Abstract
Background
The prevalence of cardiometabolic risk factors may vary by disaggregated race and ethnicity categories, and by acculturation‐related factors. We evaluated the association between nativity and length of US residence, and prevalence of diabetes, hypertension, and hypercholesterolemia by select disaggregated race and ethnicity groups.
Methods
We conducted a pooled cross‐sectional study of 218 158 US adults from the Medical Expenditure Panel Survey (2013–2022). Nativity (US born, non‐US born) and length of US residence (≥15 years or <15 years) were used as select proxies for acculturation. Self‐reported cardiometabolic risk factors included diabetes, hypertension, and hypercholesterolemia.
Results
Results showed substantial heterogeneity among both aggregated and disaggregated racial and ethnic groups. Nativity (US born versus non‐US born) was significantly associated with increased hypertension prevalence among Hispanic adults (odds ratio [OR], 1.26 [95% CI, 1.15–1.39]), whereas among detailed categories the OR varied from 0.68 (95% CI, 0.51–0.93) among Puerto Rican adults to 1.34 (95% CI, 1.18–1.52) among Mexican adults. For the association between length of US residence and hypercholesterolemia, the OR for all Non‐Hispanic Asian adults was 1.18 (95% CI, 0.92–1.51), whereas results varied in detailed categories from 1.00 (95% CI, 0.64–1.57) among Indian adults to 1.69 (95% CI, 1.08–2.64) among Chinese adults.
Conclusion
The association between US nativity or length of US residence and cardiometabolic risk factors varies by disaggregated race and ethnicity among Hispanic and Non‐Hispanic Asian adults. Future studies may evaluate comprehensive measures of acculturation and assess other race and ethnicity groups to inform tailored efforts to improve cardiometabolic risk factor prevention and treatment.
Keywords: acculturation, diabetes, hypercholesterolemia, hypertension, nativity
Subject Categories: Risk Factors, Cardiovascular Disease, Epidemiology, Race and Ethnicity
Nonstandard Abbreviations and Acronyms
- MEPS
Medical Expenditure Panel Survey
Clinical Perspective.
What Is New?
Substantial heterogeneity is observed for the association between select proxy measures of acculturation (US nativity and longer length of US residence) and the prevalence of cardiometabolic risk factors by disaggregated racial and ethnic groups.
US nativity and longer length of US residence was associated with a higher prevalence of both prevalent hypertension and hypercholesterolemia among Chinese adults.
Longer US residence was significantly associated with a higher prevalence of diabetes, hypertension, and hypercholesterolemia among Central/South American adults.
What Are the Clinical Implications?
Improved understanding of the mechanisms underlying disparities by disaggregated racial and ethnic groups may guide culturally competent care and appropriately tailored interventions to reduce cardiovascular disease risk and promote health equity.
Additional studies may identify which specific factors relating to acculturation, such as language, social networks, or dietary preferences, may be most effectively targeted to reduce disparities in cardiometabolic risk factors.
Cardiometabolic risk factors, such as prediabetes, diabetes, hypertension, and hypercholesterolemia, are associated with a greater risk of a variety of adverse cardiovascular outcomes including heart disease, ischemic stroke, and mortality. 1 , 2 , 3 Moreover, disparities in cardiometabolic risk factors continue to persist, 4 , 5 emphasizing the potential need to identify groups at greatest risk for tailored interventions to reduce health inequities.
Measures of acculturation may be important to better understand social and other related contributors to disparities in cardiometabolic risk factors. Acculturation can be broadly defined as a complex process by which an individual integrates and adopts values, attitudes, language, and behaviors of 2 cultures. 6 , 7 Acculturation can be measured in different ways ranging from multidimensional models to proxy measures more readily available in health research such as language fluency, nativity, and length of residence in a new country. The complex nature of acculturation in the United States may affect cardiometabolic risk in contrasting ways. For example, acculturation strategies can be associated with a greater risk of cardiovascular disease through suboptimal lifestyle‐related factors such as low diet quality (eg, excess sodium intake, high saturated fat intake) or physical inactivity but may also support better health outcomes by reducing barriers to preventive care. 8 , 9 , 10 Additionally, the potential effects of acculturation on cardiometabolic risk factors are often better evaluated within disaggregated categories for race and ethnicity because of variations of how acculturation occurs across and within diverse groups. Commonly used categories of race and ethnicity may inappropriately aggregate heterogeneous groups, each with unique patterns of socioeconomic, cultural, and other factors that might affect in different ways the association between acculturation and cardiometabolic risk factors.
Previous studies have generally reported a positive association between proxy measures of acculturation and prevalence of cardiometabolic risk factors. 11 , 12 , 13 One study reported a significant positive association between an acculturation score (comprising US nativity, English language fluency, and length of residence in the United States) and diabetes prevalence among Hispanic adults. 11 Another study reported that among Asian adults, US nativity and longer length of US residence were significantly associated with increased prevalence of prediabetes. 12 A third study reported among Black adults in the United States, both US nativity and longer length of US residence were significantly associated with a higher prevalence of hypertension, diabetes, and obesity. 12 , 13 However, studies conducted among disaggregated racial and ethnic groups show inconsistent results, which may be limited by out‐of‐date data sources, small sample sizes, and regional subpopulations. 6 , 11 , 12 , 13 , 14 , 15 We therefore sought to describe the association between select proxy measures of acculturation (nativity and length of US residence) and prevalence of cardiometabolic risk factors in a nationally representative sample of US adults by disaggregated race and ethnicity.
METHODS
Study Population
The data used for this study are publicly available at: https://meps.ahrq.gov/mepsweb/data_stats/download_data_files.jsp. Data were obtained from the household component of the 2013 to 2022 MEPS (Medical Expenditure Panel Survey), a nationally representative survey of the US civilian noninstitutionalized population conducted by the Agency for Healthcare Research and Quality. 16 The MEPS comprises a nationally representative subsample of households from the prior year's National Health Interview Survey. Information collected from respondents include sociodemographic variables, comorbidities, and variables related to health care use and access. This study was conducted to be consistent with applicable federal law and was not subject to institutional review board approval.
