Statistics on maternal mortality are produced based on the database of causes of death. "Maternal deaths" are selected from the database via a complex procedure, which takes into account the definition given by the WHO and is described in detail in the metadata. The tenth revision of the International Classification of Diseases (ICD-10) defines maternal death as "the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and the site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management, but not from accidental or incidental causes." "Maternal deaths should be subdivided into two groups. Direct obstetric deaths: those resulting from obstetric complications of the pregnant state (pregnancy, labour and puerperium), from interventions, omissions, incorrect treatment, or from a chain of events resulting from any of the above. Indirect obstetric deaths: those resulting from previous existing disease or disease that developed during pregnancy and which was not due to direct obstetric causes, but which was aggravated by physiologic effects of pregnancy." Furthermore, the ICD-10 also defines late maternal death as "the death of a woman from direct or indirect obstetric causes more than 42 days but less than one year after termination of pregnancy." The "maternal mortality rate" is the ratio between the number of recorded direct and indirect maternal deaths over one year and the number of live birth in the same year, expressed per 100,000 live births. Late maternal deaths are not taken into account in the calculation of this ratio. Given the small and markedly variable number of cases recorded each year in Belgium, it has been decided to calculate this ratio based on the cumulated maternal deaths and live births of five consecutive years, with the ratio calculated being recorded in the middle year. When identifying these maternal deaths, the ad hoc working group, bringing together the Belgian statistical office and all data producing federated entities, did not exclude the risk of an underestimation of these deaths, based on the only statistical bulletin used as main source. It therefore asks for continued efforts to further improve the follow-up of maternal deaths, and supports the recent initiative of the College of physicians for Mother and Newborn to consider the creation of a maternal mortality register.

Abstract

The 2019 Pakistan Maternal Mortality Survey (2019 PMMS) was the first stand-alone maternal mortality survey conducted in Pakistan. A nationally representative sample of 1,396 primary sampling units were randomly selected. The survey was expected to result in about 14,000 interviews with ever-married women age 15-49.

The primary objective of the 2019 PMMS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the survey was designed and carried out with the purpose of assessing where Pakistan stands on maternal health indicators and how well the country is moving toward these targets. Overall aims of the 2019 PMMS were as follows: - To estimate national and regional levels of maternal mortality for the 3 years preceding the survey and determine whether the MMR has declined substantially since 2006-07 - To identify medical causes of maternal deaths and the biological and sociodemographic risk factors associated with maternal mortality - To assess the impact of maternal and newborn health services, including antenatal and postnatal care and skilled birth attendance, on prevention of maternal mortality and morbidity - To estimate the prevalence and determinants of common obstetric complications and morbidities among women of reproductive age during the 3 years preceding the survey

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Woman age 15-49
• Community

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2019 PMMS used a multistage and multiphase cluster sampling methodology based on updated sampling frames derived from the 6th Population and Housing Census, which was conducted in 2017 by the Pakistan Bureau of Statistics (PBS). The sampling universe consisted of urban and rural areas of the four provinces of Pakistan (Punjab, Sindh, Khyber Pakhtunkhwa, and Balochistan), Azad Jammu and Kashmir (AJK), Gilgit Baltistan (GB), Federally Administered Tribal Areas (FATA), and the Islamabad Capital Territory (ICT). A total of 153,560 households (81,400 rural and 72,160 urban) were selected using a two-stage and two-phase stratified systematic sampling approach. The survey was designed to provide representative results for most of the survey indicators in 11 domains: four provinces (by urban and rural areas with Islamabad combined with Punjab and FATA combined with Khyber Pakhtunkhwa), Azad Jammu and Kashmir (urban and rural), and Gilgit Baltistan. Restricted military and protected areas were excluded from the sample.

The sampled households were randomly selected from 1,396 primary sampling units (PSUs) (740 rural and 656 urban) after a complete household listing. In each PSU, 110 randomly selected households were administered the various questionnaires included in the survey. All 110 households in each PSU were asked about births and deaths during the previous 3 years, including deaths among women of reproductive age (15-49 years). Households that reported at least one death of a woman of reproductive age were then visited, and detailed verbal autopsies were conducted to determine the causes and circumstances of these deaths to help identify maternal deaths. In the second phase, 10 households in each PSU were randomly selected from the 110 households selected in the first phase to gather detailed information on women of reproductive age. All eligible ever-married women age 15-49 residing in these 10 households were interviewed to gather detailed information, including a complete pregnancy history.

Note: A detailed description of the sample design is provided in Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Six questionnaires were used in the 2019 PMMS: the Short Household Questionnaire, the Long Household Questionnaire, the Woman’s Questionnaire, the Verbal Autopsy Questionnaire, the Community Questionnaire, and the Fieldworker Questionnaire. A Technical Advisory Committee was established to solicit comments on the questionnaires from various stakeholders, including representatives of government ministries and agencies, nongovernmental organisations, and international donors. The survey protocol was reviewed and approved by the National Bioethics Committee, the Pakistan Health Research Council, and the ICF Institutional Review Board. After being finalised in English, the questionnaires were translated into Urdu and Sindhi. The 2019 PMMS used paper-based questionnaires for data collection, while computer-assisted field editing (CAFE) was used to edit questionnaires in the field.

Cleaning operations

The processing of the 2019 PMMS data began simultaneously with the fieldwork. As soon as data collection was completed in each cluster, all electronic data files were transferred via the Internet File Streaming System (IFSS) to the NIPS central office in Islamabad. These data files were registered and checked for inconsistencies, incompleteness, and outliers. A double entry procedure was adopted by NIPS to ensure data accuracy. The field teams were alerted about any inconsistencies and errors. Secondary editing of completed questionnaires, which involved resolving inconsistencies and coding open-ended questions, was carried out in the central office. The survey core team members assisted with secondary editing, and the NIPS data processing manager coordinated the work at the central office. 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.

Response rate

In the four provinces, the sample contained a total of 116,169 households. All households were visited by the field teams, and 110,483 households were found to be occupied. Of these households, 108,766 were successfully interviewed, yielding a household response rate of 98%. The subsample selected for the Long Household Questionnaire comprised 11,080 households, and interviews were carried out in 10,479 of these households. A total of 12,217 ever-married women age 15-49 were eligible to be interviewed based on the Long Household Questionnaire, and 11,859 of these women were successfully interviewed (a response rate of 97%).

In Azad Jammu and Kashmir, 16,755 households were occupied, and interviews were successfully carried out in 16,588 of these households (99%). A total of 1,707 ever-married women were eligible for individual interviews, of whom 1,666 were successfully interviewed (98%). In Gilgit Baltistan, 11,005 households were occupied, and interviews were conducted in 10,872 households (99%). A total of 1,219 ever-married women were eligible for interviews, of whom 1,178 were successfully interviewed (97%).

A total of 944 verbal autopsy interviews were conducted in Pakistan overall, 150 in Azad Jammu and Kashmir, and 88 in Gilgit Baltistan. The Verbal Autopsy Questionnaire was used in almost all of the interviews, and response rates were nearly 100%.

