This statistic depicts the average body weight of U.S. men aged 20 years and over from 1999 to 2016, by ethnicity. According to the data, the average male body weight for those that identified as non-Hispanic white has increased from 192.3 in 1999-2000 to 202.2 in 2015-2016.

In the United States, the median income for Black households in 2024 was 56,020 U.S. dollars. This represented a significant drop from the previous year. Since 1990, the median income of African American households grew from 40,820 U.S. dollars (adjusted to 2024 values).

Background: Researchers have reported gender differences in the association between perceived racial discrimination (PRD) and substance use including marijuana use (MU). A limited number of longitudinal studies, however, have documented the long-term effect of PRD during adolescence on subsequent MU in young adulthood.Objective: In the current longitudinal study, we tested gender differences in the association between baseline PRD during adolescence and subsequent MU during young adulthood within Black population.Methods: A cohort of 595 Black (278 male and 317 female) ninth grade students were followed for 13 years from 1999 (mean age 20) to 2012 (mean age 33). Participants were selected from an economically disadvantaged urban area in the Midwest, United States. The independent variable was PRD measured in 1999. The outcome was average MU between 2000 and 2012 (based on eight measurements). Covariates included age, socio-demographics (family structure, and parental employment), and substance use by friends and parents. Gender was the focal moderator. Linear regression was used for statistical analysis.Results: In the pooled sample, PRD in 1999 was not associated with average MU between 2000 and 2012. We did, however, find an interaction effect between baseline PRD and gender on average MU, suggesting stronger association for males than females. In gender-specific models, baseline PRD predicted average MU between 2000 and 2012 for males, but not for females.Conclusion: Exposure to PRD during late adolescence may have a larger role on MU of male than female Black young adults. Although we found that males are more vulnerable to the effects of PRD on MU, PRD should be prevented regardless of race, gender, and other social identities. While PRD is pervasive among Black Americans, exposure to PRD increase the risk of MU for Black males. Hence, substance use prevention efforts for Black males, in particular, should emphasize coping with PRD.

View monthly updates and historical trends for US Unemployed Persons: Black or African American Men Job Seeker Average Number of Methods Used for Seeking …

In 2023, the mean income of Black Bachelor's degree holders was ****** U.S. dollars, compared to ****** U.S. dollars for White Americans with a Bachelor's degree.

Graph and download economic data for Unemployment Rate - Black or African American (LNS14000006) from Jan 1972 to Sep 2025 about African-American, 16 years +, household survey, unemployment, rate, and USA.

In the fiscal year of 2019, 21.39 percent of active-duty enlisted women were of Hispanic origin. The total number of active duty military personnel in 2019 amounted to 1.3 million people.

Ethnicities in the United States The United States is known around the world for the diversity of its population. The Census recognizes six different racial and ethnic categories: White American, Native American and Alaska Native, Asian American, Black or African American, Native Hawaiian and Other Pacific Islander. People of Hispanic or Latino origin are classified as a racially diverse ethnicity.

The largest part of the population, about 61.3 percent, is composed of White Americans. The largest minority in the country are Hispanics with a share of 17.8 percent of the population, followed by Black or African Americans with 13.3 percent. Life in the U.S. and ethnicity However, life in the United States seems to be rather different depending on the race or ethnicity that you belong to. For instance: In 2019, native Hawaiians and other Pacific Islanders had the highest birth rate of 58 per 1,000 women, while the birth rae of white alone, non Hispanic women was 49 children per 1,000 women.

The Black population living in the United States has the highest poverty rate with of all Census races and ethnicities in the United States. About 19.5 percent of the Black population was living with an income lower than the 2020 poverty threshold. The Asian population has the smallest poverty rate in the United States, with about 8.1 percent living in poverty.

The median annual family income in the United States in 2020 earned by Black families was about 57,476 U.S. dollars, while the average family income earned by the Asian population was about 109,448 U.S. dollars. This is more than 25,000 U.S. dollars higher than the U.S. average family income, which was 84,008 U.S. dollars.