Measurements
Demographic information included age and sex. Age was analyzed as a categorical variable (18–39, 40–54, 55–69, ≥70 years) because it was aggregated at ≥85 years by Agency for Healthcare Research and Quality to ensure privacy. Socioeconomic variables included educational attainment (<high school, high school or General Educational Development, >high school, missing), employment status at time of interview (yes, no), and health insurance (any private insurance, public insurance only, no insurance). Self‐reported race and ethnicity were recorded in separate questionnaire items. Respondents who identified as both Hispanic or Latino (Hispanic) and a race group were categorized as Hispanic (eg, an individual identifying as both Hispanic and Black was categorized as Hispanic). Race and ethnicity groups and corresponding detailed categories on the questionnaire included Hispanic (Central/South American, Cuban, Dominican, Mexican, Puerto Rican, Other Hispanic), non‐Hispanic (NH) Asian (Chinese, Filipino, Indian, Other Asian or Pacific Islander), NH Black, NH White, and NH multiple races.
Acculturation was assessed by 2 proxy measures from the MEPS questionnaire. Nativity, defined as US born or non‐US born, was determined by the question “Were you born in the United States?” Length of US residence was based on the question “About how long have you lived in United States?” asked to respondents who reported not being born in the United States (n=50 046), recorded as <1 year, 1 to 4.9 years, 5 to 9.9 years, 10 to 14.9 years, ≥15 years. To maximize statistical reliability, this measure was dichotomized a priori as ≥15 years or <15 years. Adults born in the United States were excluded from analyses assessing length of residence in the United States.
Cardiometabolic risk factors were measured from self‐reported history of diabetes (“Have you ever been told by a doctor or other health professional that you had diabetes?”), hypertension (“Have you ever been told by a doctor or other health professional that you had hypertension, also called high blood pressure?”), and hypercholesterolemia (“Have you ever been told by a doctor or other health professional that you had high cholesterol?”).
Statistical Analysis
Multivariable logistic regression models adjusted for age, sex, and survey year were used to estimate odds ratios (ORs) and corresponding 95% CIs for the association between nativity or length of US residence and each cardiometabolic outcome. Logistic regression models adjusted for age, sex, and survey year were also used to estimate the prevalence of cardiometabolic risk factors and corresponding 95% CIs and SEs. Other variables such as socioeconomic factors were not added as covariates to keep the models parsimonious, as model instability may have resulted from small sample sizes in some detailed categories of racial or ethnic groups. Analyses for detailed categories of other variables were not performed for similar reasons and to focus on the role of data disaggregation for racial and ethnic groups. Sample weights were used to produce nationally representative estimates. Adults who were missing data on nativity, length of US residence, or cardiometabolic risk factors were excluded. Missing data for education (n=2505; 1.1%) were categorized as a missing indicator. No other data were missing. Analyses were conducted using SAS 9.4 (SAS Institute, Cary, NC) and SUDAAN 11.0.4 (RTI International, Research Triangle Park, NC) to account for the complex survey sampling design.
RESULTS
Study Population
Of the 233 370 adults in the survey, 14 481 did not have data on either nativity or length of US residence and 1185 did not have data on any cardiometabolic risk factors, resulting in a final study sample of 218 158 adults. Characteristics of the study population, by race and ethnicity, are displayed in Table 1A and 1B. In the overall population, adults aged 18 to 39 years comprised the largest group at 37.7%, and a slight majority (51.6%) were female. Age distribution varied substantially by race and ethnicity with the proportion of adults aged ≥70 years ranging from 7.1% among Hispanic adults to 17.6% among NH White adults. Among detailed categories for Hispanic and Asian groups, this proportion varied approximately 3‐fold and 2‐fold, respectively. The distribution of educational attainment and health insurance status also varied to a similar extent among detailed categories for Asian and Hispanic groups.