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 Pakistan Maternal Mortality Survey (2019 PMMS) 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 PMMS is only one of many samples that could have been selected from the same population, using the same design and sample 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 by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2019 PMMS sample was the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed using SAS programmes developed by ICF. These programmes use the Taylor linearisation method to estimate variances for survey estimates that are means, proportions, or ratios and use the Jackknife repeated replication method for variance estimation of more complex statistics such as fertility and mortality rates.

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

Data appraisal

Data Quality Tables

- Household age distribution

Abstract

The 1992 Namibia Demographic and Health Survey (NDHS) is a nationally representative survey conducted by the Ministry of Health and Social Services, assisted by the Central Statistical Office, with the aim of gathering reliable information on fertility, family planning, infant and child mortality, maternal mortality, maternal and child health and nutrition. Interviewers collected information on the reproductive histories of 5,421 women 15-49 years and on the health of 3,562 children under the age of five years.

The Namibia Demographic and Health Survey (NDHS) is a national sample survey of women of reproductive age designed to collect data on mortality and fertility, socioeconomic characteristics, marriage patterns, breastfeeding, use of contraception, immunisation of children, accessibility to health and family planning services, treatment of children during episodes of illness, and the nutritional status of women and children. More specifically, the objectives of NDHS are: - To collect data at the national level which will allow the calculation of demographic rates, particularly fertility rates and child mortality rates, and maternal mortality rates; To analyse the direct and indirect factors which determine levels and trends in fertility and childhood mortality, Indicators of fertility and mortality are important in planning for social and economic development; - To measure the level of contraceptive knowledge and practice by method, region, and urban/rural residence; - To collect reliable data on family health: immunisations, prevalence and treatment of diarrhoea and other diseases among children under five, antenatal visits, assistance at delivery and breastfeeding; - To measure the nutritional status of children under five and of their mothers using anthropometric measurements (principally height and weight).

MAIN RESULTS

According to the NDHS, fertility is high in Namibia; at current fertility levels, Namibian women will have an average of 5.4 children by the end of their reproductive years. This is lower than most countries in sub-Saharan Africa, but similar to results from DHS surveys in Botswana (4.9 children per woman) and Zimbabwe (5.4 children per woman). Fertility in the South and Central regions is considerably lower (4.1 children per woman) than in the Northeast (6.0) and Northwest regions (6.7).

About one in four women uses a contraceptive method: 29 percent of married women currently use a method (26 percent use a modem method), and 23 percent of all women are current users. The pill, injection and female sterilisation are the most popular methods among married couples: each is used by about 7 to 8 percent of currently married women. Knowledge of contraception is high, with almost 90 percent of all women age 15-49 knowing of any modem method.

Certain groups of women are much more likely to use contraception than others. For example, urban women are almost four times more likely to be using a modem contraceptive method (47 percent) than rural women (13 percent). Women in the South and Central regions, those with more education, and those living closer to family planning services are also more likely to be using contraception.

Levels of fertility and contraceptive use are not likely to change until there is a drop in desired family size and until the idea of reproductive choice is more widely accepted. At present, the average ideal family size (5.0 children) is only slightly lower than the total fertility rate (5.4 children). Thus, the vast majority of births are wanted.

On average, Namibian women have their first child when they are about 21 years of age. The median age at first marriage is, however, 25 years. This indicates that many women give birth before marriage. In fact, married women are a minority in Namibia: 51 percent of women 15-49 were not married, 27 percent were currently married, 15 percent were currently living with a man (informal union), and 7 percent were widowed, divorced or separated. Therefore, a large proportion of children in Namibia are born out of wedlock.

The NDHS also provides inlbrmation about maternal and child health. The data indicate that 1 in 12 children dies before the fifth birthday. However, infant and child mortality have been declining over the past decade. Infant mortality has fallen from 67 deaths per 1,000 live births for the period 1983-87 to 57 per 1,000 live births for the period 1988-92, a decline of about 15 percent. Mortality is higher in the Northeast region than elsewhere in Namibia.

The leading causes of death are diarrhoea, undemutrition, acute respiratory infection (pneumonia) and malaria: each of these conditions was associated with about one-fifth of under-five deaths. Among neonatal deaths low birth weight and birth problems were the leading causes of death. Neonatal tetanus and measles were not lbund to be major causes of death.

Maternal mortality was estimated from reports on the survival status of sisters of the respondent. Maternal mortality was 225 per 100,000 live births for the decade prior to the survey. NDHS data also show considerable excess male mortality at ages 15-49, which may in part be related to the war of independence during the 1980s.

Utilisation of maternal and child health services is high. Almost 90 percent of mothers received antenatal care, and two-thirds of children were bom in health facilities. Traditional birth attendants assisted only 6 percent of births in the five years preceding the survey. Child vaccination coverage has increased rapidly since independence. Ninety-five percent of children age 12-23 months have received at least one vaccination, while 76 percent have received a measles vaccination, and 70 percent three doses of DPT and polio vaccines.

Children with symptoms of possible acute respiratory infection (cough and rapid breathing) may have pneumonia and need to be seen by a health worker. Among children with such symptoms in the two weeks preceding the survey two-thirds were taken to a health facility. Only children of mothers who lived more than 30 km from a health facility were less likely to be taken to a facility.

About one in five children had diarrhoea in the two weeks prior to the survey. Diarrhoea prevalence was very high in the Northeast region, where almost half of children reportedly had diarrhoea. The dysentery epidemic contributed to this high figure: diarrhoea with blood was reported for 17 percent of children under five in the Northeast region. Among children with diarrhoea in the last two weeks 68 percent were taken to a health facility, and 64 percent received a solution prepared from ORS packets. NDHS data indicate that more emphasis needs to put on increasing fluids during diarrhoea, since only I 1 percent mothers of children with diarrhoea said they increased the amount of fluids given during the episode.

Nearly all babies are breastfed (95 percent), but only 52 percent are put on the breast immediately. Exclusive breastfeeding is practiced for a short period, but not for the recommended 4-6 months. Most babies are given water, formula, or other supplements within the first four months of life, which both jeopardises their nutritional status and increases the risk of infection. On average, children are breastfed for about 17 months, but large differences exist by region. In the South region children are breastfed lor less than a year, in the Northwest region for about one and a half years and in the Northeast region for almost two years.

Most babies are weighed at birth, but the actual birth weight could be recalled for only 44 percent of births. Using these data and data on reported size of the newborn, for all births in the last five years, it was estimated that the mean birth weight in Namibia is 3048 grams, and that 16 percent of babies were low birth weight (less than 2500 grams).

Stunting, an indication of chronic undemutrition, was observed for 28 percent of children under five. Stunting was more common in the Northeast region (42 percent) than elsewhere in Namibia. Almost 9 percent of children were wasted, which is an indication of acute undemutrition. Wasting is higher than expected for Namibia and may have been caused by the drought conditions during 1992.

Matemal height is an indicator of nutritional status over generations. Women in Namibia have an average height of 160 cm and there is little variation by region. The Body Mass Index (BM1), defined as weight divided by squared height, is a measure of current nutritional status and was lower among women in the Northwest and the Northeast regions than among women in the South and Central regions.

