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LGA based data for Ancestry by Country of Birth of Parents, in Place of Enumeration Profile (PEP), 2016 Census. Count of responses and persons (excluding overseas visitors) in the following categories with corresponding ancestry: both parents born overseas, father born overseas, mother born overseas, both parents born in Australia, parents birthplace not stated. The list of ancestries consists of the most common 30 Ancestry responses reported in the 2011 Census. This is a multi-response dataset and therefore the total responses count will not equal the total persons count. If two responses from one person are categorised in the 'Other' category only one response is counted. If either or both parents birthplace is not stated then a single response is tallied in the 'not stated' category. The data is by LGA 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.

PLEASE, CITE AS Kalabikhina IE, Kuznetsova PO, Zhuravleva SA (2024) Size and factors of the motherhood penalty in the labour market: A meta-analysis. Population and Economics 8(2): 178-205. https://doi.org/10.3897/popecon.8.e121438

Explanatory note 1: List of papers used in the meta-analysis - see the file "Meta_regression_analysis_papers".

The data is presented in WORD format.

Explanatory note 2: Set of data used in the meta-analysis - see the file "Meta_regression_analysis_table".

The data is presented in EXCEL format.

Description of table headers:

estimate_number - Number of the estimate

paper_number - Number of the paper

paper_name - Paper (year and first author)

paper_excluded - Paper was excluded from the final sample

survey - Data source

table_in_paper - Number of the table with the regression results in the paper

coeff - Regression coefficient for parenthood variable (estimate)

se - SE of the estimate

t - t-value of the estimate

ols - Estimate is obtained using the OLS method

fixed_effects - Estimate is obtained using the fixed effects method

panel - Model considers panel data (for several years)

quintile - Estimate is obtained using the quintile regression method

other - Estimate is obtained using other methods

selection_into_motherhood - Estimate is obtained allowing for selection into motherhood

hackman - Estimate is obtained allowing for selection into employment (Heckman procedure)

annual_earnings - Annual earnings are considered in the model

monthly_wage - Monthly wage is considered in the model

daily_wage - Daily wage is considered in the model

hourly_wage - Hourly wage is considered in the model

min_age_kid - Child's age (minimum)

max_age_kid - Child's age (maximum)

motherhood - Model uses a dummy variable of the presence of children

num_kids - Model uses a variable of the number of children

kid1 - Model uses a variable of the presence of one child

kid2p - Model uses a variable of the presence of two or more children

kid2 - Model uses a variable of the presence of two children

kid3p - Model uses a variable of the presence of three or more children

kid3 - Model uses a variable of the presence of three children

kid4p - Model uses a variable of the presence of three or more children

race/nationality - Model includes a race/ethnicity variable

age - Model includes the age variable

marstat - Model includes the marital status variable

oth_char_hh - Model includes any other variables of other household characteristics

settl_type - Model includes a variable of the type of settlement (urban, rural)

region - Model includes a variable of the region of the country

education - Model includes information on the level of education

experience - Model includes a variable of work experience

pot_experience - Model includes a variable of potential work experience, to be calculated from the data on age and number of years of education

tenure - Model includes a variable of the duration of employment at the current job

interruptions - Model includes a variable of employment interruptions (related to motherhood)

occupation - Model includes an occupation variable

industry - Model includes a variable of the industry of employment

union - Model includes a variable of trade union membership

friendly_conditions - Model includes a variable of the favourable working conditions for mothers (flexible schedule, possibility to work from home, etc.).

hours - Model includes a variable of the number of hours worked

sector - Model includes a variable of the type of employer ownership (public or private)

informal - Model includes a variable of informal employment

size_ent - Model includes a variable of the employer size

min_age_woman - Woman's age (minimum)

max_age_woman - Woman's age (maximum)

mean_age_woman - Woman's age (mean)

restricted - Sample is limited

private - Model considers only private sector employees

state - Model considers only public sector employees

full_time - Model considers only full-time workers

part_time - Model considers only part-time workers

better_educated - Model considers only women with a high level of education

lower_educated - Model considers only women with a low level of education

married - Model includes only married women

single - Model includes only single women

natives - Model includes only native women (born in the country)

immigrants - Model includes only immigrant women (born abroad)

race - Model includes only women of a particular race

min_year - Time period (minimum year)

max_year - Time period (maximum year)

journal - Type of publication

usa - Sample includes women from the USA

western_europe - Sample includes women from Western Europe (Belgium, France, Germany, Luxembourg, the Netherlands, Switzerland)

north_europe - Sample includes women from Northern Europe (Denmark, Finland, Norway, Sweden)

