Skip main navigation

Social Determinants of Cardiovascular Risk Factors Among Asian American Subgroups

Originally published of the American Heart Association. 2024;13:e032509



Social determinants of health (SDOH) play a significant role in the development of cardiovascular risk factors. We investigated SDOH associations with cardiovascular risk factors among Asian American subgroups.

Methods and Results

We utilized the National Health Interview Survey, a nationally representative survey of US adults, years 2013 to 2018. SDOH variables were categorized into economic stability, neighborhood and social cohesion, food security, education, and health care utilization. SDOH score was created by categorizing 27 SDOH variables as 0 (favorable) or 1 (unfavorable). Self‐reported cardiovascular risk factors included diabetes, high cholesterol, high blood pressure, obesity, insufficient physical activity, suboptimal sleep, and nicotine exposure. Among 6395 Asian adults aged ≥18 years, 22.1% self‐identified as Filipino, 21.6% as Asian Indian, 21.0% as Chinese, and 35.3% as other Asian. From multivariable‐adjusted logistic regression models, each SD increment of SDOH score was associated with higher odds of diabetes among Chinese (odds ratio [OR], 1.45; 95% CI, 1.04–2.03) and Filipino (OR, 1.24; 95% CI, 1.02–1.51) adults; high blood pressure among Filipino adults (OR, 1.28; 95% CI, 1.03–1.60); insufficient physical activity among Asian Indian (OR, 1.42; 95% CI, 1.22–1.65), Chinese (OR, 1.58; 95% CI, 1.33–1.88), and Filipino (OR, 1.24; 95% CI, 1.06–1.46) adults; suboptimal sleep among Asian Indian adults (OR, 1.20; 95% CI, 1.01–1.42); and nicotine exposure among Chinese (OR, 1.56; 95% CI, 1.15–2.11) and Filipino (OR, 1.50; 95% CI, 1.14–1.97) adults.


Unfavorable SDOH are associated with higher odds of cardiovascular risk factors in Asian American subgroups. Culturally specific interventions addressing SDOH may help improve cardiovascular health among Asian Americans.

Nonstandard Abbreviations and Acronyms


Life's Essential 8


National Health Interview Survey


non‐Hispanic White


social determinants of health

Clinical Perspective

What Is New?

  • Unfavorable social determinants of health (SDOH) are associated with more cardiovascular risk factors among Asian Americans, including suboptimal sleep.

  • A higher number of unfavorable individual and neighborhood‐level SDOH factors are associated with a 20% to 60% greater likelihood of having cardiovascular risk factors.

  • Association between unfavorable SDOH and cardiovascular disease risk factors varies significantly between Asian subgroups.

What Are the Clinical Implications?

  • A patient's SDOH must be considered when assessing cardiovascular risk.

  • Addressing unfavorable SDOH may reduce risk of major cardiovascular risk factors, including high blood pressure, diabetes, nicotine exposure, suboptimal sleep, and physical activity levels.

Cardiovascular disease (CVD) is the leading cause of death in the United States, and the prevalence of optimal cardiovascular health remains low.1, 2 In 2022, the American Heart Association revised its definition of ideal cardiovascular health to include 8 metrics: healthy diet, sufficient physical activity, avoidance of nicotine exposure, optimal sleep quality and duration, healthy weight, and healthy levels of blood cholesterol, blood glucose, and blood pressure, titled the Life's Essential 8 (LE8).1 Optimizing these lifestyle factors is challenging, because the likelihood of meeting more than 5 of these ideal metrics was <30% among US adults over the age of 20 years.1

Optimal cardiovascular health is influenced by social determinants of health (SDOH), which encompass a wide range of domains, including socioeconomic status, health care access, education, and environmental factors such as where people live and their interactions with neighbors.1 SDOH are upstream factors that impact cardiovascular risk and health outcomes.3 Heart disease prevalence has also been shown to differ by race/ethnicity, ranging from 7.7% (non‐Hispanic Asian adults), 8.2% (Hispanic adults), 10.0% (non‐Hispanic Black adults), and 11.5% (non‐Hispanic White adults), highlighting the marked racial/ethnic disparities in heart disease in the United States.3 Although Asian Americans in aggregate have the lowest prevalence of CVD, SDOH differ substantially between Asian American subgroups. For example, the median annual household income is $86 000 for the Asian population in aggregate, ranging from $44 000 among the Burmese population to $119 000 among the Indian population.4 Consequently, CVD prevalence varies significantly among subgroups, ranging from 3.0% among Chinese adults to 6.1% among Filipino adults.5

