Germany DE: Cause of Death: by Non-Communicable Diseases: % of Total data was reported at 90.598 % in 2019. This records a decrease from the previous number of 91.046 % for 2015. Germany DE: Cause of Death: by Non-Communicable Diseases: % of Total data is updated yearly, averaging 91.273 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 91.869 % in 2000 and a record low of 90.598 % in 2019. Germany DE: Cause of Death: by Non-Communicable Diseases: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Non-communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.;Derived based on the data from Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization; 2020. Link: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death;Weighted average;

Bangladesh BD: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data was reported at 22.613 % in 2019. This records a decrease from the previous number of 28.808 % for 2015. Bangladesh BD: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data is updated yearly, averaging 30.893 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 50.247 % in 2000 and a record low of 22.613 % in 2019. Bangladesh BD: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bangladesh – Table BD.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Communicable diseases and maternal, prenatal and nutrition conditions include infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.;Derived based on the data from Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization; 2020. Link: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death;Weighted average;

WHO’s Global Health Estimates (GHE) provide the latest available data on death and disability globally, by region and country, and by age, sex and cause. The latest updates include global, regional and country trends from 2000 to 2019 inclusive. By providing key insights on mortality and morbidity trends, these estimates are a powerful tool to support informed decision-making on health policy and resource allocation.

The next update to these estimates will include an assessment of the direct and indirect impact of the COVID-19 pandemic on mortality and morbidity. The Global Health Estimates data can be accessed, analysed and used through a variety of different channels and mediums. These include an interactive visual summary of global and regional data; data visualization in the Global Health Observatory filtered by country, year, age and sex; key trends by country income group; and downloadable files of the complete data sets.

Context

Top 25 Economies 2021 latest country-level estimates of cause-specific disability-adjusted life year (DALYs), and Deaths for the year 2000, 2010, 2015 and 2019 from World Health Organization.

Content

This dataset from World Health Organization contains The latest country-level estimates of cause-specific disability-adjusted life year (DALYs), and Deaths for the year 2000, 2010, 2015 and 2019 from World Health Organization.

The burden of disease is calculated using the disability-adjusted life year (DALY). One DALY represents the loss of the equivalent of one year of full health. DALYs for a disease or health condition are the sum of years of life lost due to premature mortality (YLLs) and years of healthy life lost due to disability (YLDs) due to prevalent cases of the disease or health condition in a population.

I have used a web scraper to scrape the data from WHO site. The original dataset had data for more than 180 countries, but due to memory restrictions, I have downloaded the dataset for the worlds Top 25 Economies 2021.

Following are the columns in the dataset:

• COUNTRY_CODE : The ISO 3166-1 alpha-3 country code
• COUNTRY : The country name
• GHE_CAUSE_CODE : Code for the condition/disease
• GHE_CAUSE_TYPE : Type of the disease/condition
• GHE_CAUSE_TITLE : Title for the condition/disease
• YEAR : Reporting year
• SEX_CODE : Sex of the population for the corresponding age group for the reporting year
• AGEGROUP_CODE : Age group of the population for the corresponding sex for the reporting year
• POPULATION : Total number of people in corresponding age group and sex for the reporting year
• DEATHS : Total deaths occurred within the corresponding age group and sex for the reporting year due to the corresponding condition/disease
• DEATHS_RATE : Death rate corresponding to the POPULATION due to the corresponding condition/disease
• DEATHS_100K : Death rate per 100K POPULATION due to the corresponding condition/disease
• DALY : DALY value within the corresponding age group and sex for the reporting year due to the corresponding condition/disease
• DALY_RATE : DALY rate corresponding to the POPULATION due to the corresponding condition/disease
• DALY_100K : DALY rate per 100K POPULATION due to the corresponding condition/disease

Acknowledgements

This dataset and further information on the topic can be found at WHO website.

Inspiration

The goal is to analyze and interpret the results across multiple variables and find interesting observations, co-relations or patterns.

