Niger had the highest birth rate in the world in 2024, with a birth rate of 46.6 births per 1,000 inhabitants. Angola, Benin, Mali, and Uganda followed. Except for Afghanistan, all 20 countries with the highest birth rates in the world were located in Sub-Saharan Africa. High infant mortality The reasons behind the high birth rates in many Sub-Saharan African countries are manyfold, but a major reason is that infant mortality remains high on the continent, despite decreasing steadily over the past decades, resulting in high birth rates to counter death rates. Moreover, many nations in Sub-Saharan Africa are highly reliant on small-scale farming, meaning that more hands are of importance. Additionally, polygamy is not uncommon in the region, and having many children is often seen as a symbol of status. Fastest-growing populations As the high fertility rates coincide with decreasing death rates, countries in Sub-Saharan Africa have the highest population growth rates in the world. As a result, Africa's population is forecast to increase from 1.4 billion in 2022 to over 3.9 billion by 2100.

This map shows the average number of children born to a woman during her lifetime. Data from Population Reference Bureau's 2017 World Population Data Sheet. The world's total fertility rate reported in 2017 was 2.5 as a whole. Replacement-Level fertility is widely recognized as 2.0 children per woman, so as to "replace" each parent in the next generation. Countries depicted in pink have a total fertility rate below replacement level whereas countries depicted in teal have a total fertility rate above replacement level. In countries with very high child mortality rates, a replacement level of 2.1 could be used, since not every child will survive into their reproductive years. Determinants of Total Fertility Rate include: women's education levels and opportunities, marriage rates among women of childbearing age (generally defined as 15-49), contraceptive usage and method mix/effectiveness, infant & child mortality rates, share of population living in urban areas, the importance of children as part of the labor force (or cost/penalty to women's labor force options that having children poses), and religious and cultural norms, among many other factors. This map was made using the Global Population and Maternal Health Indicators layer.

Crude birth rates, age-specific fertility rates and total fertility rates (live births), 2000 to most recent year.

While the standard image of the nuclear family with two parents and 2.5 children has persisted in the American imagination, the number of births in the U.S. has steadily been decreasing since 1990, with about 3.6 million babies born in 2023. In 1990, this figure was 4.16 million. Birth and replacement rates A country’s birth rate is defined as the number of live births per 1,000 inhabitants, and it is this particularly important number that has been decreasing over the past few decades. The declining birth rate is not solely an American problem, with EU member states showing comparable rates to the U.S. Additionally, each country has what is called a “replacement rate.” The replacement rate is the rate of fertility needed to keep a population stable when compared with the death rate. In the U.S., the fertility rate needed to keep the population stable is around 2.1 children per woman, but this figure was at 1.67 in 2022. Falling birth rates Currently, there is much discussion as to what exactly is causing the birth rate to decrease in the United States. There seem to be several factors in play, including longer life expectancies, financial concerns (such as the economic crisis of 2008), and an increased focus on careers, all of which are causing people to wait longer to start a family. How international governments will handle falling populations remains to be seen, but what is clear is that the declining birth rate is a multifaceted problem without an easy solution.

Context

The United States Census Bureau’s international dataset provides estimates of country populations since 1950 and projections through 2050. Specifically, the dataset includes midyear population figures broken down by age and gender assignment at birth. Additionally, time-series data is provided for attributes including fertility rates, birth rates, death rates, and migration rates.

Querying BigQuery tables

You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.census_bureau_international.

Sample Query 1

What countries have the longest life expectancy? In this query, 2016 census information is retrieved by joining the mortality_life_expectancy and country_names_area tables for countries larger than 25,000 km2. Without the size constraint, Monaco is the top result with an average life expectancy of over 89 years!

standardSQL

SELECT age.country_name, age.life_expectancy, size.country_area FROM ( SELECT country_name, life_expectancy FROM bigquery-public-data.census_bureau_international.mortality_life_expectancy WHERE year = 2016) age INNER JOIN ( SELECT country_name, country_area FROM bigquery-public-data.census_bureau_international.country_names_area where country_area > 25000) size ON age.country_name = size.country_name ORDER BY 2 DESC /* Limit removed for Data Studio Visualization */ LIMIT 10