The Asian American population is the fastest growing racial/ethnic group in the United States.6 Although the Asian American population consists of multiple ethnic groups with different cultures and experiences, these groups are often aggregated into a single “Asian” category, masking the substantial heterogeneity in health among these subgroups. For example, while Asian Americans in aggregate are less likely to die from heart disease than other racial/ethnic groups in the United States,7 there is wide diversity in cardiovascular health among Asian subgroups. A 2014 study found that Filipino and South Asian populations have an increased risk of coronary heart disease compared with all other major Asian ethnic subgroups in the United States.8 Furthermore, death certificate data show that Asian Indian women and men had the highest age‐standardized mortality rates due to ischemic heart disease among Asian subgroups, which were as high as or exceeded the mortality rates of the non‐Hispanic White population.9

Although literature on the impact of SDOH on cardiovascular risk among Asian American subgroups is sparse, an extant qualitative study of 13 Asian American communities identified barriers to health care access that encompass the SDOH, including lack of health insurance, immigration status, cost of medication, transportation, appointment scheduling conflict, language access, and health literacy.10 As emerging studies continue to link unfavorable SDOH with suboptimal cardiovascular health, characterizing the associations of SDOH with cardiovascular risk among disaggregated Asian American subgroups may help identify underlying causes for differences in CVD between Asian American groups.

Using the National Health Interview Survey (NHIS) from 2013 to 2018, we investigated the relationship between 6 critical SDOH domains and cardiovascular risk factors, informed by LE8, among disaggregated Asian subgroups. We hypothesized that the association between unfavorable SDOH and cardiovascular risk factors would differ among Asian American subgroups.


Data Source

We analyzed data from the NHIS, a nationally representative US household survey from the years 2013 to 2018. The NHIS is an annual cross‐sectional survey conducted among adults and households and is representative of the noninstitutionalized US population. Details on survey structure and data collection are described in detail elsewhere.11 The NHIS was approved by the National Center for Health Statistics Internal Review Board and received informed consent from all respondents. All data have been made publicly available by the National Center for Health Statistics and can be accessed at‐questionnaires‐documentation.htm.

Inclusion/Exclusion Criteria

From 190 113 participants in the NHIS 2013 to 2018, we included all respondents who self‐identified as non‐Hispanic Asian (n=10 353), including Asian Indian, Chinese, Filipino, and “other Asian,” an aggregate category that represents Japanese, Korean, Vietnamese, and other Asian individuals. Disaggregated data on the “other Asian” group are not publicly available to maintain participant confidentiality due to small sample size. We excluded individuals who had missing responses for nativity status (n=33) and any SDOH variables (n=3925), both defined below. Our total analytical sample size was 6395 non‐Hispanic Asian adults. Compared with excluded individuals, included individuals were more likely to be women, older, have higher family income, and have greater educational attainment (Table S1). Due to the high degree of missing data, a supplementary analytic sample includes 10 167 participants with at least 10 available SDOH variables (n=10 167).

Social Determinants of Health

Our exposure of interest was a composite SDOH score, categorized into 6 domains: economic stability; neighborhood, physical environment, and social cohesion; community and social context; food security; education; and health care system. Modeling the burden of social disadvantage framework from Javed et al, we created a summative SDOH score that included variables available in the NHIS for all survey years (2013–2018).12, 13, 14 Participants who answered “yes” (an unfavorable response) to a SDOH variable question were assigned “1” to their SDOH score, while those who answered “no” (a favorable response) to the SDOH variable question were assigned “0” for that variable. The SDOH score ranged from 0 to 27, with 27 representing the least favorable SDOH score. We calculated an alternative SDOH measure using individuals responding to at least 10 of the 27 questions in the following manner: the difference between % SDOH score, calculated as the proportion of unfavorable SDOH from the total number of SDOH, and overall mean score was divided by overall % SDOH score SDs. The individual SDOH variables contributing to the summative score are listed in Table S2. SDOH score was modeled SD units. We also categorized participants into quartiles of SDOH score based on sample distribution.

