Stroke in Indigenous Africans, African Americans and European Americans: Interplay of racial and geographic factors

Abstract

Background and Purpose

The relative contributions of racial and geographic factors to higher risk of stroke in people of African ancestry have not been unraveled. We compared stroke type and contributions of vascular risk factors among indigenous Africans (IA), African Americans (AA) and European Americans (EA).

Methods

SIREN is a large multinational case-control study in West Africa - the ancestral home of 71% AA - whilst REGARDS is a cohort study including AA and EA in United States. Using harmonized assessments and standard definitions, we compared data on stroke type and established risk factors for stroke in acute stroke cases age ≥55 years in both studies.

Results

There were 811 IA, 452 AA and 665 EA stroke subjects, with mean age of 68.0±9.3, 73.0±8.3 and 76.0±8.3 years respectively (p<0.0001). Hemorrhagic stroke was more frequent among IA (27%) compared to AA (8%) and EA (5.4%; p < 0.001). Lacunar strokes were more prevalent in IA (47.1%), followed by AA (35.1%), and then EA (21.0%; p < 0.0001). The frequency of hypertension in decreasing order was IA (92.8%), followed by AA (82.5%) and then EA (64.2%; p<0.0001) and similarly for diabetes mellitus (DM) IA (38.3%), AA (36.8%) and EA (21.0 %; p<0.0001). Pre-morbid sedentary lifestyle was similar in AA (37.7%) and EA (34.0%) but lower frequency in IA (8.0%).

Conclusion

Environmental risk factors such as sedentary lifestyle may contribute to the higher proportion of ischemic stroke in AA compared to IA, while racial factors may contribute to the higher proportion of hypertension and DM among stroke subjects of African ancestry.

INTRODUCTION

Stroke is a leading cause of death, disability and dementia globally with 87% of the burden being borne by low and middle-income countries (LMIC).¹ The World Health Organization estimates indicate that death from stroke and disability adjusted life years (DALY) lost to stroke are about 7 times higher in LMIC – including much of Africa – than in high-income countries.² In sharp contrast to high income countries, estimates from the Global Burden of Disease Study (GBD) suggest that stroke incidence is rising in African countries where as a major health challenge, it is levying a heavy toll on the developing economy by affecting a relatively younger age group.^{1, 3,4}

For poorly understood reasons, people of African ancestry have a higher risk of stroke, earlier age of occurrence, poorer outcomes and relatively higher percentage of strokes being hemorrhagic type than people of other ancestry.^3–5 The Ibadan-Berlin Stroke Study, which compared stroke patients in Nigeria and Germany, suggested that regional variations in the burden of stroke risk factor may account for regional differences in the proportions of stroke phenotypes.⁶ Indeed the GBD 2013 illustrated the existence of regional differences in distribution of stroke risk factors.⁷ This was corroborated by the INTERSTROKE study^8,9 which demonstrated regional differences in stroke type and risk factors but did not decipher if the regional variations in the contributions of risk factors were due to racial (including genetic) and/or geographical (environmental) differences.^8–10

The relative contribution of racial and geographic factors to stroke and its risk factors among people of African ancestry (regardless of their present geographical location) is still unknown.^11,12 A rare opportunity to unravel this is provided given that 71% of African Americans are of the Niger-Kordofanian ancestry from West Africa from where they migrated several centuries ago.^{13, 14} Therefore, as a first step to deciphering the relative contributions of racial (including genetic) and geographic (environmental) factors for stroke in present day indigenous West Africans and African Americans (most of who originated from West Africa), we characterized the stroke type and risk factor profile of strokes in these populations in contrast to European Americans.

Specifically, we compared characteristics and risk factors of strokes in Indigenous Africans (IA) in West Africa within the Stroke Investigative Research and Educational Network (SIREN), the largest study of stroke in Africa to date.^{4, 11} with strokes in African Americans (AA) and European Americans (EA) within the REasons for Geographic And Racial Differences in Stroke (REGARDS) study in the United States.¹² Our central hypothesis a priori was that the characteristics of stroke and vascular risk factors in stroke with strong racial underpinning would be similar among IA and AA, but different from that among EA. Vascular factors with dominant racial (probably genetic) underpinnings discovered may be generalizable to people of African ancestry and serve as rewarding targets for stroke prevention and other interventions in this population.