Table 1.
Characteristics of US Adults by Race and Ethnicity, Medical Expenditure Panel Survey 2013 to 2022 (n=218 158)
| (A) | ||||||||
|---|---|---|---|---|---|---|---|---|
| Race and ethnicity | Age, y, % (SE) | Sex, % (SE) | Employed*, % (SE) | |||||
| 18–39 | 40–54 | 55–69 | ≥70 | Female | Male | No | Yes | |
| Overall | 37.7 (0.3) | 24.4 (0.2) | 23.6 (0.2) | 14.4 (0.2) | 51.6 (0.2) | 48.4 (0.2) | 37.2 (0.3) | 62.8 (0.3) |
| Hispanic | 49.4 (0.5) | 27.8 (0.4) | 15.8 (0.4) | 7.1 (0.3) | 50.1 (0.4) | 49.9 (0.4) | 34.2 (0.6) | 65.8 (0.6) |
| Central/South American | 48.3 (1.1) | 30.2 (1.0) | 16.3 (0.9) | 5.3 (0.5) | 52.5 (0.9) | 47.5 (0.9) | 28.8 (0.9) | 71.2 (0.9) |
| Cuban | 33.4 (1.8) | 26.9 (1.9) | 22.7 (1.5) | 17.0 (1.9) | 50.0 (1.7) | 50.0 (1.7) | 36.3 (2.6) | 63.7 (2.6) |
| Dominican | 46.3 (2.5) | 25.3 (1.6) | 16.9 (1.8) | 11.5 (2.4) | 56.6 (2.2) | 43.4 (2.2) | 40.8 (2.8) | 59.2 (2.8) |
| Mexican | 51.9 (0.6) | 27.7 (0.6) | 14.6 (0.5) | 5.8 (0.3) | 48.6 (0.4) | 51.4 (0.4) | 33.9 (0.8) | 66.1 (0.8) |
| Puerto Rican | 45.0 (1.4) | 26.2 (1.2) | 18.9 (1.0) | 9.9 (0.8) | 51.4 (1.3) | 48.6 (1.3) | 41.1 (1.4) | 58.9 (1.4) |
| Other Hispanic | 49.5 (1.8) | 26.6 (1.6) | 15.0 (1.2) | 8.9 (1.0) | 52.4 (1.8) | 47.6 (1.8) | 35.9 (1.9) | 64.1 (1.9) |
| NH Asian | 42.0 (1.0) | 28.4 (1.0) | 18.6 (0.7) | 11.0 (0.6) | 54.0 (0.6) | 46.0 (0.6) | 36.2 (0.8) | 63.8 (0.8) |
| Chinese | 41.3 (1.6) | 26.4 (1.6) | 20.4 (1.2) | 11.9 (1.2) | 55.3 (1.6) | 44.7 (1.6) | 36.9 (1.6) | 63.1 (1.6) |
| Filipino | 37.1 (1.9) | 27.2 (2.2) | 23.2 (1.8) | 12.5 (1.4) | 59.1 (1.6) | 41.0 (1.6) | 33.9 (2.0) | 66.1 (2.0) |
| Indian | 47.4 (2.2) | 31.1 (2.0) | 14.5 (1.3) | 7.1 (0.9) | 48.8 (1.0) | 51.2 (1.0) | 31.8 (1.2) | 68.3 (1.2) |
| Other Asian or Pacific Islander | 40.5 (1.6) | 28.1 (1.3) | 18.7 (1.0) | 12.7 (1.2) | 55.0 (1.1) | 45.0 (1.1) | 40.0 (1.5) | 60.0 (1.5) |
| NH Black | 42.3 (0.7) | 25.3 (0.4) | 22.0 (0.5) | 10.5 (0.4) | 54.2 (0.5) | 45.8 (0.5) | 39.4 (0.7) | 60.6 (0.7) |
| NH White | 32.8 (0.4) | 23.1 (0.3) | 26.5 (0.3) | 17.6 (0.3) | 51.3 (0.2) | 48.7 (0.2) | 37.6 (0.4) | 62.4 (0.4) |
| NH multiple races | 52.9 (1.4) | 20.6 (1.0) | 18.2 (0.9) | 8.4 (0.7) | 50.2 (1.2) | 49.8 (1.2) | 38.1 (1.2) | 61.9 (1.2) |
| (B) | |||||||
|---|---|---|---|---|---|---|---|
| Race and ethnicity | Educational attainment, % (SE) | Health insurance, % (SE) | |||||
| <High school | High school or GED | >High school | Missing | Private insurance | Public insurance | No insurance | |
| Overall | 13.6 (0.3) | 27.1 (0.3) | 58.7 (0.4) | 0.6 (0.0) | 68.7 (0.4) | 22.7 (0.3) | 8.6 (0.2) |
| Hispanic | 29.4 (0.6) | 29.4 (0.5) | 40.0 (0.7) | 1.2 (0.1) | 51.3 (0.8) | 26.4 (0.7) | 22.3 (0.7) |
| Central/South American | 26.4 (1.1) | 24.9 (1.0) | 47.8 (1.3) | 0.9 (0.2) | 54.0 (1.5) | 21.9 (1.0) | 24.1 (1.2) |
| Cuban | 17.9 (1.9) | 31.7 (2.1) | 49.0 (2.6) | 1.4 (0.4) | 50.0 (3.1) | 33.3 (1.8) | 16.7 (2.0) |
| Dominican | 26.5 (2.2) | 28.2 (3.2) | 43.7 (3.2) | 1.7 (0.6) | 40.8 (2.8) | 46.2 (3.0) | 13.0 (2.0) |
| Mexican | 34.5 (0.8) | 30.1 (0.6) | 33.9 (0.8) | 1.5 (0.2) | 48.9 (1.1) | 25.2 (1.1) | 25.9 (0.9) |
| Puerto Rican | 19.9 (1.1) | 31.2 (1.5) | 48.1 (1.7) | 0.8 (0.2) | 56.3 (1.7) | 35.0 (1.6) | 8.7 (0.8) |
| Other Hispanic | 14.4 (1.1) | 30.0 (1.8) | 55.3 (1.9) | 0.3 (0.1)† | 65.6 (1.7) | 21.3 (1.3) | 13.0 (1.2) |
| NH Asian | 10.3 (0.5) | 17.1 (0.8) | 71.6 (1.0) | 1.1 (0.2) | 73.3 (1.0) | 20.6 (0.9) | 6.1 (0.5) |
| Chinese | 10.5 (1.1) | 13.9 (1.2) | 75.0 (1.5) | 0.7 (0.2)† | 75.5 (1.5) | 20.3 (1.5) | 4.2 (0.7) |
| Filipino | 5.9 (1.3) | 17.6 (2.5) | 74.1 (3.0) | 2.4 (0.6) | 75.9 (2.2) | 17.4 (1.8) | 6.8 (0.9) |
| Indian | 7.9 (0.9) | 11.6 (1.2) | 80.1 (1.7) | 0.5 (0.2)† | 80.5 (1.7) | 15.3 (1.4) | 4.3 (0.6) |
| Other Asian or Pacific Islander | 13.8 (1.0) | 22.9 (1.1) | 62.2 (1.4) | 1.1 (0.3) | 65.7 (2.0) | 26.0 (2.0) | 8.3 (0.9) |
| NH Black | 15.4 (0.4) | 33.1 (0.6) | 50.8 (0.7) | 0.7 (0.1) | 59.9 (0.8) | 30.2 (0.7) | 9.8 (0.4) |
| NH White | 9.5 (0.2) | 26.4 (0.4) | 63.8 (0.5) | 0.3 (0.0) | 74.4 (0.4) | 20.5 (0.4) | 5.1 (0.2) |
| NH multiple races | 15.2 (1.0) | 26.1 (1.2) | 58.5 (1.5) | NA | 68.1 (1.3) | 24.0 (1.2) | 7.9 (0.7) |
Data presented are weighted percentages and SEs. For estimates with large sampling error (relative SE >0.50), “NA” is shown. GED indicates General Educational Development; NA, not applicable; and NH, non‐Hispanic.