Cardiovascular Risk Factors

The outcomes of interest are the presence of cardiovascular risk factors consistent with components of the American Heart Association's LE8: insufficient physical activity, nicotine exposure, sleep quality and duration, obesity, high cholesterol, diabetes, and high blood pressure.1 Physical activity was dichotomized into sufficient (≥150 minutes/wk) and insufficient (<150 minutes/wk) categories. Nicotine exposure was determined if an individual reported to be a former smoker, current every day smoker, current some day smoker, or smoker with current status unknown and does not take second‐hand or family exposure into account; otherwise, they were classified as nonsmokers. Examining smoking history and duration rather than current smoking status alone is necessary because earlier exposure is associated with increased health risk and allows for better understanding of an individual's health behaviors.15 Optimal sleep duration for adults was 7 to 9 hours, whereas suboptimal sleep was considered <7 or >9 hours. Self‐reported binary (yes/no) responses were utilized to assess health professional–diagnosed high cholesterol, diabetes, and high blood pressure. Asian‐specific body mass index (BMI) cutoffs were used, with obesity defined as BMI ≥27.5 kg/m2 or not obese if BMI <27.5 kg/m2 based on self‐reported height and weight. Studies have demonstrated higher prevalence of metabolic syndrome, including insulin resistance and systemic inflammation that are characteristic of diabetes, at lower BMI for Asian populations.16, 17 We also utilized the standard BMI ≥30 kg/m2 cutoff for obesity to compare for differences.


Age was a continuous variable, which we binned into 3 categories (18–44, 45–64, and ≥65 years). Sex was coded into binary “Male” or “Female.”

Statistical Analysis

The prevalence of cardiovascular risk factors was calculated and age standardized to the US 2010 standard population.18 We utilized Rao‐Scott χ2 and Wald tests to compare cardiovascular risk factors and SDOH among Asian subgroups. We conducted multivariable logistic regression to evaluate the association of each SD increment of SDOH score with each cardiovascular risk factor, adjusted for age category, sex, and all other cardiovascular risk factors. In sensitivity analyses, we repeated multivariable adjusted logistic regression using a z‐score standardized % SDOH score among participants with at least 10 available SDOH variables. Analyses were weighted based on pooled 6‐year sample weights extracted from the Integrated Public Use Microdata Series.19 Statistical significance was determined at a P value <0.05. All statistical analyses were conducted in RStudio Version 1.4.171720 using the survey package to account for the complex survey design of the NHIS.21


Study Demographics

The study included 6395 Asian adults ≥18 years of age, representing 8 831 514 Asian Americans in the United States (Table 1). A majority of the study population was in the 18 to 44 year age category (51.6%), female (55.9%), and born outside of the United States (77.0%).

Table 1. General Characteristics of Asian Americans in the NHIS 2013 to 2018 (n=6395)

CharacteristicWeighted % (SE)
All Asian (n=6395)Asian Indian (n=1383)Chinese (n=1341)Filipino (n=1412)Other Asian (n=2259)P value
Population frequency (SE)8 831 514 (286715)2 241 020 (113777)1 841 216 (104592)1 870 490 (101441)2 878 790 (121699)
18–4451.6 (1.0)60.5 (1.8)52.2 (1.9)43.1 (1.8)49.8 (1.7)
45–6432.6 (0.8)29.5 (1.6)31.6 (1.6)38.2 (1.7)32.1 (1.4)
≥6515.8 (0.6)10.0 (1.0)16.3 (1.4)18.7 (1.2)18.1 (1.1)
Female55.9 (0.8)50.6 (1.8)54.9 (1.7)60.1 (1.8)57.9 (1.5)<0.05
Non‐US born77.0 (0.1)91.4 (0.8)76.7 (1.4)65.6 (1.9)73.4 (1.5)<0.05

Characteristics across Asian subgroups were compared using Rao‐Scott χ2 test, with statistically significant differences at P <0.05. NHIS indicates National Health Interview Survey.