On average, women had a health facility available within 40 minutes travel time. Women in the Northwest region, however, had to travel more than one hour to reach the nearest health facility. At a distance of less than 10 km, 56 percent of women had access to antenatal services, 48 percent to maternity services, 72 percent to immunisation services, and 49 percent to family planning services. Within one hour of travel time, fifty-two percent of women had antenatal services, 48 percent delivery services, 64 percent immunisation services and 49 percent family planning services. Distance and travel time were greatest in the Northwest region.

Geographic coverage

The sample for the NDHS was designed to be nationally representative. The design involved a two- stage stratified sample which is self-weighting within each of the three health regions for which estimates of fertility and mortality were required--Northwest, Northeast, and the combined Central/South region. In order to have a sufficient number of cases for analysis, oversampling was necessary for the Northeast region, which has only 14.8 percent of the population. Therefore, the sample was not allocated proportionally across regions and is not completely

The primary objective of the 2016 Nepal Demographic and Health Survey (NDHS) is to provide up-to-date estimates of basic demographic and health indicators. The NDHS provides a comprehensive overview of population, maternal, and child health issues in Nepal. Specifically, the 2016 NDHS: Collected data that allowed calculation of key demographic indicators, particularly fertility and under-5 mortality rates, at the national level, for urban and rural areas, and for the country’s seven provinces Collected data that allowed for calculation of adult and maternal mortality rates at the national level Explored the direct and indirect factors that determine levels and trends of fertility and child mortality Measured levels of contraceptive knowledge and practice Collected data on key aspects of family health, including immunization coverage among children, prevalence and treatment of diarrhea and other diseases among children under age 5, maternity care indicators such as antenatal visits and assistance at delivery, and newborn care Obtained data on child feeding practices, including breastfeeding Collected anthropometric measures to assess the nutritional status of children under age 5 and women and men age 15-49 Conducted hemoglobin testing on eligible children age 6-59 months and women age 15-49 to provide information on the prevalence of anemia in these groups Collected data on knowledge and attitudes of women and men about sexually transmitted diseases and HIV/AIDS and evaluated potential exposure to the risk of HIV infection by exploring high-risk behaviors and condom use Measured blood pressure among women and men age 15 and above Obtained data on women’s experience of emotional, physical, and sexual violence The information collected through the 2016 NDHS is intended to assist policymakers and program managers in the Ministry of Health and other organizations in designing and evaluating programs and strategies for improving the health of the country’s population. The 2016 NDHS also provides data on indicators relevant to the Nepal Health Sector Strategy (NHSS) 2016-2021 and the Sustainable Development Goals (SDGs).

Abstract

The 1997 Yemen Demographic Maternal and Child Health Survey (YDMCHS) is part of the worldwide Demographic and Health Surveys (DHS) program. The DHS program is designed to collect data on fertility, family planning and maternal and child health.

The YDMCHS-97 has the following objectives: 1. Provide policymakers and decisionmakers with a reliable database and analyses useful for policy choices and population programs, and provide researchers, other interested persons, and scholars with such data. 2. Update and expand the national population and health data base through collection of data which will allow the calculation of demographic rates, especially fertility rates, and infant and child mortality rates; 3. Analyse the direct and indirect factors which determine levels and trends of fertility. Indicators related to fertility will serve to elaborate plans for social and economic development; 4. Measure the level of contraceptive knowledge and practice by method, by rural and urban residence including some homogeneous governorates (Sana’a, Aden, Hadhramaut, Hodeidah, Hajjah and Lahj). 5. Collect quality data on family health: immunizations, prevalence and treatment of diarrhea and other diseases among children under five, prenatal visits, assistance at delivery and breastfeeding; 6. Measure the nutritional status of mothers and their children under five years (anthropometric measurements: weight and height); 7. Measure the level of maternal mortality at the national level. 8. Develop skills and resources necessary to conduct high-quality demographic and health surveys.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE DESIGN

The 1997 YDMCHS was based on a national sample in order to provide estimates for general indicators for the following domains: Yemen as a whole, urban and rural areas (each as a separate domain), three ecological zones identified as Coastal, Mountainous, and Plateau and Desert, as well as governorates with a sample size of at least 500 completed cases. The survey sample was designed as a two-stage cluster sample of 475 enumeration areas (EA), 135 in urban areas and 340 in rural areas. The master sample, based on the 1994 census frame, was used as the frame for the 1997 YDMCHS. The population covered by the Yemen survey was the universe of all ever-married women age 15-49. The initial target sample was 10,000 completed interviews among eligible women, and the final sample was 10,414. In order to get this number of completed interviews, and using the response rate found in the 1991-92 YDMCHS survey, a total of 10,701 of the 11,435 potential households selected for the household sample were completed.

In each selected EA, a complete household listing operation took place between July and September 1997, and was undertaken by nineteen (19) field teams, taking into consideration the geographical closeness of the areas assigned to each team.

Note: See detailed description of sample design in APPENDIX B of the final survey report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two Questionnaires were used to collect survey data:

Household Questionnaire: The household questionnaire consists of two parts: a household schedule and a series of questions relating to the health and socioeconomic status of the household. The household schedule was used to list all usual household members. For each of the individuals included in the schedule, information was collected on the relationship to the household head, age, sex, marital status (for those 10 years and older), educational level (for those 6 years and older) and work status (for those 10 years and older). It also collects information on fertility, general mortality and child survival. The second part of the household questionnaire included questions on housing characteristics including the type of dwelling, location, materials used in construction, number of rooms, kitchen in use, main source of drinking water and health related aspects, lighting and toilet facilities, disposal of garbage, durable commodities, and assets, type of salt the household uses for cooking, and other related residential information.

Individual Questionnaire: The individual questionnaire was administered to all ever-married women age 15-49 years who were usual residents. It contained 10 sections on the followings topics: - Respondent's background - Reproduction - Family planning - Pregnancy and breastfeeding - Immunization and health - Birth preferences - Marriage and husband's background - Maternal mortality - Female circumcision - Height and weight

Response rate

10,701 households, distributed between urban (3,008 households) and rural areas (7,693), households which were successfully interviewed in the 1997 YDMCHS. This represents a country-wide response rate of 98.2 percent (98.7 and 98.0 percent, respectively, for urban and rural areas).

A total of 11,158 women were identified as eligible to be interviewed. Questionnaires were completed for 10,414 women, which represents a response rate of 93.3 percent. The response rate in urban areas was 93 percent; and in rural areas it was 93.5 percent.

Note: See summarized response rates by place of residence in Table 1.1 of the final survey report.

Sampling error estimates

The estimates from a sample surveys are affected by two types of errors: (1) non-sampling error, and (2) sampling error. Non-sampling 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 YDMCHS-97 to minimize this type of error, non-sampling 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 YDMCHS-97 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 have yielded results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of standard error of 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 statistics in 95 percent of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the YDMCHS-97 sample is the result of a two-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the YDMCHS-97 is the ISSA Sampling Error Module (SAMPERR). This module used the Taylor linearization method of variance estimate for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimate of more complex statistics such as fertility and mortality rates.

Note: See detailed estimate of sampling error calculation in APPENDIX C of the final survey report.

