In 2022, the median age for the first wedding among women in the United States stood at 28.6 years. For men, the median age was 30.5 years. The median age of Americans at their first wedding has been steadily increasing for both men and women since 1998.

This statistic contains data on the estimated median age of Americans at their first wedding in the United States in 2021, by race and origin. In 2021, the median age for the first wedding among Asian women stood at 28.8 years.

Age at First Marriage in America

The Effect of Population Density

By Andy Kriebel [source]

About this dataset

This dataset contains information on the median age at first marriage for women in the United States. The data is broken down by county, and includes information on population density, FIPS code, and county type

How to use the dataset

This dataset contains information on the age at first marriage for women in the United States. The data is broken down by state, county, and year. To use this dataset, you can choose to either download the entire dataset or select specific states, counties, and years of interest. If you select specific states, counties, and years of interest, be sure to filter the data accordingly

Research Ideas

To find out which states have the oldest or youngest median ages at first marriage. To understand how population density may affect the median age at first marriage. To compare the median age at first marriage across different types of counties

Acknowledgements

Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: Median Age at First Marriage .csv | Column name | Description | |:---------------------------------|:---------------------------------------------------------------------------| | FIPS | The Federal Information Processing Standard code for each county. (String) | | Name | The name of the county. (String) | | Type | The type of county. (String) | | TimeFrame | The timeframe of the data. (String) | | Median Age | The median age at first marriage for women in the county. (Float) | | Population Density per Sq Mi | The population density of the county. (Float) |

Acknowledgements

If you use this dataset in your research, please credit Andy Kriebel.

Since the mid-2000s, the average age at first wedding in France has increased gradually, for both men and women. It seems to be common for the first marriage to be celebrated later and later in Western countries. For example, the median age at first marriage in the United States went from **** years old for males and ** years old for females in 1998, up to **** years old for males and **** for females in 2022. The same thing occurred in Europe, where Spain was the country where the median age at first wedding was the oldest in 2022. French people wait longer to marry According to the source, in 2004, the average age at first wedding for French men was **** compared to **** for women. If men still tend to be older than women at first marriage, the average age at marriage for both males and females increased from 2004 to 2024. In 2024, men were on average **** at their first wedding, compared to **** for women. Most marriages in France happened between men and women, despite the implementation of same-sex marriage in 2013. The mean age at gay marriages appears to be even older than in different-sex weddings. Marriage and divorce in France Thus, the percentage of married persons in France has decreased since 2006, while the share of single and divorced people rose. However, in 2016, France was the second European country with the highest number of marriages behind Germany. On the other hand, like most other Western nations, France also has a high divorce rate. In 2016, the number of French divorces was ** per 100 marriages.

81 percent of the Silent generation were married between the age of 23 and 38. This is true for only 44 percent of Millennials.

United States Marriage Statistics

Marriage rates by gender, age group, and year in the United States (2005-2017)

By Throwback Thursday [source]

About this dataset

This dataset, titled United States Marriage Status 2005-2017, provides detailed information on marriage rates and population estimates in the United States. The data is sourced from the U.S. Census Bureau's American Community Survey 1-Year Estimates.

The dataset includes several key attributes that offer insights into different aspects of marriage status. These attributes include Year, Gender, Age Group, Metric, Estimated Percent, and Estimated Population.

The Year attribute represents the year in which the data was collected, spanning from 2005 to 2017. It allows for analysis of trends and changes in marriage rates over time.

The Gender attribute categorizes the population groups based on their gender. This information helps explore any variations or differences between male and female populations in terms of marital status.

Age Group attribute classifies individuals into specific age categories within the population. By segmenting the data based on age groups, it becomes possible to analyze how different age demographics contribute to overall marriage rates.

Metric serves as a descriptor for specific measurements or indicators being reported within this dataset. This attribute provides further context for understanding different aspects related to marriage status and its calculation methods.