Sample Query 2

Which countries have the largest proportion of their population under 25? Over 40% of the world’s population is under 25 and greater than 50% of the world’s population is under 30! This query retrieves the countries with the largest proportion of young people by joining the age-specific population table with the midyear (total) population table.

standardSQL

SELECT age.country_name, SUM(age.population) AS under_25, pop.midyear_population AS total, ROUND((SUM(age.population) / pop.midyear_population) * 100,2) AS pct_under_25 FROM ( SELECT country_name, population, country_code FROM bigquery-public-data.census_bureau_international.midyear_population_agespecific WHERE year =2017 AND age < 25) age INNER JOIN ( SELECT midyear_population, country_code FROM bigquery-public-data.census_bureau_international.midyear_population WHERE year = 2017) pop ON age.country_code = pop.country_code GROUP BY 1, 3 ORDER BY 4 DESC /* Remove limit for visualization*/ LIMIT 10

Sample Query 3

The International Census dataset contains growth information in the form of birth rates, death rates, and migration rates. Net migration is the net number of migrants per 1,000 population, an important component of total population and one that often drives the work of the United Nations Refugee Agency. This query joins the growth rate table with the area table to retrieve 2017 data for countries greater than 500 km2.

SELECT growth.country_name, growth.net_migration, CAST(area.country_area AS INT64) AS country_area FROM ( SELECT country_name, net_migration, country_code FROM bigquery-public-data.census_bureau_international.birth_death_growth_rates WHERE year = 2017) growth INNER JOIN ( SELECT country_area, country_code FROM bigquery-public-data.census_bureau_international.country_names_area

Update frequency

Historic (none)

Dataset source

United States Census Bureau

Terms of use: This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

See the GCP Marketplace listing for more details and sample queries: https://console.cloud.google.com/marketplace/details/united-states-census-bureau/international-census-data

In 2024, the average number of children born per 1,000 people in China ranged at ****. The birth rate has dropped considerably since 2016, and the number of births fell below the number of deaths in 2022 for the first time in decades, leading to a negative population growth rate. Recent development of the birth rate Similar to most East-Asian countries and territories, demographics in China today are characterized by a very low fertility rate. As low fertility in the long-term limits economic growth and leads to heavy strains on the pension and health systems, the Chinese government decided to support childbirth by gradually relaxing strict birth control measures, that had been in place for three decades. However, the effect of this policy change was considerably smaller than expected. The birth rate increased from **** births per 1,000 inhabitants in 2010 to ***** births in 2012 and remained on a higher level for a couple of years, but then dropped again to a new low in 2018. This illustrates that other factors constrain the number of births today. These factors are most probably similar to those experienced in other developed countries as well: women preferring career opportunities over maternity, high costs for bringing up children, and changed social norms, to name only the most important ones. Future demographic prospects Between 2020 and 2023, the birth rate in China dropped to formerly unknown lows, most probably influenced by the coronavirus pandemic. As all COVID-19 restrictions were lifted by the end of 2022, births figures showed a catch-up effect in 2024. However, the scope of the rebound might be limited. A population breakdown by five-year age groups indicates that the drop in the number of births is also related to a shrinking number of people with child-bearing age. The age groups between 15 and 29 years today are considerably smaller than those between 30 and 44, leaving less space for the birth rate to increase. This effect is exacerbated by a considerable gender gap within younger age groups in China, with the number of females being much lower than that of males.

