Introduction: Despite the growing efforts to standardize coding for social determinants of health (SDOH), they are infrequently captured in electronic health records (EHRs). Most SDOH variables are still captured in the unstructured fields (i.e., free-text) of EHRs. In this study we attempt to evaluate a practical text mining approach (i.e., advanced pattern matching techniques) in identifying phrases referring to housing issues, an important SDOH domain affecting value-based healthcare providers, using EHR of a large multispecialty medical group in the New England region, United States. To present how this approach would help the health systems to address the SDOH challenges of their patients we assess the demographic and clinical characteristics of patients with and without housing issues and briefly look into the patterns of healthcare utilization among the study population and for those with and without housing challenges.Methods: We identified five categories of housing issues [i.e., homelessness current (HC), homelessness history (HH), homelessness addressed (HA), housing instability (HI), and building quality (BQ)] and developed several phrases addressing each one through collaboration with SDOH experts, consulting the literature, and reviewing existing coding standards. We developed pattern-matching algorithms (i.e., advanced regular expressions), and then applied them in the selected EHR. We assessed the text mining approach for recall (sensitivity) and precision (positive predictive value) after comparing the identified phrases with manually annotated free-text for different housing issues.Results: The study dataset included EHR structured data for a total of 20,342 patients and 2,564,344 free-text clinical notes. The mean (SD) age in the study population was 75.96 (7.51). Additionally, 58.78% of the cohort were female. BQ and HI were the most frequent housing issues documented in EHR free-text notes and HH was the least frequent one. The regular expression methodology, when compared to manual annotation, had a high level of precision (positive predictive value) at phrase, note, and patient levels (96.36, 95.00, and 94.44%, respectively) across different categories of housing issues, but the recall (sensitivity) rate was relatively low (30.11, 32.20, and 41.46%, respectively).Conclusion: Results of this study can be used to advance the research in this domain, to assess the potential value of EHR's free-text in identifying patients with a high risk of housing issues, to improve patient care and outcomes, and to eventually mitigate socioeconomic disparities across individuals and communities.

