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. 2025 Mar 17;35(1):1–7. doi: 10.18865/EthnDis-2023-78

Stroke Incidence and High-Sensitivity C-Reactive Protein Among African Americans: The Jackson Heart Study

Cellas A Hayes 1,2,✉, Roland J Thorpe Jr 3, Mandip Dhamoon 4, Elizabeth Heitman 5, Keith C Norris 3,6, Bettina M Beech 3,7, Marino Bruce 3,8,9, Benjamin Walker 9, Jennifer C Reneker 9,10
PMCID: PMC11928021  PMID: 40124641

Abstract

Background

Strokes are a leading cause of death and disability among African Americans in the United States. Biological markers to predict stroke remain elusive; thus, our objective was to investigate whether inflammation, as measured by high-sensitivity C-reactive protein (hs-CRP), was associated with stroke incidence among African Americans enrolled in the Jackson Heart Study (JHS).

Methods

Baseline hs-CRP levels were categorized in quintiles: quintile 1 (0.0084 mg/L); quintile 2 (0.0085-0.0189 mg/L); quintile 3 (0.0190-0.036 mg/L); quintile 4 (0.037-0.0675 mg/L); quintile 5 (≥0.0676 mg/L). Nonfatal stroke incidence was ascertained from passive community surveillance through annual phone calls and adjudicated via hospital records. At baseline, stroke risk factors/covariates were compared across quintiles using a one-way analysis of variance and a chi-square test. The association between baseline hs-CRP levels and stroke incidence was determined using a Cox regression analysis to estimate hazard ratios (HRs) and 95% confidence intervals (CI).

Results

In the unadjusted model, hs-CRP levels in quintile 2 (HR, 1.48; 95% CI, 0.96-2.29), quintile 3 (HR, 1.44; 95% CI, 0.93-2.24), and quintile 4 (HR, 1.09; 95% CI, 0.68-1.74) were not associated with stroke incidence when compared with quintile 1 (reference). However, individuals within quintile 5 (HR, 1.78; 95% CI, 1.17-2.72) exhibited a significantly increased risk for stroke compared with those in the reference quintile. This risk persisted after adjusting for stroke risk factors (demographics, anthropometrics, health condition covariates, health behavioral risk factors, and cardiovascular disease history) for quintile 5 (HR, 1.87; 95% CI, 1.17-2.98) compared with reference quintile 1.

Conclusions

An increased and independent risk of nonfatal stroke appears at the highest quintile of hs-CRP values (≥0.0676 mg/L) among JHS participants.

Keywords: African Americans, Jackson Heart Study, Stroke, High-sensitivity C-reactive Protein, hs-CRP, Inflammation

Introduction

Strokes are a leading cause of death and a major contributor of physical and cognitive disabilities, especially for older adults in the United States.1 Although there are multiple types of strokes, 80% are classified as ischemic.1 For 6 decades, stark differences in stroke incidence between Black and White populations have been documented in the United States, with the Black population experiencing a higher incidence.2-4 People in the southern region of the United States have a disproportionately higher stroke incidence than do those in the rest of the country.5 Coincidentally, the largest population of African Americans lives in the Deep South, which likely contributes to this observed geographic disparity. Although hypertension and diabetes are known risk factors for stroke, there remains little information on biological markers that might be associated with stroke incidence, and research to identify biomarkers that could be associated with stroke incidence is ongoing. Inflammation is 1 biomarker of interest.6

Total body inflammation can be influenced by a wide array of diseases and disorders that contribute to the development and onset of cardiovascular disease and associated comorbidities.7 High-sensitivity C-reactive protein (hs-CRP) is secreted by the liver and is found in the bloodstream in response to inflammation throughout the body.8,9 Although hs-CRP does not indicate the origin of inflammation, hs-CRP does provide an indication of total systemic inflammation and bodily functions that influence the onset of metabolic and cardiovascular disease.10 Thus, hs-CRP may be a reliable predictor for various cardiovascular diseases.

