This is a source dataset for a Let's Get Healthy California indicator at https://letsgethealthy.ca.gov/. Infant Mortality is defined as the number of deaths in infants under one year of age per 1,000 live births. Infant mortality is often used as an indicator to measure the health and well-being of a community, because factors affecting the health of entire populations can also impact the mortality rate of infants. Although California’s infant mortality rate is better than the national average, there are significant disparities, with African American babies dying at more than twice the rate of other groups. Data are from the Birth Cohort Files. The infant mortality indicator computed from the birth cohort file comprises birth certificate information on all births that occur in a calendar year (denominator) plus death certificate information linked to the birth certificate for those infants who were born in that year but subsequently died within 12 months of birth (numerator). Studies of infant mortality that are based on information from death certificates alone have been found to underestimate infant death rates for infants of all race/ethnic groups and especially for certain race/ethnic groups, due to problems such as confusion about event registration requirements, incomplete data, and transfers of newborns from one facility to another for medical care. Note there is a separate data table "Infant Mortality by Race/Ethnicity" which is based on death records only, which is more timely but less accurate than the Birth Cohort File. Single year shown to provide state-level data and county totals for the most recent year. Numerator: Infants deaths (under age 1 year). Denominator: Live births occurring to California state residents. Multiple years aggregated to allow for stratification at the county level. For this indicator, race/ethnicity is based on the birth certificate information, which records the race/ethnicity of the mother. The mother can “decline to state”; this is considered to be a valid response. These responses are not displayed on the indicator visualization.

Sources:a National Institute for Population Research and Training, MEASURE Evaluation, International Centre for Diarrhoeal Disease Research (2012) Bangladesh Maternal Mortality and Health Care Survey 2010. Available: http://www.cpc.unc.edu/measure/publications/tr-12-87. Accessed October 15, 2012.b World Health Organization (ND) WHO Maternal Mortality Country Profiles. Available: www.who.int/gho/maternal_health/en/#M. Accessed 1 March 2015.c Lozano R, Wang H, Foreman KJ, Rajaratnam JK, Naghavi M, Marcus JR, et al. (2011) Progress towards Millennium Development Goals 4 and 5 on maternal and child mortality: an updated systematic analysis. Lancet 378(9797): 1139–65. 10.1016/S0140-6736(11)61337-8d UNFPA, UNICEF, WHO, World Bank (2012) Trends in maternal mortality: 1990–2010. Available: http://www.unfpa.org/public/home/publications/pid/10728. Accessed 7 October 2012.e Bangladesh Bureau of Statistics, Statistics Informatics Division, Ministry of Planning (December 2012) Population and Housing Census 2011, Socio-economic and Demographic Report, National Series–Volume 4. Available at: http://203.112.218.66/WebTestApplication/userfiles/Image/BBS/Socio_Economic.pdf. Accessed 15 February, 2015.f Mozambique National Institute of Statistics, U.S. Census Bureau, MEASURE Evaluation, U.S. Centers for Disease Control and Prevention (2012) Mortality in Mozambique: Results from a 2007–2008 Post-Census Mortality Survey. Available: http://www.cpc.unc.edu/measure/publications/tr-11-83. Accessed 6 October 2012.g Ministerio da Saude (MISAU), Instituto Nacional de Estatística (INE) e ICF International (ICFI). Moçambique Inquérito Demográfico e de Saúde 2011. Calverton, Maryland, USA: MISAU, INE e ICFI.h Mudenda SS, Kamocha S, Mswia R, Conkling M, Sikanyiti P, et al. (2011) Feasibility of using a World Health Organization-standard methodology for Sample Vital Registration with Verbal Autopsy (SAVVY) to report leading causes of death in Zambia: results of a pilot in four provinces, 2010. Popul Health Metr 9:40. 10.1186/1478-7954-9-40i Central Statistical Office (CSO), Ministry of Health (MOH), Tropical Diseases Research Centre (TDRC), University Teaching Hospital Virology Laboratory, University of Zambia, and ICF International Inc. 2014. Zambia Demographic and Health Survey 2013–14: Preliminary Report. Rockville, Maryland, USA. Available: http://dhsprogram.com/pubs/pdf/PR53/PR53.pdf. Accessed February 26, 2015.j Centers for Disease Control and Prevention (2014) Saving Mothers, Giving Life: Maternal Mortality.Phase 1 Monitoring and Evaluation Report. Atlanta, GA: Centers for Disease Control and Prevention, US Dept of Health and Human Services. Available at: http://www.savingmothersgivinglife.org/doc/Maternal%20Mortality%20(advance%20copy).pdf. Accessed 26 February 2015.k Central Statistical Office (CSO), Ministry of Health (MOH), Tropical Diseases Research Centre (TDRC), University of Zambia, and Macro International Inc. 2009. Zambia Demographic and Health Survey 2007. Calverton, Maryland, USA: CSO and Macro International Inc.Comparison of Maternal Mortality Estimates: Zambia, Bangladesh, Mozambique.