The leading causes of death among Black residents in the United States in 2023 included diseases of the heart, cancer, unintentional injuries, and stroke. The leading causes of death for African Americans generally reflect the leading causes of death for the entire United States population. However, a major exception is that death from assault or homicide is the seventh leading cause of death among African Americans but is not among the ten leading causes for the general population. Homicide among African Americans The homicide rate among African Americans has been higher than that of other races and ethnicities for many years. In 2023, around 9,284 Black people were murdered in the United States, compared to 7,289 white people. A majority of these homicides are committed with firearms, which are easily accessible in the United States. In 2023, around 13,350 Black people died by firearms. Cancer disparities There are also major disparities in access to health care and the impact of various diseases. For example, the incidence rate of cancer among African American males is the greatest among all ethnicities and races. Furthermore, although the incidence rate of cancer is lower among African American women than it is among white women, cancer death rates are still higher among African American women.

Graph and download economic data for Unemployment Rate - 16-19 Yrs., Black or African American (LNS14000018) from Jan 1972 to Sep 2025 about 16 to 19 years, African-American, household survey, unemployment, rate, and USA.

This statistic shows the median weekly earnings of full-time wage and salary workers in the United States by gender and ethnicity in the first quarter of 2025. The usual weekly earnings of a male Asian American wage worker was 1,822 U.S. dollars.

C-reactive protein (CRP) is a routinely measured blood biomarker for inflammation. Elevated levels of circulating CRP are associated with response to infection, risk for a number of complex common diseases, and psychosocial stress. The objective of this study was to compare the contributions of genetic ancestry, socioenvironmental factors, and inflammation-related health conditions to ethnic differences in C-reactive protein levels. We used multivariable regression to compare CRP blood serum levels between Black and White ethnic groups from the United Kingdom Biobank (UKBB) prospective cohort study. CRP serum levels are significantly associated with ethnicity in an age and sex adjusted model. Study participants who identify as Black have higher average CRP than those who identify as White, CRP increases with age, and females have higher average CRP than males. Ethnicity and sex show a significant interaction effect on CRP. Black females have higher average CRP levels than White females, whereas White males have higher average CRP than Black males. Significant associations between CRP, ethnicity, and genetic ancestry are almost completely attenuated in a fully adjusted model that includes socioenvironmental factors and inflammation-related health conditions. BMI, smoking, and socioeconomic deprivation all have high relative effects on CRP. These results indicate that socioenvironmental factors contribute more to CRP ethnic differences than genetics. Differences in CRP are associated with ethnic disparities for a number of chronic diseases, including type 2 diabetes, essential hypertension, sarcoidosis, and lupus erythematosus. Our results indicate that ethnic differences in CRP are linked to both socioenvironmental factors and numerous ethnic health disparities.

C-reactive protein (CRP) is a routinely measured blood biomarker for inflammation. Elevated levels of circulating CRP are associated with response to infection, risk for a number of complex common diseases, and psychosocial stress. The objective of this study was to compare the contributions of genetic ancestry, socioenvironmental factors, and inflammation-related health conditions to ethnic differences in C-reactive protein levels. We used multivariable regression to compare CRP blood serum levels between Black and White ethnic groups from the United Kingdom Biobank (UKBB) prospective cohort study. CRP serum levels are significantly associated with ethnicity in an age and sex adjusted model. Study participants who identify as Black have higher average CRP than those who identify as White, CRP increases with age, and females have higher average CRP than males. Ethnicity and sex show a significant interaction effect on CRP. Black females have higher average CRP levels than White females, whereas White males have higher average CRP than Black males. Significant associations between CRP, ethnicity, and genetic ancestry are almost completely attenuated in a fully adjusted model that includes socioenvironmental factors and inflammation-related health conditions. BMI, smoking, and socioeconomic deprivation all have high relative effects on CRP. These results indicate that socioenvironmental factors contribute more to CRP ethnic differences than genetics. Differences in CRP are associated with ethnic disparities for a number of chronic diseases, including type 2 diabetes, essential hypertension, sarcoidosis, and lupus erythematosus. Our results indicate that ethnic differences in CRP are linked to both socioenvironmental factors and numerous ethnic health disparities.