As a group, African Americans have a significantly higher median level of hs-CRP compared with White, Japanese, Chinese, and Hispanic Americans.11-13 Previous studies with diverse populations have highlighted that elevated hs-CRP is associated with increased risk of stroke,14-16 self-reported stroke incidence,17 ischemic stroke,18 recurrence of stroke,19 and functional outcomes and mortality among stroke patients.20 Although there is a documented study assessing the relationship between hs-CRP and stroke with race as the stratified group, there remains a gap in our understanding of the relationship between inflammation and stroke incidence among African Americans, the racial group at the highest risk for stroke.21 Therefore, there is a need to understand the association between hs-CRP and stroke incidence among African Americans. Utilizing longitudinal data from the Jackson Heart Study (JHS), we examined whether hs-CRP was associated with nonfatal stroke incidence in this large African American cohort. We hypothesized that the highest levels of hs-CRP are associated with an increased risk of nonfatal stroke incidence among African Americans enrolled in the JHS.

Methods

The JHS

The JHS was initiated in 1998 as a community-based longitudinal observational study designed to investigate the impact of socioeconomic status, educational attainment, lifestyle choices, and clinical and biologic risk factors on the cardiovascular health of African Americans.22 The original cohort of JHS participants included 5,306 individuals who identified as Black or African American, were aged 21-94 years at baseline, and were recruited from the 3 surrounding counties (Hinds, Rankin, and Madison) of Jackson, Mississippi. Exam 1 was conducted between 2000 and 2004, exam 2 was conducted between 2005 and 2008, and exam 3 was conducted between 2009 and 2013. For this study, hs-CRP was measured at baseline (visit 1), and stroke incidence was measured at visits 2 and 3. Individuals with a prevalent history of stroke (n=226) or who did not have hs-CRP measurements at visit 1 (n=105) were excluded. Individuals who did not release their medical records at visits 1 (n=173), 2 (n=77), and 3 (n=124) also were excluded. Participants who died during the study were included, and their date of death was used to ascertain their final number of days enrolled. The final number of participants eligible for the study was 4,601.

Nonfatal Stroke Incidence

Stroke incidence was the primary dependent variable and was determined through community surveillance via annual follow-up phone calls. Self-reported events were adjudicated through hospital records. Both ischemic and hemorrhagic strokes were included. Incident stroke events were ascertained from baseline to December 31, 2016. Possible stroke events were identified by contacting participants annually and through surveillance of local hospitals. Stroke hospitalization records with International Classification of Diseases codes (revisions 9 and 10) suggestive of stroke events were abstracted and adjudicated by physician reviewers.23 The total number of participants who experienced a nonfatal stroke in this study was 228 (211 ischemic, 14 hemorrhagic, and 3 subarachnoid hemorrhagic).

High-sensitivity C-reactive Protein

High-sensitivity C-reactive protein was the primary independent variable of interest and was derived from the results of the immunoturbidimetric CRP-Latex assay (Kamiya Biomedical Company, Tukwila, Washington) following the manufacturer’s protocol. Blood serum samples were run in duplicate, and approximately 6% of samples were measured as masked replicates on different dates for repeatability.24,25 Given the discrepancy in hs-CRP levels based on population variance, we chose to divide the sample range into 5 levels (quintiles). Baseline measurements of hs-CRP were divided as follows: quintile 1 (0.0084 mg/L), quintile 2 (0.0085-0.0189 mg/L), quintile 3 (0.0190-0.036 mg/L), quintile 4 (0.037-0.0675 mg/L), and quintile 5 (≥0.0676 mg/L). Quintiles are more discriminatory than stratifying by tertiles, which is a common approach for analyzing hs-CRP in clinical research. This division justifies our approach of segmenting the sample into relatively equal groups for quintiles.