This dataset includes counts of infant births and deaths within Austin city limits by year. The counts are calculated into an infant mortality rate for each year. Both infant deaths and infant births are reported through the Office of Vital Records.

View more details and insights related to this data set on the story page: https://data.austintexas.gov/stories/s/HE-B-3-Infant-mortality-rate-number-of-deaths-of-i/jwg4-2djc/

The number of infant deaths (babies under one year of age) per 1,000 live births within the area in a five year period. This is the most stable and commonly measured indicator of mortality in this age group. Source: Baltimore City Health Department Years Available: 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018

This table contains details about infant mortality in in King County. It has been developed for the Determinant of Equity - Health and Human Services. It includes information about Infant Mortality equity indicator. Fields describe all live births during the time period (Denominator), number of infants who die before their first birthday (Numerator), the type of equity indicator being measured (Indicator), and the value that describes this measurement (Indicator Value).The data was compiled by the Washington State Department of Health (DOH), Center for Health Statistics.Fetal and Infant Death DataFor more information about King County's equity efforts, please see:Equity, Racial & Social Justice VisionOrdinance 16948 describing the determinates of equityDeterminants of Equity and Data Tool

This thesis studies the effect of US wheat aid on infant mortality rates in developing countries. There is debate on the effectiveness of US food aid; some claim it disrupts local food production, while others discuss its role in prolonging conflict. This paper aims to address the intended impact of food aid, feeding people, rather than unintended impacts tackled by previous studies. Infant mortality rates serve as a measure of the health of pregnant woman and infants, who make up a vulnerable population that is susceptible to food crises. An instrumental variable approach is taken, which uses lagged US wheat production, a country’s tendency to receive any US food aid, a rainshock variable, population, and a measure of intrastate conflict, to determine the impact of wheat aid on infant mortality rates in recipient countries. As shown by the results, infant mortality rates decrease with more US wheat aid, which is conducive to the goals of food aid set out by USAID. Specifically, a 100% increase in US food aid, decreases infant mortality rates by 19.3 deaths per 1,000 live births. Furthermore, the effect of US wheat aid on infant mortality rates is strongest in countries that are more likely to receive aid compared to those with a below average propensity to receive US food aid.