The distribution of each SDOH item is shown in Table 2 for all Asian adults and stratified by Asian subgroup. The distribution of SDOH items differed by Asian subgroup (P <0.05). Mean SDOH score ranged from 5.2 among Asian Indian adults to 6.4 among other Asian adults. The age‐standardized prevalence of each cardiovascular risk factor stratified by Asian subgroup is shown in Figure 1. Among the Asian subgroups, other Asian adults reported the highest prevalence of nicotine exposure (9.9% [95% CI, 2.6–4.9]; P <0.05), while Asian Indian adults reported the highest prevalence of diabetes (11.9% [95% CI, 9.7–14.4]; P <0.05). Filipino adults reported the highest prevalence of 4 out of 7 cardiovascular risk factors compared with other subgroups: suboptimal sleep (40.7% [95% CI, 37.3–44.2]), high cholesterol (32.8% [95% CI, 30.1–35.6]), high blood pressure (33.7% [95% CI, 31.0–36.4]), and obesity (30.1% [95% CI, 26.8–33.5]). The prevalence of insufficient physical activity did not differ by Asian subgroup. The age‐standardized prevalence of cardiovascular risk factors stratified by SDOH quartiles was also calculated among all Asian adults (Figure 2). There is a significant trend toward higher prevalence of insufficient physical activity, nicotine exposure, suboptimal sleep, diabetes, and high blood pressure with less favorable SDOH quartiles (P trend <0.05). We did not observe a significant trend for obesity (P‐trend=0.60) or high cholesterol (P‐trend=0.24). When we conducted sensitivity analyses utilizing the ≥30 kg/m2 threshold as an alternative definition for obesity, we found similar nonsignificant trends in associations of SDOH and cardiovascular risk factors (results not shown).

Table 2. Prevalence of Each Unfavorable SDOH by Asian Subgroup

SDOH characteristicsWeighted % (SE)
All Asian (n=6395)Asian Indian (n=1383)Chinese (n=1341)Filipino (n=1412)Other Asian (n=2259)P value
Economic stability
Unemployed34.6 (0.8)29.4 (1.5)34.7 (1.7)33.6 (1.6)39.3 (1.3)<0.05
Low family income (<200% of poverty threshold)23.8 (0.9)16.2 (1.2)26.7 (1.8)18.8 (1.5)31.2 (1.6)<0.05
Difficulty paying medical bills11.5 (0.6)9.7 (1.1)6.5 (0.9)15.5 (1.3)13.6 (1.0)<0.05
High financial stress20.5 (0.8)20.3 (1.5)13.1 (1.1)26.8 (1.8)21.5 (1.2)<0.05
Poor medication adherence due to cost2.8 (0.3)1.4 (0.4)1.9 (0.5)4.1 (0.7)3.5 (0.6)<0.05
Foregone/delayed medical care due to cost4.0 (0.3)2.7 (0.4)3.4 (0.6)4.2 (0.6)5.2 (0.6)<0.05
Neighborhood and social cohesion
Home rented/other arrangement35.1 (1.0)36.6 (2.2)34.9 (1.8)29.7 (1.9)37.6 (1.5)<0.05
People in this neighborhood do not help each other out13.5 (0.6)10.1 (1.0)13.3 (1.1)15.3 (1.2)15.3 (1.1)<0.05
There are no people I can count on in this neighborhood14.2 (0.6)11.7 (1.0)13.5 (1.2)14.9 (1.3)16.2 (1.1)<0.05
People in this neighborhood cannot be trusted11.0 (0.5)6.7 (0.8)9.8 (0.8)14.3 (1.4)13.0 (0.9)<0.05
This is not a close‐knit neighborhood31.4 (0.8)27.0 (1.4)33.0 (1.9)33.5 (1.7)32.6 (1.4)<0.05
Mental health
Have psychological distress1.5 (0.2)0.6 (0.2)1.5 (0.3)2.1 (0.5)2.0 (0.4)<0.05
Food security
Food insecure3.2 (0.3)1.5 (0.4)2.0 (0.5)3.9 (0.7)4.7 (0.6)<0.05
Low English proficiency13.6 (0.7)6.4 (0.9)22.3 (1.9)3.3 (0.7)20.4 (1.5)<0.05
≤HS/GED education level22.8 (0.9)14.5 (1.4)23.0 (2.1)21.5 (1.7)29.9 (1.5)<0.05
Did not look up health information on Internet in past 12 mo47.8 (1.0)41.2 (2.0)46.3 (2.1)47.9 (1.9)53.8 (1.6)<0.05
Did not fill a prescription on Internet in past 12 mo90.3 (0.6)91.3 (0.9)90.7 (1.3)87.3 (1.4)91.1 (0.9)<0.05
Did not schedule medical appointment on Internet in past 12 mo81.0 (0.9)77.9 (1.6)77.7 (1.8)82.9 (1.5)84.3 (1.1)<0.05
Did not communicate with health care provider by email in past 12 mo82.9 (0.8)80.8 (1.5)82.2 (1.6)85.4 (1.4)83.5 (1.1)0.12
Health care utilization
Uninsured4.0 (0.3)3.1 (0.6)2.3 (0.4)4.1 (0.7)5.7 (0.8)<0.05
No place for source of care8.9 (0.5)9.7 (0.9)6.5 (0.8)8.0 (1.1)10.5 (0.8)<0.05
Delayed medical care: could not get through on phone2.2 (0.2)2.0 (0.5)1.9 (0.4)2.6 (0.6)2.4 (0.5)0.75
Delayed medical care: could not get appointment soon enough6.5 (0.5)6.3 (0.9)7.2 (1.0)6.5 (0.8)6.2 (0.8)0.84
Delayed medical care: long waiting time at MD's office4.6 (0.3)2.7 (0.4)4.7 (0.7)5.1 (0.8)5.6 (0.7)<0.05
Delayed medical care: closed when you could go2.3 (0.3)2.1 (0.5)2.9 (0.7)1.8 (0.5)2.4 (0.5)0.57
Delayed medical care: no transport1.1 (0.2)0.7 (0.3)1.1 (0.3)1.5 (0.4)1.1 (0.3)0.47
Dissatisfied with quality of care4.8 (0.4)3.7 (0.5)4.8 (0.7)4.2 (0.8)6.2 (0.8)<0.05
SDOH score mean (SD)5.8 (2.8)5.2 (2.5)5.7 (2.8)5.8 (2.7)6.4 (3.0)<0.05