Covariates

Baseline covariates included demographics, anthropometrics, health conditions, behavioral risk factors, and cardiovascular disease history. The demographic variables were age and sex. Age was defined as the age at the visit date or was calculated from the participant’s birth year at baseline. Sex was based on participants’ report of being male or female. Anthropometric variables were body mass index (BMI) and obesity status. BMI was calculated as the ratio of measured body weight (kg) and height (m2). Participants who had a BMI≥30 kg/m2 were classified as obese.26 Per the American Heart Association, weight-related health status consisted of 3 levels based on calculated BMI: (1) normal weight, <25; (2) overweight, 25 to <30; and (3) obese ≥30. Health conditions were high cholesterol indicated by total cholesterol levels, hypertension status, and diabetes status. High cholesterol was noted when a participant had a fasting total cholesterol level ≥200 mg/dL.27 Hypertension status was defined as blood pressure ≥140/90 mm Hg or reported use of blood pressure–lowering medication.28,29 Participants were categorized as being diabetic when their fasting glucose was ≥126 mg/dL (per the American Diabetes Association),30 their hemoglobin A1c level was ≥6.5%, they reported the use of diabetic medication (actual or self-reported) within the 2 weeks prior to the clinic visit, or they self-reported having diabetes.29 Behavioral risk factors were drinking alcohol and smoking. Alcohol drinking was defined by participants’ responses to being asked “were you a regular drinker in the last year” and was indicated by a “yes” or “no” response. Smoking was defined as being a current smoker or having ever been a smoker (“ever smoker”) and was indicated by a “yes” or “no” response.31,32 Cardiovascular disease history was based on self-report of a history of cardiovascular disease and was indicated by a “yes” or “no” response.33

Statistical Analysis

The study included 4,601 participants who met the eligibility criteria based on the inclusion/exclusion criteria. To compare the distribution of baseline characteristics and stroke incidence, we stratified the participants into hs-CRP quintiles, following the approach used by Ridker and colleagues.34 For continuous variables, such as baseline characteristics, we performed a one-way analysis of variance (ANOVA) to assess the differences between the quintiles. Categorical variables were analyzed using a chi-square test. The hs-CRP levels were categorized into quintiles and treated as categorical variables. We also conducted analyses treating hs-CRP quintiles as continuous variables, but the results did not differ.

To visually assess the relationship between hs-CRP quintiles and stroke incidence over time, Kaplan-Meier curves were constructed with risk tables. For Cox proportional hazard regression analysis, patients who died during the study were censored, and their date of death was used to determine the number of days they were enrolled. Cox proportional hazards regression was employed to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). We used 2 models to examine the association of hs-CRP with stroke incidence: an unadjusted model and a fully adjusted model that accounted for all baseline covariates of hs-CRP and stroke incidence. The lowest quintile of hs-CRP (quintile 1) was used as the reference group for all models. Statistical significance was determined at P<.05.

To verify the findings related to the categorical hs-CRP quintile analysis, we employed a sensitivity analysis using a continuous log-transformed hs-CRP. First, a small constant value (0.001) was introduced to ensure that all values were above zero, enabling the log transformation, which we found to be true. Notably, no values in the data set fell below the limit of detection for hs-CRP, allowing us to proceed with the log transformation. The mean and SD of the log-transformed hs-CRP values were then calculated. Subsequently, the log-transformed hs-CRP values were standardized by subtracting the mean log-transformed hs-CRP and dividing by the SD. The resulting standardized log-transformed hs-CRP values were employed for subsequent analysis. Following transformation, we visualized hs-CRP using a histogram, and it exhibited normalization.

To assess the linearity of the association between continuous hs-CRP and the risk of nonfatal stroke, a sensitivity analysis was conducted using restricted cubic splines with 4 knots. The spline analysis revealed a nonlinear relationship between hs-CRP and stroke risk, with a notable increase in risk at higher levels of hs-CRP. Given this observed nonlinearity a quintile specification was chosen for hs-CRP in the primary analysis. We conducted all data analyses and visualizations with R version 4.2.3 (R Foundation for Statistical Computing, Vienna, Austria).

Results

Demographics

The distribution of baseline characteristics across hs-CRP quintiles was analyzed and are shown in Table 1. The results of the one-way ANOVA revealed a significant difference in age among the hs-CRP quintiles (F4, 4596=6.34, P<.001). Subsequent Tukey post hoc tests indicated that participants in quintiles 2, 3, 4, and 5 had significantly higher ages than did participants in quintile 1 (P<.05). The distribution of sex differed across the hs-CRP quintiles (χ24=283.5, P<.001). Participants in quintiles 2, 3, 4, and 5 had significantly higher BMI values than did participants in quintile 1 (P<.001). The chi-square test revealed a significant association between high cholesterol and hs-CRP quintiles (χ24=25.51, P<.001). Hs-CRP quintiles also had a hypertension significant association with (χ24=83.29, P<.001) and diabetes (χ24=84.48, P<.001). There was not a significant association between current smoking and hs-CRP quintiles (χ24=8.24, P=.08) or cardiovascular disease history (χ24=0.73, P=.94).