Data appraisal

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

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

IntroductionWith high burden of maternal mortality and stagnant neonatal mortality, maternal and newborn health services have remained a priority program for Nepal. This study aims to assess the determinants of four or more antenatal care (≥4 ANC) visits, institutional delivery (ID), postnatal care (PNC) visit for mother and newborn within the first two days of delivery and the continuum of care.MethodsWe performed weighted analysis of Nepal Demographic and Health Survey (NDHS) 2022 data accounting for complex survey design. The NDHS is a nationally representative cross-sectional survey that employs a two-stage stratified sampling technique to select participants. We analyzed data from 1,891 women who had live births within two years prior to the survey. Distribution of variables are described using frequency, percentage, and 95% confidence intervals (CI). We performed bivariate and multivariable logistic regression and the results are presented in crude odds ratio (COR), adjusted odds ratio (AOR) and 95% CI.ResultsIn the study, 80.62% (95% CI: 77.95, 83.03) of participants had ≥ 4 ANC visits, 79.37% (95% CI: 76.68, 81.82) had ID, and 62.56% (95% CI: 56.67, 65.36) received PNC for mother and newborn within two days of delivery. Likewise, 67.59% (95% CI: 64.59, 70.45) had both ≥ 4 ANC visits and ID, while 51.01% (95% CI: 48.08, 53.93) had all three components of the continuum of care: ≥ 4 ANC visits, ID, and PNC visit within two days of delivery. The richest wealth quintile participants had three folds higher odds (AOR: 2.98, 95% CI: 1.83, 4.83) of completing continuum of care, while the odds were two folds (AOR: 2.04, 95% CI: 1.41, 2.94) higher for richer wealth quintile participants. Participants with birth order three or more had lower odds (AOR: 0.50, 95% CI: 0.36, 0.69) of completing all three continuum of care components. Among other variables associated with continuum of care were province, distance to facility and internet use.ConclusionSignificant disparities exist in continuum of care or its components based on wealth quintile, province, and place of residence. Tackling economic gaps, provincial disparities, and leveraging technology are crucial for ensuring fair access to essential maternal health services. Nepal’s transition to a federal structure with 7 provinces and 753 local governments with decision making authority presents an opportunity to test and scale up innovative strategies for improving continuum of care coverage.

The EDHS is part of the worldwide Demographic and Health Surveys (DHS) program, which is designed to collect data on fertility, family planning, and maternal and child health. The main objective of the EDHS is to provide policymakers and programme formulators in population and health with adequate and reliable information. The EDHS collected information on demographic characteristics, fertility, infant and child mortality, maternal mortality, nuptiality, fertility preferences, family planning and health-related matters such as breastfeeding practices, antenatal care, children's immunization, childhood disease, nutritional status of mothers and young children and awareness and behaviour regarding sexually transmitted diseases including AIDS. The objectives of the EDHS are to: Collect data at the national level which will allow the calculation of demographic rates, particularly fertility and childhood mortality rates; Analyze the direct and indirect factors which determine levels and trends of fertility; Measure the level of contraceptive knowledge and practice (women and men) by urban-rural residence; Collect reliable data on maternal and child health indicators: immunizations, prevalence and treatment of diarrhea and diseases among children under age three, antenatal care visits, assistance at delivery, and breastfeeding; Assess the nutritional status of children under age three, and their mothers, by means of anthropometric measurements (height and weight ) and analysis of child feeding practices; and Assess the prevailing level of specific knowledge and attitudes regarding AIDS and to evaluate patterns of recent behavior regarding condom use, among women and men.

Maternal Infant Care Product Market Outlook

The global maternal infant care product market size was valued at USD 24 billion in 2023 and is projected to reach USD 42 billion by 2032, growing at a compound annual growth rate (CAGR) of 6.5%. This growth can be attributed primarily to rising awareness about maternal and infant health, increasing disposable incomes, and technological advancements in healthcare products.

One of the key growth factors driving the maternal infant care product market is the increasing awareness and education regarding maternal and infant health. This trend is largely influenced by government initiatives, non-profit organizations, and healthcare providers who are focused on reducing infant mortality rates and enhancing maternal health outcomes. Educational campaigns and community health programs are playing a significant role in encouraging young mothers to adopt better prenatal and postnatal care practices, thereby boosting the demand for specialized maternal and infant care products.

The economic development in emerging markets has also contributed significantly to market growth. With the rise in disposable incomes, there is a growing willingness among consumers to invest in high-quality healthcare products, including maternal and infant care items. Furthermore, urbanization has brought about changes in lifestyle, leading to a greater demand for convenience products such as breast pumps and baby monitors that offer modern solutions for busy parents. This shift towards premium products is also evident in more developed markets, where consumers are increasingly opting for top-of-the-line brands that promise safety and efficacy.

Technological advancements in healthcare are another pivotal growth factor. Innovations such as smart baby monitors, which provide real-time data on a baby’s health, and advanced breast pumps designed for efficiency and comfort, are attracting a significant number of consumers. The integration of IoT and AI in these products is providing parents with enhanced capabilities for monitoring and ensuring the well-being of their infants, thereby fostering market growth. Additionally, advancements in the formulation of infant formula and prenatal vitamins are addressing specific nutritional needs, further driving the market.

From a regional perspective, North America currently dominates the maternal infant care product market, followed closely by Europe and Asia Pacific. North America’s leadership position is underpinned by high healthcare expenditure, robust healthcare infrastructure, and the presence of major market players. Europe’s growth is driven by similar factors, along with supportive government policies. The Asia Pacific region is expected to witness the fastest growth, attributed to its large population base, improving healthcare facilities, and increasing awareness about maternal and infant health.

Product Type Analysis

The prenatal vitamins segment holds a significant share within the maternal infant care product market. This segment's growth is primarily driven by heightened awareness about the importance of prenatal nutrition. Pregnant women are increasingly understanding the benefits of vitamins and minerals in ensuring a healthy pregnancy and fetal development. Health practitioners are also actively recommending these supplements, which has led to a surge in demand. Moreover, advancements in the formulation of prenatal vitamins, tailored to address specific nutritional deficiencies, are further propelling growth in this segment.

Breast pumps represent another vital segment in the maternal infant care product market. The increasing number of working mothers globally has significantly boosted the demand for breast pumps. These devices offer a convenient solution for nursing mothers to express and store milk, ensuring that their babies can be fed breast milk even when they are not around. Technological advancements in breast pump designs, aimed at enhancing comfort and efficiency, have further fueled market growth. Additionally, government initiatives in several countries to promote breastfeeding are positively impacting this segment.

