveys (AHS three rounds, 2010–11, 2011–12 and 2012–13) were used. Data from DLHS-4 and AHS 2012–13 round were pooled to generate estimates for the year 2012–13. Data collection methodology between the sources was compared, including the review of definitions of each type of disability. The overall, mental, visual, hearing, speech, and movement disability rate (DR) per 100,000 population were compared between the sources for India and for each state, and the percent difference in the respective rates was calculated. We explored the reliability of these estimates comparing yearly data from the AHS for three successive rounds.ResultsSurvey data were collected through proxy reporting, however, it is not entirely clear whether the data were proxy- or self-reported or a mix of both in the Census. The overall DR was 25.1% higher in the Census (2,242; 95% CI 2,241–2,243) than the survey (1,791; 95% CI 1,786–1,797) per 100,000 population, with the state-level difference ranging from -64% in Tamil Nadu to 107% in Sikkim state. Despite both sources using nearly similar definitions for overall disability and disability by type, the difference in DR was 125.5%, 54.2%, -25.7%, -19.7%, and 21.9% for hearing, speech, mental, movement, and visual DR, respectively. At the state-level, the difference in disability-specific estimates ranged from -84% to 450%. The extent of variations in the disability-specific estimates in AHS successive rounds ranged from -25% to 929% at the state-level.ConclusionsThere is momentum globally towards building disability measurement that is consistent with the data required for monitoring of the Sustainable Development Goals to ensure robust estimation of disability. The current estimates from the Census and surveys seem much lower than would be expected at the population level. We make recommendations that India needs to take serious note of in order to improve the validity and reliability of India’s disability estimates.

Abstract

The 2019-20 Gambia Demographic and Health Survey (2019-20 GDHS) is a nationwide survey with a nationally representative sample of residential households. The survey was implemented by The Gambia Bureau of Statistics (GBoS) in collaboration with the Ministry of Health (MoH).

The primary objective of the 2019-20 GDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the 2019-20 GDHS: ▪ collected data on fertility levels and preferences; contraceptive use; maternal and child health; infant, child, and neonatal mortality levels; maternal mortality; gender; nutrition; awareness about HIV/AIDS; self-reported sexually transmitted infections (STIs); and other health issues relevant to the achievement of the Sustainable Development Goals (SDGs) ▪ obtained information on the availability of, access to, and use of mosquito nets as part of the National Malaria Control Programme ▪ gathered information on other health issues such as injections, tobacco use, hypertension, diabetes, and health insurance ▪ collected data on women’s empowerment, domestic violence, fistula, and female genital mutilation/cutting ▪ tested household salt for the presence of iodine ▪ 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 anaemia testing of women age 15-49 and children age 6-59 months ▪ conducted malaria testing of children age 6-59 months

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15 to 59

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-59, and all children aged 0-5 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2019-20 GDHS was based on an updated version of the 2013 Gambia Population and Housing Census (2013 GPHC) conducted by GBoS. The census counts were updated in 2015-16 based on district-level projected counts from the 2015-16 Integrated Household Survey (IHS). Administratively, The Gambia is divided into eight Local Government Areas (LGAs). Each LGA is subdivided into districts and each district is subdivided into settlements. A settlement, a group of small settlements, or a part of a large settlement can form an enumeration area (EA). These units allow the country to be easily separated into small geographical area units, each with an urban or rural designation. There are 48 districts, 120 wards, and 4,098 EAs in The Gambia; the EAs have an average size of 68 households.

The sample for the 2019-20 GDHS was a stratified sample selected in two stages. In the first stage, EAs were selected with a probability proportional to their size within each sampling stratum. A total of 281 EAs were selected.

In the second stage, the households were systematically sampled. A household listing operation was undertaken in all of the selected clusters. The resulting lists of households served as the sampling frame from which a fixed number of 25 households were systematically selected per cluster, resulting in a total sample size of 7,025 selected households. Results from this sample are representative at the national, urban, and rural levels and at the LGA levels.

For further details on sample selection, see Appendix A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Five questionnaires were used for the 2019-20 GDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaire, and the Fieldworker Questionnaire. These questionnaires, based on The DHS Program’s standard questionnaires, were adapted to reflect the population and health issues relevant to The Gambia. Suggestions were solicited from various stakeholders representing government ministries, departments, and agencies; nongovernmental organisations; and international donors. All questionnaires were written in English, and interviewers translated the questions into the appropriate local language to carry out the interview.

Cleaning operations

All electronic data files were transferred via the Internet File Streaming System (IFSS) to the GBoS central office. The IFSS automatically encrypts the data and sends the data to a server, and the server in turn downloads the data to the data processing supervisor’s password-protected computer in the central office. The data processing operation included secondary editing, which required resolution of computeridentified inconsistencies and coding of open-ended questions. The data were processed by two IT specialists and three secondary editors who took part in the main fieldwork training; they were supervised remotely by staff from The DHS Program. Data editing was accomplished using CSPro software. During the fieldwork, field-check tables were generated to check various data quality parameters, and specific feedback was given to the teams to improve performance. Secondary editing and data processing were initiated in November 2019 and completed in May 2020.

Response rate

All 6,985 households in the selected housing units were eligible for the survey, of which 6,736 were occupied. Of the occupied households, 6,549 were successfully interviewed, yielding a response rate of 97%. Among the households successfully interviewed, 1,948 interviews were completed in 2019 and 4,601 in 2020.

