The child mortality rate in the United States, for children under the age of five, was 462.9 deaths per thousand births in 1800. This means that for every thousand babies born in 1800, over 46 percent did not make it to their fifth birthday. Over the course of the next 220 years, this number has dropped drastically, and the rate has dropped to its lowest point ever in 2020 where it is just seven deaths per thousand births. Although the child mortality rate has decreased greatly over this 220 year period, there were two occasions where it increased; in the 1870s, as a result of the fourth cholera pandemic, smallpox outbreaks, and yellow fever, and in the late 1910s, due to the Spanish Flu pandemic.

The child mortality rate in the United Kingdom, for children under the age of five, was 329 deaths per thousand births in 1800. This means that approximately one in every three children born in 1800 did not make it to their fifth birthday. Over the course of the next 220 years, this number has dropped drastically, particularly in the first half of the twentieth century, and the rate has dropped to its lowest point ever in 2020 where it is just four deaths per thousand births.

The infant mortality rate in Sweden, for children under the age of one year old, was 240 deaths per thousand births in 1800. This meant that for all babies born in 1800, approximately one quarter did not survive past their first birthday. There were some brief periods in the early and mid nineteenth century where this rate increased, but overall, Sweden's infant mortality rate has decreased steadily throughout it's recorded history. Nowadays, the figure is at it's lowest point ever, with just two deaths per thousand births recorded, meaning that 99.8 percent of children would live past their first birthday.

This collection contains five modified data sets with mortality, population, and other demographic information for five American cities (Baltimore, Maryland; Boston, Massachusetts; New Orleans, Louisiana; New York City (Manhattan only), New York; and Philadelphia, Pennsylvania) from the early 19th century to the early 20th century. Mortality was represented by an annual crude death rate (deaths per 1000 population per year). The population was linearly interpolated from U.S. Census data and state census data (for Boston and New York City). All data sets include variables for year, total deaths, census populations, estimated annual linearly interpolated populations, and crude death rate. The Baltimore data set (DS0001) also provides birth and death rate variables based on race and slave status demographics, as well as a variable for stillbirths. The Philadelphia data set (DS0005) also includes variables for total births, total infant deaths, crude birth rate, and infant deaths per 1,000 live births.

The child mortality rate in France, for children under the age of five, was 412 deaths per thousand births in 1800. This means that more than forty percent of all children born in 1800 did not make it to their fifth birthday. Child mortality remained high in the nineteenth century, before falling at a much faster rate throughout the 1900s. Despite falling consistently during the last 130 years, there were two occasions where child mortality actually increased, which can be attributed to both World Wars and the Spanish Flu Pandemic. In 2020, the child mortality rate in France is expected to be just four deaths per thousand births.

The child mortality rate in Germany, for children under the age of five, was 340 deaths per thousand births in 1800. This means that more than one in every three children born in 1800 did not make it to their fifth birthday. Child mortality increased to almost fifty percent in the mid-nineteenth century, as the country industrialized and urbanized rapidly, which allowed diseases to spread much faster. This changed however, with the introduction of mandatory vaccination in 1874, which kickstarted a gradual decline in child mortality in Germany. The decline was most rapid in the first half of the twentieth century, and by the year 2020 child mortality in Germany is expected to be as low as four deaths per thousand births.

The child mortality rate in Sweden, for children under the age of five, was 381 deaths per thousand births in 1800. This means that approximately 38 percent of all children born in 1800 did not make it to their fifth birthday. Over the course of the next 220 years, this number has dropped drastically, particularly from 1880 onwards, and the rate has dropped to its lowest point ever in 2020 where it is just two deaths per thousand births, which is the lowest in the world.

The child mortality rate in Austria, for children under the age of five, was 387 deaths per thousand births in 1800. This means that just under forty percent of all children born in 1860 did not make it to their fifth birthday. Child mortality increased to over forty percent for most of the nineteenth century, as the country became more industrialized and urbanized, which allowed diseases to spread much faster. From 1900 onwards, the child mortality rate in Austria dropped consistently until today, (apart from a small increase during the Second World War) and it is expected to fall to just four deaths per thousand births in 2020.

The infant mortality rate in Italy, for children under the age of one year old, was 231 deaths per thousand births in 1865. This means that for all babies born in 1865, over 23 percent did not survive past their first birthday. Over the course of the next 155 years, the rate has dropped to its lowest point ever, amounting to three deaths per thousand births in the period between 2015 and 2020. Since the turn of the twentieth century, infant mortality in Italy has increased just two times, once in the 1910s as a result of the First World War and Spanish Flu pandemic, and then again in the 1940s due to the Second World War.