Employed is defined as adults who reported any employment at the time of interview.
An asterisk indicates that the precision of the estimate is questionable due to a relative SE of 0.30–0.50.
The largest differences among detailed categories were observed for estimates of nativity (Table 2, Table S1). Although approximately half of Hispanic adults reported being born in the United States, when disaggregated, estimates ranged from slightly over 20% among Central/South American and Cuban adults to 75.6% among Puerto Rican adults. Among all NH Asian adults, 23.7% reported being born in the United States, whereas among detailed categories, estimates ranged from 16.4% among Indian adults to 30.2% among Other Asian or Pacific Islander adults.
Table 2.
Nativity and Length of US Residence by Race and Ethnicity, Medical Expenditure Panel Survey 2013 to 2022 (n=218 158)
| Race and ethnicity | Born in United States, % (SE) | Length of residence in the United States, % (SE) | ||
|---|---|---|---|---|
| No | Yes | <15 y | ≥15 y | |
| Overall | 17.7 (0.4) | 82.3 (0.4) | 30.5 (0.6) | 69.5 (0.6) |
| Hispanic | 51.4 (0.8) | 48.6 (0.8) | 27.7 (0.8) | 72.3 (0.8) |
| Central/South American | 79.0 (1.1) | 21.0 (1.1) | 32.6 (1.5) | 67.4 (1.5) |
| Cuban | 77.6 (1.8) | 22.4 (1.8) | 36.8 (2.6) | 63.2 (2.6) |
| Dominican | 73.2 (2.0) | 26.8 (2.0) | 33.0 (3.4) | 67.0 (3.4) |
| Mexican | 46.9 (1.0) | 53.1 (1.0) | 23.8 (1.0) | 76.3 (1.0) |
| Puerto Rican | 24.4 (1.7) | 75.6 (1.7) | 26.0 (3.7) | 74.0 (3.7) |
| Other Hispanic | 28.6 (1.8) | 71.4 (1.8) | 28.6 (3.1) | 71.4 (3.1) |
| NH Asian | 76.3 (1.3) | 23.7 (1.3) | 38.5 (1.3) | 61.5 (1.3) |
| Chinese | 79.0 (1.3) | 21.0 (1.3) | 36.6 (2.3) | 63.4 (2.3) |
| Filipino | 75.2 (1.9) | 24.8 (1.9) | 34.7 (3.1) | 65.3 (3.1) |
| Indian | 83.6 (1.4) | 16.4 (1.4) | 47.3 (2.6) | 52.7 (2.6) |
| Other Asian or Pacific Islander | 69.8 (2.4) | 30.2 (2.4) | 33.7 (1.9) | 66.3 (1.9) |
| NH Black | 11.9 (0.7) | 88.1 (0.7) | 39.1 (2.3) | 60.9 (2.3) |
| NH White | 4.7 (0.2) | 95.3 (0.2) | 21.6 (1.4) | 78.4 (1.4) |
| NH multiple races | 6.3 (0.7) | 93.7 (0.7) | 22.6 (4.4) | 77.4 (4.4) |
Data presented are weighted row percentages and SEs. NH indicates Non‐Hispanic.
For each cardiometabolic risk factor, substantial heterogeneity was observed in prevalence estimates (adjusted for age, sex, and survey year) by nativity or length of US residence and by race and ethnicity (Table 3, Table S2). For example, diabetes prevalence by nativity and race and ethnicity ranged from 4.1% among US‐born Indian adults to 19.7% among non‐US born Puerto Rican adults. Prevalence also varied substantially for other cardiometabolic risk factors, such as for hypertension, where prevalence by length of US residence varied from 13.3% among other Hispanic adults who reported residence in the United States for <15 years to 50.1% among Puerto Rican adults who reported residence in the United States for ≥15 years.
Table 3.
Prevalence of Cardiometabolic Risk Factors, by Nativity, Length of US Residence and Race and Ethnicity, Medical Expenditure Panel Survey 2013 to 2022
| Diabetes | Hypertension | Hypercholesterolemia | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Born in United States | In United States for ≥15 y | Born in United States | In United States for ≥15 y | Born in United States | In United States for ≥15 y | |||||||
| Race and ethnicity | No | Yes | No | Yes | No | Yes | No | Yes | No | Yes | No | Yes |
| Overall | 11.2 (0.3) | 9.6 (0.2) | 9.5 (0.6) | 10.9 (0.4) | 30.9 (0.5) | 37.7 (0.4) | 29.0 (1.1) | 32.8 (0.7) | 32.7 (0.5) | 32.9 (0.3) | 29.7 (1.1) | 34.4 (0.6) |
| Hispanic | 12.5 (0.4) | 14.6 (0.6) | 10.1 (0.8) | 13.5 (0.5) | 32.3 (0.7) | 37.6 (0.9) | 29.7 (1.5) | 34.1 (0.8) | 34.5 (0.6) | 31.9 (0.7) | 31.1 (1.4) | 36.4 (0.7) |
