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.

This statistic shows the 20 countries* with the highest infant mortality rate in 2024. An estimated 101.3 infants per 1,000 live births died in the first year of life in Afghanistan in 2024. Infant and child mortality Infant mortality usually refers to the death of children younger than one year. Child mortality, which is often used synonymously with infant mortality, is the death of children younger than five. Among the main causes are pneumonia, diarrhea – which causes dehydration – and infections in newborns, with malnutrition also posing a severe problem. As can be seen above, most countries with a high infant mortality rate are developing countries or emerging countries, most of which are located in Africa. Good health care and hygiene are crucial in reducing child mortality; among the countries with the lowest infant mortality rate are exclusively developed countries, whose inhabitants usually have access to clean water and comprehensive health care. Access to vaccinations, antibiotics and a balanced nutrition also help reducing child mortality in these regions. In some countries, infants are killed if they turn out to be of a certain gender. India, for example, is known as a country where a lot of girls are aborted or killed right after birth, as they are considered to be too expensive for poorer families, who traditionally have to pay a costly dowry on the girl’s wedding day. Interestingly, the global mortality rate among boys is higher than that for girls, which could be due to the fact that more male infants are actually born than female ones. Other theories include a stronger immune system in girls, or more premature births among boys.

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.

This statistic shows the 20 countries * with the lowest infant mortality rate in 2024. An estimated 1.5 out of 1,000 live births died in the first year of life in Slovenia and Singapore in 2024. Infant mortality Infant mortality rates are often used as an indicator of the health and well-being of a nation. Monaco, Iceland, and Japan are among the top three countries with the lowest infant mortality rates with around 2 infant deaths per 1,000 infants within their first year of life. Generally, the countries with the lowest infant mortality also have some of the highest average life expectancy figures. Additionally, the countries with the highest density of physicians and doctors also generally report low infant mortality. Yet, many different factors contribute to differing rates, including the overall income of a country, health spending per capita, a mother’s level of education, environmental conditions, and medical infrastructure, to name a few. This creates a lot of variation concerning the level of childbirth and infant care around the world. The countries with the highest rates of infant mortality include Afghanistan, Mali, and Somalia. These countries experience around 100 infant deaths per 1,000 infants in their first year of life. While the reasons for high rates of infant mortality are numerous, the leading causes of death for children under the year five around the world are Pneumonia, Diarrhea, and Prematurity.

UNICEF's country profile for India, including under-five mortality rates, child health, education and sanitation data.

In 2022, the infant mortality rate in the United States was 5.4 out of every 1,000 live births. This is a significant decrease from 1960, when infant mortality was at around 26 deaths out of every 1,000 live births. What is infant mortality? The infant mortality rate is the number of deaths of babies under the age of one per 1,000 live births. There are many causes for infant mortality, which include birth defects, low birth weight, pregnancy complications, and sudden infant death syndrome. In order to decrease the high rates of infant mortality, there needs to be an increase in education and medicine so babies and mothers can receive the proper treatment needed. Maternal mortality is also related to infant mortality. If mothers can attend more prenatal visits and have more access to healthcare facilities, maternal mortality can decrease, and babies have a better chance of surviving in their first year. Worldwide infant mortality rates Infant mortality rates vary worldwide; however, some areas are more affected than others. Afghanistan suffered from the highest infant mortality rate in 2024, and the following 19 countries all came from Africa, with the exception of Pakistan. On the other hand, Slovenia had the lowest infant mortality rate that year. High infant mortality rates can be attributed to lack of sanitation, technological advancements, and proper natal care. In the United States, Massachusetts had the lowest infant mortality rate, while Mississippi had the highest in 2022. Overall, the number of neonatal and post neonatal deaths in the United States has been steadily decreasing since 1995.

UNICEF's country profile for Indonesia, including under-five mortality rates, child health, education and sanitation data.

