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The types of jobs people hold often shift over time as they attain education, build new skills, and experience changes in their lives and personal preferences. An examination of this dynamic through the lenses of sex and age is particularly compelling and insightful. This BLS report provides an in-depth analysis of the occupation employment profiles of women and men, by age, in 2024.
This report presents historical and recent labor force data for women and men from the Current Population Survey (CPS), a national monthly sample survey of approximately 60,000 households, conducted by the U.S. Census Bureau for the U.S. Bureau of Labor Statistics. Unless otherwise noted, data are annual averages from the CPS. (For a detailed description of the source of the data and an explanation of the concepts and definitions used, see the technical notes.)
The occupation employment profiles of women and men varied significantly across different age groups. In this section, we look at the trends that emerge when looking through data by age.
The employment–population ratio represents the number of employed people as a percentage of the civilian noninstitutional population age 16 and over. For women, this measure steadily climbed from 31.3 percent in 1948 to a series high of 57.5 percent in 2000. By contrast, men’s employment–population ratio followed the opposite trend, decreasing from 83.5 percent in 1948 to 71.9 percent in 2000, with a further decline to 62.4 percent in 2020 (largely attributed to the economic impacts of the COVID-19 pandemic). After 2000, the ratios for both women and men generally declined. In 2024, the employment–population ratio was 55.2 percent for women and 65.2 percent for men. (See chart 1.)
The employment–population ratio gap between women and men varied significantly by age in 2024. About one-third of 16- to 19-year-old women and men were employed (33.1 percent and 31.3 percent, respectively), compared with roughly two-thirds of women and men ages 20 to 24 (65.2 percent and 67.3 percent, respectively). However, this gap widened for those age 25 and over and peaked among those ages 35 to 44, where women’s employment–population ratio (76.1 percent) was 11.7 percentage points lower than men’s (87.8 percent). The employment–population ratios for women and men both fell significantly for ages 55 to 64 (58.8 percent and 69.5 percent, respectively). For those age 65 and over, the ratio was 15.7 percent for women and 22.6 percent for men. (See table 1.)
| Age | Women | Men | Difference |
|---|---|---|---|
Total, 16 years and over | 55.2 | 65.2 | -10.0 |
16 to 19 years | 33.1 | 31.3 | 1.8 |
20 to 24 years | 65.2 | 67.3 | -2.1 |
25 to 34 years | 74.8 | 85.5 | -10.7 |
35 to 44 years | 76.1 | 87.8 | -11.7 |
45 to 54 years | 74.7 | 85.5 | -10.8 |
55 to 64 years | 58.8 | 69.5 | -10.7 |
65 years and over | 15.7 | 22.6 | -6.9 |
Source: U.S. Bureau of Labor Statistics. | |||
Educational attainment and employment status are closely related. (Educational attainment data published by BLS typically pertain to people age 25 and over because most people have completed their schooling by age 25.) Prior to the 2000s, employed men were more likely to hold a bachelor’s degree or higher than employed women. However, this trend reversed in the mid-2000s as women began pursuing higher education at a faster rate than men. By the mid-2000s, the percentage of employed women holding a bachelor’s degree and higher (33.5 percent in 2005) surpassed that of employed men (32.6 percent in 2005). After 2005, the education gap continued to grow, with 49.0 percent of employed women holding a bachelor’s degree or higher in 2024, compared with 41.3 percent of employed men. (See chart 2.)
Notably, this education gap varied by age. In 2024, among workers age 65 and over, men held a slight edge, with 45.0 percent holding a bachelor’s degree and higher, compared with 39.7 percent of women. By contrast, employed women ages 25 to 64 were more likely to hold a bachelor’s degree and higher than were employed men. Within that age range, the largest gap was between employed women and men ages 25 to 34, where 52.4 percent of women had a bachelor’s degree and higher, compared with 39.6 percent of men. (See table 2.)
