The number of deaths caused by heart disease has decreased in the United States from 321.8 per 100,000 population in 1990 to 161.5 deaths per 100,000 population in 2019. Nevertheless, heart disease is still the leading cause of death in the country, followed closely by cancer, which has a mortality rate of 146.2 per 100,000 people.

Heart disease in the U.S.

Diseases of the heart and blood vessels are often associated with atherosclerosis which occurs when plaque builds up along arterial walls. This can limit the flow of blood and can lead to blood clots, a common cause of stroke or heart attacks. Other types of heart disease include arrhythmia (abnormal heart rhythms) and heart valve problems. Many of these diseases can be treated with medication, although many complications will still remain. One of the leading cholesterol lowering drugs in the United States, Crestor, generated around 1.2 billion U.S. dollars of revenue in 2021.

Risk Factors for heart disease There are many risk factors associated with the development of heart disease including family history, ethnicity, and age. However, there are other factors that can be modified through lifestyle changes such as physical inactivity, smoking, and unhealthy diets. Obesity has also been commonly associated with risk factors like hypertension and diabetes type II. In the U.S., some 30 percent of white adults are currently obese.

In 2022, the states with the highest death rates due to heart disease were Oklahoma, Mississippi, and Alabama. That year, there were around 257 deaths due to heart disease per 100,000 population in the state of Oklahoma. In comparison, the overall death rate from heart disease in the United States was 167 per 100,000 population. The leading cause of death in the United States Heart disease is the leading cause of death in the United States, accounting for 21 percent of all deaths in 2022. That year, cancer was the second leading cause of death, followed by unintentional injuries and COVID-19. In the United States, a person has a one in six chance of dying from heart disease. Death rates for heart disease are higher among men than women, but both have seen steady decreases in heart disease death rates since the 1950s. What are risk factors for heart disease? Although heart disease is the leading cause of death in the United States, the risk of heart disease can be decreased by avoiding known risk factors. Some of the leading preventable risk factors for heart disease include smoking, heavy alcohol use, physical inactivity, an unhealthy diet, and being overweight or obese. It is no surprise that the states with the highest rates of death from heart disease are also the states with the highest rates of heart disease risk factors. For example, Oklahoma, the state with the highest heart disease death rate, is also the state with the third-highest rate of obesity. Furthermore, Mississippi is the state with the highest levels of physical inactivity, and it has the second-highest heart disease death rate in the United States.

In 2021, South Korea had the lowest rate of death from ischemic heart disease among OECD countries, with around 28 deaths per 100,000 inhabitants. In comparison, there were around 395 deaths due to ischemic heart disease per 100,000 population in Lithuania. Cardiovascular disease worldwide Fatty deposits accumulating in the inner wall of the coronary artery which restrict blood flow to the heart cause ischemic heart disease (IHD) and can also precipitate heart attacks and strokes. Cardiovascular risk factors such as smoking, heavy alcohol use, and unhealthy diet are more prevalent in Eastern European countries, contributing to a much higher burden of cardiovascular diseases and deaths. In Russia, the general public greatly underestimates the burden of cardiovascular diseases with the actual number of deaths over 40 percent higher than what people estimate. Prevention and intervention Invasive interventions for heart disease can include surgical procedures such as heart bypass surgery- where blood is diverted around clogged parts of major arteries- which ranges in cost around the world. Other medical interventions include the use of prescribed or over-the-counter drugs, such as prescription nitrates or beta blockers, or OTC medications like aspirin. Lifestyle factors to lower blood pressure and cholesterol levels can help decrease risk of heart attacks and other cardiovascular diseases, including maintaining a healthy diet, regular physical activity, and smoking and alcohol cessation.

