Abstract

The primary objective of the 2018 NDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the NDHS collected information on fertility, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and children, maternal and child health, adult and childhood mortality, women’s empowerment, domestic violence, female genital cutting, prevalence of malaria, awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections (STIs), disability, and other health-related issues such as smoking.

The information collected through the 2018 NDHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population. The 2018 NDHS also provides indicators relevant to the Sustainable Development Goals (SDGs) for Nigeria.

Geographic coverage

National coverage

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2018 NDHS is the Population and Housing Census of the Federal Republic of Nigeria (NPHC), which was conducted in 2006 by the National Population Commission. Administratively, Nigeria is divided into states. Each state is subdivided into local government areas (LGAs), and each LGA is divided into wards. In addition to these administrative units, during the 2006 NPHC each locality was subdivided into convenient areas called census enumeration areas (EAs). The primary sampling unit (PSU), referred to as a cluster for the 2018 NDHS, is defined on the basis of EAs from the 2006 EA census frame. Although the 2006 NPHC did not provide the number of households and population for each EA, population estimates were published for 774 LGAs. A combination of information from cartographic material demarcating each EA and the LGA population estimates from the census was used to identify the list of EAs, estimate the number of households, and distinguish EAs as urban or rural for the survey sample frame. Before sample selection, all localities were classified separately into urban and rural areas based on predetermined minimum sizes of urban areas (cut-off points); consistent with the official definition in 2017, any locality with more than a minimum population size of 20,000 was classified as urban.

The sample for the 2018 NDHS was a stratified sample selected in two stages. Stratification was achieved by separating each of the 36 states and the Federal Capital Territory into urban and rural areas. In total, 74 sampling strata were identified. Samples were selected independently in every stratum via a two-stage selection. Implicit stratifications were achieved at each of the lower administrative levels by sorting the sampling frame before sample selection according to administrative order and by using a probability proportional to size selection during the first sampling stage.

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

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four questionnaires were used for the 2018 NDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s standard Demographic and Health Survey (DHS-7) questionnaires, were adapted to reflect the population and health issues relevant to Nigeria. Comments were solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. In addition, information about the fieldworkers for the survey was collected through a self-administered Fieldworker Questionnaire.

Cleaning operations

The processing of the 2018 NDHS data began almost immediately after the fieldwork started. As data collection was completed in each cluster, all electronic data files were transferred via the IFSS to the NPC central office in Abuja. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors. Secondary editing, carried out in the central office, involved resolving inconsistencies and coding the open-ended questions. The NPC data processor coordinated the exercise at the central office. The biomarker paper questionnaires were compared with electronic data files to check for any inconsistencies in data entry. Data entry and editing were carried out using the CSPro software package. The concurrent processing of the data offered a distinct advantage because it maximised the likelihood of the data being error-free and accurate. Timely generation of field check tables allowed for effective monitoring. The secondary editing of the data was completed in the second week of April 2019.

Response rate

A total of 41,668 households were selected for the sample, of which 40,666 were occupied. Of the occupied households, 40,427 were successfully interviewed, yielding a response rate of 99%. In the households interviewed, 42,121 women age 15-49 were identified for individual interviews; interviews were completed with 41,821 women, yielding a response rate of 99%. In the subsample of households selected for the male survey, 13,422 men age 15-59 were identified and 13,311 were successfully interviewed, yielding a response rate of 99%.

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 2018 Nigeria Demographic and Health Survey (NDHS) 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 2018 NDHS 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 2018 NDHS sample is the result of a multistage 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 - Sibship size and sex ratio of siblings - Pregnancy-related mortality trends - Data collection period - Malaria prevalence according to rapid diagnostic test (RDT)

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

Since 2013, the Robert Wood Johnson Foundation (RWJF) has led the development of a pioneering national action framework to advance a "culture that enables all in our diverse society to lead healthier lives now and for generations to come." Accomplishing these principles requires a national paradigm shift from a traditionally disease and health care-centric view of health toward one that focuses on well-being. Recognizing that paradigm shifts require intentional actions, RWJF worked with RAND researchers to design an actionable path to fulfill the Culture of Health (CoH) vision. A central piece of this work is the development of measures to assess constructs underlying a CoH. The National Survey of Health Attitudes is a survey that RWJF and RAND analysts developed and conducted as part of the foundation's CoH strategic framework. The foundation undertook this survey to measure key constructs that could not be measured in other data sources. Thus, the survey was not meant to capture the full action framework that informs CoH, but rather just selected measure areas. The questions in this survey primarily addressed the action area: making health a shared value. The survey covers a variety of topics, including views regarding what factors influence health, such as the notion of health interdependence (peer, family, neighborhood, and workplace drivers of health), values related to national and community investment for health and well-being; behaviors around health and well-being, including civic engagement on behalf of health, and the role of community engagement and sense of community in relation to health attitudes and values. This study includes the results from the 2018 RWJF National Survey of Health Attitudes. This 2018 survey is considered the second wave, the first wave of the survey was conducted in 2015 (ICPSR 37405). In 2018, the study team fielded an updated version that included many of the same questions but added some new constructs that were of interest as part of the larger Culture of Health effort. This study complements the overview of the 2015 survey described in the RAND report Development of the Robert Wood Johnson Foundation National Survey of Health Attitudes (Carman et al., 2016).