Table 1.

Distribution of baseline characteristics of participants of the Jackson Heart Study for the total sample and stratified by hs-CRP quintiles

Variable Overall (N=4601) hs-CRP quintile
 P
1 (N=923) 2 (N=919) 3 (N=922) 4 (N=918) 5 (N=919)
Age (Years) 54.5±12.8 52.9±13.3 54.7±13.3 55.1±12.7 55.5±12.2 54.5±12.4 <.001
Sex (Male) 1710 (37.2%) 470 (50.9%) 445 (48.4%) 354 (38.4%) 269 (29.3%) 172 (18.7%) <.001
BMI 31.8±7.3 27.6±5.0 29.8±5.4 31.6±6.2 33.2±6.9 36.6±8.7 <.001
High cholesterol 1973 (42.9%) 355 (38.5%) 406 (44.2%) 428 (46.4%) 421 (45.9%) 363 (39.5%) <.001
Hypertension 2524 (54.9%) 396 (42.9%) 488 (53.1%) 522 (56.6%) 548 (59.7%) 570 (62.0%) <.001
Diabetes 1049 (22.8%) 133 (14.4%) 173 (18.8%) 213 (23.1%) 256 (27.9%) 274 (29.8%) <.001
Current smoking 603 (13.1%) 104 (11.3%) 108 (11.8%) 122 (13.2%) 129 (14.1%) 140 (15.2%) .08
CVD history 310 (6.7%) 59 (6.4%) 58 (6.3%) 65 (7.0%) 64 (7.0%) 64 (7.0%) .94
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Abbreviations: hs-CRP, high-sensitivity C-reactive protein; BMI, body mass index; CVD, cardiovascular disease history. Hs-CRP quintile 1 (reference), 0.0084 mg/L; quintile 2, 0.0085-0.0189 mg/L; quintile 3, 0.0190-0.036 mg/L; quintile 4, 0.037-0.0675 mg/L; quintile 5, 0.0676-3.3800 mg/L. Values for categorical variables are number (percentage) of participants, and those for continuous variables are mean±SD

Years From Baseline to Stroke Incidence Across hs-CRP Quintiles

We conducted an ANOVA to explore the relationship between stroke incidence, as measured by years until stroke occurrence, and the quintiles of hs-CRP levels (Table 2). There was no significant difference in years until stroke occurrence across the hs-CRP quintiles (F4, 223=1.182, P=.31).

Table 2.

Average years from baseline to stroke incidence by high-sensitivity C-reactive protein quintiles

Quintile (mg/L) N Average years to stroke
1. <0.0084 34 6.83±3.83
2. 0.0085-0.0189 50 7.25±4.18
3. 0.019-0.036 48 6.13±3.95
4. 0.0367-0.0675 37 6.04±4.48
5. >0.0676 59 7.53±4.54
Overall 228 6.83±4.24
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Values are mean±SD

Stroke Incidence Between hs-CRP Quintiles

The HRs and 95% CIs of stroke incidence among hs-CRP quintiles in the unadjusted model and the fully adjusted model, controlling for known stroke risk factors, are shown in Table 3. In the unadjusted model, no significant association was found between hs-CRP levels and stroke for quintiles 2, 3, and 4 compared with the reference quintile 1. Those participants with the highest levels of hs-CRP, quintile 5, were at a significantly increased risk for nonfatal stroke incidence compared with participants in the reference category (HR, 1.78; 95% CI, 1.17-2.72). In the fully adjusted model controlling for known stroke risk factors and comorbidities, only those participants within quintile 5 were at an increased risk for nonfatal stroke incidence (HR, 1.87; 95% CI, 1.17-2.98).

Table 3.