This layer represents the proportion of deaths in a population due to cardiovascular disease (NCHS 113: Major cardiovascular diseases). The rate represents the age adjusted rate per 100,000 population. A detailed description is available here: https://fortress.wa.gov/doh/wtn/WTNPortal#!q0=821

This layer represents the proportion of deaths in a population due to cardiovascular disease (NCHS 113: Major cardiovascular diseases). The rate represents the age adjusted rate per 100,000 population. A detailed description is available here: https://fortress.wa.gov/doh/wtn/WTNPortal#!q0=821

From 2017 to 2020, around 7.5 percent of males and 6.5 percent of females in the United States aged 40 to 59 years had coronary heart disease. This statistic shows the percentage of adults in the U.S. who had coronary heart disease in the period from 2017 to 2020, by age and gender.

BackgroundIschemic heart disease (IHD) is a leading cause of death and disability, particularly affecting the older adult population. Extreme temperatures, especially very low and very high temperatures, are known to exacerbate cardiovascular disease burden. With the ongoing global climate change, understanding the impact of non-optimal temperatures on IHD burden becomes increasingly important, especially in vulnerable populations such as the older adult.MethodsThis study used data from the Global Burden of Disease Study 2021 (GBD 2021) to analyze the spatiotemporal trends of low and high temperatures on IHD burden in the older adult population (aged 60 and above) from 1990 to 2021. We used age-standardized rates (ASR), annual percentage change (EAPC), and the Bayesian age-period-cohort (BAPC) model to forecast 2050. Additionally, the geographic differences in IHD burden were analyzed using World Bank regions.ResultsFrom 1990 to 2021, the IHD burden in the older adult population was mainly attributed to low temperatures. However, it has increased the burden of IHD due to high temperatures, especially in tropical and low-income regions. The analysis of gender difference revealed that men are usually more affected by high temperatures, though generally, women are more sensitive to low temperatures. Forecasts are that in the future, the burden of IHD due to high temperatures will continue to rise, especially in areas with limited adaptive capacity.ConclusionAlthough low temperature remains the most important contributor to IHD burden among the older adult, the burden attributable to high temperature is on the rise, which increases the need to address the extreme temperature fluctuation. That is more so in poor-income and tropical regions where the most vulnerable populations bear a higher risk for health. Thus, there is an urgent need to develop adaptive public health measures against the dual health risks from extreme temperatures. The findings emphasize that targeted interventions are necessary, with adjustments in regional differences and gender-specific risks to effectively address the growing health threats from climate change.

This dataset presents information on age-standardized prevalence of ischemic heart disease (IHD) for Alberta, for select geographies , expressed as a percentage.

Observed and age-standardised proportion of adults on prescribed antihypertensive drugs with a blood pressure reading below systolic (SBP) 140 mmHg and diastolic (DBP) 90 mmHg during the survey. The reference population used for standardisation was the Census 2001 adult (non-institutional) population of England. To help reduce the prevalence of high blood pressure in adults through medication and monitor a preventive intervention for stroke. Legacy unique identifier: P00866

Adult respondents ages 18+ who were ever diagnosed with heart disease by a doctor. Years covered are 2011 to 2012 by zip code. Data taken from the California Health Interview Survey Neighborhood Edition (AskCHIS NE) (http://askchisne.ucla.edu/), downloaded January 2016."Field" = "Definition""ZIPCODE" = postal zip code in LA County "Zip_code" = postal zip code in LA County "PAdHrtDis" = fraction of projected 18 and older population with disease conditions residing in Zip Code"PAdHrtDis2" = percentage of projected 18 and older population with Heart disease conditions residing in Zip Code"NAdHrtDis" = number of projected 18 and older population with Heart disease conditions residing in Zip Code"Pop_18olde" = projected 18 and older population total residing in Zip CodeHealth estimates available in AskCHIS NE (Neighborhood Edition) are model-based small area estimates (SAEs).SAEs are not direct estimates (estimates produced directly from survey data, such as those provided through AskCHIS).CHIS data and analytic results are used extensively in California in policy development, service planning and research, and is recognized and valued nationally as a model population-based health surveyFAQ: 1. Which cycle of CHIS does AskCHIS Neighborhood Edition provide estimates for?All health estimates in this version of AskCHIS Neighborhood Edition are based on data from the 2011- 2012 California Health Interview Survey. Socio-demographic indicators come from the 2008-2012 American Community Survey (ACS) 5-year summary tables. 2. Why do your population estimates differ from other sources like ACS? The population estimates in AskCHIS NE represent the CHIS 2011-2012 population sample, which excludes Californians living in group quarters (such as prisons, nursing homes, and dormitories). 3. Why isn't there data available for all ZIP codes / cities in Los Angeles?While AskCHIS NE has data on all ZCTAs (Zip Code Tabulation Areas), two factors may influence our ability to display the estimates:A small population (under 15,000): currently, the application only shows estimates for geographic entities with populations above 15,000. If your ZCTA has a population below this threshold, the easiest way to obtain data is to combine it with a neighboring ZCTA and obtain a pooled estimate. A high coefficient of variation: high coefficients of variation denote statistical instability.