Abstract

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

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

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

Geographic coverage

National

Analysis unit

Health facilities and healthcare providers

Universe

All health facilities providing primary-level care

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

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

Mode of data collection

Face-to-face [f2f]

Research instrument

The SDI Health Survey Questionnaire consists of four modules:

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

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

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

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

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

Cleaning operations

Quality control was performed in Stata.

The Health Examination Survey 2018-2019 of the CUORE Project is coordinated by the Department of Cardiovascular, Endocrine-metabolic Diseases and Aging of the Istituto Superiore di Sanità

The objectives of the survey, addressed to the general adult population (35-74 years), are to:

1. estimate the distribution of risk factors (arterial blood pressure, heart rate, weight, height, body mass index, waist and hips circumference);
2. study the distribution of life habits (physical activity, smoking habits, diet, alcohol consumption);
3. estimate the prevalence of conditions at risk (arterial hypertension, overweight and obesity, smoking habits);
4. evaluate the temporal trend of risk factors distribution (arterial blood pressure, heart rate, weight, height, body mass index, waist circumference and hips);
5. evaluate the temporal trend of life habits distribution (physical activity, smoking habits, diet, alcohol consumption);
6. evaluate the temporal trend of the prevalence of conditions at risk (arterial hypertension, overweight and obesity, smoking habits);
7. monitor national lifestyles campaigns, in particular estimate the average daily consumption of sodium, potassium and iodine per capita, as a result of the “Guadagnare Salute” program of the Ministry of Health;
8. evaluate physical performance, attention and memory in the elderly population (65-74 years);
9. study the degree of health literacy;

The survey is conducted in several Italian regions, between North, Central and South; in each region, a sample of 200 people is enrolled, stratified by gender and age group, randomly extracted from the general population residing in a selected municipality. For each age group (35-44, 45-54, 55-64, 65-74) and sex, 25 people are drawn.

Contains tabulated outputs on each topic from the Health Survey for England 2018

The primary objective of the 2017-18 Jordan Population and Family Health Survey (JPFHS) is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the 2017-18 JPFHS: Collected data at the national level that allowed calculation of key demographic indicators Explored the direct and indirect factors that determine levels of and trends in fertility and childhood mortality Measured levels of contraceptive knowledge and practice Collected data on key aspects of family health, including immunisation coverage among children, the prevalence and treatment of diarrhoea and other diseases among children under age 5, and maternity care indicators such as antenatal visits and assistance at delivery among ever-married women Obtained data on child feeding practices, including breastfeeding, and conducted anthropometric measurements to assess the nutritional status of children under age 5 and ever-married women age 15-49 Conducted haemoglobin testing on children age 6-59 months and ever-married women age 15-49 to provide information on the prevalence of anaemia among these groups Collected data on knowledge and attitudes of ever-married women and men about sexually transmitted infections (STIs) and HIV/AIDS Obtained data on ever-married women’s experience of emotional, physical, and sexual violence Obtained data on household health expenditures

Abstract

The 2018 Nigeria Demographic and Health Survey (2018 NDHS) was implemented by the National Population Commission (NPC). Data collection took place from 14 August to 29 December 2018. ICF provided technical assistance through The DHS Program, which is funded by the United States Agency for International Development (USAID) and offers financial support and technical assistance for population and health surveys in countries worldwide. Other agencies and organisations that facilitated the successful implementation of the survey through technical or financial support were the Global Fund, the Bill and Melinda Gates Foundation (BMGF), the United Nations Population Fund (UNFPA), and the World Health Organization (WHO).

SURVEY OBJECTIVES The primary objective of the 2018 NDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the NDHS collected information on fertility, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and children, maternal and child health, adult and childhood mortality, women’s empowerment, domestic violence, female genital cutting, prevalence of malaria, awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections (STIs), disability, and other health-related issues such as smoking.

