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.

In 2024, the number of births in South Korea stood at *******, a slight increase compared to the previous year. Around two decades earlier, this number was twice as high. Declining fertility in South Korea A phenomenon that most East Asian countries and territories grapple with is a stark decline in fertility rates. This is especially evident in South Korea, which has the lowest fertility rate in the world, far below the 2.1 children per woman threshold that represents replacement fertility. In response to the expected economic consequences of a declining population, South Korea has implemented various initiatives to encourage married couples to have children. Factors contributing to low birth rates in South Korea One major element is the societal change in attitudes toward childbirth. In a survey, half of the South Korean respondents asserted that marriages can be happy without children, and a sizable share also stated that having children was dependent on economic factors. In addition, an increasing number of South Koreans are choosing not to get married. In 2023, South Korea recorded one of the lowest numbers of marriages in its history. Furthermore, there has been a growing trend among South Korean women to prioritize their financial independence and career continuity over traditional expectations of childbearing.

Abstract

The 2009 Population and Housing Census was implemented according to Prime Ministerial Decision No. 94/2008/QD-TTg dated 10 July, 2008. This was the fourth population census and the third housing census implemented in Vietnam since the nation was reunified in 1975. The Census aimed to collect basic data on the population and housing for the entire territory of the Socialist Republic of Vietnam, to provide data for research and analysis of population and housing developments nationally and for each locality. It responded to information needs for assessing implementation of socio-economic development plans covering the period 2001 to 2010, for developing the socio-economic development plans for 2011 to 2020 and for monitoring performance on Millennium Development Goals of the United Nations to which the Vietnamese Government is committed.

Geographic coverage

National

Analysis unit

Households Individuals Dwelling

Universe

The 2009 Population and Housing Census enumerated all Vietnamese regularly residing in the territory of the Socialist Republic of Vietnam at the reference point of 0:00 on 01 April, 2009; Vietnamese citizens given permission by the authorities to travel overseas and still within the authorized period; deaths (members of the household) that occurred between the first day of the Lunar Year of the Rat (07 February, 2008) to 31 March, 2009; and residential housing of the population.

Population and housing censuses were implemented simultaneously taking the household as the survey unit. The household could include one individual who eats and resides alone or a group of individuals who eat and reside together. For household with 2 persons and over, its members may or may not share a common budget; or be related by blood or not; or marital or adoptive relationship or not; or in combination of both. The household head was the main respondent. For information of which the head of household was unaware, the enumerator was required to directly interview the survey subject. For information on labour and employment, the enumerator was required to directly interview all respondents aged 15 and older; for questions on births, the enumerator was required to directly interview women in childbearing ages (from 15 to 49 years of age) to determine the responses. For information on housing, the enumerator was required to directly survey the household head and/or combine this with direct observation to determine the information to record in the forms.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Sample size In the 2009 Population and Housing Census, besides a full enumeration, some indicators were collected in a sample survey. The census sample survey was designed to: (1) expand survey contents; (2) improve survey quality, especially for sensitive and complicated questions; and (3) save on survey costs. To improve the efficiency and reliability of the census sample data, the sample size was 15% of the total population of the country. The sample of the census is a single-stage cluster sample design with stratification and systematic sample selection. Sample selection is implemented in two steps: Step 1, select the strata to determine the sample size for each district. Step 2, independently and systematically select from the sample frame of enumeration areas in each district to determine the specific enumeration areas in the sample.

The sample size of the two census sample surveys in 1989 and 1999 was 5% and 3% respectively, only representative at the provincial level; sample survey indicators covered fertility history of women aged 15-49 years and deaths in the household in the previous 12 months. In the 2009 Census, besides the above two indicators, many other indicators were also included in the census sample survey. The census sample survey provides data representative at the district level. When determining sample size and allocation, the frequency of events was taken into account for various indicators including birth and deaths in the 12 months prior to the survey, and the number of people unemployed in urban areas, etc.; efforts were also made to ensure the ability to compare results between districts within the same province/municipality and between provinces/ municipalities.

Stratification and sample allocation across strata To ensure representativeness of the sample for each district throughout the country and because the population size is not uniform across districts or provinces, the Central Steering Committee decided to allocate the sample directly to 682 out of 684 districts (excluding 2 island districts) throughout the country in 2 steps:

Step 1: Determine the sampling rate f(r) for 3 regions including: - Region 1: including 132 urban districts; - Region 2: including 294 delta and coastal rural districts; - Region 3: including 256 mountainous and island districts.

Step 2: Allocate the sample across districts in each region based on the sampling rates for each region as determined in Step 1 using the inverse sampling allocation method. Through applying to this allocation method, the number of sampling units in each small district is increased adequately to ensure representativeness. The formula used to calculate the sample rate for each district in each region is provided on page 22 of the Census Report (Part1) provided as external resources.

Sampling unit and method The sampling unit is the enumeration area that was ascertained in the step to delimit enumeration areas. The sampling frame is the list of all enumeration areas that was made following the order of the list of administrative units at the commune level within each district. In this way, the whole country has 682 sample frames (682 strata).

The provincial steering committee was responsible for selecting sample enumeration areas using systematic random sampling as follows: Step 1: Take the total of all enumeration areas in the district, divide by the number of enumeration areas needed in the sampleto determine the skip (k), which is calculated with precision up to 1 decimal point. Step 2: Select the first enumeration area (b, with b = k), corresponding to the first enumeration area to be selected. Each successive enumeration area to be selected will correspond to the order number: bi = b + i x k ; here i = 1, 2, 3…. Stopping when the number of enumeration areas needed has been selected.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires and survey materials were designed and tested three times before final approval.