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Context

The gender pay gap or gender wage gap is the average difference between the remuneration for men and women who are working. Women are generally considered to be paid less than men. There are two distinct numbers regarding the pay gap: non-adjusted versus adjusted pay gap. The latter typically takes into account differences in hours worked, occupations were chosen, education, and job experience. In the United States, for example, the non-adjusted average female's annual salary is 79% of the average male salary, compared to 95% for the adjusted average salary.

The reasons link to legal, social, and economic factors, and extend beyond "equal pay for equal work".

The gender pay gap can be a problem from a public policy perspective because it reduces economic output and means that women are more likely to be dependent upon welfare payments, especially in old age.

This dataset aims to replicate the data used in the famous paper "The Gender Wage Gap: Extent, Trends, and Explanations", which provides new empirical evidence on the extent of and trends in the gender wage gap, which declined considerably during the 1980–2010 period.

Citation

fedesoriano. (January 2022). Gender Pay Gap Dataset. Retrieved [Date Retrieved] from https://www.kaggle.com/fedesoriano/gender-pay-gap-dataset.

Content

There are 2 files in this dataset: a) the Panel Study of Income Dynamics (PSID) microdata over the 1980-2010 period, and b) the Current Population Survey (CPS) to provide some additional US national data on the gender pay gap.

PSID variables:

NOTES: THE VARIABLES WITH fz ADDED TO THEIR NAME REFER TO EXPERIENCE WHERE WE HAVE FILLED IN SOME ZEROS IN THE MISSING PSID YEARS WITH DATA FROM THE RESPONDENTS’ ANSWERS TO QUESTIONS ABOUT JOBS WORKED ON DURING THESE MISSING YEARS. THE fz variables WERE USED IN THE REGRESSION ANALYSES THE VARIABLES WITH A predict PREFIX REFER TO THE COMPUTATION OF ACTUAL EXPERIENCE ACCUMULATED DURING THE YEARS IN WHICH THE PSID DID NOT SURVEY THE RESPONDENTS. THERE ARE MORE PREDICTED EXPERIENCE LEVELS THAT ARE NEEDED TO IMPUTE EXPERIENCE IN THE MISSING YEARS IN SOME CASES. NOTE THAT THE VARIABLES yrsexpf, yrsexpfsz, etc., INCLUDE THESE COMPUTATIONS, SO THAT IF YOU WANT TO USE FULL TIME OR PART TIME EXPERIENCE, YOU DON’T NEED TO ADD THESE PREDICT VARIABLES IN. THEY ARE INCLUDED IN THE DATA SET TO ILLUSTRATE THE RESULTS OF THE COMPUTATION PROCESS. THE VARIABLES WITH AN orig PREFIX ARE THE ORIGINAL PSID VARIABLES. THESE HAVE BEEN PROCESSED AND IN SOME CASES RENAMED FOR CONVENIENCE. THE hd SUFFIX MEANS THAT THE VARIABLE REFERS TO THE HEAD OF THE FAMILY, AND THE wf SUFFIX MEANS THAT IT REFERS TO THE WIFE OR FEMALE COHABITOR IF THERE IS ONE. AS SHOWN IN THE ACCOMPANYING REGRESSION PROGRAM, THESE orig VARIABLES AREN’T USED DIRECTLY IN THE REGRESSIONS. THERE ARE MORE OF THE ORIGINAL PSID VARIABLES, WHICH WERE USED TO CONSTRUCT THE VARIABLES USED IN THE REGRESSIONS. HD MEANS HEAD AND WF MEANS WIFE OR FEMALE COHABITOR.