Infant formula is yet another crucial segment, driven by its vital role in infant nutrition, especially for mothers who cannot breastfeed. The increasing number of working mothers and the rising awareness of the nutritional benefits of infant formula are key factors contributing to its growth. Manufacturers are focusing on developing advanced formulations that closely mimic breast milk, thereby attracting a larger consumer bas

The global pregnancy milk powder market is experiencing robust growth, driven by increasing awareness of the nutritional benefits of specialized milk powders for expectant and nursing mothers. The market, estimated at $15 billion in 2025, is projected to grow at a compound annual growth rate (CAGR) of 7% from 2025 to 2033, reaching approximately $25 billion by 2033. This expansion is fueled by several key factors. Rising disposable incomes in developing economies are increasing the affordability of premium nutritional products like pregnancy milk powder. Furthermore, heightened awareness regarding maternal and child health, coupled with aggressive marketing campaigns by major players like Abbott, Nestlé, and Meiji, is driving consumer demand. The increasing prevalence of gestational diabetes and other pregnancy-related complications is also contributing to the market's growth, as these specialized powders often contain formulations tailored to address specific nutritional needs. Market segmentation reveals strong demand for organic and fortified options, reflecting a growing preference for natural and healthier products. Competitive rivalry is intense, with established multinational corporations and regional players constantly vying for market share through product innovation, strategic partnerships, and expansion into new markets. The market's growth is not without challenges. Fluctuations in raw material prices, particularly dairy products, can impact profitability. Stringent regulatory requirements regarding product labeling and safety standards can also pose hurdles for manufacturers. However, the long-term outlook for the pregnancy milk powder market remains positive, driven by sustained growth in the global population, increasing urbanization, and a rising focus on maternal and child well-being. Regional variations exist, with developed markets exhibiting mature growth patterns while emerging economies demonstrate significant potential for future expansion. Key players are expected to continue investing in research and development to create innovative products catering to evolving consumer preferences and address the unmet needs within the market. The focus on traceability, sustainability, and ethical sourcing of ingredients will also be crucial for sustained success in this rapidly evolving market segment.

Maternal and Child Health Food Market Outlook

The global market size for maternal and child health food was valued at approximately USD 35 billion in 2023 and is projected to reach an estimated USD 60 billion by 2032, growing at a compound annual growth rate (CAGR) of 6.5% during the forecast period. The growth of this market is driven by increasing awareness about the importance of nutrition during pregnancy and early childhood, coupled with rising disposable incomes and changing lifestyles.

One of the primary growth factors for the maternal and child health food market is the increasing awareness among parents about the importance of proper nutrition during the critical stages of growth and development. Governments and non-governmental organizations are also playing a crucial role in educating people about the benefits of balanced diets and nutritional supplements for both mothers and children. This has led to a surge in demand for health foods that are specifically designed to meet the nutritional needs of pregnant women, lactating mothers, infants, and toddlers.

Another significant factor contributing to the market's growth is the rise in disposable incomes, particularly in emerging economies. As more families achieve higher income levels, they are more willing and able to invest in quality health foods for their children. Moreover, the increasing urbanization and changing lifestyles have led to a higher preference for convenient, ready-to-consume health foods. This shift in consumer behavior is further bolstered by the availability of a wide range of products that cater to different nutritional needs and preferences.

The advancements in food technology and the increasing focus on organic and natural ingredients are also important drivers for the market. Consumers are becoming more health-conscious and are looking for products that are free from artificial additives, preservatives, and genetically modified organisms (GMOs). This has led to a rise in the demand for organic and natural health foods for both mothers and children. The growing trend of clean labeling, where manufacturers provide detailed information about the ingredients and nutritional content of their products, is also positively impacting the market.

On a regional level, the Asia Pacific region is expected to witness significant growth in the maternal and child health food market. The increasing population, coupled with the rising awareness about the importance of maternal and child nutrition, is driving the demand in this region. Additionally, the presence of a large number of local and international manufacturers and the growing middle-class population are contributing to the market's expansion. North America and Europe are also key markets, driven by high consumer awareness and the availability of a wide range of products.

Product Type Analysis

The product type segment of the maternal and child health food market can be classified into infant formula, baby snacks, maternal nutrition, lactation supplements, and others. Infant formula holds a substantial share in this segment, driven by the growing number of working mothers who seek convenient and nutritious alternatives to breastfeeding. The advancements in infant formula, including the addition of essential nutrients like DHA and ARA, make it a preferred choice for many parents. Moreover, the availability of specialized formulas catering to specific health needs, such as lactose intolerance and allergies, further boosts its demand.

Baby snacks are another crucial segment that is witnessing significant growth. These snacks are designed to provide essential nutrients and energy for growing children. The increasing demand for on-the-go, healthy snack options is driving the growth of this segment. Parents are looking for convenient, nutritious snacks that can be easily incorporated into their child's diet. The wide variety of options available, including organic and gluten-free snacks, caters to different dietary preferences and needs.

Maternal nutrition products are specifically designed to meet the nutritional requirements of pregnant and lactating women. These products include prenatal vitamins, protein supplements, and other specialized foods that help ensure the health and well-being of both mothers and their babies. The growing awareness about the importance of proper nutrition during pregnancy and breastfeeding is driving the demand for these products. Additionally, the increasing availability of these products through various distribution channels is making them more accessible to a

IntroductionWith high burden of maternal mortality and stagnant neonatal mortality, maternal and newborn health services have remained a priority program for Nepal. This study aims to assess the determinants of four or more antenatal care (≥4 ANC) visits, institutional delivery (ID), postnatal care (PNC) visit for mother and newborn within the first two days of delivery and the continuum of care.MethodsWe performed weighted analysis of Nepal Demographic and Health Survey (NDHS) 2022 data accounting for complex survey design. The NDHS is a nationally representative cross-sectional survey that employs a two-stage stratified sampling technique to select participants. We analyzed data from 1,891 women who had live births within two years prior to the survey. Distribution of variables are described using frequency, percentage, and 95% confidence intervals (CI). We performed bivariate and multivariable logistic regression and the results are presented in crude odds ratio (COR), adjusted odds ratio (AOR) and 95% CI.ResultsIn the study, 80.62% (95% CI: 77.95, 83.03) of participants had ≥ 4 ANC visits, 79.37% (95% CI: 76.68, 81.82) had ID, and 62.56% (95% CI: 56.67, 65.36) received PNC for mother and newborn within two days of delivery. Likewise, 67.59% (95% CI: 64.59, 70.45) had both ≥ 4 ANC visits and ID, while 51.01% (95% CI: 48.08, 53.93) had all three components of the continuum of care: ≥ 4 ANC visits, ID, and PNC visit within two days of delivery. The richest wealth quintile participants had three folds higher odds (AOR: 2.98, 95% CI: 1.83, 4.83) of completing continuum of care, while the odds were two folds (AOR: 2.04, 95% CI: 1.41, 2.94) higher for richer wealth quintile participants. Participants with birth order three or more had lower odds (AOR: 0.50, 95% CI: 0.36, 0.69) of completing all three continuum of care components. Among other variables associated with continuum of care were province, distance to facility and internet use.ConclusionSignificant disparities exist in continuum of care or its components based on wealth quintile, province, and place of residence. Tackling economic gaps, provincial disparities, and leveraging technology are crucial for ensuring fair access to essential maternal health services. Nepal’s transition to a federal structure with 7 provinces and 753 local governments with decision making authority presents an opportunity to test and scale up innovative strategies for improving continuum of care coverage.

