BackgroundAddressing contemporary anti-Asian racism and its impacts on health requires understanding its historical roots, including discriminatory restrictions on immigration, citizenship, and land ownership. Archival secondary data such as historical census records provide opportunities to quantitatively analyze structural dynamics that affect the health of Asian immigrants and Asian Americans. Census data overcome weaknesses of other data sources, such as small sample size and aggregation of Asian subgroups. This article explores the strengths and limitations of early twentieth-century census data for understanding Asian Americans and structural racism.MethodsWe used California census data from three decennial census spanning 1920–1940 to compare two criteria for identifying Asian Americans: census racial categories and Asian surname lists (Chinese, Indian, Japanese, Korean, and Filipino) that have been validated in contemporary population data. This paper examines the sensitivity and specificity of surname classification compared to census-designated “color or race” at the population level.ResultsSurname criteria were found to be highly specific, with each of the five surname lists having a specificity of over 99% for all three census years. The Chinese surname list had the highest sensitivity (ranging from 0.60–0.67 across census years), followed by the Indian (0.54–0.61) and Japanese (0.51–0.62) surname lists. Sensitivity was much lower for Korean (0.40–0.45) and Filipino (0.10–0.21) surnames. With the exception of Indian surnames, the sensitivity values of surname criteria were lower for the 1920–1940 census data than those reported for the 1990 census. The extent of the difference in sensitivity and trends across census years vary by subgroup.DiscussionSurname criteria may have lower sensitivity in detecting Asian subgroups in historical data as opposed to contemporary data as enumeration procedures for Asians have changed across time. We examine how the conflation of race, ethnicity, and nationality in the census could contribute to low sensitivity of surname classification compared to census-designated “color or race.” These results can guide decisions when operationalizing race in the context of specific research questions, thus promoting historical quantitative study of Asian American experiences. Furthermore, these results stress the need to situate measures of race and racism in their specific historical context.

BackgroundOur current understanding of Asian American mortality patterns has been distorted by the historical aggregation of diverse Asian subgroups on death certificates, masking important differences in the leading causes of death across subgroups. In this analysis, we aim to fill an important knowledge gap in Asian American health by reporting leading causes of mortality by disaggregated Asian American subgroups.Methods and FindingsWe examined national mortality records for the six largest Asian subgroups (Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese) and non-Hispanic Whites (NHWs) from 2003-2011, and ranked the leading causes of death. We calculated all-cause and cause-specific age-adjusted rates, temporal trends with annual percent changes, and rate ratios by race/ethnicity and sex. Rankings revealed that as an aggregated group, cancer was the leading cause of death for Asian Americans. When disaggregated, there was notable heterogeneity. Among women, cancer was the leading cause of death for every group except Asian Indians. In men, cancer was the leading cause of death among Chinese, Korean, and Vietnamese men, while heart disease was the leading cause of death among Asian Indians, Filipino and Japanese men. The proportion of death due to heart disease for Asian Indian males was nearly double that of cancer (31% vs. 18%). Temporal trends showed increased mortality of cancer and diabetes in Asian Indians and Vietnamese; increased stroke mortality in Asian Indians; increased suicide mortality in Koreans; and increased mortality from Alzheimer’s disease for all racial/ethnic groups from 2003-2011. All-cause rate ratios revealed that overall mortality is lower in Asian Americans compared to NHWs.ConclusionsOur findings show heterogeneity in the leading causes of death among Asian American subgroups. Additional research should focus on culturally competent and cost-effective approaches to prevent and treat specific diseases among these growing diverse populations.

In an increasingly diverse United States (US) population, racial disparities in preterm birth outcomes continue to widen. In this study, we examined temporal trends and risk of preterm birth among Asian American women over a quarter century (1992–2018). This is a retrospective cohort study using the 1992–2018 Natality data files. We conducted joinpoint regression analyses to examine trends in preterm birth among Asian Americans and non-Hispanic (NH) Whites. Bivariate and multivariable analyses were used to identify risk factors associated with preterm birth among Asian Americans and their ethnic sub-groups as compared to NH-Whites. There were a total of 251,278 preterm births among Asian American women, corresponding to a rate of 10.0%, which was relatively stable over time. The incidence of extremely, very and moderate-to-late preterm birth among Asian Americans was 0.4%, 0.9% and 8.7% respectively. Overall, Asian American women exhibited lower adjusted odds (OR = 0.92; 95% CI: 0.88–0.97) of preterm birth than their NH-White counterparts. Comparing Asian American subgroups to NH-Whites, Filipinas and Vietnamese mothers had increased adjusted odds, whereas Chinese, Korean, Japanese and Asian Indian women showed decreased adjusted odds for preterm birth. The risk of preterm birth varied among the ethnic subgroups of Asian Americans in the United States. Future studies should explore the socio-cultural and environmental nuances that might explain these differences.