south_europe - Sample includes women from Southern Europe (Greece, Italy, Portugal, Spain)

east_centre_europe - Sample includes women from Central or Eastern Europe (Czechia, Hungary, Poland, Russia, Serbia, Ukraine)

china - Sample includes women from China

Russia - Sample includes women from Russia

others - Sample includes women from other countries

country - Country name

SA2 based data for Ancestry by Country of Birth of Parents, in Place of Enumeration Profile (PEP), 2016 Census. Count of responses and persons (excluding overseas visitors) in the following categories with corresponding ancestry: both parents born overseas, father born overseas, mother born overseas, both parents born in Australia, parents birthplace not stated. The list of ancestries consists of the most common 30 Ancestry responses reported in the 2011 Census. This is a multi-response dataset and therefore the total responses count will not equal the total persons count. If two responses from one person are categorised in the 'Other' category only one response is counted. If either or both parents birthplace is not stated then a single response is tallied in the 'not stated' category. The data is by SA2 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.

The Sudan Demographic and Health Survey (SDHS) was conducted in two phases between November 15, 1989 and May 21, 1990 by the Department of Statistics of the Ministry of Economic and National Planning. The survey collected information on fertility levels, marriage patterns, reproductive intentions, knowledge and use of contraception, maternal and child health, maternal mortality, and female circumcision. The survey findings provide the National Population Committee and the Ministry of Health with valuable information for use in evaluating population policy and planning public health programmes. A total of 5860 ever-married women age 15-49 were interviewed in six regions in northern Sudan; three regions in southern Sudan could not be included in the survey because of civil unrest in that part of the country. The SDHS provides data on fertility and mortality comparable to the 1978-79 Sudan Fertility Survey (SFS) and complements the information collected in the 1983 census. The primary objective of the SDHS was to provide data on fertility, nuptiality, family planning, fertility preferences, childhood mortality, indicators of maternal health care, and utilization of child health services. Additional information was coUected on educational level, literacy, source of household water, and other housing conditions. The SDHS is intended to serve as a source of demographic data for comparison with the 1983 census and the Sudan Fertility Survey (SFS) 1978-79, and to provide population and health data for policymakers and researchers. The objectives of the survey are to: assess the overall demographic situation in Sudan, assist in the evaluation of population and health programmes, assist the Department of Statistics in strengthening and improving its technical skills for conducting demographic and health surveys, enable the National Population Committee (NPC) to develop a population policy for the country, and measure changes in fertility and contraceptive prevalence, and study the factors which affect these changes, and examine the basic indicators of maternal and child health in Sudan. MAIN RESULTS Fertility levels and trends Fertility has declined sharply in Sudan, from an average of six children per women in the Sudan Fertility Survey (TFR 6.0) to five children in the Sudan DHS survey flTR 5.0). Women living in urban areas have lower fertility (TFR 4.1) than those in rural areas (5.6), and fertility is lower in the Khartoum and Northern regions than in other regions. The difference in fertility by education is particularly striking; at current rates, women who have attained secondary school education will have an average of 3.3 children compared with 5.9 children for women with no education, a difference of almost three children. Although fertility in Sudan is low compared with most sub-Saharan countries, the desire for children is strong. One in three currently married women wants to have another child within two years and the same proportion want another child in two or more years; only one in four married women wants to stop childbearing. The proportion of women who want no more children increases with family size and age. The average ideal family size, 5.9 children, exceeds the total fertility rate (5.0) by approximately one child. Older women are more likely to want large families than younger women, and women just beginning their families say they want to have about five children. Marriage Almost all Sudanese women marry during their lifetime. At the time of the survey, 55 percent of women 15-49 were currently married and 5 percent were widowed or divorced. Nearly one in five currently married women lives in a polygynous union (i.e., is married to a man who has more than one wife). The prevalence of polygyny is about the same in the SDHS as it was in the Sudan Fertility Survey. Marriage occurs at a fairly young age, although there is a trend toward later marriage among younger women (especially those with junior secondary or higher level of schooling). The proportion of women 15-49 who have never married is 12 percentage points higher in the SDHS than in the Sudan Fertiliy Survey. There has been a substantial increase in the average age at first marriage in Sudan. Among SDHS. Since age at first marriage is closely associated with fertility, it is likely that fertility will decrease in the