Actual value and historical data chart for World Population Female Percent Of Total

Context

This dataset compiles valuable information on how different countries worldwide rank concerning conditions and opportunities for women. It aims to shed light on the status of women's rights and gender equality across the globe, making it a valuable resource for researchers, policymakers, and organizations advocating for gender equality.

Content

This dataset contains three main columns:

1.**Rank:** This column provides the ranking of countries based on their performance or score in terms of conditions and opportunities for women. Rankings range from 1 (indicating the best country for women) to the total number of countries included in the dataset.

2.**Country:** This column lists the names of the countries under evaluation. Each row corresponds to a specific country, allowing users to identify which country the data pertains to. Examples of entries in this column include "United States," "Sweden," "India," and more.

3.**Score:** The "Score" column comprises numerical values or scores reflecting the overall assessment of each country's performance regarding conditions and opportunities for women. These scores are likely calculated based on factors such as gender equality in education, employment, healthcare, political representation, and legal rights. Higher scores generally indicate better conditions for women, while lower scores suggest room for improvement.

Use Cases:

• Researchers can analyze this dataset to identify global trends in gender equality, allowing for cross-country comparisons and the identification of areas where countries excel or need improvement.

• Policymakers can utilize this data to make informed decisions and track progress in achieving gender equality goals.

• Advocacy groups and organizations working on women's rights can leverage this dataset to support their initiatives and promote gender equality on a global scale.

• Data enthusiasts on Kaggle can explore this dataset for data visualization, machine learning, and statistical analysis projects aimed at uncovering insights and trends related to women's well-being and opportunities.

Data Source:

https://ceoworld.biz/2021/06/11/the-worlds-best-countries-for-women-2021/

Acknowledgments:

If applicable, acknowledge any individuals or organizations that contributed to collecting or compiling this dataset.

By publishing this dataset on Kaggle, you are contributing to the open data community and providing a valuable resource for data-driven insights into gender equality worldwide.

As of October 2025, 6.04 billion individuals worldwide were internet users, which amounted to 73.2 percent of the global population. Of this total, 5.66 billion, or 68.7 percent of the world's population, were social media users. Global internet usage Connecting billions of people worldwide, the internet is a core pillar of the modern information society. Northern Europe ranked first among worldwide regions by the share of the population using the internet in 2025. In the Netherlands, Norway, and Saudi Arabia, 99 percent of the population used the internet as of February 2025. North Korea was at the opposite end of the spectrum, with virtually no internet usage penetration among the general population, ranking last worldwide. Eastern Asia was home to the largest number of online users worldwide—over 1.34 billion at the latest count. Southern Asia ranked second, with around 1.2 billion internet users. China, India, and the United States rank ahead of other countries worldwide by the number of internet users. Worldwide internet user demographics As of 2024, the share of female internet users worldwide was 65 percent, five percent less than that of men. Gender disparity in internet usage was bigger in African countries, with around a 10-percent difference. Worldwide regions, like the Commonwealth of Independent States and Europe, showed a smaller usage gap between these two genders. As of 2024, global internet usage was higher among individuals between 15 and 24 years old across all regions, with young people in Europe representing the most considerable usage penetration, 98 percent. In comparison, the worldwide average for the age group of 15 to 24 years was 79 percent. The income level of the countries was also an essential factor for internet access, as 93 percent of the population of the countries with high income reportedly used the internet, as opposed to only 27 percent of the low-income markets.

Actual value and historical data chart for World Population Female

The share of women working in cloud computing has seen a slight increase in the past two years: as of 2020, **** percent of people working with cloud computing were women. The share of women working in data and AI is higher, amounting to around ** percent.

Women in Headlines: Bias

Investigating Gendered Language, Temporal Trends, and Themes

By Amber Thomas [source]

About this dataset

This dataset contains all of the data used in the Pudding essay When Women Make Headlines published in January 2022. This dataset was created to analyze gendered language, bias and language themes in news headlines from across the world. It contains headlines from top50 news publications and news agencies from four major countries - USA, UK, India and South Africa - as published by SimilarWeb (as of 2021-06-06).