Background : Substantial differences between countries were observed in terms of Covid-19 death tolls during the past two years. It was of interest to find out how the epidemiologic and/or demographic history of the population may have had a role in the high prevalence of the Covid-19 in some countries. Objective : This observational study aimed to investigate possible relations between Covid-19 death numbers in 39 countries and the prepandemic history of epidemiologic and demographic conditions. Methods : We sought the Covid-19 death toll in 39 countries in Europe, America, Africa, and Asia. Records (2019) of epidemiologic (Cancer, Alzheimer's disease) and demographic (natality, mortality, and fetility rates, percentage of people aged 65 and over) parameters as well as data on alcohol intake per capita were retrieved from official web pages. Data was analysed by simple linear or polynomial regression by the mean of Microsoft Excell software (2016). Results : When Covid-19 death numbers were plotted against the geographic latitude of each country, a bell-shaped curve was obtained for both the first and second years (coefficient of determination R2=0.38) of the pandemic. In a similar manner, bell-shaped curves were obtained when latitudes were plotted against the scores of (cancer plus Alzheimer's disease, R² = 0,65,), the percentage of advanced age (R² = 0,52,) and the alcohol intake level (R² = 0,64,). Covid-19 death numbers were positively correlated to the scores of (cancer plus Alzheimer's disease) (R2= 0.41, P= 1.61x10-5), advanced age (R2= 0.38, P= 4.09x10-5) and alcohol intake (R2= 0.48, P= 1.55x10-6). Instead, inverted bell-shaped curves were obtained when latitudes were plotted against the birth rate/mortality rate ratio (R² = 0,51) and the fetility rate (R² = 0,33). In addition, Covid-19 deaths were negatively correlated with the birth rate/mortality rate ratio (R2= 0.67) and fertility rate (R2= 0.50). Conclusion : The results show that the 39 countries in both hemisphers in this study have different patterns of epidemiologic and demographic factors, and that the negative history of epidemiologic and demographic factors of the northern hemisphere countries, as well as their high alcohol intake, were very correlated with their Covid-19 death tolls. Hence, also nutritional habits may have had a role in the general health status of people in regard to their immunity against the coronavirus.

The excess of monthly deaths by state in Brazil, mainly in 2021, point to an unprecedented mortuary catastrophe in Brazil How has the government of Brazil acted and has acted to protect its citizens from the most important, intense and deadly event of all time, in these 521 years of Brazilian history? How great is the risk of death that its inhabitants are facing, is it possible to measure and compare with other similar human beings, but who have different governments? Can we really measure, based on scientific, safe and verified data, the performance, willingness and result of actions and even the examples that the federal government of Brazil promoted in 18 months of the years 2020 and 2021? YES, we can ! Fortunately, in this era of free and unquestionable virtual environments, it is possible to develop reliable and fast ways to search, classify, verify, index, compare and publish known health epidemiological indices of human health! The internet and the Dataverse of the Harvard School allowed, not only scientists and physicians, as any being on Earth, to consult, understand and compare results that will remain available for generations, between the past and the present, but also between countries, as in this set we deal with the safest and most important health index, we show absolute numbers of deaths and births... All the most used epidemiological variables of birth and mortality per month in Brazil, from January 2014 to June 2021, by state, country and 2 large groups of states (based on a single criterion - votes Bolsonaro 1st round 2018 > 50%) All most used epidemiological variables from mortality per month in Brazil , Jan-2015 to Jun-2021, per state and country We show the death rate, number of net deaths, excess deaths, births, birth rate, annual growth rate, growth rate variation, P-score, excess mortality rate by months by state (UF), percentage of seniors over 70 years old from January 2014 to June 2021

Heterogeneous populations can lead to important differences in birth and death rates across a phylogeny. Taking this heterogeneity into account is necessary to obtain accurate estimates of the underlying population dynamics. We present a new multi-type birth-death model (MTBD) that can estimate lineage-specific birth and death rates. This corresponds to estimating lineage-dependent speciation and extinction rates for species phylogenies, and lineage-dependent transmission and recovery rates for pathogen transmission trees. In contrast with previous models, we do not presume to know the trait driving the rate differences, nor do we prohibit the same rates from appearing in different parts of the phylogeny. Using simulated datasets, we show that the MTBD model can reliably infer the presence of multiple evolutionary regimes, their positions in the tree, and the birth and death rates associated with each. We also present a re-analysis of two empirical datasets and compare the results obtai...