"Infant mortality is the death of an infant before his or her first birthday. The infant mortality rate is the number of infant deaths for every 1,000 live births. In addition to giving us key information about maternal and infant health, the infant mortality rate is an important marker of the overall health of a society. In 2017, the infant mortality rate in the United States was 5.8 deaths per 1,000 live births." For more information, see the US CDC website.Estimates developed by the UN Inter-agency Group for Child Mortality Estimation ( UNICEF, WHO, World Bank, UN DESA Population Division )
Infant Mortality source: World Bank. See: https://data.worldbank.org/indicator/SP.DYN.IMRT.IN

UNICEF's country profile for Argentina, including under-five mortality rates, child health, education and sanitation data.

This layer contains population counts and 10 indicators of global population and maternal health by country. Layer is rendered to show the percent of married women ages 15-49 using any contraception. Data is from Population Reference Bureau's 2017 World Population Data Sheet or from their DataFinder site. Fields included are:Population, mid-2017 (reported in millions)Percent of Population Ages <15Percent of Population Ages 65+Male Life Expectancy at BirthFemale Life Expectancy at BirthTotal Fertility Rate: Children per WomanInfant Mortality Rate: Infant Deaths per 1,000 BirthsMaternal Mortality Rate: Maternal Deaths per 100,000 Births (from DataFinder, data from 2013)% Births Attended by Skilled Health Personnel (from DataFinder, year of most recent data available is different for each country, oldest is 2011)% Married Women Ages 15-49 Using Modern Contraception*% Married Women Ages 15-49 Using Any Contraception**Null values indicate that data is not available.*Modern methods include anything that requires supplies or trips to a clinic: condom, pill, injection, IUD, sterilization, etc.**Any method includes modern methods as well as abstinence, fertility awareness/cycle beads, withdrawal, and any other methods that do not require supplies or clinics.For detailed definitions, sources, and footnotes, see page 20 of PRB's 2017 World Population Data Sheet and PRB's DataFinder site.

In 2022, the state of Mississippi had the highest infant mortality rate in the United States, with around 9.11 deaths per 1,000 live births. Infant mortality is the death of an infant before the age of one. The countries with the lowest infant mortality rates worldwide are Slovenia, Singapore, and Iceland. The countries with the highest infant mortality rates include Afghanistan, Somalia, and the Central African Republic. Causes of infant mortality Rates and causes of infant mortality are different depending on the country and region. However, the leading causes of neonatal deaths include preterm birth complications, intrapartum-related events, and sepsis. The leading causes of death among children aged 1 to 59 months are pneumonia, diarrhea, and injury. In the United States The infant mortality rate in the United States has decreased over the past few decades, reaching a low of 5.4 deaths per 1,000 live births in 2021. The most common causes of infant death in the United States are congenital malformations, low birth weight, and sudden infant death syndrome. In 2022, congenital malformations accounted for around 108 infant deaths per 100,000 live births.

The number of maternal deaths and maternal mortality rates for selected causes, 2000 to most recent year.

This data package contains mortality and morbidity estimates for adult, maternal, and child mortalities as well as mortalities from diseases like malaria and breast and cervical cancer.

Thailand infant mortality rate for 2025 is 6.36, a 2.37% decline from 2024.

<ul style='margin-top:20px;'>

<li>Thailand infant mortality rate for 2024 was <strong>6.51</strong>, a <strong>2.31% decline</strong> from 2023.</li>
<li>Thailand infant mortality rate for 2023 was <strong>6.67</strong>, a <strong>3.15% decline</strong> from 2022.</li>
<li>Thailand infant mortality rate for 2022 was <strong>6.88</strong>, a <strong>3.07% decline</strong> from 2021.</li>
</ul>Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given year.

UNICEF's country profile for Mali, including under-five mortality rates, child health, education and sanitation data.