In 2023, around 192 out of 100,000 Canadians died from major cardiovascular diseases. In 2000, the death rate stood at over 247 deaths per 100,000. This statistic displays the age-standardized death rate for major cardiovascular diseases in Canada from 2000 to 2023. Cardiovascular health Cardiovascular health and disease has come to the forefront of healthcare in recent years, as the burden due to these diseases and related conditions has increased over time in an aging population. Public health strategies are focused on reducing the impact of cardiovascular conditions through education and interventions targeted at decreasing the modifiable risk factors for cardiovascular diseases- many of which involve lifestyle and diet elements. Medical interventions for cardiovascular disease can range from emergency interventions to surgical procedures to pharmacological treatments: in Canada, medications for the cardiovascular system held over two percent of the sales share for patented drugs in 2021. Causes of death in Canada Worldwide, Canada ranks in the top twenty countries for life expectancy and is well above the OECD average, with the average life expectancy higher for Canadian women than for men. Much like in other developed countries, malignant neoplasms join cardiovascular diseases in the leading causes of death in Canada; other main causes of death in the country include accidents, cerebrovascular diseases, and chronic lower respiratory diseases. Over the past couple decades, the age-standardized death rate for all causes among Canada’s population has increased; in 2023, it reached nearly 814 per 100,000 population.

Adult respondents ages 18+ who were ever diagnosed with heart disease by a doctor. Years covered are from 2013-2014 by zip code. Data taken from the California Health Interview Survey Neighborhood Edition (AskCHIS NE) (http://askchisne.ucla.edu/), downloaded February 2018.AskCHIS Neighborhood Edition is an online data dissemination and visualization platform that provides health estimates at sub-county geographic regions. Estimates are powered by data from The California Health Interview Survey (CHIS). CHIS is conducted by The UCLA Center for Health Policy Research, an affiliate of UCLA Fielding School of Public Health.Health estimates available in AskCHIS NE (Neighborhood Edition) are model-based small area estimates (SAEs).SAEs are not direct estimates (estimates produced directly from survey data, such as those provided through AskCHIS).CHIS data and analytic results are used extensively in California in policy development, service planning and research, and is recognized and valued nationally as a model population-based health survey.Before using estimates from AskCHIS NE, it is recommended that you read more about the methodology and data limitations at: http://healthpolicy.ucla.edu/Lists/AskCHIS%20NE%20Page%20Content/AllItems.aspx. You can go to http://askchisne.ucla.edu/ to create your own account.Produced by The California Health Interview Survey and The UCLA Center for Health Policy Research and compiled by the Los Angeles County Department of Public Health. "Field Name = Field Definition"Zipcode" = postal zip code in the City of Los Angeles “Percent” = estimated percentage of adult respondents ages 18+ who were ever diagnosed with heart disease by a doctor"LowerCL" = the lower 95% confidence limit represents the lower margin of error that occurs with statistical sampling"UpperCL" = the upper 95% confidence limit represents the upper margin of error that occurs in statistical sampling "Population" = estimated population 18 and older (denominator) residing in the zip code Notes: 1) Zip codes are based on the Los Angeles Housing Department Zip Codes Within the City of Los Angeles map (https://media.metro.net/about_us/pla/images/lazipcodes.pdf).2) Zip codes that did not have data available (i.e., null values) are not included in the dataset; there are additional zip codes that fall within the City of Los Angeles.3) Zip code boundaries do not align with political boundaries. These data are best viewed with a City of Los Angeles political boundary file (i.e., City of Los Angeles jurisdiction boundary, City Council boundary, etc.) FAQS: 1. Which cycle of CHIS does AskCHIS Neighborhood Edition provide estimates for?All health estimates in this version of AskCHIS Neighborhood Edition are based on data from the 2013-2014 California Health Interview Survey. 2. Why do your population estimates differ from other sources like ACS? The population estimates in AskCHIS NE represent the CHIS 2013-2014 population sample, which excludes Californians living in group quarters (such as prisons, nursing homes, and dormitories). 3. Why isn't there data available for all ZIP codes in Los Angeles?While AskCHIS NE has data on all ZCTAs (Zip Code Tabulation Areas), two factors may influence our ability to display the estimates:A small population (under 15,000): currently, the application only shows estimates for geographic entities with populations above 15,000. If your ZCTA has a population below this threshold, the easiest way to obtain data is to combine it with a neighboring ZCTA and obtain a pooled estimate.A high coefficient of variation: high coefficients of variation denote statistical instability.