To collect this data we used RapidAPI's google news API to query headlines containing one or more of keywords selected based on existing research done by Huimin Xu & team and The Swaddle team. We analyzed words used in headlines manually curating two dictionaries — gendered words about women (words that are explicitly gendered) and words that denote societal/behavioral stereotypes about women. To calculate bias scores, we utilized technology developed through Yasmeen Hitti & team’s research on gender bias text analysis. To categorize words used into themes (violence/crime, empowerment, race/ethnicity/identity etc), we manually curated four dictionaries utilizing Natural Language Processing packages for Python like spacy & nltk for our analysis. Plus, inverting polarity scores with vaderSentiment algorithm helped us shed light on differences between women-centered/non-women centered polarity levels as well as differences between global polarity baselines of each country's most visited publications & news agencies according to SimilarWeb 2020 statistics..

This dataset enables journalists, researchers and educators researching issues related to gender equity within media outlets around the world further insights into potential disparities with just a few lines of code! Any discoveries made by using this data should provide valuable support for evidence-based argumentation . Let us advocate for greater awareness towards female representation better quality coverage!

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How to use the dataset

This dataset provides a comprehensive look at the portrayal of women in headlines from 2010-2020. Using this dataset, researchers and data scientists can explore a range of topics including language used to describe women, bias associated with different topics or publications, and temporal patterns in headlines about women over time.

To use this dataset effectively, it is helpful to understand the structure of the data. The columns include headline_no_site (the text of the headline without any information about which publication it is from), time (the date and time that the article was published), country (the country where it was published), bias score (calculated using Gender Bias Taxonomy V1.0) and year (the year that the article was published).

By exploring these columns individually or combining them into groups such as by publication or by topic, there are many ways to make meaningful discoveries using this data set. For example, one could explore if certain news outlets employ more gender-biased language when writing about female subjects than other outlets or investigate whether female-centric stories have higher/lower bias scores than average for a particular topic across multiple countries over time. This type of analysis helps researchers to gain insight into how our culture's dialogue has evolved over recent years as relates to women in media coverage worldwide

Research Ideas

• A comparative, cross-country study of the usage of gendered language and the prevalence of gender bias in headlines to better understand regional differences.
• Creating an interactive visualization showing the evolution of headline bias scores over time with respect to a certain topic or population group (such as women).
• Analyzing how different themes are covered in headlines featuring women compared to those without, such as crime or violence versus empowerment or race and ethnicity, to see if there’s any difference in how they are portrayed by the media

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: headlines_reduced_temporal.csv | Column name | Description | |:---------------------|:-------------------------------------------------------------------------------------...

As of 2024, the share of internet users in the CIS region (Commonwealth of Independent States) was the highest in the world, with 91 percent of the female population and 93 percent of the male population accessing the internet. As of the same year, there were 90 percent female and 92 percent male internet users in Europe, making it the second region worldwide by internet usage. Africa was the region where internet access was the lowest. Share of female and male internet users worldwide There are still disparities between the internet access rates of male and female online users in global regions. According to the latest data, 34 percent of Africa’s female population had online access, compared to 45 percent of men. Whereas in the Americas, the share of male and female internet users was the same, 83 percent. There was also a big difference in the share of female and male internet users in the Arab States. In the region, 65 percent of women had access to the internet, whereas the share of the male population using the internet was 75 percent. The gender gap was also seen in mobile internet usage in low-and middle-income countries (LMICs). Internet access and SDGs As of 2022, Africa’s online access rate was the lowest worldwide, with estimates showing that just over 30 percent of the total population was using the internet. By comparison, the global average online usage rate was 51 percent. This technological gap between Africa and the rest of the world highlights the need for continued investment in information and communication technologies on the continent, as such processes can speed up progress towards the 17 Sustainable Development Goals (SDGs) set by the United Nations. The Sustainable Development Goals, also known as the Global Goals, are a worldwide agenda to protect the planet, end poverty, and ensure global peace and prosperity. ICTs, especially mobile internet, contribute to the goals by enabling countries to participate in digital economies as well as empowering individuals to access crucial information and services. However, almost 40 percent of the world was not using the internet as of 2021. Particularly disenfranchised groups were frequently excluded from digital society, including women and girls, people with disabilities, elders, indigenous populations, people living in poverty, and inhabitants of least developed or developing countries. The digital gender gap was another obstacle for women to overcome on a global level to achieve economic advancement which would ultimately also benefit their communities.

