The United States MSA Boundaries data set contains the boundaries for metropolitan statistical areas in the United States. The data set contains information on location, identification, and size. The database includes metropolitan boundaries within all 50 states, the District of Columbia, and Puerto Rico. The general concept of a metropolitan area (MA) is one of a large population nucleus, together with adjacent communities that have a high degree of economic and social integration with that nucleus. Some MAs are defined around two or more nuclei. Each MA must contain either a place with a minimum population of 50,000 or a U.S. Census Bureau-defined urbanized area and a total MA population of at least 100,000 (75,000 in New England). An MA contains one or more central counties. An MA also may include one or more outlying counties that have close economic and social relationships with the central county. An outlying county must have a specified level of commuting to the central counties and also must meet certain standards regarding metropolitan character, such as population density, urban population, and population growth. In New England, MAs consist of groupings of cities and towns rather than whole counties. The territory, population, and housing units in MAs are referred to as "metropolitan." The metropolitan category is subdivided into "inside central city" and "outside central city." The territory, population, and housing units located outside territory designated "metropolitan" are referred to as "non-metropolitan." The metropolitan and non-metropolitan classification cuts across the other hierarchies; for example, generally there are both urban and rural territory within both metropolitan and non-metropolitan areas.

A computerized data set of demographic, economic and social data for 227 countries of the world. Information presented includes population, health, nutrition, mortality, fertility, family planning and contraceptive use, literacy, housing, and economic activity data. Tabular data are broken down by such variables as age, sex, and urban/rural residence. Data are organized as a series of statistical tables identified by country and table number. Each record consists of the data values associated with a single row of a given table. There are 105 tables with data for 208 countries. The second file is a note file, containing text of notes associated with various tables. These notes provide information such as definitions of categories (i.e. urban/rural) and how various values were calculated. The IDB was created in the U.S. Census Bureau''s International Programs Center (IPC) to help IPC staff meet the needs of organizations that sponsor IPC research. The IDB provides quick access to specialized information, with emphasis on demographic measures, for individual countries or groups of countries. The IDB combines data from country sources (typically censuses and surveys) with IPC estimates and projections to provide information dating back as far as 1950 and as far ahead as 2050. Because the IDB is maintained as a research tool for IPC sponsor requirements, the amount of information available may vary by country. As funding and research activity permit, the IPC updates and expands the data base content. Types of data include: * Population by age and sex * Vital rates, infant mortality, and life tables * Fertility and child survivorship * Migration * Marital status * Family planning Data characteristics: * Temporal: Selected years, 1950present, projected demographic data to 2050. * Spatial: 227 countries and areas. * Resolution: National population, selected data by urban/rural * residence, selected data by age and sex. Sources of data include: * U.S. Census Bureau * International projects (e.g., the Demographic and Health Survey) * United Nations agencies Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/08490

In terms of population size, the sex ratio in the United States favors females, although the gender gap is remaining stable. In 2010, there were around 5.17 million more women, with the difference projected to decrease to around 3 million by 2027.

Gender ratios by U.S. state In the United States, the resident population was estimated to be around 331.89 million in 2021. The gender distribution of the nation has remained steady for several years, with women accounting for approximately 51.1 percent of the population since 2013. Females outnumbered males in the majority of states across the country in 2020, and there were eleven states where the gender ratio favored men.

Metro areas by population National differences between male and female populations can also be analyzed by metropolitan areas. In general, a metropolitan area is a region with a main city at its center and adjacent communities that are all connected by social and economic factors. The largest metro areas in the U.S. are New York, Los Angeles, and Chicago. In 2019, there were more women than men in all three of those areas, but Jackson, Missouri was the metro area with the highest share of female population.

This dataset displays building permit statistics on an state and metropolitan area level. The data is provided on an annual basis. The data is scaled to the thousands. This data was collected from the National Association of Home Builders' Webpage at: http://www.nahb.org/reference_list.aspx?pageNumber=1&pageSize=0&sectionID=130 Access Date: November 13, 2007 NOTES: Metropolitan areas marked with an asterisk ( * ) are areas where all permit offices are requested to report monthly. ** Office of Management and Budget (OMB) revised the metropolitan classification system in June of 2003. ~Year total includes data revisions that are not captured by the monthly year-to-date (YTD) data and, for some metropolitan areas, localities that only report on an annual basis.