The information collected through the 2018 NDHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population. The 2018 NDHS also provides indicators relevant to the Sustainable Development Goals (SDGs) for Nigeria.

Geographic coverage

national coverage

Analysis unit

Households Women Men children

Universe

the survey covered all household members (permanent residents and visitor), all Women aged 15-49 years, all children 0-59 months and all men aged 15-59 years in one-third of households

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2018 NDHS is the Population and Housing Census of the Federal Republic of Nigeria (NPHC), which was conducted in 2006 by the National Population Commission. Administratively, Nigeria is divided into states. Each state is subdivided into local government areas (LGAs), and each LGA is divided into wards. In addition to these administrative units, during the 2006 NPHC each locality was subdivided into convenient areas called census enumeration areas (EAs). The primary sampling unit (PSU), referred to as a cluster for the 2018 NDHS, is defined on the basis of EAs from the 2006 EA census frame. Although the 2006 NPHC did not provide the number of households and population for each EA, population estimates were published for 774 LGAs. A combination of information from cartographic material demarcating each EA and the LGA population estimates from the census was used to identify the list of EAs, estimate the number of households, and distinguish EAs as urban or rural for the survey sample frame. Before sample selection, all localities were classified separately into urban and rural areas based on predetermined minimum sizes of urban areas (cut-off points); consistent with the official definition in 2017, any locality with more than a minimum population size of 20,000 was classified as urban.

The sample for the 2018 NDHS was a stratified sample selected in two stages. Stratification was achieved by separating each of the 36 states and the Federal Capital Territory into urban and rural areas. In total, 74 sampling strata were identified. Samples were selected independently in every stratum via a two-stage selection. Implicit stratifications were achieved at each of the lower administrative levels by sorting the sampling frame before sample selection according to administrative order and by using a probability proportional to size selection during the first sampling stage.

In the first stage, 1,400 EAs were selected with probability proportional to EA size. EA size was the number of households in the EA. A household listing operation was carried out in all selected EAs, and the resulting lists of households served as a sampling frame for the selection of households in the second stage. In the second stage’s selection, a fixed number of 30 households was selected in every cluster through equal probability systematic sampling, resulting in a total sample size of approximately 42,000 households. The household listing was carried out using tablets, and random selection of households was carried out through computer programming. The interviewers conducted interviews only in the pre-selected households. To prevent bias, no replacements and no changes of the pre-selected households were allowed in the implementing stages.

Due to the non-proportional allocation of the sample to the different states and the possible differences in response rates, sampling weights were calculated, added to the data file, and applied so that the results would be representative at the national level as well as the domain level. Because the 2018 NDHS sample was a two-stage stratified cluster sample selected from the sampling frame, sampling weights were calculated based on sampling probabilities separately for each sampling stage and for each cluster.

The survey was successfully carried out in 1,389 clusters after 11 clusters with deteriorating law-and-order situations during fieldwork were dropped. These areas were in Zamfara (4 clusters), Lagos (1 cluster), Katsina (2 clusters), Sokoto (3 clusters), and Borno (1 cluster). In the case of Borno, 11 of the 27 LGAs were dropped due to high insecurity, and therefore the results might not represent the entire state. Please refer to Appendix A in the final report for details.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four questionnaires were used for the 2018 NDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s standard Demographic and Health Survey (DHS-7) questionnaires, were adapted to reflect the population and health issues relevant to Nigeria. Comments were solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. In addition, information about the fieldworkers for the survey was collected through a self-administered Fieldworker Questionnaire.

The survey protocol was reviewed and approved by the National Health Research Ethics Committee of Nigeria (NHREC) and the ICF Institutional Review Board. After all questionnaires were finalised in English, they were translated into Hausa, Yoruba, and Igbo. The 2018 NDHS used computer-assisted personal interviewing (CAPI) for data collection.

The Household Questionnaire listed all members of and visitors to selected households. Basic demographic information was collected on each person listed, including age, sex, marital status, education, and relationship to the head of the household. For children under age 18, survival status of parents was determined. Data on age, sex, and marital status of household members were used to identify women and men who were eligible for individual interviews. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as source of drinking water; type of toilet facilities; materials used for flooring, external walls, and roofing; ownership of various durable goods; and ownership of mosquito nets. In addition, data were gathered on salt testing and disability.