future. With marriages occurring later, women am having their first birth at a later age. While one in three women age 45-49 had her first birth before age 18, only one in six women age 20-24 began childbearing prior to age 18. The women most likely to postpone marriage and childbearing are those who live in urban areas ur in the Khartoum and Northern regions, and women with pest-primary education. Breastfeeding and postpartum abstinence Breastfeeding and postpartum abstinence provide substantial protection from pregnancy after the birth uf a child. In addition to the health benefits to the child, breastfeeding prolongs the length of postpartum amenorrhea. In Sudan, almost all women breastfeed their children; 93 percent of children are still being breastfed 10-11 months after birth, and 41 percent continue breastfeeding for 20-21 months. Postpartum abstinence is traditional in Sudan and in the first two months following the birth of a child 90 percent of women were abstaining; this decreases to 32 percent after two months, and to 5 percent at~er one year. The survey results indicate that the combined effects of breastfeeding and postpartum abstinence protect women from pregnancy for an average of 15 months after the birth of a child. Knowledge and use of contraception Most currently married women (71 percent) know at least one method of family planning, and 59 percent know a source for a method. The pill (70 percent) is the most widely known method, followed by injection, female sterilisation, and the IUD. Only 39 percent of women knew a traditional method of family planning. Despite widespread knowledge of family planning, only about one-fourth of ever-married women have ever used a contraceptive method, and among currently married women, only 9 percent were using a method at the time of the survey (6 percent modem methods and 3 percent traditional methods). The level of contraceptive use while still low, has increased from less than 5 percent reported in the Sudan Fertility Survey. Use of family planning varies by age, residence, and level of education. Current use is less than 4 percent among women 15-19, increases to 10 percent for women 30-44, then decreases to 6 percent for women 45-49. Seventeen percent of urban women practice family planning compared with only 4 percent of rural women; and women with senior secondary education are more likely to practice family planning (26 percent) than women with no education (3 percent). There is widespread approval of family planning in Sudan. Almost two-thirds of currently married women who know a family planning method approve of the use of contraception. Husbands generally share their wives's views on family planning. Three-fourths of married women who were not using a contraceptive method at the time of the survey said they did not intend to use a method in the future. Communication between husbands and wives is important for successful family planning. Less than half of currently married women who know a contraceptive method said they had talked about family planning with their husbands in the year before the survey; one in four women discussed it once or twice; and one in five discussed it more than twice. Younger women and older women were less likely to discuss family planning than those age 20 to 39. Mortality among children The neonatal mortality rate in Sudan remained virtually unchanged in the decade between the SDHS and the SFS (44 deaths per 1000 births), but under-five mortality decreased by 14 percent (from 143 deaths per 1000 births to 123 per thousand). Under-five mortality is 19 percent lower in urban areas (117 per 1000 births) than in rural areas (144 per 10(30 births). The level of mother's education and the length of the preceding birth interval play important roles in child survival. Children of mothers with no education experience nearly twice the level of under-five mortality as children whose mother had attained senior secondary or nigher education. Mortality among children under five is 2.7 times higher among children born after an interval of less than 24 months than among children born after interval of 48 months or more. Maternal mortality The maternal mortality rate (maternal deaths per 1000 women years of exposure) has remained nearly constant over the twenty years preceding the survey, while the maternal mortality ratio (number of maternal deaths per 100,000 births), has increased (despite declining fertility). Using the direct method of estimation, the maternal mortality ratio is 352 maternal deaths per 100,000 births for the period 1976-82, and 552 per 100,000 births for the period 1983-89. The indirect estimate for the maternal mortality ratio is 537. The latter estimate is an average of women's experience over an extended period before the survey centred on 1977. Maternal health care The health care mothers receive during pregnancy and delivery is important to the survival and well-being of both children and mothers. The SDHS results indicate that most women in Sudan made at least one antenatal visit to a doctor or trained health worker/midwife. Eighty-seven percent of births benefitted from professional antenatal care in urban areas compared with 62 percent in rural areas. Although the proportion of pregnant mothers seen by trained health workers/midwives are similar in urban and rural areas, doctors provided antenatal care for 42 percent and 19 percent of births in urban and rural areas, respectively. Neonatal tetanus, a major cause of infant deaths in developing countries, can be prevented if mothers receive tetanus toxoid vaccinations.