Cleaning operations

The 2009 Population and Housing Census applied Intelligent Character Recognition technology/scanning technology for direct data entry from census forms to the computer to replace the traditional keyboard data entry that is commonly used in Vietnam at present. This is an advanced technology, and the first time it had been applied in a statistical survey in Vietnam. Preparatory work had to be done carefully and meticulously. Through organization of many workshops and 7 pilot applications with technical and financial assistance from the UNFPA, the new technology was mastered, and the Census Steering Committee Standing Committee approved use of this technology to process the entire results of the 2009 Population and Housing Census. The Government decided to allocate funds through the project on Modernization of the General Statistics Office using World Bank Loan funds to procure the scanning system equipment, software and technical assistance. The successful use of this technology will create a precedent for continued use of scanning technology in other statistical surveys

After checking and coding at the Provincial/municipal steering committee office, (both the complete census and the census sample survey), forms were checked and accepted then transferred for processing to one of three Statistical Computing Centres in Hanoi, Ho Chi Minh City and Da Nang. Data processing was implemented in only a few locations, following standard procedures and a fixed timeline. The steering committee at each level and processing centres fully implemented their assigned responsibilities, especially the checking, transmitting and maintenance of survey forms in good condition. The Central Steering Committee collaborated with the Statistical Computer Centres to set up a plan for processing and compiling results, setting up tabulation plans, interpreting and synthesizing output tables, and developing options for extrapolating from sample to population estimates.

The General Statistics Office completed the work of developing software applications and training using ReadSoft software (the one used in pilot testing), organized training on network management and training on systems and programs for logic checks and data editing, developed a data processing protocol, integrated these systems and completed data flow management programs. The General Statistics Office collaborated with the contractor, FPT, to develop software applications, train staff, testl the system and complete the programs using the new TIS and E-form software.

Compilation of results was implemented in 2 stages. In stage 1 data were compiled from the Census Sample Survey by the end of October, 2009, and in stage 2, data were compiled from the completed census forms, with work finalized in May 2010.

Sampling error estimates

Estimates from the Census sample survey were affected by two types of error: (1) non-sampling error, and (2) sampling error. Non-sampling error is the result of errors in implementation of data collection and processing such as visiting the

Abstract

The Kenya Demographic and Health Survey (KDHS) was conducted between December 1988 and May 1989 to collect data regarding fertility, family planning and maternal and child health. The survey covered 7,150 women aged 15-49 and a subsample of 1,116 husbands of these women, selected from a sample covering 95 percent of the population. The purpose of the survey was to provide planners and policymakers with data useful in making informed programme decisions.

OBJECTIVES

On March 1, 1988, 'on behalf of the Government of Kenya, the National Council for Population and Development (NCPD) signed an agreement with the Institute for Resource Development (IRD) to carry out the Kenya Demographic and Health Survey (KDHS).

The KDHS is intended to serve as a source of population and health data for policymakers and for the research community. In general, the objectives of the KDHS are to: assess the overall demographic situation in Kenya, assist in the evaluation of the population and health programmes in Kenya, advance survey methodology, and assist the NCPD strengthen and improve its technical skills to conduct demographic and health surveys.

The KDHS was specifically designed to: - provide data on the family planning and fertility behaviour of the Kcnyan population to enable the NCPD to evaluate and enhance the National Family Planning Programme, - measure changes in fertility and contraceptive prevalence and at the same time study the factors which affect these changes, such as marriage patterns, urban/rural residence, availability of contraception, breastfeeding habits and other socioeconomic factors, and - examine the basic indicators of maternal and child health in Kenya.

SUMMARY OF FINDINGS

The survey data can also be used to evaluate Kenya's efforts to reduce fertility and the picture that emerges shows significant strides have been made toward this goal. KDHS data provide the first evidence of a major decline in fertility. If young women continue to have children at current rates, they will have an average of 6.7 births in their lifetime. This is down considerably from the average of 7.5 births for women now at the end of their childbearing years. The fertility rate in 1984 was estimated at 7.7 births per woman.

A major cause of the decline in fertility is increased use of family pIanning. Twenty-seven percent of married women in Kenya are currcntly using a contraceptive method, compared to 17 percent in 1984. Although periodic abstinence continues to he the most common method (8 percent), of interest to programme planners is the fact that two-thirds of marricd women using contraception have chosen a modern method--either the pill (5 percent) or female sterilisation (5 percent). Contraccptive use varies by province, with those closest to Nairobi having the highest levels. Further evidence of the success in promoting family planning is the fact that more than 90 percent of married women know at least one modern method of contraception (and where to obtain it), and 45 percent have used a contraceptive method at some time in their life.

The survey indicates a high level of knowledge, use and approval of family planning by husbands of interviewed women. Ninety-three percent of husbands know a modern method of family planning. Sixty-five percent of husbands have used a method at some time and almost 49 percent are currently using a method, half of which are modern methods. Husbands in Kenya are strongly supportive of family planning. Ninety-one percent of those surveyed approve of family planning use by couples, compared to 88 percent of married women.

If couples are able to realise their childbearing preferences, fertility may continue to decline in the future. One half of married women say that they want no more children; another 26 percent want to wait at least two years before having another child. Husbands report similar views on limiting births--one-half say they want no more children. The desire to limit childbearing appears to be greater in Kenya than in other subSaharan countries. In Botswana and Zimbabwe, for example, only 33 percent of married women want no more children. Another indicator of possible future decline in fertility in Kenya is the decrease in ideal family size. According to the KDHS, the mean ideal family size declined from 5.8 in 1984 to 4.4 in 1989.

The KDHS indicates that in the area of health, government programmes have been effective in providing health services for womcn and children. Eight in ten births benefit from ante-natal care from a doctor, nurse, or midwife and one-half of births are assisted at delivery by a doctor, nurse, or midwife. At least 44 percent of children 12-23 months of age are fully immunised against the major childhood diseases, Almost all children benefit from an extended period of breastfeeding. The average duration of breastfeeding is 19 months and the practice does not appear to be waning among either younger women or urban women. Another encouraging piece of information is the high level of ORT (oral rehydration therapy) use for treating childhood diarrhoea. Among children under five reported to have had an episode of diarrhoea in the two weeks before the survey, half were treated with a homemade solution and almost one-quarter were given a solution prepared from commercially prepared packets.