In the interviewed households, 12,481 women age 15-49 were identified for individual interviews; interviews were completed with 11,865 women, yielding a response rate of 95%, a 4 percentage point increase from the 2013 GDHS. Among men, 5,337 were eligible for individual interviews, and 4,636 completed an interview; this yielded a response rate of 87%, a 5 percentage point increase from the previous survey.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes 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 2019-20 Gambia Demographic and Health Survey (GDHS) to minimise 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 2019-20 GDHS 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 among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2019-20 GDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearisation method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

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

Data appraisal

Data Quality Tables

• Household age distribution
• Age distribution of eligible and interviewed women
• Age distribution of eligible and interviewed men
• Completeness of reporting
• Births by calendar years
• Reporting of age at death in days
• Reporting of age at death in months
• Standardisation exercise results from anthropometry training
• Height and weight data completeness and quality for children
• Height measurements from random subsample of measured children
• Number of enumeration areas completed by month, according to Local Government Area, The Gambia DHS 2019-20
• Percentage of children age 6-59 months classified as having malaria according to RDT, by month and Local Government Area, The Gambia DHS 2019-20
• Completeness of information on siblings
• Sibship size and sex ratio of siblings

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

Get data of Health and Family Welfare Statistics - 2017, it provides health and family welfare performance statistics on the various facets of the health and family welfare programmes in India . It includes data on Population and Vital Statistics indicators, Performances of Family Welfare Programmes, Targets/Need Assessed and Achievements of Maternal Health Activities, Child Health, findings of Surveys on Health and Family Welfare Key Indicators [These surveys inter-alia include, National Family Health Survey (NFHS), District Level Household and Facility Survey (DLHS), Annual Health Survey (AHS), Coverage Evaluation Survey (CES) etc.], information on selected indicators from Annual Health Survey (AHS) and Concurrent Evaluation of National Health Mission, information on Infrastructure etc.

Abstract

The demand for evidence based decision making has reached unprecedented levels today more than ever before. The level of data usage has extended not only to cover basic administrative data but also to include more detailed household level information. Household surveys therefore, have become an invaluable source of information for monitoring outcome and impact indicators of national and international development frameworks.

As a key contributor to the monitoring framework, Uganda Bureau of Statistics (UBOS) has conducted large-scale surveys since 1989. The surveys have had a nationwide coverage with varying core modules and objectives. The 2005/06 round of household surveys was yet another in a series conducted by UBOS. The last household survey was conducted in 2002/03 with a focus on labourforce and informal sector in addition to the standard Socio-economic module. This time round, the survey carries an agriculture module in addition to the Socio-economic module. The surveys primarily collect socio-economic data required for measurement of human development and monitoring social goals with special reference to the measurement of poverty under the Poverty Eradication Action Plan (PEAP) and Millennium Development Goals (MDGs).

The main objective of the survey was to collect high quality and timely data on demographic, social and economic characteristics of the household population for national and international development frameworks.

Specifically, the objectives were to: 1. Provide information on the selected economic characteristics of the population including their economic activity status among others. 2. Design and conduct a country-wide agricultural survey through the household approach and to prepare and provide estimates of area and production of major crops and other characteristics at national and regional levels. 3. Meet special data needs of users for the Ministries of Finance, Planning and Economic Development, Agriculture, Animal Industry and Fisheries, Health, Education and Sports among others, and other collaborating Institutions like Economic Policy Research Centre, together with donors and the NGO community so as to monitor the progress of their activities and interventions. 4. Generate and build social and economic indicators and monitor the progress made towards social and economic development goals of the country; and 5. Consolidate efforts being made in building a permanent national household survey capability at UBOS.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Communities

Universe

The survey covered a sample of household members in each district.

Kind of data

Sample survey data [ssd]

Sampling procedure

Survey Design A two stage sampling design was used to draw the sample. At the first stage, Enumeration Areas (EAs) were drawn with Probability Proportional to Size (PPS), and at the second stage, households which are the Ultimate Sampling Units, were drawn using Simple Random Sampling (SRS).

The sample of EAs for the UNHS 2005/06 was selected using the Uganda Population and Housing Census Frame for 2002. Initially, a total of 600 Enumeration Areas (EAs) was selected. These EAs were allocated to each region on the basis of the population size of the region. However, in the Northern region, the number of EAs drawn was doubled. The extra EAs were to be held in reserve to allow for EA attrition due to insecurity.

After this sample was drawn, it was realized that the sample size in 10 districts needed to be increased to about 30 EAs in each district to have an adequate sample size for separate analysis. These extra EAs were selected using an inter-penetrating sampling method which led to drawing an extra 153 EAs. Moreover, because a considerable proportion of the population in the North was in Internally Displaced People (IDPs) camps, this was treated as a separate selection stratum and an additional sample of 30 EAs was drawn from the IDPs. Thus, a total of 783 EAs representing both the general household population and displaced population was selected for the UNHS 2005/06.

Sample Size The size required for the sample was determined by taking into consideration several factors, the three most important being: the degree of precision (reliability) desired for the survey estimates, the cost and operational limitations, and the efficiency of the design. The UNHS 2005/06 covered a sample size of about 7,400 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Five types of questionnaires were administered, namely; socio-economic survey questionnaire, agriculture questionnaire, community questionnaire, price questionnaire and crop harvest cards. The Socio-economic questionnaire collected information on household characteristics including education and literacy, the overall health status, health seeking behavior of household members, malaria, fever and disability, activity status of household members, wage employment, enterprise activities, transfers and household incomes, housing conditions assets, loans, household expenditure, welfare indicators and household shocks. The Agricultural module covered the household crop farming enterprise particulars with emphasis on land, crop area, inputs, outputs and other allied characteristics. The Community Survey questionnaire collected information about the community (LC1). The information related to community access to facilities, community services and other amenities, economic infrastructure, agriculture and markets, education and health infrastructure and agricultural technologies. The Price questioonaire was administered to provide standard equivalents of non standard units through weighing items sold in markets. It was used to collect the different local prices and the non standard units which in many cases are used in selling various items. A crop card was administered to all sampled households with an agricultural activity. Respondents were requested to record all harvests from own produce.