Aims: Although diet is one of the main modifiable risk factors of cardiovascular disease, few studies have investigated the association between added sugar intake and cardiovascular disease risk. This study aims to investigate the associations between intake of total added sugar, different sugar-sweetened foods and beverages, and the risks of stroke, coronary events, atrial fibrillation and aortic stenosis.Methods: The study population consists of 25,877 individuals from the Malmö Diet and Cancer Study, a Swedish population-based prospective cohort. Dietary data were collected using a modified diet history method. National registers were used for outcome ascertainment.Results: During the mean follow-up of 19.5 years, there were 2,580 stroke cases, 2,840 coronary events, 4,241 atrial fibrillation cases, and 669 aortic stenosis cases. Added sugar intakes above 20 energy percentage were associated with increased risk of coronary events compared to the lowest intake category (HR: 1.39; 95% CI: 1.09–1.78), and increased stroke risk compared to intakes between 7.5 and 10 energy percentage (HR: 1.31; 95% CI: 1.03 and 1.66). Subjects in the lowest intake group for added sugar had the highest risk of atrial fibrillation and aortic stenosis. More than 8 servings/week of sugar-sweetened beverages were associated with increased stroke risk, while ≤2 servings/week of treats were associated with the highest risks of stroke, coronary events and atrial fibrillation.Conclusion: The results indicate that the associations between different added sugar sources and cardiovascular diseases vary. These findings emphasize the complexity of the studied associations and the importance of considering different added sugar sources when investigating health outcomes.

Deaths, overall AAMRs, and Annual Percent Change (APC) of ischemic heart diseases-related mortality in older adults in the United States, 1999 to 2020.

Observed and age-standardised proportion of adults with high blood pressure. The term "high blood pressure" is used to refer to those who are hypertensive, i.e. with a systolic blood pressure (SBP) equal to or greater than 140 and/or a diastolic blood pressure (DBP) equal to or greater than 90, whether or not currently on any antihypertensive drugs (hypertensive treated and hypertensive untreated). Also included are those with blood pressure readings below the above thresholds, but who are currently on antihypertensive drugs (normotensive treated). The counts include all adults with a valid blood pressure reading (cf. SBP, DBP below) and data on medication specifically prescribed for controlling blood pressure. To reduce the prevalence of high blood pressure in adults. Legacy unique identifier: P00842

About this dataset

Context

The dataset tabulates the South Heart population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of South Heart. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 268 (54.81% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the South Heart population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in South Heart is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the South Heart is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for South Heart Population by Age. You can refer the same here

This statistic displays the percentage of adults who self-reported having a cardiovascular disease based on lifestyle and habits as of 2019, in selected countries. Some 15 percent of the adult population suffering from cardiovascular conditions in Brazil smoked.