The survey indicates several areas where there is room for improvement. Although young women are marrying later, many are still having births at young ages. More than 20 percent of teen-age girls have had at least one child and 7 percent were pregnant at the time of the survey. There is also evidence of an unmet need for family planning services. Of the births occurring in the 12 months before the survey, over half were either mistimed or unwanted; one fifth occurred less than 24 months after a previous birth.

Geographic coverage

The 1989 KDHS sample is national in scope, with the exclusion of all three districts in North Eastern Province and four other northern districts (Samburu and Turkana in Rift Valley Province and Isiolo and 4 Marsabit in Eastern Province). Together the excluded areas account for less than 4 percent of Kenya's population.

Analysis unit

• Household
• Women age 15-49
• Men age not specified

Universe

The population covered by the 1989 KDHS is defined as the universe of all women age 15-49 in Kenya and all husband living in the household.

Kind of data

Sample survey data

Sampling procedure

The sample for the KDHS is based on the National Sample Survey and Ewduation Programme (NASSEP) master sample maintained by the CBS. The KDHS sample is national in coverage, with the exclusion of North Eastern Province and four northern districts which together account for only about five percent of Kenya's population. The KDHS sample was designed to produce completed interviews with 7,500 women aged 15-49 and with a subsample of 1,000 husbands of these women.

The NASSEP master sample is a two-stage design, stratified by urban-rural residence, and within the rural stratum, by individual district. In the first stage, 1979 census enumeration areas (EAs) were selected with probability proportional to size. The selected EAs were segmented into the expected number of standard-sized clusters, one of which was selected at random to form the NASSEP cluster. The selected clusters were then mapped and listed by CBS field staff. In rural areas, household listings made betwecn 1984 and 1985 were used to select the KDHS households, while KDHS pretest staff were used to relist households in the selected urban clusters.

Despite the emphasis on obtaining district-level data for phoning purposes, it was decided that reliable estimates could not be produced from the KDHS for all 32 districts in NASSEP, unless the sample were expanded to an unmanageable size. However, it was felt that reliable estimates of certain variables could be produced lbr the rural areas in the 13 districts that have been initially targeted by the NCPD: Kilifi, Machakos, Meru, Nyeri, Murang'a, Kirinyaga, Kericho, Uasin Gishu, South Nyanza, Kisii, Siaya, Kakamega, and Bungoma. Thus, all 24 rural clusters in the NASSEP were selected for inclusion in the KDHS sample in these 13 districts. About 450 rural households were selected in each of these districts, just over 1000 rural households in other districts, and about 3000 households in urban areas, for a total of almost 10,000 households. Sample weights were used to compensate for the unequal probability of selection between strata, and weighted figures are used throughout the remainder of this report.

Mode of data collection

Face-to-face

Research instrument

The KDHS utilised three questionnaires: a household questionnaire, a woman's questionnaire, and a husband's questionnaire. The first two were based on the DHS Programme's Model "B" Questionnaire that was designed for low contraceptive prevalence countries, while the husband's questionnaire was based on similar questionnaires used in the DHS surveys in Ghana and Burundi. A two-day seminar was held in Nyeri in November 1987 to develop the questionnaire design. Participants included representatives from the Central Bureau of Statistics (CBS), the Population Studies Research Institute at the University of Nairobi, the Community Health Department of Kenyatta Hospital, and USAID. The decision to include a survey of husbands was based on the recommendation of the seminar participants. The questionnaires were subsequently translated into eight local languages (Kalenjin, Kamba, Kikuyu, Kisii, Luhya, Luo, Meru and Mijikenda), in addition to Kiswahili.

Cleaning operations

Data

Abstract

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

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

Geographic coverage

National coverage

Analysis unit

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

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

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

Mode of data collection

Face-to-face [f2f]

Research instrument

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

Cleaning operations

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

Response rate

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

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

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

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2019 Pakistan Maternal Mortality Survey (2019 PMMS) to minimise this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2019 PMMS is only one of many samples that could have been selected from the same population, using the same design and sample size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

If the sample of respondents had been selected by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2019 PMMS sample was the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed using SAS programmes developed by ICF. These programmes use the Taylor linearisation method to estimate variances for survey estimates that are means, proportions, or ratios and use the Jackknife repeated replication method for variance estimation of more complex statistics such as fertility and mortality rates.

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

Data appraisal

Data Quality Tables

- Household age distribution

Abstract

The 2003 Nigeria Demographic and Health Survey (2003 NDHS) is the third national Demographic and Health Survey conducted in Nigeria. The 2003 NDHS is based on a nationally representative sample of over 7,000 households. All women age 15-49 in these households and all men age 15-59 in a subsample of one-third of the households were individually interviewed. The survey provides up-to-date information on the population and health situation in Nigeria.

The 2003 NDHS was designed to provide estimates for key indicators such as fertility, contraceptive use, infant and child mortality, immunization levels, use of family planning, maternal and child health, breastfeeding practices, nutritional status of mothers and young children, use of mosquito nets, female genital cutting, marriage, sexual activity, and awareness and behaviour regarding AIDS and other sexually transmitted infections in Nigeria.

MAIN RESULTS

• FERTILITY

Fertility Levels, Trends, and Preferences. The total fertility rate (TFR) in Nigeria is 5.7. This means that at current fertility levels, the average Nigerian woman who is at the beginning of her childbearing years will give birth to 5.7 children by the end of her lifetime. Compared with previous national surveys, the 2003 survey shows a modest decline in fertility over the last two decades: from a TFR of 6.3 in the 1981-82 National Fertility Survey (NFS) to 6.0 in the 1990 NDHS to 5.7 in the 2003 NDHS. However, the 2003 NDHS rate of 5.7 is significantly higher than the 1999 NDHS rate of 5.2. Analysis has shown that the 1999 survey underestimated the true levels of fertility in Nigeria.

On average, rural women will have one more child than urban women (6.1 and 4.9, respectively). Fertility varies considerably by region of residence, with lower rates in the south and higher rates in the north. Fertility also has a strong negative correlation with a woman's educational attainment.