| Sex and age | Total | Less than a high school diploma | High school graduates | Some college | Bachelor's degree and higher |
|---|---|---|---|---|---|
Women, 16 years and over | 100.0 | 6.0 | 22.3 | 26.6 | 45.1 |
16 to 19 years | 100.0 | 46.6 | 28.9 | 23.2 | 1.2 |
20 to 24 years | 100.0 | 3.7 | 30.3 | 40.0 | 26.0 |
25 to 34 years | 100.0 | 3.1 | 20.4 | 24.1 | 52.4 |
35 to 44 years | 100.0 | 4.5 | 18.9 | 24.2 | 52.5 |
45 to 54 years | 100.0 | 5.3 | 19.9 | 24.6 | 50.1 |
55 to 64 years | 100.0 | 5.1 | 24.9 | 27.9 | 42.2 |
65 years and over | 100.0 | 5.3 | 25.6 | 29.5 | 39.7 |
Men, 16 years and over | 100.0 | 8.7 | 29.1 | 24.2 | 38.1 |
16 to 19 years | 100.0 | 47.3 | 36.8 | 15.1 | 0.8 |
20 to 24 years | 100.0 | 6.3 | 42.3 | 32.8 | 18.6 |
25 to 34 years | 100.0 | 5.8 | 30.5 | 24.0 | 39.6 |
35 to 44 years | 100.0 | 7.7 | 26.1 | 23.0 | 43.2 |
45 to 54 years | 100.0 | 8.8 | 26.3 | 23.2 | 41.7 |
55 to 64 years | 100.0 | 8.0 | 28.4 | 24.6 | 38.9 |
65 years and over | 100.0 | 6.9 | 24.0 | 24.0 | 45.0 |
Note: Due to rounding, the sum of percent distributions may not equal 100. Source: U.S. Bureau of Labor Statistics. | |||||
The largest share of working women age 16 years and over, 30.3 percent, were employed in professional and related occupations in 2024. By comparison, 20.0 percent of men worked in this occupational group. Another large segment of women, 23.8 percent, worked in sales and office occupations in 2024, whereas 13.9 percent of men were employed in this field. Additionally, 20.0 percent of women worked in service occupations, higher than the 13.2 percent of men employed in this occupational group.
Within professional and related occupations, women’s representation varied significantly. For instance, 10.4 percent of women were employed in healthcare practitioners and technical occupations, compared with 3.0 percent of their male counterparts. Similarly, 9.3 percent of women were employed in education, training, and library occupations, while 3.0 percent of men were employed in these occupations. (See table 3.)
| Occupation | Total | Women | Men | Percent of employed women | Percent of employed men | Difference in percent employed |
|---|---|---|---|---|---|---|
Total, 16 years and over | 161,346 | 76,033 | 85,313 | 100.0 | 100.0 | 0.0 |
Management, business, and financial operations occupations | 30,602 | 13,989 | 16,613 | 18.4 | 19.5 | -1.1 |
Management occupations | 20,657 | 8,640 | 12,017 | 11.4 | 14.1 | -2.7 |
Business and financial operations occupations | 9,945 | 5,349 | 4,596 | 7.0 | 5.4 | 1.6 |
Professional and related occupations | 40,142 | 23,039 | 17,103 | 30.3 | 20.0 | 10.3 |
Computer and mathematical occupations | 6,386 | 1,686 | 4,700 | 2.2 | 5.5 | -3.3 |
Architecture and engineering occupations | 3,552 | 613 | 2,940 | 0.8 | 3.4 | -2.6 |
Life, physical, and social science occupations | 1,877 | 952 | 925 | 1.3 | 1.1 | 0.2 |
Community and social service occupations | 2,950 | 2,054 | 896 | 2.7 | 1.1 | 1.7 |
Legal occupations | 1,832 | 992 | 840 | 1.3 | 1.0 | 0.3 |
Education, training, and library occupations | 9,587 | 7,036 | 2,551 | 9.3 | 3.0 | 6.3 |
Arts, design, entertainment, sports, and media occupations | 3,483 | 1,770 | 1,713 | 2.3 | 2.0 | 0.3 |
Healthcare practitioners and technical occupations | 10,475 | 7,936 | 2,539 | 10.4 | 3.0 | 7.5 |
Service occupations | 26,452 | 15,206 | 11,246 | 20.0 | 13.2 | 6.8 |
Healthcare support occupations | 5,456 | 4,615 | 841 | 6.1 | 1.0 | 5.1 |
Protective service occupations | 3,110 | 783 | 2,327 | 1.0 | 2.7 | -1.7 |
Food preparation and serving related occupations | 8,061 | 4,376 | 3,685 | 5.8 | 4.3 | 1.4 |
Building and grounds cleaning and maintenance occupations | 5,770 | 2,347 | 3,422 | 3.1 | 4.0 | -0.9 |
Personal care and service occupations | 4,055 | 3,084 | 971 | 4.1 | 1.1 | 2.9 |
Sales and office occupations | 29,885 | 18,061 | 11,825 | 23.8 | 13.9 | 9.9 |
Sales and related occupations | 14,090 | 6,754 | 7,337 | 8.9 | 8.6 | 0.3 |
Office and administrative support occupations | 15,795 | 11,307 | 4,488 | 14.9 | 5.3 | 9.6 |
Natural resources, construction, and maintenance occupations | 14,391 | 861 | 13,530 | 1.1 | 15.9 | -14.7 |
Farming, fishing, and forestry occupations | 970 | 269 | 701 | 0.4 | 0.8 | -0.5 |
Construction and extraction occupations | 8,520 | 370 | 8,150 | 0.5 | 9.6 | -9.1 |
Installation, maintenance, and repair occupations | 4,901 | 222 | 4,680 | 0.3 | 5.5 | -5.2 |
Production, transportation, and material moving occupations | 19,873 | 4,877 | 14,996 | 6.4 | 17.6 | -11.2 |
Production occupations | 7,944 | 2,291 | 5,653 | 3.0 | 6.6 | -3.6 |
Transportation and material moving occupations | 11,930 | 2,586 | 9,344 | 3.4 | 11.0 | -7.6 |
Source: U.S. Bureau of Labor Statistics. | ||||||
By contrast, women were underrepresented in certain professional and related occupations. Among working women, 2.2 percent were employed in computer and mathematical occupations and 0.8 percent were employed in architecture and engineering occupations. Conversely, men were much more likely to be employed in these occupations (5.5 percent and 3.4 percent, respectively), highlighting the persisting sex disparity in these high-paying fields.