1. intnum68: 1968 INTERVIEW NUMBER
2. pernum68: PERSON NUMBER 68
3. wave: Current Wave of the PSID
4. sex: gender SEX OF INDIVIDUAL (1=male, 2=female)
5. intnum: Wave-specific Interview Number
6. farminc: Farm Income
7. region: regLab Region of Current Interview
8. famwgt: this is the PSID’s family weight, which is used in all analyses
9. relhead: ER34103L this is the relation to the head of household (10=head; 20=legally married wife; 22=cohabiting partner)
10. age: Age
11. employed: ER34116L Whether or not employed or on temp leave (everyone gets a 1 for this variable, since our wage analyses use only the currently employed)
12. sch: schLbl Highest Year of Schooling
13. annhrs: Annual Hours Worked
14. annlabinc: Annual Labor Income
15. occ: 3 Digit Occupation 2000 codes
16. ind: 3 Digit Industry 2000 codes
17. white: White, nonhispanic dummy variable
18. black: Black, nonhispanic dummy variable
19. hisp: Hispanic dummy variable
20. othrace: Other Race dummy variable
21. degree: degreeLbl Agent's Degree Status (0=no college degree; 1=bachelor’s without advanced degree; 2=advanced degree)
22. degupd: degreeLbl Agent's Degree Status (Updated with 2009 values)
23. schupd: schLbl Schooling (updated years of schooling)
24. annwks: Annual Weeks Worked
25. unjob: unJobLbl Union Coverage dummy variable
26. usualhrwk: Usual Hrs Worked Per Week
27. labincbus: Labor Income from...

Diversity in Tech Statistics: In today's tech-driven world, discussions about diversity in the technology sector have gained significant traction. Recent statistics shed light on the disparities and opportunities within this industry. According to data from various sources, including reports from leading tech companies and diversity advocacy groups, the lack of diversity remains a prominent issue. For example, studies reveal that only 25% of computing jobs in the United States are held by women, while Black and Hispanic individuals make up just 9% of the tech workforce combined. Additionally, research indicates that LGBTQ+ individuals are underrepresented in tech, with only 2.3% of tech workers identifying as LGBTQ+. Despite these challenges, there are promising signs of progress. Companies are increasingly recognizing the importance of diversity and inclusion initiatives, with some allocating significant resources to address these issues. For instance, tech giants like Google and Microsoft have committed millions of USD to diversity programs aimed at recruiting and retaining underrepresented talent. As discussions surrounding diversity in tech continue to evolve, understanding the statistical landscape is crucial in fostering meaningful change and creating a more inclusive industry for all. Editor’s Choice In 2021, 7.9% of the US labor force was employed in technology. Women hold only 26.7% of tech employment, while men hold 73.3% of these positions. White Americans hold 62.5% of the positions in the US tech sector. Asian Americans account for 20% of jobs, Latinx Americans 8%, and Black Americans 7%. 83.3% of tech executives in the US are white. Black Americans comprised 14% of the population in 2019 but held only 7% of tech employment. For the same position, at the same business, and with the same experience, women in tech are typically paid 3% less than men. The high-tech sector employs more men (64% against 52%), Asian Americans (14% compared to 5.8%), and white people (68.5% versus 63.5%) compared to other industries. The tech industry is urged to prioritize inclusion when hiring, mentoring, and retaining employees to bridge the digital skills gap. Black professionals only account for 4% of all tech workers despite being 13% of the US workforce. Hispanic professionals hold just 8% of all STEM jobs despite being 17% of the national workforce. Only 22% of workers in tech are ethnic minorities. Gender diversity in tech is low, with just 26% of jobs in computer-related sectors occupied by women. Companies with diverse teams have higher profitability, with those in the top quartile for gender diversity being 25% more likely to have above-average profitability. Every month, the tech industry adds about 9,600 jobs to the U.S. economy. Between May 2009 and May 2015, over 800,000 net STEM jobs were added to the U.S. economy. STEM jobs are expected to grow by another 8.9% between 2015 and 2024. The percentage of black and Hispanic employees at major tech companies is very low, making up just one to three percent of the tech workforce. Tech hiring relies heavily on poaching and incentives, creating an unsustainable ecosystem ripe for disruption. Recruiters have a significant role in disrupting the hiring process to support diversity and inclusion. You May Also Like To Read Outsourcing Statistics Digital Transformation Statistics Internet of Things Statistics Computer Vision Statistics

According to a survey conducted among British consumers, men expected to spend more on Black Friday 2025 than women. On average, male consumers would spend around 147 British pounds.

