71 datasets found
  1. Maternal mortality rates worldwide in 2022, by country

    • statista.com
    Updated Dec 12, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). Maternal mortality rates worldwide in 2022, by country [Dataset]. https://www.statista.com/statistics/1240400/maternal-mortality-rates-worldwide-by-country/
    Explore at:
    Dataset updated
    Dec 12, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Worldwide
    Description

    Maternal mortality rates can vary significantly around the world. For example, in 2022, Estonia had a maternal mortality rate of zero per 100,000 live births, while Mexico reported a rate of 38 deaths per 100,000 live births. However, the regions with the highest number of maternal deaths are Sub-Saharan Africa and Southern Asia, with differences between countries and regions often reflecting inequalities in health care services and access. Most causes of maternal mortality are preventable and treatable with the most common causes including severe bleeding, infections, complications during delivery, high blood pressure during pregnancy, and unsafe abortion. Maternal mortality in the United States In 2022, there were a total of 817 maternal deaths in the United States. Women aged 25 to 39 years accounted for 578 of these deaths, however, rates of maternal mortality are much higher among women aged 40 years and older. In 2022, the rate of maternal mortality among women aged 40 years and older in the U.S. was 87 per 100,000 live births, compared to a rate of 21 among women aged 25 to 39 years. The rate of maternal mortality in the U.S. has risen in recent years among all age groups. Differences in maternal mortality in the U.S. by race/ethnicity Sadly, there are great disparities in maternal mortality in the United States among different races and ethnicities. In 2022, the rate of maternal mortality among non-Hispanic white women was about 19 per 100,000 live births, while non-Hispanic Black women died from maternal causes at a rate of almost 50 per 100,000 live births. Rates of maternal mortality have risen for white and Hispanic women in recent years, but Black women have by far seen the largest increase in maternal mortality. In 2022, around 253 Black women died from maternal causes in the United States.

  2. G

    Maternal mortality by country, around the world | TheGlobalEconomy.com

    • theglobaleconomy.com
    csv, excel, xml
    Updated May 6, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Globalen LLC (2020). Maternal mortality by country, around the world | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/rankings/maternal_mortality/
    Explore at:
    excel, csv, xmlAvailable download formats
    Dataset updated
    May 6, 2020
    Dataset authored and provided by
    Globalen LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 2000 - Dec 31, 2020
    Area covered
    World, World
    Description

    The average for 2020 based on 182 countries was 138 deaths per 100,000 births. The highest value was in Chad: 1063 deaths per 100,000 births and the lowest value was in Belarus: 1 deaths per 100,000 births. The indicator is available from 2000 to 2020. Below is a chart for all countries where data are available.

  3. Maternal mortality rate in Africa 2020, by country

    • statista.com
    Updated Jul 8, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Maternal mortality rate in Africa 2020, by country [Dataset]. https://www.statista.com/statistics/1122869/maternal-mortality-rate-in-africa-by-country/
    Explore at:
    Dataset updated
    Jul 8, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2020
    Area covered
    Africa
    Description

    In South Sudan, Chad, and Nigeria the maternal mortality rate was above one thousand in 2020. South Sudan recorded the highest number of mothers' deaths per 100,000 live births. That year, for every 100,000 children, 1,223 mothers died from any cause related to or aggravated by pregnancy or its management. The maternal death rate in Chad equaled to 1,063. Nigeria followed with 1,047 deaths per 100,000 live births.

  4. P

    Palestinian Territory PS: Maternal Mortality Ratio: National Estimate: per...

    • ceicdata.com
    Updated Jan 15, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2025). Palestinian Territory PS: Maternal Mortality Ratio: National Estimate: per 100,000 Live Births [Dataset]. https://www.ceicdata.com/en/palestinian-territory-occupied/social-health-statistics/ps-maternal-mortality-ratio-national-estimate-per-100000-live-births
    Explore at:
    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2010 - Dec 1, 2018
    Area covered
    Palestine
    Description

    State of Palestine (West Bank and Gaza) PS: Maternal Mortality Ratio: National Estimate: per 100,000 Live Births data was reported at 14.000 Ratio in 2018. This records a decrease from the previous number of 34.000 Ratio for 2017. State of Palestine (West Bank and Gaza) PS: Maternal Mortality Ratio: National Estimate: per 100,000 Live Births data is updated yearly, averaging 41.000 Ratio from Dec 2010 (Median) to 2018, with 9 observations. The data reached an all-time high of 56.000 Ratio in 2010 and a record low of 14.000 Ratio in 2018. State of Palestine (West Bank and Gaza) PS: Maternal Mortality Ratio: National Estimate: per 100,000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s State of Palestine (West Bank and Gaza) – Table PS.World Bank.WDI: Social: Health Statistics. Maternal mortality ratio is the number of women who die from pregnancy-related causes while pregnant or within 42 days of pregnancy termination per 100,000 live births.;The country data compiled, adjusted and used in the estimation model by the Maternal Mortality Estimation Inter-Agency Group (MMEIG). The country data were compiled from the following sources: civil registration and vital statistics; specialized studies on maternal mortality; population based surveys and censuses; other available data sources including data from surveillance sites.;;

  5. o

    Maternal Mortality Rate per 100,000 live births - Dataset - openAFRICA

    • open.africa
    Updated Apr 13, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2022). Maternal Mortality Rate per 100,000 live births - Dataset - openAFRICA [Dataset]. https://open.africa/dataset/maternal-mortality-rate-per-100-000-live-births
    Explore at:
    Dataset updated
    Apr 13, 2022
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Maternal Mortality Rate per 100,000 live births in Selected West African Countries

  6. w

    Maternal Health Survey 2017 - Ghana

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Jul 11, 2019
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ghana Statistical Service (GSS) (2019). Maternal Health Survey 2017 - Ghana [Dataset]. https://microdata.worldbank.org/index.php/catalog/3186
    Explore at:
    Dataset updated
    Jul 11, 2019
    Dataset provided by
    Ghana Health Service (GHS)
    Ghana Statistical Service (GSS)
    Time period covered
    2017
    Area covered
    Ghana
    Description

    Abstract

    The 2017 Ghana Maternal Health Survey (2017 GMHS) was designed to produce representative estimates for maternal mortality indicators for the country as a whole, and for each of the three geographical zones, namely Coastal (Western, Central, Greater Accra and Volta), Middle (Eastern, Ashanti and Brong Ahafo) and Northern (Northern, Upper East and Upper West). For other indicators such as maternal care, fertility and child mortality, the survey was designed to produce representative results for the country as whole, for the urban and rural areas, and for each of the country’s 10 administrative regions.

    The primary objectives of the 2017 GMHS were as follows: • To collect data at the national level that will allow an assessment of the level of maternal mortality in Ghana for the country as a whole and for three zones: Coastal (Western, Central, Greater Accra, and Volta regions), Middle (Eastern, Ashanti, and Brong Ahafo regions), and Northern (Northern, Upper East, and Upper West regions) • To identify specific causes of maternal and non-maternal deaths, in particular deaths due to abortionrelated causes, among adult women • To collect data on women’s perceptions of and experiences with antenatal, maternity, and emergency obstetrical care, especially with regard to care received before, during, and following the termination or abortion of a pregnancy • To measure indicators of the utilisation of maternal health services, especially post-abortion care services • To allow follow-on studies and surveys that will be used to observe possible reductions in maternal mortality as well as abortion-related mortality

    The information collected through the 2017 GMHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population.

