In 2023, California had the highest Hispanic population in the United States, with over 15.76 million people claiming Hispanic heritage. Texas, Florida, New York, and Illinois rounded out the top five states for Hispanic residents in that year. History of Hispanic people Hispanic people are those whose heritage stems from a former Spanish colony. The Spanish Empire colonized most of Central and Latin America in the 15th century, which began when Christopher Columbus arrived in the Americas in 1492. The Spanish Empire expanded its territory throughout Central America and South America, but the colonization of the United States did not include the Northeastern part of the United States. Despite the number of Hispanic people living in the United States having increased, the median income of Hispanic households has fluctuated slightly since 1990. Hispanic population in the United States Hispanic people are the second-largest ethnic group in the United States, making Spanish the second most common language spoken in the country. In 2021, about one-fifth of Hispanic households in the United States made between 50,000 to 74,999 U.S. dollars. The unemployment rate of Hispanic Americans has fluctuated significantly since 1990, but has been on the decline since 2010, with the exception of 2020 and 2021, due to the impact of the coronavirus (COVID-19) pandemic.
As of 2023, around 37.99 million people of Mexican descent were living in the United States - the largest of any Hispanic group. Puerto Ricans, Salvadorans, Cubans, and Dominicans rounded out the top five Hispanic groups living in the U.S. in that year.
The number of people of Hispanic origin living in the United States has increased around 80 percent from 2000 to 2023. During this last year, about 65.22 million people of Hispanic origin were living in the United States. California and Texas ranked as the states with the highest number of Hispanic origin people as of 2023.
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This list ranks the 51 states in the United States by Hispanic American Indian and Alaska Native (AIAN) population, as estimated by the United States Census Bureau. It also highlights population changes in each states over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
In 2022, around 48.59 percent of New Mexico's population was of Hispanic origin, compared to the national percentage of 19.45. California, Texas, and Arizona also registered shares over 30 percent. The distribution of the U.S. population by ethnicity can be accessed here.
This dataset is compiled from the Mexican Population and Household Census from 2005 (Conteo de Poblacion y Vivienda 2005). The data is at municipal level (of almost 2,000 municipalities) and is comprised of number of localities and their populations by the size of localities. Where there were inconsistencies in municipality boundaries between the Mexican data and the available shapefile, the data have been combined in the appropriate fashion. The polygons that contain data from more than one municipality are labeled with all municipality names. Values of -1 represent no available data.
This dataset is compiled from the Mexican Population and Household Census from 2005 (Conteo de Poblacion y Vivienda 2005). The data is at municipal level (of almost 2,000 municipalities) and is comprised of total population, population by age groups, population by sex, average age by sex and the male to female ratio. Where there were inconsistencies in municipality boundaries between the Mexican data and the available shapefile, the data have been combined in the appropriate fashion. The polygons that contain data from more than one municipality are labeled with all municipality names. Values of -1 represent no available data.
Out of a total of nearly **** million Mexican emigrants around the world in 2020, almost **** million relocated to the United States. The second most popular country of destination for emigrants of this Latin American nation was Canada followed by Spain. In 2019, nearly ** percent of Mexican emigrants living abroad were women.
This study was designed to systematically examine the similarities and differences of experience among four groups of adolescents: Mexicans (born of Mexican parents and residing in Mexico), Mexican immigrants (born of Mexican parents in Mexico and now residing in the United States), second-generation Mexican Americans (born and raised in the United States of Mexican immigrant parents), and White Americans (born and raised in the United States of white, non-Hispanic, U.S.-born parents). Specifically, the study explores how family orientation (i.e., familism and family conflict) and achievement orientation differ among these groups. The participants were 189 adolescents (96 girls and 93 boys) between the ages of 13 and 18 who were attending public middle and high schools. The participants were equally divided among the four groups. Data for the Mexican sample were gathered in 1991 and 1992 in Guanajuato, one of three Mexican states from which a majority of emigrants to the United States originate. Data for the other three groups were gathered in 1992 from public schools in California. The data collection methods consisted of classroom observations, ethnographic interviews, and tests which were conducted in either English, Spanish, or both according to the students' preference and proficiency. The interviews covered demographic, life-history, and migration-related information as well as issues related to their experiences at school and with their families and peers. The interview included a number of psychological tests: Familism Scale (Sabogal et al.,1987), Family Conflict Scale (Beavers, Hampson, and Hulgus, 1985), Sentence Completion Test (De Vos, 1973), Problem Situation Test (De Vos, 1973), and Thematic Apperception Tests (Murray, 1943). The Murray Research Archive holds the completed interview booklets as well as audiotapes of interviews. A follow-up of the study is possible with the collaboration of the contributor. Audio Data Availability Note: This study contains audio data that have been digitized. There are 284 audio files available.