Cleaning operations

Double entry was done to take care of data entry errors. Interactive data cleaning and secondary editing was done. All these processes were done using CSPro ( Census Survey Processing Data Entry application).

To ensure good quality of data, a system of double entry was used. A manual system of editing questionnaires was set-up in June 2005 and two office editors were recruited to further assess the consistency of the data collected. A computer program (hot-deck scrutiny) for verification and validation was developed and operated during data processing.

Range and consistency checks were included in the data-entry program that was developed in CSPro. More intensive and thorough checks were carried out using MS-ACCESS by the processing team.

Sampling error estimates

The estimates were derived from a scientifically selected sample and analysis of survey data was undertaken at national, regional and rural-urban levels. Sampling Errors (SE) and Coefficients of Variations (CVs) of some of the variables have been presented in Appendices of the Socio-Economic Report and Agricultural Module Reports to show the precision levels.

Abstract

The Integrated Household Survey (IHS-I) was a comprehensive socio-economic survey of the living standards of households in all districts of Malawi. The National Statistical Office administered the IHS questionnaire to about 12,900 households over a 12 month period, November 1997 to October 1998. The IHS had five main objectives: - · To provide a complete and integrated data set to arrive at a better understanding of households in poverty. · To serve a much broader set of applications on policy issues regarding: Household behaviour and welfare, Distribution of income and expenditure, Employment and Migration, Health, fertility and nutrition, Education and Access to Social facilities. · To provide fresh information on expenditure patterns of households. This information could be useful in the revision of commodity weights for the consumer price indices. · To provide estimates of final household consumption expenditure to serve as a basis for deriving direct estimates in the National Accounts of final household consumption expenditure. · To rationalise data collection, since household surveys were carried out in an uncoordinated manner in the past. The IHS addresses the interests of various users in one integrated data set with inter-linked modules.

Geographic coverage

National

The survey covered households from both the urban and rural areas of the country. The sample coverage of 12,960 households was designed such that it would give an overall relative standard error of 15 percent. These households were chosen from 29 Survey Districts (Statistical abstract Main survey.pdf page 5 ).

Data were collected in monthly rounds of 60 enumeration areas/clusters over a period of 12 months to account for seasonal effects during the year. There were 720 Enumeration Areas/Clusters (EAs) with 20 households being selected from each rural EA and 10 households from each urban EA. The sampling was designed to ensure that at least 240 households were interviewed in each survey district to provide an acceptable level of accuracy for each variable.

Analysis unit

The IHS have the following units of analysis: individuals and households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey households were chosen following a multi-stage clustered random sampling approach. The 29 survey districts were grouped into 4 urban and 25 rural districts. All the districts were included in the survey. Separate procedures were followed in urban and rural areas.

This survey was carried out between November 1997 and October 1998 by our counterpart agency, the National Statistical Office, based in Zomba. The desire was to produce information that was representative at the district level. Consequently, all of the 25 administrative districts of the country formed clusters for the first stage of the sampling process. (There are now 26 districts, as one of the 25 was since subdivided.) Additionally, each of the four urban centers of Malawi - Blantyre, Zomba, Lilongwe, and Mzuzu - were treated as a separate statistical district. In total, twenty-nine statistical districts for which representative data was sought were delimited. Slightly different sample selection procedures were used in the rural and urban districts.

Rural district sample selection The next level below the district in the administrative hierarchy of the country is the traditional authority (TA) in rural areas and the ward in urban areas. In each of the 25 rural statistical districts, TAs were randomly selected from comprehensive lists of all TAs in the district. The number of TAs selected was done roughly proportional to population size in the statistical district. In the districts with small populations, only one TA was selected. The median number of TAs selected in a district was two, whereas in Lilongwe district, the most populous district, five TAs were selected. Comprehensive lists of all enumeration areas (EA) - a sub-unit of the TA - in the selected TAs were drawn up. Twelve EAs were randomly selected in each TA. The interview schedule involved interviewing all sample households in one of these twelve EAs each month of the year from November 1997 to October 1998. Comprehensive lists of all households in these selected EAs were then drawn up. Twenty households were randomly selected from these lists in each EA, for a total of 240 households for any one TA.

Urban district sample selection In the urban areas, the wards were ignored. Rather a comprehensive list of the enumeration areas - a sub-unit of the wards - was used for random selection of EAs. The number selected was roughly in proportion to population with the number of EAs being multiples of 12 to reflect the 12 months of the survey year (Blantyre - 60 EAs, Zomba - 24 EAs, Lilongwe - 36 EAs, Mzuzu - 24 EAs). Ten, rather than twenty, households in each of the EAs were then randomly selected from comprehensive lists of households in the selected EAs. Each EA was assigned to be interviewed in one of the twelve months of the survey year, e.g. all of the selected households in five EAs were interviewed each month in Blantyre, three EAs in Lilongwe, and all selected households in two EAs in Zomba and Mzuzu.

Overview The total sample size was 12,960 households, with 11,520 households in rural areas and 1,440 urban households. Each sample household was interviewed at the beginning of one of the twelve months of the survey year. The sample households were provided with a diary of expenditures to complete over the following 28 days. All household expenditures over that period were recorded in the diary. The households were visited every third day during the month to monitor the diary entries.

