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. Author manuscript; available in PMC: 2026 Jul 27.
Published in final edited form as: Ethn Health. 2025 Apr 1;30(4):532–552. doi: 10.1080/13557858.2025.2484581

The association of discrimination, inflammation, and coping style on self-rated health among South Asian individuals in the MASALA Study

Raji Pillai a, Sahiti Myneni b, Constance M Johnson a, Nilay S Shah c, Alka M Kanaya d, Jennifer E S Beauchamp a
PMCID: PMC13401951  NIHMSID: NIHMS2194213  PMID: 40169421

Abstract

Objectives:

South Asian individuals (SAs) may have heightened levels of inflammatory markers, such as C reactive protein (CRP), Tumor Necrosis Factor-α (TNF-α), leptin, and resistin, and decreased levels of anti-inflammatory adiponectin, contributing to higher cardiovascular disease (CVD) incidence. Social determinants of health, like discrimination, are also associated with risks for CVD in SAs. This study examined the associations between discrimination and inflammation and whether coping styles moderated the association between discrimination and self-rated health (SRH) among SAs in the United States.

Design:

Secondary analysis of data obtained from 1164 SAs (mean age = 57 years, SD = 9.4, 48% women) enrolled in the Mediators of Atherosclerosis in South Asians Living in America (MASALA) study was conducted. Discrimination was measured using the Everyday Discrimination Scale (EDS). Inflammatory markers (CRP, TNF-α, leptin, resistin) and anti-inflammatory adiponectin were measured from blood samples. SRH was self-reported by participants. Coping styles were defined as problem-focused or emotion-focused. Multiple regression with bootstrapping was used to examine associations between discrimination and inflammatory markers and adiponectin. Moderation analysis assessed whether coping styles moderated the association between discrimination and SRH.

Results:

No significant associations were found between discrimination and inflammation. Discrimination was inversely associated with SRH (OR = 0.969, p = 0.005). Emotion-focused coping moderated the association between discrimination and SRH (OR = 0.969, 95% CI = 0.940-0.999, p = 0.044). Among participants who used emotion-focused coping strategies, an increase in self-reported discriminatory experiences was associated with lower odds of having good or excellent SRH. Problem-focused coping did not moderate the association between discrimination and SRH.

Conclusion:

The unknown magnitude and duration, and the lack of variability in discrimination among participants could explain the null findings between discrimination and inflammation. Gaining a better understanding of the ways in which SAs appraise and cope with discriminatory experiences may help to develop future interventions targeted to reduce the adverse health consequences of discrimination among SAs.

Keywords: South Asian, discrimination, inflammatory markers, self-rated health, coping style, MASALA

SUSTAINABLE DEVELOPMENT GOALS: Good health and well-being, Reduced inequalities, Sustainable cities and communities

Introduction

South Asian individuals (SAs) (individuals from India, Pakistan, Bangladesh, Sri Lanka, Nepal, Bhutan, and the Maldives) account for nearly 60% of the global cardiovascular disease (CVD) burden (Martinez-Amezcua et al. 2020). CVD is the leading cause of death among SAs in the United States (U.S.), even when compared to all forms of cancer and chronic lower respiratory disease combined (Fernandez Perez et al. 2022; Volgman et al. 2018). The risk of incident CVD in SAs is more than two-fold when compared with age and sex-adjusted European populations (Patel et al. 2021). SAs in developed countries, including the U.S., are found to have significantly higher odds of CVD-related mortality compared to White individuals (Patel, Abatcha, and Uthman 2022). A study of 10.5 million U.S. death records between 2003 and 2010 found a higher proportional mortality rate from ischemic heart disease in Asian Indian individuals (1.12 for women, 1.43 for men) when compared to White individuals (0.92 for women, 1.08 for men) (Jose et al. 2014).

Inflammation and cardiovascular disease

Epidemiological and clinical studies have shown strong and consistent relationships between inflammation and CVD (Henein et al. 2022; Willerson and Ridker 2004). Inflammation triggers the production of proinflammatory cytokines (e.g. tumor necrosis factor-α [TNF-α]), which has been shown to cause endothelial dysfunction and CVD (Henein et al. 2022). Moreover, systemic inflammation, as evidenced by increased levels of inflammatory biomarkers (e.g. C reactive protein [CRP], leptin, and resistin), plays a significant role in the progression of atherosclerosis and the development of CVD (Willerson and Ridker 2004).

While the prevalence of certain risk factors (e.g. insulin resistance and dyslipidemia) have been cited as major contributors to the early development of CVD in SAs, SAs have also been found to have high levels of inflammatory biomarkers such as CRP and TNF-α, further contributing to CVD (Palaniappan et al. 2018; Volgman et al. 2018). Contrarily, anti-inflammatory adipokines (e.g. adiponectin) protect against inflammation and plaque formation, and levels of anti-inflammatory adipokines have been found to be lower in SAs when compared to White individuals (Anand et al. 2011). While studies have linked elevated inflammatory biomarker levels and decreased anti-inflammatory biomarker levels to CVD risk factors (e.g. excess adipose tissue and insulin resistance) (Anand et al. 2011), the mechanisms by which these biomarkers are elevated in SAs have not been fully explained by these factors alone.