The infant mortality rate in the United States, for children under the age of one (twelve months), was 60 deaths per thousand births in 1935. Approximately six percent of children born in 1935 did not survive past their first birthday. Over the course of the next 85 years, this number has dropped significantly, and the rate has reached its lowest point ever in the period between 2015 and 2020, at six deaths per thousand births. Figures have been below ten since the 1990s.

The child mortality rate in Australia, for children under the age of five, was 391 deaths per thousand births in 1860. This means that just under forty percent of all children born in 1860 did not make it to their fifth birthday. This number dropped drastically over the next ten years, then it remained between 150 and two hundred for the remainder of the 1800s, before dropping consistently from 1900 until today. By 2020, child mortality in Australia is expected to be approximately four deaths per thousand births.

The child mortality rate in Afghanistan (for children under the age of five) was around 475 deaths per 1000 births during the course of 19th century. Given as a percentage, this means that 47.5% of children born would not make it to their 5th birthday. After 1950, the child morality rate dropped significantly due to considerable medical advancements, falling to 68 deaths per thousand in 2020. Despite this considerable decline in recent decades, Afghanistan still has one of the highest child mortality rates in the world. Afghanistan's infant mortality rate (among those aged below one year) in 2020 is 52 deaths per thousand births, meaning that the majority of child deaths occur during infancy.

In 2025, India overtook China as the world's most populous country and now has almost 1.46 billion people. China now has the second-largest population in the world, still with just over 1.4 billion inhabitants, however, its population went into decline in 2023. Global population As of 2025, the world's population stands at almost 8.2 billion people and is expected to reach around 10.3 billion people in the 2080s, when it will then go into decline. Due to improved healthcare, sanitation, and general living conditions, the global population continues to increase; mortality rates (particularly among infants and children) are decreasing and the median age of the world population has steadily increased for decades. As for the average life expectancy in industrial and developing countries, the gap has narrowed significantly since the mid-20th century. Asia is the most populous continent on Earth; 11 of the 20 largest countries are located there. It leads the ranking of the global population by continent by far, reporting four times as many inhabitants as Africa. The Demographic Transition The population explosion over the past two centuries is part of a phenomenon known as the demographic transition. Simply put, this transition results from a drastic reduction in mortality, which then leads to a reduction in fertility, and increase in life expectancy; this interim period where death rates are low and birth rates are high is where this population explosion occurs, and population growth can remain high as the population ages. In today's most-developed countries, the transition generally began with industrialization in the 1800s, and growth has now stabilized as birth and mortality rates have re-balanced. Across less-developed countries, the stage of this transition varies; for example, China is at a later stage than India, which accounts for the change in which country is more populous - understanding the demographic transition can help understand the reason why China's population is now going into decline. The least-developed region is Sub-Saharan Africa, where fertility rates remain close to pre-industrial levels in some countries. As these countries transition, they will undergo significant rates of population growth.

BackgroundMany studies have shown the impact of heat and cold on total and age-specific mortality, but knowledge gaps remain regarding weather vulnerability of very young infants. This study assessed the association of temperature extremes with perinatal mortality (stillbirths and deaths in the first week of life), among two ethnic groups in pre-industrial northern Sweden.MethodsWe used population data of indigenous Sami and non-Sami in selected parishes of northern Sweden, 1800–1895, and monthly temperature data. Multiple logistic regression models were conducted to estimate the association of cold (90th percentile) in the month of birth with perinatal mortality, adjusted for cold and warmth in the month prior birth and period, stratified by season and ethnicity.ResultsPerinatal mortality was slightly higher in Sami than in non-Sami (46 vs. 42 / 1000 live and stillbirths), but showed large variations across the region and over time. Both groups saw the highest perinatal mortality in autumn. For Sami, winter was a high-risk time as well, while for non-Sami, seasonality was less distinct. We found an association between exposure to cold and perinatal mortality among winter-born Sami [Odds ratio (OR) 1.91, 95% confidence interval (CI) 1.26–2.92, compared to moderate temperature], while there was little effect of cold or warmth during other seasons. Non-Sami, meanwhile, were affected in summer by warmth (OR 0.20, CI 0.05–0.81), and in autumn by cold (OR 0.39, CI 0.19–0.82).ConclusionsIn this pre-industrial, subarctic setting, the indigenous Sami’s perinatal mortality was influenced by extreme cold in winter, while non-Sami seemed to benefit from high temperature in summer and low temperature in autumn. Climate vulnerability of these two ethnic groups sharing the same environment was shaped by their specific lifestyles and living conditions.