Striking racial/ethnic disparities exist in pregnancy outcomes among various racial/ethnic To determine the incidence and risk factors associated with stillbirth in Asian-American women. We conducted this retrospective cohort study using the United States Birth and Fetal Death data files 2014–2017. We used the fetuses‐at‐risk approach to generate stillbirth trends by gestational age among Non-Hispanic (NH)-White and Asian-American births during the study period. We calculated the adjusted risk of stillbirth for Asian-Americans, overall, and for each Asian-American subgroup: Asian Indians, Koreans, Chinese, Vietnamese, Japanese and Filipinos, with NH-Whites as the referent category. Of the 715,297 births that occurred among Asian-Americans during the study period, stillbirth incidence rate was 3.86 per 1000 births. From the gestational age of 20 weeks through 41 weeks, the stillbirth rates were consistently lower among Asian-Americans compared to NH-Whites. Stillbirth incidence ranged from a low rate of 2.6 per 1000 births in Koreans to as high as 5.3 per 1000 births in Filipinos. After adjusting for potentially confounding characteristics, Asian-Americans were about half as likely to experience stillbirth compared to NH-White mothers [adjusted hazards ratio (AHR) = 0.57, 95% confidence interval (CI) = 0.51–0.64]. This intrauterine survival advantage was evident in all Asian-American subgroups. The risk of stillbirth is twofold lower in Asian-Americans than in NH-Whites. It will be an important research agenda to determine reasons for the improved intrauterine survival among Asian-Americans in order to uncover clues for reducing the burden of stillbirth among other racial/ethnic minority women in the United States.

Release Date: 2020-05-19.The Census Bureau has reviewed this data product for unauthorized disclosure of confidential information and has approved the disclosure avoidance practices applied (Approval ID: CBDRB-FY20-008)...Release Schedule:.Data in this file come from estimates of business ownership by sex, ethnicity, race, and veteran status from the 2018 Annual Business Survey (ABS) collection. Data are also obtained from administrative records, the 2017 Economic Census and other economic surveys...Note: The collection year is the year in which the data are collected. A reference year is the year that is referenced in the questions on the survey and in which the statistics are tabulated. For example, the 2018 ABS collection year produces statistics for the 2017 reference year. The "Year" column in the table is the reference year. The ABS has a larger sample size during the benchmark year of 2017. Due to the larger size, more detailed data are shown for reference year 2017...For more information about ABS planned data product releases, see Tentative ABS Schedule...Key Table Information:.Includes U.S. firms with paid employees, operating during the reference year with receipts of $1,000 or more, which are classified in the North American Industry Classification System (NAICS), Sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Employer firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. Employment reflects the number of paid employees during the pay period in the reference year that included March 12...Data Items and Other Identifying Records:.Data include estimates on:.Number of employer firms (firms with paid employees). Sales and receipts of employer firms (reported in $1,000s of dollars). Number of employees (during the March 12 pay period). Annual payroll (reported in $1,000s of dollars)...These data are aggregated by the following demographic classifications of firm for:.All firms. Classifiable (firms classifiable by sex, ethnicity, race, and veteran status). . Sex. Female. Male. Equally male/female. . Ethnicity. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Equally minority/nonminority. Nonminority (Firms classified as non-Hispanic and White). . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Equally veteran/nonveteran. Nonveteran. . . . Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status). ...Moreover, the 2017 reference year statistics include detailed race and ethnicity data tabulated for:.Hispanic subgroups. Mexican, Mexican American, Chicano. Puerto Rican. Cuban. Other Hispanic, Latino, or Spanish. . Asian subgroups. Asian Indian. Chinese. Filipino. Japanese. Korean. Vietnamese. Other Asian. . Native Hawaiian and Other Pacific Islander subgroups. Native Hawaiian. Guamanian or Chamorro. Samoan. Other Pacific Islander. ...Data Notes:.. Business ownership is defined as having 51 percent or more of the stock or equity in the business. Data are provided for businesses owned equally (50% / 50%) by men and women, by Hispanics and non-Hispanics, by minorities and nonminorities, and by veterans and nonveterans. Firms not classifiable by sex, ethnicity, race, and veteran status are counted and tabulated separately.. The detail may not add to the total or subgroup total because a Hispanic or Latino firm may be of any race, and because a firm could be tabulated in more than one racial group. For example, if a firm responded as both Chinese and Black majority owned, the firm would be included in the detailed Asian and Black estimates but would only be counted once toward the higher level all firms' estimates.. References such as "Mexican-owned," "Puerto Rican-owned," "Cuban-owned" or "other Hispanic- or Latino-owned" businesses refer only to businesses operating in the 50 states and the District of Columbia that self-identified 51 percent or more of their ownership in 2017 to be by individuals of Mexican, Puerto Rican, Cuban or other Hispanic or Latino origin. The ABS does not distinguish between U.S. residents and nonresidents. Companies owned by foreign governments or owned by other companies, foreign or domestic, are included in the category "Unclassifiable."...Industry and Geogr...