    Geographic coverage

    National coverage

    Analysis unit

    • Household
    • Individual
    • Woman age 15-49

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sample for the 2017 GMHS was designed to provide estimates of key reproductive health indicators for the country as a whole, for urban and rural areas separately, for three zonal levels (Coastal, Middle, and Northern), and for each of the 10 administrative regions in Ghana (Western, Central, Greater Accra, Volta, Eastern, Ashanti, Brong Ahafo, Northern, Upper East, and Upper West).

    The sampling frame used for the 2017 GMHS is the frame of the 2010 Population and Housing Census (PHC) conducted in Ghana. The 2010 PHC frame is maintained by GSS and updated periodically as new information is received from various surveys. The frame is a complete list of all census enumeration areas (EAs) created for the PHC.

    The 2017 GMHS sample was stratified and selected from the sampling frame in two stages. Each region was separated into urban and rural areas; this yielded 20 sampling strata. Samples of EAs were selected independently in each stratum in two stages. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before the sample selection, according to administrative units at different levels, and by using a probability proportional to size selection at the first stage of sampling.

    In the first stage, 900 EAs (466 EAs in urban areas and 434 EAs in rural areas) were selected with probability proportional to EA size and with independent selection in each sampling stratum. A household listing operation was implemented from 25 January to 9 April 2017 in all of the selected EAs. The resulting lists of households then served as a sampling frame for the selection of households in the second stage. The household listing operation included inquiring of each household if there had been any deaths in that household since January 2012 and, if so, the name, sex, and age at time of death of the deceased person(s).

    Some of the selected EAs were very large. To minimise the task of household listing, each large EA selected for the 2017 GMHS was segmented. Only one segment was selected for the survey with probability proportional to segment size. Household listing was conducted only in the selected segment. Thus, in the GMHS, a cluster is either an EA or a segment of an EA. As part of the listing, the field teams updated the necessary maps and recorded the geographic coordinates of each cluster. The listing was conducted by 20 teams that included a supervisor, three listers/mappers, and a driver.

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

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Three questionnaires were used in the 2017 GMHS: the Household Questionnaire, the Woman’s Questionnaire, and the Verbal Autopsy Questionnaire.

    Cleaning operations

    All electronic data files for the 2017 GMHS were transferred via the IFSS to the GSS central office in Accra, where they were stored on a password-protected computer. The data processing operation included registering and checking for any inconsistencies and outliers. Data editing and cleaning included structure and consistency checks to ensure completeness of work in the field. The central office also conducted secondary editing, which required resolution of computer-identified inconsistencies and coding of openended questions. The data were processed by five GSS staff members. Data editing was accomplished using CSPro software. Secondary editing and data processing were initiated in June and completed in November 2017.

    Response rate

    A total of 27,001 households were selected for the sample, of which 26,500 were occupied at the time of fieldwork. Of the occupied households, 26,324 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 25,304 eligible women were identified for individual interviews; interviews were completed with 25,062 women, yielding a response rate of 99%.

    Sampling error estimates

    The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2017 Ghana Maternal Health Survey (2017 GMHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

    Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2017 GMHS is only one of many samples that could have been selected from the same population, using the same design and sample size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

    If the sample of respondents had been selected by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2017 GMHS sample is the result of a multi-stage stratified sampling, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed by SAS programs developed by ICF International. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used 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 - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months - Completeness of information on siblings - Sibship size and sex ratio of siblings - Pregnancy-related mortality trends

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

  7. Data from: Neonatal Mortality Rate

    • data.internationalmidwives.org
    Updated May 1, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    International Confederation of Midwives (2025). Neonatal Mortality Rate [Dataset]. https://data.internationalmidwives.org/datasets/neonatal-mortality-rate
    Explore at:
    Dataset updated
    May 1, 2025
    Dataset authored and provided by
    International Confederation of Midwives
    Area covered
    Description

    This dataset presents the number of neonatal deaths per 1,000 live births, using data from the UNICEF Data Warehouse. Neonatal mortality refers to the death of a baby within the first 28 days of life and is a critical indicator of newborn health and health system performance. Monitoring this rate supports efforts to improve the quality of care around birth and during the early postnatal period, and to reduce preventable newborn deaths through timely, skilled interventions.Data Source:UNICEF Data Warehouse: https://data.unicef.org/resources/data_explorer/unicef_f/?ag=UNICEF&df=GLOBAL_DATAFLOW&ver=1.0&dq=.CME_MRM0.&startPeriod=1990&endPeriod=2024Data Dictionary: The data is collated with the following columns:Column headingContent of this columnPossible valuesRefNumerical counter for each row of data, for ease of identification1+CountryShort name for the country195 countries in total – all 194 WHO member states plus PalestineISO3Three-digit alphabetical codes International Standard ISO 3166-1 assigned by the International Organization for Standardization (ISO). e.g. AFG (Afghanistan)ISO22 letter identifier code for the countrye.g. AF (Afghanistan)ICM_regionICM Region for countryAFR (Africa), AMR (Americas), EMR (Eastern Mediterranean), EUR (Europe), SEAR (South east Asia) or WPR (Western Pacific)CodeUnique project code for each indicator:GGTXXnnnGG=data group e.g. OU for outcomeT = N for novice or E for ExpertXX = identifier number 00 to 30nnn = identifier name eg mmre.g. OUN01sbafor Outcome Novice Indicator 01 skilled birth attendance Short_nameIndicator namee.g. maternal mortality ratioDescriptionText description of the indicator to be used on websitee.g. Maternal mortality ratio (maternal deaths per 100,000 live births)Value_typeDescribes the indicator typeNumeric: decimal numberPercentage: value between 0 & 100Text: value from list of text optionsY/N: yes or noValue_categoryExpect this to be ‘total’ for all indicators for Phase 1, but this could allow future disaggregation, e.g. male/female; urban/ruraltotalYearThe year that the indicator value was reported. For most indicators, we will only report if 2014 or more recente.g. 2020Latest_Value‘LATEST’ if this is the most recent reported value for the indicator since 2014, otherwise ‘No’. Useful for indicators with time trend data.LATEST or NOValueIndicator valuee.g. 99.8. NB Some indicators are calculated to several decimal places. We present the value to the number of decimal places that should be displayed on the Hub.SourceFor Caesarean birth rate [OUN13cbr] ONLY, this column indicates the source of the data, either OECD when reported, or UNICEF otherwise.OECD or UNICEFTargetHow does the latest value compare with Global guidelines / targets?meets targetdoes not meet targetmeets global standarddoes not meet global standardRankGlobal rank for indicator, i.e. the country with the best global score for this indicator will have rank = 1, next = 2, etc. This ranking is only appropriate for a few indicators, others will show ‘na’1-195Rank out ofThe total number of countries who have reported a value for this indicator. Ranking scores will only go as high as this number.Up to 195TrendIf historic data is available, an indication of the change over time. If there is a global target, then the trend is either getting better, static or getting worse. For mmr [OUN04mmr] and nmr [OUN05nmr] the average annual rate of reduction (arr) between 2016 and latest value is used to determine the trend:arr <-1.0 = getting worsearr >=-1.0 AND <=1.0 = staticarr >1.0 = getting betterFor other indicators, the trend is estimated by comparing the average of the last three years with the average ten years ago:decreasing if now < 95% 10 yrs agoincreasing if now > 105% 10 yrs agostatic otherwiseincreasingdecreasing Or, if there is a global target: getting better,static,getting worseNotesClarification comments, when necessary LongitudeFor use with mapping LatitudeFor use with mapping DateDate data uploaded to the Hubthe following codes are also possible values:not reported does not apply don’t knowThis is one of many datasets featured on the Midwives’ Data Hub, a digital platform designed to strengthen midwifery and advocate for better maternal and newborn health services.