This dataset explores the intriguing phenomenon of life expectancy disparity between genders across various countries spanning the years 1950 to 2020. Delving into the age-old statement that "women live longer than men," this dataset provides insights into the evolving trends in life expectancy and population dynamics worldwide.

Dataset Glossary (Column-wise):

• Year: The year of observation (1950-2020).
• Female Life Expectancy: The average life expectancy at birth for females in a given year and country.
• Male Life Expectancy: The average life expectancy at birth for males in a given year and country.
• Population: The total population of the country in a given year.
• Life Expectancy Gap: The difference between female and male life expectancy, highlighting the disparity between genders.

The dataset aims to facilitate comprehensive analyses regarding gender-based life expectancy disparities over time and across different nations. Researchers, policymakers, and analysts can utilize this dataset to explore patterns, identify contributing factors, and devise strategies to address gender-based health inequalities.

License - This Dataset falls under the Creative Commons Attribution 3.0 IGO License. You can check the Terms of Use of this Data. If you want to learn more, visit the Website.

Acknowledgement: Image :- Freepik

PLEASE if you use or like this dataset UPVOTE 👁️

This dataset offers a detailed historical record of global life expectancy, covering data from 1960 to the present. It is meticulously curated to enable deep analysis of trends and gender disparities in life expectancy worldwide.

Dataset Structure & Key Columns:

Country Code (🔤): Unique identifier for each country.

Country Name (🌍): Official name of the country.

Region (🌐): Broad geographical area (e.g., Asia, Europe, Africa).

Sub-Region (🗺️): More specific regional classification within the broader region.

Intermediate Region (🔍): Additional granular geographical grouping when applicable.

Year (📅): The specific year to which the data pertains.

Life Expectancy for Women (👩‍⚕️): Average years a woman is expected to live in that country and year.

Life Expectancy for Men (👨‍⚕️): Average years a man is expected to live in that country and year.

Context & Use Cases:

This dataset is a rich resource for exploring long-term trends in global health and demography. By comparing life expectancy data over decades, researchers can:

Analyze Time Series Trends: Forecast future changes in life expectancy and evaluate the impact of health interventions over time.

Study Gender Disparities: Investigate the differences between life expectancy for women and men, providing insights into social, economic, and healthcare factors influencing these trends.

Regional & Sub-Regional Analysis: Compare and contrast life expectancy across various regions and sub-regions to understand geographical disparities and their underlying causes.

Support Public Policy Research: Inform policymakers by linking life expectancy trends with public health policies, socioeconomic developments, and other key indicators.

Educational & Data Science Applications: Serve as a comprehensive teaching tool for courses on public health, global development, and data analysis, as well as for Kaggle competitions and projects.

With its detailed, structured format and broad temporal coverage, this dataset is ideal for anyone looking to gain a nuanced understanding of global health trends and to drive impactful analyses in public health, social sciences, and beyond.

Feel free to ask for further customizations or additional details as needed!

Description

This comprehensive dataset provides a wealth of information about all countries worldwide, covering a wide range of indicators and attributes. It encompasses demographic statistics, economic indicators, environmental factors, healthcare metrics, education statistics, and much more. With every country represented, this dataset offers a complete global perspective on various aspects of nations, enabling in-depth analyses and cross-country comparisons.