This is a source dataset for a Let's Get Healthy California indicator at https://letsgethealthy.ca.gov/. Adult smoking prevalence in California, males and females aged 18+, starting in 2012. Caution must be used when comparing the percentages of smokers over time as the definition of ‘current smoker’ was broadened in 1996, and the survey methods were changed in 2012. Current cigarette smoking is defined as having smoked at least 100 cigarettes in lifetime and now smoking every day or some days. Due to the methodology change in 2012, the Centers for Disease Control and Prevention (CDC) recommend not conducting analyses where estimates from 1984 – 2011 are compared with analyses using the new methodology, beginning in 2012. This includes analyses examining trends and changes over time. (For more information, please see the narrative description.) The California Behavioral Risk Factor Surveillance System (BRFSS) is an on-going telephone survey of randomly selected adults, which collects information on a wide variety of health-related behaviors and preventive health practices related to the leading causes of death and disability such as cardiovascular disease, cancer, diabetes and injuries. Data are collected monthly from a random sample of the California population aged 18 years and older. The BRFSS is conducted by Public Health Survey Research Program of California State University, Sacramento under contract from CDPH. The survey has been conducted since 1984 by the California Department of Public Health in collaboration with the Centers for Disease Control and Prevention (CDC). In 2012, the survey methodology of the California BRFSS changed significantly so that the survey would be more representative of the general population. Several changes were implemented: 1) the survey became dual-frame, with both cell and landline random-digit dial components, 2) residents of college housing were eligible to complete the BRFSS, and 3) raking or iterative proportional fitting was used to calculate the survey weights. Due to these changes, estimates from 1984 – 2011 are not comparable to estimates from 2012 and beyond. Center for Disease Control and Policy (CDC) and recommend not conducting analyses where estimates from 1984 – 2011 are compared with analyses using the new methodology, beginning in 2012. This includes analyses examining trends and changes over time.Current cigarette smoking was defined as having smoked at least 100 cigarettes in lifetime and now smoking every day or some days. Prior to 1996, the definition of current cigarettes smoking was having smoked at least 100 cigarettes in lifetime and smoking now.

