In 2023 the poverty rate in the United States was highest among people between 18 and 24, with a rate of 16 percent for male Americans and a rate of 21 percent for female Americans. The lowest poverty rate for both men and women was for those aged between 45 and 54. What is the poverty line? The poverty line is a metric used by the U.S. Census Bureau to define poverty in the United States. It is a specific income level that is considered to be the bare minimum a person or family needs to meet their basic needs. If a family’s annual pre-tax income is below this income level, then they are considered impoverished. The poverty guideline for a family of four in 2021 was 26,500 U.S. dollars. Living below the poverty line According to the most recent data, almost one-fifth of African Americans in the United States live below the poverty line; the most out of any ethnic group. Additionally, over 7.42 million families in the U.S. live in poverty – a figure that has held mostly steady since 1990, outside the 2008 financial crisis which threw 9.52 million families into poverty by 2012. The poverty gender gap Wage inequality has been an ongoing discussion in U.S. discourse for many years now. The poverty gap for women is most pronounced during their child-bearing years, shrinks, and then grows again in old age. While progress has been made on the gender pay gap over the last 30 years, there are still significant disparities, even in occupations that predominantly employ men. Additionally, women are often having to spend more time attending to child and household duties than men.

According to a 2020 survey, the coronavirus (COVID-19) crisis will increase female poverty worldwide. Globally, *** million women aged 15 years and older will be living on less than 1.90 U.S. dollars per day in 2021, compared to *** million men. The gender poverty gap is expected to increase by 2030, as women will still be the majority of the world's extreme poor.

In 2021, the national poverty rate of Venezuela was reported at 94.46 percent. In comparison, more women than men were estimated to live in poverty. Up to 95.1 percent of the female population in Venezuela lived in poverty, whereas the male poverty rate stood 1.34 percentage points lower. Younger segments of the Venezuelan population registered higher poverty rates than the national average.

While many data gaps remain, we know that women are vulnerable to extreme poverty because they face greater burdens of unpaid work, have fewer assets and productive resources than men, are exposed to gender-based violence (GBV), and are more likely to be forced into early marriage —all factors that reduce their ability to participate fully in the economy and to reap the benefits of growth. This paper begins with a discussion of these factors and how they predispose women to extreme poverty. It then presents opportunities for reducing women’s extreme poverty through gender-sensitive programming in three key sectors: agriculture, education, and reproductive health. It outlines the challenges inherent in this type of work, including a need to better connect how sector-specific outcomes—which reflect improvements in women’s lives—also contribute to poverty reduction. Recommendations for moving forward include considering the unique links between gender and extreme poverty early in the project design process, taking into consideration underlying cultural practices and gender norms, and collecting rigorous, sex-disaggregated data to evaluate the effects of interventions on women.

Abstract

The 2018 Dhaka Low Income Area Gender, Inclusion, and Poverty (DIGNITY) survey attempts to fill in the data and knowledge gaps on women's economic empowerment in urban areas, specifically the factors that constrain women in slums and low-income neighborhoods from engaging in the labor market and supplying their labor to wage earning or self-employment. While an array of national-level datasets has collected a wide spectrum of information, they rarely comprise all of the information needed to study the drivers of Female Labor Force Participation (FLFP). This data gap is being filled by the primary data collection of the specialized DIGNITY survey; it is representative of poor urban areas and is specifically designed to address these limitations. The DIGNITY survey collected information from 1,300 urban households living in poor areas of Dhaka in 2018 on a range of issues that affect FLFP as identified through the literature. These range from household composition and demographic characteristics to socioeconomic characteristics such as detailed employment history and income (including locational data and travel details); and from technical and educational attributes to issues of time use, migration history, and attitudes and perceptions.

The DIGNITY survey was designed to shed light on poverty, economic empowerment, and livelihood in urban areas of Bangladesh. It has two main modules: the traditional household module (in which the head of household is interviewed on basic information about the household); and the individual module, in which two respondents from each household are interviewed individually. In the second module, two persons - one male and one female from each household, usually the main couple, are selected for the interview. The survey team deployed one male and one female interviewer for each household, so that the gender of the interviewers matched that of the respondents. Collecting economic data directly from a female and male household member, rather than just the head of the household (who tend to be men in most cases), was a key feature of the DIGNITY survey.

Geographic coverage

The DIGNITY survey is representative of low-income areas and slums of the Dhaka City Corporations (North and South, from here on referred to as Dhaka CCs), and an additional low-income site from the Greater Dhaka Statistical Metropolitan Area (SMA).