Discrimination and cardiovascular disease

Social determinants of health (SDOH) are the conditions in which people are born, work, live, and age, influencing health outcomes (World Health Organization n.d.). Discrimination is considered to be an SDOH and is the differential treatment of individuals by social institutions and/or other individuals (Williams et al. 2019). Systemic discrimination involves excluding people from social institutions and systems, such as political and criminal justice systems (Braveman et al. 2022). Institutional discrimination is the involvement of institutional systems and structures in race-based discrimination and oppression (e.g. hospitals) (Braveman et al. 2022). Interpersonal discrimination is a mechanism of social exclusion between people, including manifestations from racially motivated assault to verbal abuse, ostracism, and exclusion (Goosby, Cheadle, and Mitchell 2018).

Major and everyday discrimination are the two types of perceived discrimination. Exposure to major discrimination is typically assessed by asking individuals the number of times they have experienced an acute discriminatory event, such as being denied a bank loan or prevented from buying a home (Cuevas et al. 2020; Williams et al. 1997). The timeframe for experiencing major discrimination is longer than everyday discrimination and includes major events that might have happened years ago (Ayalon and Gum 2011). Everyday discrimination, often referred to as chronic discrimination, is characterized as being treated unfairly on a day-to-day basis in different social contexts (Williams et al. 1997). Everyday discrimination encompasses more recent events (e.g. within the last 12 months), and the frequency of such events is expected to be higher than events of major discrimination (Ayalon and Gum 2011).

The American Heart Association (AHA) recently recognized SDOH, such as discrimination, as foundational factors associated with CVD (Lloyd-Jones et al. 2022). Experiences of discrimination have been shown to be associated with CVD risk factors (e.g. unhealthy diet, poorer sleep quality) in SAs residing in the U.S. (Nadimpalli et al. 2016; Park et al. 2022). However, SAs are often inappropriately considered model minorities, a highly successful ethnic minority group that has overcome adversity and discrimination (Shih, Chang, and Chen 2019). Research suggests that SAs are often excluded from studies of discrimination and health due to the model minority myth (Nadimpalli et al. 2016). A potential pathway by which discrimination is linked to CVD is chronic inflammation, a key contributor to conditions such as CVD (Chen et al. 2022).

Discrimination and inflammation

Exposure to discrimination has been found to affect health through negative emotional states or stressors that activate dysregulation of neuroendocrine and immune systems, and result in acute and chronic pro-inflammatory activity (Chen et al. 2022; Cuevas et al. 2020). For example, chronic or everyday exposure to discrimination has been linked with increased levels of inflammatory biomarkers among Black individuals (Cuevas et al. 2020). Specifically, the association between chronic discrimination and increased levels of CRP has been reported in African-American adults 65 years and older (Lewis et al. 2010). Discrimination has also been shown to be associated with higher concentrations of inflammatory biomarkers in adolescent males of African-American descent (Chen et al. 2022) and higher ratios of pro- to anti-inflammatory cytokines in Latina women (Caceres et al. 2021). Whether exposure to discrimination is associated with increased inflammatory biomarkers and decreased anti-inflammatory adipokines in SAs is unknown.

Discrimination and self-rated health

Studies of discrimination and health among diverse ethnic minority groups (e.g. African American, Latino, Asian American, and Asian Indian populations) have shown that discrimination is associated with poorer self-rated health (SRH) (McMurtry et al. 2019; Nadimpalli et al. 2016; Paradies 2006). SRH is a subjective measure of an individual’s health status and has been shown to be a significant predictor of CVD (Latham and Peek 2012; van der Linde et al. 2013). SRH was found to be a predictor of fatal and non-fatal CVD events over an 11-year time frame among a previously healthy, middle-aged European population after adjusting for socio-demographic, behavioral, and clinical CVD risk factors (van der Linde et al. 2013). SRH has also been shown to be a significant predictor of the development of chronic diseases, including coronary heart disease, among late midlife adults living in the U.S. (Latham and Peek 2012).

Discrimination and coping style

The health consequences of perceived discrimination may vary according to an individual’s coping style (Pascoe and Smart Richman 2009). Coping style is the characteristic manner in which an individual deals with external and/or internal demands or stress and can be beneficial or detrimental to an individual’s health (Algorani and Gupta 2023). Coping styles in response to discrimination can be broadly classified as problem-focused and emotion-focused (Forster et al. 2022; Krieger and Sidney 1996). Problem-focused coping involves strategies (e.g. support seeking, cognitive reframing, experimentation, planning, and problem-solving) to modify the stressful situation to accommodate the person’s desires and motives (Forster et al. 2022; Zimmer-Gembeck and Skinner 2011). Emotion-focused coping involves strategies (e.g. removing oneself from a situation, minimizing a situation, keeping feelings to oneself, seeking alternative rewards, and engaging in behavioral distractions) to reduce the psychological distress associated with a problem and can be adaptive or maladaptive (Des Marais 2022; Forster et al. 2022; Zimmer-Gembeck and Skinner 2011). Maladaptive emotion-focused coping strategies are characterized by behavioral disengagements like denying the situation, suppressing the emotions, or engaging in substance use and are linked to negative outcomes (Des Marais 2022). Adaptive emotion-focused approaches involve exploring and understanding one’s feelings about the situation. Some of the effective emotion-focused coping strategies are journaling, mindfulness meditation, forgiveness, accepting the situation, and openly expressing emotions (Des Marais 2022).