BackgroundLike many developing countries, Mali has few sources of mortality data. High quality mortality estimates are available from household surveys, such as the demographic and health surveys (DHS), approximately every five years, making it difficult to track progress in reducing mortality. The Rapid Mortality Monitoring (RMM) project in Mali aimed to address this issue by testing a community-based approach to measuring under-five mortality on a yearly basis.Methods and FindingsSeventy-eight community-based workers (relais) were identified in 20 villages comprising approximately 5,300 households. The relais reported pregnancies, births, and under-five deaths from July, 2012 to November, 2013. Data were double-entered, reconciled, cleaned, and analyzed monthly. In November-December 2013, we administered a full pregnancy history (FPH) to women of reproductive age in a census of the households in the project villages. We assessed the completeness of the counts of births and deaths, and the validity of under-five, infant, and neonatal mortality rates from the community-based method against the retrospective FPH for two rolling twelve-month periods. Monthly reporting by relais was high, with reports on pregnancies, births, and deaths consistently provided from all 78 relais catchment areas. Relais reported 1,660 live births and 276 under-five deaths from July, 2012 to November, 2013. The under-five mortality rate calculated from the relais data was similar to that estimated using the validation survey, where the overall ratios of the community-based to FPH-based mortality rates for the reporting periods were 100.4 (95% CI: 80.4, 120.5) and 100.8 (95% CI: 79.5, 122.0).ConclusionsOn a small scale, the community-based method in Mali produced estimates of annualized under-five mortality rates that were consistent with those obtained from a FPH. The community-based method should be considered for scale-up in Mali, with appropriate measures to ensure community engagement, data quality, and cross-validation with comparable FPHs.

Infant mortality rate is number of infant deaths per 1,000 live births. Data are for Santa Clara County residents. The measure is summarized for total county population, by race/ethnicity and Asian/Pacific Islander subgroups. Data are presented for single years at county level and pooled years combined for population subgroups. Source: Santa Clara County Public Health Department, 2007-2015 Birth Statistical Master File; Santa Clara County Public Health Department, VRBIS, 2007-2015. Data as of 05/26/2017.METADATA:Notes (String): Lists table title, sourceYear (String): Year of death. Pooled data years are used for certain categories to meet the minimum data requirements.Category (String): Lists the category representing the data: Santa Clara County is for total population, race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only), and Asian/Pacific Islander subgroups: Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese and Pacific Islanders.Rate per 1,000 live births (Numeric): Infant mortality rate is number of infant (under the age of 1 year) deaths in a year per 1,000 live births in the same time period.

Abstract

The 1993 Turkish Demographic and Health Survey (TDHS) is a nationally representative survey of ever-married women less than 50 years old. The survey was designed to provide information on fertility levels and trends, infant and child mortality, family planning, and maternal and child health. The TDHS was conducted by the Hacettepe University Institute of Population Studies under a subcontract through an agreement between the General Directorate of Mother and Child Health and Family Planning, Ministry of Health and Macro International Inc. of Calverton, Maryland. Fieldwork was conducted from August to October 1993. Interviews were carried out in 8,619 households and with 6,519 women.

The Turkish Demographic and Health Survey (TDHS) is a national sample survey of ever-married women of reproductive ages, designed to collect data on fertility, marriage patterns, family planning, early age mortality, socioeconomic characteristics, breastfeeding, immunisation of children, treatment of children during episodes of illness, and nutritional status of women and children. The TDHS, as part of the international DHS project, is also the latest survey in a series of national-level population and health surveys in Turkey, which have been conducted by the Institute of Population Studies, Haeettepe University (HIPS).

More specifically, the objectives of the TDHS are to:

Collect data at the national level that will allow the calculation of demographic rates, particularly fertility and childhood mortality rates; Analyse the direct and indirect factors that determine levels and trends in fertility and childhood mortality; Measure the level of contraceptive knowledge and practice by method, region, and urban- rural residence; Collect data on mother and child health, including immunisations, prevalence and treatment of diarrhoea, acute respiratory infections among children under five, antenatal care, assistance at delivery, and breastfeeding; Measure the nutritional status of children under five and of their mothers using anthropometric measurements.

The TDHS information is intended to assist policy makers and administrators in evaluating existing programs and in designing new strategies for improving family planning and health services in Turkey.

MAIN RESULTS

Fertility in Turkey is continuing to decline. If Turkish women maintain current fertility rates during their reproductive years, they can expect to have all average of 2.7 children by the end of their reproductive years. The highest fertility rate is observed for the age group 20-24. There are marked regional differences in fertility rates, ranging from 4.4 children per woman in the East to 2.0 children per woman in the West. Fertility also varies widely by urban-rural residence and by education level. A woman living in rural areas will have almost one child more than a woman living in an urban area. Women who have no education have almost one child more than women who have a primary-level education and 2.5 children more than women with secondary-level education.