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling procedure followed a two-stage stratification design. The major features include the following steps (they are discussed in more detail in a copy of the study's report and the sampling document located in "External Resources"):

FIRST STAGE: Selection of the PSUs

Low-income primary sampling units (PSUs) were defined as nonslum census enumeration areas (EAs), in which the small-sample area estimate of the poverty rate is higher than 8 percent (using the 2011 Bangladesh Poverty Map). The sampling frame for these low-income areas in the Dhaka City Corporations (CCs) and Greater Dhaka is based on the population census of 2011. For the Dhaka CCs, all low-income census EAs formed the sampling frame. In the Greater Dhaka area, the frame was formed by all low-income census EAs in specific thanas (i.e. administrative unit in Bangladesh) where World Bank project were located.

Three strata were used for sampling the low-income EAs. These strata were defined based on the poverty head-count ratios. The first stratum encompasses EAs with a poverty headcount ratio between 8 and 10 percent; the second stratum between 11 and 14 percent; and the third stratum, those exceeding 15 percent.

Slums were defined as informal settlements that were listed in the Bangladesh Bureau of Statistics' slum census from 2013/14. This census was used as sampling frame of the slum areas. Only slums in the Dhaka City Corporations are included. Again, three strata were used to sample the slums. This time the strata were based on the size of the slums. The first stratum comprises slums of 50 to 75 households; the second 76 to 99 households; and the third, 100 or more households. Small slums with fewer than 50 households were not included in the sampling frame. Very small slums were included in the low-income neighborhood selection if they are in a low-income area.

Altogether, the DIGNITY survey collected data from 67 PSUs.

SECOND STAGE: Selection of the Households

In each sampled PSU a complete listing of households was done to form the frame for the second stage of sampling: the selection of households. When the number of households in a PSU was very large, smaller sections of the neighborhood were identified, and one section was randomly selected to be listed. The listing data collected information on the demographics of the household to determine whether a household fell into one of the three categories that were used to stratify the household sample:

i) households with both working-age male and female members; ii) households with only a working-age female; iii) households with only a working-age male.

Households were selected from each stratum with the predetermined ratio of 16:3:1. In some cases there were not enough households in categories (ii) and (iii) to stick to this ratio; in this case all of the households in the category were sampled, and additional households were selected from the first category to bring the total number of households sampled in each PSU to 20.

The total sample consisted of 1,300 households (2,378 individuals).

Sampling deviation

The sampling for 1300 households was planned after the listing exercise. During the field work, about 115 households (8.8 percent) could not be interviewed due to household refusal or absence. These households were replaced with reserved households in the sample.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaires for the survey were developed by the World Bank, with assistance from the survey firm, DATA. Comments were incorporated following the pilot tests and practice session/pretest.

Cleaning operations

Collected data was entered into a computer by using the customized MS Access data input software developed by Data Analysis and Technical Assistance (DATA). Once data entry was completed, two different techniques were employed to check consistency and validity of data as follows:

1. Five (5%) percent of the filled-in questionnaire was checked against entered data to measure the transmission error or typos, and;
2. A logical consistency checking technique was employed to identify inconsistencies using SPSS and or STATA software.

Alaska had the highest male to female ratio in the United States in 2020, with ***** men for every 100 women. The male to female ratio was lowest in the District of Columbia, with **** men for every 100 women. The final frontier Alaska, which was purchased from the Russian Empire in 1867, is the largest state in the U.S. and one of the newest states, having been admitted to the U.S. in 1959. Although oil production dominates the economy, Alaska has a very high poverty rate and consistently has the highest unemployment rate in the country. It’s a man’s world Alaska is one of 10 states in the U.S. that has more men than women. The male to female ratio in the United States as a whole is about even, but as the population ages, there tend to be more females than males. Even though the sex ratio in the U.S. is almost one to one, a little more than ** percent of all females participated in the labor force in 2021, compared with **** percent of men.