| Central/South American | 8.6 (0.7) | 9.3 (2.2) | 5.2 (0.9) | 9.9 (0.9) | 30.5 (1.4) | 31.2 (4.1) | 23.6 (2.4) | 33.5 (1.6) | 37.1 (1.3) | 34.3 (3.2) | 29.5 (2.3) | 39.9 (1.5) |
| Cuban | 8.9 (1.0) | 11.0 (3.4)* | 9.3 (1.3) | 7.6 (1.7) | 37.4 (2.4) | 40.0 (5.4) | 31.5 (4.4) | 39.6 (2.3) | 34.7 (1.7) | 28.0 (5.0) | 33.5 (3.1) | 34.1 (2.1) |
| Dominican | 12.2 (3.1) | 9.3 (3.8)* | 14.6 (3.7) | 12.5 (2.8) | 45.4 (2.9) | 45.4 (7.0) | 47.8 (4.7) | 44.6 (3.5) | 34.8 (2.6) | 42.0 (7.9) | 38.0 (4.1) | 34.7 (3.3) |
| Mexican | 14.6 (0.6) | 14.8 (0.7) | 11.7 (1.5) | 15.2 (0.8) | 31.0 (0.9) | 37.6 (1.2) | 28.5 (2.2) | 32.8 (1.2) | 32.1 (0.8) | 31.4 (0.9) | 26.5 (2.0) | 34.3 (0.9) |
| Puerto Rican | 19.7 (2.1) | 16.8 (1.6) | 18.8 (4.8) | 22.4 (2.7) | 47.9 (3.2) | 38.6 (2.3) | 47.6 (4.3) | 50.1 (3.4) | 50.5 (4.1) | 33.1 (1.9) | 54.2 (8.6) | 49.7 (3.3) |
| Other Hispanic | 7.2 (1.4) | 12.4 (1.7) | NA | 6.7 (1.8) | 25.8 (3.1) | 34.5 (2.8) | 13.3 (4.6)* | 26.5 (4.6) | 33.7 (3.1) | 29.2 (2.4) | 35.7 (7.6) | 35.5 (4.1) |
| NH Asian | 10.5 (0.6) | 9.0 (1.1) | 9.6 (1.1) | 10.5 (0.9) | 27.9 (1.1) | 31.7 (1.9) | 28.0 (1.9) | 29.1 (1.3) | 32.6 (1.0) | 32.2 (2.1) | 30.4 (2.3) | 34.0 (1.3) |
| Chinese | 5.2 (0.7) | 6.0 (2.1)* | 4.2 (1.3)* | 5.1 (0.9) | 19.3 (1.7) | 34.1 (4.4) | 17.0 (3.1) | 21.8 (2.0) | 27.4 (1.9) | 37.8 (5.0) | 21.1 (2.8) | 31.1 (2.6) |
| Filipino | 13.2 (1.7) | 11.4 (4.2)* | 7.5 (2.2) | 9.6 (2.0) | 39.9 (2.9) | 33.2 (5.0) | 39.5 (6.4) | 41.1 (3.4) | 37.8 (2.6) | 22.2 (4.4) | 35.1 (5.4) | 38.5 (3.4) |
| Indian | 13.7 (1.7) | 4.1 (2.0)* | 14.1 (2.4) | 13.0 (2.1) | 26.4 (2.2) | 20.3 (4.3) | 30.7 (4.0) | 23.4 (2.0) | 32.0 (2.0) | 28.4 (5.7) | 32.4 (3.9) | 32.3 (2.6) |
| Other Asian or Pacific Islander | 9.8 (1.0) | 10.0 (1.4) | 7.7 (1.7) | 11.0 (1.2) | 29.1 (1.8) | 32.9 (2.7) | 25.6 (2.5) | 32.8 (2.2) | 32.7 (1.9) | 33.5 (2.4) | 27.8 (3.8) | 34.5 (2.2) |
| NH Black | 11.3 (0.8) | 14.8 (0.4) | 9.6 (1.9) | 10.9 (1.4) | 36.8 (1.9) | 53.5 (0.8) | 32.4 (3.6) | 41.8 (2.3) | 23.5 (1.5) | 30.5 (0.6) | 17.6 (2.6) | 26.7 (1.8) |
| NH White | 7.3 (0.6) | 8.5 (0.2) | 7.1 (1.5) | 5.3 (0.8) | 31.5 (1.3) | 35.6 (0.4) | 29.1 (4.1) | 32.3 (1.7) | 33.1 (1.2) | 33.2 (0.3) | 35.0 (3.6) | 33.5 (1.5) |
| NH multiple races | 10.0 (2.6) | 13.1 (1.0) | NA | 5.7 (2.2)* | 32.7 (4.4) | 42.8 (1.8) | 28.0 (13.2)* | 35.9 (6.7) | 34.7 (4.5) | 32.9 (1.7) | 23.6 (9.4)* | 40.3 (6.1) |
Prevalence estimates and corresponding SEs derive from logistic regression models adjusted for age, sex, and survey year. For estimates with large sampling error (relative SE >0.50), “NA” is shown. NA indicates not applicable; and NH, Non‐Hispanic.
An asterisk indicates that the precision of the estimate is questionable due to a relative SE of 0.30–0.50.
Diabetes
In models adjusted for age, sex, and survey year, US nativity, compared with non‐US nativity, was significantly associated with a higher prevalence of self‐reported diagnosed diabetes among Hispanic (OR, 1.20 [95% CI, 1.07–1.35]) and NH Black (OR, 1.36 [95% CI, 1.16–1.60]) adults (Figure 1A). Among both Asian and Hispanic detailed categories, ORs had high variability and were generally not statistically significant.
Figure 1. Association between proxy measures of acculturation and diabetes in the United States, by race and ethnicity, MEPS 2013 to 2022.
Estimates derive from logistic regression models adjusted for age, sex, and survey year. Bold text indicates a statistically significant odds ratio (P<0.05). A, P‐interaction=0.01. B, P‐interaction =0.07. The number of cases refers to the number of adults with diabetes in each race and ethnicity group. *An asterisk indicates that the precision of the estimate is questionable due to a relative SEof 0.30–0.50. Estimates with large sampling error (relative SE >0.50) are not shown. MEPS indicates Medical Expenditure Panel Survey; NH, Non‐Hispanic; OR, odds ratio; and PI, Pacific Islander.