This dataset covers ballots 247-78, 250-52, and 254, spanning March, May, July, September-November 1956. The dataset contains the data resulting from these polls in ASCII. The ballots are as follows: 247 - March This Gallup poll aims to collect the opinions of Canadians on such issues as politics, current events, trends and habits. Some of the questions also inquire about topics like the Trans-Canada Pipeline, marriage and funerals. Respondents were also asked questions so that they could be grouped according to geographic, demographic and social variables. Topics of interest include: the 30 hour work week; the Academy awards; awareness towards Australia; broadcasting regulation; the Canadian Broadcasting Corporation (CBC); dining out; doctors; federal elections; a two party electoral system; funerals; government competition; health care; hospital problems; husbands' faults; marriage; movies; phone ownership; preferred political parties; price trends; the Quebec provincial election; television's influence; the Trans-Canada pipeline; union membership; voting behaviour; and wives faults. Basic demographics variables are also included. 248 - May This Gallup polls seeks the opinions of Canadians on current events in Canada and around the world, the continuing development of industry and communities in Canada, and some lighter topics including holidays. Respondents were also asked questions so that they could be grouped according to geographic, demographic, and social variables. Topics of interest include: American influence over Canada; American investment in Canada; the conflict between Israel and the Arabs; arms sales in Canada; bilingualism and unity; the British commonwealth; federal elections; fluoridation of water; gender issues; how to spend holidays; major development of Canada; preferred political parties; prevention of war; standards of living; union membership; the United Nations; and voting behaviour. Basic demographics variables are also included. 250 - July This Gallup poll seeks to collect the opinions of Canadians on issues of importance to the country. Questions relating to such issues as politics, health, highways and Russia are included in this survey. Respondents were also asked questions so that they could be grouped according to geographic, demographic and social variables. Topics of interest include: the Canadian Broadcasting Corporation (CBC); car ownership; cremation; drivers license possession; exercise and walking; family budget; federal elections; highway speed limit; hospital costs; St. Laurent's performance as Prime Minister; phone ownership; preferred political parties; Russia's desire to dominate; smoking habits; speed limit; Stalin affecting Russian policy towards to west; television ownership; Trans-Canada pipeline; union membership; voting behaviour; and world leaders. Basic demographics variables are also included. 251 - September This Gallup poll seeks to collect the opinions of Canadians on a variety of subjects. The main topics of discussion are politics and elections, children, and the average Canadian. In addition, there are several current events topics, with subjects that include income taxes, obesity, and sports. Respondents were also asked questions so that they could be grouped according to geographic, demographic, and social variables. Topics of interest include: the American election; the average Canadian; car ownership; child pampering; donating to a political campaign; drivers license possession, the Duke of Windsor; the federal election; federal office; government problems; the Grey Cup, opinions on what happiness is; how happy the respondents are; income tax rates; the lifespan of obese people; mandatory military service; whether obese people are more prone to heart attacks; population predictions; preferred political parties; traffic tickets; the Suez Canal dispute; Union membership; voting behaviour; and how world relations are affected by the Olympics. Basic demographics variables are also included. 252 - October This Gallup Poll aims primarily to seek the political opinions of Canadians. The majority of questions concern either politicians or policy, both in Canada and/or abroad. Respondents were also asked questions so that they could be grouped according to geographic, demographic, and social variables. Topics of interest include: the airforce's manpower; American foreign policy; the army's manpower; British foreign policy; Canadian premiers; car ownership; careers to bring fame; church attendance patterns; Conservative party leader; economic depression predictions; the federal election; the next Governor General; income tax authorities; the main role of labour unions; the navy's manpower; preferred political parties; price changes; politicians; the quality of the past year for farmers; union membership; and voting behaviours. Basic demographics variables have also been included. 254 - November This Gallup poll seeks the opinions and awareness levels of Canadians on issues of political and legal importance. There are also several questions relating to the United Nations and international affairs. The respondents were also asked questions so that they could be grouped according to geographic, demographic and social variables. Topics of interest include: American foreign policy; British foreign policy; danger of losing personal rights; federal elections; laws regarding arrest warrants; personal goals for 1957; preferred political parties; protection of personal rights; rights of arrested people; success of family life; the Suez Canal dispute; television ownership; union membership; and voting behaviour. Basic demographics variables are also included. The codebook for this dataset is available through the UBC Library catalogue, with call number HN110.Z9 P84.

The spatial distribution of populations and settlements across a country and their interconnectivity and accessibility from urban areas are important for delivering healthcare, distributing resources and economic development. However, existing spatially explicit population data across Africa are generally based on outdated, low resolution input demographic data, and provide insufficient detail to quantify rural settlement patterns and, thus, accurately measure population concentration and accessibility. Here we outline approaches to developing a new high resolution population distribution dataset for Africa and analyse rural accessibility to population centers. Contemporary population count data were combined with detailed satellite-derived settlement extents to map population distributions across Africa at a finer spatial resolution than ever before. Substantial heterogeneity in settlement patterns, population concentration and spatial accessibility to major population centres is exhibited across the continent. In Africa, 90% of the population is concentrated in less than 21% of the land surface and the average per-person travel time to settlements of more than 50,000 inhabitants is around 3.5 hours, with Central and East Africa displaying the longest average travel times. The analyses highlight large inequities in access, the isolation of many rural populations and the challenges that exist between countries and regions in providing access to services. The datasets presented are freely available as part of the AfriPop project, providing an evidence base for guiding strategic decisions.

Abstract

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

Geographic coverage

National coverage

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

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

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

Mode of data collection

Face-to-face [f2f]

Research instrument

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

Cleaning operations

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

Response rate

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

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

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors result from mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2017 Indonesia Demographic and Health Survey (2017 IDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2017 IDHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling error is a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2017 IDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2017 IDHS is a STATA program. This program used the Taylor linearization method for variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