Most Nigerians, irrespective of their number of living children, want large families. The ideal number of children is 6.7 for all women and 7.3 for currently married women. Nigerian men want even more children than women. The ideal number of children for all men is 8.6 and for currently married men is 10.6. Clearly, one reason for the slow decline in Nigerian fertility is the desire for large families.

• FAMILY PLANNING

Knowledge of Family Planning Methods. About eight in ten women and nine in ten men know at least one modern method of family planning. The pill, injectables, and the male condom are the most widely known modern methods among both women and men. Mass media is an important source of information on family planning. Radio is the most frequent source of family planning messages: 40 percent of women and 56 percent of men say they heard a radio message about family planning during the months preceding the survey. However, more than half of women (56 percent) and 41 percent men were not exposed to family planning messages from a mass media source.

Current Use. A total of 13 percent of currently married women are using a method of family planning, including 8 percent who are using a modern method. The most common modern methods are the pill, injectables, and the male condom (2 percent each). Urban women are more than twice as likely as rural women to use a method of contraception (20 percent versus 9 percent). Contraceptive use varies significantly by region. For example, one-third of married women in the South West use a method of contraception compared with just 4 percent of women in the North East and 5 percent of women in the North West.

• CHILD HEALTH

Mortality. The 2003 NDHS survey estimates infant mortality to be 100 per 1,000 live births for the 1999-2003 period. This infant mortality rate is significantly higher than the estimates from both the 1990 and 1999 NDHS surveys; the earlier surveys underestimated mortality levels in certain regions of the country, which in turn biased downward the national estimates. Thus, the higher rate from the 2003 NDHS is more likely due to better data quality than an actual increase in mortality risk overall.

The rural infant mortality rate (121 per 1,000) is considerably higher than the urban rate (81 per 1,000), due in large part to the difference in neonatal mortality rates. As in other countries, low maternal education, a low position on the household wealth index, and shorter birth intervals are strongly associated with increased mortality risk. The under-five mortality rate for the 1999-2003 period was 201 per 1,000.

Vaccinations. Only 13 percent of Nigerian children age 12-23 months can be considered fully vaccinated, that is, have received BCG, measles, and three doses each of DPT and polio vaccine (excluding the polio vaccine given at birth). This is the lowest vaccination rate among African countries in which DHS surveys have been conducted since 1998. Less than half of children have received each of the recommended vaccinations, with the exception of polio 1 (67 percent) and polio 2 (52 percent). More than three times as many urban children as rural children are fully vaccinated (25 percent and 7 percent, respectively). WHO guidelines are that children should complete the schedule of recommended vaccinations by 12 months of age. In Nigeria, however, only 11 percent of children age 12-23 months received all of the recommended vaccinations before their first birthday.

• WOMEN'S HEALTH

Breastfeeding. Breastfeeding is almost universal in Nigeria, with 97 percent of children born in the five years preceding the survey having been breastfed. However, just one-third of children were given breast milk within one hour of birth (32 percent), and less than two-thirds were given breast milk within 24 hours of birth (63 percent). Overall, the median duration of any breastfeeding is 18.6 months, while the median duration of exclusive breastfeeding is only half a month.

Complementary Feeding. At age 6-9 months, the recommended age for introducing complementary foods, three-quarters of breast-feeding infants received solid or semisolid foods during the day or night preceding the interview; 56 percent received food made from grains, 25 percent received meat, fish, shellfish, poultry or eggs, and 24 percent received fruits or vegetables. Fruits and vegetables rich in vitamin A were consumed by 20 percent of breastfeeding infants age 6-9 months.

Maternal Care. Almost two-thirds of mothers in Nigeria (63 percent) received some antenatal care (ANC) for their most recent live birth in the five years preceding the survey. While one-fifth of mothers (21 percent) received ANC from a doctor, almost four in ten women received care from nurses or midwives (37 percent). Almost half of women (47 percent) made the minimum number of four recommended visits, but most of the women who received antenatal care did not get care within the first three months of pregnancy.

In terms of content of care, slightly more than half of women who received antenatal care said that they were informed of potential pregnancy complications (55 percent). Fifty-eight percent of women received iron tablets; almost two-thirds had a urine or blood sample taken; and 81 percent had their blood pressure measured. Almost half (47 percent) received no tetanus toxoid injections during their most recent birth.

WOMEN'S CHARACTERISTICS AND STATUS

Across all maternal care indicators, rural women are disadvantaged compared with urban women, and there are marked regional differences among women. Overall, women in the south, particularly the South East and South West, received better care than women in the north, especially women in the North East and North West.

Female Circumcision. Almost one-fifth of Nigerian women are circumcised, but the data suggest that the practice is declining. The oldest women are more than twice as likely as the youngest women to have been circumcised (28 percent versus 13 percent). Prevalence is highest among the Yoruba (61 percent) and Igbo (45 percent), who traditionally reside in the South West and South East. Half of the circumcised respondents could not identify the type of procedure performed. Among those women who could identify the type of procedure, the most common type of circumcision involved cutting and removal of flesh (44 percent of all circumcised women). Four percent of women reported that their vaginas were sewn closed during circumcision.

MALARIA CONTROL PROGRAM INDICATORS

Nets. Although malaria is a major public health concern in Nigeria, only 12 percent of households report owning at least one mosquito net. Even fewer, 2 percent of households, own an insecticide treated net (ITN). Rural households are almost three times as likely as urban households to own at least one mosquito net. Overall, 6 percent of children under age five sleep under a mosquito net, including 1 percent of children who sleep under an ITN. Five percent of pregnant women slept under a mosquito net the night before the survey, one-fifth of them under an ITN.

Use of Antimalarials. Overall, 20 percent of women reported that they took an antimalarial for prevention of malaria during their last pregnancy in the five years preceding the survey. Another 17 percent reported that they took an unknown drug, and 4 percent took paracetamol or herbs to prevent malaria. Only 1 percent received intermittent preventative treatment (IPT)-or preventive treatment with sulfadoxine-pyrimethamine (Fansidar/SP) during an antenatal care visit. Among pregnant women who took an antimalarial, more than half (58 percent) used Daraprim, which has been found to be ineffective as a chemoprophylaxis during pregnancy. Additionally, 39 percent used chloroquine, which was the chemoprophylactic drug of choice until the introduction of IPT in Nigeria in 2001.