  8. P

    Palestinian Territory PS: Lifetime Risk of Maternal Death: 1 in: Rate Varies...

    • ceicdata.com
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com, Palestinian Territory PS: Lifetime Risk of Maternal Death: 1 in: Rate Varies by Country [Dataset]. https://www.ceicdata.com/en/palestinian-territory-occupied/health-statistics/ps-lifetime-risk-of-maternal-death-1-in-rate-varies-by-country
    Explore at:
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2004 - Dec 1, 2015
    Area covered
    Palestinian territories, Palestine
    Description

    State of Palestine (West Bank and Gaza) PS: Lifetime Risk of Maternal Death: 1 in: Rate Varies by Country data was reported at 490.000 NA in 2015. This records an increase from the previous number of 470.000 NA for 2014. State of Palestine (West Bank and Gaza) PS: Lifetime Risk of Maternal Death: 1 in: Rate Varies by Country data is updated yearly, averaging 270.000 NA from Dec 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 490.000 NA in 2015 and a record low of 120.000 NA in 1992. State of Palestine (West Bank and Gaza) PS: Lifetime Risk of Maternal Death: 1 in: Rate Varies by Country data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s State of Palestine (West Bank and Gaza) – Table PS.World Bank.WDI: Health Statistics. Life time risk of maternal death is the probability that a 15-year-old female will die eventually from a maternal cause assuming that current levels of fertility and mortality (including maternal mortality) do not change in the future, taking into account competing causes of death.; ; WHO, UNICEF, UNFPA, World Bank Group, and the United Nations Population Division. Trends in Maternal Mortality: 1990 to 2015. Geneva, World Health Organization, 2015; Weighted average;

  9. The 2017 Ghana Maternal Health Survey - Ghana

    • microdata-catalog.afdb.org
    Updated Jun 6, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ghana Statistical Service (2022). The 2017 Ghana Maternal Health Survey - Ghana [Dataset]. https://microdata-catalog.afdb.org/index.php/catalog/study/GHA-GMHS-2017-V01
    Explore at:
    Dataset updated
    Jun 6, 2022
    Dataset provided by
    Ghana Health Service
    Ghana Statistical Service
    Time period covered
    2017
    Area covered
    Ghana
    Description

    Abstract

    The 2017 Ghana Maternal Health Survey (GMHS) was implemented by the Ghana Statistical Service (GSS). Data collection took place from 15 June to 12 October 2017. ICF provided technical assistance through The DHS Program, which is funded by the United States Agency for International Development (USAID) and offers financial support and technical assistance for population and health surveys in countries worldwide. Financial support for the 2017 GMHS was provided by the Government of Ghana through the Ministry of Health (MOH) and by USAID, the European Union (EU) delegation to Ghana, and the United Nations Population Fund (UNFPA).

    SURVEY OBJECTIVES The primary objectives of the 2017 GMHS were as follows: - To collect data at the national level that will allow an assessment of the level of maternal mortality in Ghana for the country as a whole and for three zones: Coastal (Western, Central, Greater Accra, and Volta regions), Middle (Eastern, Ashanti, and Brong Ahafo regions), and Northern (Northern, Upper East, and Upper West regions) - To identify specific causes of maternal and non-maternal deaths, in particular deaths due to abortionrelated causes, among adult women - To collect data on women’s perceptions of and experiences with antenatal, maternity, and emergency obstetrical care, especially with regard to care received before, during, and following the termination or abortion of a pregnancy - To measure indicators of the utilisation of maternal health services, especially post-abortion care services - To allow follow-on studies and surveys that will be used to observe possible reductions in maternal mortality as well as abortion-related mortality

    The information collected through the 2017 GMHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population.

    Geographic coverage

    National coverage

    Analysis unit

    Household Woman

    Universe

    the survey covered all household members, all women aged 15-49 and for autopsy questionnaire women aged 12-49.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sample for the 2017 GMHS was designed to provide estimates of key reproductive health indicators for the country as a whole, for urban and rural areas separately, for three zonal levels (Coastal, Middle, and Northern), and for each of the 10 administrative regions in Ghana (Western, Central, Greater Accra, Volta, Eastern, Ashanti, Brong Ahafo, Northern, Upper East, and Upper West).

    The sampling frame used for the 2017 GMHS is the frame of the 2010 Population and Housing Census (PHC) conducted in Ghana. The 2010 PHC frame is maintained by GSS and updated periodically as new information is received from various surveys. The frame is a complete list of all census enumeration areas (EAs) created for the PHC. An EA is a geographic area that covers an average of 161 households (per updates to the PHC frame from the 2014 Ghana Demographic and Health Survey [GDHS]). Individual EA size is the number of residential households in the EA according to the 2010 PHC. The average size of urban EAs (185 households) is slightly larger than the average size of rural EAs (114 households). The sampling frame contains information about the EA’s location, type of residence (urban or rural), and estimated number of residential households.

    The 2017 GMHS sample was stratified and selected from the sampling frame in two stages. Each region was separated into urban and rural areas; this yielded 20 sampling strata. Samples of EAs were selected independently in each stratum in two stages. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before the sample selection, according to administrative units at different levels, and by using a probability proportional to size selection at the first stage of sampling.

    In the first stage, 900 EAs (466 EAs in urban areas and 434 EAs in rural areas) were selected with probability proportional to EA size and with independent selection in each sampling stratum. A household listing operation was implemented from 25 January to 9 April 2017 in all of the selected EAs. The resulting lists of households then served as a sampling frame for the selection of households in the second stage. The household listing operation included inquiring of each household if there had been any deaths in that household since January 2012 and, if so, the name, sex, and age at time of death of the deceased person(s).

    Some of the selected EAs were very large. To minimise the task of household listing, each large EA selected for the 2017 GMHS was segmented. Only one segment was selected for the survey with probability proportional to segment size. Household listing was conducted only in the selected segment. Thus, in the GMHS, a cluster is either an EA or a segment of an EA. As part of the listing, the field teams updated the necessary maps and recorded the geographic coordinates of each cluster. The listing was conducted by 20 teams that included a supervisor, three listers/mappers, and a driver.

    The second stage of selection provided two outputs: the list of households selected for the main survey (Household Questionnaire and Woman’s Questionnaire) and the list of households selected for the verbal autopsy survey (Verbal Autopsy Questionnaire).