METHODS

The detailed protocols of the SIREN¹¹ and REGARDS^{12, 15} studies have been published elsewhere. SIREN is a case-control study while REGARDS is a population-based cohort study. A brief summary of the protocols is presented in Supplemental Information 1. This is a comparative analysis of stroke subjects in both studies.

Data Harmonization and Risk Factor Definitions

For the purpose of this comparison and because those aged 45–54 were not initially recruited in the REGARDS study, we included only persons aged ≥ 55 years in both studies.

For both studies, risk factor definitions were standardized as follows:

• Hypertension was defined as sustained systolic BP≥140mmHg or diastolic BP≥90mmHg, history of hypertension (SIREN only), or taking antihypertensive medications before stroke.^8,9

• Diabetes mellitus was defined based on history of diabetes mellitus, use of medications for diabetes mellitus, fasting plasma glucose levels ≥ 126mg/dL (or ≥ 200 mg/dL if failing to fast) and/or HBA1c > 6.5%.

• Dyslipidemia was defined according to the recommendations of the US National Cholesterol Education Program as high fasting serum total cholesterol ≥200 mg/dl or HDL≤40 mg/dl¹⁶ or LDL≥ 130 or Triglyceride ≥ 150 mg/dL or history of use of statins before stroke.

• Smoking status was defined as never, former, or current smoker. In SIREN, current smokers were classified as individuals who smoked any tobacco in the past 12 months and included those who had quit within the past year. Former smokers were defined as those who had quit > a year earlier. In REGARDS, current smokers were defined by a positive response to “Do you smoke cigarettes now, even occasionally?” Past smokers were defined as non-current smokers who responded positively to “Have you smoked at least 100 cigarettes in your lifetime?”

• Alcohol intake was categorized into never or former drinker, or current drinker.^{8, 17}

• In SIREN, history of cardiac disease included myocardial infarction (MI), rheumatic valvular heart disease, prosthetic heart valve, atrial fibrillation or flutter based on self-reported history, clinical examination, review of baseline electrocardiography (ECG) and/or echocardiography.^{8, 17} In REGARDS, cardiac disease was defined by baseline ECG evidence of an MI, self-reported physician diagnosis of MI, or previous coronary artery bypass graft (CABG), angioplasty or coronary stenting.

• Obesity: Both studies assessed height (m) and weight (kg); body-mass index (kg/m²) was calculated and classified as underweight (<18.5), normal (18.5–24.9), overweight (25–29.9), or obese (30+)^{8, 17}

• Physical activity: In SIREN, individuals were classified as sedentary if they were not involved in any form of physical exercise (including walking, cycling, or gardening) or strenuous exercise (jogging, football, and vigorous swimming) before the stroke.^{8, 17} In REGARDS, individuals were classified as sedentary if they responded “zero” to “how many times per week do you exercise enough to sweat?”¹⁸ All participants were categorized into two groups as “no exercise” and “at least some exercise”.

Statistical Analysis

Descriptive statistics including means and standard deviation for continuous variables and proportions for categorical variables were computed. Differences in means and proportions were assessed using Bonferroni corrected 2-sample t tests and chi-square tests, respectively. All statistical tests were performed using a 2-sided level of α = 0. 0167 after adjustment for multiple comparisons^19,20 Data management and analyses were performed using MS Excel and IBM SPSS Statistics for Windows, Version 24.0 (IBM Corp., Armonk, NY).

RESULTS

Demographic characteristics of study participants

The present analysis of 1,928 stroke subjects included 811 IA recruited in the SIREN study, 452 AA and 665 EA participants in the REGARDS study who had a stroke event. Overall, 53% of stroke subjects were men, comprised of 55.5% IA, 41.2% AA and 58% EA with significant differences between the two African groups and between Africans and EAs (Table 1). The mean (±SD) age at onset of stroke was significantly different across the three groups being 68.0 ± 9.3, to 73.0 ± 8.3 and 76.0 ± 8.3 years among IA, AA and EA respectively, p<0.0001.