Among children

In 2024, around **** million babies were born in China. The number of births has increased slightly from **** million in the previous year, but is much lower than the ***** million births recorded in 2016. Demographic development in China In 2022, the Chinese population decreased for the first time in decades, and population decline is expected to accelerate in the upcoming years. To curb the negative effects of an aging population, the Chinese government decided in 2013 to gradually relax the so called one-child-policy, which had been in effect since 1979. From 2016 onwards, parents in China were allowed to have two children in general. However, as the recent figures of births per year reveal, this policy change had only short-term effects on the general birth rate: the number of births slightly increased from 2014 onwards, but then started to fell again in 2018. In 2024, China was the second most populous country in the world, overtaken by India that year. China’s aging population The Chinese society is aging rapidly and facing a serious demographic shift towards older age groups. The median age of China’s population has increased massively from about ** years in 1970 to **** years in 2020 and is projected to rise continuously until 2080. In 2020, approximately **** percent of the Chinese were 60 years and older, a figure that is forecast to rise as high as ** percent by 2060. This shift in demographic development will increase social and elderly support expenditure of the society as a whole. One measure for this social imbalance is the old-age dependency ratio, measuring the relationship between economic dependent older age groups and the working-age population. The old-age dependency ratio in China is expected to soar to ** percent in 2060, implying that by then three working-age persons will have to support two elderly persons.

Abstract

The Labour Force Survey (LFS) is a study of the employment circumstances of the UK population. It is the largest household study in the UK and provides the official measures of employment and unemployment.The first Labour Force Survey (LFS) in the United Kingdom was conducted in 1973, under the terms of a Regulation derived from the Treaty of Rome. The provision of information for the Statistical Office of the European Communities (SOEC) continued to be one of the reasons for carrying out the survey on an annual basis. SOEC co-ordinated information from labour force surveys in the member states in order to assist the EC in such matters as the allocation of the Social Fund. The survey was carried out biennially from 1973 to 1983 and was increasingly used by UK government departments to obtain information which would assist in the framing of social and economic policy. By 1983 it was being used by the Employment Department (now the Department for Work and Pensions) to obtain information which was not available from other sources or was only available for Census years. From 1984 the survey was carried out annually, and since that time the LFS has consisted of two elements:

• a quarterly survey conducted in Great Britain throughout the year, in which each sampled address was called on five times at quarterly intervals, and which yielded about 15,000 responding households in every quarter;
• a 'boost' survey in the spring quarter (March-May), which produced interviews at over 44,000 households in Great Britain and over 4,000 households in Northern Ireland.

Users should note that only the data from the spring quarter and the 'boost' survey were included in the annual datasets for public release, and that only data from 1975-1991 are available from the UK Data Archive. The depositor recommends only considered use of data for 1975 and 1977 (SNs 1757 and 1758), as the concepts behind the definitions of economic activity changed and are not comparable with later years. Also the survey methodology was being developed at the time and so the estimates may not be reliable enough to use.

During 1991 the survey was developed, so that from spring 1992 the data were made available quarterly, with a quarterly sample size approximately equivalent to that of the previous annual data. The Quarterly Labour Force Survey series therefore superseded the annual LFS series, and is held at the Data Archive under GN 33246.

The study is being conducted by the Office for National Statistics (ONS), the government's largest producer of statistics. They compile independent information about the UK's society and economy which provides evidence for policy and decision making, and for directing resources to where they are needed most. The ten-yearly census, measures of inflation, the National Accounts, and population and migration statistics are some of our highest-profile outputs.

Geographic coverage

The whole country.

Analysis unit

• Individuals
• Families/households

Universe

• Households
• All persons normally resident in private households in the United Kingdom

Kind of data

Sample survey data [ssd]

Sampling procedure

Stratified multi-stage sample; for further details see annual reports. Until 1983 two sampling frames were used; in England, Northern Ireland and Wales, the Valuation Roll provided the basis for a sample which, in England and Wales, included all 69 metropolitan districts, and a two-stage selection from among the remaining non-metropolitan districts. In Northern Ireland wards were the primary sampling units. In Scotland, the Address File (i.e. post codes) was used as the basis for a stratified sample.From 1983 the Postoffice Address File has been used instead of the Valuation Roll in England and Wales. In 1984 sample rotation was introduced along with a panel element, the quarterly survey, which uses a two-stage clustered sample design.

The sample comprises about 90,000 addresses drawn at random from the rating lists in 190 different areas of England and Wales With such a large sample, it Will happen by chance that a small number of addresses which were selected at random for the 1979 survey Will come up again In addition 2,000 addresses in 8 of the areas selected in 1979 have been deliberately re-selected again this time (me Interviewers who get these addresses In their work w,ll receive a special letter to take with them.)

The sample is drawn from the "small users" sub-file of the Postcode Address File (PAF), which is a list of all addresses (delivery points) to which mail is delivered, prepared by the Post OffIce and held on computer. "Small users" are delivery points that receive less than 25 afiicles of mail a day and include all but a small proportion of private households. The PAF is updated regularly by the Post Office but, as mentioned in Chapter 1, there was an interruption in the supply of updates in the period leading up to the 1988 msurvey. As a result one third of the sample was drawn from the PAF as at March 1986 and two thirds from the sample as at September 1986. Although the PAF includes newly built properties ahead of their actual occupation, the 1988 sample does seem to have been light in the most recently built properties. The 1991 sample was drawn from the PAF as at May 1990 and should include most newly built houses.

Sample sizes and response rates Numbers of households who answered the questions in the Housing. Trailer were 37,175 in 1991. The corresponding response rates were 81.9 percent. Response rates were highest in East Anglia with nearly 87 percent in 1991, lowest in Inner London with only 66 percent in 1991.