The Woman’s Questionnaire was used to collect information from all eligible women age 15-49. These women were asked questions on the following topics: - Background characteristics (including age, education, and media exposure) - Birth history and child mortality - Knowledge, use, and source of family planning methods - Antenatal, delivery, and postnatal care - Vaccinations and childhood illnesses - Breastfeeding and infant feeding practices - Women’s minimum dietary diversity - Marriage and sexual activity - Fertility preferences (including desire for more children and ideal number of children) - Women’s work and husbands’ background characteristics - Knowledge, awareness, and behaviour regarding HIV/AIDS and other sexually transmitted infections (STIs) - Knowledge, attitudes, and behaviour related to other health issues (e.g., smoking) - Female genital cutting - Fistula - Adult and maternal mortality - Domestic violence

The Man’s Questionnaire was administered to all men age 15-59 in the subsample of households selected for the men’s survey. The Man’s Questionnaire collected much of the same information as the Woman’s Questionnaire but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health.

The Biomarker Questionnaire was used to record the results of anthropometry measurements and other biomarkers for women and children. This questionnaire was administered only to the subsample selected for the men’s survey. All children age 0-59 months and all women age 15-49 were eligible for height and weight measurements. Women age 15-49 were also eligible for haemoglobin testing. Children age 6-59 months were also eligible for haemoglobin testing, malaria testing, and genotype testing for sickle cell disease.

The purpose of the Fieldworker Questionnaire was to collect basic background information on the people who were collecting data in the field, including the team supervisor, field editor, interviewers, and the biomarker team

Abstract copyright UK Data Service and data collection copyright owner.

The Health Survey for England (HSE) is a series of surveys designed to monitor trends in the nation's health. It was commissioned by NHS Digital and carried out by the Joint Health Surveys Unit of the National Centre for Social Research and the Department of Epidemiology and Public Health at University College London.
The aims of the HSE series are:

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

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

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

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

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

The EUL version of the HSE 2018 is held under SN 8961.

Main Topics:

Core topics:

• General health
• Longstanding illness
• Smoking
• Average weekly alcohol consumption
• Drinking (heaviest day in last week)
• Consent to data linkage (NHS central register, HES)
• Socio-economic information: sex, age, income, education, employment etc
• Prescribed medications (nurse)

Additional topics:

• Social care receipt
• Asthma
• Gambling

Measurements:

• Height and weight
• Blood pressure (nurse)
• Waist and hip circumference (nurse)
• Blood sample for cholesterol, glycated haemoglobin (nurse)
• Saliva sample (nurse)

Abstract

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

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

The Kenya SDI Health survey team visited a sample of 3,098 health facilities across Kenya between March and July 2018. The 2018 Kenya SDI is the largest to date. The survey team collected rosters covering 24,098 workers for absenteeism and assessed 4,499 health workers for competence using patient case simulation.

Geographic coverage

National

Analysis unit

Health facilities and healthcare providers

Universe

All health facilities providing primary-level care

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

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

Mode of data collection

Face-to-face [f2f]

Research instrument

The SDI Health Survey Questionnaire consists of four modules, plus weights:

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

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

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

Module 4: Public expenditure tracking - Information on facility finances

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

Cleaning operations

Quality control was performed in Stata.

Abstract

The primary objective of the 2018 ZDHS was to provide up-to-date estimates of basic demographic and health indicators. Specifically, the ZDHS collected information on: - Fertility levels and preferences; contraceptive use; maternal and child health; infant, child, and neonatal mortality levels; maternal mortality; and gender, nutrition, and awareness regarding HIV/AIDS and other health issues relevant to the achievement of the Sustainable Development Goals (SDGs) - Ownership and use of mosquito nets as part of the national malaria eradication programmes - Health-related matters such as breastfeeding, maternal and childcare (antenatal, delivery, and postnatal), children’s immunisations, and childhood diseases - Anaemia prevalence among women age 15-49 and children age 6-59 months - Nutritional status of children under age 5 (via weight and height measurements) - HIV prevalence among men age 15-59 and women age 15-49 and behavioural risk factors related to HIV - Assessment of situation regarding violence against women

Geographic coverage

National coverage

Analysis unit

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

Universe

The survey covered all de jure household members (usual residents), all women age 15-49, all men age 15-59, and all children age 0-5 years who are usual members of the selected households or who spent the night before the survey in the selected households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2018 ZDHS is the Census of Population and Housing (CPH) of the Republic of Zambia, conducted in 2010 by ZamStats. Zambia is divided into 10 provinces. Each province is subdivided into districts, each district into constituencies, and each constituency into wards. In addition to these administrative units, during the 2010 CPH each ward was divided into convenient areas called census supervisory areas (CSAs), and in turn each CSA was divided into enumeration areas (EAs). An enumeration area is a geographical area assigned to an enumerator for the purpose of conducting a census count; according to the Zambian census frame, each EA consists of an average of 110 households.

