Determinants of Inflammatory Markers in a Bi-ethnic Population

Ethn Dis. Author manuscript; available in PMC 2012 August 24.

Published in final edited form as:

Ethn Dis. 2011 Spring; 21(2): 142–149.

PMCID: PMC3427005

NIHMSID: NIHMS398665

Determinants of Inflammatory Markers in a Bi-ethnic Population

Michael Paalani, MS, Jerry W. Lee, PhD, Ella Haddad, DrPH, and Serena Tonstad, MD

Department of Health Promotion and Education (MP, JL, ST) and Department of Nutrition (EH) Loma Linda University, Loma Linda, California

Address correspondence and reprint requests to: Serena Tonstad, MD; Department of Preventive Care; Loma Linda University; 24951 N Circle Drive, Loma Linda, CA 92354; 909.558.4741; Email: stonstad/at/llu.edu

See other articles in PMC that cite the published article.

Abstract

Background

Inflammation is a common pathophysiological pathway for a number of chronic diseases, and is strongly influenced by sociodemographic factors and lifestyle. Less is known about factors that may influence the inflammatory response in individuals of distinct ethnic backgrounds. Therefore, this study examined the relationship between ethnicity and blood levels of inflammatory markers in a sample of non-smoking church-goers.

Methods

In a cross-sectional investigation, 508 men and women (>35 years old, 62% White, 38% Black) participated in the Biopsy-chosocial Religion and Health substudy of the Adventist Health Study 2. The contribution of socioeconomic status (education level and difficulty meeting expenses for basic needs) and health covariates (exercise, vegetarian or other type of diet, body mass index, and presence of inflammatory conditions) toward serum levels of C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) was assessed with linear regression models. Levels of interleukin-10 (IL-10), an anti-inflammatory marker, were also assessed.

Results

Blacks showed higher levels of CRP and IL-6 than Whites. Controlling for socio-demographic and health variables attenuated the ethnic difference in CRP while IL-6 levels remained higher in Blacks than in Whites (β=.118; 95% confidence interval=.014–.206; P=.025). Ethnic differences in IL-10 and TNF-α were not found. Vegetarian diet was associated with lower CRP levels while exercise frequency was associated with higher IL-10 levels.

Conclusion

Higher susceptibility of Blacks to inflammatory diseases may reflect higher IL-6, which could be important in assessing health disparities among Blacks and Whites. Vegetarian diet and exercise may counteract effects of disparities.

Keywords: Inflammatory Markers, Ethnicity, Health Behavior, Adventists

Introduction

Ethnic differences in chronic disease incidence have been widely studied, with Blacks having a higher risk of hypertension, stroke and renal failure compared to Whites.¹ The reason for this disparity has not been completely elucidated but may be due to increased prevalence of disease risk factors among Blacks. Inflammation has been determined to be an important factor associated with chronic diseases, and is often indexed by elevated circulating levels of C-reactive protein (CRP) and pro-inflammatory cytokines.² Behavioral factors have a direct impact on inflammatory processes.³

The association between ethnicity and inflammation has been analyzed as well, showing that Blacks often have higher CRP than Whites.^4–6 Other inflammatory molecules include inter-leukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) which are associated with a pro-inflammatory response while IL-10 has anti-inflammatory effects.⁷ Some studies have shown that Blacks have higher IL-6 levels than Whites,^6,8 but it is unclear whether IL-10 and TNF-α levels vary according to ethnic background.^8–10

Ethnic specific differences in inflammation may have diverse determinants. For instance, low socioeconomic status (SES) has been associated with increased levels of CRP, IL-6 and TNF-α.^11–12 It is therefore possible that SES may partially explain why certain ethnicities are at higher risk for inflammatory problems. Health behavior factors also play a role in inflammation. Physical activity has been associated with lower circulating levels of CRP and IL-6 in both healthy and patient populations¹³ and has been shown to increase concentrations of anti-inflammatory cytokines (such as IL-1 receptor antagonist and IL-10) to lower the inflammatory response.¹⁴ In addition, diets rich in fruits, vegetables, whole grains and nuts have been associated with reductions in CRP and IL-6 levels, while diets high in red meat and high fat dairy have been directly correlated with increased inflammation.^15–16

Among other lifestyle factors, alcohol consumption has been associated with lower levels of CRP among moderate drinkers compared to non-drinkers and heavy drinkers, a U-shaped pattern.^17–18 Cigarette smoking has been found to be a potent risk factor for increased levels of low-grade inflammation based on elevated CRP and IL-6 levels.^19–20

One of the populations in which determinants of chronic disease have been studied is Seventh-day Adventists, a conservative religious group whose members normally abstain from alcohol and tobacco.^21–22 Thus, the population avoids some of the major identified factors involved in increasing inflammation and may provide the opportunity to illuminate the role of other factors, including ethnicity and lifestyle variables. In our study, ethnic differences in inflammation were assessed among a population of church-going Adventists. We also determined whether the ethnicity-inflammation relationship is affected by demographic, SES, behavioral or health status variables. The inflammatory markers that were analyzed include both pro-inflammatory (IL-6 and TNF-α) and anti-inflammatory (IL-10) cytokines as well as an acute phase protein (CRP).