Key Features

• Country: Name of the country.
• Density (P/Km2): Population density measured in persons per square kilometer.
• Abbreviation: Abbreviation or code representing the country.
• Agricultural Land (%): Percentage of land area used for agricultural purposes.
• Land Area (Km2): Total land area of the country in square kilometers.
• Armed Forces Size: Size of the armed forces in the country.
• Birth Rate: Number of births per 1,000 population per year.
• Calling Code: International calling code for the country.
• Capital/Major City: Name of the capital or major city.
• CO2 Emissions: Carbon dioxide emissions in tons.
• CPI: Consumer Price Index, a measure of inflation and purchasing power.
• CPI Change (%): Percentage change in the Consumer Price Index compared to the previous year.
• Currency_Code: Currency code used in the country.
• Fertility Rate: Average number of children born to a woman during her lifetime.
• Forested Area (%): Percentage of land area covered by forests.
• Gasoline_Price: Price of gasoline per liter in local currency.
• GDP: Gross Domestic Product, the total value of goods and services produced in the country.
• Gross Primary Education Enrollment (%): Gross enrollment ratio for primary education.
• Gross Tertiary Education Enrollment (%): Gross enrollment ratio for tertiary education.
• Infant Mortality: Number of deaths per 1,000 live births before reaching one year of age.
• Largest City: Name of the country's largest city.
• Life Expectancy: Average number of years a newborn is expected to live.
• Maternal Mortality Ratio: Number of maternal deaths per 100,000 live births.
• Minimum Wage: Minimum wage level in local currency.
• Official Language: Official language(s) spoken in the country.
• Out of Pocket Health Expenditure (%): Percentage of total health expenditure paid out-of-pocket by individuals.
• Physicians per Thousand: Number of physicians per thousand people.
• Population: Total population of the country.
• Population: Labor Force Participation (%): Percentage of the population that is part of the labor force.
• Tax Revenue (%): Tax revenue as a percentage of GDP.
• Total Tax Rate: Overall tax burden as a percentage of commercial profits.
• Unemployment Rate: Percentage of the labor force that is unemployed.
• Urban Population: Percentage of the population living in urban areas.
• Latitude: Latitude coordinate of the country's location.
• Longitude: Longitude coordinate of the country's location.

Potential Use Cases

• Analyze population density and land area to study spatial distribution patterns.
• Investigate the relationship between agricultural land and food security.
• Examine carbon dioxide emissions and their impact on climate change.
• Explore correlations between economic indicators such as GDP and various socio-economic factors.
• Investigate educational enrollment rates and their implications for human capital development.
• Analyze healthcare metrics such as infant mortality and life expectancy to assess overall well-being.
• Study labor market dynamics through indicators such as labor force participation and unemployment rates.
• Investigate the role of taxation and its impact on economic development.
• Explore urbanization trends and their social and environmental consequences.

Data Source: This dataset was compiled from multiple data sources

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This dataset provides values for RETIREMENT AGE WOMEN reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This World Marriage Dataset provides a comparable and up-to-date set of data on the marital status of the population by age and sex for 232 countries or different regions of the world from 1970 to 2019. There are 271605 rows and 9 columns in this dataset. Each row of the dataset represents a specific age group of men, either divorced or married or Single. The columns include:

Sr. No.: A serial number to identify each entry. Country: The country of focus. Age Group: The age range of the surveyed individuals. Sex: The gender of the surveyed individuals. Marital Status: The marital status of the individuals, categorized as either "Divorced" or "Married" or "Single". Data Process: The method used to collect the data. Data Collection (Start Year): The year when data collection began. Data Collection (End Year): The year when data collection ended. Data Source: The source of the data. This dataset helps to understand the marital status distribution among different age groups of men and women in all over the world from 1970 to 2019.

Four-way weighted least-squares analysis of covariance (WLS ANCOVA) main effects and interactions on mean earnings.