SDOH prevalence and SDOH score mean across Asian subgroups were compared using Rao‐Scott χ2 test and Wald test, respectively, with statistically significant differences at P <0.05. GED indicates general education development; HS, high school; MD, medical doctor; and SDOH, social determinants of health.

Figure 1. Age‐standardized prevalence of cardiovascular risk factors among Asian subgroups.

*Denotes that cardiovascular prevalence differed significantly by Asian subgroup (P <0.05).

Figure 2. Age‐standardized prevalence of cardiovascular risk factors by unfavorable SDOH quartile among Asian adults.

*Denotes that cardiovascular prevalence differed significantly by SDOH quartile (P <0.05). Note: 1st quartile: SDOH score from 0 to 4; 2nd quartile: SDOH score from 5 to 6; 3rd quartile: SDOH score from 7 to 8; 4th quartile: SDOH score ≥9. SDOH indicates social determinants of health.

SDOH Score and Cardiovascular Risk Factors

After adjusting for covariates, we observed significant relationships between SDOH score and 6 out of 7 cardiovascular risk factors among aggregated Asian adults in the study (Table 3): a 1 SD higher SDOH score (a score difference of 2.8; ie, less favorable SDOH) was associated with a 11% lower odds of high cholesterol (odds ratio [OR], 0.89 [95% CI, 0.82– 0.97]), 14% greater odds of high blood pressure (OR, 1.14 [95% CI, 1.05–1.25]), 17% greater odds of suboptimal sleep (OR, 1.17 [95% CI, 1.08– 1.27]), 24% greater odds of diabetes (OR, 1.24 [95% CI, 1.10–1.41]), 38% greater odds of insufficient physical activity (OR, 1.38 [95% CI, 1.28–1.48]), and a 39% greater odds of nicotine exposure (OR, 1.39 [95% CI, 1.21–1.59]). The association between SDOH score and obesity was not significant using the Asian‐specific obesity cut point (OR, 0.99 [95% CI, 0.91–1.08]) or the standard obesity cut point (OR, 1.04 [95% CI, 0.93–1.17]). The interaction between SDOH score and Asian subgroup was not significant for any cardiovascular risk factor, and Asian subgroup‐stratified analyses revealed similar trends (Table 3). For example, a 1 SD higher SDOH score was associated with greater odds of diabetes by 45% among Chinese adults (95% CI, 1.04– 2.03), 24% among Filipino adults (95% CI, 1.02–1.51), and 22% among other Asian adults (95% CI, 1.00–1.50).