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

Data appraisal

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

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

The Central Statistical Office (CSO) conducted the third Zimbabwe Demographic and Health Survey (ZDHS) between August and November 1999. The 1999 Zimbabwe Demographic and Health Survey (ZDHS) is a nationally representative survey that was implemented by the Central Statistical Office (CSO) from August to November 1999. Although significantly expanded in content, the 1999 ZDHS is a follow-on to the 1988 and 1994 ZDHS surveys and provides updated estimates of the basic demographic and health indicators covered in the earlier surveys. The 1999 ZDHS was conducted in all of the ten provinces of Zimbabwe. The 1999 Zimbabwe Demographic and Health Survey (ZDHS) is one of a series of surveys undertaken by the Central Statistical Office (CSO) as part of the Zimbabwe National Household Survey Capability Programme (ZNHSCP) and the worldwide MEASURE DHS+ programme. The Zimbabwe National Family Planning Council (ZNFPC), the Department of Population Studies of the University of Zimbabwe (UZ), the National AIDS Coordinating Programme (NACP), and the Ministry of Health and Child Welfare (MOH&CW) contributed significantly to the design, implementation, and analysis of the ZDHS results. The U.S. Agency for International Development (USAID) provided funds for the implementation of the 1999 ZDHS. Macro International Inc. provided technical assistance through its contract with USAID. UNICEF/Zimbabwe supported the survey by providing additional funds for fieldwork transportation. The primary objectives of the 1999 ZDHS were to provide up-to-date information on fertility levels, nuptiality, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of mothers and young children, early childhood mortality and maternal mortality, maternal and child health, and awareness and behaviour regarding AIDS and other sexually transmitted diseases. The 1999 ZDHS is a follow-up of the 1988 and 1994 ZDHS surveys, also implemented by CSO. The 1999 ZDHS is significantly expanded in scope and provides updated estimates of basic demographic and health indicators covered in the earlier surveys. KEY RESULTS Like the 1988 ZDHS and the 1994 ZDHS, the 1999 ZDHS was designed to provide information on levels and trends in fertility, family planning knowledge and use, infant and child mortality, and maternal and child health. Specific questions were also asked about the respondent's knowledge, attitude, and practice regarding the HIV/AIDS virus and other sexually transmitted diseases. Like the1994 ZDHS, the 1999 ZDHS also collected data on mortality related to pregnancy and childbearing (i.e., maternal mortality). The ZDHS data are intended for use by programme managers and policymakers to evaluate and improve family planning and health programmes in Zimbabwe. Fertility. The 1988, 1994, and 1999 ZDHS results show that Zimbabwe continues to experience a fairly rapid decline in fertility. Marriage. The median age at first marriage in Zimbabwe has risen slowly over the past 30 years. Women age 20-24 marry about one year later than women 40-49 (19.7 years and 18.8 years, respectively). The proportion of women married by age 15 declined from 9 percent among those age 45-49 to 2 percent among women age 15-19 years. Polygyny. One in six women in Zimbabwe reported being in a polygynous union. Fertility Preferences. More than half (53 percent) of the married women in Zimbabwe would like to have another child. Family Planning. Since 1994, knowledge of family planning in Zimbabwe has been universal and has not varied across subgroups of the population. The pill, condoms, and injectables are the most widely known methods. Antenatal Care. Utilisation of antenatal services is high in Zimbabwe; in the five years before the survey, mothers received antenatal care from a trained medical professional for 93 percent of their most recent births; 13 percent from a doctor and 80 percent from a trained nurse or a midwife. Delivery Characteristics. In 1999, the percentage of births delivered in health facilities (72 percent) was slightly higher than the percentage recorded in the 1994 ZDHS (69 percent). Childhood Vaccination. Three in four children 12-23 months have been vaccinated against six diseases (tuberculosis, diphtheria, pertussis, tetanus, polio, and measles). Two in three children completed the vaccination schedule by the time they turned one year. Childhood Diseases. In the 1999 ZDHS, mothers were asked whether their children under the age of five years had been ill with a cough accompanied by short, rapid breathing in the two weeks preceding the survey. Childhood Mortality. Data from surveys since 1988 indicate that early childhood mortality in Zimbabwe declined until the late 1980s, after which there was stagnation and an upward trend in the past five years. Adult and Maternal Mortality. As in 1994, the 1999 ZDHS collected information that allows estimation of adult and maternal mortality. Perceived Problems in Accessing Women's Health Care. Women are sometimes perceived to have problems in seeking health care services for themselves. Nutrition. Breastfeeding is nearly universal in Zimbabwe; 98 percent of the children born in the past five years were breastfed at some time. AIDS-related Knowledge and Behaviour. Although practically all Zimbabwean women and men have heard of AIDS, the quality of that knowledge is sometimes poor; 17 percent of women and 7 percent of men could not cite a single means to avoid getting HIV/AIDS.