This dataset is a more different and reliable version to KumarRajarshi's Life Expectancy (WHO) dataset - where some of his values and methods can be questioned.

Context All of the data in this dataset is compiled and downloaded from the Global Health Observatory (GHO) – which is a public health data repository established by the World Health Organisation (WHO). This makes the dataset very reliable and valid.

Challenges - Perform EDA to explore factors that affect life expectancy? - Produce a model to predict life expectancy?

Dataset Contents Life Expectancy from birth: - https://www.who.int/data/gho/data/indicators/indicator-details/GHO/life-expectancy-at-birth-(years)

Mean BMI (kg/m²) (crude estimate): - https://www.who.int/data/gho/data/indicators/indicator-details/GHO/mean-bmi-(kg-m-)-(crude-estimate)

Alcohol, total per capita (15+) consumption (in litres of pure alcohol): - https://www.who.int/data/gho/data/indicators/indicator-details/GHO/total-(recorded-unrecorded)-alcohol-per-capita-(15-)-consumption

The rest of the factors: - https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death (BY COUNTRY, Summary tables of mortality estimates by cause, age and sex, by country, 2000–2019, Number of Deaths [2000, 2010, 2015, 2019]). All of the values are crude estimates number of deaths per 1000.

I did this so you don't have to!

Data Collected: March 2023

Belarus BY: Cause of Death: by Injury: % of Total data was reported at 5.715 % in 2019. This records a decrease from the previous number of 6.403 % for 2015. Belarus BY: Cause of Death: by Injury: % of Total data is updated yearly, averaging 7.563 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 10.286 % in 2000 and a record low of 5.715 % in 2019. Belarus BY: Cause of Death: by Injury: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Belarus – Table BY.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Injuries include unintentional and intentional injuries.;Derived based on the data from Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization; 2020. Link: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death;Weighted average;

Hello, my data set is entitled "Akyildiz Causes of death in Germany for both sexes aged all ages (2019)" and I generated it on the following WHO (World Health Organization) website: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death The data set lists the reasons for death in 2019 and is filtered for the following factors: a: Country - Germany b: Year -2019 c: Gender - male and female d: Age group - everyone Link dataset: https://docs.google.com/spreadsheets/d/1FoIj-D-d3ObpPZYWT_FE2VhR7XN8SYBh/edit?usp=drive_link&ouid=102863814638990452957&rtpof=true&sd=true

Bolivia BO: Cause of Death: by Non-Communicable Diseases: % of Total data was reported at 72.676 % in 2019. This records an increase from the previous number of 70.254 % for 2015. Bolivia BO: Cause of Death: by Non-Communicable Diseases: % of Total data is updated yearly, averaging 67.435 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 72.676 % in 2019 and a record low of 53.198 % in 2000. Bolivia BO: Cause of Death: by Non-Communicable Diseases: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bolivia – Table BO.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Non-communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.;Derived based on the data from Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization; 2020. Link: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death;Weighted average;

Germany DE: Cause of Death: by Injury: % of Total data was reported at 4.642 % in 2019. This records an increase from the previous number of 3.947 % for 2015. Germany DE: Cause of Death: by Injury: % of Total data is updated yearly, averaging 4.032 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 4.642 % in 2019 and a record low of 3.868 % in 2010. Germany DE: Cause of Death: by Injury: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Injuries include unintentional and intentional injuries.;Derived based on the data from Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization; 2020. Link: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death;Weighted average;