Methods

Study Population

This study was a cross-sectional analysis of the data gathered from a substudy of the Adventist Health Study-2 (AHS-2) referred to as the Biopsychosocial Religion and Health Study (BRHS).²³ Approximately 20,000 participants randomly selected from the 96,000 case AHS-2 sample were sent a 20-page religion and health questionnaire, and about 11,000 returned the questionnaire. The data collection began in September 2006 and was largely completed by August 2007. The study population consisted mainly of Black and White, Seventh-day Adventist males and females who were aged ≥35 years. In addition to completing the questionnaire, 508 BRHS participants also attended study-specific clinics in Loma Linda, Riverside, or Los Angeles to be assessed for biologic indicators and anthropometric measurements. Cytokine analysis was based on fasting blood samples provided by the participants on the day they attended the clinic. The institutional review board at Loma Linda University approved the study protocol, and informed consent was obtained from all participants.

Measurement of Variables

Sociodemographic Variables

Sociodemographic variables included age, sex, and ethnicity. Ethnicity was coded as Black or White based on self-report. Ethnicity was divided into Black (Black/African American, West Indian/Caribbean, African or other Black) and White (White non-Hispanic, Hispanic, Middle Eastern, Asian, Native Hawaiian/other Pacific Islander or American Indian) in the current analysis.

Socioeconomic Status

Socioeconomic status was assessed based on the participants’ highest level of education as well as the degree of difficulty meeting family expenses for basic needs in the last year. Education was categorized as follows: a) grade school or some high school, b) high school or trade school diploma, c) some college, an Associate’s degree, or a Bachelor’s degree, and d) a Master’s or Doctoral degree. The response choices for assessing the degree of difficulty meeting family expenses were: not at all, a little, somewhat, fairly, and very.

Health Behavior Variables

Behavioral variables included exercise, vegetarian diet, smoking, and alcohol consumption. Exercise was measured by the number of times per week that the participant engaged in regular vigorous activities using previously validated questions.^24–25 A 14-item food frequency questionnaire was used to assess the participants’ dietary intake, and vegetarian status was assessed by whether or not participants consumed red meats, turkey or chicken, or fish over the last 12 months as three separate questionnaire items. A score of 1 indicated that participants never or rarely consumed the food items mentioned above, and a score of 2 indicated that participants consumed any of these foods at least 1 time per month. All values of 1 were coded as vegetarians, and all values of 2 were coded as non-vegetarians. Since there was only 1 current smoker and 18 participants who consumed alcohol more than 1 time per week, we did not control for these variables in the final analysis. Results did not change substantially when analyses were run with alcohol and smoking included as control variables (data not shown).

Health Status Variables

The participants’ health status was assessed based on their height, weight, waist circumference, and calculated BMI as well as the presence of inflammatory conditions. Waist circumference was measured midway between the lower rib margin and the iliac crest to the nearest millimeter. Waist circumference measurements were not controlled for in the final regression analysis because of their high degree of correlation with BMI (r=.729; P=.000). The participants were assessed for the presence of a disease associated with inflammation based on whether or not they reported any of the following conditions: type 2 diabetes, stroke, transient ischemic attack, angina pectoris, rheumatoid arthritis, or sleep apnea.

Inflammatory Markers

Serum concentrations of CRP, IL-6, IL-10 and TNF-α were assessed based on fasting blood samples provided by participants that were processed and stored in −70°C freezers until they were ready to be tested. These inflammatory markers were measured in duplicate by enzyme linked immunosorbent assay (ELISA) kits from Assaypro (CRP), R & D Systems (IL-6), and ThermoScientific (IL-10 and TNF-α). The minimum detectable concentrations were 100 pg/mL for CRP, .039 pg/mL for IL-6, 3 pg/mL for IL-10, and 2 pg/mL for TNF-α. The intra-assay and inter-assay coefficient of variation (CV) were 5.5% and 7.6% for CRP, 6.9% and 7.2% for IL-6, 8.7% and 9.4% for IL-10, and 4.2% and 5.2% for TNF-α. All ELISA kits used were specific for the measurement of natural human CRP, IL-6, IL-10 and TNF-α concentrations in serum, and did not cross-react with other cytokine molecules. Standard ELISA plate readers were used to measure the absorbance of each sample.