Total number of deaths, age-adjusted mortality rates, and rate ratios (RR) from all causes by racial/ethnic group and sex in the United States, 2003–2011 (36 States and District of Columbia).

This is the final imputed list of API decedents used to calculate rates of fatal police violence experienced by Asian American & Pacific Islander subgroups (2013-2019) in "Disaggregating Asian American and Pacific Islander Risk of Fatal Police Violence" (Schwartz & Jahn, PLOS One 2022). Data include the national/ethnic or regional background of decedents, as well as IDs to link these files to the original source data (Fatal Encounters, or via their Fatal Encounters identifier, Mapping Police Violence). We also provide information on how participants' backgrounds were identified; for more detail, see the published version of the paper referenced above.

The Community Health Resources and Needs Assessment (CHRNA) project is a large-scale health needs assessment in diverse, low-income Asian American communities in New York City. The project uses a community-engaged and community venue-based approach to assess existing health issues, available resources, and best approaches to meet community health needs. Questions asked in the CHRNAs assess various determinants of health, including length of residence in the United States, English language proficiency, educational attainment, employment and income, perceived health, health insurance and access to care, nutrition and physical activity, mental health, screening for cancer and other chronic diseases, sleep deprivation, and connections to social and religious environments.

The first round of CHRNAs, conducted between 2004 and 2006, surveyed approximately 100 individuals were surveyed from each of the following Asian subgroups: Cambodians, Chinese, Filipinos, Japanese, Koreans, South Asians, Thai, and Vietnamese (n=1,201).

IntroductionAsian American populations face unique structural/social inequities contributing to poor diet quality and health disparities. The current body of literature on diet and food consumption of Asian Americans mainly focuses on the health of Filipino and East Asian Americans, or those with pre-existing non-communicable diseases.ObjectiveThe aim of this review is to comprehensively compile all available literature on nutrition and dietary consumption among the general population in Asian American ethnic subgroups, highlight any disparities and research gaps, and suggest further research action.MethodsWith guidance from a research librarian, we enumerated and searched key terms related to diet, food, nutrition, and Asian Americans in PubMed/MEDLINE, Food Science Collection (CABI Digital Library), CINAHL (EBSCO), Scopus, Food Science and Technology Abstracts (Web of Science), and Biological & Agricultural Index Plus (EBSCO) in accordance with PRISMA-S guidelines. An article will be included if it was published in the English language; is a peer-reviewed research manuscript or published in grey literature from 2000 to present; and describes what food groups and macronutrients healthy non-institutionalized Asian Americans in the U.S. are eating. An article will be excluded if it contains only research conducted outside of the U.S.; combines Asian Americans with Native Hawaiian and Pacific Islanders; and had no explicit focus on Asian American nutrition and dietary consumption. Two or more reviewers will participate in the study screening and selection process. We will record article characteristics, diet outcomes, and recommendations from final included articles using a data extraction table and prepare a summary narrative with key findings.Expected outputsResults will be disseminated through a peer-reviewed manuscript. The findings from this review can have broad implications for designing and implementing nutrition-focused initiatives that will appropriately reflect and address the needs as well as norms and values of each distinct Asian American ethnic subgroup.

1Age-adjusted mortality rates standardized to 2000 US standard populationAge-adjusted mortality rates (AR) per 100,000 by cause of death, racial/ethnic group, and sex: 36 U.S. States and District of Columbia, 2003–2011 average.