Table 3. Associations Between Unfavorable SDOH Score and Cardiovascular Risk Factors

All Asian (OR, 95% CI)Asian Indian (OR, 95% CI)Chinese (OR, 95% CI)Filipino (OR, 95% CI)Other Asian (OR, 95% CI)
Insufficient physical activity1.38 (1.28–1.48)*1.42 (1.22–1.65)*1.58 (1.33–1.88)*1.24 (1.06–1.46)*1.31 (1.16–1.49)*
Nicotine exposure1.39 (1.21–1.59)*1.15 (0.84–1.58)1.56 (1.15–2.11)*1.50 (1.14–1.97)*1.34 (1.09–1.65)*
Suboptimal sleep1.17 (1.08–1.27)*1.20 (1.01–1.42)*1.11 (0.93–1.32)1.05 (0.90–1.22)1.26 (1.12–1.41)*
Obesity0.99 (0.91–1.08)1.10 (0.92–1.32)0.95 (0.77–1.18)1.00 (0.85–1.17)0.94 (0.80–1.12)
High cholesterol0.89 (0.82–0.97)*0.83 (0.69–1.01)1.05 (0.86–1.28)0.86 (0.71–1.04)0.88 (0.75–1.03)
Diabetes1.24 (1.10–1.41)*1.14 (0.88–1.47)1.45 (1.04–2.03)*1.24 (1.02–1.51)*1.22 (1.00–1.50)*
High blood pressure1.14 (1.05–1.25)*1.07 (0.87–1.31)0.88 (0.70–1.10)1.28 (1.03–1.60)*1.25 (1.06–1.46)*

All models are adjusted for age, sex, and all other cardiovascular risk factors. Example: Diabetes OR is adjusted for age, sex, high cholesterol, high blood pressure, obesity, physical activity, smoking, and sleep. Models run among All Asians are also adjusted for Asian subgroups. OR indicates odds ratio; and SDOH, social determinants of health.

*Denotes statistical significance (P<0.05).

Sensitivity Analyses

Among the 10 167 participants with at least 10 available SDOH variables, participant characteristics did not differ significantly between included and excluded participants except for the Asian subgroup (P <0.05) (Table S3). In multivariable‐adjusted logistic regression, we found similar associations, where among Asian adults, a 1‐z‐score % increase in SDOH score was associated with increased odds of insufficient physical activity, nicotine exposure, suboptimal sleep, diabetes, and high blood pressure and a lower odds of high cholesterol (Table S4). We examined associations between SDOH and nicotine exposure by sex and found that they did not differ significantly among Asian Americans (P=0.08). Race/ethnic‐specific associations are shown in Table S5, and we noted similar findings across the racial/ethnic groups.


In this large population study of Asian American adults, unfavorable SDOH were significantly associated with insufficient physical activity, nicotine exposure, suboptimal sleep, and diabetes among Asian Americans. In contrast, unfavorable SDOH was associated with lower odds of high cholesterol. These relationships did not differ by Asian subgroups in stratified analyses. SDOH are associated with higher prevalence of cardiovascular risk factors across all Asian adults.

Domains of SDOH are interconnected and promote unfavorable cardiovascular risk profiles through complex mechanisms.22 Research has shown cumulative burden of SDOH domains to associate with risk of stroke23 and cardiovascular risk factors (eg, hypertension, diabetes, smoking, and obesity)24 among US adults. Thus, measuring the cumulative impact of SDOH provides additional context that may assist in understanding cardiovascular health outcomes in an under‐researched population. Socioeconomic status is an SDOH with significant impact on cardiovascular risk.25 For example, in the Atherosclerosis Risk in Communities Study, Wang et al found that a ≥50% household income drop over an average of 6 years was associated with greater likelihood of incident CVD, compared with participants who did not experience this drop.26 The researchers attribute this finding to shifts in health behaviors, such as consumption of energy dense and high caloric foods, loss of health insurance, and increased stress. Furthermore, income volatility and income drop over 15 years was associated with a 2‐fold increase of CVD events.27 In a study focused on Asian American subgroups conducted in New York City, residence in neighborhoods with lower economic privilege, quantified as the census‐tract level disparity in number of high versus low income households, was associated with increased prevalence of both diabetes and hypertension.28 The strength of this relationship differed by Asian subgroup, with Bangladeshi and Pakistani adults experiencing the highest prevalence of diabetes and Filipino adults experiencing the highest prevalence of hypertension. In contrast, the opposite relationship was observed among Korean adults, warranting future study into the heterogeneous impact of neighborhood economic gradients on cardiovascular risk by Asian subgroup.