Likewise, outside of professional and related occupations, women were less likely than men to work in management, business, and financial operations occupations, with 18.4 percent of women holding these occupations, compared with 19.5 percent of men. Finally, women were significantly underrepresented in natural resources, construction, and maintenance occupations (1.1 percent compared with 15.9 percent of men) and in production, transportation, and material moving occupations (6.4 percent compared with 17.6 percent of men).
The employment patterns in the six major occupational groups varied significantly across different age groups for both women and men. These occupations have different education requirements, and shifting between these groups has implications for earnings over a lifetime.
Women ages 16 to 19 were more likely than men of the same ages to be employed in service occupations (44.9 percent compared with 36.9 percent) and in sales and office occupations (33.8 percent compared with 22.0 percent). Additionally, about one-fifth of men in this age group were employed in production, transportation, and material moving occupations, compared with less than one-tenth of women ages 16 to 19. (See chart 3.)
Women ages 20 to 24 were less likely than their younger counterparts to work in service occupations (31.9 percent) and in sales and office occupations (27.2 percent). However, they were still more likely to work in these occupations than their male peers (20.9 percent of men ages 20 to 24 were employed in service occupations and 17.9 percent were employed in sales and office occupations). In 2024, 20.8 percent of men ages 20 to 24 worked in production, transportation, and material moving occupations and 18.4 percent worked in natural resources, construction, and maintenance occupations—much higher than the shares of women in these occupations, across all age groups.
Within service occupations, young women and men were more likely to be employed in food preparation and serving related occupations than women and men age 25 and over. In 2024, 28.9 percent of women ages 16 to 19 and 13.9 percent of women ages 20 to 24 held jobs in these occupations. A smaller share of men worked in these occupations—24.0 percent of those ages 16 to 19 and 10.3 percent of those ages 20 to 24. However, occupational patterns shifted with age. (See chart 4.)
For women, healthcare support occupations became the most prevalent service occupation after age 25. For men ages 25 to 34, the most prevalent service occupation was food preparation and serving related occupations; for men age 35 and over, building and grounds cleaning and maintenance occupations were the most common occupations.
Historically, people ages 25 to 54 are more likely to be employed in professional and related occupations: these occupations tend to require higher levels of education and, in some cases, offer higher earnings.1 Moreover, people ages 25 to 54 are the most likely to participate in the labor force and be employed.2 In 2024, about one-third of employed women ages 25 to 54 worked in these occupations, with 35.2 percent of women ages 25 to 34, 33.7 percent of women ages 35 to 44, and 32.0 percent of women ages 45 to 54 holding these occupations. Men in the same age groups also gravitated towards professional occupations, though at lower rates than women: 22.5 percent of men ages 25 to 34, 22.3 percent of men ages 35 to 44, and 20.4 percent of men ages 45 to 54. (See chart 3.)
Women ages 25 to 54 who worked in professional and related occupations were predominantly employed in healthcare and education. Among employed women ages 25 to 34, 12.9 percent worked in healthcare practitioners and technical occupations and 8.8 percent worked in education, training, and library occupations, compared with about 3 percent of men in each of these fields. Similarly, women ages 35 to 44 were more likely to be employed in healthcare (11.9 percent) and education (10.1 percent) than were men of the same ages (3.7 percent were employed in healthcare and 3.1 percent in education). Among employed people ages 45 to 54, about 11 percent of women were employed in each of these two fields, compared with around 3 percent of men. (See chart 5.)