Estimated Percent denotes the estimated percentage of a particular population group falling into a specific category related to marital status. It offers valuable insights into relative proportions within each demographic group.

Estimated Population showcases estimated count figures representing various subgroups' populations classified by gender, age groupings, and metric categories specified previously. These estimates allow researchers to explore potential correlations between population sizes and marriage rates across various segments of society over time period covered by this dataset.

Overall, this comprehensive United States Marriage Status dataset provides a valuable resource for analyzing trends in marriage rates while considering gender demographics, age distributions within these populations along with respective metrics indicating changes occurring over time periods marked since 2005 until 2017 (date-range excluding exact dates provided). By exploring relationships among these factors using reliable census data available through American Community Survey 1-Year Estimates, researchers can gain deep understanding of marriage status dynamics in the United States

How to use the dataset

• Understand the Columns:

  • Year: This column represents the year in which the data was collected. It provides a timeline for analyzing marriage trends over time.
  • Gender: This column categorizes individuals based on their gender, providing insights into marriage rates and patterns specific to each gender.
  • Age Group: This column categorizes individuals based on their age group. It allows for a detailed analysis of marriage rates and statistics among different age groups.
  • Metric: This column specifies the type of data or measurement being reported, providing clarity on what aspect of marriage is being analyzed.
  • Estimated Percent: This column represents the estimated percentage of individuals within a population group falling into a particular category. It quantifies marriage rates as percentages.
  • Estimated Population: This column provides an estimation of the total population count within a specific category, offering insights into the size and distribution of different population groups.

• Analyzing Trends: Use this dataset to analyze trends in US marriage statistics by leveraging various combinations of columns:

  • Gender vs Metric: Compare different metrics (e.g., number of marriages, divorce rate) between genders, allowing for an understanding of any gender-specific variations in marital trends.
  • Year vs Metric: Study changes in various metrics over time (e.g., changes in average age at first marriage), identifying trends and potential shifts in societal attitudes towards marriage.
  • Age Group vs Metric/Gender/Year: Examine how different age groups contribute to overall marital statistics (e.g., comparing divorce rates among different age groups or analyzing changes over time within specific age cohorts).

• Interpreting Results: When analyzing this dataset's results, keep these factors in mind:

  • Size Differences: Ensure you factor in the estimated population count for eac...

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Tell us what you think. Provide feedback to help make American Community Survey data more useful for you..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2012-2016 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2012-2016 American Community Survey 5-Year Estimates

In 2022, there were 67.85 million married men and 68.45 million married women living in the United States. This is compared to 3.7 million widowed men and 11.48 million widowed women.

Marriage in the United States

Nevada had the highest marriage rate in the United States in 2021, followed by Hawaii and Montana. This can be attributed to marriage accessibility in the state. Las Vegas weddings are known for being quick, easy, and inexpensive chapel weddings. In comparison to the cheap weddings available in Las Vegas, the average expenditure for a wedding in the United States was the highest in New Jersey, clocking in at 51,000 U.S. dollars.

Same-sex marriage

The number of Americans who think that same-sex marriage should be recognized by law has more than doubled since 1996, while the number of Americans who think it should not be valid has decreased. It was not until June 26, 2015 that the United States Supreme Court legalized same-sex marriage in all 50 states. Before then, it was up to the states to decide if they allowed same-sex marriage. States in the Southeast are the most opposed to same-sex marriage, whereas the strongest support comes from Northern coastal states.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2021 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2019 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself.An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.An "(X)" means that the estimate is not applicable or not available.

This dataset provides valuable insights into the work and household characteristics of married individuals in the United States. With 753 observations representing individuals, the dataset offers a comprehensive view of various factors that influence work patterns and family dynamics.

Details

These data seem to have come from the same source as carData::Mroz, though each data set has variables not in the other. The variables that are shared have different names. On 2019-11-04 Bruno Rodrigues explained that Ecdat::Mroz['work'] had the two labels incorrectly swapped, and wooldridge::mroz['inlf'] was correct; wooldridge matches carData::Mroz['lfp'].