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BackgroundFew studies have examined weight transitions in contemporary multi-ethnic populations spanning early childhood through adulthood despite the ability of such research to inform obesity prevention, control, and disparities reduction.Methods and ResultsWe characterized the ages at which African American, Caucasian, and Mexican American populations transitioned to overweight and obesity using contemporary and nationally representative cross-sectional National Health and Nutrition Examination Survey data (n = 21,220; aged 2–80 years). Age-, sex-, and race/ethnic-specific one-year net transition probabilities between body mass index-classified normal weight, overweight, and obesity were estimated using calibrated and validated Markov-type models that accommodated complex sampling. At age two, the obesity prevalence ranged from 7.3% in Caucasian males to 16.1% in Mexican American males. For all populations, estimated one-year overweight to obesity net transition probabilities peaked at age two and were highest for Mexican American males and African American females, for whom a net 12.3% (95% CI: 7.6%-17.0%) and 11.9% (95% CI: 8.5%-15.3%) of the overweight populations transitioned to obesity by age three, respectively. However, extrapolation to the 2010 U.S. population demonstrated that Mexican American males were the only population for whom net increases in obesity peaked during early childhood; age-specific net increases in obesity were approximately constant through the second decade of life for African Americans and Mexican American females and peaked at age 20 for Caucasians.ConclusionsAfrican American and Mexican American populations shoulder elevated rates of many obesity-associated chronic diseases and disparities in early transitions to obesity could further increase these inequalities if left unaddressed.
In 2023, almost 2.42 million female Hispanics in the United States were aged between 30 and 34 years. In that same year, about 4.83 million male Hispanics were between the ages of 35 and 44 years old.
Incoming border crossing/entry data 2006 for vehicles, containers, passengers and pedestrians. The data represents activity at the port level on the U.S.-Canadian and U.S.-Mexican land border and international ferry crossings. The data is provided to BTS by the U.S. Department of Homeland Security - Customs and Border Protection Missing and/or Null values were filled with -1
https://www.icpsr.umich.edu/web/ICPSR/studies/35032/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/35032/terms
This dataset was produced in the 1990s by Myron Gutmann and others at the University of Texas to assess demographic change in European- and Mexican-origin populations in Texas from the mid-nineteenth to early-twentieth centuries. Most of the data come from manuscript records for six rural Texas counties - Angelina, DeWitt, Gillespie, Jack, Red River, and Webb - for the U.S. Censuses of 1850-1880 and 1900-1910, and tax records where available. Together, the populations of these counties reflect the cultural, ethnic, economic, and ecological diversity of rural Texas. Red River and Angelina Counties, in Eastern Texas, had largely native-born white and black populations and cotton economies. DeWitt County in Southeast Texas had the most diverse population, including European and Mexican immigrants as well as native-born white and black Americans, and its economy was divided between cotton and cattle. The population of Webb County, on the Mexican border, was almost entirely of Mexican origin, and economic activities included transportation services as well as cattle ranching. Gillespie County in Central Texas had a mostly European immigrant population and an economy devoted to cropping and livestock. Jack County in North-Central Texas was sparsely populated, mainly by native-born white cattle ranchers. These counties were selected to over-represent the European and Mexican immigrant populations. Slave schedules were not included, so there are no African Americans in the samples for 1850 or 1860. In some years and counties, the Census records were sub-sampled, using a letter-based sample with the family as the primary sampling unit (families were chosen if the surname of the head began with one of the sample letters for the county). In other counties and years, complete populations were transcribed from the Census microfilms. For details and sample sizes by county, see the County table in the Original P.I. Documentation section of the ICPSR Codebook, or see Gutmann, Myron P. and Kenneth H. Fliess, How to Study Southern Demography in the Nineteenth Century: Early Lessons of the Texas Demography Project (Austin: Texas Population Research Center Papers, no. 11.11, 1989).
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This list ranks the 499 cities in the Arkansas by Hispanic Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
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Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2021 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..The 2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.
This dataset represents the popular last names in the United States for Hispanic.
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View the live USD/MXN rate, historical performance, and forecasts for the Mexican Peso. Stay up to date with charts, data, and analysis from Trading Economics.