Vanishing twins, spared cohorts, and the difference in birthweight between the frailest White and Black infants in the United States

https://doi.org/10.5061/dryad.xksn02vp9

Description of the data and file structure

The data are time series for 288 months beginning January 1995 and ending December 2018.

The variable dictionary is as follows.

Variable Dictionary

tperimwN=count of periviable male Nhwhite twins

tperimwN=count of periviable male NHwhite twins

tperifbN=count of periviable female NHblack twins

tperifbN=count of periviable female NHblack twins

_

spmumwbw=mean birthweight for singleton nhwhite males

spmdmwbw=median birthweight for singleton nhwhite males

spp1mwbw= first percentile birthweight for singleton nhwhite males

spp5mwbw =fifth percentile birthweight for singleton nhwhite males

spmufwbw=mean birthweight for singleton nhwhite females

spmdfwbw=median birthweight for singleton nhwhite females

spp1fwbw...

Prevalence of mild cognitive impairment by socio-demographics.

The American black bear (Ursus americanus) has one of the broadest geographic distributions of any mammalian carnivore in North America. Populations occur from high to low elevations and from mesic to arid environments, and their demographic traits have been documented in a wide variety of environments. However, the demography of American black bears in semiarid environments, which comprise a significant portion of the geographic range, is poorly documented. To fill this gap in understanding, we used data from a long-term mark-recapture study of black bears in the semiarid environment of eastern Utah, USA. Cub and yearling survival were low and adult survival was high relative to other populations. Adult life stages had the highest reproductive value, comprised the largest proportion of the population, and exhibited the highest elasticity contribution to the population growth rate (i.e., λ). Vital rates of black bears in this semiarid environment are skewed toward higher survival of adu..., Mark-Recapture study We estimated survival rates from long-term mark-recapture data gathered as part of a 27-year study on American black bears of the East Tavaputs Plateau. During the first 12 years of the study (June to August 1991-2003) female bears were captured and radio-collared, and all bears were tagged in the ear, except for cubs and yearlings. For the entire study (1992 – 2019), collared females were visited in their dens annually during their winter hibernation to count newborn cubs and surviving yearlings. Age of individual bears was determined by 2 methods: (1) direct observation of cubs or yearlings (i.e., year of birth was known) or (2) cementum annuli analysis of a cross-section of the root of an extracted premolar (Palochak, 2004; Willey, 1974). The data we used to derive survival and fecundity rates consisted of the ID_number, cohort (cub, yearling, subadult, prime-aged adult, and old adult), age in years, sex (female, male, unknown), number of cubs, number of yearling..., , # Demography of American black bears (Ursus americanus) in a semiarid environment

https://doi.org/10.5061/dryad.98sf7m0t8

Description of the data and file structure

Files and variables

File: Age-Specific_Survivorship.csv

Description:Â

This CSV file contains data collected from a mark-recapture study during 1991 - 2019. We calculated the age-specific average survival rate for each cohort. The average survival rate of each cohort was later used in the matrix transition model as matrix elements to retrieve important demographic information about this population of North American black bears (Ursus americanus) found in a semiarid environment.Â

Variables

• Cohort:Â Yearling = 1 year to 2 years;Â Subadult = 2 years to 4 years;Â Prime-aged Adult = 4 years to 14 years;Â Old Adult = 15 years and older.
• Sex:Â M = male; F = female; U = unknown
• Cubs and Yearlings:Â NV = not visited; number = number of cubs or yearlings presen...

Weighted proportion [and 95% confidence interval] of mild cognitive impairment by social disconnectedness and perceived isolation.

AS – Average score Race – Whether the student is white, black or Hispanic; Male – 1 if male, 0 if female; ParEd – Parents Education by Category; HoursKids – Time parents spend with kids, in hours; GradestImport – Where parents believe that grades are important (1 = important); Attend – How many times the student attends the afterschool event; HourStudy – How much time student studies at home (in hours); Sports – 1 if a student plays sports, otherwise 0