In 2024, the number of live births in Poland was the lowest since 2017 and amounted to *** per 1,000 population. The highest rate was recorded in 1950 when the number of births per **** people was nearly **. Population in Poland Since 2010, the year in which the census was conducted in Poland, the population has been gradually and systematically decreasing. The society has reduced by ******* since 2010. Many factors influence this state. Both the birth and death rate and the migration rate. When analyzing the birth and death rate, one must consider both the size of the group of women at reproductive age, the number of elderly, and the fertility rate. The latter can be stimulated by an increase in household income as well as by social transfers, such as the government program for families with children called “500+”. It is predicted that by **** the population of Poland will decline to over **** million people. Situation of Polish families In developed countries, the financial situation plays a key role in family planning. The average family in Poland had **** people in 2023, and since 2010 this indicator has been systematically decreasing. Although the financial situation of Poles is improving every year, their increasing costs of living, lack of stability, and awareness of investments related to having a family make Poles postpone their decision on parenthood. The government's “500 plus” family support program was designed to help Polish families with children to develop further. However, recent surveys of birth rates indicate that this goal has not been fully achieved.

The study’s theme: The development of infant mortality in Germany for the 19th century is only poorly documented. Especially for the period prior to 1871 only small area statistics are available. With the preparation of the information collected by the authorities of the former German States the author tries to create a new statistical basis. The reconstructed national series of birth and infant mortality (from 1826) documents relatively high infant mortality rates with little progress (i.e. improvement of the situation) until the beginning of the 20th Century. Considering the influence of urbanization the evaluation of the different regional patterns and trends leads to a new weighting of the problem. Thus the living and working conditions in the country were of considerable importance. Overall, the prevailing habits and attitudes are considered crucial to the survival of small children (Gehrmann 2011, S. 807) Data and data preparation, source problems:The federal structure of the Empire leads to the problem that the printed statistics on infant mortality before 1901 remained incomplete. In some German states, information concerning infant mortality was not collected from the beginning of the registry offices. However, the ‘Kaiserliches Statistisches Amt’ (Imperial Statistical Office) was able to create despi9te the difficult situation a life table, which represented 97,3% of live birth for the period of 1872 to 1880. Hence, the annual infant mortality rate in 1872 is known. „Die föderale Struktur des Kaiserreichs hatte (…) zur Folge, dass die gedruckte Statistik zur Säuglingssterblichkeit vor 1901 lückenhaft blieb. Mehr noch: es wurden offensichtlich in einigen Staaten diesbezügliche Angaben gar nicht oder zumindest nicht von Anfang an bei den Standesämtern abgefragt. Als das Kaiserliche Statistische Amt in den 1880er Jahren die erste Sterbetafel für das Deutsche Reich erstellen wollte, musste es deshalb konstatieren, dass in den Einzelstaaten „fast alle in der Statistik überhaupt üblichen Arten und Grade der Spezialisierung vertreten“ (Kaiserliches Statistisches Amt 1887: 21) waren, aus manchen aber trotzdem keine geeigneten Unterlagen beschafft werden konnten. Immerhin repräsentierte die Sterbetafel am Ende doch 96,8% der Reichsbevölkerung im Jahre 1885 und 97,3% der Lebendgeborenen 1872 bis 1880. Damit ist auch die jährliche Säuglingssterblichkeitsrate ab 1872 bekannt. (…) Mit Hilfe des Sterbetafel-Materials kann die statistische Reihe aus „Bevölkerung und Wirtschaft“ also um fast 30 Jahre nach hinten verlängert werden. (…) Komplizierter stellt sich die Sachlage für weiter zurückliegende Zeitabschnitte dar. „ (S. 812-813)Although in most German states statistical collection on population movement has been carried out, the statistics vary considerably in quality. In the first step therefore, the author reject the procedure of simply extrapolating the birth rates because of the qualitative differences of the early statistics are too fundamental. Especially, in this approach of simply summing up, the values of the undocumented areas would equate with the values of the other well documented regions. Therefore, the author chose a complex way to estimate the lacking values: The missing values in small territories are estimated on the basis of the values of neighboring regions. Finally, it can be seen, that the data for the period from 1828 to 1871, calculated by the complex procedure of filling in missing data does not lead to significantly different results comparing to the data row calculated by the simple sum of the different sources. Per year, the difference between the two series (the series calculated in the complex way and the series calculated by summing up the values of the available statistics) is not more than 0,9 percent points, which can be seen as a slight difference between the two series in relation to the former level of infant mortality. The indeterminate values of those German states lacking a birth statistics may not being significantly different to those calculated on the basis of the complex procedure, because even unexpected, extreme runaway values in individual states can not realistically assumed to be so large that they could have a sufficient impact on the overall values. Thus, the presented row is a solid basis for the assessment of the overall development of the German Empire’s birth development. „Vielmehr empfiehlt es sich, zunächst in kleinen Schritten für die einzelnen Territorien fehlende Werte durch wahrscheinliche zu ersetzen. Diese ergeben sich in erster Linie aus dem Vergleich der Säuglingssterblichkeitswerte benachbarter Gebiete zu anderen Zeitpunkten. So können für Württemberg die vor 1859 zu längeren Zeiträumen zusammengefassten Informationen auf Einzeljahre herunter gerechnet werden, indem die Verteilung über die Jahre wie in Bayern angenommen wird. … Alle ermittelten Werte beziehen sich auf Lebendgeborene.“ (S. 814) „Die komplexe Prozedur der Ergänzung fehlend...