Discrimination-related problem-focused coping has been associated with lower blood pressure and better mental health when compared to emotion-focused coping to discrimination (Forster et al. 2022; Krieger and Sidney 1996). Among SAs in the U.S., discrimination-related problem-focused coping has been associated with improved mental health (Nadimpalli et al. 2016). Few studies have looked at the moderating effect of coping style on perceived discrimination and health and reported mixed results regarding the optimal coping style for improved health (Noh et al. 1999; Noh and Kaspar 2003). No known study has linked experiences of discrimination, coping styles, and SRH among SAs living in the U.S.

Covariates

The covariates included in the analysis were selected based on a literature review. Socio-demographic factors shown to be related to discrimination and inflammation (e.g. age, sex, education, and income) were included in the analysis (Yip, Gee, and Takeuchi 2008). Since prior studies have shown ethnic identity as a source of discrimination for immigrant SAs (Nadimpalli et al. 2016; Yip, Gee, and Takeuchi 2008), cultural beliefs were also included as a covariate. Furthermore, research has shown the beneficial role of social support in coping with discrimination among SAs (Tummala-Narra, Alegria, and Chen 2012) and associations between discrimination, mental health, and anger among SAs; therefore, social support, depression (Tummala-Narra, Alegria, and Chen 2012), anxiety and anger (Nadimpalli et al. 2016) were included as covariates. Lastly, body mass index (BMI; Artemniak-Wojtowicz, Kucharska, and Pyrżak 2020), diet, and physical activity (Cuevas et al. 2020) were included as covariates based on studies reporting associations between these variables and inflammation.

Conceptual framework

This study was guided by an existing conceptual framework linking discrimination exposure to health (Cuevas et al. 2020). The framework was adapted to propose inter-actions between discrimination, coping style, physiological systems, inflammation, and overall health of the individual (Figure 1). Exposure to discrimination can trigger three regulatory physiological systems, neuroendocrine, cardiovascular, and immune function (Ong, Deshpande, and Williams 2017), which are interrelated and play a critical role in maintaining homeostasis (McEwen 2008). These physiological responses, however, are dependent on the person’s coping styles to discriminatory situations (Cuevas et al. 2020). Unlike the problem-focused coping style, the maladaptive emotion-focused coping style may evoke changes in these physiological systems that initiate the expression of pro-inflammatory cytokines and anti-inflammatory adipokines (Liu, Wang, and Jiang 2017) and lead to increased risk of poor SRH and chronic conditions like CVD later in life (Ong, Deshpande, and Williams 2017).

Figure 1.

Figure 1.

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A conceptual framework based on the relationship between discrimination exposure and health. Adapted from Cuevas et al. 2020.

Objectives

The objectives of this study were to examine (1) the associations of discrimination with inflammatory biomarkers and anti-inflammatory adipokines and (2) the moderating effect of coping styles on the relationship between discrimination and SRH among SAs in the U.S. It was hypothesized that self-reported discrimination would be associated with higher pro-inflammatory biomarkers and lower anti-inflammatory adipokines, and coping style would moderate the link between discrimination and SRH among SAs.

Methods

Study design

This study was a secondary data analysis of data available from the Mediators of Atherosclerosis in South Asians Living in America (MASALA) Study (Kanaya et al. 2013). MASALA is an ongoing, prospective cohort study, investigating the prevalence, correlates, and outcomes associated with CVD in a population-based sample of SAs from San Francisco Bay and greater Chicago areas (Kanaya et al. 2013). The study began in October 2010, and final participant enrollment for baseline exam 1 concluded in March 2013. A new wave of participants (Exam 1A) was recruited from March 2017 to March 2018 (Kanaya et al. 2019).

Participants

Data from the MASALA participants (Baseline Exam 1 and Exam 1A) who completed all variables of interest (e.g. discrimination and coping with discrimination questionnaire, socio-demographic information, blood tests, and self-reported health question) were included (n = 1164). The participants self-identified as South Asian, were between ages 40 and 84 years, were able to speak and/or read English, Hindi, or Urdu, and were recruited from two clinical sites (Kanaya et al. 2013). Baseline Exam 1 participants were recruited through a surname-based sampling method (Kanaya et al. 2013), and Exam 1A participants through community-based, participant referrals, and electronic health record-based recruitment (Kanaya et al. 2019). Detailed information on the MASALA study has been provided elsewhere (Kanaya et al. 2013; Kanaya et al. 2019). All participants were free of clinically evident CVD, defined as no history of heart attack, stroke or transient ischemic attack, heart failure, angina, use of nitroglycerin, CVD procedures, or any surgery on the heart or arteries, or current atrial fibrillation at baseline (Kanaya et al. 2013).

Participants with missing values on discrimination and coping with discrimination questionnaire, socio-demographic information, inflammatory markers, self-reported health questions, and any covariates were excluded from the current analyses. Inflammatory markers were not measured in Exam 1A participants (n = 258) and were thus excluded from Aim 1 analyses. The MASALA study protocol and procedures were approved by the University of California, San Francisco (UCSF) and Northwestern University (NWU) Institutional Review Boards. All study participants signed informed consent (Kanaya et al. 2019). The UTHealth Houston Institutional Review Board approved the secondary data analysis.