Malaysia Maternal Mortality Rate: per 1000 Persons data was reported at 0.200 NA in 2013. This stayed constant from the previous number of 0.200 NA for 2012. Malaysia Maternal Mortality Rate: per 1000 Persons data is updated yearly, averaging 0.800 NA from Dec 1938 (Median) to 2013, with 76 observations. The data reached an all-time high of 10.800 NA in 1938 and a record low of 0.200 NA in 2013. Malaysia Maternal Mortality Rate: per 1000 Persons data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Malaysia – Table MY.G008: Vital Statistics: Infant Mortality & Mortality Rate. 1933 - 1962 : Peninsular Malaysia1963 - Onwards : Malaysia

UNICEF's country profile for Niger, including under-five mortality rates, child health, education and sanitation data.

Between 2020 and 2025, Pakistan had the highest infant mortality rate throughout South Asia, with an estimated ** infant deaths for every one thousand live births. Comparatively, there were **** infant deaths for every one thousand live births in the Maldives between 2020 to 2025.

Abstract

The Government of The Gambia has always been committed to the “Health for All” year 2000 and beyond Alma Ata Declaration (1978) as well as other conventions such as the 1987 Global Conference on Safe Motherhood, the 1990 Convention on the Rights of the Child and the 1994 ICPD-Cairo Plan of Action, amongst others. A unique recommendation from all these conventions was the reduction of maternal mortality by half by the year 2000 and the provision of a comprehensive reproductive health programme using the life cycle approach from birth to death.

The 1987 conference on safe motherhood brought about increased awareness in the health sector on the issue of maternal mortality following which the “sisterhood” method of estimating levels of maternal mortality was first tested in The Gambia in 1987. This field test was done by the MRC field station located in one of the rural divisions of The Gambia and a total of 90 maternal deaths were identified. The lifetime risk of maternal death was estimated to be higher than one woman in twenty (Greenwood et al.). Subsequently, this revelation by the MRC study sparked a new impetus into the “silent epidemic” of maternal mortality following which the Department of State for Health through its MCH/FP programme commissioned a national survey in 1990. The results, which were quite startling, revealed a maternal mortality level of 1,050 per 100,000 live births nationally. There were variations between urban (600 per 100,000) and rural communities with trained birth attendants (894 per 100,000), and communities without trained birth attendants (1,600 per 100,000).

Recent isolated studies on maternal mortality have suggested a general decline in those areas. However, in the absence of a viable vital registration system in The Gambia, there has been a felt need to conduct another national survey, since the 1990 survey. Furthermore, the Department of State for Health’s proposed shift from MCH/FP service provision into a broad-focussed reproductive health programme also requires the availability of current baseline information and the identification of relevant process indicators, all of which justify the need to establish current levels of mortality and use of contraceptives.

It should be noted that current national policies and programmes continue to refer to data obtained from the 1990 maternal mortality study, the 1990 Gambia contraceptive prevalence and fertility determinants survey as well as the 1993 population and housing census as baseline benchmarks both for programme intervention and implementation. This long period to some extent renders the data quite obsolete and unsuitable for many national and development purposes. A simple compromise has been that of making comprehensive demographic, health and socio-economic projections. However, one important limitation of statistical projections is the period between the time the base data were collected and the time span of the projections. The probable margin of error in making projections with reference periods of eight or more years ago could be so large to warrant the acceptance of such projections within any reasonable statistical intervals.

Since there has been no comprehensive national survey on maternal, infant and child mortality during the past 10 years, and given that it would take a number of years before the final analyses of data obtained from the forthcoming census, it was found prudent to carry out a comprehensive study that would collect information on key reproductive health indicators. Furthermore, the complexity involved in studying maternal mortality compounded by its rarity of occurrence in the general population has necessitated conduction of a specialised study. Such a study would be useful in filling in the data deficiencies and providing baseline data for programme intervention and evaluation, especially in an era of a general shift of emphasis of population programmes from vertical family planning activities in favour of a more generally accepted concept - reproductive health.