BackgroundUnderstanding the past-year prevalence of male-perpetrated intimate partner violence (IPV) and risk factors is essential for building evidence-based prevention and monitoring progress to Sustainable Development Goal (SDG) 5.2, but so far, population-based research on this remains very limited. The objective of this study is to compare the population prevalence rates of past-year male-perpetrated IPV and nonpartner rape from women’s and men’s reports across 4 countries in Asia and the Pacific. A further objective is to describe the risk factors associated with women’s experience of past-year physical or sexual IPV from women’s reports and factors driving women’s past-year experience of partner violence.Methods and findingsThis paper presents findings from the United Nations Multi-country Study on Men and Violence in Asia and the Pacific. In the course of this study, in population-based cross-sectional surveys, 5,206 men and 3,106 women aged 18–49 years were interviewed from 4 countries: Cambodia, China, Papua New Guinea (PNG), and Sri Lanka. To measure risk factors, we use logistic regression and structural equation modelling to show pathways and mediators. The analysis was not based on a written plan, and following a reviewer’s comments, some material was moved to supplementary files and the regression was performed without variable elimination. Men reported more lifetime perpetration of IPV (physical or sexual IPV range 32.5%–80%) than women did experience (physical or sexual IPV range 27.5%–67.4%), but women’s reports of past-year experience (physical or sexual IPV range 8.2%–32.1%) were not very clearly different from men’s (physical or sexual IPV range 10.1%–34.0%). Women reported much more emotional/economic abuse (past-year ranges 1.4%–5.7% for men and 4.1%–27.7% for women). Reports of nonpartner rape were similar for men (range 0.8%–1.9% in the past year) and women (range 0.4%–2.3% in past year), except in Bougainville, where they were higher for men (11.7% versus 5.7%). The risk factor modelling shows 4 groups of variables to be important in experience of past-year sexual and/or physical IPV: (1) poverty, (2) all childhood trauma, (3) quarrelling and women’s limited control in relationships, and (4) partner factors (substance abuse, unemployment, and infidelity). The population attributable fraction (PAF) was largest for quarrelling often, but the second greatest PAF was for the group related to exposure to violence in childhood. The relationship control variable group had the third highest PAF, followed by other partner factors. Currently married women were also more at risk. In the structural model, a resilience pathway showed less poverty, higher education, and more gender-equitable ideas were connected and conveyed protection from IPV. These are all amenable risk factors. This research was cross-sectional, so we cannot be sure of the temporal sequence of exposure, but the outcome being a past-year measure to some extent mitigates this problem.ConclusionsPast-year IPV indicators based on women’s reported experience that were developed to track SDG 5 are probably reasonably reliable but will not always give the same prevalence as may be reported by men. Report validity requires further research. Interviews with men to track past-year nonpartner rape perpetration are feasible and important. The findings suggest a range of factors are associated with past-year physical and/or sexual IPV exposure; of particular interest is the resilience pathway suggested by the structural model, which is highly amenable to intervention and explains why combining economic empowerment of women and gender empowerment/relationship skills training has been successful. This study provides additional rationale for scaling up violence prevention interventions that combine economic and gender empowerment/relationship skills building of women, as well as the value of investing in girls’ education with a view to long-term violence reduction.

Extensive scholarly work engages with the growing number of women in legislatures around the world and highlights their role as advocates of women’s interests during parliamentary decision-making processes. This article sheds light on the reactions of men MPs (members of parliament) to this trend by uncovering how women’s numerical strength in party parliamentary groups shapes the issues that their men colleagues emphasize when speaking about women during plenary debates. I argue that, the higher the share of women in a party parliamentary group, the more will men representatives emphasize women’s interests in the context of issues they can easily relate to – either because the issues lie in men’s area of responsibility according to ideas about traditional role distributions in the society, e.g. the financing of gender equality projects, or because they are part of broader patterns of societal inequality, such as poverty or health. I provide empirical evidence for this argument based on original time-series cross-sectional data from plenary debates in six German states between 2005 and 2021 using a structural topic model. These findings shed light on men’s role as critical actors and have implications for gender equality and the functioning of representative democracy more broadly.

Objective: To assess the effect of experienced stigma on depth of multidimensional poverty of persons with severe mental illness (PSMI) in Delhi, India, controlling for gender, age and caste. Design: Matching case (hospital)–control (population) study. Setting: University Hospital (cases) and National Capital Region (controls), India. Participants: A case–control study was conducted from November 2011 to June 2012. 647 cases diagnosed with schizophrenia or affective disorders were recruited and 647 individuals of same age, sex and location of residence were matched as controls at a ratio of 1:2:1. Individuals who refused consent or provided incomplete interview were excluded. Main outcome measures: Higher risk of poverty due to stigma among PSMI. Results: 38.5% of PSMI compared with 22.2% of controls were found poor on six dimensions or more. The difference in multidimensional poverty index was 69% between groups with employment and income of the main contributors. Multidimensional poverty was strongly associated with stigma (OR 2.60, 95% CI 1.27 to 5.31), scheduled castes/scheduled tribes/other backward castes (2.39, 1.39 to 4.08), mental illness (2.07, 1.25 to 3.41) and female gender (1.87, 1.36 to 2.58). A significant interaction between stigma, mental illness and gender or caste indicates female PSMI or PSMI from 'lower castes' were more likely to be poor due to stigma than male controls (p<0.001) or controls from other castes (p<0.001). Conclusions: Public stigma and multidimensional poverty linked to SMI are pervasive and intertwined. In particular for low caste and women, it is a strong predictor of poverty. Exclusion from employment linked to negative attitudes and lack of income are the highest contributors to multidimensional poverty, increasing the burden for the family. Mental health professionals need to be aware of and address these issues.