This data collection contains summary statistics on population and housing subjects derived from the responses to the 2010 Census questionnaire. Population items include sex, age, average household size, household type, and relationship to householder such as nonrelative or child. Housing items include tenure (whether a housing unit is owner-occupied or renter-occupied), age of householder, and household size for occupied housing units. Selected aggregates and medians also are provided. The summary statistics are presented in 71 tables, which are tabulated for multiple levels of observation (called "summary levels" in the Census Bureau's nomenclature), including, but not limited to, regions, divisions, states, metropolitan/micropolitan areas, counties, county subdivisions, places, ZIP Code Tabulation Areas (ZCTAs), school districts, census tracts, American Indian and Alaska Native areas, tribal subdivisions, and Hawaiian home lands. There are 10 population tables shown down to the county level and 47 population tables and 14 housing tables shown down to the census tract level. Every table cell is represented by a separate variable in the data. Each table is iterated for up to 330 population groups, which are called "characteristic iterations" in the Census Bureau's nomenclature: the total population, 74 race categories, 114 American Indian and Alaska Native categories, 47 Asian categories, 43 Native Hawaiian and Other Pacific Islander categories, and 51 Hispanic/not Hispanic groups. Moreover, the tables for some large summary areas (e.g., regions, divisions, and states) are iterated for portions of geographic areas ("geographic components" in the Census Bureau's nomenclature) such as metropolitan/micropolitan statistical areas and the principal cities of metropolitan statistical areas. The collection has a separate set of files for every state, the District of Columbia, Puerto Rico, and the National File. Each file set has 11 data files per characteristic iteration, a data file with geographic variables called the "geographic header file," and a documentation file called the "packing list" with information about the files in the file set. Altogether, the 53 file sets have 110,416 data files and 53 packing list files. Each file set is compressed in a separate ZIP archive (Datasets 1-56, 72, and 99). Another ZIP archive (Dataset 100) contains a Microsoft Access database shell and additional documentation files besides the codebook. The National File (Dataset 99) constitutes the National Update for Summary File 2. The National Update added summary levels for the United States as a whole, regions, divisions, and geographic areas that cross state lines such as Core Based Statistical Areas.

VITAL SIGNS INDICATOR
Poverty (EQ5)

FULL MEASURE NAME
The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED
January 2023

DESCRIPTION
Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE
U.S Census Bureau: Decennial Census - http://www.nhgis.org
1980-2000

U.S. Census Bureau: American Community Survey - https://data.census.gov/
2007-2021
Form C17002

CONTACT INFORMATION
vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)
The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or non-cash benefits (such as public housing, Medicaid and food stamps).

For the national poverty level definitions by year, see: US Census Bureau Poverty Thresholds - https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html.

For an explanation on how the Census Bureau measures poverty, see: How the Census Bureau Measures Poverty - https://www.census.gov/topics/income-poverty/poverty/guidance/poverty-measures.html.

American Community Survey (ACS) 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.

We used individual-level death data to estimate county-level life expectancy at 25 (e25) for Whites, Black, AIAN and Asian in the contiguous US for 2000-2005. Race-sex-stratified models were used to examine the associations among e25, rurality and specific race proportion, adjusted for socioeconomic variables. Individual death data from the National Center for Health Statistics were aggregated as death counts into five-year age groups by county and race-sex groups for the contiguous US for years 2000-2005 (National Center for Health Statistics 2000-2005). We used bridged-race population estimates to calculate five-year mortality rates. The bridged population data mapped 31 race categories, as specified in the 1997 Office of Management and Budget standards for the collection of data on race and ethnicity, to the four race categories specified under the 1977 standards (the same as race categories in mortality registration) (Ingram et al. 2003). The urban-rural gradient was represented by the 2003 Rural Urban Continuum Codes (RUCC), which distinguished metropolitan counties by population size, and nonmetropolitan counties by degree of urbanization and adjacency to a metro area (United States Department of Agriculture 2016). We obtained county-level sociodemographic data for 2000-2005 from the US Census Bureau. These included median household income, percent of population attaining greater than high school education (high school%), and percent of county occupied rental units (rent%). We obtained county violent crime from Uniform Crime Reports and used it to calculate mean number of violent crimes per capita (Federal Bureau of Investigation 2010). This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Request to author. Format: Data are stored as csv files. This dataset is associated with the following publication: Jian, Y., L. Neas, L. Messer, C. Gray, J. Jagai, K. Rappazzo, and D. Lobdell. Divergent trends in life expectancy across the rural-urban gradient among races in the contiguous United States. International Journal of Public Health. Springer Basel AG, Basel, SWITZERLAND, 64(9): 1367-1374, (2019).

Metropolitan area median home prices -2005, 2006, 2007(p) and individual quarters for 2007.