Objectives of the survey: a) To establish current levels of maternal, peri-natal, neonatal and infant mortality rates. b) To establish the current levels of contraceptive prevalence rates and barriers to use. c) To elicit how the situation has improved or otherwise during the last ten years. d) Make practical recommendations to Department of State for Health for subsequent and long-term actions required.

Geographic coverage

National.

Analysis unit

• Households
• Women and men (both in child-bearing age)

Universe

The survey covered women age 15 to 49 years old and men age 18 years and over.

Kind of data

Sample survey data [ssd]

Sampling procedure

A multi-stage stratified cluster sampling procedure was used for this study. The country is divided into 41 Districts and each of these districts was identified as a stratum. Stratification by districts increases the efficiency of the sample given the homogeneity of the districts. The sample size for the study was 4000 households and was based on the level of maternal mortality which was estimated at 1050 per 100,000 at the time of the study. According to WHO/UNICEF, 1997 publication on Sisterhood Method in Estimating Maternal Mortality, 4,000 households or less would be adequate for study of maternal mortality if the level of maternal mortality is at least 500 per 100,000.

Based on the Rule of Thumb, a 15 per cent sample of EAs (240) was selected for this study, which is also more than adequate for the study of other variables like contraceptive prevalence, infant mortality, fertility and its determinants. The selection of population elements were done at two stages; a representative sample of 240 Enumeration Areas (EAs) were randomly selected and allocated based on the Probability Proportional to the Size (PPS) of the district using random numbers. The EA is a cluster of settlements with an estimated population of 500 peoples.

A total of 4,000 households were then allocated to the districts with probability proportional to the size of each district. For the 240 selected EAs, a specified number of households were randomly selected for interview using a systematic sampling procedure. A complete listing of selected household members was done and all eligible male and female respondents were interviewed.

Sampling deviation

There were no discrepancies between the sample units obtained and the iniitial planned samples.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey tools included a compound and household schedules, female and male questionnaires. The compound and household schedules were used to collect information on local government area, health division and household number, together with residence, sex, age, education and eligibility status of the household members. The female and male questionnaires were administered to women aged 15-49 years and men aged 18 years and above respectively. The survey instruments were similar to the core modules of the Demographic and Health Survey questionnaires (Macro International), with adaptation to suit The Gambian needs. In addition a review of medical records in the three main hospitals in The Gambia (Royal Victoria Hospital, Farafenni Hospital and Bansang Hospital) was carried out in November 2001 to undertake first-hand assessment of the maternal mortality situation at the major referral facilities.

The Survey team with support and guidance of the Technical Team prepared the survey instruments by adapting the Demographic and Health survey modules. The main instruments for this study are: - Male questionnaire which was used to obtain information from males 18 years and above; - Female questionnaire, which obtained information from females, 15-49 years ; - Household questionnaire contains information on Local Government Area (LGA), Districts and Household numbers.

For each person listed on the household questionnaire, relationship to head of household, age, and sex are recorded.

The female questionnaire contains the following key information: - Respondent's background - Reproduction - Contraception - Marriage - Fertility preferences - Maternal mortality

The male questionnaire on the other hand, contained the following information: - Respondent's background - Contraception - Marriage - Maternal mortality

Response rate

All respondents with missing age were excluded from the model. There were about 15 percent of the responses with missing information on the deaths. Imputations were made to establish whether or not they qualified to be classified as maternal deaths. For instance, those missing sex of the sibling but had correctly answered maternal death-related questions, the sex was taken to be female and therefore included in the maternal mortality model. Responses with no information on the type of maternal death, but had indicated the death as having been as a result of complications of pregnancy or child birth, were imputed to be pregnancy-related. On the other hand, responses on symptoms before death were used to impute the type of death in case it was missing.

Data appraisal

All respondents with missing age were excluded from the model. There were about 15 percent of the responses with missing information on the deaths.

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.