Mode of data collection

Face-to-face [f2f]

Research instrument

Data were collected using two main forms (Refer appendices). These forms are described in more detail below: - (a) FORM IHS-2: Household Characteristics, Income and Expenditure: This form collected data on almost all the modules of the Integrated Household Survey (37 modules). The data collected included the household roster, vital statistics, fertility and mortality, nutrition and anthropometrics, education, health, household expenditure, crop production and sales, livestock and poultry ownership, non-farm activities and income, assets, employment and migration and access to facilities. (b) Form IHS- 3: Diary of Expenditure: Data on daily expenditure was captured using this type of form. Households were asked to maintain the diary for a period of 28 days.

Cleaning operations

Data entry programs were written in IMPS (Integrated Microcomputer Processing System) and data from the questionnaires was captured onto computers initially at NSO's regional centres, and later at NSO headquarters in Zomba. The output from IMPS was in ASCII format, which had to be translated to SPSS. The data was then cleaned in and tabulated in SPSS and STATA, a process which was largely completed by end May 2000.

*all maternal health service utilisation includes: received any ANC service, had institutional delivery, and received postnatal care check-up.Proportion of currently married women who used maternal health services and received advice by background characteristics (Uttar Pradesh, India; DLHS, 2007–08).

Abstract

The objectives of the Smallholder Household Survey in Mozambique were to:

• Generate a clear picture of the smallholder sector at the national level, including household demographics, agricultural profile, and poverty status and market relationships; • Segment smallholder households in Mozambique according to the most compelling variables that emerge; • Characterize the demand for financial services in each segment, focusing on customer needs, attitudes and perceptions related to both agricultural and financial services; and, • Detail how the financial needs of each segment are currently met, with both informal and formal services, and where there may be promising opportunities to add value.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The universe for the survey consists of smallholder households defined as households with the following criteria: 1) Household with up to 5 hectares OR farmers who have less than 50 heads of cattle, 100 goats/sheep/pigs, or 1,000 chickens 2) Agriculture provides a meaningful contribution to the household livelihood, income, or consumption.

Kind of data

Sample survey data [ssd]

Sampling procedure

The CGAP smallholder household survey in Mozambique is a nationally-representative survey with a target sample size of 3,000 smallholder households. The sample was designed to provide reliable survey estimates at the national level and for the following regions: 1. North region, comprised of the provinces of Niassa, Cabo Delgado, and Nampula; 2. Centre region, comprised of Zambezia, Tete, Maica, and Sofala, Manica; and 3. South region, consisting of Inhambane, Maputo Province, Maputo City and Gaza.

(a) SAMPLING FRAME

The sampling frame for the smallholder household survey is the 2009-2010 Census of Agriculture and Livestock (Censo Agro-Pecuário, CAP II) conducted by the Mozambique National Statistical Office (INE) and based on the 2007 Census of Population and Housing (2007 RGPH). CAP II is a large sample that was designed to be representative at the district level and its sample of enumeration areas (EAs) is considered as the master sample; for the national agricultural surveys. EAs with less than 15 agricultural households (mostly in urban areas) were excluded from the sampling frame for CAP II.

(b) SAMPLE ALLOCATION AND SELECTION

In order to take non-response into account, the target sample size was increased to 3,158 households assuming a household non-response rate of 5% observed in similar national households. The total sample size was first allocated to the three regions based on the number of agricultural households. Within each region, the resulting sample was further distributed proportionally to urban and rural areas. The sample for the smallholder survey is a stratified multistage sample. Stratification was achieved by separating urban and rural areas within each region. Since the CAP II master sample that was used as the sampling frame for the survey is stratified by district, rural and urban areas, the rural strata of the individual districts for the CAP II master sample were collapsed up to the province level, and the same for the urban strata within each province. However, the district was still used as a sorting variable in order to provide implicit stratification by district. At the first sampling stage the CAP II sample EAs were selected systematically with PPS within each district, rural and urban stratum, where the measure of size was the number of agricultural households in the census frame.

The full description of the sample design can be found in the user guide for this data set.

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

During data collection, InterMedia received a weekly partial SPSS data file from the field which was analysed for quality control and used to provide timely feedback to field staff while they were still on the ground. The partial data files were also used to check and validate the structure of the data file. The full data file was also checked for completeness, inconsistencies and errors by InterMedia and corrections were made as necessary and where possible.

Response rate

85.8 percent for single respondent questionnare and 92.5 percent for household questionnaire

Sampling error estimates

The sample design for the smallholder household survey was a complex sample design featuring clustering, stratification and unequal probabilities of selection. For key survey estimates, sampling errors considering the design features were produced using either the SPSS Complex Sample module or STATA based on the Taylor series approximation method.

Data appraisal

Following the finalization of questionnaires, a script was developed using Dooblo to support data collection on smart phones. The script was thoroughly tested and validated before its use in the field.

Abstract

This data is from the first round of a unique, cross-country panel survey conducted in Sri Lanka by the Secure Livelihoods Research Consortium (SLRC). The Overseas Development Institute (ODI) is the lead organisation of SLRC. SLRC partners who participated in the survey were: the Centre for Poverty Analysis (CEPA) in Sri Lanka, Feinstein International Center (FIC, Tufts University), the Sustainable Development Policy Institute(SDPI) in Pakistan, Humanitarian Aid and Reconstruction, based at Wageningen University (WUR) in the Netherlands, the Nepal Centre for Contemporary Research (NCCR), and the Food and Agriculture Organization (FAO).

This survey generated the first round of data on people's livelihoods, their access to and experience of basic services, and their views of governance actors. SLRC will attempt to re-interview the same respondents in 2015 to find out how the livelihoods and governance perceptions of people shift (or not) over time, and which factors may have contributed towards that change.