    Selection for Main Survey In the second stage of selection for the main survey, a fixed number of 30 households were selected from each cluster, resulting in a total sample size of 27,000 households. Replacement of nonresponding households was not allowed. Due to the non-proportional allocation of the sample to the different regions and the possible differences in response rates, sampling weights are required for any analysis that uses the 2017 GMHS data. This ensures the representativeness of the survey results at the national and regional levels. Results shown in this report have been weighted to account for the complex sample design.

    All women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed.

    Selection for Verbal Autopsy Survey In the second stage of selection for the verbal autopsy survey, all households in which a female resident age 10-54 died in 2012 or later were selected to be visited by an interviewer. However, only the deaths of female residents who were age 12-49 at the time of death were eligible to be included in the survey. A wider age range was used for the initial selection in case of minor inaccuracies on the part of the person who provided information during the household listing operation; the first questions in the Verbal Autopsy Questionnaire established true eligibility, and interviews ended if the deceased woman was discovered to have died before age 12, after age 49, or before 2012.

    There is a chance that some households were both purposively selected for the verbal autopsy survey and randomly selected for the main survey.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Three questionnaires were used in the 2017 GMHS: the Household Questionnaire, the Woman’s Questionnaire, and the Verbal Autopsy Questionnaire. The survey protocol was reviewed and approved by the ICF Institutional Review Board.

    The Household Questionnaire and the Woman’s Questionnaire were adapted from The DHS Program’s standard Demographic and Health Survey questionnaires and the questionnaires used in the 2007 GMHS to reflect the specific interests and data needs of this survey. The Verbal Autopsy Questionnaire was adapted from the recent 2016 World Health Organization (WHO) verbal autopsy instrument.

    For all questionnaires, input was solicited from stakeholders representing government ministries and development partners. After the finalization of the questionnaires in English, they were translated into three major languages: Akan, Ga, and Ewe. The Household and Woman’s Questionnaires were programmed into tablet computers to facilitate computer-assisted personal interviewing (CAPI) for data collection purposes, with the capability to choose any of the four languages for either of the questionnaires.

    The Verbal Autopsy Questionnaire was filled out on paper during data collection and entered into the CAPI system afterwards. The tablet computers were equipped with Bluetooth® technology to enable remote electronic transfer of files, such as assignments from the team supervisor to the interviewers, individual questionnaires among survey team members, and completed questionnaires from interviewers to team supervisors. The CAPI data collection system employed in the 2017 GMHS was developed by The DHS Program using the mobile version of CSPro. The CSPro software was developed jointly by the U.S. Census Bureau, The DHS Program, and Serpro S.A.

    Household Questionnaire The Household Questionnaire was used to list all members of and visitors to selected households. Basic demographic information was collected on the characteristics of each person listed, including his or her age, sex, marital status, education, and relationship to the head of the household. The data on age and sex of household members obtained in the Household Questionnaire were used to identify women who were eligible for individual interviews. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as source of water, type of toilet facilities, materials used for the floor of the dwelling unit, and ownership of various

  10. d

    Ghana - Maternal Health Survey 2017 - Dataset - waterdata

    • waterdata3.staging.derilinx.com
    Updated Mar 16, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2020). Ghana - Maternal Health Survey 2017 - Dataset - waterdata [Dataset]. https://waterdata3.staging.derilinx.com/dataset/ghana-maternal-health-survey-2017
    Explore at:
    Dataset updated
    Mar 16, 2020
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ghana
    Description

    The 2017 Ghana Maternal Health Survey (2017 GMHS) was designed to produce representative estimates for maternal mortality indicators for the country as a whole, and for each of the three geographical zones, namely Coastal (Western, Central, Greater Accra and Volta), Middle (Eastern, Ashanti and Brong Ahafo) and Northern (Northern, Upper East and Upper West). For other indicators such as maternal care, fertility and child mortality, the survey was designed to produce representative results for the country as whole, for the urban and rural areas, and for each of the country’s 10 administrative regions. The primary objectives of the 2017 GMHS were as follows: • To collect data at the national level that will allow an assessment of the level of maternal mortality in Ghana for the country as a whole and for three zones: Coastal (Western, Central, Greater Accra, and Volta regions), Middle (Eastern, Ashanti, and Brong Ahafo regions), and Northern (Northern, Upper East, and Upper West regions) • To identify specific causes of maternal and non-maternal deaths, in particular deaths due to abortionrelated causes, among adult women • To collect data on women’s perceptions of and experiences with antenatal, maternity, and emergency obstetrical care, especially with regard to care received before, during, and following the termination or abortion of a pregnancy • To measure indicators of the utilisation of maternal health services, especially post-abortion care services • To allow follow-on studies and surveys that will be used to observe possible reductions in maternal mortality as well as abortion-related mortality The information collected through the 2017 GMHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population.

  11. P

    Palestinian Territory PS: Lifetime Risk Of Maternal Death

    • ceicdata.com
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com, Palestinian Territory PS: Lifetime Risk Of Maternal Death [Dataset]. https://www.ceicdata.com/en/palestinian-territory-occupied/health-statistics/ps-lifetime-risk-of-maternal-death
    Explore at:
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2004 - Dec 1, 2015
    Area covered
    Palestine
    Description

    State of Palestine (West Bank and Gaza) PS: Lifetime Risk Of Maternal Death data was reported at 0.206 % in 2015. This records a decrease from the previous number of 0.214 % for 2014. State of Palestine (West Bank and Gaza) PS: Lifetime Risk Of Maternal Death data is updated yearly, averaging 0.372 % from Dec 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 0.864 % in 1990 and a record low of 0.206 % in 2015. State of Palestine (West Bank and Gaza) PS: Lifetime Risk Of Maternal Death data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s State of Palestine (West Bank and Gaza) – Table PS.World Bank.WDI: Health Statistics. Life time risk of maternal death is the probability that a 15-year-old female will die eventually from a maternal cause assuming that current levels of fertility and mortality (including maternal mortality) do not change in the future, taking into account competing causes of death.; ; WHO, UNICEF, UNFPA, World Bank Group, and the United Nations Population Division. Trends in Maternal Mortality: 1990 to 2015. Geneva, World Health Organization, 2015; Weighted average;

  12. Preterm Birth Rate

    • data.internationalmidwives.org
    Updated Jun 14, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    International Confederation of Midwives (2025). Preterm Birth Rate [Dataset]. https://data.internationalmidwives.org/datasets/preterm-birth-rate
    Explore at:
    Dataset updated
    Jun 14, 2025
    Dataset authored and provided by
    International Confederation of Midwives
    Area covered
    Description