Sampling deviation

One of the limitations of the LFS is that the sample design provides no guarantee of adequate coverage of any industry, as the survey is not industrially stratified. The LFS coverage also omits communal establishments, except NHS housing, students in halls of residence and at boarding schools. Members of the armed forces are only included if they live in private accommodation. Also, workers under 16 are not covered. As in previous years, the sample for the boost survey was drawn in a single stage in the most densely populated areas, in two stages elsewhere. The areas where the sample was drawn in a single stage were:

(I) local authority districts in the metropolitan counties and Greater London; (II) districts which, based on the 1981 Census.

Mode of data collection

Face-to-face [f2f]

Research instrument

All questions in the specification are laid out using the same format. Some questions (for instance USUWRKM) have a main group routed to them, but subsets of this group are asked variations of the question. In such cases the main routing is at the foot of the question as usual, and the subsets are listed separately above it, with the individual aspect of the routing indented slightly from the left of the page.

Cleaning operations

Information Technology Centres provides one-year training and practical work experience course in the use of computers and word processors and other aspects of information technology (eg teletex, editing, computer maintenance).

Response rate

The response rate achieved averaged between 79 percent. The method of calculating response rates is the following: The response rate indicates how many interviews were achieved as a proportion of those eligible for the survey. The formula used is as follows: RR = (FR + PR)/(FR + PR + OR + CR + RHQ + NC + RRI*) where RR = response rate, FR = full response, PR = partial response, OR = outright refusal, CR = circumstantial refusal, RHQ = refusal to HQ, NC = non contact, RRI = refusal to re-interview, *applies to waves two to five only.

Sampling error estimates

As with any sample survey, the results of the Labour Force Survey are subject to sampling errors. In addition, the results of any sample survey are affected by non-sampling errors, i.e. the whole variety of errors other then those due to sampling.

Data appraisal

Day of birth and date of birth variables have been removed from the annual LFS datasets, in the same way that they have been removed from the quarterly LFS datasets from 1992 onwards, as this information is now considered to be disclosive. The variable AGEDFE (age at proceeding 31 August) has been added to all annual datasets.

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.

In 2021 the live birth rate of the United Kingdom fell to 10.4 births per 1,000 population, the lowest it had been during this time period. The UK's birth rate has been declining steadily since 2010 when the birth rate was 12.9 births per 1,000 population. After 1938, the year with the highest birth rate in the UK was 1947, when the crude birth rate was 21.2 births per 1,000 population. Under two children per mother in 2021 The most recent crude live birth rate for this statistic is based on the 694,685 births, that occurred in 2021 as well as the mid-year population estimate of 67 million for the United Kingdom. It has a close relation to the fertility rate which estimates the average number of children women are expected to have in their lifetime, which was 1.53 in this reporting year. Among the constituent countries of the UK, Northern Ireland had the highest birth rate at 11.6, followed by England at 10.5, Wales at 9.3, and Scotland at 8.7. International comparisons The UK is not alone in seeing its birth and fertility rates decline dramatically in recent decades. Across the globe, fertility rates have fallen noticeably since the 1960s, with the fertility rate for Asia, Europe, and the Americas being below two in 2021. As of this year, the global fertility rate was 2.31, and was by far the highest in Africa, which had a fertility rate of 4.12, although this too has fallen from a high of 6.72 in the late 1960s. A reduction in infant mortality, as well as better access to contraception, are factors that have typically influenced declining fertility rates recently.

The fertility rate of a country is the average number of children that women from that country will have throughout their reproductive years. In the United States in 1800, the average woman of childbearing age would have seven children over the course of their lifetime. As factors such as technology, hygiene, medicine and education improved, women were having fewer children than before, reaching just two children per woman in 1940. This changed quite dramatically in the aftermath of the Second World War, rising sharply to over 3.5 children per woman in 1960 (children born between 1946 and 1964 are nowadays known as the 'Baby Boomer' generation, and they make up roughly twenty percent of todays US population). Due to the end of the baby boom and increased access to contraception, fertility reached it's lowest point in the US in 1980, where it was just 1.77. It did however rise to over two children per woman between 1995 and 2010, although it is expected to drop again by 2020, to just 1.78.

The number of abortion-related deaths in the U.S. has decreased dramatically since 1973. In 1973, the number of deaths related to abortions was 47. In 2021, the number of reported deaths related to abortions had decreased to just five. Abortion is the act of ending a pregnancy so that it does not result in the birth of a baby. Abortions in the U.S. Abortions can be performed in a surgical setting or a medical setting (the pill). The number of legal abortions reported in the U.S. has generally declined yearly since 1990. The most frequently performed kind of abortion in the U.S. in 2022 were medical abortions. Abortion and the legality and morality of the procedure has been a publicly debated topic in the United States for many years. Public opinions on abortion Opinions on abortion in the United States can be divided into two campaigns. Pro-choice is the belief that women have the right to decide when they want to become pregnant and if they want to terminate the pregnancy through an abortion. Pro-life, is the belief that women should not be able to choose to have an abortion. As of 2023, around 52 percent of the U.S. population was pro-choice, while 44 percent considered themselves pro-life. However, these shares have fluctuated over the past couple decades, with a majority of people saying they were pro-life as recently as 2019.