Geographic coverage

Regional

Analysis unit

Households

Universe

Randomly selected households in purposely sampled sites (sampling procedure varied slightly by country). Within a selected household, only one household members was interviewed about the household. Respondents were adults and we aimed to interview a fairly even share of men/ women. In some countries this was achieved, but in other countries the share of male respondents is substantially higher (e.g. Pakistan).

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling strategy was designed to select households that are relevant to the main research questions and as well as being of national relevance, while also being able to produce statistically significant conclusions at the study and village level. To meet these objectives, purposive and random sampling were combined at different stages of the sampling strategy. The first stages of the sampling process involved purposive sampling, with random sampling only utilized in the last stage of the process. Sampling locations were selected purposely (including districts and locations within districts), and then randomly households were selected within these locations. A rigorous sample is geared towards meeting the objectives of the research. The samples are not representative for the case study countries and cannot be used to represent the case study countries as a whole, nor for the districts. The samples are representative at the village level, with the exception of Uganda.

Sampling locations (sub-regions or districts, sub-districts and villages) were purposively selected, using criteria, such as levels of service provision or levels of conflict, in order to locate the specific groups of interest and to select geographical locations that are relevant to the broader SLRC research areas and of policy relevance at the national level. For instance, locations experienced high/ low levels of conflict and locations with high/ low provision of services were selected and locations that accounted for all possible combinations of selection criteria were included. Survey locations with different characteristics were chose, so that we could explore the relevance of conflict affectedness, access to services and variations in geography and livelihoods on our outcome variables. Depending on the administrative structure of the country, this process involved selecting a succession of sampling locations (at increasingly lower administrative units).

The survey did not attempt to achieve representativeness at the country /or district level, but it aimed for representativeness at the sub-district /or village level through random sampling (Households were randomly selected within villages so that the results are representative and statistically significant at the village level and so that a varied sample was captured. Households were randomly selected using a number of different tools, depending on data availability, such as random selection from vote registers (Nepal), construction of household listings (DRC) and a quasi-random household process that involved walking in a random direction for a random number of minutes (Uganda).

The samples are statistically significant at the survey level and village level (in all countries) and at the district level in Sri Lanka and sub-region level in Uganda. The sample size was calculated with the aim to achieve statistical significance at the study and village level, and to accommodate the available budget, logistical limitations, and to account for possible attrition between 2012-2015. In a number of countries estimated population data had to be used, as recent population data were not available. The minimum overall sample size required to achieve significance at the study level, given population and average household size across districts, was calculated using a basic sample size calculator at a 95% confidence level and confidence interval of 5. The sample size at the village level was again calculated at the using a 95% confidence level and confidence interval of 5. . Finally, the sample was increased by 20% to account for possible attrition between 2012 and 2015, so that the sample size in 2015 is likely to be still statistically significant. The overall sample required to achieve the sampling objectives in selected districts in each country ranged from 1,259 to 3,175 households.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

CSPro was used for data entries in most countries.

Data editing took place at a number of stages throughout the processing, including: - Office editing and coding - During data entry - Structure checking and completeness - Extensive secondary editing conducted by ODI

Response rate

approximately 99

Sampling error estimates

No further estimations of sampling error was conducted beyond the sampling design stage.

Data appraisal

Done on an ad hoc basis for some countries, but not consistently across all surveys and domains.

Data and analysis code for "The interaction between district-level development and individual-level socio-economic gradients of cardiovascular disease risk factors in India: A cross-sectional study of 2.4 million adults " (accepted in Social Science and Medicine) and "Nationally representative household survey data for studying the interaction between district-level development and individual-level socioeconomic gradients of cardiovascular disease risk factors in India" (submitted in Data in brief)

Abstract

Annual Household Survey 2015/16 (AHS IV) is the fourth of its kind. AHS is conducted to provide estimations of some major socio-economic indicators on an annual basis, which would not be possible with other periodic surveys like Nepal Labour Force Surveys (NLFS) and Nepal Living Standards Surveys (NLSS) which are undertaken at longer intervals. The survey basically aims to provide estimates of consumption and labour force for Nepal by sex, urban-rural area and consumption quintiles/deciles. Although the major thrust of AHS is on consumption and employment situations, other sectors like education, housing and demographic characteristics are also included. As this year NLSS survey is conducted so, this survey does not contain information on employment situation as in previous annual household surveys.

This survey (AHS IV) has used sampling frame of the National Population Census 2011 that has provided the list of wards with the number of households. It has enumerated a total of 300 sample Primary Sampling Unit (PSU) (150 in urban and 150 in rural). The total sample household was 4,500 (2,250 from urban PSU and 2,250 from rural PSU).

A survey was conducted in 10 months from August 2015 to July 2016. Different PSUs of strata were enumerated at different months. Demographic information was collected as of the date of the survey. The reference period of food consumption was a week (last seven days) prior to the date of enumeration. The data of last 7 days was annualized. Non-food consumption and consumer durables refer to the last 12 months from the date of the survey. Questions on time use in economic and non-economic activities of the last seven days were asked for all household members of age 5 years and above.

The general objective of the survey is to provide data required to monitor annual changes in employment, consumption and other socio-economic indicators of Nepal. The specific objectives of the survey are: 1. To measure the changes in the structure and the level of consumption expenditure of Nepalese households, 2. To provide other socio-economic information useful for economic planning and annual budgeting.

Geographic coverage

The survey covers the whole country (National), Ecological belts (Mountain, Hill, Terai) and, rural and urban.