Employed men ages 25 to 54 were more likely to work in computer and mathematical occupations than were employed women. Men ages 25 to 34 and ages 35 to 44 (both at about 7 percent) were more than twice as likely to work in computer occupations than women in these age groups (both at around 3 percent). Among men ages 45 to 54, 5.8 percent worked in computer occupations, compared with 1.9 percent of women. Employed men were also more likely to work in architecture and engineering occupations: around 3 percent to 4 percent of men between the ages of 25 to 54, compared with around 1 percent of women across the same age groups.
Like the shift towards professional and related occupations, women and men ages 25 to 54 were also more likely to work in management, business, and financial operations occupations compared to younger workers. The share of workers ages 20 to 24 in these occupations was approximately 8 percent for both women and men, and this share increased sharply to 17.9 percent for women and 15.8 percent for men ages 25 to 34. However, employed men ages 45 to 54 were more likely than women in the same age group to work in management, business, and financial operations (23.8 percent versus 21.8 percent, respectively). (See chart 3.)
Interestingly, women age 55 and over were more likely to be employed in sales and office occupations than were women ages 25 to 54. This may reflect a combination of factors, including historical differences in educational and career opportunities, the dynamic nature of women’s working lives across different life stages, and broader trends where women in certain fields might experience disparities in earnings and retirement timing. Moreover, among women age 65 and over specifically, nearly one-third worked in sales and office occupations (29.6 percent) and another one-fifth worked in service occupations (20.1 percent), higher than the shares of women ages 25 to 64 employed in those respective occupations. Nearly one in four employed men age 45 and over were in management, business, and financial operations occupations, higher than the share of employed men in younger age groups. (See chart 3.)
Within sales and office occupations, office and administrative support occupations were more common among women age 55 and older: 18.3 percent of those ages 55 to 64 and 18.6 percent of those age 65 and older were employed in these occupations. By contrast, only about 5 percent of men in both the 55 to 64 and 65 and older age groups worked in these occupations. (See chart 6.)
Employed women and men ages 25 to 54 were more likely to be working in professional and related occupations than women and men in other age groups. Based on earnings data for workers age 16 and over, within professional and related occupations, women often were more likely to work in occupations with lower pay. For instance, men were more likely to be employed in higher-paying occupations, such as computer and mathematical occupations (with median weekly earnings of $1,921) and architecture and engineering occupations ($1,873), while women were more heavily represented in healthcare practitioners and technical occupations ($1,472) and education, training, and library occupations ($1,217). (See chart 8.)
Over a career, these differences in earnings can accumulate, impacting not only women’s financial stability but also their ability to invest in career development and education, which can be crucial for their career advancement.3 Legal occupations ($1,904) were an exception, with women more likely to be in these high-earning occupations. However, within legal occupations, only 42.0 percent of lawyers—the occupation with the highest median earnings among legal occupations—were women.4 (See chart 8.)
Historically, the employment–population ratio for men was much higher than for women, but this gap has narrowed throughout the history of the series. In 1948, the ratio was 31.3 percent for women and 83.5 percent for men, compared with 55.2 percent for women and 65.2 percent for men in 2024. Starting in the mid-2000s, the share of employed women holding a bachelor's degree or higher surpassed the share of men, a significant shift in educational attainment. In 2024, 49.0 percent of employed women had achieved this level of education, compared with 41.3 percent of men.
The occupation employment profiles of women and men varied significantly across different age groups, reflecting changing life circumstances, educational attainment, skill accumulation, and personal preferences. Among the employed, women were more likely than men to work in professional and related occupations, particularly in healthcare and education, while men were more likely to be employed in natural resources, construction, and maintenance occupations, as well as in production, transportation, and material moving occupations.
The data also revealed notable differences in occupation patterns with age. For instance, younger workers were more likely to be employed in service occupations, employed women ages 25 to 54 were more likely to work in professional occupations, and employed men ages 25 to 54 were more likely to work in professional occupations and in management, business, and financial operations occupations. Professional and related occupations often require higher levels of education but do not necessarily come with higher earnings. Within professional occupations, men ages 25 to 54 were more likely to be employed in higher paying occupations, like computer and engineering occupations, while women of the same ages were more represented in lower paying healthcare and education occupations. The findings highlight differences in women's and men’s workforce participation by age group and the persisting sex disparities in certain high-paying fields.