Hazard ratios (95% confidence intervals) of stroke incidence among high-sensitivity C-reactive protein (hs-CRP) quintiles in the unadjusted and fully adjusted model controlling for known stroke risk factors

Quintile (mg/L) N Sequential modelsa
Unadjusted Adjusted
1. <0.0084 (reference) 923 1.0 1.0
2. 0.0085-0.0189 919 1.48 (0.96-2.29) 1.27 (0.79-2.03)
3. 0.019-0.036 922 1.44 (0.93-2.24) 1.18 (0.73-1.91)
4. 0.0367-0.0675 918 1.09 (0.68-1.74) 0.91 (0.55-1.52)
5. >0.0676 919 1.78 (1.17-2.72) 1.87 (1.17-2.98)
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a

Unadjusted model included only hs-CRP; adjusted model included hs-CRP plus age, sex, obesity category, total cholesterol, hypertension status, diabetes status, current smoking status, ever smoking status, and cardiovascular disease history

Discussion

The purpose of this study was to examine the association between hs-CRP and stroke incidence among participants in the JHS, a cohort of solely African Americans in Mississippi. Our central findings demonstrated a significant association between hs-CRP levels >0.0676 mg/L (quintile 5) and an increased risk for incident nonfatal stroke across the study timeframe.

Several studies have suggested that elevations in hs-CRP are associated with stroke incidence;14,35-37 however, other studies have not corroborated these findings.38 There is a wide array of literature indicating that African Americans have higher median hs-CRP levels compared with members of other racial and ethnic groups.11-13,39-44 These observed higher median hs-CRP levels are likely due to the high prevalence of hypertension and type 2 diabetes, arguably 2 of the most prominent predispositions to stroke.45,46 Importantly, hs-CRP has been associated with hypertension47 and type 2 diabetes in the JHS.25 Because of the overt evidence that Black individuals have a higher hs-CRP than other races/ethnicities, we hypothesized that increased levels of hs-CRP are associated with a greater stroke incidence. Interestingly, we found a significant association with the highest levels of hs-CRP and nonfatal stroke incidence after adjusting for multiple variables, suggesting an independent role for hs-CRP at the higher levels. Moreover, these findings were furthered emphasized using a sensitivity analysis with a continuous hs-CRP variable generated through log-transformation and a cubic splines method to include in Cox regression for stroke incidence analysis. Our results suggests that hs-CRP levels >0.0676 mg/L may be a useful predictor for nonfatal stroke incidence for African Americans who may already have elevated hs-CRP levels compared with people of other races and ethnicities.

In a separate population study, the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, similar findings were presented.21 Specifically, a splines analysis revealed that there was a difference in the association between the highest levels of hs-CRP (>10 mg/L) and ischemic stroke risk in African Americans and Black participants. Although these findings were nontraditional at the time, they were the first that presented evidence that only African Americans who had the highest levels of hs-CRP were at an increased risk for ischemic stroke. To our knowledge, our study is the second to find this relationship in African Americans, which increases the likelihood that these are true associations in differing populations. We further caution the clinicians in recommending a different cut point of hs-CRP for African Americans until further research in conducted and validate both our findings and those of Evans et al.21

Although hs-CRP is the most common way to measure systemic inflammation, numerous acute-phase proteins, cytokines, and cell adhesion molecules contribute to total hs-CRP production. Multiples of these biological markers, such as interleukin-10, soluble intercellular adhesion molecule 1, and lipoprotein-associated phospholipase A2, have been shown to be associated with stroke.48-50 In addition, hs-CRP levels are influenced by comorbidities such as type 2 diabetes and hypertension. Although the majority of epidemiological studies do not measure specific cytokines/chemokines and related molecules, they do control for covariates that are known to change these markers, affecting the overall hs-CRP level. The contribution of multiple inflammatory biological molecules demonstrates the complexity of assessing whether total systemic inflammation is a reliable biomarker for disease incidence. Yet, our specific findings within the highest quintile of hs-CRP levels suggest that African Americans with an hs-CRP level >0.0676mg/L are at a greater risk for a stroke.

This study has limitations surrounding our central question of whether increased hs-CRP levels in African Americans are associated with nonfatal stroke incidence. One limitation is that we examined nonfatal stroke and did not include stroke death data. Those participants within quintile 5 were arguably the unhealthiest based on BMI and the presence of baseline stroke risk factors. It is possible that individuals with hs-CRP levels in quintile 5 are more likely to die because of fatal stroke or heart disease due to the contribution of other known stroke risk factors; however, these data are difficult to obtain, especially in post-stroke deaths that came in the weeks posti-ncidence. Future studies investigating disease incidence to understand possible biomarkers should also assess disease-caused death, which could provide participants with insights on their life expectancy based on possible health trajectories.