Source

Mroz, T. (1987) “The sensitivity of an empirical model of married women's hours of work to economic and statistical assumptions”, Econometrica, 55, 765-799. 1976 Panel Study of Income Dynamics.

References

Greene, W.H. (2003) Econometric Analysis, Prentice Hall, https://archive.org/details/econometricanaly0000gree_f4x3, Table F4.1.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2017 American Community Survey (ACS) data generally reflect the July 2015 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas, in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2017 American Community Survey 1-Year Estimates

The Wedding Services industry provides a wide variety of wedding day services, apparel retailers and venues. Evolving social norms and medical advancements, which enable women to safely give birth later in life, have caused the marriage rate to decline in recent decades. Extended periods of cohabitation before marriage and family planning have increasingly become normal among young couples. As a result, the industry has contended with declining revenue over the past five years. Despite fewer couples getting married, increasing per capita disposable income has enabled those seeking to spend more on their big day, limiting revenue declines. Nonetheless, as couples postponed or downsized their weddings during the COVID-19 pandemic, industry revenue dropped significantly in 2020 alone. Consequently, industry revenue fell at a CAGR of 4.1% to $70.3 billion over the past five years, including a decrease of 0.6% in 2023 alone.Despite rising wedding budgets, which translated to higher revenue, heightened competition has hindered revenue per operator. Over the past five years, the barriers to entry for operators in this industry have decreased as more couples can find vendors through the internet. Online marketing and social media have increased visibility for wedding services and lowered marketing budgets, making it easier for new companies to enter the industry. But, coronavirus-related pressures forced many of these new entrants out of the industry. Also, limited demand because of the declining marriage rate has led to lower revenue per operator somewhat deterring new entrants.Moving forward, industry demand will continue to be pressured by the marriage rate, which will further decline over the next five years. Even so, continued pent-up demand from previously postponed weddings will support industry revenue. During the outlook period, rising consumer confidence indicates that individuals will be more willing to take on nonessential expenditures and incur high wedding costs. Also, the increasing average age of marriage and the length of engagements will give couples more time to plan and save money for their ceremonies. Overall, industry revenue will rise at a CAGR of 0.2% to $71.1 billion over the next five years.

NOTE: For information on confidentiality protection, nonsampling error, and definitions, see http://www.census.gov/prod/cen2010/doc/sf1.pdf..Source: U.S. Census Bureau, 2010 Census..NOTE: "Families" consist of a householder and one or more other people related to the householder by birth, marriage, or adoption. They do not include same-sex married couples even if the marriage was performed in a state issuing marriage certificates for same-sex couples. Responses of "same-sex spouse" were edited during processing to "unmarried partner."

The focus of this domain is on the European Neighbourhood Policy (ENP) countries on the southern and eastern shores of the Mediterranean (ENP-South), namely:

• Algeria (DZ),
• Egypt (EG),
• Israel (IL),
• Jordan (JO),
• Lebanon (LB),
• Libya (LY),
• Morocco (MA),
• Palestine (PS) (¹),
• Syria (SY) and
• Tunisia (TN).

An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain.

The data and their denomination in no way constitute the expression of an opinion by the European Commission on the legal status of a country or territory or on the delimitation of its borders.

Data supplied by and under the responsibility of the national statistical authorities of each of the countries or territories.

(¹) This designation shall not be construed as recognition of a State of Palestine and is without prejudice to the individual positions of the Member States on this issue.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the .Technical Documentation.. section......Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the .Methodology.. section..Source: U.S. Census Bureau, 2018 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see .ACS Technical Documentation..). The effect of nonsampling error is not represented in these tables..While the 2018 American Community Survey (ACS) data generally reflect the July 2015 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas, in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:..An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself..An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution..An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution..An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An "(X)" means that the estimate is not applicable or not available....