Measurements

Independent variable

Discrimination:

Discrimination was measured using the Everyday Discrimination Scale (EDS) (Williams et al. 1997). The EDS is a self-report instrument with nine items on a 6-point Likert-type scale, with choices ranging from ‘almost every day’ to ‘never.’ The nine items were summed to capture the frequency of the following experiences in the day-to-day lives of participants: being treated with less courtesy than others; less respect than others; receiving poorer service than others in restaurants or stores; people acting as if you are not smart; they are better than you; they are afraid of you; they think you are dishonest; being called names or insulted, and being threatened or harassed (Williams et al. 1997). The EDS was developed to assess routine, chronic, non-race-based, and relatively minor experiences of unfair treatment (Williams et al. 1997). The score ranges from 9 to 54 and higher scores on the EDS correspond to a greater frequency of everyday discrimination. The EDS is a widely used scale and has been validated in Asian American adults (Park et al. 2022). A Cronbach’s alpha of 0.88 was produced for this scale among the current sample.

Dependent variables

Inflammatory biomarkers:

In the MASALA study, blood samples were taken from a peripheral vein after a 12-hour fast to measure inflammatory biomarkers (Kanaya et al. 2013). The inflammatory biomarkers analyzed in the MASALA study included CRP, TNF-α, leptin, resistin, and adiponectin and were assessed as continuous variables. CRP levels were measured using the BNII nephelometer (N High Sensitivity CRP; Siemens Healthcare Diagnostics, Deerfield, IL); the intra-assay coefficient of variation was 3.5% (Mehta et al. 2018). TNF-α and leptin levels were measured using the Millipore Adipokine panel B (EMD Millipore, Billerica, MA), and the intra-assay coefficient of variation was 18.6% for TNF-α and 6.0% for leptin (Mehta et al. 2018). Adiponectin and resistin were measured using Millipore Luminex adipokine panel A (EMD Millipore, Billerica, MA). The inter-assay coefficient of variation was 2.3-4.1% for adiponectin and 3.3-5.5% for resistin (Mehta et al. 2018).

Self-rated Health:

In the MASALA study, SRH was measured by asking participants to rate their health on a continuous scale of 1–10, with 1 being poor and 10 being excellent (Kandula et al. 2018). SRH showed moderate to substantial test-retest reliability (Cohen’s kappa 0.62) and good predictive validity regarding all-cause mortality among Chinese middle-aged and older adults (Pan et al. 2022). SRH was assessed via a binary variable (1 = score of 1–6 indicating poor/fair SRH and 2 = score of 7–10 indicating good/excellent SRH).

Moderator

Coping style:

Coping styles to discrimination were assessed by asking participants whether they used problem-focused or emotion-focused coping styles to discrimination experienced in the MASALA study. The problem-focused/emotion-focused coping question (response to unfair treatment) is a part of the Experiences of Discrimination (EOD) scale (Krieger and Sidney 1996). The first two questions in this self-reported questionnaire concerned typical responses to unfair treatment; choices were (1) ‘accept it as a fact of life’ (emotion-focused coping) vs. ‘try to do something about it’ (problem-focused coping) and (2) ‘talk to other people about it’ (problem-focused coping) vs. ‘keep it to yourself’ (emotion-focused coping) (Krieger and Sidney 1996). The validity and reliability (Cronbach’s alpha 0.74 or greater) of EOD have been established in African-American and Latino-American participants (Krieger et al. 2005). The coping style was assessed via a binary variable.

Covariates

Socio-demographic variables:

Participants’ self-reported age in years was coded as a continuous variable. Participants’ sex (male vs. female), study site (NWU vs. UCSF), level of education (bachelor’s degree or higher vs. less than a bachelor’s degree), and family income (> = $75,000/year vs. <$75,000/year) were included as binary measures. English fluency (1 = speaks English poorly, 2 = fairly well, 3 = very well) and tobacco use (0 = never, 1 = former, 2 = current) were divided into three categories. Marital status (0 = married or living with a partner, 1 = separated/divorced, 2 = widowed, 3 = single, 4 = refused) and the number of years lived in the U.S. (1 = 0-10 yrs, 2 = > 10-20 yrs, 3 = > 20-30 yrs, 4 = > 30-40 yrs, 5 = > 40 yrs) both included five categories.

Traditional cultural beliefs:

The traditional cultural beliefs were measured using the traditional cultural beliefs scale, a continuous measure asking participants how much they wished SA cultural traditions would be practiced in the U.S. (Kanaya et al. 2014). The scale includes seven items: performing religious ceremonies; serving sweets at ceremonies; fasting on specific occasions; living in a joint family; having an arranged marriage; eating a staple diet of chapattis, rice, daal, vegetables, and yogurt; using spices for health and healing (Kanaya et al. 2014). The items were scored on a Likert scale with scores ranging from 0 to 28, with lower scores reflecting higher traditional cultural beliefs and higher scores reflecting lower cultural beliefs (Kanaya et al. 2014). The Cronbach’s alpha for this scale in the baseline MASALA cohort was 0.83 (Kanaya et al. 2014).

Social support:

Social support was measured using a six-item continuous low social support to high social support scale from the Enhancing Recovery in Coronary Heart Disease Patients Social Support Instrument (ESSI). The scores ranged from 0 to 24, including questions such as ‘Is there someone available to give you advice about a problem?’ (Mitchell et al. 2003). There were five response options ranging from experiencing items on the social support questionnaire none of the time to all of the time. This scale had a Cronbach’s alpha of 0.88 in studies involving AIs in the U.S. (Nadimpalli et al. 2016; Nadimpalli et al. 2016).

Depression:

The Center for Epidemiologic Studies Depression Scale (CES-D Scale) was used to measure depression. CES-D Scale is a 20-item continuous scale (0-60) measuring depressive symptoms such as sadness, feeling lonely, and crying spells (Radloff 1977). Participants were provided with four response options ranging from experiencing such symptoms rarely or none of the time to most of the time. The CES-D Scale had a Cronbach’s alpha of 0.65 for AIs in the U.S. (Nadimpalli et al. 2016; Nadimpalli et al. 2016).