Despite these limitations, this study adds much needed evidence to bridge gaps in the epidemiologic literature on biomarkers in cardiovascular disease in the African American population. A strength of this study is that the JHS is the largest minority health disparities study of only African Americans in the United States, providing a novel opportunity to determine whether hs-CRP is independently associated with nonfatal stroke incidence in this large cohort of well-studied African Americans, the racial group at highest risk for premature stroke in the Stroke Belt. A second strength is that self-reported stroke incidence was corroborated with health records providing the exact date of the event for adjudication of time-to-event analysis. A third strength is the size of the population included in this study: 4,601 participants. Thus, our study provided a substantial number of participants for detecting robust associations in a population with a high risk for stroke. Furthermore, the participants in this study were followed for over a decade and assessed for incident stroke events at the second and third visits. The greatest strength is that our findings corroborate those from a similar study of the REGARDS participants.21 These findings are clinically relevant, indicating that there is a threshold of hs-CRP for African Americans that could serve as a disease predictor that warrants investigation in populations outside of the Stroke Belt.

Conclusions

Our findings provide an innovative perspective that increased hs-CRP values are not always associated with increased stroke risk, but a dose threshold of hs-CRP can serve as a biomarker for stroke risk for African Americans. To strengthen the impact of these results, future epidemiological studies should be conducted to quantify additional established systemic inflammatory markers beyond hs-CRP. Given that inflammation and cardiovascular disease risk are influenced by hypertension and type 2 diabetes, which are more common among African Americans, our findings indicate the need to incorporate additional biomarkers related to cardiovascular diseases and the known comorbidities that are known risk factors/mediators. With the disparate ratio of cardiovascular disease risk factors in the African American population, these findings are an important step for define thresholds for biomarkers for diseases such as stroke that are highly prevalent in the Black population.

In this study, we found that elevations in hs-CRP were associated with numerous stroke risk factors, including age and comorbidities such as hypertension and diabetes. Our key findings were that the risk of nonfatal stroke was significantly increased for participants with hs-CRP levels >0.0676 mg/L. These findings are unique and clinically relevant and add to a body of work suggesting that increased hs-CRP is a powerful risk for stroke. We have also defined a potential reference for the African American population in which hs-CRP could be a reliable independent predictor for nonfatal stroke incidence. Future controlled prospective studies aimed at refining the potential of biological markers to predict cardiovascular diseases such as stroke are warranted.

Acknowledgments

The Jackson Heart Study (JHS) is supported and conducted in collaboration with contracts to Jackson State University (HHSN268201800013I), Tougaloo College (HHSN268201800014I), the Mississippi State Department of Health (HHSN268201800015I), and the University of Mississippi Medical Center (HHSN268201800010I, HHSN268201800011I, and HHSN268201800012I) from the National Heart, Lung, and Blood Institute (NHLBI) and the National Institute on Minority Health and Health Disparities. The authors also wish to thank the staff and participants of the JHS. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the NHLBI, the National Institutes of Health, or the US Department of Health and Human Services. CAH was supported by the National Institute of Health Neurological Disorders and Stroke of the National Institutes of Health under award F31NS124302, the Southern Regional Educational Board, the Neuroscience Scholar Program sponsored by the Society for Neuroscience, Stanford Propel Postdoctoral Fellowship, Burroughs Wellcome Fund Postdoctoral Diversity Enrichment Program (PDEP) 1267001, and the HABS-HD Health Equity Scholars Program (HESP) U19AG078109.

Footnotes

Conflict of Interest: No conflict of interest reported by authors.

Author Contributions: Research concept and design: Hayes, Thorpe, Reneker; Data analysis and interpretation: Hayes, Thorpe, Walker, Reneker. Manuscript draft: Hayes, Thorpe, Dhamoon, Heitman, Norris, Beech, Marino Bruce, Walker, Reneker; Statistical Expertise: Thorpe, Walker; Supervision: Thorpe, Reneker

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