This data explores 8th grade writing scores as measured by the Nation's Report Card. This report presents the results of the 2007 National Assessment of Educational Progress (NAEP) writing assessment. It was administered to a nationally representative sample of more than 165,000 eighth- and twelfth-graders from public and private schools. In addition to national results, the report includes state and urban district results for grade 8 public school students. Forty-five states, the Department of Defense schools, and 10 urban districts voluntarily participated. To measure their writing skills, the assessment engaged students in narrative, informative, and persuasive writing tasks. NAEP presents the writing results as scale scores and achievement-level percentages. Results are also reported for student performance by various demographic characteristics such as race/ethnicity, gender, and eligibility for the National School Lunch Program. The 2007 national results are compared with results from the 2002 and 1998 assessments. At grades 8 and 12, average writing scores and the percentages of students performing at or above Basic were higher than in both previous assessments. The White -- Black score gap narrowed at grade 8 compared to 1998 and 2002 but showed no significant change at grade 12. The gender score gap showed no significant change at grade 8 compared with previous assessments but narrowed at grade 12 since 2002. Eighth-graders eligible for free or reduced-price school lunch scored lower on average than students who were not eligible. Compared with 2002, average writing scores for eighth-graders increased in 19 states and the Department of Defense schools, and scores decreased in one state. Compared with 1998, scores increased in 28 states and the Department of Defense Schools, and no states showed a decrease. Scores for most urban districts at grade 8 were comparable to or higher than scores for large central cities but were below the national average.

VITAL SIGNS INDICATOR

Poverty (EQ5)

FULL MEASURE NAME

The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED

December 2018

DESCRIPTION

Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE

U.S Census Bureau: Decennial Census

http://www.nhgis.org (1980-1990)

http://factfinder2.census.gov (2000)

U.S. Census Bureau: American Community Survey

Form C17002 (2006-2017)

http://api.census.gov

METHODOLOGY NOTES (across all datasets for this indicator)

The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. Poverty rates do not include unrelated individuals below 15 years old or people who live in the following: institutionalized group quarters, college dormitories, military barracks, and situations without conventional housing. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps). For the national poverty level definitions by year, see: https://www.census.gov/hhes/www/poverty/data/threshld/index.html

For an explanation on how the Census Bureau measures poverty, see: https://www.census.gov/hhes/www/poverty/about/overview/measure.html

For the American Community Survey datasets, 1-year data was used for region, county, and metro areas whereas 5-year rolling average data was used for city and census tract.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

The goal is to predict the rate of heart disease (per 100,000 individuals) across the United States at the county-level from other socioeconomic indicators. The data is compiled from a wide range of sources and made publicly available by the United States Department of Agriculture Economic Research Service (USDA ERS).

There are 33 variables in this dataset. Each row in the dataset represents a United States county, and the dataset we are working with covers two particular years, denoted a, and b We don't provide a unique identifier for an individual county, just a row_id for each row.

The variables in the dataset have names that of the form category_variable, where category is the high level category of the variable (e.g. econ or health). variable is what the specific column contains.

We're trying to predict the variable heart_disease_mortality_per_100k (a positive integer) for each row of the test data set.

Columns

area — information about the county

area_rucc — Rural-Urban Continuum Codes "form a classification scheme that distinguishes metropolitan counties by the population size of their metro area, and nonmetropolitan counties by degree of urbanization and adjacency to a metro area. The official Office of Management and Budget (OMB) metro and nonmetro categories have been subdivided into three metro and six nonmetro categories. Each county in the U.S. is assigned one of the 9 codes." (USDA Economic Research Service, https://www.ers.usda.gov/data-products/rural-urban-continuum-codes/)

area_urban_influence — Urban Influence Codes "form a classification scheme that distinguishes metropolitan counties by population size of their metro area, and nonmetropolitan counties by size of the largest city or town and proximity to metro and micropolitan areas." (USDA Economic Research Service, https://www.ers.usda.gov/data-products/urban-influence-codes/)

econ — economic indicators

econ_economic_typology — County Typology Codes "classify all U.S. counties according to six mutually exclusive categories of economic dependence and six overlapping categories of policy-relevant themes. The economic dependence types include farming, mining, manufacturing, Federal/State government, recreation, and nonspecialized counties. The policy-relevant types include low education, low employment, persistent poverty, persistent child poverty, population loss, and retirement destination." (USDA Economic Research Service, https://www.ers.usda.gov/data-products/county-typology-codes.aspx)

econ_pct_civilian_labor — Civilian labor force, annual average, as percent of population (Bureau of Labor Statistics, http://www.bls.gov/lau/)

econ_pct_unemployment — Unemployment, annual average, as percent of population (Bureau of Labor Statistics, http://www.bls.gov/lau/)

econ_pct_uninsured_adults — Percent of adults without health insurance (Bureau of Labor Statistics, http://www.bls.gov/lau/) econ_pct_uninsured_children — Percent of children without health insurance (Bureau of Labor Statistics, http://www.bls.gov/lau/)

health — health indicators

health_pct_adult_obesity — Percent of adults who meet clinical definition of obese (National Center for Chronic Disease Prevention and Health Promotion)

health_pct_adult_smoking — Percent of adults who smoke (Behavioral Risk Factor Surveillance System)