1 According to data from the Occupational Requirements Survey (ORS), 66.9 percent of workers in architecture and engineering occupations and 55.1 percent in computer and mathematical occupations held jobs that required at least a bachelor’s degree as their minimum formal education, in 2024. Similar education requirements were observed in other occupations, with 56.4 percent of those employed in education instruction and 23.2 percent of those employed in healthcare practitioners and technical occupations holding jobs that required at least a bachelor’s degree. ORS estimates for 2024 are preliminary.
2 For this reason, analyses often focus on workers ages 25 to 54.
3 Rakesh Kochhar, “The enduring grip of the gender pay gap” (Pew Research Center, March 2023), https://www.pewresearch.org/social-trends/2023/03/01/the-enduring-grip-of-the-gender-pay-gap/; The simple truth about the gender pay gap – 2022 update (American Association of University Women (AAUW), 2022), https://www.aauw.org/app/uploads/2022/12/SimpleTruth_12.22_2.1-002.pdf.
4 “Employed persons by detailed occupation, sex, race, and Hispanic or Latino ethnicity, annual averages 2024” (U.S. Bureau of Labor Statistics, last modified January 29, 2025), https://www.bls.gov/cps/data/aa2024/cpsaat11.htm.
To access additional CPS data about women and men, visit the 2024 Annual Average tables page.
The estimates in this report were obtained from the Current Population Survey (CPS), a national monthly sample survey of approximately 60,000 eligible households that provides a wide range of information on the labor force, employment, and unemployment. The survey is conducted for the U.S. Bureau of Labor Statistics (BLS) by the U.S. Census Bureau using a scientifically selected national sample, with coverage in all 50 states and the District of Columbia.
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The civilian noninstitutional population is made up of people 16 years of age and older who reside in any of the 50 states or the District of Columbia; are not confined to institutions, such as nursing homes and prisons; and are not on Active Duty in the Armed Forces.
The employed are people who, during the survey reference week (which, in CPS, is generally the week including the 12th day of the month), (a) did any work at all as paid employees, (b) worked in their own business or profession or on their own farm, or (c) worked 15 or more hours as unpaid workers in a family member’s business. People who were temporarily absent from their jobs or business because of illness, vacation, a labor dispute, or another reason are also counted as employed.
The employment–population ratio represents the number of employed people as a percentage of the population.
Information on occupation applies to the job held during the reference week. People with two or more jobs are classified into the occupation in which they worked the greatest number of hours. The occupation classification of CPS data is based on the 2018 Census occupational classification system, which is derived from the 2018 Standard Occupation Classification (SOC). For more information, see the Occupational and Industry classifications used in the CPS.
Usual weekly earningsreflect earnings before taxes and other deductions and include any overtime pay, commissions, or tips usually received (at the main job in the case of multiple jobholders). Since January 1994, respondents have been asked to identify the easiest way for them to report earnings (hourly, weekly, biweekly, twice monthly, monthly, annually, or other) and how much they usually earn in the reported time period. Earnings reported on a basis other than weekly are converted to a weekly equivalent. The term “usual” is determined by each respondent’s own understanding of the term. If the respondent asks for a definition of “usual,” interviewers are instructed to define the term as more than half the weeks worked during the past 4 or 5 months.
Earnings estimates are presented as median usual weekly earnings of full-time wage and salary workers. All self-employed workers, both incorporated and unincorporated, are excluded from CPS earnings estimates. The median is the point at which half of all workers had higher earnings and half had lower earnings.
The weekly earnings estimates in this report reflect information collected from one-fourth of the CPS monthly survey and averaged for the calendar year. The earnings comparisons in this report are on a broad level and do not control for many factors that can be important in explaining earnings differences, such as job skills and responsibilities, work experience, and specialization.
Statistics based on the CPS are subject to both sampling and nonsampling error. When a sample, rather than an entire population, is surveyed, there is a chance that the sample estimates may differ from the true population values they represent. There are two reasons this occurs: sampling error and nonsampling error. Sampling error occurs because samples differ by chance. The sampling error variability is measured by the standard error of the estimate. There is about a 90-percent chance, or level of confidence, that an estimate based on a sample will differ by no more than 1.6 standard errors from the true population value because of sampling error. BLS analyses are generally conducted at the 90-percent level of confidence.
All other types of error are referred to as nonsampling error. Nonsampling error can occur for many reasons, including the failure to sample a segment of the population, inability to obtain information for all respondents in the sample, inability or unwillingness of respondents to provide correct information, and errors made in the collection or processing of data. For more information on sampling and non-sampling errors in the CPS and estimating standard errors, see the Reliability of estimates from the CPS.