The degree of neighborhood cohesion has been found to influence associations between other SDOH and health outcomes in areas with diverse Asian American populations. Social cohesion and capital are negatively associated with obesity and positively associated with physical activity, which may be due to supportive social and physical environments.29 On the other hand, the lack of association between SDOH and obesity in our study may arise from the self‐reported nature of the NHIS, resulting in measurement inaccuracies and more conservative (nonsignificant) estimates. In contrast, a prior NHIS study found unfavorable SDOH associated with higher obesity prevalence among US adults.12 This study evaluated the general US population and utilized an obesity threshold of BMI ≥30 kg/m2 whereas our study used the World Health Organization recommended threshold specific to Asian populations (BMI >27.5 kg/m2). The lower threshold may account for environmental, dietary, and social differences that contribute to greater prevalence of CVD at lower BMI for Asian populations. Our observation of nonsignificant trends between SDOH and cardiovascular risk factors after threshold adjustment is also seen in a New York City study that adjusted BMI thresholds to evaluate obesity prevalence among Asian American adults.29 Despite lower BMI prevalence, there is a significant association of increasing BMI and risk of hypertension and diabetes among Asian American people when using race/ethnic‐specific thresholds.30, 31

Education and health literacy status may also contribute to cardiovascular health among Asian Americans observed in our study. Blomster et al found an increased risk of major cardiovascular events (death from CVD, nonfatal stroke, or nonfatal myocardial infarction), microvascular events (new or worsening renal disease or diabetic eye disease), and all‐cause mortality associated with low educational attainment in adjusted models that accounted for lifestyle factors.32 For the Asian American population, the “Model Minority” myth has often been perpetuated, which inaccurately stereotypes all Asian Americans to have high income, educational background, and better overall health compared with other racial/ethnic subgroups.30 However, there are many Asian subgroup disparities and inequities not captured in our study. For example, 25% of Mongolian Americans are living in poverty and only 15% of Bhutanese Americans have a college degree, compared with 10% of the Asian population living in poverty and 54% of Asian adults with a bachelor's degree or higher, respectively.33 Lower levels of educational attainment have been associated with less ideal cardiovascular health among US‐ and foreign‐born Asian adults even when stratified by length of residence in the United States.34 Our group has previously demonstrated that higher levels of acculturation are associated with higher prevalence of cardiovascular risk factors among Asian immigrants in the NHIS.35

Food security plays a role in cardiovascular health risks, as adults who reported low food security had over 2‐fold higher odds of 10‐year atherosclerotic CVD risk of >20% compared with those who were food secure,36 and remains an overlooked issue in Asian populations. Research from the California Health Interview Survey revealed heterogeneity in the prevalence of food security among Asian subgroups, with the Vietnamese American population having the highest prevalence of food insecurity. Lower English proficiency was also associated with food insecurity, because foreign‐born Chinese, Filipino, and South Asian populations have greater food insecurity compared with their respective US‐born populations.37 The temporal trends of lower physical activity and healthy dietary patterns in Asian Americans have been associated with lower prevalence of normal weight and higher blood pressure levels in sensitivity analyses.38 Potential dietary restrictions imposed by financial burdens could also heighten the desire for caloric overconsumption and affect chronic diseases or coping behaviors, such as smoking, that contribute to CVD risk.36 Dietary consumption patterns have also been linked to cardiovascular risk factors, including obesity, hypertension, and diabetes.39 A recent National Health and Nutrition Examination Survey found an association of ultraprocessed food intake, which has been linked to CVD, and increased acculturation among Asian Americans.40