Statistical Analysis

All statistical analysis was performed using SPSS (version 17). Ethnic differences in the study characteristics were determined using independent t tests for continuous variables or chi-square tests for categorical variables (Table 1). In addition, Mann-Whitney tests were also used to determine the differences in inflammation between Blacks and Whites since the CRP, IL-6, IL-10 and TNF-values were not normally distributed and required log transformation before regression analysis could be performed (Table 2).

Table 1

Main characteristics of the study population according to ethnicity

Table 2

Ethnic differences in inflammatory marker concentrations

Multiple linear regression analysis was utilized to test the association between ethnicity and inflammation among the study population after controlling for demographic, socioeconomic, behavioral and health status variables. Separate models were utilized to test the effects of these variables on inflammation, and each model was analyzed in a stepwise fashion. Ethnicity was included in model 1, while model 2 added age, sex, education, and degree of difficulty meeting family expenses. Model 3 additionally added exercise and vegetarian diet consumption, and BMI was included in model 4. Model 5 added whether the participants were diagnosed with a medical condition. The serum concentrations of log transformed CRP, IL-6, TNF-α, and IL-10 served as continuous outcome variables in separate linear regression equations. Cytokine concentrations below the limit of detection were given a value of .001 representing a near zero value as demonstrated in a previous study.²⁶ The regression analysis was based on standardized regression coefficient values as well as R² change values which were used to determine the amount of variability in inflammation explained by the predictor variables in each of the given models.

Results

The study population characteristics and differences between Blacks and Whites are shown in Table 1. The mean age was 68.8 years (range: 36–102); 63% of the participants were women and 37% were Black. Black participants were younger, achieved a lower level of education, and had more difficulty meeting family expenses for basic needs in the last year. Blacks were also less likely to consume a vegetarian diet, and had a higher mean BMI and waist circumference (waist circumference data not shown). Table 2 shows that higher levels of CRP and IL-6 were present among Black participants compared to the White participants while IL-10 and TNF-α levels did not differ between the two groups.

Regression coefficients for the association of each predictor variable with serum concentrations of CRP and IL-6 are illustrated in Table 3 and and4,4, respectively. CRP levels were found to be significantly higher among Blacks than Whites, but this relationship was no longer significant after controlling for the demographic and SES variables in model 2. After controlling for all covariates, CRP levels were positively associated with age, being female, BMI, and being non-vegetarian (Table 3). IL-6 was positively associated with age, BMI, and being Black after controlling for all other factors. Increased exercise frequency was associated with a decrease in IL-6 levels, but this relationship was no longer significant after controlling for BMI (Table 4). Nevertheless, IL-10 was positively associated with exercise frequency after controlling for all other covariates (β=.147, P=.005).

Table 3

Regression analysis models illustrating the association between various predictor variables and CRP

Table 4

Regression analysis models illustrating the association between various predictor variables and IL-6

The R² change values are provided in Table 3 and and4.4. A significant proportion of variability in CRP was explained by ethnicity (P=.047), age, gender, education, and difficulty meeting family expenses for basic needs (P=.000), health behavior variables (P=.000), and BMI (P=.000). Likewise, ethnicity (P=.011), age, sex, education, and difficulty meeting family expenses for basic needs (P=.003), health behavior variables (P=.047) and BMI (P=.003) also explained significant amounts of variability in IL-6 levels. Finally, health behavior variables (mainly exercise frequency) explained a significant proportion of IL-10 variability based on the regression analysis (R² change=.025; P=.006).

Discussion

This study has shown that IL-6 may serve as an important ethnic-specific cytokine that is higher among Blacks than Whites, while the other inflammatory markers or anti-inflammatory marker (IL-10) did not differ between Blacks and Whites. Healthy lifestyle behaviors were associated with a lower inflammatory status, after controlling for ethnic differences, as increased exercise frequency was associated with increased IL-10 levels, and consumption of a vegetarian diet was associated with lower CRP levels.

The present study provides further evidence of an association between ethnicity and inflammation, in line with other studies that have found higher IL-6 levels among Blacks compared to Whites.^8,27,28 However, these studies did not control for variables such as diet or exercise when assessing the ethnic differences in IL-6, and may have been confounded by differences between Blacks and Whites in regard to lifestyle induced changes in inflammation. Earlier study designs were also based on a much smaller sample size than was used for the current investigation.