    This dataset presents the estimated percentage of babies born alive before 37 weeks of pregnancy are completed, by country. Preterm birth is a leading cause of neonatal morbidity and mortality. Understanding national rates supports efforts to improve antenatal care, timely interventions, and newborn outcomes. These estimates are adapted from Liang et al. (2024), based on the Global Burden of Disease Study 2021, and provide a globally comparable measure of preterm birth burden.Data Dictionary: The data is collated with the following columns:Column headingContent of this columnPossible valuesRefNumerical counter for each row of data, for ease of identification1+CountryShort name for the country195 countries in total – all 194 WHO member states plus PalestineISO3Three-digit alphabetical codes International Standard ISO 3166-1 assigned by the International Organization for Standardization (ISO). e.g. AFG (Afghanistan)ISO22 letter identifier code for the countrye.g. AF (Afghanistan)ICM_regionICM Region for countryAFR (Africa), AMR (Americas), EMR (Eastern Mediterranean), EUR (Europe), SEAR (South east Asia) or WPR (Western Pacific)CodeUnique project code for each indicator:GGTXXnnnGG=data group e.g. OU for outcomeT = N for novice or E for ExpertXX = identifier number 00 to 30nnn = identifier name eg mmre.g. OUN01sbafor Outcome Novice Indicator 01 skilled birth attendance Short_nameIndicator namee.g. maternal mortality ratioDescriptionText description of the indicator to be used on websitee.g. Maternal mortality ratio (maternal deaths per 100,000 live births)Value_typeDescribes the indicator typeNumeric: decimal numberPercentage: value between 0 & 100Text: value from list of text optionsY/N: yes or noValue_categoryExpect this to be ‘total’ for all indicators for Phase 1, but this could allow future disaggregation, e.g. male/female; urban/ruraltotalYearThe year that the indicator value was reported. For most indicators, we will only report if 2014 or more recente.g. 2020Latest_Value‘LATEST’ if this is the most recent reported value for the indicator since 2014, otherwise ‘No’. Useful for indicators with time trend data.LATEST or NOValueIndicator valuee.g. 99.8. NB Some indicators are calculated to several decimal places. We present the value to the number of decimal places that should be displayed on the Hub.SourceFor Caesarean birth rate [OUN13cbr] ONLY, this column indicates the source of the data, either OECD when reported, or UNICEF otherwise.OECD or UNICEFTargetHow does the latest value compare with Global guidelines / targets?meets targetdoes not meet targetmeets global standarddoes not meet global standardRankGlobal rank for indicator, i.e. the country with the best global score for this indicator will have rank = 1, next = 2, etc. This ranking is only appropriate for a few indicators, others will show ‘na’1-195Rank out ofThe total number of countries who have reported a value for this indicator. Ranking scores will only go as high as this number.Up to 195TrendIf historic data is available, an indication of the change over time. If there is a global target, then the trend is either getting better, static or getting worse. For mmr [OUN04mmr] and nmr [OUN05nmr] the average annual rate of reduction (arr) between 2016 and latest value is used to determine the trend:arr <-1.0 = getting worsearr >=-1.0 AND <=1.0 = staticarr >1.0 = getting betterFor other indicators, the trend is estimated by comparing the average of the last three years with the average ten years ago:decreasing if now < 95% 10 yrs agoincreasing if now > 105% 10 yrs agostatic otherwiseincreasingdecreasing Or, if there is a global target: getting better,static,getting worseNotesClarification comments, when necessary LongitudeFor use with mapping LatitudeFor use with mapping DateDate data uploaded to the Hubthe following codes are also possible values:not reported does not apply don’t knowThis is one of many datasets featured on the Midwives’ Data Hub, a digital platform designed to strengthen midwifery and advocate for better maternal and newborn health services.

  13. f

    Data from: S1 Dataset -

    • plos.figshare.com
    bin
    Updated Mar 13, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Hiluf Ebuy Abraha; Hale Teka; Awol Yemane Legesse; Mohamedawel Mohamedniguss Ebrahim; Mache Tsadik; Girmatsion Fisseha; Bereket Berhe; Brhane Ayele; Gebrehaweria Gebrekurstos; Tesfit Gebremeskel; Tsega Gebremariam; Martha Yemane Hadush; Tigist Hagos; Abraha Gebreegziabher; Kibrom Muez; Haile Tesfay; Hagos Godefay; Afework Mulugeta (2024). S1 Dataset - [Dataset]. http://doi.org/10.1371/journal.pone.0299650.s003
    Explore at:
    binAvailable download formats
    Dataset updated
    Mar 13, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Hiluf Ebuy Abraha; Hale Teka; Awol Yemane Legesse; Mohamedawel Mohamedniguss Ebrahim; Mache Tsadik; Girmatsion Fisseha; Bereket Berhe; Brhane Ayele; Gebrehaweria Gebrekurstos; Tesfit Gebremeskel; Tsega Gebremariam; Martha Yemane Hadush; Tigist Hagos; Abraha Gebreegziabher; Kibrom Muez; Haile Tesfay; Hagos Godefay; Afework Mulugeta
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundIn resource-limited countries with weak healthcare systems, women of reproductive age are particularly vulnerable during times of conflict. In Tigray, Ethiopia, where a war broke out on 04 November 2020, there is a lack of information on causes of death (CoD) among women of reproductive age. This study aims to determine the underlying CoD among women of reproductive age during the armed conflict in Tigray.MethodsThis community-based survey was carried out in six Tigray zones, excluding the western zone for security reasons. We used a multistage stratified cluster sampling method to select the smallest administrative unit known as Tabiya. Data were collected using a standardized 2022 WHO Verbal Autopsy (VA) tool. The collected data were analyzed using the InterVA model using R analytic software. The study reported both group-based and cause-specific mortality fractions.ResultsA total of 189,087 households were screened and 832 deaths were identified among women of reproductive age. The Global Burden of Disease classification showed that infectious and maternal disorders were the leading CoD, accounting for 42.9% of all deaths. External causes contributed to 26.4% of fatalities, where assault accounted for 13.2% of the deaths. Maternal deaths made up 30.0% of the overall mortality rate. HIV/AIDS was the primary CoD, responsible for 13.2% of all deaths and 54.0% of infectious causes. Other significant causes included obstetric hemorrhage (11.7%) and other and unspecified cardiac disease (6.6%).ConclusionsThe high proportion of infectious diseases related CoD, including HIV/AIDS, as well as the occurrence of uncommon external CoD among women, such as assault, and a high proportion of maternal deaths are likely the result of the impact of war in the region. This highlights the urgent need for targeted interventions to address these issues and prioritize sexual and reproductive health as well as maternal health in Tigray.

  14. i

    Number of live births

    • data.internationalmidwives.org
    Updated Jun 14, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    International Confederation of Midwives (2025). Number of live births [Dataset]. https://data.internationalmidwives.org/datasets/number-of-live-births
    Explore at:
    Dataset updated
    Jun 14, 2025
    Dataset authored and provided by
    International Confederation of Midwives
    Area covered
    Description