Goal 3Ensure healthy lives and promote well-being for all at all agesTarget 3.1: By 2030, reduce the global maternal mortality ratio to less than 70 per 100,000 live birthsIndicator 3.1.1: Maternal mortality ratioSH_STA_MORT: Maternal mortality ratioIndicator 3.1.2: Proportion of births attended by skilled health personnelSH_STA_BRTC: Proportion of births attended by skilled health personnel (%)Target 3.2: By 2030, end preventable deaths of newborns and children under 5 years of age, with all countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live births and under-5 mortality to at least as low as 25 per 1,000 live birthsIndicator 3.2.1: Under-5 mortality rateSH_DYN_IMRTN: Infant deaths (number)SH_DYN_MORT: Under-five mortality rate, by sex (deaths per 1,000 live births)SH_DYN_IMRT: Infant mortality rate (deaths per 1,000 live births)SH_DYN_MORTN: Under-five deaths (number)Indicator 3.2.2: Neonatal mortality rateSH_DYN_NMRTN: Neonatal deaths (number)SH_DYN_NMRT: Neonatal mortality rate (deaths per 1,000 live births)Target 3.3: By 2030, end the epidemics of AIDS, tuberculosis, malaria and neglected tropical diseases and combat hepatitis, water-borne diseases and other communicable diseasesIndicator 3.3.1: Number of new HIV infections per 1,000 uninfected population, by sex, age and key populationsSH_HIV_INCD: Number of new HIV infections per 1,000 uninfected population, by sex and age (per 1,000 uninfected population)Indicator 3.3.2: Tuberculosis incidence per 100,000 populationSH_TBS_INCD: Tuberculosis incidence (per 100,000 population)Indicator 3.3.3: Malaria incidence per 1,000 populationSH_STA_MALR: Malaria incidence per 1,000 population at risk (per 1,000 population)Indicator 3.3.4: Hepatitis B incidence per 100,000 populationSH_HAP_HBSAG: Prevalence of hepatitis B surface antigen (HBsAg) (%)Indicator 3.3.5: Number of people requiring interventions against neglected tropical diseasesSH_TRP_INTVN: Number of people requiring interventions against neglected tropical diseases (number)Target 3.4: By 2030, reduce by one third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-beingIndicator 3.4.1: Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory diseaseSH_DTH_NCOM: Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease (probability)SH_DTH_NCD: Number of deaths attributed to non-communicable diseases, by type of disease and sex (number)Indicator 3.4.2: Suicide mortality rateSH_STA_SCIDE: Suicide mortality rate, by sex (deaths per 100,000 population)SH_STA_SCIDEN: Number of deaths attributed to suicide, by sex (number)Target 3.5: Strengthen the prevention and treatment of substance abuse, including narcotic drug abuse and harmful use of alcoholIndicator 3.5.1: Coverage of treatment interventions (pharmacological, psychosocial and rehabilitation and aftercare services) for substance use disordersSH_SUD_ALCOL: Alcohol use disorders, 12-month prevalence (%)SH_SUD_TREAT: Coverage of treatment interventions (pharmacological, psychosocial and rehabilitation and aftercare services) for substance use disorders (%)Indicator 3.5.2: Alcohol per capita consumption (aged 15 years and older) within a calendar year in litres of pure alcoholSH_ALC_CONSPT: Alcohol consumption per capita (aged 15 years and older) within a calendar year (litres of pure alcohol)Target 3.6: By 2020, halve the number of global deaths and injuries from road traffic accidentsIndicator 3.6.1: Death rate due to road traffic injuriesSH_STA_TRAF: Death rate due to road traffic injuries, by sex (per 100,000 population)Target 3.7: By 2030, ensure universal access to sexual and reproductive health-care services, including for family planning, information and education, and the integration of reproductive health into national strategies and programmesIndicator 3.7.1: Proportion of women of reproductive age (aged 15–49 years) who have their need for family planning satisfied with modern methodsSH_FPL_MTMM: Proportion of women of reproductive age (aged 15-49 years) who have their need for family planning satisfied with modern methods (% of women aged 15-49 years)Indicator 3.7.2: Adolescent birth rate (aged 10–14 years; aged 15–19 years) per 1,000 women in that age groupSP_DYN_ADKL: Adolescent birth rate (per 1,000 women aged 15-19 years)Target 3.8: Achieve universal health coverage, including financial risk protection, access to quality essential health-care services and access to safe, effective, quality and affordable essential medicines and vaccines for allIndicator 3.8.1: Coverage of essential health servicesSH_ACS_UNHC: Universal health coverage (UHC) service coverage indexIndicator 3.8.2: Proportion of population with large household expenditures on health as a share of total household expenditure or incomeSH_XPD_EARN25: Proportion of population with large household expenditures on health (greater than 25%) as a share of total household expenditure or income (%)SH_XPD_EARN10: Proportion of population with large household expenditures on health (greater than 10%) as a share of total household expenditure or income (%)Target 3.9: By 2030, substantially reduce the number of deaths and illnesses from hazardous chemicals and air, water and soil pollution and contaminationIndicator 3.9.1: Mortality rate attributed to household and ambient air pollutionSH_HAP_ASMORT: Age-standardized mortality rate attributed to household air pollution (deaths per 100,000 population)SH_STA_AIRP: Crude death rate attributed to household and ambient air pollution (deaths per 100,000 population)SH_STA_ASAIRP: Age-standardized mortality rate attributed to household and ambient air pollution (deaths per 100,000 population)SH_AAP_MORT: Crude death rate attributed to ambient air pollution (deaths per 100,000 population)SH_AAP_ASMORT: Age-standardized mortality rate attributed to ambient air pollution (deaths per 100,000 population)SH_HAP_MORT: Crude death rate attributed to household air pollution (deaths per 100,000 population)Indicator 3.9.2: Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (exposure to unsafe Water, Sanitation and Hygiene for All (WASH) services)SH_STA_WASH: Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (deaths per 100,000 population)Indicator 3.9.3: Mortality rate attributed to unintentional poisoningSH_STA_POISN: Mortality rate attributed to unintentional poisonings, by sex (deaths per 100,000 population)Target 3.a: Strengthen the implementation of the World Health Organization Framework Convention on Tobacco Control in all countries, as appropriateIndicator 3.a.1: Age-standardized prevalence of current tobacco use among persons aged 15 years and olderSH_PRV_SMOK: Age-standardized prevalence of current tobacco use among persons aged 15 years and older, by sex (%)Target 3.b: Support the research and development of vaccines and medicines for the communicable and non-communicable diseases that primarily affect developing countries, provide access to affordable essential medicines and vaccines, in accordance with the Doha Declaration on the TRIPS Agreement and Public Health, which affirms the right of developing countries to use to the full the provisions in the Agreement on Trade-Related Aspects of Intellectual Property Rights regarding flexibilities to protect public health, and, in particular, provide access to medicines for allIndicator 3.b.1: Proportion of the target population covered by all vaccines included in their national programmeSH_ACS_DTP3: Proportion of the target population with access to 3 doses of diphtheria-tetanus-pertussis (DTP3) (%)SH_ACS_MCV2: Proportion of the target population with access to measles-containing-vaccine second-dose (MCV2) (%)SH_ACS_PCV3: Proportion of the target population with access to pneumococcal conjugate 3rd dose (PCV3) (%)SH_ACS_HPV: Proportion of the target population with access to affordable medicines and vaccines on a sustainable basis, human papillomavirus (HPV) (%)Indicator 3.b.2: Total net official development assistance to medical research and basic health sectorsDC_TOF_HLTHNT: Total official development assistance to medical research and basic heath sectors, net disbursement, by recipient countries (millions of constant 2018 United States dollars)DC_TOF_HLTHL: Total official development assistance to medical research and basic heath sectors, gross disbursement, by recipient countries (millions of constant 2018 United States dollars)Indicator 3.b.3: Proportion of health facilities that have a core set of relevant essential medicines available and affordable on a sustainable basisSH_HLF_EMED: Proportion of health facilities that have a core set of relevant essential medicines available and affordable on a sustainable basis (%)Target 3.c: Substantially increase health financing and the recruitment, development, training and retention of the health workforce in developing countries, especially in least developed countries and small island developing StatesIndicator 3.c.1: Health worker density and distributionSH_MED_DEN: Health worker density, by type of occupation (per 10,000 population)SH_MED_HWRKDIS: Health worker distribution, by sex and type of occupation (%)Target 3.d: Strengthen the capacity of all countries, in particular developing countries, for early warning, risk reduction and management of national and global health risksIndicator 3.d.1: International Health Regulations (IHR) capacity and health emergency preparednessSH_IHR_CAPS: International Health Regulations (IHR) capacity, by type of IHR capacity (%)Indicator 3.d.2: Percentage of bloodstream infections due to selected antimicrobial-resistant organismsiSH_BLD_MRSA: Percentage of bloodstream infection due to methicillin-resistant Staphylococcus aureus (MRSA) among patients seeking care and whose

95% CI: 95% confidence interval.*Age- adjusted percentages for men or women. †Age- and sex- adjusted percentages. ‡ Sex-adjusted percentages for each age group. Adjustment was conducted with the 2010 Chinese National Census Population by the direct method.