The first requirement of success ill family planning is the knowledge of family planning methods. Knowledge of any method is almost universal among Turkish women and almost all those who know a method also know the source of the method. Eighty percent of currently married women have used a method sometime in their life. One third of currently married women report ever using the IUD. Overall, 63 percent of currently married women are currently using a method. The majority of these women are modern method users (35 percent), but a very substantial proportion use traditional methods (28 percent). the IUD is the most commonly used modern method (I 9 percent), allowed by the condom (7 percent) and the pill (5 percent). Regional differences are substantial. The level of current use is 42 percent in tile East, 72 percent in tile West and more than 60 percent in tile other three regions. "File common complaints about tile methods are side effects and health concerns; these are especially prevalent for the pill and IUD.

One of the major child health indicators is immunisation coverage. Among children age 12-23 months, the coverage rates for BCG and the first two doses of DPT and polio were about 90 percent, with most of the children receiving those vaccines before age one. The results indicate that 65 percent of the children had received all vaccinations at some time before the survey. On a regional basis, coverage is significantly lower in the Eastern region (41 percent), followed by the Northern and Central regions (61 percent and 65 percent, respectively). Acute respiratory infections (ARI) and diarrhea are the two most prevalent diseases of children under age five in Turkey. In the two weeks preceding the survey, the prevalence of ARI was 12 percent and the prevalence of diarrhea was 25 percent for children under age five. Among children with diarrhea 56 percent were given more fluids than usual.

Breastfeeding in Turkey is widespread. Almost all Turkish children (95 percent) are breastfed for some period of time. The median duration of breastfeeding is 12 months, but supplementary foods and liquids are introduced at an early age. One-third of children are being given supplementary food as early as one month of age and by the age of 2-3 months, half of the children are already being given supplementary foods or liquids.

By age five, almost one-filth of children arc stunted (short for their age), compared to an international reference population. Stunting is more prevalent in rural areas, in the East, among children of mothers with little or no education, among children who are of higher birth order, and among those born less than 24 months after a prior birth. Overall, wasting is not a problem. Two percent of children are wasted (thin for their height), and I I percent of children under five are underweight for their age. The survey results show that obesity is d problem among mothers. According to Body Mass Index (BMI) calculations, 51 percent of mothers are overweight, of which 19 percent are obese.

Geographic coverage

The Turkish Demographic and Health Survey (TDHS) is a national sample survey.

Analysis unit

• Household
• Women age 12-49
• Children under five

Universe

The population covered by the 1993 DHS is defined as the universe of all ever-married women age 12-49 who were present in the household on the night before the interview were eligible for the survey.

Kind of data

Sample survey data

Sampling procedure

The sample for the TDHS was designed to provide estimates of population and health indicators, including fertility and mortality rates for the nation as a whole, fOr urban and rural areas, and for the five major regions of the country. A weighted, multistage, stratified cluster sampling approach was used in the selection of the TDHS sample.

Sample selection was undertaken in three stages. The sampling units at the first stage were settlements that differed in population size. The frame for the selection of the primary sampling units (PSUs) was prepared using the results of the 1990 Population Census. The urban frame included provinces and district centres and settlements with populations of more than 10,000; the rural frame included subdistricts and villages with populations of less than 10,000. Adjustments were made to consider the growth in some areas right up to survey time. In addition to the rural-urban and regional stratifications, settlements were classified in seven groups according to population size.

The second stage of selection involved the list of quarters (administrative divisions of varying size) for each urban settlement, provided by the State Institute of Statistics (SIS). Every selected quarter was subdivided according tothe number of divisions(approximately 100 households)assigned to it. In rural areas, a selected village was taken as a single quarter, and wherever necessary, it was divided into subdivisions of approximately 100 households. In cases where the number of households in a selected village was less than 100 households, the nearest village was selected to complete the 100 households during the listing activity, which is described below.