    This dataset presents the estimated number of live births in each country for the most recent reference year, based on the 2024 revision of the UN Population Division’s World Population Prospects. Live birth estimates are a key demographic indicator, used for planning health services, calculating health coverage indicators, and understanding population growth trends. These figures support maternal and newborn health monitoring and workforce planning at national and global levels.Data Source:UN Population Division World Population Prospects: https://population.un.org/wpp/Download/StandardData Dictionary: The data is collated with the following columns:Column headingContent of this columnPossible valuesRefNumerical counter for each row of data, for ease of identification1+CountryShort name for the country195 countries in total – all 194 WHO member states plus PalestineISO3Three-digit alphabetical codes International Standard ISO 3166-1 assigned by the International Organization for Standardization (ISO). e.g. AFG (Afghanistan)ISO22 letter identifier code for the countrye.g. AF (Afghanistan)ICM_regionICM Region for countryAFR (Africa), AMR (Americas), EMR (Eastern Mediterranean), EUR (Europe), SEAR (South east Asia) or WPR (Western Pacific)CodeUnique project code for each indicator:GGTXXnnnGG=data group e.g. OU for outcomeT = N for novice or E for ExpertXX = identifier number 00 to 30nnn = identifier name eg mmre.g. OUN01sbafor Outcome Novice Indicator 01 skilled birth attendance Short_nameIndicator namee.g. maternal mortality ratioDescriptionText description of the indicator to be used on websitee.g. Maternal mortality ratio (maternal deaths per 100,000 live births)Value_typeDescribes the indicator typeNumeric: decimal numberPercentage: value between 0 & 100Text: value from list of text optionsY/N: yes or noValue_categoryExpect this to be ‘total’ for all indicators for Phase 1, but this could allow future disaggregation, e.g. male/female; urban/ruraltotalYearThe year that the indicator value was reported. For most indicators, we will only report if 2014 or more recente.g. 2020Latest_Value‘LATEST’ if this is the most recent reported value for the indicator since 2014, otherwise ‘No’. Useful for indicators with time trend data.LATEST or NOValueIndicator valuee.g. 99.8. NB Some indicators are calculated to several decimal places. We present the value to the number of decimal places that should be displayed on the Hub.SourceFor Caesarean birth rate [OUN13cbr] ONLY, this column indicates the source of the data, either OECD when reported, or UNICEF otherwise.OECD or UNICEFTargetHow does the latest value compare with Global guidelines / targets?meets targetdoes not meet targetmeets global standarddoes not meet global standardRankGlobal rank for indicator, i.e. the country with the best global score for this indicator will have rank = 1, next = 2, etc. This ranking is only appropriate for a few indicators, others will show ‘na’1-195Rank out ofThe total number of countries who have reported a value for this indicator. Ranking scores will only go as high as this number.Up to 195TrendIf historic data is available, an indication of the change over time. If there is a global target, then the trend is either getting better, static or getting worse. For mmr [OUN04mmr] and nmr [OUN05nmr] the average annual rate of reduction (arr) between 2016 and latest value is used to determine the trend:arr <-1.0 = getting worsearr >=-1.0 AND <=1.0 = staticarr >1.0 = getting betterFor other indicators, the trend is estimated by comparing the average of the last three years with the average ten years ago:decreasing if now < 95% 10 yrs agoincreasing if now > 105% 10 yrs agostatic otherwiseincreasingdecreasing Or, if there is a global target: getting better,static,getting worseNotesClarification comments, when necessary LongitudeFor use with mapping LatitudeFor use with mapping DateDate data uploaded to the Hubthe following codes are also possible values:not reported does not apply don’t knowThis is one of many datasets featured on the Midwives’ Data Hub, a digital platform designed to strengthen midwifery and advocate for better maternal and newborn health services.

  15. Countries with the lowest fertility rates 2024

    • statista.com
    • ai-chatbox.pro
    Updated Apr 16, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Countries with the lowest fertility rates 2024 [Dataset]. https://www.statista.com/statistics/268083/countries-with-the-lowest-fertility-rates/
    Explore at:
    Dataset updated
    Apr 16, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    Worldwide
    Description

    The statistic shows the 20 countries with the lowest fertility rates in 2024. All figures are estimates. In 2024, the fertility rate in Taiwan was estimated to be at 1.11 children per woman, making it the lowest fertility rate worldwide. Fertility rate The fertility rate is the average number of children born per woman of child-bearing age in a country. Usually, a woman aged between 15 and 45 is considered to be in her child-bearing years. The fertility rate of a country provides an insight into its economic state, as well as the level of health and education of its population. Developing countries usually have a higher fertility rate due to lack of access to birth control and contraception, and to women usually foregoing a higher education, or even any education at all, in favor of taking care of housework. Many families in poorer countries also need their children to help provide for the family by starting to work early and/or as caretakers for their parents in old age. In developed countries, fertility rates and birth rates are usually much lower, as birth control is easier to obtain and women often choose a career before becoming a mother. Additionally, if the number of women of child-bearing age declines, so does the fertility rate of a country. As can be seen above, countries like Hong Kong are a good example for women leaving the patriarchal structures and focusing on their own career instead of becoming a mother at a young age, causing a decline of the country’s fertility rate. A look at the fertility rate per woman worldwide by income group also shows that women with a low income tend to have more children than those with a high income. The United States are neither among the countries with the lowest, nor among those with the highest fertility rate, by the way. At 2.08 children per woman, the fertility rate in the US has been continuously slightly below the global average of about 2.4 children per woman over the last decade.

  16. P

    Palestinian Territory PS: Number of Maternal Death

    • ceicdata.com
    Updated Nov 23, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2021). Palestinian Territory PS: Number of Maternal Death [Dataset]. https://www.ceicdata.com/en/palestinian-territory-occupied/health-statistics/ps-number-of-maternal-death
    Explore at:
    Dataset updated
    Nov 23, 2021
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2004 - Dec 1, 2015
    Area covered
    Palestine
    Description

    State of Palestine (West Bank and Gaza) PS: Number of Maternal Death data was reported at 69.000 Person in 2015. This stayed constant from the previous number of 69.000 Person for 2014. State of Palestine (West Bank and Gaza) PS: Number of Maternal Death data is updated yearly, averaging 82.000 Person from Dec 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 120.000 Person in 1993 and a record low of 69.000 Person in 2015. State of Palestine (West Bank and Gaza) PS: Number of Maternal Death data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s State of Palestine (West Bank and Gaza) – Table PS.World Bank.WDI: Health Statistics. A maternal death refers to the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management but not from accidental or incidental causes.; ; WHO, UNICEF, UNFPA, World Bank Group, and the United Nations Population Division. Trends in Maternal Mortality: 1990 to 2015. Geneva, World Health Organization, 2015; Sum;

  17. s

    Ghana Maternal Health Survey 2007 - Ghana

    • microdata.statsghana.gov.gh
    Updated Dec 5, 2013
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ghana Statistical Service (2013). Ghana Maternal Health Survey 2007 - Ghana [Dataset]. https://microdata.statsghana.gov.gh/index.php/catalog/58
    Explore at:
    Dataset updated
    Dec 5, 2013
    Dataset authored and provided by
    Ghana Statistical Service
    Time period covered
    2007
    Area covered
    Ghana
    Description

    Abstract

    The principal objective of the 2007 Ghana Maternal Health Survey (GMHS) is intended to serve as a source of data on maternal health and maternal death for policymakers and the research community involved in the Reducing Maternal Morbidity and Mortality (R3M) program. Specifically, the data collected in the GMHS is intended to help the Government of Ghana and the consortium of organizations participating in the R3M program to launch a series of collaborative efforts to significantly expand women's access to modern family planning services and comprehensive abortion care (CAC), reduce unwanted fertility, and reduce severe complications and deaths resulting from unsafe abortion. The GMHS collected data from a nationally representative sample of households and women of reproductive age (15-49). The data were collected in two phases. The primary objectives of the 2007 GMHS were: • To collect data at the national level that will allow an assessment of the level of maternal mortality in Ghana for the country as a whole, for the R3M program regions (Greater Accra, Ashanti and Eastern Regions), and for the non-program regions; • To identify specific causes of maternal and non-maternal deaths, and specifically to be able to identify deaths due to abortion-related causes, among adult women; •To collect data on women’s perceptions and experience with antenatal, maternity, and emergency obstetrical care, especially with regard to care received before, during, and after the termination or abortion of a pregnancy; • To measure indicators of the utilization of maternal health services and especially post-abortion care services in Ghana; and • To provide baseline data for the R3M program and for follow-on studies and surveys that will be used to observe possible reductions in maternal mortality as well as reductions in abortion-related mortality.It also contributes to the ever-growing international database on maternal health-related information.