LGA based data for Ancestry by Country of Birth of Parents, in General Community Profile (GCP), 2016 Census. Count of responses and persons in the following categories with corresponding ancestry: …Show full descriptionLGA based data for Ancestry by Country of Birth of Parents, in General Community Profile (GCP), 2016 Census. Count of responses and persons in the following categories with corresponding ancestry: both parents born overseas, father born overseas, mother born overseas, both parents born in Australia, parents birthplace not stated. The list of ancestries consists of the most common 30 Ancestry responses reported in the 2011 Census. This is a multi-response dataset and therefore the total responses count will not equal the total persons count. If two responses from one person are categorised in the 'Other' category only one response is counted. If either or both parents birthplace is not stated then a single response is tallied in the 'not stated' category. The data is by LGA 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census. Copyright attribution: Government of the Commonwealth of Australia - Australian Bureau of Statistics, (2017): ; accessed from AURIN on 12/16/2021. Licence type: Creative Commons Attribution 2.5 Australia (CC BY 2.5 AU)

LGA based data for Ancestry by Country of Birth of Parents, in Place of Enumeration Profile (PEP), 2016 Census. Count of responses and persons (excluding overseas visitors) in the following …Show full descriptionLGA based data for Ancestry by Country of Birth of Parents, in Place of Enumeration Profile (PEP), 2016 Census. Count of responses and persons (excluding overseas visitors) in the following categories with corresponding ancestry: both parents born overseas, father born overseas, mother born overseas, both parents born in Australia, parents birthplace not stated. The list of ancestries consists of the most common 30 Ancestry responses reported in the 2011 Census. This is a multi-response dataset and therefore the total responses count will not equal the total persons count. If two responses from one person are categorised in the 'Other' category only one response is counted. If either or both parents birthplace is not stated then a single response is tallied in the 'not stated' category. The data is by LGA 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census. Copyright attribution: Government of the Commonwealth of Australia - Australian Bureau of Statistics, (2017): ; accessed from AURIN on 12/16/2021. Licence type: Creative Commons Attribution 2.5 Australia (CC BY 2.5 AU)