The current version of the EA frame for the 2010 CPH was updated to accommodate some changes in districts and constituencies that occurred between 2010 and 2017. The list of EAs incorporates census information on households and population counts. Each EA has a cartographic map delineating its boundaries, with identification information and a measure of size, which is the number of residential households enumerated in the 2010 CPH. This list of EAs was used as the sampling frame for the 2018 ZDHS.

The 2018 ZDHS followed a stratified two-stage sample design. The first stage involved selecting sample points (clusters) consisting of EAs. EAs were selected with a probability proportional to their size within each sampling stratum. A total of 545 clusters were selected.

The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected clusters. During the listing, an average of 133 households were found in each cluster, from which a fixed number of 25 households were selected through an equal probability systematic selection process, to obtain a total sample size of 13,625 households. Results from this sample are representative at the national, urban and rural, and provincial levels.

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

Mode of data collection

Face-to-face [f2f]

Research instrument

Four questionnaires were used in the 2018 ZDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s Model Questionnaires, were adapted to reflect the population and health issues relevant to Zambia. Input on questionnaire content was solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international cooperating partners. After all questionnaires were finalised in English, they were translated into seven local languages: Bemba, Kaonde, Lozi, Lunda, Luvale, Nyanja, and Tonga. In addition, information about the fieldworkers for the survey was collected through a self-administered Fieldworker Questionnaire.

Cleaning operations

All electronic data files were transferred via a secure internet file streaming system to the ZamStats central office in Lusaka, where they were stored on a password-protected computer. The data processing operation included secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by two IT specialists and one secondary editor 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 July 2018 and completed in March 2019.

Response rate

Of the 13,595 households in the sample, 12,943 were occupied. Of these occupied households, 12,831 were successfully interviewed, yielding a response rate of 99%.

In the interviewed households, 14,189 women age 15-49 were identified as eligible for individual interviews; 13,683 women were interviewed, yielding a response rate of 96% (the same rate achieved in the 2013-14 survey). A total of 13,251 men were eligible for individual interviews; 12,132 of these men were interviewed, producing a response rate of 92% (a 1 percentage point increase from the previous survey).

Of the households successfully interviewed, 12,505 were interviewed in 2018 and 326 in 2019. As the large majority of households were interviewed in 2018 and the year for reference indicators is 2018.

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 2018 Zambia Demographic and Health Survey (ZDHS) 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 2018 ZDHS 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 2018 ZDHS 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 - Completeness of information on siblings - Sibship size and sex ratio of siblings - Height and weight data completeness and quality for children - Number of enumeration areas completed by month, according to province, Zambia DHS 2018

Note: Data quality tables are presented in APPENDIX C of the report.

This report shares important findings from a major survey conducted in Trinidad and Tobago about violence against women. The survey, known as the Trinidad and Tobago Women's Health Survey (WHS), was carried out in 2017. It involved 1,079 women aged between 15 and 64. For the first time on a national scale, it provides detailed information about two serious issues: Violence by a partner (known as intimate partner violence or IPV) and Sexual violence by someone who isn't a partner (non-partner sexual violence or NPSV). These findings help us understand how widespread these challenges are in Trinidad and Tobago. Copyright © 2018 Inter-American Development Bank. This work is licensed under a Creative Commons IGO 3.0 Attribution-NonCommercial-NoDerivatives (CC-IGO BY-NC-ND 3.0 IGO) license (https://creativecommons.org/licenses/by-nc-nd/3.0/igo/legalcode) and may be reproduced with attribution to the IDB and for any non-commercial purpose. No derivative work is allowed. The following citation is recommended: [© IDB] [Year of publication] [Title of content] [Page number (for publications)] [Location on IDB website] [Date accessed and/or downloaded] Example: © IDB 2018, National Women's Health Survey for Trinidad and Tobago, DOI: http://dx.doi.org/10.18235/0001006, Accessed on 19/09/2023.

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Yearly

Sampling procedure

Sample size:

This report presents findings on the health and health-related behaviours of the Lesbian, Gay and Bisexual (LGB) population in England. These are analysed by age, sex and ethnicity. The data are based on a representative sample of adults, aged 16 and over, who participated in the Health Survey for England from 2011–2018. 2% of adults surveyed in 2011-2018 identified as lesbian, gay or bisexual (LGB) The Health Survey for England series was designed to monitor trends in the health, and health related behaviours, of adults and children in England.

Abstract

The GSHS is a school-based survey which uses a self-administered questionnaire to obtain data on young people's health behaviour and protective factors related to the leading causes of morbidity and mortality among children and adults worldwide.