Abstract

Violence against women (VAW), in its many forms and manifestations, and across all settings, is a violation of human rights and fundamental freedoms. Around the world, many women experience violence regardless of age, class, race and ethnicity. Most of this violence is driven by the fact that they are women, and related to gender roles in society. Violence against women is predominately perpetrated by men, and most often by intimate partners. According to most recent global estimates, 35% of women aged 15 years or older globally have experienced physical and/or sexual violence during their lifetime (Devries et al., 2013; WHO, 2013). Intimate partner violence is the leading cause of homicide in women globally (Stockl et al., 2013) and has many other major short- and long-term health consequences (WHO, 2013). The economic and social costs associated with VAW are significant, and global evidence shows that violence consistently undermines development efforts at various levels, affecting physical, human and social capital (WHO, 2005). In Cambodia, the state of research on violence against women points toward widespread experiences of violence across the country (CDHS, 2012; Fulu et al., 21013). Women of all cultures and classes are subjected to many forms of physical, psychological, sexual and economic violence. This includes, but is not limited to intimate partner violence (IPV), rape and sexual assault, sexual harassment, acid violence and trafficking (MoWA, 2008). The Royal Government of Cambodia (RGC) has made a strong commitment to addressing violence against women by introducing a number of legislative and policy reforms including domestic violence legislation and a national action plan. Cambodia has demonstrated its strong commitment to promoting gender equality and ending VAW by ratifying several core international human rights conventions. In addition, there is widespread recognition among Cambodian government leaders that having quality data on the prevalence and health and other consequences of different forms of VAW is essential to increase awareness, inform evidencebased programming and policies, including the NAPVAW, and to monitor progress in the implementations of such interventions. Between 2014-2015, to fill the identified knowledge gaps, the Royal Government of Cambodia with support from the World Health Organization (WHO) and UN Women conducted a national prevalence study using the WHO multicountry study methodology. This methodology was selected because it has been widely used and is known to produce reliable data, that can be used for cross-country comparisons, and it adheres to internationally recognized ethical and safety standards.

Specific Objectives: Among specific objectives, the following deserve special mention:

ESTIMATE THE PREVALENCE AND FREQUENCY of different forms of VAW: physical, sexual, emotional and economic violence against women by intimate partners, as well as sexual and physical violence by perpetrators other than partners (in this document also referred to as ‘nonpartners’) since the age of 15, and sexual violence before the age of 15;

DETERMINE THE ASSOCIATION of physical and/or sexual intimate partner violence with a range of health and other outcomes;

IDENTIFY FACTORS that may be associated with either reducing (protective factors) or increasing (risk factors) women’s risk of hysical and/or sexual intimate partner violence; DOCUMENT THE STRATEGIES and services that women use to cope with violence by an intimate partner.

INCREASE NATIONAL CAPACITY and collaboration among researchers and women’s organisations working on domestic violence;

INCREASE AWARENESS about and sensitivity to partner violence among researchers, policymakers and health care providers;

CONTRIBUTE TO THE DEVELOPMENT of a network of people committed to addressing

Geographic coverage

National

Analysis unit

• Households
• Individuals

Universe

All resident households in Cambodia

Kind of data

Sample survey data [ssd]

Sampling procedure

• The survey sample design was developed by the NIS in the Ministry of Planning. A multi-stage sampling strategy was used based on a sampling frame that took into consideration the 24 provinces in the country delineated into a total of 225 districts for a total of 14,172 "villages" or 28,701 enumeration areas (EAs) in the country. The sample is self-weighted at the household level.

• The results achieved on VAW 2015 sampling design is already completed and describes as follows: a.Two level of survey results will be produces as: first at National level and second sub-national (Urban and Rural) b.Survey methods of VAW 2015 were designed bases on the three- stage stratified cluster sampling. b1. First stage: selected the sample Enumeration area consisting of 200 sample EAs b2. Second stage: selected the sample households consisting of 4,000 households b3. Selected the sample Women consisting of 4,000 eligible women

Mode of data collection

Face-to-face [f2f]

Cleaning operations

The questionnaire was programmed into electronic format using CAPI software, which allowed interviewers to enter the responses to questions directly into the electronic devises that were uploaded on a daily basis. Data entry was therefore not required. The software directly checked internal consistency, range and error checking, and skip patterns of the responses at the point of entering the answers during the interview. The uploaded files were aggregated at a central level and were immediately available for data analysis.