BackgroundPerinatal mortality rate is one of indictors used to measure the quality of obstetric and pediatric services globally. Compared to developed settings, perinatal mortality rate is higher in low-income countries, indicating societal inequities in health care and a scarcity of prenatal services. It is responsible for roughly 42% of all stillbirth in Sub-Saharan Africa, and 41% of newborn death globally. Despite Ethiopia’s efforts to reduce perinatal mortality by improving the quality of care for maternal and child health, perinatal mortality rate is still very high, and as to our search of pieces of literature there is no study in Emerging regions of the country. Therefore, this study aimed to assess the factors that contribute to perinatal mortality rate in emerging region (Afar, Gambela, Somali, and Benishangul Gumuz) of Ethiopia’s.MethodsThis study relied on data from the 2016 Ethiopian Demographic and Health Survey (EDHS). The analysis included the outcomes of 4, 070 pregnancies with a gestational age of 7 months or more. A multi-level mixed logistic regression analysis was used to examine individual and community-level predictors, accounting for the data’s hierarchical structure. A statistically significant association was determined with a p-value of ≤ 0.05.ResultsOf the 4,070 (weighted) pregnancies in total, 432 (57.36%) children were born to women with a mean age of 28.68 ± 6.53 (ages ± SD). The overall perinatal mortality rate in emerging regions of Ethiopia was 36 deaths per 1,000 pregnancies. The study found that having a birth interval < 2 years (AOR = 3.2, 95% CI: 1.51, 6.59), maternal age greater than or equal to 35 (AOR = 4.3, 95% CI: 1.84, 10.14), drinking an unimproved water source (AOR = 2.7, 95% CI: 1.14, 6.27), and mothers with no education (AOR = 0.33, 95% CI: 0.13, 0.86) were factors significantly associated with a high odds of perinatal mortality rate.ConclusionThis study revealed a higher perinatal mortality rate as compared to national average. Maternal age, drinking an unimproved water source, and birth interval were significantly associated with perinatal deaths. Despite the enhanced effort to improve maternal and child services, there is still a need for more attention to these interconnected issues helps to reduce effectively the perinatal mortality rate in emerging regions of Ethiopia. Future researchers may benefit from focusing on strong study designs to investigate further the determinants of perinatal mortality, and policymakers good to pay special attention to incorporating the findings into policy.

Factors associated with the requirement for massive transfusion in patients with primary postpartum hemorrhage in multivariate analysis.

The global market for water specifically formulated for mothers and infants is experiencing robust growth, driven by increasing awareness of hydration's importance during pregnancy and infancy, coupled with rising disposable incomes in developing economies. The market, currently estimated at $5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033, reaching approximately $9 billion by 2033. This growth is fueled by several key factors. Firstly, the rising prevalence of maternal and child health awareness campaigns emphasizes the crucial role of proper hydration in supporting healthy pregnancies and infant development. Secondly, the increasing adoption of premium and specialized infant formulas, often including recommendations for complementary hydration with specialized water, contributes significantly. Furthermore, the expanding availability of fortified waters tailored to meet the specific nutritional needs of mothers and infants in supermarkets and online channels broadens market reach. Key players such as Nestle, Wahaha, and Nongfu Spring are leading the market, investing heavily in research and development to introduce innovative products with enhanced nutritional profiles and convenient packaging. However, market growth is not without its challenges. Regulatory hurdles surrounding product labeling and claims, varying consumer preferences across different regions, and the potential for substitution with other hydrating beverages like breast milk or formula represent key restraints. Market segmentation primarily revolves around product type (purified water, mineral water, fortified water), packaging (bottles, pouches), distribution channel (online, offline), and geographic location. While developed markets like North America and Europe already boast a considerable market presence, developing economies in Asia and Africa are emerging as significant growth opportunities, offering substantial potential for expansion as incomes rise and health awareness improves. Companies are leveraging digital marketing and strategic partnerships with healthcare providers to further penetrate these markets and build brand loyalty. The forecast period of 2025-2033 presents a promising outlook, with continued growth expected as the focus on maternal and infant well-being strengthens globally.

Baseline data for the Kybele-GHS partnership.

Abstract

The 2016 Timor-Leste Demographic and Health Survey (TLDHS) was implemented by the General Directorate of Statistics (GDS) of the Ministry of Finance in collaboration with the Ministry of Health (MOH). Data collection took place from 16 September to 22 December, 2016.

The primary objective of the 2016 TLDHS project is to provide up-to-date estimates of basic demographic and health indicators. The TLDHS provides a comprehensive overview of population, maternal, and child health issues in Timor-Leste. More specifically, the 2016 TLDHS: • Collected data at the national level, which allows the calculation of key demographic indicators, particularly fertility, and child, adult, and maternal mortality rates • Provided data to explore the direct and indirect factors that determine the levels and trends of fertility and child mortality • Measured the levels of contraceptive knowledge and practice • Obtained data on key aspects of maternal and child health, including immunization coverage, prevalence and treatment of diarrhea and other diseases among children under age 5, and maternity care, including antenatal visits and assistance at delivery • Obtained data on child feeding practices, including breastfeeding, and collected anthropometric measures to assess nutritional status in children, women, and men • Tested for anemia in children, women, and men • Collected data on the knowledge and attitudes of women and men about sexually-transmitted diseases and HIV/AIDS, potential exposure to the risk of HIV infection (risk behaviors and condom use), and coverage of HIV testing and counseling • Measured key education indicators, including school attendance ratios, level of educational attainment, and literacy levels • Collected information on the extent of disability • Collected information on non-communicable diseases • Collected information on early childhood development • Collected information on domestic violence • The information collected through the 2016 TLDHS is intended to assist policy makers and program managers in evaluating and designing programs and strategies for improving the health of the country’s population.

Geographic coverage

National

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), 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 sampling frame used for the TLDHS 2016 survey is the 2015 Timor-Leste Population and Housing Census (TLPHC 2015), provided by the General Directorate of Statistics. The sampling frame is a complete list of 2320 non-empty Enumeration Areas (EAs) created for the 2015 population census. An EA is a geographic area made up of a convenient number of dwelling units which served as counting units for the census, with an average size of 89 households per EA. The sampling frame contains information about the administrative unit, the type of residence, the number of residential households and the number of male and female population for each of the EAs. Among the 2320 EAs, 413 are urban residence and 1907 are rural residence.

There are five geographic regions in Timor-Leste, and these are subdivided into 12 municipalities and special administrative region (SAR) of Oecussi. The 2016 TLDHS sample was designed to produce reliable estimates of indicators for the country as a whole, for urban and rural areas, and for each of the 13 municipalities. A representative probability sample of approximately 12,000 households was drawn; the sample was stratified and selected in two stages. In the first stage, 455 EAs were selected with probability proportional to EA size from the 2015 TLPHC: 129 EAs in urban areas and 326 EAs in rural areas. In the second stage, 26 households were randomly selected within each of the 455 EAs; the sampling frame for this household selection was the 2015 TLPHC household listing available from the census database.

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 for the 2016 TLDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. These questionnaires, based on The DHS Program’s standard Demographic and Health Survey questionnaires, were adapted to reflect the population and health issues relevant to Timor-Leste.

Cleaning operations

The data processing operation included registering and checking for inconsistencies, incompleteness, and outliers. Data editing and cleaning included structure and consistency checks to ensure completeness of work in the field. The central office also conducted secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by two staff who took part in the main fieldwork training. Data editing was accomplished with CSPro software. Secondary editing and data processing were initiated in October 2016 and completed in February 2017.

Response rate

A total of 11,829 households were selected for the sample, of which 11,660 were occupied. Of the occupied households, 11,502 were successfully interviewed, which yielded a response rate of 99 percent.