Geographic coverage

National plus Highland, Plains and Valley

Analysis unit

Individuals

Universe

School-going adolescents aged 13-17 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Bolivia GSHS was a school-based survey of students in 2nd Secondary - 6th Secondary, which are typically attended by students aged 13-17. A two-stage cluster sample design was used to produce data representative of all students in 2nd Secondary - 6th Secondary in Bolivia. At the first stage, schools were selected with probability proportional to enrollment size. At the second stage, classes were randomly selected and all students in selected classes were eligible to participate.

Mode of data collection

self-administered

Research instrument

The following core modules were included in the survey: alcohol use dietary behaviours drug use hygiene mental health physical activity protective factors sexual behaviours tobacco use violence and unintentional injury

Cleaning operations

All data processing (scanning, cleaning, editing, and weighting) was conducted at the US Centers for Disease Control.

Response rate

National: The school response rate was 94%, the student response rate was 84%, and the overall response rate was 79%. Highland: The school response rate was 100%, the student response rate was 88%, and the overall response rate was 88%. Plains: The school response rate was 97%, the student response rate was 83%, and the overall response rate was 80%. Valley: The school response rate was 84%, the student response rate was 81%, and the overall response rate was 68%.

This series of code and corresponding data files are intended for use in cognitive decline and Alzheimer’s disease and related dementias (ADRD) research. The files include twelve years of cleaned datasets derived from the 2007-2018 years of the National Health Interview Survey (NHIS). NHIS is a nationally representative study aimed at monitoring the health of the non-institutionalized United States population. The provided datasets include sociodemographic information on respondents’ age, sex, race, and marital status from the Sample Adult Files, cognition variables from the Sample Adult files and, in applicable years, merged cognition data from the Adult Functioning and Disability (AFD) supplement. The files were constructed to allow for users to append multiple years of data for longitudinal analysis. Brief and detailed summaries of the variables available in these datasets along with more detailed descriptions of performed calculations can be found in the provided data dictionaries. Users may also refer to the provided “Overview of variables across years” document to see which variables are available each year. SAS, Stata, and CSV data file formats are provided as are the full coding scripts used in Stata.

Abstract

The 2017-18 Albania Demographic and Health Survey (2017-18 ADHS) is a nationwide survey with a nationally representative sample of approximately 17,160 households. All women age 15-49 who are usual residents of the selected households or who slept in the households the night before the survey were eligible for the survey. Women 50-59 years old were interviewed with an abbreviated questionnaire that only covered background characteristics and questions related to noncommunicable diseases.

The primary objective of the 2017-2018 ADHS was to provide estimates of basic sociodemographic and health indicators for the country as a whole and the twelve prefectures. Specifically, the survey collected information on basic characteristics of the respondents, fertility, family planning, nutrition, maternal and child health, knowledge of HIV behaviors, health-related lifestyle, and noncommunicable diseases (NCDs). The information collected in the ADHS will assist policymakers and program managers in evaluating and designing programs and in developing strategies for improving the health of the country’s population.

The sample for the 2017-18 ADHS was designed to produce representative results for the country as a whole, for urban and rural areas separately, and for each of the twelve prefectures known as Berat, Diber, Durres, Elbasan, Fier, Gjirokaster, Korce, Kukes, Lezhe, Shkoder, Tirana, and Vlore.

Geographic coverage

National coverage

Analysis unit

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

Universe

The survey covered all de jure household members (usual residents), children age 0-4 years, women age 15-49 years and men age 15-59 years resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The ADHS surveys were done on a nationally representative sample that was representative at the prefecture level as well by rural and urban areas. A total of 715 enumeration areas (EAs) were selected as sample clusters, with probability proportional to each prefecture's population size. The sample design called for 24 households to be randomly selected in every sampling cluster, regardless of its size, but some of the EAs contained fewer than 24 households. In these EAs, all households were included in the survey. The EAs are considered the sample's primary sampling unit (PSU). The team of interviewers updated and listed the households in the selected EAs. Upon arriving in the selected clusters, interviewers spent the first day of fieldwork carrying out an exhaustive enumeration of households, recording the name of each head of household and the location of the dwelling. The listing was done with tablet PCs, using a digital listing application. When interviewers completed their respective sections of the EA, they transferred their files into the supervisor's tablet PC, where the information was automatically compiled into a single file in which all households in the EA were entered. The software and field procedures were designed to ensure there were no duplications or omissions during the household listing process. The supervisor used the software in his tablet to randomly select 24 households for the survey from the complete list of households.