In Figure 1B, residence in the United States for ≥15 years was significantly associated with a higher prevalence of self‐reported diabetes among Hispanic (OR, 1.39 [95% CI, 1.14–1.69]) adults compared with length of residence < 15 years. Among Hispanic detailed categories, results were significant only for Central/South American adults (OR, 2.02 [95% CI, 1.32–3.10]). Results among NH Asian detailed categories showed high variability and were not statistically significant.
Hypertension
Among Hispanic detailed categories, ORs for significant associations between nativity and self‐reported hypertension ranged from 0.68 (95% CI, 0.51–0.93) among Puerto Rican adults to 1.34 (95% CI, 1.18–1.52) among Mexican adults (Figure 2A). Among all NH Asian adults, nativity was not significantly associated with self‐reported hypertension (OR, 1.20 [95% CI, 0.97–1.48]), although among detailed categories the association was significant for Chinese adults (OR, 2.16 [95% CI, 1.36–3.45]). US nativity, compared with non‐US nativity, was significantly associated with a higher prevalence of self‐reported hypertension for NH Black (OR, 1.98 [95% CI, 1.69–2.32]), NH White (OR, 1.20 [95% CI, 1.07–1.35]) and NH multiple race adults (OR, 1.54 [95% CI, 1.03–2.29]).
Figure 2. Association between proxy measures of acculturation and hypertension in the United States, by race and ethnicity, MEPS 2013 to 2022.
Estimates derive from logistic regression models adjusted for age, sex, and survey year. Bold text indicates a statistically significant odds ratio (P<0.05). A, P‐interaction <0.001. B, P‐interaction=0.049. The number of cases refers to the number of adults with hypertension in each race and ethnicity group.*An asterisk indicates that the precision of the estimate is questionable due to a relative SE of 0.30–0.50. Estimates with large sampling error (relative SE >0.50) are not shown. MEPS indicates Medical Expenditure Panel Survey; NH, Non‐Hispanic; OR, odds ratio; and PI, Pacific Islander.
Residence in the US of ≥15 years compared with residence <15 years was significantly associated with greater odds of self‐reported hypertension among all Hispanic adults and multiple Hispanic detailed groups (Figure 2B; Hispanic, OR, 1.23 [95% CI, 1.04–1.45]; Central/South American, OR, 1.63 [95% CI, 1.21–2.21]; other Hispanic, OR, 2.35 [95% CI, 1.02–5.41]). Among all NH Asian adults, results were not significant but the OR for other Asian or Pacific Islander adults was significant at 1.42 (95% CI, 1.04–1.95). Residence of ≥15 years was also significantly associated with a higher prevalence of self‐reported hypertension for NH Black (OR, 1.50 [95% CI, 1.05–2.13]) adults than residence of <15 years.
Hypercholesterolemia
US nativity compared with non‐US nativity was significantly associated with a lower prevalence of self‐reported hypercholesterolemia among all Hispanic adults (OR, 0.89 [95% CI, 0.82–0.97]) and among Puerto Rican adults (OR, 0.49 [95% CI, 0.33–0.73]; Figure 3A). Although there was no significant association among NH Asian adults overall, a significant negative association was observed among Filipino adults (OR, 0.47 [95% CI, 0.26–0.83]) and a significant positive association among Chinese adults (OR, 1.61 [95% CI, 1.00–2.58]). US nativity showed a significant positive association among NH Black adults (OR, 1.43 [95% CI, 1.19–1.71]).
Figure 3. Association between proxy measures of acculturation and hypercholesterolemia in the United States, by race and ethnicity, MEPS 2013 to 2022.
Estimates derive from logistic regression models adjusted for age, sex, and survey year. Bold text indicates a statistically significant odds ratio (P<0.05). A, P‐interaction <0.001. B, P‐interaction=0.03. The number of cases refers to the number of adults with hypercholesterolemia in each race and ethnicity group.*An asterisk indicates that the precision of the estimate is questionable due to a relative SE of 0.30–0.50. Estimates with large sampling error (relative SE >0.50) are not shown. MEPS indicates Medical Expenditure Panel Survey; NH, Non‐Hispanic; OR, odds ratio; and PI, Pacific Islander.
Length of US residence was significantly associated with a higher prevalence of self‐reported hypercholesterolemia overall among Hispanic adults (OR, 1.27 [95% CI, 1.10–1.45]), and additionally in 2 detailed categories (Central/South American, OR, 1.59 [95% CI, 1.25–2.02]; Mexican, OR, 1.45 [95% CI, 1.17–1.81]; Figure 3B). There was no significant association overall among NH Asian adults, but a significant positive association was observed among Chinese adults (OR, 1.69 [95% CI, 1.08–2.64]). Longer length of residence in the United States was also significantly associated with self‐reported hypercholesterolemia among NH Black adults (OR, 1.71 [95% CI, 1.16–2.51]).
DISCUSSION
In a large nationwide sample of adults, we observed substantial heterogeneity among disaggregated racial and ethnic groups for the associations between nativity and length of US residence and prevalent cardiometabolic risk factors. In some groups, US nativity or longer length of US residence was associated with a higher prevalence of self‐reported cardiometabolic risk factors, although opposite associations were observed in other groups.