ABSTRACT OBJECTIVE To analyze the contribution of linkage between databases of live births and infant mortality to improve the completeness of the variables common to the Mortality Information System (SIM) and the Live Birth Information System (SINASC) in Brazilian capitals in 2012. METHODS We studied 9,001 deaths of children under one year registered in the SIM in 2012 and 1,424,691 live births present in the SINASC in 2011 and 2012. The databases were related with linkage in two steps – deterministic and probabilistic. We calculated the percentage of incompleteness of the variables common to the SIM and SINASC before and after using the technique. RESULTS We could relate 90.8% of the deaths to their respective declarations of live birth, most of them paired deterministically. We found a higher percentage of pairs in Porto Alegre, Curitiba, and Campo Grande. In the capitals of the North region, the average of pairs was 84.2%; in the South region, this result reached 97.9%. The 11 variables common to the SIM and SINASC had 11,278 incomplete fields cumulatively, and we could recover 91.4% of the data after linkage. Before linkage, five variables presented excellent completeness in the SINASC in all Brazilian capitals, but only one variable had the same status in the SIM. After applying this technique, all 11 variables of the SINASC became excellent, while this occurred in seven variables of the SIM. The city of birth was significantly associated with the death component in the quality of the information. CONCLUSIONS Despite advances in the coverage and quality of the SIM and SINASC, problems in the completeness of the variables can still be identified, especially in the SIM. In this perspective, linkage can be used to qualify important information for the analysis of infant mortality.

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 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

Linkage between fertility variables and population data.

Long time series of Vienna’s population history from 1700 to 1999.

With this study the author A. Weigl submits the first detailed report on the population history of Vienna over the period from the late mediaevial time until the 20th century.

The author documents by means of the development of migration, reproduction and mortality the process of Vienna’s population history. Important influencing factors as for excample food pattern, plagues and epidemics, medical advance, the change of mentalities and influences by demographic policies are discussed in detail. The significant role of modenization-processes is in the focus of the publication.

By means of numerous long time series data the pecesses are documented empirically.

Content of the Study: - Demographic Change and Modernization - Main Features of Vienna’s Population Development - Migration: The Impetus for an Increasing Town - Mortality: From Town Refurbishment to Municipal Welfare Policy - Fertility: The Genesis of the Modern Family - The Common Modernizationcontext of Transition

List of Data-Tables in the GESIS-ZA-Online-Database HISTAT:

A. Population Development of Vienna

A.01 Population (1200-1999) A.02 Population Development by Territory as of Today (1590-1999) A.03 Regional Population Development (1700-1991) A.04 Population Movement (1869-1991) A.05 Agestructure (1856-1991) A.06 Population Development of the City, the suburbs and the periphery (1777-1857) A.07 Population by Urban Districts by Territory as of Today (1777-1991) A.08 Population by Urban Districts (1869-1939) A.09 Native Birth of the Population (1856-1934) A.10 Natural Population Movement (1707-1999) A.11 Proportion of Persons Younger than 14 Years by Urban Districts (1869-1939) A.12 Proportion of Persons in the Age of 60 and older by Urban Districts (1869-1939) A.13 Population and Birth Rates by Religious Denomination (1856-1939)