health_pct_diabetes — Percent of population with diabetes (National Center for Chronic Disease Prevention and Health Promotion, Division of Diabetes Translation)

health_pct_low_birthweight — Percent of babies born with low birth weight (National Center for Health Statistics)

health_pct_excessive_drinking — Percent of adult population that engages in excessive consumption of alcohol (Behavioral Risk Factor Surveillance System, )

health_pct_physical_inacticity — Percent of adult population that is physically inactive (National Center for Chronic Disease Prevention and Health Promotion)

health_air_pollution_particulate_matter — Fine particulate matter in µg/m³ (CDC WONDER, https://wonder.cdc.gov/wonder/help/pm.html)

health_homicides_per_100k — Deaths by homicide per 100,000 population (National Center for Health Statistics)

health_motor_vehicle_crash_deaths_per_100k — Deaths by motor vehicle crash per 100,000 population (National Center for Health Statistics)

health_pop_per_dentist — Population per dentist (HRSA Area Resource File)

health_pop_per_primary_care_physician — Population per Primary Care Physician (HRSA Area Resource File)

demo — demographics information

demo_pct_female — Percent of population that is female (US Census Population Estimates)

demo_pct_below_18_years_of_age — Percent of population that is below 18 years of age (US Census Population Estimates)

demo_pct_aged_65_years_and_older — Percent of population that is aged 65 years or older (US Census Population Estimates)

dem...

Abstract

The 2015-16 Armenia Demographic and Health Survey (2015-16 ADHS) is the fourth in a series of nationally representative sample surveys designed to provide information on population and health issues. It is conducted in Armenia under the worldwide Demographic and Health Surveys program. Specifically, the objective of the 2015-16 ADHS is to provide current and reliable information on fertility and abortion levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of young children, childhood mortality, maternal and child health, domestic violence against women, child discipline, awareness and behavior regarding AIDS and other sexually transmitted infections (STIs), and other health-related issues such as smoking, tuberculosis, and anemia. The survey obtained detailed information on these issues from women of reproductive age and, for certain topics, from men as well.

The 2015-16 ADHS results are intended to provide information needed to evaluate existing social programs and to design new strategies to improve the health of and health services for the people of Armenia. Data are presented by region (marz) wherever sample size permits. The information collected in the 2015-16 ADHS will provide updated estimates of basic demographic and health indicators covered in the 2000, 2005, and 2010 surveys.

The long-term objective of the survey includes strengthening the technical capacity of major government institutions, including the NSS. The 2015-16 ADHS also provides comparable data for longterm trend analysis because the 2000, 2005, 2010, and 2015-16 surveys were implemented by the same organization and used similar data collection procedures. It also adds to the international database of demographic and health–related information for research purposes.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-49

Universe

The survey covered all de jure household members (usual residents), children age 0-4 years, women age 15-49 years and men age 15-49 years resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was designed to produce representative estimates of key indicators at the national level, for Yerevan, and for total urban and total rural areas separately. Many indicators can also be estimated at the regional (marz) level.

The sampling frame used for the 2015-16 ADHS is the Armenia Population and Housing Census, which was conducted in Armenia in 2011 (APHC 2011). The sampling frame is a complete list of enumeration areas (EAs) covering the whole country, a total number of 11,571 EAs, provided by the National Statistical Service (NSS) of Armenia, the implementing agency for the 2015-16 ADHS. This EA frame was created from the census data base by summarizing the households down to EA level. A representative probability sample of 8,749 households was selected for the 2015-16 ADHS sample. The sample was selected in two stages. In the first stage, 313 clusters (192 in urban areas and 121 in rural areas) were selected from a list of EAs in the sampling frame. In the second stage, a complete listing of households was carried out in each selected cluster. Households were then systematically selected for participation in the survey. Appendix A provides additional information on the sample design of the 2015-16 Armenia DHS. Because of the approximately equal sample size in each marz, the sample is not self-weighting at the national level, and weighting factors have been calculated, added to the data file, and applied so that results are representative at the national level.

For further details on sample design, see Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Five questionnaires were used for the 2015-16 ADHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaire, and the Fieldworker Questionnaire. These questionnaires, based on The DHS Program’s standard Demographic and Health Survey questionnaires, were adapted to reflect the population and health issues relevant to Armenia. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organizations, and international donors. After all questionnaires were finalized in English, they were translated into Armenian. They were pretested in September-October 2015.

