Gender Pay Gap*

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Ratio of women's median earnings to men's median earnings for all full-time, year-round workers, presented as The 2024 Annual Data Release used data from 2018-2022 for this measure.

A gender pay gap persists across industries in the United States, with women earning an estimated 80 cents for every dollar a man earns.1 The pay gap remains even though women make up the majority of college-educated adults in the U.S., and decades after the Equal Pay Act of 1963 made it illegal to pay men and women different salaries for similar work.2 Unequal pay by gender can harm women’s health and wellbeing. Women who earn a lower income for the same work are more likely to suffer from mood disorders including depression and anxiety.3 Larger gaps in pay and gender inequities are also associated with worse mortality outcomes, poorer self-rated health, and increased disability.4-6 Eliminating the gender pay gap, on the other hand, could significantly reduce poverty, especially among single, female-headed households.7 Over 16% of children live in poverty across the country, and as a result these children may experience lasting educational, financial, and health effects into adulthood.10  

Find strategies to address Gender Pay Gap*

Data and methods

Data Source

American Community Survey, 5-year estimates

The American Community Survey (ACS) is a nationwide survey designed to provide communities with a fresh look at how they are changing. It is a critical element in the Census Bureau's reengineered decennial census program. The ACS collects and produces population and housing information every year instead of every ten years, and publishes both one-year and five-year estimates. We use American Community Survey data for measures of social and economic factors.

Website to download data
For more detailed methodological information

Key Measure Methods

Gender Pay Gap is a ratio

Gender Pay Gap is expressed as "cents on the dollar," or women's median earnings in cents compared to every dollar (100 cents) of men's median earnings. 

Women's median earnings are the level of earnings where half of full-time, year-round, female workers are earning more than this value, and half are earning less. Men's median earnings follow the same definition for male workers.

Caution should be used when comparing these estimates across years

Caution should be used when comparing data across years as data comes from overlapping 5-year spans. Additionally, margins of error for 5-year estimates containing data collected in 2020 increased compared to prior 5-year estimates. For more information about data comparability please visit Comparing 2022 American Community Survey Data.

Measure limitations

Pay inequities are even more stark for most women of color. The pay gap is the largest for American Indian Alaska Native women.8 This measure is not disaggregated by race, which could help quantify the effects of a combined gender and race pay gap affecting opportunity and outcomes for women of color. 

The American Community Survey captures a binary representation of gender. People living intersectional identities (e.g., transgender women) experience compounding power differentials, which are not captured in these data. The Gender Pay Gap measure is a representation of median annual earnings; studies using median hourly or weekly earnings show an even larger gender pay gap.9 


The numerator is women's median annual earnings for full-time, year-round workers ages 16 and older with earnings in a county.


The denominator is men's median annual earnings for full-time, year-round workers ages 16 and older with earnings in a county.

Can This Measure Be Used to Track Progress

This measure can be used to track progress with some caveats. It is important to note that the estimate provided in the Health Snapshots uses a 5-year average of which may make year-to-year changes harder to observe. However, for counties with a population greater than 20,000 individuals, single-year estimates can be obtained from the resource listed in Finding More Data.

Finding More Data

Disaggregation means breaking data down into smaller, meaningful subgroups. Disaggregated data are often broken down by characteristics of people or where they live. Disaggregated data can reveal inequalities that are otherwise hidden. These data can be disaggregated by:

  • Gender
  • Race
  • Education
  • Income
  • Subcounty Area

You can find data on earnings stratified by income, education, and gender in table S2001, and you can calculate the gender pay gap by race using tables B20017A-G. For many communities, you can access these same tables at the census tract or census block level. 


1 Gould E, Schieder J, Geier K. What is the gender pay gap and is it real? Economic Policy Institute. 2016.  

2 Fry R. U.S. women near milestone in the college-educated labor force. 2019.  

3 Platt J, Prins S, Bates L, Keyes K. Unequal depression for equal work? How the wage gap explains gendered disparities in mood disorders. 2016;149:1-8.   

4 Kawachi I, Kennedy BP, Gupta V, Prothrow-Stith D. Women's status and the health of women and men: A view from the States. Social science & medicine. 1999;48(1):21-32. 

5 Milner A, Kavanagh A, Scovelle AJ, et al. Gender equality and health in high-income countries: A systematic review of within-country indicators of gender equality in relation to health outcomes. Women's Health Reports. 2021;2(1):113-123. 

6 Jun HJ, Subramanian SV, Gortmaker S, Kawachi I. A multilevel analysis of women's status and self-rated health in the United States. Journal of the American Medical Women's Association (1972). 2004;59(3):172-180. 

7Kramer KZ, Myhra LL, Zuiker VS, et al. Comparison of poverty and income disparity of single mothers and fathers across three decades: 1990-2010. Gender Issues. 2016;33:22-41.

8 Payscale. 2024 Gender pay gap report.

9 Lips H. The gender pay gap: Challenging the rationalizations. Perceived equity, discrimination, and the limits of human capital models. Sex Roles. 2013;68:169-185. 

10 Benson C. U.S. Poverty Rate Varies by Age Groups. U.S. Census Bureau. 2023.