In 2019, 80% of the 7.4 million global child deaths occurred in low- and middle-income countries (LMICs). Global and regional estimates of cause of hospital death and admission in LMIC children are needed to guide global and local priority setting and resource allocation but are currently lacking. The study objective was to estimate global and regional prevalence for common causes of pediatric hospital mortality and admission in LMICs. We performed a systematic review and meta-analysis to identify LMIC observational studies published January 1, 2005-February 26, 2021. Eligible studies included: a general pediatric admission population, a cause of admission or death, and total admissions. We excluded studies with data before 2,000 or without a full text. Two authors independently screened and extracted data. We performed methodological assessment using domains adapted from the Quality in Prognosis Studies tool. Data were pooled using random-effects models where possible. We reported prevalence as a proportion of cause of death or admission per 1,000 admissions with 95% confidence intervals (95% CI). Our search identified 29,637 texts. After duplicate removal and screening, we analyzed 253 studies representing 21.8 million pediatric hospitalizations in 59 LMICs. All-cause pediatric hospital mortality was 4.1% [95% CI 3.4%–4.7%]. The most common causes of mortality (deaths/1,000 admissions) were infectious [12 (95% CI 9–14)]; respiratory [9 (95% CI 5–13)]; and gastrointestinal [9 (95% CI 6–11)]. Common causes of admission (cases/1,000 admissions) were respiratory [255 (95% CI 231–280)]; infectious [214 (95% CI 193–234)]; and gastrointestinal [166 (95% CI 143–190)]. We observed regional variation in estimates. Pediatric hospital mortality remains high in LMICs. Global child health efforts must include measures to reduce hospital mortality including basic emergency and critical care services tailored to the local disease burden. Resources are urgently needed to promote equity in child health research, support researchers, and collect high-quality data in LMICs to further guide priority setting and resource allocation.

Определение: Уровень смертности от сердечно-сосудистых заболеваний, рака, диабета или хронических респираторных заболеваний. Вероятность смерти в возрасте от 30 до 70 лет от сердечно-сосудистых заболеваний, рака, диабета или хронических респираторных заболеваний, определяемая как процент 30-летних людей, которые умрут до своего 70-летия от сердечно-сосудистых заболеваний, рака, диабета или хронических респираторных заболеваний, при условии, что они/у него были бы текущие показатели смертности в любом возрасте, и он/она не умер бы ни от какой другой причины смерти (например, от травм или ВИЧ/СПИДа). Этот показатель рассчитывается с использованием методов таблицы продолжительности жизни (более подробную информацию смотрите в разделе 3.3). [Переведено с en: английского языка] Тематическая область: Цели в области устойчивого развития [Переведено с en: английского языка] Область применения: ПОКАЗАТЕЛЬ 3.4.1 Уровень смертности от сердечно-сосудистых заболеваний, рака, диабета или хронических респираторных заболеваний [Переведено с en: английского языка] Единица измерения: Номер [Переведено с en: английского языка] Источник данных: Оценки глобального здравоохранения на 2019 год: Смертность в разбивке по причинам, возрасту, полу, странам и регионам, 2000-2019 гг. Женева, Всемирная организация здравоохранения, 2020 г. [Переведено с es: испанского языка] Последнее обновление: Jan 8 2024 1:20AM Организация-источник: Глобальная база данных Организации Объединенных Наций по ЦУР [Переведено с en: английского языка] Definition: Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease. Probability of dying between the ages of 30 and 70 years from cardiovascular diseases, cancer, diabetes or chronic respiratory diseases, defined as the per cent of 30-year-old-people who would die before their 70th birthday from cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS). This indicator is calculated using life table methods (see further details in section 3.3). Thematic Area: Sustainable Development Goals Application Area: INDICATOR 3.4.1 Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease Unit of Measurement: Number Data Source: Global Health Estimates 2019: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization, 2020 Last Update: Jan 8 2024 1:20AM Source Organization: United Nations Global SDG Database

Colombia CO: Cause of Death: by Injury: % of Total data was reported at 14.015 % in 2019. This records a decrease from the previous number of 16.221 % for 2015. Colombia CO: Cause of Death: by Injury: % of Total data is updated yearly, averaging 18.432 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 27.795 % in 2000 and a record low of 14.015 % in 2019. Colombia CO: Cause of Death: by Injury: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Injuries include unintentional and intentional injuries.;Derived based on the data from Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization; 2020. Link: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death;Weighted average;