Analysis unit

Household, Individual

Universe

• All households in the country determined on the basis of the usual place of their residence (de jure househols). The households of diplomatic missions, the institutional households (like people living in schools
  hostels, prisons, army camps and hospitals) were excluded from the survey.
• All persons aged 5 years and above household members.

Kind of data

Sample survey data [ssd]

Sampling procedure

A complete list of wards with number of the households provided by the ward/Enumeration Area (EA) level household data of the National Population Census 2011 was used as the sampling frame for the survey. In 2015, 72 new municipalities were formed, which on adding to the existing 58 municipalities become a total of 130 municipalities. In order to avoid extremity of the size of wards, some big wards were segregated into blocks or enumeration areas (EAs). The sampling frame contained 4,861 EAs in urban and 36,181 EAs in rural areas making a total of 41,042 EAs in Nepal. It was 300 primary sampling units (PSUs) for AHS IV. AHS IV covered all 300 sample PSUs (150 PSUs in urban and 150 PSUs in rural areas). The total sample household was 4500 (2250 from urban and 2250 from rural) taking 15 households from each selected PSUs. In AHS III the sample size was 4,500 households.

The survey aimed to provide estimates for Nepal as well as urban and rural area, and accordingly, the population was stratified into urban and rural area. Wards or sub-wards (EAs) were the primary sampling units (PSUs). The numbers of PSUs to be selected were 150 from rural and 150 from urban area making a total of 300 PSUs. The sample size was determined on the basis of the sampling variance of previous surveys. PSUs were selected on the basis of probability proportional to the size (PPS), the measure of the size being the number of households in each ward. Selected PSUs were spread over 65 districts.

Households were the ultimate sampling units (USUs) and were selected with equal probability on the basis of two-stage systematic random sampling technique. Fifteen (15) households were selected from each PSUs. Altogether 4500 households were selected for the interview.

In a nutshell, procedures followed to select sample households were: 1. Selection of PSUs based on PPS from the frame, 2. Listing of households in the selected PSU, and 3. Selection of USUs from the updated list of households in the selected PSU.

Mode of data collection

Face-to-face [f2f]

Research instrument

The contents of the questionnaire are basically guided by the objectives of the survey. The questionnaire mainly contained household information and individual information. Part 1 of the questionnaire included individual level information using roster and covered questions on demographic characteristics, migration, literacy/education, etc. Parts 2, 3 and 4 covered household level information that consisted of housing, food and non-food consumption expenditure consumption of durables and own account production respectively. The food consumption part of the questionnaire has covered broad food categories only. The household consumption part of the questionnaire has been designed in line with that of Nepal Living Standards Survey.

Cleaning operations

Data entry and data verification of Annual Household Survey 2015-2016 was conductaed at field. For this task, a simple and clear data entry programme was developed in CSPro software, and each team was given a personal computer having the entry program so that every team could be able to enter the interviewed household data in the respective field area. In other words, data entry and data verification work was done in the field residing in the corresponding PSU. Therefore both mannual and batch editing was carried out and CSPro programme was used for consistancy checking.

Response rate

The survey enumerated 300 (100%) sample households from 300 primary sampling unit 150 PSUs of rural area and 150 PSUs of urban area. Thus, in total 4,500 (100%) households(2250 from urban and 2250 from rural) were enumerated in the survey.

Abstract

This data is from the first round of a unique, cross-country panel survey conducted in Pakistan by the Secure Livelihoods Research Consortium (SLRC). The Overseas Development Institute (ODI) is the lead organisation of SLRC. SLRC partners who participated in the survey were: the Centre for Poverty Analysis (CEPA) in Sri Lanka, Feinstein International Center (FIC, Tufts University), the Sustainable Development Policy Institute(SDPI) in Pakistan, Humanitarian Aid and Reconstruction, based at Wageningen University (WUR) in the Netherlands, the Nepal Centre for Contemporary Research (NCCR), and the Food and Agriculture Organization (FAO).

This survey generated the first round of data on people's livelihoods, their access to and experience of basic services, and their views of governance actors. SLRC will attempt to re-interview the same respondents in 2015 to find out how the livelihoods and governance perceptions of people shift (or not) over time, and which factors may have contributed towards that change.

Geographic coverage

Pakistan: Swat and Lower Dir districts of Khyber Pakhtunkhwa (KP) Rural and urban

Analysis unit

Some questions are at the level of individuals in household (e.g. livelihood activities, education levels); other questions are at the household level (e.g. assets). A sizeable share of the questionnaire is devoted to perceptions based questions, which are at the individual (respondent) level.

Universe

Randomly selected households in purposely sampled sites (sampling procedure varied slightly by country).

Within a selected household, only one household members was interviewed about the household. Respondents were adults and we aimed to interview a fairly even share of men/ women. In some countries this was achieved, but in other countries the share of male respondents is substantially higher (e.g. Pakistan).

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling strategy was designed to select households that are relevant to the main research questions and as well as being of national relevance, while also being able to produce statistically significant conclusions at the study and village level. To meet these objectives, purposive and random sampling were combined at different stages of the sampling strategy. The first stages of the sampling process involved purposive sampling, with random sampling only utilized in the last stage of the process. Sampling locations were selected purposely (including districts and locations within districts), and then randomly households were selected within these locations. A rigorous sample is geared towards meeting the objectives of the research. The samples are not representative for the case study countries and cannot be used to represent the case study countries as a whole, nor for the districts. The samples are representative at the village level, with the exception of Uganda.