In 2023, **** percent of Black people living in the United States were living below the poverty line, compared to *** percent of white people. That year, the total poverty rate in the U.S. across all races and ethnicities was **** percent. Poverty in the United States Single people in the United States making less than ****** U.S. dollars a year and families of four making less than ****** U.S. dollars a year are considered to be below the poverty line. Women and children are more likely to suffer from poverty, due to women staying home more often than men to take care of children, and women suffering from the gender wage gap. Not only are women and children more likely to be affected, racial minorities are as well due to the discrimination they face. Poverty data Despite being one of the wealthiest nations in the world, the United States had the third highest poverty rate out of all OECD countries in 2019. However, the United States' poverty rate has been fluctuating since 1990, but has been decreasing since 2014. The average median household income in the U.S. has remained somewhat consistent since 1990, but has recently increased since 2014 until a slight decrease in 2020, potentially due to the pandemic. The state that had the highest number of people living below the poverty line in 2020 was California.

Intraspecific hybrid sterility is a common form of postzygotic reproductive isolation in Asian cultivated rice, which is also the major obstacle to utilize the strong heterosis in the rice breeding program. Here, we review recent progress in classification and hybrid sterility in Asian cultivated rice. A genome-wide analysis of numerous wild relatives of rice and Asian cultivated rice has provided insights into the origin and differentiation of Asian cultivated rice, and divided Asian cultivated rice into five subgroups. More than 40 conserved and specific loci were identified to be responsible for the hybrid sterility between subgroup crosses by genetic mapping, which also contributed to the divergence of Asian cultivated rice. Most of the studies are focused on the sterile barriers between indica and japonica crosses, ignoring hybrid sterility among other subgroups, leading to neither a systematical understanding of the nature of hybrid sterility and subgroup divergence, nor effectively utilizing strong heterosis between the subgroups in Asian cultivated rice. Future studies will aim at identifying and characterizing genes for hybrid sterility and segregation distortion, comparing and understanding the molecular mechanism of hybrid sterility, and drawing a blueprint for intraspecific hybrid sterility loci derived from cross combinations among the five subgroups. These studies would provide scientific and accurate guidelines to overcome the intraspecific hybrid sterility according to the parent subgroup type identification, allowing the utilization of heterosis among subgroups, also helping us unlock the mysterious relationship between hybrid sterility and Asian cultivated rice divergence.

Source: National Center for Health Statistics: Diseases of the heart (International Classification of Diseases- 10th revision [ICD-10] codes I00-I09, I11, I13, I20-I51); Malignant Neoplasms (C00-C97); Chronic lower respiratory diseases (J40-J47); Accidents-unintentional injury (V01-X59, Y85-Y86); Cerebrovascular disease (I60-I69); Diabetes Mellitus (E10-E14); Intentional self-harm (suicide) (U03, X60-X84, Y87.0); Influenza and pneumonia (J09-J18); Alzheimer’s Disease (G30); Nephritis, nephrotic syndrome, and nephrosis (N00-N07, N17-N19, N25-N27); Septicemia (A40-A41).Rankings (Rk), death count, and percentage of death due to cause (%) by racial/ethnic group and sex, from 2003–2011 (36 States and District of Columbia).

Age-adjusted rate of suicide deaths for Santa Clara County residents. The data are provided for the total county population and by sex and race/ethnicity. Data trends are presented from 2007 to 2016. Source: Santa Clara County Public Health Department, VRBIS, 2007-2016. Data as of 05/26/2017; U.S. Census Bureau, 2010 Census.METADATA:Notes (String): Lists table title, notes and sourceYear (String): Year of death Category (String): Lists the category representing the data: Santa Clara County is for total population, sex: Male and Female, race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only) and Asian/Pacific Islander subgroups: Asian Indian, Chinese. Filipino, Korean and Vietnamese.Age adjusted rate per 100,000 people (Numeric): The Tenth Revision of the International Classification of Diseases codes (ICD-10) are used for coding causes of death. Age-adjusted rate is calculated using 2000 U.S. Standard Population. Suicide rate is number of suicide deaths in a year per 100,000 people in the same time period.

Characteristics of police violence fatalities, 2013–2019.

Patient, tumor, and treatment characteristics in the Asian subgroups with lung or bronchial cancer.

Multivariable analysis of Asian subgroups associated with DSS using a Cox proportional hazards model for four age groups and four disease-stage groups.

Five- and 10-year survival rates in the patients with lung or bronchial cancer by ethnic group.

Multivariable analysis of clinicopathologic and ethnic variables associated with DSS using a Cox proportional hazards model for four age groups and four disease-stage groups.

Selected US averages informing assumed differences in thriving, suffering, and life expectancy by race/ethnicity: Black; Hispanic; Asian; White; American Indian, Alaska Native.