BackgroundEstimating and analyzing trends and patterns of health loss are essential to promote efficient resource allocation and improve Peru’s healthcare system performance.MethodsUsing estimates from the Global Burden of Disease (GBD), Injuries, and Risk Factors Study (2019), we assessed mortality and disability in Peru from 1990 to 2019. We report demographic and epidemiologic trends in terms of population, life expectancy at birth (LE), mortality, incidence, prevalence, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) caused by the major diseases and risk factors in Peru. Finally, we compared Peru with 16 countries in the Latin American (LA) region.ResultsThe Peruvian population reached 33.9 million inhabitants (49.9% women) in 2019. From 1990 to 2019, LE at birth increased from 69.2 (95% uncertainty interval 67.8–70.3) to 80.3 (77.2–83.2) years. This increase was driven by the decline in under-5 mortality (−80.7%) and mortality from infectious diseases in older age groups (+60 years old). The number of DALYs in 1990 was 9.2 million (8.5–10.1) and reached 7.5 million (6.1–9.0) in 2019. The proportion of DALYs due to non-communicable diseases (NCDs) increased from 38.2% in 1990 to 67.9% in 2019. The all-ages and age-standardized DALYs rates and YLLs rates decreased, but YLDs rates remained constant. In 2019, the leading causes of DALYs were neonatal disorders, lower respiratory infections (LRIs), ischemic heart disease, road injuries, and low back pain. The leading risk factors associated with DALYs in 2019 were undernutrition, high body mass index, high fasting plasma glucose, and air pollution. Before the COVID-19 pandemic, Peru experienced one of the highest LRIs-DALYs rates in the LA region.ConclusionIn the last three decades, Peru experienced significant improvements in LE and child survival and an increase in the burden of NCDs and associated disability. The Peruvian healthcare system must be redesigned to respond to this epidemiological transition. The new design should aim to reduce premature deaths and maintain healthy longevity, focusing on effective coverage and treatment of NCDs and reducing and managing the related disability.

Определение: Коэффициент смертности от самоубийств определяется как число смертей от самоубийств в год, деленное на численность населения и умноженное на 100 000. [Переведено с en: английского языка] Тематическая область: Цели в области устойчивого развития [Переведено с en: английского языка] Область применения: ПОКАЗАТЕЛЬ 3.4.2 Уровень смертности от самоубийств [Переведено с en: английского языка] Единица измерения: Номер [Переведено с en: английского языка] Источник данных: Оценки глобального здравоохранения на 2019 год: Смертность в разбивке по причинам, возрасту, полу, странам и регионам, 2000-2019 гг. Женева, Всемирная организация здравоохранения, 2020 г. [Переведено с es: испанского языка] Последнее обновление: Jan 7 2024 11:14PM Организация-источник: Глобальная база данных Организации Объединенных Наций по ЦУР [Переведено с en: английского языка] Definition: The Suicide mortality rate as defined as the number of suicide deaths in a year, divided by the population, and multiplied by 100 000. Thematic Area: Sustainable Development Goals Application Area: INDICATOR 3.4.2 Suicide mortality rate Unit of Measurement: Number Data Source: Global Health Estimates 2019: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization, 2020 Last Update: Jan 7 2024 11:14PM Source Organization: United Nations Global SDG Database

Argentina AR: Cause of Death: by Injury: % of Total data was reported at 5.709 % in 2019. This records a decrease from the previous number of 6.212 % for 2015. Argentina AR: Cause of Death: by Injury: % of Total data is updated yearly, averaging 6.060 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 6.993 % in 2000 and a record low of 5.709 % in 2019. Argentina AR: Cause of Death: by Injury: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Argentina – Table AR.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Injuries include unintentional and intentional injuries.;Derived based on the data from Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization; 2020. Link: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death;Weighted average;

