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

Number of births per 1,000 women. Note:Teenage birth rates are calculated using the Australian female Estimated Resident Population (ERP) aged 15–19 as the denominator.

5,30 (per thousand population) in 2021. Birth Rate (or Crude Birth Rate) refers to the ratio of the number of births to the average population (or mid-period population) during a certain period of time (usually a year), expressed in ‰. Birth rate refers to annual birth rate. The following formula is used: (Number of births)/(Annual average population)*1000‰. Number of births in the formula refers to live births, i.e. when a baby has breathed or showed any vital phenomena regardless of the length of pregnancy. Annual average population is the average of the number of population at the beginning of the year and that at the end of the year. Sometimes it is substituted by the mid-year population.

13,8 (Births per 1'000 Population) in 2010. Total country and regional values are calculated as live births according to the development of new correction factors (methodology explained in Appendix B of Vital Statistics Yearbook 2009). For the calculation of these rates estimated population as of June 30 of the current year is used according to the current Administrative Policy Division and considering the INE population estimates and projections, based on the 2002 Census. 2010: provisional figures.

The dataset contains the birth rates calculated with municipal detail for 1,000 residents in the period January - October of the year 2022. The source of the data is Istat - Demographic Report

1,60 (Children per woman) in 2016. The total fertility rate in a specific year is defined as the total number of children that would be born to each woman if she were to live to the end of her child-bearing years and give birth to children in alignment with the prevailing age-specific fertility rates. The value of indicator does not depend on age structure of population and shows average birth rate at given period. Total fertility rate is calculated as the sum of age-specific (15-49 years) fertility rates.

1.53 (Children per woman) in 2019. Total fertility rate shows potential amount of children that one woman would bear during whole childbearing period (15-50 years) if birth rate for each age remained unchanged on the level of the year, for which indicator is calculated. The value of indicator does not depend on age structure of population and shows average birth rate at given calendar period. Total fertility rate is calculated as the sum of age-specific (15-49 years) fertility rates.

1,50 (Children per woman) in 2019. The total fertility rate in a specific year is defined as the total number of children that would be born to each woman if she were to live to the end of her child-bearing years and give birth to children in alignment with the prevailing age-specific fertility rates. The value of indicator does not depend on age structure of population and shows average birth rate at given period. Total fertility rate is calculated as the sum of age-specific (15-49 years) fertility rates.

1,80 (Children per woman) in 2019. Total fertility rate shows potential amount of children that one woman would bear during whole childbearing period (15-50 years) if birth rate for each age remained unchanged on the level of the year, for which indicator is calculated. The value of indicator does not depend on age structure of population and shows average birth rate at given calendar period. Total fertility rate is calculated as the sum of age-specific (15-49 years) fertility rates.

1,48 (Children per woman) in 2019. Total fertility rate shows potential amount of children that one woman would bear during whole childbearing period (15-50 years) if birth rate for each age remained unchanged on the level of the year, for which indicator is calculated. The value of indicator does not depend on age structure of population and shows average birth rate at given calendar period. Total fertility rate is calculated as the sum of age-specific (15-49 years) fertility rates.

1,43 (Children per woman) in 2019. The total fertility rate in a specific year is defined as the total number of children that would be born to each woman if she were to live to the end of her child-bearing years and give birth to children in alignment with the prevailing age-specific fertility rates. The value of indicator does not depend on age structure of population and shows average birth rate at given period. Total fertility rate is calculated as the sum of age-specific (15-49 years) fertility rates.

1,34 (Children per woman) in 2019. Total fertility rate shows potential amount of children that one woman would bear during whole childbearing period (15-50 years) if birth rate for each age remained unchanged on the level of the year, for which indicator is calculated. The value of indicator does not depend on age structure of population and shows average birth rate at given calendar period. Total fertility rate is calculated as the sum of age-specific (15-49 years) fertility rates.

Explanations of factors represented in the calculation process of PBQ.

1,56 (Children per woman) in 2019. Total fertility rate shows potential amount of children that one woman would bear during whole childbearing period (15-50 years) if birth rate for each age remained unchanged on the level of the year, for which indicator is calculated. The value of indicator does not depend on age structure of population and shows average birth rate at given calendar period. Total fertility rate is calculated as the sum of age-specific (15-49 years) fertility rates.

Abstract

The 1995 Uganda Demographic and Health Survey (UDHS-II) is a nationally-representative survey of 7,070 women age 15-49 and 1,996 men age 15-54. The UDHS was designed to provide information on levels and trends of fertility, family planning knowledge and use, infant and child mortality, and maternal and child health. Fieldwork for the UDHS took place from late-March to mid-August 1995. The survey was similar in scope and design to the 1988-89 UDHS. Survey data show that fertility levels may be declining, contraceptive use is increasing, and childhood mortality is declining; however, data also point to several remaining areas of challenge.