Two online overviews offer comprehensive metadata on the EVS datasets and variables. The extended study description for the EVS 2008 provides country-specific information on the origin and outcomes of the national surveys The variable overview of the four EVS waves 1981 1990 1999/2000 and 2008 allows for identifying country specific deviations in the question wording within and across the EVS waves. These overviews can be found at: http://info1.gesis.org/EVS/Studies (Extended Study Description), http://info1.gesis.org/EVS/Variables (Variable Overview). Moral, religious, societal, political, work, and family values of Europeans. Topics: 1. Perceptions of life: importance of work, family, friends and acquaintances, leisure time, politics and religion; frequency of political discussions with friends; happiness; self-assessment of own health; memberships and unpaid work (volunteering) in: social welfare services, religious or church organizations, education, or cultural activities, labor unions, political parties, local political actions, human rights, environmental or peace movement, professional associations, youth work, sports clubs, women´s groups, voluntary associations concerned with health or other groups; tolerance towards minorities (people with a criminal record, of a different race, left/right wing extremists, alcohol addicts, large families, emotionally unstable people, Muslims, immigrants, AIDS sufferers, drug addicts, homosexuals, Jews, gypsies and Christians - social distance); trust in people; estimation of people´s fair and helpful behavior; internal or external control; satisfaction with life. 2. Work: reasons for people to live in need; importance of selected aspects of occupational work; employment status; general work satisfaction; freedom of decision-taking in the job; importance of work(work ethics, scale); important aspects of leisure time; attitude towards following instructions at work without criticism (obedience work); give priority to nationals over foreigners as well as men over women in jobs. 3. Religion: Individual or general clear guidelines for good and evil; religious denomination; current and former religious denomination; current frequency of church attendance and at the age of 12; importance of religious celebration at birth, marriage, and funeral; self-assessment of religiousness; churches give adequate answers to moral questions, problems of family life, spiritual needs and social problems of the country; belief in God, life after death, hell, heaven, sin and re-incarnation; personal God versus spirit or life force; own way of connecting with the divine; interest in the sacred or the supernatural; attitude towards the existence of one true religion; importance of God in one´s life (10-point-scale); experience of comfort and strength from religion and belief; moments of prayer and meditation; frequency of prayers; belief in lucky charms or a talisman(10-point-scale); attitude towards the separation of church and state. 4. Family and marriage: most important criteria for a successful marriage (scale); attitude towards childcare (a child needs a home with father and mother, a woman has to have children to be fulfilled, marriage is an outdated institution, woman as a single-parent); attitude towards marriage, children, and traditional family structure(scale); attitude towards traditional understanding of one´s role of man and woman in occupation and family (scale); attitude towards: respect and love for parents, parent´s responsibilities for their children and the responsibility of adult children for their parents when they are in need of long-term care; importance of educational goals; attitude towards abortion. 5. Politics and society: political interest; political participation; preference for individual freedom or social equality; self-assessment on a left-right continuum (10-point-scale); self-responsibility or governmental provision; free decision of job-taking of the unemployed or no permission to refuse a job; advantage or harmfulness of competition; liberty of firms or governmental control; equal incomes or incentives for individual efforts; attitude concerning capitalism versus government ownership; postmaterialism (scale); expectation of future development (less emphasis on money and material possessions, greater respect for authority); trust in institutions; satisfaction with democracy; assessment of the political system of the country as good or bad (10-point-scale); preferred type of political system(strong leader, expert decisions, army should rule the country, or democracy); attitude towards democracy (scale). 6. Moral attitudes (scale: claiming state benefits without entitlement, cheating on taxes, joyriding, taking soft drugs, lying, adultery, bribe money, homosexuality, abortion, divorce, euthanasia, suicide, corruption, paying cash, casual sex, avoiding fare on publictransport, prostitution, experiments with human embryos, geneticmanipulation of food, insemination or in-vitro fertilization and deathpenalty). 7. National identity: geographical group the respondent feels belonging to (town, region of country, country, Europe, the world); citizenship; national pride; fears associated with the European Union(the loss of social security and national identity, growing expenditure of the own country, the loss of power in the world for one´s own country and the loss of jobs); attitude towards the enlargement of the European Union (10-point-scale); voting intensions in the next election and party preference; party that appeals most; preferred immigrant policy; opinion on terrorism; attitude towards immigrants and their customs and traditions (take jobs away, undermine a country´s cultural life, make crime problems worse, strain on country´s welfare system, threat to society, maintain distinct customs and traditions); feeling like a stranger in one´s own country; too many immigrants; important aspects of national identity (being born in the country, to respect country´s political institutions and laws, to have country´s ancestry, to speak the national language, to have lived for a long time in the country); interest in politics in the media; give authorities information to help justice versus stick to own affairs; closeness to family, neighborhood, the people in the region, countrymen, Europeans and mankind; concerned about the living conditions of elderly people, unemployed, immigrants and sick or disabled people. 8. Environment: attitude towards the environment (scale: readiness to give part of own income for the environment, overpopulation, disastrous consequences from human interference with nature, human ingenuity remains earth fit to live in, the balance of nature is strong enough to cope with the impacts of modern industrial nations, humans were meant to rule over the rest of nature, an ecological catastrophe is inevitable). Demography: sex; age (year of birth); born in the country of interview; country of birth; year of immigration into the country; father and mother born in the country; country of birth of father and mother; current legal marital status; living together with the partner before marriage or before the registration of partnership; living together with a partner and living with a partner before; steady relationship; married to previous partner; living together with previous partner before marriage; end of relationship; number of children; year of birth of the first child; size and composition of household; experienced events: the death of a child, of father or mother, the divorce of a child, of the parents or of another relative; age of respondent when these events took place; age at completion of education; highest educational level attained; employment status; employed or self-employed in the last job; profession (ISCO-88) and occupational position; supervising function and span of control; size of company. Social origin and partner: respondent´s partner or spouse: partner was born in the country and partner´s country of birth; highest educational level; employment status of the partner; employment or self-employment of the partner in his/her last job; partner´s profession (ISCO-88) and occupational position; supervising function of the partner and span of control; unemployment and dependence on social-security of the respondent and his partner longer than three months in the last five years; scale of household income; living together with parents when the respondent was 14 years old; highest educational level of father/mother; employment status of father/mother when the respondent was 14 years old; profession of father/mother (ISCO-88) and kind of work; number of employees (size of business); supervising function and span of control of father and mother; characterization of the parents when respondent was 14 years old (scale: liked to read books, discussed politics at home with their child, liked to follow the news, had problems making ends meet, had problems replacing broken things); region the respondent lived at the age of 14, present place of residence (postal code); size of town; region. Interviewer rating: respondent´s interest in the interview. Additionally encoded: interviewer number; date of the interview; total length of the interview; time of the interview (start hour and start minute, end hour and end minute); language in which the interview was conducted. Additional country specific variables are included in this national dataset.