Despite efforts of the NHIS to oversample Asian American individuals,41 the sample size of Asian adults was relatively small, which precluded disaggregated analysis of the other major Asian populations, including Japanese, Korean, Vietnamese people, and other smaller Asian subgroups. Due to exclusion of individuals missing responses to variables of interest, certain demographic characteristics (women, older age, higher family income, and greater educational attainment) were more prevalent in the study population. This may limit the generalizability of our results to the US population. Hence, we conducted sensitivity analyses among included and excluded respondents and found consistent results (Tables S3 and S4). Furthermore, the LE8 standardized metrics utilize ranges to measure cardiovascular health; for example, those who quit smoking ≥5 years ago are given a score closer to that of a nonsmoker, and diet is assessed based on self‐reported intake.1 However, the NHIS survey does not provide such information, so our cardiovascular health assessments could not exactly align with LE8 because we did not have temporal details on smoking status or any dietary variable. The survey was cross‐sectional, so we cannot assess long‐term SDOH patterns that may affect the development of cardiovascular risk factors. Underestimation of risk due to language barriers may have also influenced the representation of Asian and non‐English/Spanish‐speaking respondents, because the survey was only conducted in English and Spanish. Thus, these excluded individuals may have unfavorable SDOH that are not captured in our analysis, as limited linguistic proficiency has been demonstrated to affect an individual's access to care and health status.42 The survey relied primarily on self‐reporting, so recall and social desirability biases may be present in the collected data. We recognize that SDOH may encompass other factors not captured in our study, but our SDOH score was based on previously published research using the NHIS database.12, 13, 14 Additionally, we aimed to account for many SDOH variables, such as financial burden due to medical cost or delaying medical care, that have not been thoroughly studied in relation to SDOH and cardiovascular risks specific to the Asian American population. The SDOH score model creates a holistic approach to analyzing cardiovascular risk across Asian subgroups by integrating different aspects of health patterns and environmental conditions.

Despite the perception that Asian Americans may have lower SDOH scores or be less impacted by SDOH compared with other racial/ethnic groups, our findings indicate that unfavorable SDOH profiles are associated with higher prevalence of cardiovascular risk factors among Asian Americans, including insufficient physical activity, nicotine exposure, suboptimal sleep, diabetes, and high blood pressure (Table S5). Given the limitations of the data and small sample sizes for many Asian American subgroups, it is vital to enrich national surveys, such as the NHIS and the National Health and Nutrition Examination Survey, with more Asian Americans to reveal potential differences in optimal SDOH profiles and cardiovascular risk factor prevalence and outcomes.

Sources of Funding

This study was considered not human subject research by the Stanford University Institutional Review Board (protocol #57474) and was funded by the Stanford Center for Asian Health Research and Education (CARE) and Chi‐Li Pao Foundation. N.S.S. is supported by NIH/NHLBI (K23HL157766). T.E. is supported by NIH/NIMHD (K01MD014158 and P50MD017356). E.Y. is supported by the UW Medicine Asian Health Initiative and the Carl and Renée Behnke Endowed Professorship for Asian Health. The views expressed in this article are those of the authors and do not necessarily represent the views of the Journal of the American Heart Association.


Dr Yang reports a relationship with the American College of Cardiology, Genentech, Mineralys, and Sky Labs that includes consulting/honoraria, reports a relationship with Microsoft that includes research grants, and reports a relationship with Clocktree, Measure Labs, and TenPoint7 that includes consulting or advisory and equity or stocks. The remaining authors have no disclosures to report.


The authors would like to thank the Stanford Center for Asian Research and Education for their support of this study.


* Correspondence to: Eugene Yang, MD, MS, Division of Cardiology, University of Washington School of Medicine, 1959 NE Pacific S, Box 356005, Seattle, WA 98195. Email:

This manuscript was sent to Mahasin S. Mujahid, PhD, MS, Associate Editor, for review by expert referees, editorial decision, and final disposition.

Supplemental Material is available at

For Sources of Funding and Disclosures, see page 9.



eLetters should relate to an article recently published in the journal and are not a forum for providing unpublished data. Comments are reviewed for appropriate use of tone and language. Comments are not peer-reviewed. Acceptable comments are posted to the journal website only. Comments are not published in an issue and are not indexed in PubMed. Comments should be no longer than 500 words and will only be posted online. References are limited to 10. Authors of the article cited in the comment will be invited to reply, as appropriate.

Comments and feedback on AHA/ASA Scientific Statements and Guidelines should be directed to the AHA/ASA Manuscript Oversight Committee via its Correspondence page.