Cleaning operations

The processing of the 2015-16 ADHS data began shortly after fieldwork commenced. All completed questionnaires were edited immediately by field editors while still in the field and checked by the supervisors before being dispatched to the data processing center at the NSS central office in Yerevan. These completed questionnaires were edited and entered by 15 data processing personnel specially trained for this task. All data were entered twice for 100 percent verification. Data were entered using the CSPro computer package. The concurrent processing of the data was an advantage because the senior ADHS technical staff were able to advise field teams of problems detected during the data entry. In particular, tables were generated to check various data quality parameters. Moreover, the double entry of data enabled easy comparison and identification of errors and inconsistencies. As a result, specific feedback was given to the teams to improve performance. The data entry and editing phase of the survey was completed in June 2016.

Response rate

A total of 8,749 households were selected in the sample, of which 8,205 were occupied at the time of the fieldwork. The main reason for the difference is that some of the dwelling units that were occupied during the household listing operation were either vacant or the household was away for an extended period at the time of interviewing. The number of occupied households successfully interviewed was 7,893, yielding a household response rate of 96 percent. The household response rate in urban areas (96 percent) was nearly the same as in rural areas (97 percent).

In these households, a total of 6,251 eligible women were identified; interviews were completed with 6,116 of these women, yielding a response rate of 98 percent. In one-half of the households, a total of 2,856 eligible men were identified, and interviews were completed with 2,755 of these men, yielding a response rate of 97 percent. Among men, response rates are slightly lower in urban areas (96 percent) than in rural areas (97 percent), whereas rates for women are the same in urban and in rural areas (98 percent).

The 2015-16 ADHS achieved a slightly higher response rate for households than the 2010 ADHS (NSS 2012). The increase is only notable for urban households (96 percent in 2015-16 compared with 94 percent in 2010). Response rates in all other categories are very close to what they were in 2010.

Sampling error estimates

SAS computer software were used to calculate sampling errors for the 2015-16 ADHS. The programs used the Taylor linearization method of variance estimation for means or proportions and the Jackknife repeated replication method for variance estimation of more complex statistics such as fertility and mortality rates.

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

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months - Nutritional status of children based on the NCHS/CDC/WHO International Reference Population - Vaccinations by background characteristics for children age 18-29 months

See details of the data quality tables in Appendix C of the survey final report.

The map data is derived from the United Nations Environment Programme (UNEP) for 1960 to 2005. The map shows the concentration of the total percent of the total population that is considered urban population within each country. "Total population residing in urban areas. Because of national differences in the characteristics that distinguish urban from rural areas, the distinction between urban and rural population is not amenable to a single definition that would be applicable to all countries. National definitions are most commonly based on size of locality. Population which is not urban is considered rural." Online resource: http://geodata.grid.unep.ch URL original source: http://www.un.org/esa/population/unpop.htm

VITAL SIGNS INDICATOR
Poverty (EQ5)

FULL MEASURE NAME
The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED
January 2023

DESCRIPTION
Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE
U.S Census Bureau: Decennial Census - http://www.nhgis.org
1980-2000

U.S. Census Bureau: American Community Survey - https://data.census.gov/
2007-2021
Form C17002

CONTACT INFORMATION
vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)
The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or non-cash benefits (such as public housing, Medicaid and food stamps).

For the national poverty level definitions by year, see: US Census Bureau Poverty Thresholds - https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html.

For an explanation on how the Census Bureau measures poverty, see: How the Census Bureau Measures Poverty - https://www.census.gov/topics/income-poverty/poverty/guidance/poverty-measures.html.

American Community Survey (ACS) 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

Abstract

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

Abstract

The 1993 National Demographic Survey (NDS) is a nationally representative sample survey of women age 15-49 designed to collect information on fertility; family planning; infant, child and maternal mortality; and maternal and child health. The survey was conducted between April and June 1993. The 1993 NDS was carried out by the National Statistics Office in collaboration with the Department of Health, the University of the Philippines Population Institute, and other agencies concerned with population, health and family planning issues. Funding for the 1993 NDS was provided by the U.S. Agency for International Development through the Demographic and Health Surveys Program.

Close to 13,000 households throughout the country were visited during the survey and more than 15,000 women age 15-49 were interviewed. The results show that fertility in the Philippines continues its gradual decline. At current levels, Filipino women will give birth on average to 4.1 children during their reproductive years, 0.2 children less than that recorded in 1988. However, the total fertility rate in the Philippines remains high in comparison to the level achieved in the neighboring Southeast Asian countries.

The primary objective of the 1993 NDS is to provide up-to-date inform ation on fertility and mortality levels; nuptiality; fertility preferences; awareness, approval, and use of family planning methods; breastfeeding practices; and maternal and child health. This information is intended to assist policymakers and administrators in evaluating and designing programs and strategies for improving health and family planning services in 'the country.

MAIN RESULTS

Fertility varies significantly by region and socioeconomic characteristics. Urban women have on average 1.3 children less than rural women, and uneducated women have one child more than women with college education. Women in Bicol have on average 3 more children than women living in Metropolitan Manila.