Response rate

Eligible woman response rate: 98% Household response rate: 99.5% Household refused: 0.5%

Sampling error estimates

Sample size calculations: Z (95% Confidence Interval), the value of 1.96 P = 30%. In many countries were data are available, lifetime intimate partner sexual violence often reaches 25-30% and lifetime intimate partner physical violence is 65-70%. In a normal distribution the highest variance for a factor would be at the 50% level (resulting in needing a very large sample) and the lowest variance would be at the extremes (needing the smallest sample). We compromise at 30% which is identical to assuming 70% so the resulting sample size is large, but not unmanageable. DEFF = 2. We have used this value for all the national surveys, to date. E = 0.02291. We calculate the sample size using margin of error 2.291%.

The sample size results are as follow: Confidence Level :1.96 Margin of Error (MOE): 0.02291 Baseline levels of the indicator: 0.3 Design effect (Deff): 2 Sample size (n) - Female: 3,074

IntroductionCervical cancer is a significant public health problem for women worldwide. It is the fourth most frequent cancer in women globally. While early detection of cancerous lesions through screening tests leads to a better prognosis and a better chance of being cured, the number of people who go for screening is still low, especially for groups that are marginalized, like immigrant women.ObjectiveThe purpose of this study was to identify cervical cancer screening practices and factors influencing screening status among Yemeni immigrant women living in the Klang Valley, Malaysia.MethodA cross-sectional study among 355 randomly selected respondents between the ages of 20 and 65 was conducted through an online survey. A questionnaire was sent directly to the participants via WhatsApp. The analysis was conducted using SPSS 25 with a significance level of 0.05. It included descriptive analysis, chi-square and multiple logistic regression.ResultsThe response rate was 59%, with the majority of the respondents being married and between the ages of 35 and 49. Screening was reported at 23.1% in the previous three years. The final model revealed that age group 50–65 years (AOR = 5.39, 95% CI: 1.53–18.93), insurance status (AOR 2.22, 95% CI = 1.15–4.3), knowledge (AOR = 6.67, 95% CI = 3.45–12.9), access to health care facilities (AOR = 4.64, 95% CI = 1.29–16.65), and perceived barriers (AOR = 2.5, 95% CI = 1.3–4.83) were significant predictors of cervical screening uptake among Yemeni immigrant women in Malaysia (p

As of October 2025, users aged 25 to 34 years made up Facebook's largest audience in the United States, accounting for **** percent of the social network's user base, with **** percent of those users being women. Overall, *** percent of users aged 35 to 44 years were women, and *** percent were men. How many people use Facebook in the United States? ******** is by far the most used social network in the world and finds a huge share of its audience in ****************** Facebook’s U.S. audience size comes second only to India. In 2023, there were over *** million Facebook users in the U.S. By 2028, it is estimated that around *** million people in the U.S. will be signed up for the platform. How do users in the United States view the platform? Although Facebook is widely used and very popular with U.S. consumers, there are issues of trust with its North American audience. As of November 2021, ** percent of respondents reported that they did not trust Facebook with their personal data. Despite having privacy doubts, a May 2022 survey found that ** percent of adults had a very favorable opinion of Facebook, and one-third held a somewhat positive view of the platform.

IntroductionIn the world, 33% of soils are degraded, and 2.9 million people are affected by land degradation, with problems associated with food security, conflicts over natural resources, and migration with different impacts on men or women. To support sustainable soil management, it is necessary to include women’s contributions to soil Sciences; their achievements and academic performance still need to be represented. Women in Science represent 30% worldwide. In Mexico, only 24% of top academic positions are women. For commitment to soil Sciences for Sustainable Development Goals (SDGs), UNAM created the University Program for Interdisciplinary Soil Studies (PUEIS).MethodsThis research evaluates women’s representation through gender indicators in the PUEIS and SNI datasets and discusses their implications for the gender gap in the soil Science community from Mexico. The data was collected with an online semi-structured survey and the gender indicators selected were related to participation, gender gap, sexism, equal opportunities, exclusion, and academic performance.ResultsThe results show that in the PUEIS, 54% of members identify themselves as women and 46% as men. The gender gap shows equality in the total number of members. However, low-rank jobs, such as lecturers and lab technicians are women dominated, and the top-ranked positions as a full professor, associate professor, and research scientist are equal. One result to consider for the PUEIS members is that the younger generation, as is the older generation, is dominated by men. This could indicate a setback in intermediate generations’ progress toward achieving gender equality. In the case of SNI members, there is a gender gap problem; of members with a Ph.D. degree, only 38% are women, and the elite group of scientists with a Ph.D. at the top position is represented only by 24% of females.DiscussionThis work constitutes the first gender exercise for analyzing women’s participation in the soil Sciences in Mexico. From our perspective, it is not about competition in scientific careers between women and men; however, it is essential to recognize that gender inequalities are related to income, professional development, and science funding inequalities, and these disparities impact women more than men.