This statistic shows the average income of married and unmarried men in the United States in 2016, by age. In that year, 45-year-old married men had an average income of **** thousand U.S. dollars, compared to 45-year-old unmarried men, who had an average income of **** thousand U.S. dollars.

Estimates of the average ages at marriage in 1990 for different education levels.

The highest share of home buyers in the United States in 2024 across all age groups were married couples. Married couples made up at least ** percent of home buyers in all age groups that year, except for homebuyers aged between 18 and 25 years old.

Abstract

The 1990 Nigeria Demographic and Health Survey (NDHS) is a nationally representative survey conducted by the Federal Office of Statistics with the aim of gathering reliable information on fertility, family planning, infant and child mortality, maternal care, vaccination status, breastfeeding, and nutrition. Data collection took place two years after implementation of the National Policy on Population and addresses issues raised by that policy.

Fieldwork for the NDHS was conducted in two phases: from April to July 1990 in the southern states and from July to October 1990 in the northern states. Interviewers collected information on the reproductive histories of 8,781 women age 15-49 years and on the health of their 8,113 children under the age of five years.

OBJECTIVES

The Nigeria Demographic and Health Survey (NDHS) is a national sample survey of women of reproductive age designed to collect data on socioeconomic characteristics, marriage patterns, history of child bearing, breastfeeding, use of contraception, immunisation of children, accessibility to health and family planning services, treatment of children during episodes of illness, and the nutritional status of children.

The primary objectives of the NDHS are:

(i) To collect data for the evaluation of family planning and health programmes; (ii) To assess the demographic situation in Nigeria; and (iii) To support dissemination and utilisation of the results in planning and managing family planning and health programmes.

MAIN RESULTS

According to the NDHS, fertility remains high in Nigeria; at current fertility levels, Nigerian women will have an average of 6 children by the end of their reproductive years. The total fertility rate may actually be higher than 6.0, due to underestimation of births. In a 1981/82 survey, the total fertility rate was estimated to be 5.9 children per woman.

One reason for the high level of fertility is that use of contraception is limited. Only 6 percent of married women currently use a contraceptive method (3.5 percent use a modem method, and 2.5 percent use a traditional method). These levels, while low, reflect an increase over the past decade: ten years ago just 1 percent of Nigerian women were using a modem family planning method. Periodic abstinence (rhythm method), the pill, IUD, and injection are the most popular methods among married couples: each is used by about 1 percent of currently married women. Knowledge of contraception remains low, with less than half of all women age 15-49 knowing of any method.

Certain groups of women are far more likely to use contraception than others. For example, urban women are four times more likely to be using a contraceptive method (15 percent) than rural women (4 percent). Women in the Southwest, those with more education, and those with five or more children are also more likely to be using contraception.

Levels of fertility and contraceptive use are not likely to change until there is a drop in desired family size and until the idea of reproductive choice is more widely accepted. At present, the average ideal family size is essentially the same as the total fertility rate: six children per woman. Thus, the vast majority of births are wanted. The desire for childbearing is strong: half of women with five children say that they want to have another child.

Another factor leading to high fertility is the early age at marriage and childbearing in Nigeria. Half of all women are married by age 17 and half have become mothers by age 20. More than a quarter of teenagers (women age 15-19 years) either are pregnant or already have children.

National statistics mask dramatic variations in fertility and family planning between urban and rural areas, among different regions of the country, and by women's educational attainment. Women who are from urban areas or live in the South and those who are better educated want and have fewer children than other women and are more likely to know of and use modem contraception. For example, women in the South are likely to marry and begin childbearing several years later than women in the North. In the North, women continue to follow the traditional pattern and marry early, at a median age of 15, while in the South, women are marrying at a median age of 19 or 20. Teenagers in the North have births at twice the rate of those in the South: 20 births per 1130 women age 15-19 in the North compared to 10 birdas per 100 women in the South. Nearly half of teens in the North have already begun childbearing, versus 14 percent in South. This results in substantially lower total fertility rates in the South: women in the South have, on average, one child less than women in the North (5.5 versus 6.6).