    The pregnancy-related mortality ratio (PRMR) for the 7-year period preceding the survey, calculated from the sibling history data, is 451 deaths per 100,000 live births and for the 5-year period preceding the survey is 378 deaths per 100,000 live births.Induced abortion accounts for more than one in ten maternal deaths and the obstetric risk from induced abortion is highest among young women age 15-24. Although almost all women seek antenatal care from a health professional, only one in two women deliver in a health facility, and three in four women seek postnatal care. Despite the emphasis on continuity of care, less than one in two women receive all three maternity care components (antenatal care, delivery care, and postnatal care) from a skilled provider. Clearly, Ghana has a long way to go towards achieving the MDG-5 target.

    Geographic coverage

    National

    Analysis unit

    Individual

    Universe

    1. All women age 12-49 years in households and residents in Ghana

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    To achieve the above-mentioned objectives and to obtain an accurate measure of the causes of maternal mortality at the national level, and for the Reducing Maternal Morbidity and Mortality( R3M) regions (Greater Accra, Ashanti and Eastern regions) and other regions (Western, Central, Volta, Brong Ahafo, Northern, Upper East and Upper West), 1600 primary sampling units were selected (half from the R3M regions and half from the other regions) within the 10 administrative regions of the country, across urban and rural areas. The primary sampling units consisted of wards or subwards drawn from the 2000 Population Census. This sample size was estimated from information in the 2003 Ghana DHS survey; it was expected that each primary sampling unit would yield, on average, 150 households. GSS and GHS enumerators carried out a complete mapping and listing of the 1600 selected clusters. This first phase of data collection yielded a total of 227,715 households.

    A short household questionnaire was administered to identify deaths that occurred in the five years preceding the survey to women age 12-49 in each household listed in the selected cluster. In the second phase of data collection a verbal autopsy questionnaire was administered in all households identified in the first phase as having experienced the death of a woman age 12-49. This yielded a total of 4,203 completed verbal autopsy questionnaires.

    In the second phase of fieldwork, 400 clusters were randomly selected from the 1600 clusters identified in the first phase. Households with women age 15-49 were selected from these 400 clusters (half from the R3M regions and half from the other regions) and were stratified by region and urban-rural residence to yield 10,858 completed household interviews and 10,370 individual women's interviews. These households were selected randomly and independently from the households identified in the first phase as having experienced a female death.

    Institutional populations (those in hospitals, army barracks, etc.) and households residing in refugee camps were excluded from the GMHS sample.

    Sampling deviation

    No deviation of the original sample design was made

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The GMHS used four questionnaires: (1) a Phase I short household questionnaire administered at the time of listing; (2) a Phase II verbal autopsy questionnaire administered in households identified at listing as having experienced the death of a female household member age 12-49; (3) a Phase II long-form household questionnaire administered in independently selected households chosen for the individual woman’s interview, and (4) a Phase II questionnaire for individual women age 15-49 in the same phase two selected households. The primary purpose of the short household questionnaire administered at the time of listing during Phase I was to identify deaths to women age 12-49, for administering the verbal autopsy questionnaire on the causes of female deaths, particularly maternal deaths and abortion-related deaths. Unique identifiers for households in phase one and households in phase two were not maintained; therefore households cannot be matched across both phases of the survey. During the first phase of the survey, all households in each selected cluster were listed and administered the short household questionnaire. This questionnaire was administered to identify households that experienced the death of a female [regular] household member in the five years preceding the survey. The verbal autopsy questionnaire (VAQ) was administered during the second phase of fieldwork in those households in which thefemale who died was age 12-49. The VAQ was designed to collect as much information as possible on the causes of all female deaths, to inform the subsequent categorization of maternal deaths, and facilitate specific identification of abortion-related deaths. During the second phase of fieldwork, a longer household questionnaire was administered in the independent subsample of households, to identify eligible women age 15- 49 for the individual woman’s questionnaire and to obtain some background information on the socioeconomic status of these women. The individual questionnaire included the maternal mortality module, which allows for the calculation of direct estimates of pregnancy-related mortality rates and ratios based on the sibling history. The individual questionnaire also gathered information on abortions and miscarriages, the utilization of maternal health services and post-abortion care, women’s knowledge of the legality of abortion in Ghana, the services they have utilized for abortion and if not, the reasons they have not been able to access professional health care for abortions, the places that offer abortion-related care, the persons offering such services, and other related questions. During the design of these questionnaires, input was sought from a variety of organizations that are expected to use the resulting data. After preparation of the questionnaires in English, they were translated into three languages: Akan, Ga, and Ewe. Back translations into English were carried out by people other than the initial translators to verify the accuracy of the translations in the three languages to be used. All problems arising during the translations were resolved before the pretest. The translated questionnaires were pretested to detect any problems in the translations or the flow of the questionnaire, as well as to gauge the length of time required for interviews. GSS and GHS engaged 20 interviewers for approximately two weeks for the pretest (with proficiency in each of the local languages used in the survey). All the pretest interviewers were trained for two weeks. The pretest interviewing took about one week to complete, during which approximately 30 women were interviewed in each of the local languages. The pretest results were used to modify the survey instruments as necessary. All changes in the questionnaire after the pretest were agreed to by GSS, GHS, and Macro. GSS and GHS were responsible for producing a sufficient number of the various questionnaires for the main fieldwork. During the pretest and main survey training, experts in the areas of health and family planning were identified by GSS and GHS to provide guidance in the presentation of topics in their fields, as they relate to the GMHS questionnaires. Other technical documents that were finalized include: • Household listing manual, listing forms and cartographic materials; • Interviewer’s manual; • Supervisor’s manual; • Interviewer and Supervisor’s

  18. d

    Year wise different item-wise reports statistics the state of West Bengal...