Belgium BE: Cause of Death: by Injury: % of Total data was reported at 6.121 % in 2019. This records a decrease from the previous number of 6.201 % for 2015. Belgium BE: Cause of Death: by Injury: % of Total data is updated yearly, averaging 6.212 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 6.498 % in 2000 and a record low of 6.121 % in 2019. Belgium BE: Cause of Death: by Injury: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Belgium – Table BE.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Injuries include unintentional and intentional injuries.;Derived based on the data from Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization; 2020. Link: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death;Weighted average;

Определение: Уровень смертности от сердечно-сосудистых заболеваний, рака, диабета или хронических респираторных заболеваний. Вероятность смерти в возрасте от 30 до 70 лет от сердечно-сосудистых заболеваний, рака, диабета или хронических респираторных заболеваний, определяемая как процент 30-летних людей, которые умрут до своего 70-летия от сердечно-сосудистых заболеваний, рака, диабета или хронических респираторных заболеваний, при условии, что они/у него были бы текущие показатели смертности в любом возрасте, и он/она не умер бы ни от какой другой причины смерти (например, от травм или ВИЧ/СПИДа). Этот показатель рассчитывается с использованием методов таблицы продолжительности жизни (более подробную информацию смотрите в разделе 3.3). [Переведено с en: английского языка] Тематическая область: Цели в области устойчивого развития [Переведено с en: английского языка] Область применения: ПОКАЗАТЕЛЬ 3.4.1 Уровень смертности от сердечно-сосудистых заболеваний, рака, диабета или хронических респираторных заболеваний [Переведено с en: английского языка] Единица измерения: Процент [Переведено с en: английского языка] Источник данных: Оценки глобального здравоохранения на 2019 год: Смертность в разбивке по причинам, возрасту, полу, странам и регионам, 2000-2019 гг. Женева, Всемирная организация здравоохранения, 2020 г. [Переведено с es: испанского языка] Последнее обновление: Jan 7 2024 11:08PM Организация-источник: Глобальная база данных Организации Объединенных Наций по ЦУР [Переведено с en: английского языка] Definition: Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease. Probability of dying between the ages of 30 and 70 years from cardiovascular diseases, cancer, diabetes or chronic respiratory diseases, defined as the per cent of 30-year-old-people who would die before their 70th birthday from cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS). This indicator is calculated using life table methods (see further details in section 3.3). Thematic Area: Sustainable Development Goals Application Area: INDICATOR 3.4.1 Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease Unit of Measurement: Percentage Data Source: Global Health Estimates 2019: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization, 2020 Last Update: Jan 7 2024 11:08PM Source Organization: United Nations Global SDG Database

This data presents national-level provisional maternal mortality rates based on a current flow of mortality and natality data in the National Vital Statistics System. Provisional rates which are an early estimate of the number of maternal deaths per 100,000 live births, are shown as of the date specified and may not include all deaths and births that occurred during a given time period (see Technical Notes). A maternal death is the death of a woman while pregnant or within 42 days of termination of pregnancy irrespective of the duration and the site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management, but not from accidental or incidental causes. In this data visualization, maternal deaths are those deaths with an underlying cause of death assigned to International Statistical Classification of Diseases, 10th Revision (ICD-10) code numbers A34, O00–O95, and O98–O99. The provisional data include reported 12 month-ending provisional maternal mortality rates overall, by age, and by race and Hispanic origin. Provisional maternal mortality rates presented in this data visualization are for “12-month ending periods,” defined as the number of maternal deaths per 100,000 live births occurring in the 12-month period ending in the month indicated. For example, the 12-month ending period in June 2020 would include deaths and births occurring from July 1, 2019, through June 30, 2020. Evaluation of trends over time should compare estimates from year to year (June 2020 and June 2021), rather than month to month, to avoid overlapping time periods. In the visualization and in the accompanying data file, rates based on death counts less than 20 are suppressed in accordance with current NCHS standards of reliability for rates. Death counts between 1-9 in the data file are suppressed in accordance with National Center for Health Statistics (NCHS) confidentiality standards. Provisional data presented on this page will be updated on a quarterly basis as additional records are received. Previously released estimates are revised to include data and record updates received since the previous release. As a result, the reliability of estimates for a 12-month period ending with a specific month will improve with each quarterly release and estimates for previous time periods may change as new data and updates are received.