All women age 15-49 who were usual residents of the selected households or who slept in the households the night before the survey were eligible for individual interviews with the full Woman's Questionnaire. Women age 50-59 were also interviewed, but with an abbreviated questionnaire that left out all questions related to reproductive health and mother and child health. A 50% subsample was selected for the survey of men. Every man age 15-59 who was a usual resident of or had slept in the household the night before the survey was eligible for an individual interview in these households.

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

Mode of data collection

Face-to-face [f2f]

Research instrument

Four questionnaires were used in the ADHS, one for the household and others for women age 15-49, for women age 50-59, and for men age 15-59. In addition to these four questionnaires, a form was used to record the vaccination information for children born in the 5 years preceding the survey whose mothers had been successfully interviewed.

Cleaning operations

Supervisors sent the accumulated fieldwork data to INSTAT’s central office via internet every day, unless for some reason the teams did not have access to the internet at the time. The data received from the various teams were combined into a single file, which was used to produce quality control tables, known as field check tables. These tables reveal systematic errors in the data such as omission of potential respondents, age displacement, inaccurate recording of date of birth and age at death, inaccurate measurement of height and weight, and other key indicators of data quality. These tables were reviewed and evaluated by ADHS senior staff, which in turn provided feedback and advice to the teams in the field.

Response rate

A total of 16,955 households were selected for the sample, of which 16,634 were occupied. Of the occupied households, 15,823 were successfully interviewed, which represents a response rate of 95%. In the interviewed households, 11,680 women age 15-49 were identified for individual interviews. Interviews were completed for 10,860 of these women, yielding a response rate of 93%. In the same households, 4,289 women age 50-59 were identified, of which 4,140 were successfully interviewed, yielding a 97% response rate. In the 50% subsample of households selected for the male survey, 7,103 eligible men age 15-59 were identified, of which 6,142 were successfully interviewed, yielding a response rate of 87%.

Response rates were higher in rural than in urban areas, which is a pattern commonly found in household surveys because in urban areas more people work and carry out activities outside the home.

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 2017-18 Albania Demographic and Health Survey (ADHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2017-18 ADHS 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 2017-18 ADHS 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 linearization 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.

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

Data appraisal

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

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

This data represents the age-adjusted prevalence of high total cholesterol, hypertension, and obesity among US adults aged 20 and over between 1999-2000 to 2017-2018. Notes: All estimates are age adjusted by the direct method to the U.S. Census 2000 population using age groups 20–39, 40–59, and 60 and over. Definitions Hypertension: Systolic blood pressure greater than or equal to 130 mmHg or diastolic blood pressure greater than or equal to 80 mmHg, or currently taking medication to lower high blood pressure High total cholesterol: Serum total cholesterol greater than or equal to 240 mg/dL. Obesity: Body mass index (BMI, weight in kilograms divided by height in meters squared) greater than or equal to 30. Data Source and Methods Data from the National Health and Nutrition Examination Surveys (NHANES) for the years 1999–2000, 2001–2002, 2003–2004, 2005–2006, 2007–2008, 2009–2010, 2011–2012, 2013–2014, 2015–2016, and 2017–2018 were used for these analyses. NHANES is a cross-sectional survey designed to monitor the health and nutritional status of the civilian noninstitutionalized U.S. population. The survey consists of interviews conducted in participants’ homes and standardized physical examinations, including a blood draw, conducted in mobile examination centers.

Abstract

The Pakistan Demographic and Health Survey PDHS 2017-18 was the fourth of its kind in Pakistan, following the 1990-91, 2006-07, and 2012-13 PDHS surveys.

The primary objective of the 2017-18 PDHS is to provide up-to-date estimates of basic demographic and health indicators. The PDHS provides a comprehensive overview of population, maternal, and child health issues in Pakistan. Specifically, the 2017-18 PDHS collected information on:

• Key demographic indicators, particularly fertility and under-5 mortality rates, at the national level, for urban and rural areas, and within the country’s eight regions
• Direct and indirect factors that determine levels and trends of fertility and child mortality
• Contraceptive knowledge and practice
• Maternal health and care including antenatal, perinatal, and postnatal care
• Child feeding practices, including breastfeeding, and anthropometric measures to assess the nutritional status of children under age 5 and women age 15-49
• Key aspects of family health, including vaccination coverage and prevalence of diseases among infants and children under age 5
• Knowledge and attitudes of women and men about sexually transmitted infections (STIs), including HIV/AIDS, and potential exposure to risk
• Women's empowerment and its relationship to reproductive health and family planning
• Disability level
• Extent of gender-based violence
• Migration patterns

The information collected through the 2017-18 PDHS is intended to assist policymakers and program managers at the federal and provincial government levels, in the private sector, and at international organisations in evaluating and designing programs and strategies for improving the health of the country’s population. The data also provides information on indicators relevant to the Sustainable Development Goals.