B. Migration

B.01 Ratios of Mobility-Transition (1710-1991) B.02 Acceptation of new Members into the Homeland Association (Naturalizations) (1919-1938)

C. Mortality

C.01 Age specific Mortality-Rates of Vienna (1856-1939) C.02 Age standardized Morality-Rates by Sex and by Causes of Death (1910-1935) C.03 Cholera-Mortality by Urnab Districts (1831-1873) C.04 Variola-Mortality (1728-1938) C.05 Average Life Expectancy (1830-1998) C.06a Age-Specific Mortality: Mortality Rates (1650-1999) C.06b Age-Specific Mortality: Agestructure of the Deceased (1650-1999) C.07a Infant Mortality (1728-1999) C.07b Infant Mortality Rate by Territory as of Today (1871-1938) C.08 Mortality Rates by Urban Districts (1871-1938) C.09 Infant Mortality by Urban Districts (1885-1911) C.10 Pulmonary Tuberculosis-Mortality by Urban Districts (1871-1938)

D. Fertiliy

D.01 General Fertility-Rate of Vienna (1856-1939) D.02 Fertility-Rate (1754-1999) D.03 Fertility-Indizes by Metropolitan Comparison (1910-1960) D.04 Illegitimacy-Rates (1797-1999) D.05 Marriage Rate, Birthrate and Deathrate (1706-1938) D.06 Marriage-, Mortality- and Infant Mortality Rate by Territory as of Today (1871-1938) D.07 Birth Rate by Urban Districts (1783-1938)

E. Housholds

E.01 Average Householdsize (1780-1991)

Presents the distribution of SINGLETON PERINATAL DEATHS for 2014 by cause of death and Birthweight. This table outlines perinatal mortality rates and numbers (total) by cause of death for SINGLETON perinatal deaths. The Perinatal Statistics Report 2014 is a report on national data on Perinatal events in 2014. Information on every birth in the Republic of Ireland is submitted to the National Perinatal Reporting System (NPRS). All births are notified and registered on a standard four part birth notification form (BNF01) which is completed where the birth takes place. Part 3 of this form is sent to the HPO for data entry and validation. The information collected includes data on pregnancy outcomes (with particular reference to perinatal mortality and important aspects of perinatal care), as well as descriptive social and biological characteristics of mothers giving birth. See the complete Perinatal Statistics Report 2014 at http://www.hpo.ie/latest_hipe_nprs_reports/NPRS_2014/Perinatal_Statistics_Report_2014.pdf