A consistent finding among detailed categories of Hispanic groups was the association between longer US residence and a higher prevalence of all 3 cardiometabolic risk factors among Central/South American adults. Descriptive data on socioeconomic status in the current study do not provide strong evidence to explain these results, suggesting other unmeasured socioeconomic, cultural, lifestyle, or other factors may be driving this association. A prior, similar study suggested that among US‐born adults but not those born outside the United States, both Central and South American adults had a lower odds of self‐reported hypertension and diabetes compared with NH White adults. 17 However, results may not be comparable because length of US residence was not evaluated within detailed categories of Hispanic groups. Moreover, this study may not have comprised a comparable population as all participants resided in California and were sampled from 2001 to 2007. Furthermore, these findings may be better explained if further disaggregated data were available, given that Central and South America comprise heterogenous populations with likely different patterns of health‐related factors 18 that may affect how acculturation is associated with the prevalence of cardiometabolic risk factors. As comparable quantitative studies of cardiometabolic risk factors in Central/South American adults are few, potential explanations of the observed findings are predominately hypothetical, although this might also explain similar differences among other disaggregated racial and ethnic groups. For example, these findings might be partly explained by a healthy immigrant effect, where any health advantage from selective migration of individuals with better health status can be mitigated over time by increased exposure to risk factors associated with cardiometabolic disease. Such risk factors can include lifestyle factors such as unhealthy dietary patterns, decreased physical activity, and smoking. 19 , 20 Other factors might also explain an initial health advantage. For example, immigrants' increasing need for health care access over time 21 might be limited by barriers such as lack of insurance or language barriers, therefore worsening health outcomes. Moreover, after cumulative exposure to stressors associated with acculturation, mental health may decline, potentially leading to a corresponding decline in cardiometabolic health. 22 , 23 , 24 Lastly, different racial and ethnic groups experience varying rates of losing an initial health advantage, 19 although it is unknown if similar differences exist among disaggregated racial and ethnic groups.
Prior studies have evaluated the association between proxy measures of acculturation and prevalent hypertension among Mexican adults, reporting similar results to the current study in a survey study of adults in California 25 and in a cohort study of 6 large metropolitan areas of the United States. 26 Previous studies assessing hypercholesterolemia among Mexican adults are difficult to compare as they used composite measures of cardiometabolic risk or different reference groups. 14 , 27 , 28 For example, one study reported that among 2298 Mexican adults, US nativity was associated with an approximate 2‐fold increased risk of a composite measure of cardiovascular risk comprising a history of cardiovascular disease and at least 1 of several other markers of cardiovascular risk such as diabetes, hypertension, hypercholesterolemia, and current smoking. 28 Although data on lifestyle factors were not available in the current study, these associations were previously attributed to a higher prevalence of lifestyle risk factors, such as increased dietary salt intake and smoking among more acculturated adults. 26
To our knowledge, the finding of a lower prevalence of hypertension and hypercholesterolemia among US‐born Puerto Rican adults compared with those who were not born in the United States has not been previously reported. One similar study evaluating a regional population of 1357 adults reported that greater acculturation, measured by English language preference for daily activities, was significantly associated with higher self‐rated health. 29 Based on these studies, it is unclear why, among all other detailed categories of Hispanic adults, results were either not significant or showed a significant negative association. It is possible that due to the unique status of Puerto Rico as a US territory, there was misclassification in self‐reported nativity. For example, since the questionnaire item on US nativity did not specify being born in a US state or territory, if some adults interpreted the question to refer only to US states, the observed findings may be attributed to differences between mainland‐born and archipelago‐born Puerto Rican adults, such as greater health care access and socioeconomic advantage among mainland‐born adults. 30
The most consistent finding among detailed Asian groups was the positive association between US nativity and longer length of US residence and both prevalent hypertension and hypercholesterolemia among Chinese adults. Prior studies to explain potential mechanisms are mostly limited to small, regional populations of immigrants showing greater acculturation to be associated with a range of findings from unhealthy dietary changes to increased physical activity. 6 , 31 , 32 , 33 One study conducted by Lim et al. in a nationally representative sample of 6029 Asian adults reported similar findings of a higher prevalence of diabetes, hypertension, and hypercholesterolemia among Chinese adults who were born in the United States compared with those who were not born in the United States, although it is not clear if these differences were statistically significant. 34 The collective evidence is therefore limited and unlikely to adequately explain the observed results. Moreover, it is unclear why greater acculturation may be associated with a higher prevalence of cardiometabolic risk factors among Chinese adults and not among other Asian detailed categories in the current study.
US nativity among Filipino adults was negatively associated with hypercholesterolemia. Reflecting these findings, Lim et al. reported a hypercholesterolemia prevalence of 39.0% among non‐US born Filipino adults compared with 33.8% among US‐born Filipino adults. 34 Another study among Filipino adults in California reported similar findings for hypertension, showing US nativity compared with non‐US nativity was associated with a lower prevalence of hypertension. 35 One study reported a significant 16% higher prevalence of hypercholesterolemia among Southeast Asian adults compared with NH White adults, although these findings are difficult to compare due to differing methodologies. 36 In the current study, because associations between nativity or length of US residence and other cardiometabolic risk factors were not significant, results may be spurious and attributed to statistical variability. However, prior studies consistently showed that among Asian detailed categories, Filipino and Indian adults had the highest prevalence of cardiometabolic risk factors, cardiovascular disease, and obesity. 37 , 38 , 39 This high‐risk profile therefore renders more plausible causal explanations for how acculturation might affect these Filipino adults differently compared with other Asian detailed categories.