Congenital syphilis (CS) is a significant public health problem in Brazil. Despite efforts to increase syphilis testing and treatment among pregnant women, rates of CS in the country remain high. We conducted a retrospective case-control study to identify potential associations between the mothers’ sociodemographic characteristics, clinical factors related to the current and previous pregnancies, and the occurrence of CS among newborns in Fortaleza, a populous city with one of the highest incidences of CS in Brazil. Data from newborns diagnosed with CS between 2017 and 2020 were extracted from SINAN, the national database for notifiable diseases. Data from women who had delivered an infant with CS were extracted from SINASC, the national database for registration of live births, and linked with their infant’s data. CS cases and non-CS controls were matched by year of birth at a ratio of 1:3 respectively. Potential associations were estimated using a multivariate regression model accounting for sociodemographic, obstetric, and antenatal care-related factors. Epidemiological data from 8,744 live births were included in the analysis, including 2,186 cases and 6,588 controls. The final multivariate regression model identified increased odds of delivering an infant with CS among pregnant women and girls aged below 20 years (OR 1.29), single women (OR 1.48), women who had less than 8 years of formal education (OR 2.42), women who delivered in a public hospital (OR 6.92), women who had more than 4 previous pregnancies (OR 1.60), and women who had one or more prior fetal loss (OR 1.19). The odds of delivering an infant with CS also increased as the number of antenatal visits decreased. Women who did not attend any antenatal visits had 3.94 times the odds of delivering an infant with CS compared to women who attended 7 or more visits. Our study found that increased odds of delivering an infant with CS were highly associated with factors related to socioeconomic vulnerability. These determinants not only affect the access to essential antenatal care services, but also the continuity and quality of such preventive measures. Future policies aimed at reducing the incidence of CS should not only target those pregnant women and adolescents with identifiable risk factors for testing, but also assure high quality care, treatment and follow-up for this group.

SA4 based data for Ancestry by Country of Birth of Parents, in General Community Profile (GCP), 2016 Census. Count of responses and persons in the following categories with corresponding ancestry: …Show full descriptionSA4 based data for Ancestry by Country of Birth of Parents, in General Community Profile (GCP), 2016 Census. Count of responses and persons in the following categories with corresponding ancestry: both parents born overseas, father born overseas, mother born overseas, both parents born in Australia, parents birthplace not stated. The list of ancestries consists of the most common 30 Ancestry responses reported in the 2011 Census. This is a multi-response dataset and therefore the total responses count will not equal the total persons count. If two responses from one person are categorised in the 'Other' category only one response is counted. If either or both parents birthplace is not stated then a single response is tallied in the 'not stated' category. The data is by SA4 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census. Copyright attribution: Government of the Commonwealth of Australia - Australian Bureau of Statistics, (2017): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution 2.5 Australia (CC BY 2.5 AU)

SA4 based data for Ancestry by Country of Birth of Parents, in General Community Profile (GCP), 2016 Census. Count of responses and persons in the following categories with corresponding ancestry: both parents born overseas, father born overseas, mother born overseas, both parents born in Australia, parents birthplace not stated. The list of ancestries consists of the most common 30 Ancestry responses reported in the 2011 Census. This is a multi-response dataset and therefore the total responses count will not equal the total persons count. If two responses from one person are categorised in the 'Other' category only one response is counted. If either or both parents birthplace is not stated then a single response is tallied in the 'not stated' category. The data is by SA4 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.

SA2 based data for Ancestry by Country of Birth of Parents, in General Community Profile (GCP), 2016 Census. Count of responses and persons in the following categories with corresponding ancestry: …Show full descriptionSA2 based data for Ancestry by Country of Birth of Parents, in General Community Profile (GCP), 2016 Census. Count of responses and persons in the following categories with corresponding ancestry: both parents born overseas, father born overseas, mother born overseas, both parents born in Australia, parents birthplace not stated. The list of ancestries consists of the most common 30 Ancestry responses reported in the 2011 Census. This is a multi-response dataset and therefore the total responses count will not equal the total persons count. If two responses from one person are categorised in the 'Other' category only one response is counted. If either or both parents birthplace is not stated then a single response is tallied in the 'not stated' category. The data is by SA2 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census. Copyright attribution: Government of the Commonwealth of Australia - Australian Bureau of Statistics, (2017): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution 2.5 Australia (CC BY 2.5 AU)

SA2 based data for Ancestry by Country of Birth of Parents, in Place of Enumeration Profile (PEP), 2016 Census. Count of responses and persons (excluding overseas visitors) in the following …Show full descriptionSA2 based data for Ancestry by Country of Birth of Parents, in Place of Enumeration Profile (PEP), 2016 Census. Count of responses and persons (excluding overseas visitors) in the following categories with corresponding ancestry: both parents born overseas, father born overseas, mother born overseas, both parents born in Australia, parents birthplace not stated. The list of ancestries consists of the most common 30 Ancestry responses reported in the 2011 Census. This is a multi-response dataset and therefore the total responses count will not equal the total persons count. If two responses from one person are categorised in the 'Other' category only one response is counted. If either or both parents birthplace is not stated then a single response is tallied in the 'not stated' category. The data is by SA2 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census. Copyright attribution: Government of the Commonwealth of Australia - Australian Bureau of Statistics, (2017): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution 2.5 Australia (CC BY 2.5 AU)

GCCSA based data for Ancestry by Country of Birth of Parents, in Place of Enumeration Profile (PEP), 2016 Census. Count of responses and persons (excluding overseas visitors) in the following categories with corresponding ancestry: both parents born overseas, father born overseas, mother born overseas, both parents born in Australia, parents birthplace not stated. The list of ancestries consists of the most common 30 Ancestry responses reported in the 2011 Census. This is a multi-response dataset and therefore the total responses count will not equal the total persons count. If two responses from one person are categorised in the 'Other' category only one response is counted. If either or both parents birthplace is not stated then a single response is tallied in the 'not stated' category. The data is by GCCSA 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.