TABLE 1.

Comparison of characteristics of stroke and stroke risk factors in Indigenous Africans, African Americans and European Americans.

Characteristic	Indigenous Africans Group A	African Americans Group B	Prevalence Difference (95%CI) A vs B	P-value A vs B	Group A + B	European Americans Group C	Prevalence Difference (95% CI) (A+B) vs C	P-value (A+B) vs C	Prevalence Difference (95% CI) A vs C	P-value A vs C
Age, mean ± SD	68.0 ± 9.3	73.0 ± 8.3	5.0 (4.0–6.0)*	<0.0001	69.8 ± 9.3	76.0 ± 8.3	6.2 (5.0 – 7.4)*	<0.0001	8.0 (7.1 – 8.9)*	<0.0001
Age categories, n (%)
55–64 years	325/811 (40.1)	75/452 (16.6)	23.5 (18.7–28.3)	<0.0001	402/1263 (31.8)	73/665 (11.0)	20.7 (15.3 – 26.1)	<0.0001	29.1 (25.0–33.2)	<0.0001
65–74 years	275/811 (33.9)	193/452 (42.7)	8.8 (3.1–14.4)	0.0513	469/1263 (37.1)	226/665 (34.0)	3.1 (−3.6 – 9.7)	0.1114	0.8 (−4.8 – 4.9)	1.0000
>75years	211/811 (26.0)	184/452 (40.7)	14.7 (9.2–20.1)	0.0004	392/1263 (31.1)	366/665 (55.0)	23.8 (17–0.30)	<0.0001	29.0 (24.2–33.9)	<0.0001
Male gender, n (%)	450/811 (55.5)	186/452 (41.2)	14.3 (8.7–20.0)	<0.0001	636/1263 (50.3)	386/665 (58.0)	7.7 (0.9–14.5)	0.0006	2.6 (−2.5–7.6)	1.0000
Incident Stroke type, N (%)#
Ischemic	592/811 (73.0)	376/416 (90.4)	17.4 (13.2–21.6)	<0.0001	968/1227 (78.9)	561/629 (89.2)	10.3 (5.5–15.1)	<0.0001	16.2 (12.3–20.1)	<0.0001
Hemorrhagic	219/811 (27.0)	40/416 (9.6)	17.4 (13.2–21.6)	<0.0001	259/1227 (21.1)	68/629 (11.8)	10.3 (5.5–15.1)	0.0308	16.2 (12.3–20.1)	<0.0001
Vascular Risk Factors
Hypertension	710/765 (92.8)	372/451 (82.5)	10.3 (6.4–14.3)	<0.0001	1082/1216 (89.0)	424/661 (64.2)	24.8 (19.4–30.2)	<0.0001	28.7 (24.6–32.8)	<0.0001
Systolic BP, mean ± SD, mmHg	151.5 ± 30.8	135.6 ± 16.8	15.9 (13.2–18.6)*	<0.0001	148.8 ± 26.1	130.2 ± 17.0	15.4 (12.4–18.4)*	<0.0001	21.3 (18.8–23.8)*	<0.0001
Diastolic BP, mean ± SD, mmHg	93.1 ± 18.3	79.1 ± 10.2	14.0 (12.4–15.6)*	<0.0001	87.5 ± 15.6	75.6 ± 9.5	12.3 (10.5–14.1)*	<0.0001	17.5 (16.0–19.0)*	<0.0001
Dyslipidemia, n (%)	657/795 (82.6)	363/450 (80.7)	2.0 (−2.5–6.5)	1.0000	1020/1245 (81.9)	552/651 (84.8)	2.9 (−2.4–8.1)	0.3232	2.2 (−1.7–6.0)	0.7753
Total cholesterol, mean ± SD, mmol/L	5.0 ± 1.6	5.0 ± 1.2	0.0 (−0.1 – 0.2)*	1.0000	5.0 ± 1.4	4.9 ± 1.0	0.1 (−0.0 – 0.3)*	0.0685	0.1 (−0.0–0.3)*	0.2373