Brazil and the United States are the two most populous countries in the Americas today. In 1500, the year that Pedro Álvares Cabral made landfall in present-day Brazil and claimed it for the Portuguese crown, it is estimated that there were roughly one million people living in the region. Some estimates for the present-day United States give a population of two million in the year 1500, although estimates vary greatly. By 1820, the population of the U.S. was still roughly double that of Brazil, but rapid growth in the 19th century would see it grow 4.5 times larger by 1890, before the difference shrunk during the 20th century. In 2024, the U.S. has a population over 340 million people, making it the third most populous country in the world, while Brazil has a population of almost 218 million and is the sixth most populous. Looking to the future, population growth is expected to be lower in Brazil than in the U.S. in the coming decades, as Brazil's fertility rates are already lower, and migration rates into the United States will be much higher. Historical development The indigenous peoples of present-day Brazil and the U.S. were highly susceptible to diseases brought from the Old World; combined with mass displacement and violence, their population growth rates were generally low, therefore migration from Europe and the import of enslaved Africans drove population growth in both regions. In absolute numbers, more Europeans migrated to North America than Brazil, whereas more slaves were transported to Brazil than the U.S., but European migration to Brazil increased significantly in the early 1900s. The U.S. also underwent its demographic transition much earlier than in Brazil, therefore its peak period of population growth was almost a century earlier than Brazil. Impact of ethnicity The demographics of these countries are often compared, not only because of their size, location, and historical development, but also due to the role played by ethnicity. In the mid-1800s, these countries had the largest slave societies in the world, but a major difference between the two was the attitude towards interracial procreation. In Brazil, relationships between people of different ethnic groups were more common and less stigmatized than in the U.S., where anti-miscegenation laws prohibited interracial relationships in many states until the 1960s. Racial classification was also more rigid in the U.S., and those of mixed ethnicity were usually classified by their non-white background. In contrast, as Brazil has a higher degree of mixing between those of ethnic African, American, and European heritage, classification is less obvious, and factors such as physical appearance or societal background were often used to determine racial standing. For most of the 20th century, Brazil's government promoted the idea that race was a non-issue and that Brazil was racially harmonious, but most now acknowledge that this actually ignored inequality and hindered progress. Racial inequality has been a prevalent problem in both countries since their founding, and today, whites generally fare better in terms of education, income, political representation, and even life expectancy. Despite this adversity, significant progress has been made in recent decades, as public awareness of inequality has increased, and authorities in both countries have made steps to tackle disparities in areas such as education, housing, and employment.

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.

In 2024, 34.59 percent of all households in the United States were two person households. In 1970, this figure was at 28.92 percent. Single households Single mother households are usually the most common households with children under 18 years old found in the United States. As of 2021, the District of Columbia and North Dakota had the highest share of single-person households in the United States. Household size in the United States has decreased over the past century, due to customs and traditions changing. Families are typically more nuclear, whereas in the past, multigenerational households were more common. Furthermore, fertility rates have also decreased, meaning that women do not have as many children as they used to. Average households in Utah Out of all states in the U.S., Utah was reported to have the largest average household size. This predominately Mormon state has about three million inhabitants. The Church of the Latter-Day Saints, or Mormonism, plays a large role in Utah, and can contribute to the high birth rate and household size in Utah. The Church of Latter-Day Saints promotes having many children and tight-knit families. Furthermore, Utah has a relatively young population, due to Mormons typically marrying and starting large families younger than those in other states.

Globally, about 25 percent of the population is under 15 years of age and 10 percent is over 65 years of age. Africa has the youngest population worldwide. In Sub-Saharan Africa, more than 40 percent of the population is below 15 years, and only three percent are above 65, indicating the low life expectancy in several of the countries. In Europe, on the other hand, a higher share of the population is above 65 years than the population under 15 years. Fertility rates The high share of children and youth in Africa is connected to the high fertility rates on the continent. For instance, South Sudan and Niger have the highest population growth rates globally. However, about 50 percent of the world’s population live in countries with low fertility, where women have less than 2.1 children. Some countries in Europe, like Latvia and Lithuania, have experienced a population decline of one percent, and in the Cook Islands, it is even above two percent. In Europe, the majority of the population was previously working-aged adults with few dependents, but this trend is expected to reverse soon, and it is predicted that by 2050, the older population will outnumber the young in many developed countries. Growing global population As of 2025, there are 8.1 billion people living on the planet, and this is expected to reach more than nine billion before 2040. Moreover, the global population is expected to reach 10 billions around 2060, before slowing and then even falling slightly by 2100. As the population growth rates indicate, a significant share of the population increase will happen in Africa.

In the past four centuries, the population of the Thirteen Colonies and United States of America has grown from a recorded 350 people around the Jamestown colony in Virginia in 1610, to an estimated 346 million in 2025. While the fertility rate has now dropped well below replacement level, and the population is on track to go into a natural decline in the 2040s, projected high net immigration rates mean the population will continue growing well into the next century, crossing the 400 million mark in the 2070s. Indigenous population Early population figures for the Thirteen Colonies and United States come with certain caveats. Official records excluded the indigenous population, and they generally remained excluded until the late 1800s. In 1500, in the first decade of European colonization of the Americas, the native population living within the modern U.S. borders was believed to be around 1.9 million people. The spread of Old World diseases, such as smallpox, measles, and influenza, to biologically defenseless populations in the New World then wreaked havoc across the continent, often wiping out large portions of the population in areas that had not yet made contact with Europeans. By the time of Jamestown's founding in 1607, it is believed the native population within current U.S. borders had dropped by almost 60 percent. As the U.S. expanded, indigenous populations were largely still excluded from population figures as they were driven westward, however taxpaying Natives were included in the census from 1870 to 1890, before all were included thereafter. It should be noted that estimates for indigenous populations in the Americas vary significantly by source and time period. Migration and expansion fuels population growth The arrival of European settlers and African slaves was the key driver of population growth in North America in the 17th century. Settlers from Britain were the dominant group in the Thirteen Colonies, before settlers from elsewhere in Europe, particularly Germany and Ireland, made a large impact in the mid-19th century. By the end of the 19th century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. It is also estimated that almost 400,000 African slaves were transported directly across the Atlantic to mainland North America between 1500 and 1866 (although the importation of slaves was abolished in 1808). Blacks made up a much larger share of the population before slavery's abolition. Twentieth and twenty-first century The U.S. population has grown steadily since 1900, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. Since WWII, the U.S. has established itself as the world's foremost superpower, with the world's largest economy, and most powerful military. This growth in prosperity has been accompanied by increases in living standards, particularly through medical advances, infrastructure improvements, clean water accessibility. These have all contributed to higher infant and child survival rates, as well as an increase in life expectancy (doubling from roughly 40 to 80 years in the past 150 years), which have also played a large part in population growth. As fertility rates decline and increases in life expectancy slows, migration remains the largest factor in population growth. Since the 1960s, Latin America has now become the most common origin for migrants in the U.S., while immigration rates from Asia have also increased significantly. It remains to be seen how immigration restrictions of the current administration affect long-term population projections for the United States.