The 2006 Uganda Demographic and Health Survey (UDHS) is a nationally representative survey of 8,531 women age 15-49 and 2,503 men age 15-54. The UDHS is the fourth comprehensive survey conducted in Uganda as part of the worldwide Demographic and Health Surveys (DHS) project. The primary purpose of the UDHS is to furnish policymakers and planners with detailed information on fertility; family planning; infant, child, adult, and maternal mortality; maternal and child health; nutrition; and knowledge of HIV/AIDS and other sexually transmitted infections. In addition, in one in three households selected for the survey, women age 15-49, men age 15-54, and children under age 5 years were weighed and their height was measured. Women, men, and children age 6-59 months in this subset of households were tested for anaemia, and women and children were tested for vitamin A deficiency. The 2006 UDHS is the first DHS survey in Uganda to cover the entire country. The 2006 Uganda Demographic and Health Survey (UDHS) was designed to provide information on demographic, health, and family planning status and trends in the country. Specifically, the UDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, and breastfeeding practices. In addition, data were collected on the nutritional status of mothers and young children; infant, child, adult, and maternal mortality; maternal and child health; awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections; and levels of anaemia and vitamin A deficiency. The 2006 UDHS is a follow-up to the 1988-1989, 1995, and 2000-2001 UDHS surveys, which were also implemented by the Uganda Bureau of Statistics (UBOS). The specific objectives of the 2006 UDHS are as follows: To collect data at the national level that will allow the calculation of demographic rates, particularly the fertility and infant mortality rates To analyse the direct and indirect factors that determine the level and trends in fertility and mortality To measure the level of contraceptive knowledge and practice of women and men by method, by urban-rural residence, and by region To collect data on knowledge and attitudes of women and men about sexually transmitted infections and HIV/AIDS, and to evaluate patterns of recent behaviour regarding condom use To assess the nutritional status of children under age five and women by means of anthropometric measurements (weight and height), and to assess child feeding practices To collect data on family health, including immunizations, prevalence and treatment of diarrhoea and other diseases among children under five, antenatal visits, assistance at delivery, and breastfeeding To measure vitamin A deficiency in women and children, and to measure anaemia in women, men, and children To measure key education indicators including school attendance ratios and primary school grade repetition and dropout rates To collect information on the extent of disability To collect information on the extent of gender-based violence. MAIN RESULTS Fertility : Survey results indicate that the total fertility rate (TFR) for the country is 6.7 births per woman. The TFR in urban areas is much lower than in the rural areas (4.4 and 7.1 children, respectively). Kampala, whose TFR is 3.7, has the lowest fertility. Fertility rates in Central 1, Central 2, and Southwest regions are also lower than the national level. Removing four districts from the 2006 data that were not covered in the 20002001 UDHS, the 2006 TFR is 6.5 births per woman, compared with 6.9 from the 2000-2001 UDHS. Education and wealth have a marked effect on fertility, with uneducated mothers having about three more children on average than women with at least some secondary education and women in the lowest wealth quintile having almost twice as many children as women in the highest wealth quintile. Family planning : Overall, knowledge of family planning has remained consistently high in Uganda over the past five years, with 97 percent of all women and 98 percent of all men age 15-49 having heard of at least one method of contraception. Pills, injectables, and condoms are the most widely known modern methods among both women and men. Maternal health : Ninety-four percent of women who had a live birth in the five years preceding the survey received antenatal care from a skilled health professional for their last birth. These results are comparable to the 2000-2001 UDHS. Only 47 percent of women make four or more antenatal care visits during their entire pregnancy, an improvement from 42 percent in the 2000-2001 UDHS. The median duration of pregnancy for the first antenatal visit is 5.5 months, indicating that Ugandan women start antenatal care at a relatively late stage in pregnancy. Child health : Forty-six percent of children age 12-23 months have been fully vaccinated. Over nine in ten (91 percent) have received the BCG vaccination, and 68 percent have been vaccinated against measles. The coverage for the first doses of DPT and polio is relatively high (90 percent for each). However, only 64 percent go on to receive the third dose of DPT, and only 59 percent receive their third dose of polio vaccine. There are notable improvements in vaccination coverage since the 2000-2001 UDHS. The percentage of children age 12-23 months fully vaccinated at the time of the survey increased from 37 percent in 2000-2001 to 44 percent in 2006. The percentage who had received none of the six basic vaccinations decreased from 13 percent in 2000-2001 to 8 percent in 2006. Malaria : The 2006 UDHS gathered information on the use of mosquito nets, both treated and untreated. The data show that only 34 percent of households in Uganda own a mosquito net, with 16 percent of households owning an insecticide-treated net (ITN). Only 22 percent of children under five slept under a mosquito net on the night before the interview, while a mere 10 percent slept under an ITN. Breastfeeding and nutrition : In Uganda, almost all children are breastfed at some point. However, only six in ten children under the age of 6 months are exclusively breast-fed. HIV/AIDS AND stis : Knowledge of AIDS is very high and widespread in Uganda. In terms of HIV prevention strategies, women and men are most aware that the chances of getting the AIDS virus can be reduced by limiting sex to one uninfected partner who has no other partners (89 percent of women and 95 percent of men) or by abstaining from sexual intercourse (86 percent of women and 93 percent of men). Knowledge of condoms and the role they can play in preventing transmission of the AIDS virus is not quite as high (70 percent of women and 84 percent of men). Orphanhood and vulnerability : Almost one in seven children under age 18 is orphaned (15 percent), that is, one or both parents are dead. Only 3 percent of children under the age of 18 have lost both biological parents. Women's status and gender violence : Data for the 2006 UDHS show that women in Uganda are generally less educated than men. Although the gender gap has narrowed in recent years, 19 percent of women age 15-49 have never been to school, compared with only 5 percent of men in the same age group. Mortality : At current mortality levels, one in every 13 Ugandan children dies before reaching age one, while one in every seven does not survive to the fifth birthday. After removing districts not covered in the 2000-2001 UDHS from the 2006 data, findings show that infant mortality has declined from 89 deaths per 1,000 live births in the 2000-2001 UDHS to 75 in the 2006 UDHS. Under-five mortality has declined from 158 deaths per 1,000 live births to 137.