The 1995 UDHS was a follow-up to a similar survey conducted in 1988-89. In addition to including most of the same questions included in the 1988-89 UDHS, the 1995 UDHS added more detailed questions on AIDS and maternal mortality, as well as incorporating a survey of men. The general objectives of the 1995 UDHS are to: - provide national level data which will allow the calculation of demographic rates, particularly fertility and childhood mortality rates; - analyse the direct and indirect factors which determine the level and trends of fertility; - measure the level of contraceptive knowledge and practice (of both women and men) by method, by urban-rural residence, and by region; - collect reliable data on maternal and child health indicators; immunisation, prevalence, and treatment of diarrhoea and other diseases among children under age four; antenatal visits; assistance at delivery; and breastfeeding; - assess the nutritional status of children under age four and their mothers by means of anthropometric measurements (weight and height), and also child feeding practices; and - assess among women and men the prevailing level of specific knowledge and attitudes regarding AIDS and to evaluate patterns of recent behaviour regarding condom use.

MAIN RESULTS

• Fertility:

Fertility Trends. UDHS data indicate that fertility in Uganda may be starting to decline. The total fertility rate has declined from the level of 7.1 births per woman that prevailed over the last 2 decades to 6.9 births for the period 1992-94. The crude birth rate for the period 1992-94 was 48 live births per I000 population, slightly lower than the level of 52 observed from the 1991 Population and Housing Census. For the roughly 80 percent of the country that was covered in the 1988-89 UDHS, fertility has declined from 7.3 to 6.8 births per woman, a drop of 7 percent over a six and a half year period.

Birth Intervals. The majority of Ugandan children (72 percent) are born after a "safe" birth interval (24 or more months apart), with 30 percent born at least 36 months after a prior birth. Nevertheless, 28 percent of non-first births occur less than 24 months after the preceding birth, with 10 percent occurring less than 18 months since the previous birth. The overall median birth interval is 29 months. Fertility Preferences. Survey data indicate that there is a strong desire for children and a preference for large families in Ugandan society. Among those with six or more children, 18 percent of married women want to have more children compared to 48 percent of married men. Both men and women desire large families.

• Family planning:

Knowledge of Contraceptive Methods. Knowledge of contraceptive methods is nearly universal with 92 percent of all women age 15-49 and 96 percent of all men age 15-54 knowing at least one method of family planning. Increasing Use of Contraception. The contraceptive prevalence rate in Uganda has tripled over a six-year period, rising from about 5 percent in approximately 80 percent of the country surveyed in 1988-89 to 15 percent in 1995.

Source of Contraception. Half of current users (47 percent) obtain their methods from public sources, while 42 percent use non-governmental medical sources, and other private sources account for the remaining 11 percent.

• Maternal and child health:

High Childhood Mortality. Although childhood mortality in Uganda is still quite high in absolute terms, there is evidence of a significant decline in recent years. Currently, the direct estimate of the infant mortality rate is 81 deaths per 1,000 births and under five mortality is 147 per 1,000 births, a considerable decline from the rates of 101 and 180, respectively, that were derived for the roughly 80 percent of the country that was covered by the 1988-89 UDHS.

Childhood Vaccination Coverage. One possible reason for the declining mortality is improvement in childhood vaccination coverage. The UDHS results show that 47 percent of children age 12-23 months are fully vaccinated, and only 14 percent have not received any vaccinations.

Childhood Nutritional Status. Overall, 38 percent of Ugandan children under age four are classified as stunted (low height-for-age) and 15 percent as severely stunted. About 5 percent of children under four in Uganda are wasted (low weight-for-height); 1 percent are severely wasted. Comparison with other data sources shows little change in these measures over time.

• AIDS:

Virtually all women and men in Uganda are aware of AIDS. About 60 percent of respondents say that limiting the number of sexual partners or having only one partner can prevent the spread of disease. However, knowledge of ways to avoid AIDS is related to respondents' education. Safe patterns of sexual behaviour are less commonly reported by respondents who have little or no education than those with more education. Results show that 65 percent of women and 84 percent of men believe that they have little or no chance of being infected.

Availability of Health Services. Roughly half of women in Uganda live within 5 km of a facility providing antenatal care, delivery care, and immunisation services. However, the data show that children whose mothers receive both antenatal and delivery care are more likely to live within 5 km of a facility providing maternal and child health (MCH) services (70 percent) than either those whose mothers received only one of these services (46 percent) or those whose mothers received neither antenatal nor delivery care (39 percent).

Geographic coverage

The 1995 Uganda Demographic and Health Survey (UDHS-II) is a nationally-representative survey. For the purpose of the 1995 UDHS, the following domains were utilised: Uganda as a whole; urban and rural areas separately; each of the four regions: Central, Eastern, Northern, and Western; areas in the USAID-funded DISH project to permit calculation of contraceptive prevalence rates.