The child mortality rate in Finland, for children under the age of five, was 420 deaths per thousand births in 1800. This means that for every thousand babies born in 1800, roughly 42 percent did not make it to their fifth birthday. Over the course of the next 220 years, this number has dropped drastically, and the rate has dropped to its lowest point ever in 2020 where it is just seven deaths per thousand births, which is the lowest of any country n the world. Since 1800, the child mortality rate in Finland has dropped gradually, particularly since the turn of the twentieth century, and the only time since 1900 where the mortality rate increased was between 1915 and 1920, as a result of the Spanish Flu pandemic that swept across the globe.

The child mortality rate in India, for children under the age of five, was 509 deaths per thousand births in 1880. This means that over half of all children born in 1880 did not survive past the age of five, and it remained this way until the twentieth century. From 1900 until today, the child mortality rate has fallen from over 53 percent in 1900, to under four percent in 2020. Since 1900, there were only two times where the child mortality rate increased in India, which were as a result of the Spanish Flu pandemic in the 1910s, and in the 1950s as India adjusted to its newfound independence.

Abstract

The 2011–2012 Multiple Indicator Cluster Survey (MICS) on Roma in BiH was conducted by the Ministry for Human Rights and Refugees of BiH (MHRR BiH) in cooperation with the Agency for Statistics of BiH (BHAS). Financial and technical support was provided by UNICEF, with additional financial support being provided by UNFPA and the UNHCR. The survey was undertaken as part of the fourth global round of MICS (MICS4).

The survey is based on a representative sample of 1,791 households, with a response rate of 86 percent. In these households, 1,380 women and 1,456 men aged 15-49 were interviewed and questionnaires completed for 748 children under age five.

Geographic coverage

National

Analysis unit

• Individuals
• Households

Universe

The survey covered household members in Roma settlements, all women aged between 15-49 years, all children under 5 living in the household, and all men aged 15-49 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary objective of the sample design for the MICS survey on Roma in BiH was to produce statistically reliable estimates for most indicators at the BiH, FBiH and RS level.

A one-stage stratified sampling approach was used for the selection of the survey sample.

The target sample size for the Roma communities MICS was calculated as 1,800 households in 62 municipalities. Data from MICS3 on Roma in Serbia in 2005 was used to calculate specific indicators. At the time of the sample design the Serbian MICS3 was the only unique source of data on the Roma population in the sub-region (BiH, Montenegro, Croatia, the Former Yugoslav Republic of Macedonia and Serbia). The key indicator used for the calculation of the sample size was the immunisation coverage rate for the tuberculosis vaccine amongst children aged 18-29 months. Out of the 30 indicators 17 required a smaller sample size than 1,800 households and the remaining 13 required a larger sample size of households. Of the 13 indicators that required a larger sample size than that of 1,800 households the average size of the confidence interval for a sample of 1,800 households was calculated at 7.4 percent.

Sampling frames for the Roma population were non-existent in BiH until 2009 when MHRR BiH conducted an enumeration of Roma in BiH as part of activities within the Decade of Roma Inclusion 2005-2015.

The master sample frame was prepared using information from the 2009 enumeration. During the 2009 enumeration procedure data was collected on 4,307 Roma households living in Roma communities in 67 municipalities. The total number of municipalities in BiH is 142. Data from the remaining 75 municipalities was not collected due to a lack of information on the presence of Roma in these municipalities. Five municipalities with 1 Roma household were excluded from the master sample frame.

Municipalities in the FBiH, RS and BD were identified as the sample strata and a one-stage stratified sampling approach was used for the selection of the survey sample, with households defined as the primary sampling units (PSUs).

Households were selected from each of the sampling strata (municipalities) by using systematic pps sampling procedures, based on the estimated sizes of the strata from the 2009 enumeration of Roma in BiH.

All households where the head of household declared himself or herself to be of Roma ethnicity were considered as Roma households.

Households were selected within each stratum based on the date of birth of the household head. If the date of birth of the household head was not available then the date of birth of the next oldest person in the household with an available date of birth was used. If none of the household members had an available date of birth then the date of birth of the interviewer was used as the reference.

The sampling procedures are more fully described in "Bosnia and Herzegovina Multiple Indicator Cluster Survey (MICS) 2011 - Roma Settlements - Final Report" pp.144-147.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for the Generic MICS were structured questionnaires based on the MICS4 model questionnaire with some modifications and additions. Household questionnaires were administered in each household, which collected various information on household members including sex, age and relationship. The household questionnaire includes household listing form, education, water and sanitation, household characteristics, child discipline and hand washing.

In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49, children under age five and men age 15-49. For children, the questionnaire was administered to the mother or primary caretaker of the child.