In the interviewed households, 12,998 eligible women were identified for individual interviews. Interviews were completed with 12,607 women, yielding a response rate of 97 percent. In the subsample of households selected for the men’s interviews, 4,878 eligible men were identified and 4,622 were successfully interviewed, yielding a response rate of 95 percent. Response rates were higher in rural than in urban areas, with the difference being more pronounced among men (97 percent versus 90 percent, respectively) than among women (98 percent versus 94 percent, respectively). The lower response rates for men were likely due to their more frequent and longer absences from the household.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling 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 TLDHS 2016 to minimize this type of error, non-sampling 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 TLDHS 2016 is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the TLDHS 2016 sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the TLDHS 2016 is a SAS program. This program used the Taylor linearization method of variance estimation 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 - Height and weight data completeness and quality for children - Completeness of information on siblings - Sibship size and sex ratio of siblings - Pregnancy-related mortality trends

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

The Pakistan Demographic and Health Survey (PDHS) was fielded on a national basis between the months of December 1990 and May 1991. The survey was carried out by the National Institute of Population Studies with the objective of assisting the Ministry of Population Welfare to evaluate the Population Welfare Programme and maternal and child health services. The PDHS is the latest in a series of surveys, making it possible to evaluate changes in the demographic status of the population and in health conditions nationwide. Earlier surveys include the Pakistan Contraceptive Prevalence Survey of 1984-85 and the Pakistan Fertility Survey of 1975. The primary objective of the Pakistan Demographic and Health Survey (PDHS) was to provide national- and provincial-level data on population and health in Pakistan. The primary emphasis was on the following topics: fertility, nuptiality, family size preferences, knowledge and use of family planning, the potential demand for contraception, the level of unwanted fertility, infant and child mortality, breastfeeding and food supplementation practices, maternal care, child nutrition and health, immunisations and child morbidity. This information is intended to assist policy makers, administrators and researchers in assessing and evaluating population and health programmes and strategies. The PDHS is further intended to serve as a source of demographic data for comparison with earlier surveys, particularly the 1975 Pakistan Fertility Survey (PFS) and the 1984-85 Pakistan Contraceptive Prevalence Survey (PCPS). MAIN RESULTS Until recently, fertility rates had remained high with little evidence of any sustained fertility decline. In recent years, however, fertility has begun to decline due to a rapid increase in the age at marriage and to a modest rise in the prevalence of contraceptive use. The lotal fertility rate is estimated to have fallen from a level of approximately 6.4 children in the early 1980s to 6.0 children in the mid-1980s, to 5.4 children in the late 1980s. The exact magnitude of the change is in dispute and will be the subject of further research. Important differentials of fertility include the degree ofurbanisation and the level of women's education. The total fertility rate is estimated to be nearly one child lower in major cities (4.7) than in rural areas (5.6). Women with at least some secondary schooling have a rate of 3.6, compared to a rate of 5.7 children for women with no formal education. There is a wide disparity between women's knowledge and use of contraceptives in Pakistan. While 78 percent of currently married women report knowing at least one method of contraception, only 21 percent have ever used a method, and only 12 percent are currently doing so. Three-fourths of current users are using a modem method and one-fourth a traditional method. The two most commonly used methods are female sterilisation (4 percent) and the condom (3 percent). Despite the relatively low level of contraceptive use, the gain over time has been significant. Among married non-pregnant women, contraceptive use has almost tripled in 15 years, from 5 percent in 1975 to 14 percent in 1990-91. The contraceptive prevalence among women with secondary education is 38 percent, and among women with no schooling it is only 8 percent. Nearly one-third of women in major cities arc current users of contraception, but contraceptive use is still rare in rural areas (6 percent). The Government of Pakistan plays a major role in providing family planning services. Eighty-five percent of sterilised women and 81 percent of IUD users obtained services from the public sector. Condoms, however, were supplied primarily through the social marketing programme. The use of contraceptives depends on many factors, including the degree of acceptability of the concept of family planning. Among currently married women who know of a contraceptive method, 62 percent approve of family planning. There appears to be a considerable amount of consensus between husbands and wives about family planning use: one-third of female respondents reported that both they and their husbands approve of family planning, while slightly more than one-fifth said they both disapprove. The latter couples constitute a group for which family planning acceptance will require concerted motivational efforts. The educational levels attained by Pakistani women remain low: 79 percent of women have had no formal education, 14 percent have studied at the primary or middle school level, and only 7 percent have attended at least some secondary schooling. The traditional social structure of Pakistan supports a natural fertility pattern in which the majority of women do not use any means of fertility regulation. In such populations, the proximate determinants of fertility (other than contraception) are crucial in determining fertility levels. These include age at marriage, breastfeeding, and the duration of postpartum amenorrhoea and abstinence. The mean age at marriage has risen sharply over the past few decades, from under 17 years in the 1950s to 21.7 years in 1991. Despite this rise, marriage remains virtually universal: among women over the age of 35, only 2 percent have never married. Marriage patterns in Pakistan are characterised by an unusually high degree of consangninity. Half of all women are married to their first cousin and an additional 11 percent are married to their second cousin. Breasffeeding is important because of the natural immune protection it provides to babies, and the protection against pregnancy it gives to mothers. Women in Pakistan breastfeed their children for an average of20months. Themeandurationofpostpartumamenorrhoeais slightly more than 9 months. After tbebirth of a child, women abstain from sexual relations for an average of 5 months. As a result, the mean duration of postpartum insusceptibility (the period immediately following a birth during which the mother is protected from the risk of pregnancy) is 11 months, and the median is 8 months. Because of differentials in the duration of breastfeeding and abstinence, the median duration of insusceptibility varies widely: from 4 months for women with at least some secondary education to 9 months for women with no schooling; and from 5 months for women residing in major cities to 9 months for women in rural areas. In the PDHS, women were asked about their desire for additional sons and daughters. Overall, 40 percent of currently married women do not want to have any more children. This figure increases rapidly depending on the number of children a woman has: from 17 percent for women with two living children, to 52 percent for women with four children, to 71 percent for women with six children. The desire to stop childbearing varies widely across cultural groupings. For example, among women with four living children, the percentage who want no more varies from 47 percent for women with no education to 84 percent for those with at least some secondary education. Gender preference continues to be widespread in Pakistan. Among currently married non-pregnant women who want another child, 49 percent would prefer to have a boy and only 5 percent would prefer a girl, while 46 percent say it would make no difference. The need for family planning services, as measured in the PDHS, takes into account women's statements concerning recent and future intended childbearing and their use of contraceptives. It is estimated that 25 percent of currently married women have a need for family planning to stop childbearing and an additional 12 percent are in need of family planning for spacing children. Thus, the total need for family planning equals 37 percent, while only 12 percent of women are currently using contraception. The result is an unmet need for family planning services consisting of 25 percent of currently married women. This gap presents both an opportunity and a challenge to the Population Welfare Programme. Nearly one-tenth of children in Pakistan die before reaching their first birthday. The infant mortality rate during the six years preceding the survey is estimaled to be 91 per thousand live births; the under-five mortality rate is 117 per thousand. The under-five mortality rates vary from 92 per thousand for major cities to 132 for rural areas; and from 50 per thousand for women with at least some secondary education to 128 for those with no education. The level of infant mortality is influenced by biological factors such as mother's age at birth, birth order and, most importantly, the length of the preceding birth interval. Children born less than two years after their next oldest sibling are subject to an infant mortality rate of 133 per thousand, compared to 65 for those spaced two to three years apart, and 30 for those born at least four years after their older brother or sister. One of the priorities of the Government of Pakistan is to provide medical care during pregnancy and at the time of delivery, both of which are essential for infant and child survival and safe motherhood. Looking at children born in the five years preceding the survey, antenatal care was received during pregnancy for only 30 percent of these births. In rural areas, only 17 percent of births benefited from antenatal care, compared to 71 percent in major cities. Educational differentials in antenatal care are also striking: 22 percent of births of mothers with no education received antenatal care, compared to 85 percent of births of mothers with at least some secondary education. Tetanus, a major cause of neonatal death in Pakistan, can be prevented by immunisation of the mother during pregnancy. For 30 percent of all births in the five years prior to the survey, the mother received a tetanus toxoid vaccination. The differentials are about the same as those for antenatal care generally. Eighty-five percent of the births occurring during the five years preceding the survey were delivered