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

Today's Kinetoplastida form a diverse order of flagellated protozoans that have evolved from an ancient lineage, rooted near the base of the eukaryotic tree. The disease caused by some species of the Order Kinetoplastida have always plagued mankind, and today most are at least as prevalent as they have ever been. Kinetoplastid parasites cause disease in humans, animals and plants, severely affecting human health and retarding agriculture development in less developed countries. Sleeping sickness (caused by pathogenic subspecies ofTrypanosoma brucei), Chagas disease (caused byTrypanosoma cruzi) and the Leishmaniases (caused byLeishmania spp) are the major human diseases caused by kinetoplastids. According to the World Health Organization "sleeping sickness" affects more than 60 million men, women and children in 36 countries of sub-Saharan Africa, most of which are among the least developed countries in the world. In many of these countries sleeping sickness is currently epidemic, re-emerging in some as a greater cause of morbidity than evenHIV/AIDS.T. cruzicurrently infects 14 million people in Latin America. It is the agent ofChagas disease, the leading infectious cardiomyopathy in the world. Theleishmaniasesand the suffering they cause threaten 350 million women, men and children in 88 countries around the world, 72 of which are developing countries. In addition to their medical importance kinetoplastid parasites also cost developing nations millions of dollars in lost agricultural revenues, since other kinetoplastids are pestilences that strike agricultural produce from crops, to fish to cattle.

Background: Over 650 million people worldwide lack access to safe water supplies, and even among those who have gained access to ‘improved’ sources, water may be seasonally unreliable, far from homes, expensive, and provide insufficient quantity. Measurement of water access at the level of communities and households remains crude, and better measures of household water insecurity are urgently needed to inform needs assessments and monitoring and evaluation. We set out to assess the validity of a quantitative scale of household water insecurity, and to investigate (1) whether improvements to community water supply reduce water insecurity, (2) whether water interventions affect women’s psychological distress, and (3) the impacts of water insecurity on psychological distress, independent of socio-economic status, food security, and harvest quality. Methods and Findings: Measures were taken before and one to six months after a community water supply improvement in three villages in rural northern Ethiopia. Villages similar in size and access to water sources and other amenities did not receive interventions, and served as controls. Household water insecurity was assessed using a 21-item scale based on prior qualitative work in Ethiopia. Women’s psychological distress was assessed using the WHO Self-Reporting Questionnaire (SRQ-20). Respondents were either female heads of household or wives of the heads of household (n = 247 at baseline, n = 223 at endline); 123 households provided data at both rounds. The intervention was associated with a decline of approximately 2 points on the water insecurity scale between baseline and endline compared to the control (beta -1.99; 95% CI’s -3.15, -0.84). We did not find evidence of impact of the intervention on women’s psychological distress. Water insecurity was, however, predictive of psychological distress (p <0.01), independent of household food security and the quality of the previous year’s harvest. Conclusion: These results contribute to the construct validity of our water insecurity scale, and establish our approach to measuring water insecurity as a plausible means of evaluating water interventions. Improvements to community water supplies were effective in reducing household water insecurity, but not psychological distress, in this population. Water insecurity was an important predictor of psychological distress. This study contributes to an emerging literature on quantitative assessment of household water insecurity, and draws attention to the potential impact of improved access to water on women’s mental well-being.