Geographic coverage

National coverage

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2017-18 PDHS is a complete list of enumeration blocks (EBs) created for the Pakistan Population and Housing Census 2017, which was conducted from March to May 2017. The Pakistan Bureau of Statistics (PBS) supported the sample design of the survey and worked in close coordination with NIPS. The 2017-18 PDHS represents the population of Pakistan including Azad Jammu and Kashmir (AJK) and the former Federally Administrated Tribal Areas (FATA), which were not included in the 2012-13 PDHS. The results of the 2017-18 PDHS are representative at the national level and for the urban and rural areas separately. The survey estimates are also representative for the four provinces of Punjab, Sindh, Khyber Pakhtunkhwa, and Balochistan; for two regions including AJK and Gilgit Baltistan (GB); for Islamabad Capital Territory (ICT); and for FATA. In total, there are 13 secondlevel survey domains.

The 2017-18 PDHS followed a stratified two-stage sample design. The stratification was achieved by separating each of the eight regions into urban and rural areas. In total, 16 sampling strata were created. Samples were selected independently in every stratum through a two-stage selection process. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units at different levels, and by using a probability-proportional-to-size selection at the first stage of sampling.

The first stage involved selecting sample points (clusters) consisting of EBs. EBs were drawn with a probability proportional to their size, which is the number of households residing in the EB at the time of the census. A total of 580 clusters were selected.

The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected clusters, and a fixed number of 28 households per cluster was selected with an equal probability systematic selection process, for a total sample size of approximately 16,240 households. The household selection was carried out centrally at the NIPS data processing office. The survey teams only interviewed the pre-selected households. To prevent bias, no replacements and no changes to the pre-selected households were allowed at the implementing stages.

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

Mode of data collection

Face-to-face [f2f]

Research instrument

Six questionnaires were used in the 2017-18 PDHS: Household Questionnaire, Woman’s Questionnaire, Man’s Questionnaire, Biomarker Questionnaire, Fieldworker Questionnaire, and the Community Questionnaire. The first five questionnaires, based on The DHS Program’s standard Demographic and Health Survey (DHS-7) questionnaires, were adapted to reflect the population and health issues relevant to Pakistan. The Community Questionnaire was based on the instrument used in the previous rounds of the Pakistan DHS. Comments were solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. The survey protocol was reviewed and approved by the National Bioethics Committee, Pakistan Health Research Council, and ICF Institutional Review Board. After the questionnaires were finalised in English, they were translated into Urdu and Sindhi. The 2017-18 PDHS used paper-based questionnaires for data collection, while computerassisted field editing (CAFE) was used to edit the questionnaires in the field.

Cleaning operations

The processing of the 2017-18 PDHS data began simultaneously with the fieldwork. As soon as data collection was completed in each cluster, all electronic data files were transferred via IFSS to the NIPS central office in Islamabad. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors. Secondary editing was carried out in the central office, which involved resolving inconsistencies and coding the openended questions. The NIPS data processing manager coordinated the exercise at the central office. The PDHS core team members assisted with the secondary editing. Data entry and editing were carried out using the CSPro software package. The concurrent processing of the data offered a distinct advantage as it maximised the likelihood of the data being error-free and accurate. The secondary editing of the data was completed in the first week of May 2018. The final cleaning of the data set was carried out by The DHS Program data processing specialist and completed on 25 May 2018.

Response rate

A total of 15,671 households were selected for the survey, of which 15,051 were occupied. The response rates are presented separately for Pakistan, Azad Jammu and Kashmir, and Gilgit Baltistan. Of the 12,338 occupied households in Pakistan, 11,869 households were successfully interviewed, yielding a response rate of 96%. Similarly, the household response rates were 98% in Azad Jammu and Kashmir and 99% in Gilgit Baltistan.

In the interviewed households, 94% of ever-married women age 15-49 in Pakistan, 97% in Azad Jammu and Kashmir, and 94% in Gilgit Baltistan were interviewed. In the subsample of households selected for the male survey, 87% of ever-married men age 15-49 in Pakistan, 94% in Azad Jammu and Kashmir, and 84% in Gilgit Baltistan were successfully interviewed.

Overall, the response rates were lower in urban than in rural areas. The difference is slightly less pronounced for Azad Jammu and Kashmir and Gilgit Baltistan. The response rates for men are lower than those for women, as men are often away from their households for work.

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 2017-18 Pakistan Demographic and Health Survey (2017-18 PDHS) 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 2017-18 PDHS 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

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