Analysis unit

• Household
• Women age 15-49
• Men age 15-54
• Children under four

Universe

The population covered by the 1995 UDHS is defined as the universe of all women age 15-49 in Uganda. But because of insecurity, eight EAs could not be surveyed (six in Kitgum District, one in Apac District, and one in Moyo District). An additional two EAs (one in Arua and one in Moroto) could not be surveyed, but substitute EAs were selected in their place.

Kind of data

Sample survey data

Sampling procedure

A sample of 303 primary sampling units (PSU) consisting of enumeration areas (EAs) was selected from a sampling frame of the 1991 Population and Housing Census. For the purpose of the 1995 UDHS, the following domains were utilised: Uganda as a whole; urban and rural areas separately; each of the four regions: Central, Eastern, Northern, and Western; areas in the USAID-funded DISH project to permit calculation of contraceptive prevalence rates.

Districts in the DISH project area were grouped by proximity into the following five reporting domains: - Kasese and Mbarara Districts - Masaka and Rakai Districts - Luwero and Masindi Districts - Jinja and Kamuli Districts - Kampala District

The sample for the 1995 UDHS was selected in two stages. In the first stage, 303 EAs were selected with probability proportional to size. Then, within each selected EA, a complete household listing and mapping exercise was conducted in December 1994 forming the basis for the second-stage sampling. For the listing exercise, 11 listers from the Statistics Department were trained. Institutional populations (army barracks, hospitals, police camps, etc.) were not listed.

From these household lists, households to be included in the UDHS were selected with probability inversely proportional to size based on the household listing results. All women age 15-49 years in these households were eligible to be interviewed in the UDHS. In one-third of these selected households, all men age 15-54 years were eligible for individual interview as well. The overall target sample was 6,000 women and 2,000 men. Because of insecurity, eight EAs could not be surveyed (six in Kitgum District, one in Apac District, and one in Moyo District). An additional two EAs (one in Arua and one in Moroto) could not be surveyed, but substitute EAs were selected in their place.

Since one objective of the survey was to produce estimates of specific demographic and health indicators for the areas included in the DISH project, the sample design allowed for oversampling of households in these districts relative to their actual proportion in the population. Thus, the 1995 UDHS sample is not self-weighting at the national level; weights are required to estimate national-level indicators. Due to the weighting factor and rounding of estimates, figures may not add to totals. In addition, the percent total may not add to 100.0 due to rounding.

Mode of data collection

Face-to-face

Research instrument

Four questionnaires were used in the 1995 UDHS.

a) A Household Schedule was used to list the names and certain

This dataset contains California’s adolescent birth rate (ABR) by county, age group and race/ethnicity using aggregated years 2014-2016. The ABR is calculated as the number of live births to females aged 15-19 divided by the female population aged 15-19, multiplied by 1,000. Births to females under age 15 are uncommon and thus added to the numerator (total number of births aged 15-19) in calculating the ABR for aged 15-19. The categories by age group are aged 18-19 and aged 15-17; births occurring to females under aged 15 are added to the numerator for aged 15-17 in calculating the ABR for this age group. The race and ethnic groups in this table utilized five mutually exclusive race and ethnicity categories. These categories are Hispanic and the following Non-Hispanic categories of Multi-Race, Black, American Indian (includes Eskimo and Aleut), Asian and Pacific Islander (includes Hawaiian) combined, and White. Note that there are birth records with missing race/ethnicity or categorized as “Other” and not shown in the dataset but included in the ABR calculation overall.

Contains data on the number of births in a year per 1,000 inhabitants of the resident population for all municipalities in Veneto from 1990 to the last year available. The data come from the Istat survey “Movement and calculation of the annual resident population”.

1,52 (Children per woman) in 2016. The total fertility rate in a specific year is defined as the total number of children that would be born to each woman if she were to live to the end of her child-bearing years and give birth to children in alignment with the prevailing age-specific fertility rates. The value of indicator does not depend on age structure of population and shows average birth rate at given period. Total fertility rate is calculated as the sum of age-specific (15-49 years) fertility rates.

1,35 (Children per woman) in 2019. The total fertility rate in a specific year is defined as the total number of children that would be born to each woman if she were to live to the end of her child-bearing years and give birth to children in alignment with the prevailing age-specific fertility rates. The value of indicator does not depend on age structure of population and shows average birth rate at given period. Total fertility rate is calculated as the sum of age-specific (15-49 years) fertility rates.

Analysis of ‘BirthData 2010 13 WayneZips’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/f71b8987-9136-4cc5-92a4-590f882f0df5 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

Annual average birth data by zip code from the Michigan Department of Community Health, Vital Statistics. Covers years 2009-11, 2010-12, and 2011-13. Birth rates were calculated by Kurt Metzger. Birth Rate = Number of births per 1,000 Women 15-44 years of age (2010 Census).

--- Original source retains full ownership of the source dataset ---