The second National Family Health Survey (NFHS-2), conducted in 1998-99, provides information on fertility, mortality, family planning, and important aspects of nutrition, health, and health care. The International Institute for Population Sciences (IIPS) coordinated the survey, which collected information from a nationally representative sample of more than 90,000 ever-married women age 15-49. The NFHS-2 sample covers 99 percent of India's population living in all 26 states. This report is based on the survey data for 25 of the 26 states, however, since data collection in Tripura was delayed due to local problems in the state. IIPS also coordinated the first National Family Health Survey (NFHS-1) in 1992-93. Most of the types of information collected in NFHS-2 were also collected in the earlier survey, making it possible to identify trends over the intervening period of six and one-half years. In addition, the NFHS-2 questionnaire covered a number of new or expanded topics with important policy implications, such as reproductive health, women's autonomy, domestic violence, women's nutrition, anaemia, and salt iodization. The NFHS-2 survey was carried out in two phases. Ten states were surveyed in the first phase which began in November 1998 and the remaining states (except Tripura) were surveyed in the second phase which began in March 1999. The field staff collected information from 91,196 households in these 25 states and interviewed 89,199 eligible women in these households. In addition, the survey collected information on 32,393 children born in the three years preceding the survey. One health investigator on each survey team measured the height and weight of eligible women and children and took blood samples to assess the prevalence of anaemia. SUMMARY OF FINDINGS POPULATION CHARACTERISTICS Three-quarters (73 percent) of the population lives in rural areas. The age distribution is typical of populations that have recently experienced a fertility decline, with relatively low proportions in the younger and older age groups. Thirty-six percent of the population is below age 15, and 5 percent is age 65 and above. The sex ratio is 957 females for every 1,000 males in rural areas but only 928 females for every 1,000 males in urban areas, suggesting that more men than women have migrated to urban areas. The survey provides a variety of demographic and socioeconomic background information. In the country as a whole, 82 percent of household heads are Hindu, 12 percent are Muslim, 3 percent are Christian, and 2 percent are Sikh. Muslims live disproportionately in urban areas, where they comprise 15 percent of household heads. Nineteen percent of household heads belong to scheduled castes, 9 percent belong to scheduled tribes, and 32 percent belong to other backward classes (OBCs). Two-fifths of household heads do not belong to any of these groups. Questions about housing conditions and the standard of living of households indicate some improvements since the time of NFHS-1. Sixty percent of households in India now have electricity and 39 percent have piped drinking water compared with 51 percent and 33 percent, respectively, at the time of NFHS-1. Sixty-four percent of households have no toilet facility compared with 70 percent at the time of NFHS-1. About three-fourths (75 percent) of males and half (51 percent) of females age six and above are literate, an increase of 6-8 percentage points from literacy rates at the time of NFHS-1. The percentage of illiterate males varies from 6-7 percent in Mizoram and Kerala to 37 percent in Bihar and the percentage of illiterate females varies from 11 percent in Mizoram and 15 percent in Kerala to 65 percent in Bihar. Seventy-nine percent of children age 6-14 are attending school, up from 68 percent in NFHS-1. The proportion of children attending school has increased for all ages, particularly for girls, but girls continue to lag behind boys in school attendance. Moreover, the disparity in school attendance by sex grows with increasing age of children. At age 6-10, 85 percent of boys attend school compared with 78 percent of girls. By age 15-17, 58 percent of boys attend school compared with 40 percent of girls. The percentage of girls 6-17 attending school varies from 51 percent in Bihar and 56 percent in Rajasthan to over 90 percent in Himachal Pradesh and Kerala. Women in India tend to marry at an early age. Thirty-four percent of women age 15-19 are already married including 4 percent who are married but gauna has yet to be performed. These proportions are even higher in the rural areas. Older women are more likely than younger women to have married at an early age: 39 percent of women currently age 45-49 married before age 15 compared with 14 percent of women currently age 15-19. Although this indicates that the proportion of women who marry young is declining rapidly, half the women even in the age group 20-24 have married before reaching the legal minimum age of 18 years. On average, women are five years younger than the men they marry. The median age at marriage varies from about 15 years in Madhya Pradesh, Bihar, Uttar Pradesh, Rajasthan, and Andhra Pradesh to 23 years in Goa. As part of an increasing emphasis on gender issues, NFHS-2 asked women about their participation in household decisionmaking. In India, 91 percent of women are involved in decision-making on at least one of four selected topics. A much lower proportion (52 percent), however, are involved in making decisions about their own health care. There are large variations among states in India with regard to women's involvement in household decisionmaking. More than three out of four women are involved in decisions about their own health care in Himachal Pradesh, Meghalaya, and Punjab compared with about two out of five or less in Madhya Pradesh, Orissa, and Rajasthan. Thirty-nine percent of women do work other than housework, and more than two-thirds of these women work for cash. Only 41 percent of women who earn cash can decide independently how to spend the money that they earn. Forty-three percent of working women report that their earnings constitute at least half of total family earnings, including 18 percent who report that the family is entirely dependent on their earnings. Women's work-participation rates vary from 9 percent in Punjab and 13 percent in Haryana to 60-70 percent in Manipur, Nagaland, and Arunachal Pradesh. FERTILITY AND FAMILY PLANNING Fertility continues to decline in India. At current fertility levels, women will have an average of 2.9 children each throughout their childbearing years. The total fertility rate (TFR) is down from 3.4 children per woman at the time of NFHS-1, but is still well above the replacement level of just over two children per woman. There are large variations in fertility among the states in India. Goa and Kerala have attained below replacement level fertility and Karnataka, Himachal Pradesh, Tamil Nadu, and Punjab are at or close to replacement level fertility. By contrast, fertility is 3.3 or more children per woman in Meghalaya, Uttar Pradesh, Rajasthan, Nagaland, Bihar, and Madhya Pradesh. More than one-third to less than half of all births in these latter states are fourth or higher-order births compared with 7-9 percent of births in Kerala, Goa, and Tamil Nadu. Efforts to encourage the trend towards lower fertility might usefully focus on groups within the population that have higher fertility than average. In India, rural women and women from scheduled tribes and scheduled castes have somewhat higher fertility than other women, but fertility is particularly high for illiterate women, poor women, and Muslim women. Another striking feature is the high level of childbearing among young women. More than half of women age 20-49 had their first birth before reaching age 20, and women age 15-19 account for almost one-fifth of total fertility. Studies in India and elsewhere have shown that health and mortality risks increase when women give birth at such young ages?both for the women themselves and for their children. Family planning programmes focusing on women in this age group could make a significant impact on maternal and child health and help to reduce fertility. INFANT AND CHILD MORTALITY NFHS-2 provides estimates of infant and child mortality and examines factors associated with the survival of young children. During the five years preceding the survey, the infant mortality rate was 68 deaths at age 0-11 months per 1,000 live births, substantially lower than 79 per 1,000 in the five years preceding the NFHS-1 survey. The child mortality rate, 29 deaths at age 1-4 years per 1,000 children reaching age one, also declined from the corresponding rate of 33 per 1,000 in NFHS-1. Ninety-five children out of 1,000 born do not live to age five years. Expressed differently, 1 in 15 children die in the first year of life, and 1 in 11 die before reaching age five. Child-survival programmes might usefully focus on specific groups of children with particularly high infant and child mortality rates, such as children who live in rural areas, children whose mothers are illiterate, children belonging to scheduled castes or scheduled tribes, and children from poor households. Infant mortality rates are more than two and one-half times as high for women who did not receive any of the recommended types of maternity related medical care than for mothers who did receive all recommended types of care. HEALTH, HEALTH CARE, AND NUTRITION Promotion of maternal and child health has been one of the most important components of the Family Welfare Programme of the Government of India. One goal is for each pregnant woman to receive at least three antenatal check-ups plus two tetanus toxoid injections and a full course of iron and folic acid supplementation. In India, mothers of 65 percent of the children born in the three years preceding NFHS-2 received at least one antenatal