Adipose tissue synthesizes inflammatory markers such as IL-6, and increased body mass has been associated with higher inflammation levels among Blacks.^29,30 However, the ethnic specific difference in IL-6 was significant even after controlling for BMI in the current study, so other factors may be responsible for this relationship. One possible reason for the ethnic variations in the level of this cytokine is due to differences in cytokine gene polymorphisms. It has been suggested that specific allelic variations in the regulatory regions of inflammatory cytokine genes may alter the expression of some cytokines.³¹ One of the genotypes that results in high IL-6 production (G/G IL-6 genotype) has been predominantly found in Blacks, and may explain higher levels of this cytokine among this ethnic group.³²

Although there were higher CRP levels among Blacks in the present study, this association was no longer significant after controlling for the other covariates. Studies among the US population have shown that there are higher CRP levels among Blacks in relation to Whites.^33–35 However, like the results from the present study, the ethnicity-CRP association found in some of the investigations ultimately disappeared after controlling for various health-related factors.^36–37 In the current study, the ethnicity-CRP relationship was largely attenuated after controlling for vegetarian diet consumption as well as exercise frequency, and even more attenuated after controlling for BMI. Therefore, future studies should investigate lifestyle components as well as other variables associated with obesity that may serve as important mediating factors between ethnicity and CRP.

No significant differences in IL-10 and TNF-α levels were found between Black and White patients in the present study. Although lower levels of IL-10 among Blacks compared to Whites have been reported previously,⁹ the analysis was based on stimulated peripheral blood samples rather than basal cyto-kine levels in the blood. Therefore, no direct evidence of ethnic differences in circulating IL-10 levels was shown. As far as ethnic differences in TNF-α are concerned, the results are mixed. A study by Kalra et al⁸ found that TNF-α levels were higher among Blacks in relation to Whites from the United Kingdom, while Elkind et al¹⁰ found no significant difference in TNF-α levels among Blacks and Whites from the United States. Therefore, geographic location, environmental factors, and other variables such as diet, exercise and body mass may play an important role in the onset of inflammation among different ethnic groups.

Based on the results provided, engaging in exercise and consuming a vegetarian diet was associated with lower inflammation levels. Vegetarians demonstrated a lower blood concentration of CRP compared to non-vegetarians which is in accordance with previous research showing that long-term vegetarians have a lower risk of coronary heart disease and an improved antioxidant and inflammatory status compared to non-vegetarians.³⁸ In addition, greater amounts of regular physical activity have been associated with elevated IL-10 levels in healthy older males,³⁹ and aerobic exercise training has been reported to exert anti-inflammatory effects in type 2 diabetics due to increases in IL-10 concentrations.⁴⁰ Specifically, high intensity exercise has been more strongly associated with increased IL-10 levels when compared to moderate and light intensity exercises among healthy, well-trained participants,⁴¹ suggesting that more vigorous exercise may provide stronger anti-inflammatory effects.

Strengths and Limitations

This study assessed pro-inflammatory and anti-inflammatory cytokines that were not examined together in previous studies. The absence of cigarette smokers and low amount of alcohol consumption allowed the confounding effects of smoking and excess alcohol on inflammatory markers to be avoided. Finally, the current study sample size provided sufficient power for detecting associations between the study variables.

This was a cross-sectional study so causality between ethnicity and other variables and levels of inflammatory markers cannot be assumed. There were differences in baseline factors between Blacks and Whites. We adjusted for these factors, but residual confounding may remain due to the effects of other variables not measured in the present study (such as lean body mass differences between Blacks and Whites) as well as incomplete statistical adjustment. However, abdominal fat content was assessed by waist circumference which showed the same ethnic specific differences found based on BMI measurements.

The study population consisted of only Adventist church goers and generalizability to the larger population may be limited. Genetic markers of the inflammatory cytokines were not examined, limiting our analysis to cytokine concentrations rather than specific gene activity. The TNF-α concentration of 204 of the study participants (63% White and 37% Black) was below the limit of detection as well, similar to the proportion of Whites and Blacks in the overall study. It is possible that this population of church goers may have been less susceptible to increased inflammation based on their overall health and lifestyle practices, making it difficult to detect this inflammatory marker. Therefore, future analysis of inflammation using TNF-receptor 1 as a surrogate marker for TNF-α may be preferable since TNF-α has a short half-life (~15 minutes) and can be difficult to detect among certain populations using standard ELISA kits.⁴²

Conclusion

Inflammatory based risk for health problems may vary according to ethnicity and other demographic factors. Yet inflammation levels also seem to be influenced by other variables such as diet, exercise, and overall body mass. Interventions that focus on improving these health behaviors may therefore be the key to reducing the risk for chronic diseases.

Acknowledgments

This research was funded in part by a grant from the Throne Holst Foundation in Oslo, Norway and was supported by the Biopsychosocial Religion and Health Study funded by the National Institute of Aging (1R01AG026348-01). We also acknowledge Kate McCarthy for her assistance with laboratory analyses.

Footnotes

Author Contributions

Design concept of study: Paalani, Lee, Tonstad

Acquisition of data: Lee, Haddad

Data analysis and interpretation: Paalani, Tonstad

Manuscript draft: Paalani, Tonstad

Statistical expertise: Paalani, Lee

Acquisition of funding: Tonstad

Administrative: Paalani, Lee

Supervision: Haddad, Tonstad

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