    • dataful.in
    Updated May 22, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Dataful (Factly) (2024). Year wise different item-wise reports statistics the state of West Bengal under Health Management Information System (HMIS) [Dataset]. https://dataful.in/datasets/5868
    Explore at:
    csv, xlsx, application/x-parquetAvailable download formats
    Dataset updated
    May 22, 2024
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Area covered
    West Bengal
    Variables measured
    Medical item-wise reports
    Description

    The data shows the statistics of different item-wise reports on a cumulative yearly basis in states up to the sub-district level in West Bengal. It included 1) Ante Natal Care (ANC) - Antenatal care (ANC) is a means to identify high-risk pregnancies and educate women so that they might experience healthier delivery and outcomes. 2) Deliveries - The delivery of the baby by the pregnant women 3) Number of Caesarean (C-Section) deliveries - Caesarean delivery (C-section) is used to deliver a baby through surgical incisions made in the abdomen and uterus. 4) Pregnancy outcome & details of new-born - The records kept of the pregnancy outcome along with the details of new-born 5) Complicated Pregnancies - The different pregnancies that were not normal and had complications 6) Post Natal Care (PNC) - Postnatal care is defined as care given to the mother and her new-born baby immediately after the birth of the placenta and for the first six weeks of life 7) Reproductive Tract Infections/Sexually Transmitted Infections (RTI/STI) Cases - The records of reproductive tract infections along with the records of the sexually transmitted cases 8) Family Planning - The different methods used by families to keep track of family 9) CHILD IMMUNISATION - The records of child immunisation which are records of vaccination 10) Number of cases of Childhood Diseases (0-5 years) - The records of the number of cases of childhood diseases within the age of 5 years old 11) NVBDCP - The National Vector Borne Disease Control Programme (NVBDCP) is one of the most comprehensive and multi-faceted public health activities in the country and concerned with the prevention and control of vector-borne diseases, namely Malaria, Filariasis, Kala-azar, Dengue and Japanese Encephalitis (JE). 12) Adolescent Health - The record of the conditions of adolescent health 13 ) Directly Observed Treatment, Short-course (DOTS) - Directly observed treatment, short-course (DOTS, also known as TB-DOTS) is the name given to the tuberculosis (TB) control strategy recommended by the World Health Organization 14) Patient Services - Patient Services means those which vary with the number of personnel; professional and para-professional skills of the personnel; specialised equipment, and reflect the intensity of the medical and psycho-social needs of the patients. 15) Laboratory Testing - A medical procedure that involves testing a sample of blood, urine, or other substance from the body. Laboratory tests can help determine a diagnosis, plan treatment, check if the treatment works, or monitor the disease over time. 16) Details of deaths reported with probable causes - The reports of deaths recorded with possible reasons are given in a detail 17) Vaccines - The reports of vaccines which are recorded 18) Syringes - It is the number of syringes that are used and recorded 19) Rashtriya Bal Swasthaya Karyakram (RBSK) - Rashtriya Bal Swasthya Karyakram (RBSK) is an important initiative aiming at early identification and early intervention for children from birth to 18 years to cover 4 'D's viz. Defects at birth, Deficiencies, Diseases, Development delays, including disability. 20) Coverage under WIFS JUNIOR - The coverage of the Weekly Iron Folic Acid Supplementation Programme for children six to one 21) Maternal Death Reviews (MDR) - A maternal death review is cross-checking how the mother died. It provides a rare opportunity for a group of health staff and community members to learn from a tragic – and often preventable. 22) Janani Shishu Suraksha Karyakaram (JSSK)- This initiative provides free and cashless services to pregnant women, including normal deliveries and caesarean operations. It entitles all pregnant women in public health institutions to free and no-expense delivery, including caesarean section.

  19. f

    The three broad causes of death categories and subcategories among women of...

    • plos.figshare.com
    xls
    Updated Mar 13, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Hiluf Ebuy Abraha; Hale Teka; Awol Yemane Legesse; Mohamedawel Mohamedniguss Ebrahim; Mache Tsadik; Girmatsion Fisseha; Bereket Berhe; Brhane Ayele; Gebrehaweria Gebrekurstos; Tesfit Gebremeskel; Tsega Gebremariam; Martha Yemane Hadush; Tigist Hagos; Abraha Gebreegziabher; Kibrom Muez; Haile Tesfay; Hagos Godefay; Afework Mulugeta (2024). The three broad causes of death categories and subcategories among women of reproductive age death in Tigray, Northern Ethiopia, 2020–2022 (n = 832). [Dataset]. http://doi.org/10.1371/journal.pone.0299650.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Mar 13, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Hiluf Ebuy Abraha; Hale Teka; Awol Yemane Legesse; Mohamedawel Mohamedniguss Ebrahim; Mache Tsadik; Girmatsion Fisseha; Bereket Berhe; Brhane Ayele; Gebrehaweria Gebrekurstos; Tesfit Gebremeskel; Tsega Gebremariam; Martha Yemane Hadush; Tigist Hagos; Abraha Gebreegziabher; Kibrom Muez; Haile Tesfay; Hagos Godefay; Afework Mulugeta
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ethiopia, Tigray
    Description

    The three broad causes of death categories and subcategories among women of reproductive age death in Tigray, Northern Ethiopia, 2020–2022 (n = 832).

  20. Demographic and Health Survey 2003 - Nigeria

    • dev.ihsn.org
    • catalog.ihsn.org
    • +2more
    Updated Apr 25, 2019
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    National Population Commission (2019). Demographic and Health Survey 2003 - Nigeria [Dataset]. https://dev.ihsn.org/nada/catalog/study/NGA_2003_DHS_v01_M
    Explore at:
    Dataset updated
    Apr 25, 2019
    Dataset authored and provided by
    National Population Commissionhttps://nationalpopulation.gov.ng/
    Time period covered
    2003
    Area covered
    Nigeria
    Description

    Abstract

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

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

    MAIN RESULTS

    • FERTILITY

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

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

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

    • FAMILY PLANNING

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

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

    • CHILD HEALTH

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

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

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

    • WOMEN'S HEALTH

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

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

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

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

    WOMEN'S CHARACTERISTICS AND STATUS

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

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

    MALARIA CONTROL PROGRAM INDICATORS

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

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

    Among children

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2024). Maternal mortality rates worldwide in 2022, by country [Dataset]. https://www.statista.com/statistics/1240400/maternal-mortality-rates-worldwide-by-country/
Organization logo

Maternal mortality rates worldwide in 2022, by country

Explore at:
4 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Dec 12, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2022
Area covered
Worldwide
Description

Maternal mortality rates can vary significantly around the world. For example, in 2022, Estonia had a maternal mortality rate of zero per 100,000 live births, while Mexico reported a rate of 38 deaths per 100,000 live births. However, the regions with the highest number of maternal deaths are Sub-Saharan Africa and Southern Asia, with differences between countries and regions often reflecting inequalities in health care services and access. Most causes of maternal mortality are preventable and treatable with the most common causes including severe bleeding, infections, complications during delivery, high blood pressure during pregnancy, and unsafe abortion. Maternal mortality in the United States In 2022, there were a total of 817 maternal deaths in the United States. Women aged 25 to 39 years accounted for 578 of these deaths, however, rates of maternal mortality are much higher among women aged 40 years and older. In 2022, the rate of maternal mortality among women aged 40 years and older in the U.S. was 87 per 100,000 live births, compared to a rate of 21 among women aged 25 to 39 years. The rate of maternal mortality in the U.S. has risen in recent years among all age groups. Differences in maternal mortality in the U.S. by race/ethnicity Sadly, there are great disparities in maternal mortality in the United States among different races and ethnicities. In 2022, the rate of maternal mortality among non-Hispanic white women was about 19 per 100,000 live births, while non-Hispanic Black women died from maternal causes at a rate of almost 50 per 100,000 live births. Rates of maternal mortality have risen for white and Hispanic women in recent years, but Black women have by far seen the largest increase in maternal mortality. In 2022, around 253 Black women died from maternal causes in the United States.

Search
Clear search
Close search
Google apps
Main menu