Anxiety:

The Spielberger Trait Anxiety Scale evaluates feelings of anxiety based on prompts such as ‘I feel nervous and restless’ (Spielberger 1980). There are ten items and four response options for the anxiety scale, ranging from almost never to almost always. The score ranges from 10 to 40, and higher scores correspond to a higher anxiety level. The Cronbach’s alpha for this scale was 0.81 for AIs (Nadimpalli et al. 2016).

Anger:

The Spielberger Trait Anger Scale (10 items; 10–40-point range) evaluates feelings of anger through questions related to temper, being ‘hot-headed,’ or ‘flying off the handle’ (Spielberger 1980). There were four response options for the anger scale ranging from almost never to almost always, and higher scores corresponded to higher levels of anger. The Cronbach’s alpha for this scale was 0.81 for AIs (Nadimpalli et al. 2016).

BMI:

BMI was calculated from weight and height measured during a physical exam (Kanaya et al. 2013). Based on Asian cut-offs recommended by World Health Organization expert consultation, BMI was classified as normal (1 = < 23.0 kg/m2), overweight (2 = 23.0 to <27.5 kg/m2), or obese (3 = ≥ 27.5 kg/m2).

Diet:

Diet quality was measured using the Alternative Healthy Eating Index (AHEI), which includes 11 food components with scores ranging from 0 to 10 for each component, as a measure of diet quality. AHEI scores were measured on a continuous scale from 0 to 110, with higher scores indicating a higher diet quality (Chiuve et al. 2012).

Physical activity:

Physical activity was assessed using the Typical Week’s Physical Activity Questionnaire designed to identify the time and frequency spent on various physical activities during a typical week in the past month (Ainsworth et al. 1999).

Statistical analyses

Bivariate associations between predictor variables, moderator variables, and covariates were examined, and descriptive statistics were calculated for all study variables. Two-sided tests were used, and p-values and 95% Confidence Intervals (CIs) were presented to address statistical significance.

Aim 1:

The first aim of the study was to examine the associations between discrimination and inflammation among SAs in the U.S. The dependent variables were evaluated for normality and were not normally distributed. Bootstrapping was done to account for this deviation from normality. Multivariable linear regression with bootstrapping was used to examine the association between discrimination and inflammatory markers after adjusting for covariates. The inflammatory markers (CRP, TNF-α, leptin, and resistin) and anti-inflammatory adipokine (adiponectin) were tested as outcome variables in five separate regression models. In each of the five models, covariates were selected based on the available literature and univariable analyses. The covariates initially included in all models were socio-demographic variables (age, sex, study site, marital status, level of education, family income, English fluency, years in the US, tobacco use), traditional cultural beliefs, social support, depression, anxiety, anger, BMI, diet, and physical activity. Covariates significantly associated with each outcome variable (p < 0.10) were then included in the respective regression analyses. After excluding 273 participants with missing data, a final sample size of 891 SAs was included in the statistical analyses.

Aim 2:

The second aim of the study was to examine whether the association between discrimination and SRH among SAs is moderated by coping style. First, the association between discrimination and SRH was evaluated using logistic regression. Moderation analyses were then used to evaluate the relationship between discrimination and SRH and moderating factors (coping style). Levels of education, anxiety, and physical activity were included as covariates based on available literature and univariable analysis. SRH was operationalized as a dichotomized variable. After excluding seven individuals with missing data, 1157 participants were included in the final analyses. Two separate regression models were used for the two questions assessing the coping style. Interaction terms were created by multiplying each potential moderator (problem-focused/emotion-focused coping) by the predictor variable, discrimination. The interaction terms were then analyzed separately with logistic regression adjusting for all potential covariates. Data were analyzed using SPSS Statistics for Windows, Version 29.0 (IBM 2023).

Results

Participant characteristics

Participants were, on average, 56.7 years of age (range: 39–83 years, SD 9.4), 47.8% females, and had high levels of education (86.4% with bachelor’s degree or higher) and income (68.7% with a family income of > = $75,000/year). Majority of the participants (67.5%) had lived in the U.S. for more than 20 years and were overweight (46.3%) or obese (31.1%). The average level of discrimination reported by the participants was M = 14.8 (SD = 6.2) on a scale of 9–54 and 82.5% reported good or excellent health on the SRH scale. See Table 1 for a detailed description of participant characteristics.

Table 1.

MASALA Study Participant Characteristics, 2010–2013 and 2017–2018.