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This list ranks the 14 cities in the Baldwin County, AL by Hispanic American Indian and Alaska Native (AIAN) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
In January 2018, 798 Hispanic/Latino adults living in the United States were recruited through Qualtrics Panels to complete a survey in English or Spanish. Respondents were diverse in their nativity (e.g., 52% Mexican or Mexican American; 17% Puerto Rican; 8.5% Cuban). The survey included the following measures: -Demographic and Health Information – Demographic and Health Data Questionnaire (DHDQ). This researcher-constructed questionnaire is designed to obtain participant information such as: (a) race/ethnicity, (b) age, (c) gender, (d) sexual orientation, (e) relationship status, (f) household income, (g) generational status, (h) education level, (i) presence of chronic health conditions, (j) self-reported height and weight, (k) overall health status, (l) native language and proficient language(s), (m) number of health care visits in the past year, and (n) perceived weight. -Media and Technology Usage and Attitudes Scale (MTUAS). The Media and Technology Usage and Attitudes Scale is a 60-item scale used to measure the frequency of use from specific forms of media and attitudes toward technology (Rosen, Whaling, Carrier, Cheever, & Rokkum, 2013). The scale consists of eleven media usage subscales and four attitude subscales. For the purposes of this study, only the smartphone usage subscale will be included (9 items). Prompts assessing the frequency of technology use stated: “Please indicate how often you do each of the following…” and asked about smartphone usage habits on a scale from 1(Never) to 10 (All the time). Higher scores are indicative of more technology use. The MTUAS was found to show sufficient proof of reliability for smartphone usage subscale (α = .93). Validity has also been shown through comparisons with measures of daily media usage hours, technology-related anxiety, and the Internet Addiction Test (Rosen et al., 2013). -The Sedentary Behavior Questionnaire (SBQ). The Sedentary Behavior Questionnaire is an 18-item scale designed to assess nine different sedentary behaviors including the use of technological devices, hobbies, and sitting due to transportation and work (Rosenberg et al., 2010). The measure is designed to assess sedentary behaviors over weekdays as well as the weekend and then are multiplied to estimate the sum amounts of sedentary hours during a week/weekend. The scale consisted of nine items with answer choices ranging from 1 (None) to 9 (6 hours or more). The current study will slightly alter the SBQ as some of the items may be dated in regards to the technology. An example is “sitting listening to music on the radio, tapes, or CDs.” The examples used in the items will be reflective of sedentary forms of technology used nowadays. The SBQ has been found to be a reliable measure for sedentary behaviors as intraclass correlation coefficients found that the items were sufficient for both weekday (.64-.90) and weekends (.51-.93). Validity of the measure was also sufficient as partial correlations were used to compare the self-reported ratings of the SBQ to accelerometer measures of activity. The study also found that in comparison to the International Physical Activity Questionnaire and body mass index, there were significant correlations with both male and female samples (Rosenberg et al., 2010). -PHQ-9- English: The Patient Health Questionnaire (PHQ-9). The PHQ-9 is a 9-item instrument that measures depressive symptoms (Kroenke, Spitzer, & Williams, 2001). Instructions on the PHQ-9 are as follows: “Over the last 2 weeks, how often have you been bothered by any of the following problems?” The assessment uses a 4-point Likert-type scale with responses ranging from 0 (not at all) to 3 (nearly every day). Scores for PHQ-9 scale are determined by assigning a score to each response ranging from 0 to 3 and then summing the responses. The PHQ-9 score can range from 0 to 27. Higher scores on the measure indicate higher levels of depressive symptoms. -Health Promoting Behaviors – Health Promoting Lifestyle Profile II (HPLP-II). The HPLP-II is a 52-item inventory designed to measure engagement in behaviors that characterize a health-promoting lifestyle (Walker, Sechrist, Pender, 1995). The HPLPII is comprised of a scale and six subscales, which include Spiritual Growth, Interpersonal Relations, Nutrition, Physical Activity, Health Responsibility, and Stress Management. Only the Nutrition (9 items) and Physical Activity (8 items) subscales will be used for the current study. Instructions on the HPLP-II are to indicate level of engagement in each listed behavior using a Likert-type scale, with responses ranging from 1 (never) to 4 (routinely). Scores for the HPLP-II scale and subscale are determined by calculating means for each. Higher scores on the scale and subscales indicate higher levels of engagement in the assessed health promoti... Visit https://dataone.org/datasets/sha256%3A947312a2e719300f2006c0c8f48294d38a5b6a63ad0f31869ed48ea690048cde for complete metadata about this dataset.
The graph shows the Hispanic population in the United States in 2022 and offers a forecast until 2060. According to this projection, there will be almost 98 million people of Hispanic descent in the United States in 2060.
In 2023, California had the highest Hispanic population in the United States, with over 15.76 million people claiming Hispanic heritage. Texas, Florida, New York, and Illinois rounded out the top five states for Hispanic residents in that year. History of Hispanic people Hispanic people are those whose heritage stems from a former Spanish colony. The Spanish Empire colonized most of Central and Latin America in the 15th century, which began when Christopher Columbus arrived in the Americas in 1492. The Spanish Empire expanded its territory throughout Central America and South America, but the colonization of the United States did not include the Northeastern part of the United States. Despite the number of Hispanic people living in the United States having increased, the median income of Hispanic households has fluctuated slightly since 1990. Hispanic population in the United States Hispanic people are the second-largest ethnic group in the United States, making Spanish the second most common language spoken in the country. In 2021, about one-fifth of Hispanic households in the United States made between 50,000 to 74,999 U.S. dollars. The unemployment rate of Hispanic Americans has fluctuated significantly since 1990, but has been on the decline since 2010, with the exception of 2020 and 2021, due to the impact of the coronavirus (COVID-19) pandemic.