ABSTRACT Background : The Covid-19 pandemic associated with the SARS-CoV-2 has caused very high death tolls in many countries, while it has had less prevalence in other countries of Africa and Asia. Climate and geographic conditions, as well as other epidemiologic and demographic conditions, were a matter of debate on whether or not they could have an effect on the prevalence of Covid-19. Objective : In the present work, we sought a possible relevance of the geographic location of a given country on its Covid-19 prevalence. On the other hand, we sought a possible relation between the history of epidemiologic and demographic conditions of the populations and the prevalence of Covid-19 across four continents (America, Europe, Africa, and Asia). We also searched for a possible impact of pre-pandemic alcohol consumption in each country on the two year death tolls across the four continents. Methods : We have sought the death toll caused by Covid-19 in 39 countries and obtained the registered deaths from specialized web pages. For every country in the study, we have analysed the correlation of the Covid-19 death numbers with its geographic latitude, and its associated climate conditions, such as the mean annual temperature, the average annual sunshine hours, and the average annual UV index. We also analyzed the correlation of the Covid-19 death numbers with epidemiologic conditions such as cancer score and Alzheimer score, and with demographic parameters such as birth rate, mortality rate, fertility rate, and the percentage of people aged 65 and above. In regard to consumption habits, we searched for a possible relation between alcohol intake levels per capita and the Covid-19 death numbers in each country. Correlation factors and determination factors, as well as analyses by simple linear regression and polynomial regression, were calculated or obtained by Microsoft Exell software (2016). Results : In the present study, higher numbers of deaths related to Covid-19 pandemic were registered in many countries in Europe and America compared to other countries in Africa and Asia. The analysis by polynomial regression generated an inverted bell-shaped curve and a significant correlation between the Covid-19 death numbers and the geographic latitude of each country in our study. Higher death numbers were registered in the higher geographic latitudes of both hemispheres, while lower scores of deaths were registered in countries located around the equator line. In a bell shaped curve, the latitude levels were negatively correlated to the average annual levels (last 10 years) of temperatures, sunshine hours, and UV index of each country, with the highest scores of each climate parameter being registered around the equator line, while lower levels of temperature, sunshine hours, and UV index were registered in higher latitude countries. In addition, the linear regression analysis showed that the Covid-19 death numbers registered in the 39 countries of our study were negatively correlated with the three climate factors of our study, with the temperature as the main negatively correlated factor with Covid-19 deaths. On the other hand, cancer and Alzheimer's disease scores, as well as advanced age and alcohol intake, were positively correlated to Covid-19 deaths, and inverted bell-shaped curves were obtained when expressing the above parameters against a country’s latitude. Instead, the (birth rate/mortality rate) ratio and fertility rate were negatively correlated to Covid-19 deaths, and their values gave bell-shaped curves when expressed against a country’s latitude. Conclusion : The results of the present study prove that the climate parameters and history of epidemiologic and demographic conditions as well as nutrition habits are very correlated with Covid-19 prevalence. The results of the present study prove that low levels of temperature, sunshine hours, and UV index, as well as negative epidemiologic and demographic conditions and high scores of alcohol intake may worsen Covid-19 prevalence in many countries of the northern hemisphere, and this phenomenon could explain their high Covid-19 death tolls. Keywords : Covid-19, Coronavirus, SARS-CoV-2, climate, temperature, sunshine hours, UV index, cancer, Alzheimer disease, alcohol.

Presents the distribution of MULTIPLE PERINATAL DEATHS for 2014 by cause of death and Birthweight . This table outlines perinatal mortality rates and numbers (total) by cause of death for MULTIPLE perinatal deaths. The Perinatal Statistics Report 2014 is a report on national data on Perinatal events in 2014. Information on every birth in the Republic of Ireland is submitted to the National Perinatal Reporting System (NPRS). All births are notified and registered on a standard four part birth notification form (BNF01) which is completed where the birth takes place. Part 3 of this form is sent to the HPO for data entry and validation. The information collected includes data on pregnancy outcomes (with particular reference to perinatal mortality and important aspects of perinatal care), as well as descriptive social and biological characteristics of mothers giving birth. See the complete Perinatal Statistics Report 2014 at http://www.hpo.ie/latest_hipe_nprs_reports/NPRS_2014/Perinatal_Statistics_Report_2014.pdf

TABLE 3.12: Perinatal Statistics Report 2015: Month of Birth: Total Births, Live Births, Mortality Rates, and Maternities, 2015. Published by Health Service Executive. Available under the license cc-by (CC-BY-4.0).Presents the distribution of TOTAL, SINGLETON AND MULTIPLE births for 2015 by Month of Birth. This table outlines data for total births, live births, stillbirths, early neonatal deaths and perinatal mortality rates, as well as presenting the number of maternities. The Perinatal Statistics Report 2015 is a report on national data on Perinatal events in 2015. Information on every birth in the Republic of Ireland is submitted to the National Perinatal Reporting System (NPRS). All births are notified and registered on a standard four part birth notification form (BNF01) which is completed where the birth takes place. Part 3 of this form is sent to the HPO for data entry and validation. The information collected includes data on pregnancy outcomes (with particular reference to perinatal mortality and important aspects of perinatal care), as well as descriptive social and biological characteristics of mothers giving birth. See the complete Perinatal Statistics Report 2015 at http://www.hpo.ie/latest_hipe_nprs_reports/NPRS_2015/Perinatal_Statistics_Report_2015.pdf...