After the selection of the secondary sampling units (SSUs), a household listing was obtained for each by the TDHS listing teams. The listing activity was carried out in May and June. From the household lists, a systematic random sample of households was chosen for the TDHS. All ever-married women age 12-49 who were present in the household on the night before the interview were eligible for the survey.

Mode of data collection

Face-to-face

Research instrument

Two questionnaires were used in the main fieldwork for the TDHS: the Household Questionnaire and the Individual Questionnaire for ever-married women of reproductive age. The questionnaires were based on the model survey instruments developed in the DHS program and on the questionnaires that had been employed in previous Turkish population and health surveys. The questionnaires were adapted to obtain data needed for program planning in Turkey during consultations with population and health agencies. Both questionnaires were developed in English and translated into Turkish.

a) The Household Questionnaire was used to enumerate all usual members of and visitors to the selected households and to collect information relating to the socioeconomic position of the households. In the first part of the Household Questionnaire, basic information was collected on the age, sex, educational attainment, marital status and relationship to the head of household for each person listed as a household member

In 2020, the highest COVID-19 pandemic-related excess mortality rate was among older Hispanics. “Excess deaths” represent the number of deaths beyond what is expected in a typical year. This measure illustrates the mortality directly or indirectly associated with the COVID-19 pandemic. This statistic presents COVID-19 pandemic-related excess mortality rates in the U.S. in 2020, by age group and ethnicity.

Years of life lost due to mortality from all causes (ICD-10 A00-Y99). Years of life lost (YLL) is a measure of premature mortality. Its primary purpose is to compare the relative importance of different causes of premature death within a particular population and it can therefore be used by health planners to define priorities for the prevention of such deaths. It can also be used to compare the premature mortality experience of different populations for a particular cause of death. The concept of years of life lost is to estimate the length of time a person would have lived had they not died prematurely. By inherently including the age at which the death occurs, rather than just the fact of its occurrence, the calculation is an attempt to better quantify the burden, or impact, on society from the specified cause of mortality. Legacy unique identifier: P00331

Avoidable mortality covers both preventable and treatable causes of mortality. Preventable mortality refers to mortality that can mainly be avoided through effective public health and primary prevention interventions (i.e. before the onset of diseases/injuries, to reduce incidence). Treatable mortality can mainly be avoided through timely and effective health care interventions, including secondary prevention and treatment (after the onset of diseases to reduce case-fatality). The total avoidable mortality includes a number of infectious diseases, several types of cancers, endocrine and metabolic diseases, as well as some diseases of the nervous, circulatory, respiratory, digestive, genitourinary systems, some diseases related to pregnancy, childbirth and the perinatal period, a number of congenital malformations, adverse effects of medical and surgical care, a list of injuries and alcohol and drug related disorders. The data are presented as standardised death rates, meaning they are adjusted to a standard age distribution in order to measure death rates independently of different age structures of populations. This approach improves comparability over time and between countries. The standardised death rates used here are calculated on the basis of the standard European population. Copyright notice and free re-use of data on: https://ec.europa.eu/eurostat/about-us/policies/copyright

The indicator measures the standardised death rate of homicide and injuries inflicted by another person with the intent to injure or kill by any means, including ‘late effects’ from assault (International Classification of Diseases (ICD) codes X85 to Y09 and Y87.1). It does not include deaths due to legal interventions or war (ICD codes Y35 and Y36). The rate is calculated by dividing the number of people dying due to homicide or assault by the total population. Data on causes of death (COD) refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. The data are presented as standardised death rates, meaning they are adjusted to a standard age distribution in order to measure death rates independently of different age structures of populations. This approach improves comparability over time and between countries. The standardised death rates used here are calculated on the basis of the standard European population referring to the residents of the countries.

In 2020, the infant mortality rate in the Indian union territory of Daman and Diu was 16 deaths per 1,000 live births. Infant mortality is measured by the number of deaths of children under one year of age per 1,000 live births.