Sampling locations (sub-regions or districts, sub-districts and villages) were purposively selected, using criteria, such as levels of service provision or levels of conflict, in order to locate the specific groups of interest and to select geographical locations that are relevant to the broader SLRC research areas and of policy relevance at the national level. For instance, locations experienced high/ low levels of conflict and locations with high/ low provision of services were selected and locations that accounted for all possible combinations of selection criteria were included. Survey locations with different characteristics were chose, so that we could explore the relevance of conflict affectedness, access to services and variations in geography and livelihoods on our outcome variables. Depending on the administrative structure of the country, this process involved selecting a succession of sampling locations (at increasingly lower administrative units).

The survey did not attempt to achieve representativeness at the country /or district level, but it aimed for representativeness at the sub-district /or village level through random sampling (Households were randomly selected within villages so that the results are representative and statistically significant at the village level and so that a varied sample was captured. Households were randomly selected using a number of different tools, depending on data availability, such as random selection from vote registers (Nepal), construction of household listings (DRC) and a quasi-random household process that involved walking in a random direction for a random number of minutes (Uganda).

The samples are statistically significant at the survey level and village level (in all countries) and at the district level in Sri Lanka and sub-region level in Uganda. The sample size was calculated with the aim to achieve statistical significance at the study and village level, and to accommodate the available budget, logistical limitations, and to account for possible attrition between 2012-2015. In a number of countries estimated population data had to be used, as recent population data were not available.

The minimum overall sample size required to achieve significance at the study level, given population and average household size across districts, was calculated using a basic sample size calculator at a 95% confidence level and confidence interval of 5. The sample size at the village level was again calculated at the using a 95% confidence level and confidence interval of 5. . Finally, the sample was increased by 20% to account for possible attrition between 2012 and 2015, so that the sample size in 2015 is likely to be still statistically significant.

The overall sample required to achieve the sampling objectives in selected districts in each country ranged from 1,259 to 3,175 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

One questionnaire per country that includes household level, individual level and respondent level perceptions based questions.

The general structure and content of the questionnaire is similar across all five countries, with about 80% of questions similar, but tailored to the country-specific process. Country-specific surveys were tailored on the basis of a generic survey instrument that was developed by ODI specifically for this survey.

The questionnaires are published in English.

Cleaning operations

CSPro was used for data entries in most countries.

Data editing took place at a number of stages throughout the processing, including: • Office editing and coding • During data entry • Structure checking and completeness • Extensive secondary editing conducted by ODI

Response rate

The required sample sizes were achieved in all countries. Response rates were extremely high, ranging from 99%-100%.

Sampling error estimates

No further estimations of sampling error was conducted beyond the sampling design stage.

Data appraisal

Done on an ad hoc basis for some countries, but not consistently across all surveys and domains.

Abstract

The Second Malawi Integrated Household Survey is a nationally representative sample survey designed to provide information on the various aspects of household welfare in Malawi. The survey was conducted by the National Statistical Office from March 2004- April 2005. The survey collected information from a nationally representative sample of 11,280 households. The sampling design is representative at both national and district level hence the survey provides reliable estimates for those areas.

This is the third survey conducted under the Integrated Household Surveys Programme. The other surveys conducted under this Programme were; the Household Expenditure and Small Scale Economic Activities (HESSEA) conducted in 1990 and the first Integrated Household Survey (IHS1) conducted in 1997/98. The National Statistical Office also conducted the Core Welfare Indicators Questionnaire (CWIQ) in 2002 and the Welfare Monitoring Survey (WMS 2005). The WMS has been designed to provide quick results of welfare levels of the country and is less comprehensive relative to the IHS.

The survey is designed to cover a wide array of subject matter, whose primary objective of is to provide a complete and integrated data set to better understand the target population of households affected by poverty. Some specific objectives of the survey are as follows; · Provide timely and reliable information on key welfare and socio-economic indicators and meet special data needs for the review of the Malawi Poverty Reduction Strategy, which have been implemented in Malawi for the last five years since year 2002. · Provide data to come up with an update of the poverty profile for Malawi (poverty incidence, poverty gap, severity of poverty) · Derive indicators for monitoring of Malawi’s progress towards achievement of the Millennium Development Goals (MDGS) and the MPRS targets. · Provide an understanding of the people of Malawi’s living conditions. · Derive an independent estimate of total household expenditure. · Provide information on household consumption on selected items with the aim of revising the weights in the Malawi Consumer Price Index (CPI).

Geographic coverage

The sample frame includes all three regions of Malawi: north, centre and south and it is representative at both national and district level

Analysis unit

Households Individuals Communities

Kind of data

Sample survey data [ssd]

Sampling procedure

The IHS2 had a total sample size of 11,280 households. The sample for IHS-2 was drawn using a two-stage stratified sampling procedure from a sample frame using the 1998 Population and Housing Census enumeration areas (EAs). Each of the twenty-seven districts was considered as a separate sub-stratum of the main rural stratum (except for Likoma district). The urban stratum includes the four major urban areas: Lilongwe, Blantyre, Mzuzu, and the Municipality of Zomba.

The IHS-2 used a two-stage stratified sample selection process. The primary sampling units (PSU) were the Enumeration areas. These were selected for each strata on the basis of probability proportional to size (PPS). The second stage involved randomly selecting 20 households in each EA. Every listed household in an EA had an equal chance of being selected to be enumerated.

The sample frame includes all three regions of Malawi: north, centre and south. The IHS-2 stratified the country into rural and urban strata. The total sample was 11,280 households (564 EAs x 20 households)

The listing of all households in the enumeration area was conducted by NSO staff in three phases in January, May and October 2004.