Virtually all women know of a family planning method; the pill, female sterilization, IUD and condom are known to over 90 percent of women. Four in 10 married women are currently using contraception. The most popular method is female sterilization ( 12 percent), followed by the piU (9 percent), and natural family planning and withdrawal, both used by 7 percent of married women.

Contraceptive use is highest in Northern Mindanao, Central Visayas and Southern Mindanao, in urban areas, and among women with higher than secondary education. The contraceptive prevalence rate in the Philippines is markedly lower than in the neighboring Southeast Asian countries; the percentage of married women who were using family planning in Thailand was 66 percent in 1987, and 50 percent in Indonesia in 199l.

The majority of contraceptive users obtain their methods from a public service provider (70 percent). Government health facilities mainly provide permanent methods, while barangay health stations or health centers are the main sources for the pill, IUD and condom.

Although Filipino women already marry at a relatively higher age, they continue to delay the age at which they first married. Half of Filipino women marry at age 21.6. Most women have their first sexual intercourse after marriage.

Half of married women say that they want no more children, and 12 percent have been sterilized. An additional 19 percent want to wait at least two years before having another child. Almost two thirds of women in the Philippines express a preference for having 3 or less children. Results from the survey indicate that if all unwanted births were avoided, the total fertility rate would be 2.9 children, which is almost 30 percent less than the observed rate,

More than one quarter of married women in the Philippines are not using any contraceptive method, but want to delay their next birth for two years or more (12 percent), or want to stop childbearing (14 percent). If the potential demand for family planning is satisfied, the contraceptive prevalence rate could increase to 69 percent. The demand for stopping childbearing is about twice the level for spacing (45 and 23 percent, respectively).

Information on various aspects of maternal and child health---antenatal care, vaccination, breastfeeding and food supplementation, and illness was collected in the 1993 NDS on births in the five years preceding the survey. The findings show that 8 in 10 children under five were bom to mothers who received antenatal care from either midwives or nurses (45 percent) or doctors (38 percent). Delivery by a medical personnel is received by more than half of children born in the five years preceding the survey. However, the majority of deliveries occurred at home.

Tetanus, a leading cause of infant deaths, can be prevented by immunization of the mother during pregnancy. In the Philippines, two thirds of bitlhs in the five years preceding the survey were to mothers who received a tetanus toxoid injection during pregnancy.

Based on reports of mothers and information obtained from health cards, 90 percent of children aged 12-23 months have received shots of the BCG as well as the first doses of DPT and polio, and 81 percent have received immunization from measles. Immunization coverage declines with doses; the drop out rate is 3 to 5 percent for children receiving the full dose series of DPT and polio. Overall, 7 in 10 children age 12-23 months have received immunization against the six principal childhood diseases---polio, diphtheria, ~rtussis, tetanus, measles and tuberculosis.

During the two weeks preceding the survey, 1 in 10 children under 5 had diarrhea. Four in ten of these children were not treated. Among those who were treated, 27 percent were given oral rehydration salts, 36 percent were given recommended home solution or increased fluids.

Breasffeeding is less common in the Philippines than in many other developing countries. Overall, a total of 13 percent of children born in the 5 years preceding the survey were not breastfed at all. On the other hand, bottle feeding, a widely discouraged practice, is relatively common in the Philippines. Children are weaned at an early age; one in four children age 2-3 months were exclusively breastfed, and the mean duration of breastfeeding is less than 3 months.

Infant and child mortality in the Philippines have declined significantly in the past two decades. For every 1,000 live births, 34 infants died before their first birthday. Childhood mortality varies significantly by mother's residence and education. The mortality of urban infants is about 40 percent lower than that of rural infants. The probability of dying among infants whose mother had no formal schooling is twice as high as infants whose mother have secondary or higher education. Children of mothers who are too young or too old when they give birth, have too many prior births, or give birth at short intervals have an elevated mortality risk. Mortality risk is highest for children born to mothers under age 19.

The 1993 NDS also collected information necessary for the calculation of adult and maternal mortality using the sisterhood method. For both males and females, at all ages, male mortality is higher than that of females. Matemal mortality ratio for the 1980-1986 is estimated at 213 per 100,000 births, and for the 1987-1993 period 209 per 100,000 births. However, due to the small number of sibling deaths reported in the survey, age-specific rates should be used with caution.

Information on health and family planning services available to the residents of the 1993 NDS barangay was collected from a group of respondents in each location. Distance and time to reach a family planning service provider has insignificant association with whether a woman uses contraception or the choice of contraception being used. On the other hand, being close to a hospital increases the likelihood that antenatal care and births are to respondents who receive ANC and are delivered by a medical personnel or delivered in a health facility.

Geographic coverage

National. The main objective of the 1993 NDS sample is to allow analysis to be carried out for urban and rural areas separately, for 14 of the 15 regions in the country. Due to the recent formation of the 15th region, Autonomous Region in Muslim Mindanao (ARMM), the sample did not allow for a separate estimate for this region.