The influenza pandemic of 1918, known as the Spanish Flu, was one of the deadliest and widespread pandemics in human history. The scale of the outbreak, as well as limitations in technology, medicine and communication, create difficulties when trying to uncover accurate figures relating to the pandemic. Estimates suggest that the virus, known as the H1N1 influenza virus, infected more than one quarter of the global population, which equated to approximately 500 million people in 1920. It was responsible for roughly 25 million fatalities, although some projections suggest that it could have caused double this number of deaths. The exact origins of this strain of influenza remain unclear to this day, however it was first noticed in Western Europe in the latter stages of the First World War. Wartime censorship in Europe meant that the severity of the pandemic was under-reported, while news outlets in neutral Spain were free to report openly about the impact of the virus; this gave the illusion that the virus was particularly strong in Spain, giving way to the term "Spanish Flu".

Effects of the virus

By late summer 1918, the pandemic had spread across the entire continent, and the H1N1 virus had mutated into a deadlier strain that weakened the infected's immune system more than traditional influenzas. Some studies suggest that, in contrast to these traditional influenza viruses, having a stronger immune system was actually a liability in the case of the H1N1 virus as it triggered what is known as a "cytokine storm". This is where white blood cells release proteins called cytokines, which signal the body to attack the virus, in turn releasing more white blood cells which release more cytokines. This cycle over-works and greatly weakens the immune system, often giving way to other infections; most commonly pneumonia in the case of the Spanish Flu. For this reason, the Spanish Flu had an uncommonly high fatality rate among young adults, who are traditionally the healthiest group in society. Some theories for the disproportionate death-rate among young adults suggest that the elderly's immune systems benefitted from exposure to earlier influenza pandemics, such as the "Asiatic/Russian Flu" pandemic of 1889.

Decrease in life expectancy As the war in Europe came to an end, soldiers returning home brought the disease to all corners of the world, and the pandemic reached global proportions. Isolated and under-developed nations were especially vulnerable; particularly in Samoa, where almost one quarter of the population died within two months and life expectancy fell to just barely over one year for those born in 1918; this was due to the arrival of a passenger ship from New Zealand in November 1918, where the infected passengers were not quarantined on board, allowing the disease to spread rapidly. Other areas where life expectancy dropped below ten years for those born in 1918 were present-day Afghanistan, the Congo, Fiji, Guatemala, Kenya, Micronesia, Serbia, Tonga and Uganda. The British Raj, now Bangladesh, India and Pakistan, saw more fatalities than any other region, with as many as five percent of the entire population perishing as a result of the pandemic. The pandemic also had a high fatality rate among pregnant women and infants, and greatly impacted infant mortality rates across the world. There were several waves of the pandemic until late 1920, although they decreased in severity as time progressed, and none were as fatal as the outbreak in 1918. A new strain of the H1N1 influenza virus did re-emerge in 2009, and was colloquially known as "Swine Flu"; thankfully it had a much lower fatality rate due to medical advancements across the twentieth century.

The First World War saw the mobilization of more than 65 million soldiers, and the deaths of almost 15 million soldiers and civilians combined. Approximately 8.8 million of these deaths were of military personnel, while six million civilians died as a direct result of the war; mostly through hunger, disease and genocide. The German army suffered the highest number of military losses, totaling at more than two million men. Turkey had the highest civilian death count, largely due to the mass extermination of Armenians, as well as Greeks and Assyrians. Varying estimates suggest that Russia may have suffered the highest number of military and total fatalities in the First World War. However, this is complicated by the subsequent Russian Civil War and Russia's total specific to the First World War remains unclear to this day.

Proportional deaths In 1914, Central and Eastern Europe was largely divided between the empires of Austria-Hungary, Germany and Russia, while the smaller Balkan states had only emerged in prior decades with the decline of the Ottoman Empire. For these reasons, the major powers in the east were able to mobilize millions of men from across their territories, as Britain and France did with their own overseas colonies, and were able to utilize their superior manpower to rotate and replace soldiers, whereas smaller nations did not have this luxury. For example, total military losses for Romania and Serbia are around 12 percent of Germany's total military losses; however, as a share of their total mobilized forces these countries lost roughly 33 percent of their armies, compared to Germany's 15 percent mortality rate. The average mortality rate of all deployed soldiers in the war was around 14 percent.

Unclarity in the totals Despite ending over a century ago, the total number of deaths resulting from the First World War remains unclear. The impact of the Influenza pandemic of 1918, as well as various classifications of when or why fatalities occurred, has resulted in varying totals with differences ranging in the millions. Parallel conflicts, particularly the Russian Civil War, have also made it extremely difficult to define which conflicts the fatalities should be attributed to. Since 2012, the totals given by Hirschfeld et al in Brill's Encyclopedia of the First World War have been viewed by many in the historical community as the most reliable figures on the subject.

In the Nordic countries, Sweden has the largest population with over ten million inhabitants in 2023. Denmark, Finland, and Norway all have between 5.5 and six million inhabitants, whereas Iceland clearly has the lowest number with only 390,000 people. The population increased in all five Nordic countries over the past 20 years. Aging population In all five Nordic countries, the average age of the population is increasing. In all countries except Iceland, people aged 70 years or more make up the largest age groups. Hence, one of the issues facing the Nordic countries in the coming decades is that of a shrinking working stock, while there will be more elderly people in need of daily care. Births, deaths, and migration The two reasons behind the constantly increasing population in the Nordic countries are that more people are born than people dying, and a positive net migration. Except for Finland, the death rate decreased in all Nordic countries over the past 20 years. However, the fertility rate has also fallen in all five countries in the recent years, meaning that an increasing immigration play an important role in sustaining the population growth.