The "motherhood and childhood health index" symbolizes the health condition on birth related issues of a certain area in 2010. The quality of health system is an important factor determining the adaptive capacity. Beside the lack of medical services we should consider also the lack of access to these services. The index results from the third cluster of the Principal Component Analysis preformed among 16 potential variables. The analysis identify three dominant variables, namely "maternal mortality", "infant mortality" and "percentage of delivery in a healthcare facility", assigning respectively the weights of 0.39, 0.38 and 0.23. Before to perform the analysis all the variables were log transformed (except "infant mortality") to shorten the extreme variation and then were score-standardized (converted to distribution with average of 0 and standard deviation of 1; with inverse method for "maternal mortality" and "infant mortality") in order to be comparable. Country-based data of maternal mortality rate were collected from World Bank in particular the modeled mortality per 100,000 live births average of the period 2008-2012 was computed. Tabular data were linked by country to the national boundaries shapefile (FAO/GAUL) and then converted into raster format (resolution 0.5 arc-minute). The first administrative level data for "infant mortality" (deaths per 1,000 live births before 12 months of life) was derived by the Center for International Earth Science Information Network (CIESIN) at Columbia University using survey data (collected between 1998 and 2012) from DHS, UNDP National Human Development Reports, UNICEF statistics, and in some cases national survey data. Tabular data were linked by first administrative unit to the first administrative boundaries shapefile (FAO/GAUL) and then converted into raster format (resolution 0.5 arc-minute). The first administrative level data for the "percentage of delivery in a healthcare facility" was derived using survey data collected between 1998 and 2012 from DHS, UNDP National Human Development Reports, UNICEF statistics, and in some cases national survey data. Maternal and infant mortality are proxy to measure the quality of the health system. Moreover, the "percentage of delivery in a healthcare facility" is traditionally used to assess the capacity to access to healthcare by local population. This dataset has been produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 4 (WP4). More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