Analysis unit

• Household
• Women age 15-49

Universe

The population covered by the 1993 Phillipines NDS is defined as the universe of all females age 15-49 years, who are members of the sample household or visitors present at the time of interview and had slept in the sample households the night prior to the time of interview, regardless of marital status.

Kind of data

Sample survey data

Sampling procedure

The main objective of the 1993 National Demographic Survey (NDS) sample is to provide estimates with an acceptable precision for sociodemographics characteristics, like fertility, family planning, health and mortality variables and to allow analysis to be carried out for urban and rural areas separately, for 14 of the 15 regions in the country. Due to the recent formation of the 15th region, Autonomous Region in Muslim Mindanao (ARMM), the sample did not allow for a separate estimate for this region.

The sample is nationally representative with a total size of about 15,000 women aged 15 to 49. The Integrated Survey of Households (ISH) was used as a frame. The ISH was developed in 1980, and was comprised of samples of primary sampling units (PSUs) systematically selected and with a probability proportional to size in each of the 14 regions. The PSUs were reselected in 1991, using the 1990 Population Census data on

As of 2023, teenagers between the ages of ** and ** living in urban areas in Indonesia had a literacy rate of ***** percent. In Indonesia, the urban literacy rates were higher than the national literacy rates across all age groups.

Abstract

The 2006-07 Swaziland Demographic and Health Survey (SDHS) is a nationally representative survey of 4,843 households, 4,987 women age 15-49, and 4,156 men age 15-49. The SDHS also included individual interviews with boys and girls age 12-14 and older adults age 50 and over. The survey of persons age 12-14 and age 50 and over was carried out in every other household selected in the SDHS. Interviews were completed for 459 girls and 411 boys age 12-14, and 661 women and 456 men age 50 and over.

The 2006-07 SDHS is the first national survey conducted in Swaziland as part of the Demographic and Health Surveys (DHS) programme. The data are intended to furnish programme managers and policymakers with detailed information on levels and trends in fertility; nuptiality; sexual activity; fertility preferences; awareness and use of family planning methods; breastfeeding practices; nutritional status of mothers and young children; early childhood mortality and maternal mortality; maternal and child health; and awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections. The survey also collected information on malaria prevention and treatment.

The 2006-07 SDHS is the first nationwide survey in Swaziland to provide population-based prevalence estimates for anaemia and HIV. Children age 6 months and older as well as adults were tested for anaemia. Children age 2 years and older as well as adults were tested for HIV.

The principal objective of the 2006-07 Swaziland Demographic and Health Survey (SDHS) was to provide up-to-date information on fertility, childhood mortality, marriage, fertility preferences, awareness, and use of family planning methods, infant feeding practices, maternal and child health, maternal mortality, HIV/AIDS-related knowledge and behaviour and prevalence of HIV and anaemia.

More specifically the 2006-07 SDHS was aimed at achieving the following; - Determine key demographic rates, particularly fertility, under-five mortality, and adult mortality rates - Investigate the direct and indirect factors which determine the level and trends of fertility - Measure the level of contraceptive knowledge and practice of women and men by method - Determine immunization coverage and prevalence and treatment of diarrhoea and acute respiratory diseases among children under five - Determine infant and young child feeding practices and assess the nutritional status of children 6-59 months, women age 15-49 years, and men aged 15-49 years - Estimate prevalence of anaemia - Assess knowledge and attitudes of women and men regarding sexually transmitted infections and HIV/AIDS, and evaluate patterns of recent behaviour regarding condom use - Identify behaviours that protect or predispose the population to HIV infection - Examine social, economic, and cultural determinants of HIV
- Determine the proportion of households with orphans and vulnerable children (OVCs) - Determine the proportion of households with sick people taken care at household level - Determine HIV prevalence among males and females age 2 years and older - Determine the use of iodized salt in households - Describe care and protection of children age 12-14 years, and their knowledge and attitudes about sex and HIV/AIDS.

This information is intended to provide data to assist policymakers and programme implementers to monitor and evaluate existing programmes and to design new strategies for demographic, social and health policies in Swaziland. The survey also provides data to monitor the country's achievement towards the Millenium Development Goals.

MAIN RESULTS

• Fertility in Swaziland has been declining rapidly, with the TFR falling from 6.4 births per woman in 1986 to 3.8 births at the time of the SDHS. As expected, fertility is higher in rural areas (4.2 births per woman) than in urban areas (3.0 births per woman). Fertility differentials by education and wealth are substantial. Women with no education have on average 4.9 children compared with 2.4 children for women with tertiary education. Fertility varies widely according to household wealth. Women in the highest wealth quintile have 2.9 children fewer than women in the lowest quintile (2.6 and 5.5 births per woman, respectively).