The global maternal and infant care product market is experiencing robust growth, driven by several key factors. Rising birth rates in developing economies, increasing awareness of maternal and infant health, and technological advancements leading to improved product efficacy and safety are significant contributors. The market is segmented by product type (maternity care and baby care) and application (hospital, clinic, household). Maternity care products, encompassing prenatal and postnatal care items, are witnessing strong demand fueled by a greater emphasis on preventative care and improved maternal health outcomes. Baby care products, ranging from diapers and formula to feeding bottles and safety equipment, benefit from consistently high demand driven by the increasing number of newborns globally. The household application segment is experiencing the fastest growth, reflecting a rising preference for convenient and high-quality home-based care solutions. Leading companies, such as GE Healthcare, Siemens Healthcare, and Philips Healthcare, are strategically investing in research and development to enhance their product portfolio and cater to the evolving needs of consumers and healthcare providers. This includes focusing on innovative product features, improved user-friendliness, and data-driven solutions to optimize patient care. Geographic growth varies significantly. Developed regions such as North America and Europe currently hold a substantial market share, due to higher disposable incomes and advanced healthcare infrastructure. However, developing regions in Asia-Pacific, particularly India and China, are experiencing the fastest growth rates due to increasing healthcare spending and rising awareness of maternal and infant well-being. Competitive pressures are increasing, with established players focused on mergers and acquisitions to expand their market reach and emerging players entering with innovative product offerings. Challenges facing the market include varying regulatory landscapes across different regions, pricing pressures, and potential supply chain disruptions. The long-term outlook for the maternal and infant care product market remains positive, with projected continued growth fueled by ongoing demographic shifts and increasing healthcare investment.

Abstract

The primary objective of the 2016 Nepal Demographic and Health Survey (NDHS) is to provide up-to-date estimates of basic demographic and health indicators. The NDHS provides a comprehensive overview of population, maternal, and child health issues in Nepal. Specifically, the 2016 NDHS: - Collected data that allowed calculation of key demographic indicators, particularly fertility and under-5 mortality rates, at the national level, for urban and rural areas, and for the country’s seven provinces - Collected data that allowed for calculation of adult and maternal mortality rates at the national level - Explored the direct and indirect factors that determine levels and trends of fertility and child mortality - Measured levels of contraceptive knowledge and practice - Collected data on key aspects of family health, including immunization coverage among children, prevalence and treatment of diarrhea and other diseases among children under age 5, maternity care indicators such as antenatal visits and assistance at delivery, and newborn care - Obtained data on child feeding practices, including breastfeeding - Collected anthropometric measures to assess the nutritional status of children under age 5 and women and men age 15-49 - Conducted hemoglobin testing on eligible children age 6-59 months and women age 15-49 to provide information on the prevalence of anemia in these groups - Collected data on knowledge and attitudes of women and men about sexually transmitted diseases and HIV/AIDS and evaluated potential exposure to the risk of HIV infection by exploring high-risk behaviors and condom use - Measured blood pressure among women and men age 15 and above - Obtained data on women’s experience of emotional, physical, and sexual violence

The information collected through the 2016 NDHS is intended to assist policymakers and program managers in the Ministry of Health and other organizations in designing and evaluating programs and strategies for improving the health of the country’s population. The 2016 NDHS also provides data on indicators relevant to the Nepal Health Sector Strategy (NHSS) 2016-2021 and the Sustainable Development Goals (SDGs).

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), 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 2016 NDHS is an updated version of the frame from the 2011 National Population and Housing Census (NPHC), conducted by the Central Bureau of Statistics (CBS).

The sampling frame contains information about ward location, type of residence (urban or rural), estimated number of residential households, and estimated population. In rural areas, the wards are small in size (average of 104 households) and serve as the primary sampling units (PSUs). In urban areas, the wards are large, with average of 800 households per ward. The CBS has a frame of enumeration areas (EAs) for each ward in the original 58 municipalities. However, for the 159 municipalities declared in 2014 and 2015, each municipality is composed of old wards, which are small in size and can serve as EAs.

The 2016 NDHS sample was stratified and selected in two stages in rural areas and three stages in urban areas. In rural areas, wards were selected as primary sampling units, and households were selected from the sample PSUs. In urban areas, wards were selected as PSUs, one EA was selected from each PSU, and then households were selected from the sample EAs.

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 administered in the 2016 NDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaire, the Fieldworker Questionnaire, and the Verbal Autopsy Questionnaire (for neonatal deaths). 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 Nepal. The Verbal Autopsy Questionnaire was based on the recent 2014 World Health Organization (WHO) verbal autopsy instruments (WHO 2015a).

Cleaning operations

The processing of the 2016 NDHS data began simultaneously with the fieldwork. As soon as data collection was completed in each cluster, all electronic data files were transferred via the IFSS to the New ERA central office in Kathmandu. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The biomarker paper questionnaires were compared with the electronic data files to check for any inconsistencies in data entry. Data entry and editing were carried out using the CSPro software package. The secondary editing of the data was completed in the second week of February 2017. The final cleaning of the data set was carried out by The DHS Program data processing specialist and was completed by the end of February 2017.

Response rate

A total of 11,473 households were selected for the sample, of which 11,203 were occupied. Of the occupied households, 11,040 were successfully interviewed, yielding a response rate of 99%.

In the interviewed households, 13,089 women age 15-49 were identified for individual interviews; interviews were completed with 12,862 women, yielding a response rate of 98%. In the subsample of households selected for the male survey, 4,235 men age 15-49 were identified and 4,063 were successfully interviewed, yielding a response rate of 96%.

Response rates were lower in urban areas than in rural areas. The difference was slightly more prominent for men than for women, as men in urban areas were 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. Non-sampling errors result from mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding 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 2016 Nepal DHS (NDHS) 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 2016 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 between 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 percent of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2016 NDHS 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 either ISSA or SAS, using programs developed by ICF. These programs use the Taylor linearization method of variance estimation 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 - Sibling size and sex ratio of siblings - Pregnancy-related mortality trends

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