Create maps of U.S. stroke death rates by county. Data can be stratified by age, race/ethnicity, and sex. Visit the CDC/DHDSP Atlas of Heart Disease and Stroke for additional data and maps. Atlas of Heart Disease and StrokeData SourceMortality data were obtained from the National Vital Statistics System. Bridged-Race Postcensal Population Estimates were obtained from the National Center for Health Statistics. International Classification of Diseases, 10th Revision (ICD-10) codes: I60-I69; underlying cause of death.Data DictionaryData for counties with small populations are not displayed when a reliable rate could not be generated. These counties are represented in the data with values of '-1.' CDC/DHDSP excludes these values when classifying the data on a map, indicating those counties as 'Insufficient Data.' Data field names and descriptionsstcty_fips: state FIPS code + county FIPS codeOther fields use the following format: RRR_S_aaaa (e.g., API_M_35UP)   RRR: 3 digits represent race/ethnicity     All - Overall     AIA - American Indian and Alaska Native, non-Hispanic     API - Asian and Pacific Islander, non-Hispanic     BLK - Black, non-Hispanic     HIS - Hispanic     WHT - White, non-Hispanic   S: 1 digit represents sex     A - All    F - Female     M - Male  aaaa: 4 digits represent age. The first 2 digits are the lower bound for age and the last 2 digits are the upper bound for age. 'UP' indicates the data includes the maximum age available and 'LT' indicates ages less than the upper bound.  Example: The column 'BLK_M_65UP' displays rates per 100,000 black men aged 65 years and older.MethodologyRates are calculated using a 3-year average and are age-standardized in 10-year age groups using the 2000 U.S. Standard Population. Rates are calculated and displayed per 100,000 population. Rates were spatially smoothed using a Local Empirical Bayes algorithm to stabilize risk by borrowing information from neighboring geographic areas, making estimates more statistically robust and stable for counties with small populations. Data for counties with small populations are coded as '-1' when a reliable rate could not be generated. County-level rates were generated when the following criteria were met over a 3-year time period within each of the filters (e.g., age, race, and sex).At least one of the following 3 criteria: At least 20 events occurred within the county and its adjacent neighbors.ORAt least 16 events occurred within the county.ORAt least 5,000 population years within the county.AND all 3 of the following criteria:At least 6 population years for each age group used for age adjustment if that age group had 1 or more event.The number of population years in an age group was greater than the number of events.At least 100 population years within the county.More Questions?Interactive Atlas of Heart Disease and StrokeData SourcesStatistical Methods

Data from: Priority setting for global WASH challenges in the age of wastewater-based epidemiological surveillance

https://doi.org/10.5061/dryad.fj6q5742f

A brief summary of dataset contents

Dataset #1: Estimates of mortality due to inadequate water, sanitation, and hygiene (WASH) during the COVID-19 Global Health Emergency

VARIABLES Region = The name for country groupings used by WHO
Age category = All observations have either the value 1 (<5 years) or 5 (all ages) Deaths 2019 due to unsafe WASH point estimate = The point estimate for the number of deaths due to unsafe WASH in 2019, by WHO region, by age category Deaths 2019 due to unsafe WASH upper estimate = The upper bound estimate for the number of deaths due to unsafe WASH in 2019, by WHO region, by age category Deaths 2019 due to unsafe WASH lower estimate = The lower bound estimate for the number of deaths due to unsafe WASH in 2019, by WHO region, by age category Estimated number Jan 3 2020-May 5 20...