The women's questionnaire includes woman's background, access to mass media and ICT, child mortality, desire for last birth, maternal and newborn health, illness symptoms, contraception, unmet need, attitudes toward domestic violence, marriage/union, sexual behavior, HIV/AIDS, tobacco and alcohol use, life satisfaction and health care.

The children's questionnaire includes child's age, birth registration, early childhood development, breastfeeding, care of illness, immunisation and anthropometry.

The men's questionnaire includes man's background, access to mass media and ICT, child mortality, attitudes toward domestic violence, marriage/union, sexual behavior, HIV/AIDS, tobacco and alcohol use, life satisfaction and health care.

The questionnaires were based on the MICS4 model questionnaire. From the MICS4 model English version the questionnaires were translated into the local languages used in BiH. The questionnaires were pre-tested in the FBiH in three municipalities in Sarajevo Canton (Centar, Ilijas and Novo Sarajevo) during September 2011. The plan provided for 18 households to be interviewed (9 each in urban and rural areas). These households were selected using a random selection method based on the date of birth of the household head. On the basis of the pre-test results, modifications were then made to the wording and translation of the questionnaires for the survey.

Cleaning operations

The data was entered and processed by the MHRR BiH. The data was entered using CSPro software into four microcomputers by 4 trained data entry operators; the process was supervised by data entry supervisors and a data entry coordinator. Data entry began ten days after the start of data collection (20 November 2011) and was completed on 26 April 2012.

The SPSS (Statistical Package for Social Sciences) software programme (Version 18) was used to analyse the data and model syntax and tabulation plans developed by UNICEF were also used for this purpose. In order to ensure quality control all questionnaires were double entered and internal consistency checks were performed. Procedures and standard programmes developed under the global MICS4 programme and adapted to the questionnaires for the survey on Roma in BiH were used throughout.

Response rate

Of the 1,791 households selected for the sample 1,788 were found to be occupied. Of these, 1,544 households were successfully interviewed for a household response rate of 86 percent. In the interviewed households 1,457 women aged 15-49 were identified of which 1,380 were successfully interviewed, yielding a response rate of 95 percent. In addition, 1,559 men aged 15-49 were listed in the household questionnaire. Questionnaires were completed for 1,456 eligible men, which corresponds to a response rate of 93 percent. There were 760 children under age five listed in the household questionnaire and questionnaires were completed for 748 children, which corresponds to a response rate of 98 percent. The overall response rates for the women’s, men’s and children’s questionnaires were 82 percent, 81 percent and 85 percent respectively.

Sampling error estimates

The sample of respondents selected in the MICS survey on Roma in BiH was only one of the samples that could have been selected from the same population, using the same design and size. Each of these samples would have yielded results that differed somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between the estimates from all possible samples. The extent of variability is not known exactly but can be estimated statistically from the survey data.

The simple one-stage stratified sample design for the MICS survey on Roma in BiH is reflected in the calculations of the sampling errors, whereby the strata are municipalities and the primary sampling units (PSUs) are households (clusters of persons).

Given the overall high sampling rate (1,800/3,784), sampling without replacement was used in order to apply a finite population correction factor. As part of the estimation procedure, the first stage sampling rate for each stratum (municipality) was specified. For strata with a sampling rate of 1, the finite population correction factor was zero (resulting in a zero variance component for the corresponding stratum).

The sampling error measures below are presented in this appendix for each of the selected indicators.

• Standard error (se): Sampling errors are usually measured in terms of standard errors for particular indicators (means, proportions etc). Standard error is the square root of the variance of the estimate. The Taylor Linearization method was used for the estimation of standard errors.
• Coefficient of variation (se/r): is the ratio of the standard error to the value of the indicator and is a measure of the relative

The child mortality rate in Japan, for children under the age of five, was 363 deaths per thousand births in 1865. This meant that for every one thousand babies born in 1865, over 36 percent did not survive past their fifth birthday. Over the course of the next 155 years, this number dropped drastically. Child mortality reached its lowest point ever in the five year span between 2015 and 2020, at just two deaths per one thousand births. This was the lowest of any country in the world.

The child mortality rate in the Netherlands, for children under the age of five, was 324 deaths per thousand births in 1800. This means that just under one third of all children born in 1860 did not make it to their fifth birthday. Child mortality reached its highest recorded level in the Netherlands in the late nineteenth century, as rapid industrialization led to increased urbanization, which in turn allowed diseases to spread much faster, although it did decrease from 1875 until today. The only times where the rate deviated were in the 1910s and 1940s, due to the Spanish Flu pandemic and the Second World War. By 2020, the child mortality rate of the Netherlands is expected to be just three deaths per thousand.

Abstract This article aims to evaluate the factors associated with a skin-to-skin contact time