• Knowledge of family planning is universal in Swaziland. The most widely known method is the male condom (99 percent for both males and females). Among women, other widely known methods include injectables (96 percent), the pill (95 percent), and the female condom (91 percent). For men, the best known methods besides the male condom are the female condom (94 percent) and the pill and injectables (84 percent each).

• Children are considered fully vaccinated when they receive one dose of BCG vaccine, three doses each of DPT and polio vaccines, and one dose of measles vaccine. BCG coverage among children age 12-23 months is nearly universal (97 percent); coverage is also high for the first doses of DPT (96 percent) and polio (97 percent). The proportion of children receiving subsequent doses of DPT and polio vaccines drops slightly, with 92 percent of children receiving the third dose of DPT and 87 percent receiving the third dose of polio. Ninety-two percent of children had received a measles vaccination by the time of the SDHS. Overall, 82 percent of children age 12-23 months are fully immunised.

• In Swaziland, almost all women who had a live birth in the five years preceding the survey received antenatal care from health professionals (97 percent); 9 percent received care from a doctor, and 88 percent received care from a trained nurse or midwife. Only 3 percent of mothers did not receive any antenatal care

• Overall, 87 percent of children in Swaziland are breastfed for some period of time (ever breastfed). The median duration of any breast-feeding in Swaziland is almost 17 months. However, the median duration of exclusive breast-feeding is much shorter (0.7 months).

• In interpreting the malaria programme indicators in Swaziland, it is important to recognise that the disease affects an estimated 30 percent of the population where malaria is most prevalent (the Lubombo Plateau, the lowveld, and parts of the middleveld). Malaria is also seasonal, occurring mainly during or after the rainy season (from November to March). A substantial part of the SDHS fieldwork took place outside of this period.

• Results from the HIV testing component in the 2006-07 SDHS indicate that 26 percent of Swazi adults age 15-49 are infected with HIV. Among women, the HIV rate is 31 percent, compared with 20 percent among men. HIV prevalence peaks at 49 percent for women age 25-29, which is almost five times the rate among women age 15-19 and more than twice the rate observed among women age 45-49. HIV prevalence increases from 2 percent among men in the 15-19 age group to 45 percent in the age group 35-39 and then decreases to 28 percent among men age 45-49. HIV prevalence for women and men age 50 or over is 12 percent and 18 percent, respectively. Among the population age 2-14 years, 4 percent of girls and boys are infected.

Geographic coverage

The 2006-07 Swaziland Demographic and Health Survey (SDHS) is a nationally representative survey. It was designed to provide estimates of health and demographic indicators at the national level, for urban-rural areas, and for the four regions of Manzini, Hhohho, Lubombo, and Shiselweni.

Analysis unit

• Household
• Women age 15-49
• Men age 15-49
• Young adults age 12-14
• adults age 50 and over

Universe

The population covered by the 2006 SWZDHS is defined as the universe of all women Ever-married women in the reproductive ages (i.e., women 15-49).

Kind of data

Sample survey data

Sampling procedure

The 2006-07 SDHS was designed to provide estimates of health and demographic indicators at the national level, for urban-rural areas, and for the four regions of Manzini, Hhohho, Lubombo, and Shiselweni. Standard DHS sampling policy recommends a minimum of 1,000 to 1,200 women per major domain. To meet this criterion, the number of households selected in each of the various domains, particularly urban areas, was not proportional to the actual size of the population in the domain. As a result, the SDHS sample is not self-weighting at the national level, and weights must be applied to the data to obtain the national-level estimates.

The 2006-07 SDHS sample points (clusters) were selected from a list of enumeration areas (EAs) defined in the 1997 Swaziland Population and Housing Census. A total of 275 clusters were drawn from the census sample frame, 111 in the urban areas and 164 in the rural areas.

CSO staff conducted an exhaustive listing of households in each of the SDHS clusters in August and September 2005. From these lists, a systematic sample of households was drawn for a total of 5,500 households. All women and men age 15-49 identified in these households were eligible for individual interview. In addition, a sub-sample of half of these households (2,750 households) was selected randomly in which all boys and girls age 12-14 and persons age 50 and older were eligible for individual interview. In the SDHS households where youth and older adults were interviewed, all individuals age 6 months and older were eligible for anaemia testing and all individuals age 2 and older were eligible for HIV testing. In the SDHS households where only women and men age 15-49 were interviewed, children age 6 months to 5 years were eligible for the anaemia testing and women and men age 15-49 were eligible for anaemia and HIV testing.

During the household listing, field staff used Global Positioning System (GPS) receivers to establish and record the

This table provides statistical information about people in Canada by their demographic, social and economic characteristics as well as provide information about the housing units in which they live.