Total N = 1164 N (%) or Mean (SD)
Age (years) 56.7 (9.4)
Female, % 47.8
Study Site %
 NWU 47.3
 UCSF 52.7
Marital Status %
 Married / Partner 90.7
 Separated / Divorced 3.3
 Widowed 4.6
 Single 1.5
 Education ≥ Bachelor’s Degree % 86.4
 Income ≥ $ 75 K, % (n = 1126) 68.7
English fluency %
 Poor 5.6
 Fair 9.7
 Well/ Very well 84.7
Years in the U.S, % (n = 1142)
 0–10 yrs 7.2
 > 10–20 yrs 23.4
 > 20–30 yrs 26.5
 > 30–40 yrs 26.7
 >40 yrs 14.3
Tobacco use %
 Never 83.3
 Former 13.5
 Current 3.2
 Traditional cultural beliefs (0-28) (n = 1162) 13.6 (6.4)
 Social support (0– 24) 19 (5)
 Depression (0-60) 7.6 (7)
 Anxiety (10– 40) 16 (4.4)
 Anger (10-40) 16 (3.9)
BMI (Asian) kg/m2%
 Normal 22.6
 Overweight 46.3
 Obese 31.1
 Diet (AHEI score) (0-110) (n = 892) 70.1 (6.8)
 Physical activity (METmin/week) 9935 (4094)
 Discrimination (9-54) 14.8 (6.2)
 Self-rated health (Good / Excellent) % 82.5
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Inflammatory markers

Leptin (M = 15933.6 PG/ML) and adiponectin (M = 11803.6 NG/DL) were moderately skewed, with skewness of 2.1 and 1.3, respectively. CRP (M = 2.5 UG/ML), TNF-α (M = 4.1 PG/ML), and Resistin (M = 21785.4 PG/DL) showed substantial non-normality, and their skewness was calculated as 10.3, 23, and 7.6, respectively.

Main analyses

Aim 1:

The results from the first regression analysis (Model 1) show that discrimination was not associated with CRP F (1, 883) = 0.063, p = 0.802. In the second regression analysis (Model 2), discrimination was not associated with TNF-alpha F (1, 889) = 0.311, p = 0.577. Subsequent analyses in Models 3, 4, and 5 with leptin F (1, 885) = 1.829, p = 0.177, resistin F (1, 888) = 0.332, p = 0.565 and adiponectin F (1, 842) = 0.068, p = 0.794 also did not show any associations with discrimination. Table 2 presents the F values and relevant coefficients for the discrimination and inflammation analyses.

Table 2.

Regression analyses for relationships between discrimination and inflammation, MASALA Study.

Outcome
Variable Model 1: CRP
 Model 2: TNF α
 Model 3: Leptin
 Model 4: Resistin
 Model 5: Adiponectin
df MS F df MS F df MS F df MS F df MS F
Age 1 32.52 1.65 1 1054016283.5 7.63* 1 2686662253.9 81.89**
Sex 1 32161738373 340.07** 1 6148704035.3 187.42**
Study site 1 576503267.46 17.57**
Marital status 3 391.34 19.88**
Family income 1 100195660.57 3.05
Tobacco use 2 99.16 5.04*
BMI 2 525.00 26.67** 2 14492803214 153.24** 2 507755958.33 15.48**
Depression sdd sdd sdd 1 225157190.84 2.38 sdd sdd
Diet 1 143289970.17 4.37*
Discrimination 1 1.24 0.06 1 139.49 0.31 1 172941424.92 1.83 1 45899600.83 0.33 1 2241098.73 0.07
Error 883 19.69 889 448.14 885 94574484.38 888 138196300.24 842 32806964.69
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**

p < 0.001.

*

p < 0.05.

Note. N = 891. BMI = Body mass index; CRP = C-reactive protein; TNF α = Tumor necrosis factor-alpha.

Aim 2:

Regression analysis showed a negative relationship between discrimination and SRH among SAs in the present study. An increase in the discrimination score was associated with a decreased probability of a high SRH score >6 [Exp(B) = 0.969, (SE = 0.011), p = 0.005]. Subsequent moderation analyses showed that emotion-focused coping style moderated the association between discrimination and SRH (Odds Ratio [OR] = 0.969, 95% Confidence Interval [CI] = 0.940-0.999, p = 0.044) after adjusting for covariates (see Table 3). The OR for discrimination (0.969) indicates that among participants who coped emotionally by keeping the discriminatory experience to themselves, a one-unit higher discrimination score was associated with 3% lower odds of a high SRH score >6, indicating better health (p = 0.044). However, when participants chose problem-focused coping by talking to others about the discriminatory experience, there was no evidence of an association between discrimination and SRH (OR = 1.045, 95% CI = 0.997-1.094, p = 0.066). Regression analyses showed that the coping styles that utilized accepting the discriminatory experiences (emotion-focused) or trying to do something about it (problem-focused) did not moderate the relationship between discrimination and SRH (OR = 0.987, 95% CI = 0.954-1.021, p = 0.433 for emotion-focused coping, OR = 1.003, 95% CI = 0.969-1.038, p = 0.867 for problem-focused coping) (see Table 4).

Table 3.

Moderation analyses for relationships between discrimination and self-rated health – 15B.

Variable Outcome
Model 1
Problem-focused coping
 ssd Model 2
Emotion-focused coping
B S.E. P OR B S.E. P OR
Discrimination 0.044 0.024 0.066 1.045 ssd −0.031 0.016 0.044 0.969
Level of education 0.331 0.215 0.124 1.392 0.331 0.215 0.124 1.392
Anxiety −0.113 0.019 <0.001 0.893 −0.113 0.019 <0.001 0.893
Physical activity 0.000 0.000 0.007 1.000 0.000 0.000 0.007 1.000
Coping style 1.403 0.445 0.002 4.067 −1.403 0.445 0.002 0.246
Discrimination × Coping style −0.075 0.027 0.006 0.928 0.075 0.027 0.006 1.078
Open in a new tab

Note. N = 1157. Problem-focused coping = Talk to other people about it; Emotion-focused coping = Keep it to yourself.

Table 4.

Moderation analyses for relationships between discrimination and self-rated health – 15A.