In 2025, Costa Rica was the Latin American country with the highest gender gap index, with 0.786 points. Another Central American country, Belize, had the worst score in the region with 0.7 points. This means that, on average, women in this country have 30 percent less opportunities than men in education, health, the economy, and politics.

Gender Inequality in Latin America
Based on a 2023 survey conducted among the populace in each nation, Mexico has been perceived as having the least gender-based wage equality, receiving a score of 0.5 out of 1, which is the lowest. In contrast, Barbados is regarded as the most gender-equal among the LATAM countries. Furthermore, the labor market exhibits a male bias, as women have consistently experienced higher unemployment rates over the years, with a rate of 11.3 percent as of 2021. Additionally, it is more common across the countries to observe a greater proportion of females experiencing higher poverty rates, with Mexican and Colombian women being the primary two groups representing this circumstance.

Literacy gender gap
As education progresses in both the educational and labor sectors, the goal is to ensure that basic literacy is accessible to everyone. However, research data reveals that the gender parity index for adult and youth literacy in Latin America remains at around 1 percent. This means that one woman out of 100 is less likely to possess literacy skills compared to men. Furthermore, this rate shows a significant gender gap, with 93.71 percent of females in this region accounting for this skill. Consequently, in the labor field, there are implications for skilled workers due to this literacy gap, resulting in higher rates of unemployment, a lack of training, and a non-educational population. This issue affects approximately 28.4 percent of women in Latin America.

According to the Gender Inequality Index (GII), Denmark and Norway were the most gender equal countries in the world in 2023, reporting an index of ***** and *****, respectively. The Gender Inequality Index measures inequality between women and men in three dimensions: reproductive health, empowerment, and the labor market. A low GII value indicates low inequality between women and men and vice versa. Yemen was considered the least gender equal country that same year. Gender inequality in the workplace The most prominent source of gender inequality is the workplace, often captured by the gender pay gap. In 2023, women still earned one percent less than their male counterparts with the same qualification and the same job. Women are less represented in senior roles and top management positions, with only one third percent of companies worldwide having a woman in leadership positions. The same situation can be observed in government roles - only 17 out of 195 countries worldwide have ever had a woman in the highest position of executive power. Future outlook Numbers on how long it will take to close gender gaps highly differ between regions. In Europe, it is estimated that it will take around 67 years to achieve equality between the genders. In East Asia and the Pacific, on the other hand, it is projected to take 189 years. New data shows that the COVID-19 pandemic has increased female poverty worldwide and widened the gender poverty gap even further. Heightened female poverty will also negatively impact the Gender Inequality Index (GII).

In 2022, the total male population living in poverty in India was about ** million. By contrast, the number of females in poverty during the same time period was around ** million.

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.

In 2021, women were the head of most households in Venezuela, as it was reported that the national share of female household heads was 53.8 percent, compared to 46.2 percent of households with a male head. Among all Venezuelan states, Portuguesa registered the highest share of households led by women, with 69.6 percent. The state with the highest share of households led by men was Amazonas, with 66.1 percent. Women in Venezuela are more likely to live in poverty than men.

Across the whole world, women earn less than men. Worldwide, they earn ** percent of total income before tax. However, there are striking regional differences; whereas female workers in Europe and North America earn around ** percent of the total income, women in the Middle East and North Africa earn less than ** percent of it.

Literacy in India has been increasing as more and more people receive a better education, but it is still far from all-encompassing. In 2023, the degree of literacy in India was about 77 percent, with the majority of literate Indians being men. It is estimated that the global literacy rate for people aged 15 and above is about 86 percent. How to read a literacy rateIn order to identify potential for intellectual and educational progress, the literacy rate of a country covers the level of education and skills acquired by a country’s inhabitants. Literacy is an important indicator of a country’s economic progress and the standard of living – it shows how many people have access to education. However, the standards to measure literacy cannot be universally applied. Measures to identify and define illiterate and literate inhabitants vary from country to country: In some, illiteracy is equated with no schooling at all, for example. Writings on the wallGlobally speaking, more men are able to read and write than women, and this disparity is also reflected in the literacy rate in India – with scarcity of schools and education in rural areas being one factor, and poverty another. Especially in rural areas, women and girls are often not given proper access to formal education, and even if they are, many drop out. Today, India is already being surpassed in this area by other emerging economies, like Brazil, China, and even by most other countries in the Asia-Pacific region. To catch up, India now has to offer more educational programs to its rural population, not only on how to read and write, but also on traditional gender roles and rights.