The number of deaths due to unsafe water sources has generally decreased over time. In low-income countries, unsafe water sources are the cause of 2.3 percent of deaths as of 2021. In Chad, seven percent of deaths are due to these unsafe water resources.

Approximately ** million people in the United States were served by large and very large drinking water systems with elevated levels of nitrate between 2017 and 2019. The most affected state was California, where approximately **** million consumed drinking water with high nitrate levels in the period. This represents more than half of the state's population. The second most affected state during this period was Arizona, where the number of people served nitrate-contaminated drinking water was approximately *** million. Farm run-off is a major cause of water pollution, with croplands accounting for ** percent of global nitrate contamination in groundwater.

Japan JP: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data was reported at 0.200 Ratio in 2016. Japan JP: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data is updated yearly, averaging 0.200 Ratio from Dec 2016 (Median) to 2016, with 1 observations. Japan JP: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank: Health Statistics. Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

The global death rate due to unsafe water access has decreased in the past decades. As of 2021, there were approximately ten deaths per 100,000 people worldwide, a considerable decrease from almost 41 deaths per 100,000 people in 1990.

Chad TD: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data was reported at 101.000 Ratio in 2016. Chad TD: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data is updated yearly, averaging 101.000 Ratio from Dec 2016 (Median) to 2016, with 1 observations. Chad TD: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chad – Table TD.World Bank: Health Statistics. Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

Series Name: Mortality rate attributed to unsafe water unsafe sanitation and lack of hygiene (deaths per 100 000 population)Series Code: SH_STA_WASHRelease Version: 2021.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.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)Target 3.9: By 2030, substantially reduce the number of deaths and illnesses from hazardous chemicals and air, water and soil pollution and contaminationGoal 3: Ensure healthy lives and promote well-being for all at all agesFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

This dataset explores the relationship between water pollution and the prevalence of waterborne diseases worldwide. It includes water quality indicators, pollution levels, disease rates, and socio-economic factors that influence health outcomes. The dataset provides information on different countries and regions, spanning the years 2000-2025.

It covers key factors such as contaminant levels, access to clean water, bacterial presence, water treatment methods, sanitation coverage, and the incidence of diseases like diarrhea, cholera, and typhoid. Additionally, it incorporates socio-economic variables such as GDP per capita, urbanization rate, and healthcare access, which help assess the broader impact of water pollution on communities.

This dataset can be used for:

Public health research on the impact of water pollution.

Environmental studies to analyze trends in water contamination.

Policy-making for clean water access and sanitation improvements.

Machine learning models to predict disease outbreaks based on water quality.

Prevalence: Covers 10 countries (e.g., USA, India, China, Brazil, Nigeria, Bangladesh, Mexico, Indonesia, Pakistan, Ethiopia).

Includes 5 regions per country (e.g., North, South, East, West, Central).

Spans 26 years (2000-2025).

Features 3,000 unique records representing various water sources and pollution conditions.

Burundi BI: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data was reported at 65.400 Ratio in 2016. Burundi BI: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data is updated yearly, averaging 65.400 Ratio from Dec 2016 (Median) to 2016, with 1 observations. Burundi BI: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Burundi – Table BI.World Bank: Health Statistics. Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

Sub-Saharan Africa had the highest death rate due to unsafe water worldwide in 2021, at almost ** people per 100,000. Nevertheless, this was a considerable decrease from the *** deaths for every 100,000 people recorded in the region in 1990.

Time series data for the statistic Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (per 100,000 population) and country Finland. Indicator Definition:Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.

Time series data for the statistic Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (per 100,000 population) and country Poland. Indicator Definition:Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.

Time series data for the statistic Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (per 100,000 population) and country China. Indicator Definition:Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.

Time series data for the statistic Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (per 100,000 population) and country Sweden. Indicator Definition:Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.

Time series data for the statistic Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (per 100,000 population) and country Romania. Indicator Definition:Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.

Time series data for the statistic Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene, male (per 100,000 male population) and country Eswatini. Indicator Definition:Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.

There were an estimated 35.2 deaths per 100,000 people due to unsafe water sources in India in 2021. The annual number of deaths due to unsafe water sources in India has fallen by more than 80 percent since 1990. Neverthless, the death rate from this health risk was still three times above the global average in 2021. Unsafe water sources are among the leading death risk factors in India.

Mexico MX: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data was reported at 1.100 Ratio in 2016. Mexico MX: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data is updated yearly, averaging 1.100 Ratio from Dec 2016 (Median) to 2016, with 1 observations. Mexico MX: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank.WDI: Health Statistics. Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

BackgroundAccording to the most recent estimates, 842,000 deaths in low- to middle-income countries were attributable to inadequate water, sanitation and hygiene in 2012. Despite billions of dollars and decades of effort, we still lack a sound understanding of which kinds of WASH interventions are most effective in improving public health outcomes, and an important corollary–whether the right things are being measured. The World Health Organization (WHO) has made a concerted effort to compile comprehensive data on drinking water quality and sanitation in the developing world. A recent 2014 report provides information on three phenotypes (responses): Unsafe Water Deaths, Unsafe Sanitation Deaths, Unsafe Hygiene Deaths; two grouped phenotypes: Unsafe Water and Sanitation Deaths and Unsafe Water, Sanitation and Hygiene Deaths; and six explanatory variables (predictors): Improved Sanitation, Unimproved Water Source, Piped Water To Premises, Other Improved Water Source, Filtered and Bottled Water in the Household and Handwashing.Methods and FindingsRegression analyses were performed to identify statistically significant associations between these mortality responses and predictors. Good fitted-model performance required: (1) the use of population-normalized death fractions as opposed to number of deaths; (2) transformed response (logit or power); and (3) square-root predictor transformation. Given the complexity and heterogeneity of the relationships and countries being studied, these models exhibited remarkable performance and explained, for example, about 85% of the observed variance in population-normalized Unsafe Sanitation Death fraction, with a high F-statistic and highly statistically significant predictor p-values. Similar performance was found for all other responses, which was an unexpected result (the expected associations between responses and predictors–i.e., water-related with water-related, etc. did not occur). The set of statistically significant predictors remains the same across all responses. That is, Unsafe Water Source (UWS), Improved Sanitation (IS) and Filtered and Bottled Water in the Household (FBH) were the only statistically significant predictors whether the response was Unsafe Sanitation Death Fraction, Unsafe Hygiene Death Fraction or Unsafe Water Death Fraction. Moreover, the fraction of variance explained for all fitted models remained relatively high (adjusted R2 ranges from 0.7605 to 0.8533). We find that two of the statistically significant predictors–Improved Sanitation and Unimproved Water Sources–are particularly influential. We also find that some predictors (Piped Water to Premises, Other Improved Water Sources) have very little explanatory power for predicting mortality and one (Other Improved Water Sources) has a counterintuitive effect on response (Unsafe Sanitary Death Fraction increases with increases in OIWS) and one predictor (Hand Washing) to have essentially no explanatory usefulness.ConclusionsOur results suggest that a higher priority may need to be given to improved sanitation than has been the case. Nevertheless, while our focus in this paper is mortality, morbidity is a staggering consequence of inadequate water, sanitation and hygiene, and lower impact on mortality may not mean a similarly low impact on morbidity. More specifically, those predictors that we found uninfluential for predicting mortality-related responses may indeed be important when morbidity is the response.

Time series data for the statistic Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (per 100,000 population) and country Cabo Verde. Indicator Definition:Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.

Time series data for the statistic Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (per 100,000 population) and country Samoa. Indicator Definition:Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.