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Mode of data collection

Face-to-face [f2f]

Research instrument

The IHS-2 household questionnaire maintained comparisons with the earlier IHS-1 household questionnaire wherever possible. However, the IHS-2 questionnaire is more detailed and new modules were added. The questionnaire covered the socio economic characteristics of the household in the following modular aspects; · Demographic, · Education, · Health · Agriculture · Labour-force · Anthropometric information

There were five modules included in the 2004 questionnaire that did not appear in the 1997-98 questionnaire. These included; · Security and Safety, · Social Safety Nets, · Credit, · Subjective Assessment of Well-being, and · Recent Shocks to the Household.

In addition there were seven agricultural modules that collected more detailed information on the agricultural situation in households than was collected in IHS-1.

The IHS-2 Community Questionnaire was designed to collect information that is common to all households in a given area. During the survey a “community” was defined as the village or urban location surrounding the selected enumeration area, which most residents recognise as being their community. The questionnaire was administered to a group of several knowledgeable residents such as the village headman, headmaster of the local school, agricultural field assistant, religious leaders, local merchants, health workers and long-term knowledgeable residents. Information collected included basic physical and demographic characteristics of the community; access to basic services; economic activities; agriculture; how conditions have changed over the last five years; and prices for 47 common food items, non-food items, and ganyu labor.

Cleaning operations

(a) Data Entry Data capturing for the IHS-2 started as soon as the first months of fieldwork was completed in April 2005. Data entry was done concurrently with data collection. The IHS-2 data entry centre was centralised at the National Statistical Office headquarters and was organized as follows; Once the questionnaires arrived the data editor checked the questionnaires and assigned questionnaire numbers. The CSPRO software was used to capturer the data. This software provides automatic data checks for acceptable values for the variables, and checks between different modules of the questionnaire.

(b) Data Cleaning The data cleaning process was done in several stages. The first stage was to make sure that the data as captured reflected the information that the informants provided. The data processing manager did the error checks for each enumeration area. These were cross-examined physically with the questionnaires, and the errors were documented.

Response rate

total of 11,280 were selected for the sample of which 10,777 households were occupied and successfully interviewed, yielding a response rate of 96 percent. Of the selected households 507 replacements were made. The primary reason for replacement was that the dwelling could be found but no household member could be found after repeated attempts or the dwelling was unoccupied.

Abstract

The October Household Survey is an annual survey based on a survey of a large number of households (ranging from 16 000 in 1996 through to 30 000 in 1997 and 1998, depending on the availability of funding). It covers a range of development indicators, including unemployment rates (official and expanded), according to standard definitions of the International Labour Organisation (ILO).

Geographic coverage

The survey had national coverage.

Analysis unit

Households and individuals

Universe

The survey covered households and household members in households in the nine provinces of South Africa

Kind of data

Sample survey data

Sampling procedure

A sample of 20 000 households was drawn in 2 000 enumerator areas (EAs) (that is 10 households per enumerator area). A two-stage sampling procedure was applied and the sample was stratified, clustered and selected to meet the requirements of probability sampling. The sample was based on the 1996 Population Census enumerator areas and the estimated number of people from the administrative records of the 1996 population Census. The sampled population excluded all prisoners in prisons, patients in hospitals, people residing in boarding houses and hotels (whether temporary or semi-permanent). The sample was explicitly stratified by province, Transitional Metropolitan Council (TMC)and District Council (DC). A square root method was used for the allocation of the sample EAs to the explicit strata.

Within each explicit stratum the EAs were stratified by simply arranging them in geographical order by magisterial district and, within the magisterial district, by EA. The allocated number of EAs was systematically selected with probability proportional to size in each stratum. The measure of size was the estimated number of people in Each EA. A systematic sample of 10 households was drawn.

Mode of data collection

Face-to-face [f2f]

Research instrument

The data files in the October Household Survey 1997 (OHS 1997) correspond to the following sections in the questionnaire:
PERSON: Indivitual-level data from Section 1 and Section 4; BIRTHS: Data from Section 2; CHILDREN: Data from Section2; WORKER: Data from Section 3; MIGRANT: Data from Section 5; DEATHS: Data from Section 6; MIGRATION: Data from Section 7; DOMESTIC: Data from Section 8; HOUSE: Household-level data from Section 9

Errors in the marital codes in the original OHS 1998 questionnaire: The questionnaire for the OHS 1998 originally provided by Statistics SA with the data files was incorrect. It was the OHS 1997 questionnaire with a OHS 1998 flap. The marital codes were different in the two surveys. In 1997, the codes for the variable Marital Status were: 1 Never married 2 Married - civil 3 Married - customary 4 Living together 5 Widowed 6 Divorced

In the 1998 survey, the codes for the variable Marital Status are:

1 Married - civil 2 Married - traditional (customary) 3 Living together 4 Widower/widow 5 Divorced/separated 6 Never married

DataFirst notified Statistics SA of this error on 13 July 2007 and they sent a corrected questionnaire. The correct questionnaire is version 2, available with the data since 2007.

Data appraisal

Errors in the marital codes in the original OHS 1998 questionnaire:

The questionnaire for the OHS 1998 originally provided by Statistics SA with the data files was incorrect. It was the OHS 1997 questionnaire with a OHS 1998 flap. The marital codes were different in the two surveys. In 1997, the codes for the variable Marital Status were: 1 Never married 2 Married - civil 3 Married - customary 4 Living together 5 Widowed 6 Divorced

In the 1998 survey, the codes for the variable Marital Status are:

1 Married - civil 2 Married - traditional (customary) 3 Living together 4 Widower/widow 5 Divorced/separated 6 Never married

DataFirst notified Statistics SA of this error on 13 July 2007 and they sent a corrected questionnaire. The correct questionnaire is version 2, available with the data since 2007.