SA1 based data for Ancestry by Country of Birth of Parents, in General Community Profile (GCP), 2016 Census. Count of responses and persons in the following categories with corresponding ancestry: both parents born overseas, father born overseas, mother born overseas, both parents born in Australia, parents birthplace not stated. The list of ancestries consists of the most common 30 Ancestry responses reported in the 2011 Census. This is a multi-response dataset and therefore the total responses count will not equal the total persons count. If two responses from one person are categorised in the 'Other' category only one response is counted. If either or both parents birthplace is not stated then a single response is tallied in the 'not stated' category. The data is by SA1 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.

GCCSA based data for Ancestry by Country of Birth of Parents, in Place of Enumeration Profile (PEP), 2016 Census. Count of responses and persons (excluding overseas visitors) in the following categories with corresponding ancestry: both parents born overseas, father born overseas, mother born overseas, both parents born in Australia, parents birthplace not stated. The list of ancestries consists of the most common 30 Ancestry responses reported in the 2011 Census. This is a multi-response dataset and therefore the total responses count will not equal the total persons count. If two responses from one person are categorised in the 'Other' category only one response is counted. If either or both parents birthplace is not stated then a single response is tallied in the 'not stated' category. The data is by GCCSA 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.

SA3 based data for Ancestry by Country of Birth of Parents, in General Community Profile (GCP), 2016 Census. Count of responses and persons in the following categories with corresponding ancestry: both parents born overseas, father born overseas, mother born overseas, both parents born in Australia, parents birthplace not stated. The list of ancestries consists of the most common 30 Ancestry responses reported in the 2011 Census. This is a multi-response dataset and therefore the total responses count will not equal the total persons count. If two responses from one person are categorised in the 'Other' category only one response is counted. If either or both parents birthplace is not stated then a single response is tallied in the 'not stated' category. The data is by SA3 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.

SA1 based data for Ancestry by Country of Birth of Parents, in General Community Profile (GCP), 2016 Census. Count of responses and persons in the following categories with corresponding ancestry: both parents born overseas, father born overseas, mother born overseas, both parents born in Australia, parents birthplace not stated. The list of ancestries consists of the most common 30 Ancestry responses reported in the 2011 Census. This is a multi-response dataset and therefore the total responses count will not equal the total persons count. If two responses from one person are categorised in the 'Other' category only one response is counted. If either or both parents birthplace is not stated then a single response is tallied in the 'not stated' category. The data is by SA1 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.