The survey also provides information related to maternal and child health. The data indicate that nearly 1 in 5 children dies before their fifth birthday. Of every 1,000 babies born, 87 die during their first year of life (infant mortality rate). There has been little improvement in infant and child mortality during the past 15 years. Mortality is higher in rural than urban areas and higher in the North than in the South. Undemutrition may be a factor contributing to childhood mortality levels: NDHS data show that 43 percent of the children under five are chronically undemourished. These problems are more severe in rural areas and in the North.

Preventive and curative health services have yet to reach many women and children. Mothers receive no antenatal care for one-third of births and over 60 percent of all babies arc born at home. Only one-third of births are assisted by doctors, trained nurses or midwives. A third of the infants are never vaccinated, and only 30 percent are fully immunised against childhood diseases. When they are ill, most young children go untreated. For example, only about one-third of children with diarrhoea were given oral rehydration therapy.

Women and children living in rural areas and in the North are much less likely than others to benefit from health services. Almost four times as many births in the North are unassisted as in the South, and only one-third as many children complete their polio and DPT vaccinations. Programmes to educate women about the need for antenatal care, immunisation, and proper treatment for sick children should perhaps be aimed at mothers in these areas,

Mothers everywhere need to learn about the proper time to introduce various supplementary foods to breastfeeding babies. Nearly all babies are breastfed, however, almost all breastfeeding infants are given water, formula, or other supplements within the first two months of life, which both jeopardises their nutritional status and increases the risk of infection.

Geographic coverage

The 1990 Nigeria Demographic and Health Survey (NDHS) is a nationally representative survey. The sample was constructed so as to provide national estimates as well as estimates for the four Ministry of Health regions.

Analysis unit

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

Universe

The population covered by the 1990 DHS is defined as the universe of all women age 15-49 in Nigeria.

Kind of data

Sample survey data

Sampling procedure

The NDHS Sample was drawn from the National Master Sample for the 1987/1992 National Integrated Survey of Households (NISH) programme being implemented by the Federal Office of Statistics (FOS). NISH, as part of the United Nations National Household Survey Capability Programme, is a multi- subject household-based survey system.

The NISH master sample was created in 1986 on the basis of the 1973 census enumeration areas (EA). Within each state, EAs were stratified into three sectors (urban, semiurban, and rural), from which an initial selection of approximately 8C0 EAs was made from each state. EAs were selected at this stage with equal probability within sectors. A quick count of households was conducted in each of the selected EAs, and a final selection of over 4,000 EAs was made over the entire country, with probability proportional to size. This constitutes the NISH master sample from which the NDHS EAs were subsampled.

Prior to the NDHS selection of EAs, the urban and semiurban sectors of NISH were combined into one category, while the rural retained the NISH classification. A sample of about 10,000 households in 299 EAs was designed with twofold oversampling of the urban stratum, yielding 132 urban EAs and 167 rural EAs. The sample was constructed so as to provide national estimates as well as estimates for the four Ministry of Health regions.

The NDHS conducted its own EA identification and listing operation; a new listing of housing units and households was compiled in each of the selected 299 EAs. For each EA, a list of the names of the head of households was constructed, from which a systematic sample of 34 households was selected to be interviewed. A fixed number of 34 households per EA was taken in order to have better control of the sample size (given the variability in EA size of the NISH sample). Thus, the NDHS sample is a weighted sample, maintaining the twofold over sampling of the urban sector.

Mode of data collection

Face-to-face

Research instrument

Three questionnaires were used in the main fieldwork for the NDHS: a) the household questionnaire, b) the individual questionnaire, and c) the service availability questionnaire. The first two questionnaires were adapted from the DHS model B questionnaire, which was designed for use in countries with low contraceptive prevalence. The questionnaires were developed in English, and then translated into six of the major Nigerian languages: Efik, Hausa, Igbo, Kanuri,