Among aggregated racial groups, the association between US nativity or longer length of US residence and an increased prevalence in all 3 cardiometabolic risk factors among NH Black adults has been previously reported. 13 , 40 , 41 These findings have been attributed to a variety of factors, such as higher socioeconomic status, a higher prevalence of healthy lifestyle behaviors, increased screening, and a lower prevalence of obesity among non‐US born NH Black adults compared with US‐born NH Black adults. 40 , 41 , 42 Similar mechanisms among NH White adults 43 are hypothesized to underlie the association between US nativity and prevalent hypertension observed in this population, which has also been previously reported. 44 Although detailed categories for NH Black and NH White adults were not available in the current study, future studies with such data might show differences in the association between proxy measures of acculturation and the prevalence of cardiometabolic risk factors, given results of prior similar studies. For example, given that the heterogeneity of adults categorized as NH White might contribute to differences in disability among detailed categories of NH White adults, similar differences might also be seen for other risk factors or health outcomes. 43 Moreover, a prior study showing higher screening rates for cardiometabolic risk factors among African immigrants with a longer length of stay in the United States also showed that screenings rates differed based on country of origin. 42
Challenges in identifying how and why proxy measures of acculturation are associated with cardiometabolic risk factors lie in the lack of a sufficiently large evidence base, given the difficulty in both collecting adequate measures of acculturation and statistically reliable disaggregated race and ethnicity data. New federal standards for collecting disaggregated race and ethnicity data in the United States 45 may be followed to ensure such data are available for future studies. Research may also be advanced with the availability of disaggregated race or ethnicity data in electronic health record data, 46 which may provide sufficiently large sample sizes for reliable estimates, though may be subject to greater misclassification. 47 An additional challenge lies in how acculturation is defined and operationalized in health research. Given the complexity of acculturation as a multidimensional construct, it has been defined inconsistently as a quantifiable variable in epidemiologic research. 48 , 49 Although detailed questionnaires tailored for each racial and ethnic detailed category might be most comprehensive, they may be impractical and feasible only in research cohorts. In practice, proxy measures of acculturation such as nativity, length of residence, and language preference can be used with appropriate acknowledgment of their strengths and limitations and made available in administrative data, such as insurance claims or electronic health record data. 46 , 50
Additional studies using both disaggregated data and comprehensive measures of acculturation may shed light on mechanisms such as the Hispanic paradox of lower cardiovascular mortality risk among Hispanic populations despite a higher risk profile, 51 an association that may be mediated in part by acculturation 52 and that has not been thoroughly explored among disaggregated data. From a public health perspective, it may be most impactful to identify those aspects of acculturation that can shape feasible and practical interventions to maximize the effectiveness of efforts to reduce cardiometabolic risk. Moreover, future studies may also distinguish acculturation from assimilation, a construct defined as adopting a dominant culture's practices and values while discarding those from one's culture of origin, and which may form part of the acculturation process. 49 Assimilation might affect cardiometabolic risk in Hispanic populations through pathways such as loss of social support and healthy behaviors associated with traditional cultural values. 53 Lastly, given that 88% of population growth through 2065 is projected to be attributed to non‐US born individuals and their descendants, along with the shifting trends in detailed categories of racial and ethnic groups comprising the US population, 54 , 55 continuous public health surveillance may best identify groups facing the greatest burden of cardiometabolic risk.
The study is subject to at least 5 limitations. First, proxy measures of acculturation were limited. Although high statistical correlation has been reported between more comprehensive measures of acculturation and proxy measures such as length of residence in the United States, 56 , 57 the measures used in the current study might be insufficient to capture other constructs of acculturation (eg, language preference, cultural identification, social networks, collectivism, dietary preferences). 49 , 58 For example, assessing individual characteristics such as nativity and length of US residence might not capture the multidimensional nature of acculturation. Appropriate measurement of acculturation may also vary for each racial and ethnic detailed category, as evidenced by the variety of acculturation scales developed for specific detailed categories. 58 Second, the questionnaire collected data on only disaggregated Asian and Hispanic groups, limiting generalizability to the broader population. Disaggregation of other groups, such as NH Black adults by region of birth, and further disaggregation of existing detailed categories, such as to delineate other Asian and Pacific Islander adults, which were unavailable, may also demonstrate heterogeneity in the association between acculturation and cardiometabolic risk factors. 13 Third, self‐reported observational data may result in residual confounding (eg, with ordinal categories of age or unmeasured factors such as interpersonal or structural racism) and recall bias for both the select proxy measures of acculturation and cardiometabolic risk factors. For example, recall bias may result in an underestimate of actual prevalence of cardiometabolic risk factors due to factors such as undiagnosed risk factors or social desirability bias. Fourth, the self‐reported cross‐sectional data also limit the ability to assess to what extent the positive association between length of residence in the United States and cardiometabolic risk factors can be attributed to an actual increase in prevalence (due to increased adoption of unhealthy lifestyle behaviors, discrimination, and other stressors) or due to greater detection from factors such as increased health care access or English proficiency. 6 , 13 Lastly, the association between length of US residence and cardiometabolic risk factors may differ by age. For example, younger adults born outside the United States who have spent less time in the country may be at lower risk for cardiometabolic risk factors compared with those with longer US residence, as the latter are more likely to have adopted aspects of the host culture early in life. 49 In contrast, older adults with shorter US residence may be less likely to assimilate to the new culture. 49 However, because cardiometabolic risk factors are more prevalent among adults in mid‐ to late life, the influence of age on the association between length of residence and cardiometabolic risk may be small.
CONCLUSIONS
The substantial heterogeneity in the association between proxy measures of acculturation and cardiometabolic risk factors highlights the role of data disaggregation in accurate characterization of such associations. These findings are particularly salient in light of the continuously shifting demographic composition of the United States and the key role of diabetes, hypertension, and hypercholesterolemia as modifiable risk factors for cardiovascular disease. However, with the currently limited evidence base, potential explanations for disparities among detailed categories of racial and ethnic groups are predominately speculative rather than evidence based. Further studies can be facilitated by using longitudinal samples and increased collection of disaggregated data among all race and ethnicity groups, which may increase with recently updated federal standards for data collection. A better understanding of the mechanisms underlying the observed disparities may then guide culturally competent care and appropriately tailored interventions to reduce cardiovascular disease risk.
Disclaimer
The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
Sources of Funding
No funding was received for the conduct of this study.
Disclosures
Dr Yang reports the following relationships: Advisory Board: Measure Labs, Mineralys, Qure.ai, Sky Labs, TenPoint7; Consulting: Genentech; Honoraria: American College of Cardiology; Research Grants: Microsoft Research.
Supporting information
Tables S1–S2
This article was sent to Tiffany M. Powell‐Wiley, MD, MPH, Associate Editor, for review by expert referees, editorial decision, and final disposition.
Supplemental Material is available at https://www.ahajournals.org/doi/suppl/10.1161/JAHA.124.038306
For Sources of Funding and Disclosures, see page 13.
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Supplementary Materials
Tables S1–S2