SNP genotypes of naturally established seedlings in Pinus pinaster at Fuencaliente (Ciudad Real, Spain)One column per individual genotype, comprising 356 diploid SNP loci. The two alleles at each locus are listed together in one column. Missing data coded with hyphens. Seedling samples collected in the field where found over the entire population at three sequential times: "R1" (November 2010), "R2" (March 2011) and "R3" (July 2011). DNA extracted with Invisorb DNA Plant HTS 96 Kit. Genotyped with an oligo pool assay including a selection of 384 SNPs using the Illumina VeraCode platform (see Table S2 in Budde et al. 2014 New Phytologist 201:230-241 for details about the assay and the candidate genes involved).Ppinaster_seedlings_Fuencaliente_SNPs.csvC++ code of the SGCS computer program to infer viability selection coefficients using sequential random genotypic samples drawn from a genetic cohort mortality studyThe SGCS program implements a quasi-exact neutrality test and a Bayesian met...

BackgroundThe global COVID-19 pandemic confronts people with their fragility, vulnerability, and mortality. To date, scales to measure death awareness mainly focus on the anxiety-provoking aspect of mortality cues. This study aims to cross-culturally adapt and validate the Death Reflection Scale (DRS), a scale for measuring positive, growth-oriented cognitions of life reflection and prosocial behavior following confrontation with the finiteness of life.Materials and MethodsThe Death Reflection Scale was translated and adapted in a multi-step process to the German language. In this anonymous, cross-sectional, online survey at a large university in Germany, students, healthcare professionals (HCP) and other staff completed the DRS alongside comparison measures. Multi-group confirmatory factor analysis was used to assess configural, metric, and scalar measurement equivalence across four age and occupational groups. Convergent/divergent validity testing was done via Spearman correlations.Results1,703 participants provided data for a response rate of ∼5%. 24% of respondents were HCP, 22% students. Confirmatory factor analysis showed a higher-order structure of the DRS with a strong general factor and the originally proposed five subscales (CFI 0.945, SRMR 0.045, RMSEA 0.055). Multi-group CFA showed partial metric equivalence across age groups and partial scalar invariance across occupational groups. Non-invariant scales were the Motivation to live, Putting life into perspective, and Legacy subscales. In the convergent validity testing, two hypotheses were fully confirmed, two partially and four were not confirmed. Experiencing a propensity for increased contemplation and life reflection during the pandemic together with spirituality showed correlations of moderate to large size to the DRS and its subscales (Spearman’s rho ranging from 0.31 to 0.52).ConclusionFurther conceptual work for death awareness to explore the construct’s stability in different population groups needs to be undertaken. However, the DRS can be mostly used to assess positive and growth-oriented aspects of death awareness and death reflection which may be an important avenue when developing counseling and support interventions for groups experiencing a high burden during the pandemic.

In 2020, the infant mortality rate in the state of Odisha in India was 36 deaths per 1,000 live births. Infant mortality is measured by the number of deaths of children under one year of age per 1,000 live births.

Deaths were determined to be COVID-associated if they met the Department of Public Health's surveillance definition at the time of death.The cumulative COVID-19 mortality rate can be used to measure the most severe impacts of COVID-19 in a community. There have been documented inequities in COVID-19 mortality rates by demographic and geographic factors. Black and Brown residents, seniors, and those living in areas with higher rates of poverty have all been disproportionally impacted.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

Years of life lost due to mortality from breast cancer (ICD-10 C50). Years of life lost (YLL) is a measure of premature mortality. Its primary purpose is to compare the relative importance of different causes of premature death within a particular population and it can therefore be used by health planners to define priorities for the prevention of such deaths. It can also be used to compare the premature mortality experience of different populations for a particular cause of death. The concept of years of life lost is to estimate the length of time a person would have lived had they not died prematurely. By inherently including the age at which the death occurs, rather than just the fact of its occurrence, the calculation is an attempt to better quantify the burden, or impact, on society from the specified cause of mortality. Legacy unique identifier: P00164