Outcome
Model 1
Problem-focused coping		 Model 2
Emotion-focused coping
Variable B S.E. P OR ssd B S.E. P OR
Discrimination 0.003 0.018 0.867 1.003 −0.014 0.017 0.433 0.987
Level of education 0.385 0.214 0.073 1.469 0.385 0.214 0.073 1.469
Anxiety −0.114 0.019 <0.001 0.892 −0.114 0.019 <0.001 0.892
Physical activity 0.000 0.000 0.008 1.000 0.000 0.000 0.008 1.000
Coping style 0.327 0.408 0.422 1.387 −0.327 0.408 0.422 0.721
Discrimination × Coping style −0.017 0.024 0.489 0.984 0.017 0.024 0.489 1.017
Open in a new tab

Note. N = 1158. Problem-focused coping = Try to do something about it; Emotion-focused coping = Accept it as a fact of life.

Discussion

This study examined whether experiences of discrimination were associated with inflammation and whether coping styles in response to the experiences of discrimination moderated the relationship between discrimination and SRH among SAs in the U.S. An association between discrimination and inflammation among MASALA participants was not found. However, the inverse association between discrimination and SRH was moderated by the coping styles to discrimination. Among SAs who adopted emotion-focused coping, a higher frequency of discrimination was associated with decreased SRH. Problem-focused coping did not moderate the association between discrimination and SRH.

One possible explanation for the null findings between discrimination and inflammation may be the failure to capture the magnitude (major experiences) and the duration of discrimination among participants. The EDS scale measured the frequency of relatively less severe (minor experiences) discrimination in everyday life. The overall impact of stressors like discrimination on the physiological systems may depend on the magnitude, duration, and frequency of the stressor (Ayalon and Gum 2011; Cuevas et al. 2019). A combination of one or more of these factors of discrimination at a certain level may be required to trigger a physiologic response causing the expression of pro- and anti-inflammatory markers in individuals who experience discrimination. In a study that examined the associations between major lifetime and everyday discrimination and inflammation among Puerto Rican adults, Cuevas et al. (2019) found that inflammation was related to the magnitude and duration of the discriminatory events. The results showed that greater major lifetime discrimination was associated with higher odds of having a higher CRP level, whereas greater everyday discrimination was associated with lower odds of having a higher CRP level among the participants.

The MASALA study measured CRP, TNF-α, leptin, and resistin, which are found to be generated by stressors like discrimination. However, there are many other inflammatory markers produced by underlying systemic inflammation that have been linked to discrimination. For example, interleukin-6 (IL-6) is one of the most assessed inflammatory markers in discrimination studies (Cuevas et al. 2020). Studies among White and Black populations have shown a positive association between IL-6 and discrimination, contributing to an increased risk of atherosclerotic disease (Stepanikova, Bateman, and Oates 2017). No known studies among SAs are available in the existing literature and, if conducted, may yield a more comprehensive understanding of the role of discrimination contributing to inflammation.

Additionally, lower scores on the discrimination scale among participants may have lacked the variability required to identify associations between discrimination and inflammation. However, the results of this study are consistent with previous work by Zahodne et al. (2019), where no association was found between discrimination and CRP levels in a four-year study of 12,382 Black, White, and Hispanic participants. No similar studies exploring the association between discrimination and inflammation among SAs were found in the available literature.

One of the reasons for low discrimination levels among the participants in the current study may be the high social support they reported. Previous research has suggested that social support may act as a buffer against discrimination against Asian Americans (Mossakowski and Zhang 2014; Noh and Kaspar 2003). Social support from friends, family, and the community was shown to help manage discrimination-related stress and provide support in coping with discrimination among SAs (Nadimpalli et al. 2016; Tummala-Narra, Alegria, and Chen 2012).

Consistent with previous studies in Asian Indian adults, discrimination was negatively associated with SRH in SAs in the present study (Nadimpalli et al. 2016). Current study results demonstrated that higher discrimination scores were related to decreased SRH among the participants. Frequent exposure to discrimination can activate both physiological and psychological stress responses and negative emotional states (Pascoe and Smart Richman 2009). It can also lead to health risk behaviors like smoking and alcohol use, contributing to poor SRH (Pascoe and Smart Richman 2009). Existing literature highlights the significant negative effects of discrimination on SRH (Nadimpalli et al. 2016; Pascoe and Smart Richman 2009). Poor SRH has also been found to be significantly associated with CVD-related mortality and morbidity across varied populations from the U.S. and Europe (Latham and Peek 2012; van der Linde et al. 2013). This finding has major implications for the CVD research among SAs because of the increased prevalence of CVD in this population (Volgman et al. 2018). For example, assessment of SRH in primary care settings may be a simple and helpful strategy for CVD risk assessment among SAs. Risk models currently being used to assess the CVD risk (e.g. Framingham Risk Score) do not incorporate SRH, a significant clinical care gap. Similarly, whether SRH can be used as an outcome measure for assessing CVH promotion interventions is uncertain (van der Linde et al. 2013). Further research is needed to identify whether the measurement of SRH as an additional CVD risk factor can be implemented and whether SRH can be modified to improve CVD outcomes in SAs.