Data publication: 2014-09-01

Supplemental Information:

ClimAfrica was an international project funded by European Commission under the 7th Framework Programme (FP7) for the period 2010-2014. The ClimAfrica consortium was formed by 18 institutions, 9 from Europe, 8 from Africa, and the Food and Agriculture Organization of United Nations (FAO).

ClimAfrica was conceived to respond to the urgent international need for the most appropriate and up-to-date tools and methodologies to better understand and predict climate change, assess its impact on African ecosystems and population, and develop the correct adaptation strategies. Africa is probably the most vulnerable continent to climate change and climate variability and shows diverse range of agro-ecological and geographical features. Thus the impacts of climate change can be very high and can greatly differ across the continent, and even within countries.

The project focused on the following specific objectives:

1. Develop improved climate predictions on seasonal to decadal climatic scales, especially relevant to SSA;

2. Assess climate impacts in key sectors of SSA livelihood and economy, especially water resources and agriculture;

3. Evaluate the vulnerability of ecosystems and civil population to inter-annual variations and longer trends (10 years) in climate;

4. Suggest and analyse new suited adaptation strategies, focused on local needs;

5. Develop a new concept of 10 years monitoring and forecasting warning system, useful for food security, risk management and civil protection in SSA;

6. Analyse the economic impacts of climate change on agriculture and water resources in SSA and the cost-effectiveness of potential adaptation measures.

The work of ClimAfrica project was broken down into the following work packages (WPs) closely connected. All the activities described in WP1, WP2, WP3, WP4, WP5 consider the domain of the entire South Sahara Africa region. Only WP6 has a country specific (watershed) spatial scale where models validation and detailed processes analysis are carried out.

Contact points:

Metadata Contact: FAO-Data

Resource Contact: Selvaraju Ramasamy

Resource constraints:

copyright

Online resources:

Motherhood and childhood health index (2010)

Scenarios of major production systems in Africa

CLIMAFRICA – Climate change predictions in Sub-Saharan Africa: impacts and adaptations