Coping styles to experiences of discrimination moderated the association between discrimination and SRH. Among SAs who coped emotionally by keeping the discriminatory experience to themselves, a greater frequency of discrimination was associated with decreased SRH. Maladaptive emotion-focused coping strategies like behavioral disengagement are found to be associated with negative health outcomes. (Forster et al. 2022; Zimmer-Gembeck and Skinner 2011) These findings are consistent with previous studies (Krieger and Sidney 1996; Noh and Kaspar 2003) where emotion-focused coping to experiences of discrimination was associated with elevated blood pressure among Black individuals and debilitating mental health effects in Korean adults. Conversely, Noh et al. (1999) found that emotion-focused coping against experiences of discrimination diminished the strength of the link between discrimination and depression among Southeast Asians.

No association was found between discrimination and SRH when the participants used problem-focused coping by talking about the discriminatory experience. Noh et al. (1999) reported a similar finding where problem-focused coping had no effect on the relationship between discrimination and depression among Southeast Asians in Canada. The authors attributed the findings to the subtle nature of the discriminatory experience and that a problem-focused approach to such situations may be ineffective.

The coping styles that utilized emotion-focused coping by accepting the discriminatory experience vs. problem-focused coping by doing something about it did not moderate the association between discrimination and SRH. Coping is a dynamic variable, and people may use different coping styles during various periods. Research suggests that the coping styles people tend to use depend on the type of discriminatory experience and the extent of control they have over the situation (Forster et al. 2022).

The effective ways of coping with discrimination may vary by ethnicity, culture, and gender (Pascoe and Smart Richman 2009). Only a few studies have examined the moderating effect of coping styles on discrimination and health and obtained mixed results regarding the best coping style for better SRH. There is a gap in the literature in this area, especially among SAs, and future research should examine how certain coping styles to discrimination can be more effective than others in reducing the negative health consequences of discrimination among various ethnic and racial populations.

Strengths

The current study analyzed data from a well-conducted prospective cohort study (Kanaya et al. 2013; Kanaya et al. 2019). This study looked at the aggregate data from two waves of recruitment (baseline exam 1 and Exam 1A). The inclusion of the most recent (Exam 1A) data increased the generalizability of the results because the socio-demographic characteristics of the recent participants were different from those enrolled in the initial baseline exam 1. Participants in the recent recruitment were older, had lived in the U.S. for more years, were more likely to be non-Indian SA immigrants, and had lower educational attainment than initial enrollees. Another significant strength of the study is that this is the first study to examine self-reported discrimination, inflammation, SRH, and moderating factors in a large SA cohort. Social stressors like discrimination are understudied in SAs. This study provides data to inform the development of effective patient education and patient-provider health communications to cope with experiences of discrimination in SAs.

Limitations

The MASALA study participants were primarily middle-aged first-generation immigrants from India, had high socio-economic status, and were from only two geographic areas in the U.S. Therefore, the findings may not be generalizable to all SAs living in the U.S. Due to budget constraints, no inflammatory markers were measured from the Exam 1A participants. Self-report of discrimination, SRH, and coping styles may pose the limitation of response bias.

The current measurement of discrimination in the study did not assess the magnitude and duration of discriminatory experiences, which might have failed to capture the influence of discrimination on inflammation accurately. Alternatively, experiences of discrimination may be conceptualized differently among SAs, and the EDS scale used might have failed to capture it entirely among this population. Analyzing only a limited number of inflammatory markers may not fully explain the physiological effects of discrimination on various body systems.

Cross-sectional studies like the present study may not be able to capture the temporal nature of the association between discrimination and inflammation. Discrimination and inflammatory markers may need to be measured longitudinally in order to understand how changes in discrimination influence changes in inflammation levels over a period of time. For example, a study by Chen et al. (2022) found that exposure to discrimination during adolescence was associated with higher concentrations of inflammatory biomarkers (soluble urokinase plasminogen activator receptor) among African American males across their late 20s. The lack of similar studies on SAs creates a significant gap in the literature.

Future studies should also integrate the molecular mechanisms related to discrimination and inflammation that go beyond the measurement of blood cytokines. Inflammation involves activating several immune cells like monocytes, lymphocytes, and neutrophils in response to a stressor-like discrimination (Cuevas et al. 2020). Measurement of circulating inflammatory markers alone cannot identify whether they originated from immune cells or any other areas like adipose tissue (Chen et al. 2022). Therefore, future research should integrate in vitro studies of immune cell responses to triggering stimuli and measurement of blood cytokines.

Conclusion

Contrary to the vast body of literature highlighting the association between discrimination and inflammation among other ethnic and racial groups, this study did not find a similar association among SAs in the U.S. However, emotion-focused coping style to experiences of discrimination was a moderator in the relationship between discrimination and SRH among SAs in the study. Future longitudinal studies, integrating molecular mechanisms, including other potential inflammatory markers and anti-inflammatory adipokines, and measuring the magnitude and duration of discrimination to explore the influence of discrimination on inflammation in SAs over time are needed. Future research may also include examining coping strategies that effectively reduce the negative health consequences of discrimination among SAs. The scope of SRH assessment as a marker of risk for CVD in SAs may be considered for the primary prevention of CVD in this high-risk population.

Acknowledgments

The MASALA study described was supported by Grant Number R01HL093009 from the National Heart, Lung, And Blood Institute and the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through UCSF-CTSI Grant Number UL1RR024131 and UL1TR001872. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Heart, Lung, And Blood Institute or the National Institutes of Health. The authors thank the other investigators, the staff, and the participants of the MASALA study for their valuable contributions.

Funding

The author(s) reported there is no funding associated with the work featured in this article.

Footnotes

Disclosure statement

No potential conflict of interest was reported by the author(s).

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