LDL-cholesterol, mean ± SD, mmol/L	3.1 ± 1.4	3.0 ± 1.0	0.1 (0.0–0.3)*	0.0785	3.1 ± 1.2	2.8 ± 0.9	0.3 (0.1 –0.4)*	<0.0001	0.3 (0.2–0.4)*	<0.0001
HDL-cholesterol, mean ± SD, mmol/L	1.3 ± 0.5	1.4 ± 0.5	0.1 (0.0–0.2)*	0.0005	1.3 ± 0.5	1.2 ± 0.4	0.1 (0.0–0.1)*	0.0005	0.0 (−0.0–0.1)*	0.4536
Triglycerides, mean ± SD, mmol/L	1.4 ± 0.8	1.3 ± 0.8	0.1 (−0.0–0.2)*	0.6309	1.4 ± 0.8	1.7 ± 1.1	0.4 (0.2 – 0.5)*	<0.0001	0.3 (0.2–0.4)*	<0.0001
Diabetes Mellitus, n (%)	304/794 (38.3)	159/432 (36.8)	1.5 (−4.2 – 7.1)	1.0000	463/1226 (37.8)	136/648 (21.0)	16.8 (10.3 – 23.3)	<0.0001	17.3 (12.7–21.9)	<0.0001
Cardiac disease, n (%)	96/767 (12.5)	111/444 (25.0)	12.5 (7.8–17.1)	<0.0001	207/1211 (17.1)	207/654 (31.7)	14.6 (8.7 – 20.4)	<0.0001	19.1 (14.9–23.4)	<0.0001
BMI, mean ± SD, kg/m2	26.4 ± 5.1	29.7 ± 5.9	3.3 (2.7–3.9)*	<0.0001	28.8 ± 5.6	27.9 ± 5.3	0.3 (−0.4–1.1)*	0.5662	1.5 (1.0–2.0)*	<0.0001
BMI Categories, n (%)
Underweight	9/339 (2.7)	4/449 (0.9)	1.8 (−0.2 – 3.7)	0.2044	13/788 (1.6)	9/661 (1.4)	0.3 (−1.8 – 2.4)	1.0000	1.3 (−0.6–3.2)	0.5691
Normal	142/339 (41.9)	89/449 (19.8)	22.1 (15.6–28.5)	<0.0001	231/788 (29.3)	182/661 (27.5)	1.8 (−5.5 – 9.0)	1.0000	14.4 (8.1–20.6)	<0.0001
Overweight	124/339 (36.6)	171/449 (38.1)	1.5 (−5.3–8.3)	1.0000	295/788 (37.4)	280/661 (42.4)	4.9 (−2.9 – 12.7)	0.1666	5.8 (−0.6–12.1)	0.2232
Obese	64/339 (18.9)	185/449 (41.2)	22.3 (16.1–28.5)	<0.0001	249/788 (31.6)	190/661 (28.7)	2.9 (−4.2 – 9.9)	0.6678	9.9 (4.4 – 15.2)	0.0012
Smoking, n (%)
Never smoked	672/759 (88.5)	196/449 (43.7)	44.9 (39.8–50.0)	<0.0001	868/1208 (71.9)	270/662 (40.8)	31.1 (24.7–37.4)	<0.0001	47.8 (43.4–52.1)	<0.0001
Current smoker	17/759 (2.2)	82/449 (18.3)	16.0 (12.3–19.7)	<0.0001	99/1208 (8.1)	95/662 (14.4)	6.2 (1.6 – 10.7)	0.0002	12.1 (9.2 – 15.0)	<0.0001
Past smoker	70/759 (9.3)	171/449 (38.0)	28.9 (23.9–33.8)	<0.0001	241/1208 (20.0)	297/662 (44.9)	24.9 (18.7 – 31.1)	<0.0001	35.6 (31.3–40.0)	<0.0001
Alcohol categories, n (%)
Never	471/763 (61.7)	169/452 (37.4)	24.3 (18.7–30.0)	<0.0001	640/1215 (52.6)	191/665 (28.7)	24.0 (17.3–30.6)	<0.0001	33.0 (28.1–37.9)	<0.0001
Current	127/763 (16.6)	163/452 (36.1)	19.4 (14.3–24.6)	<0.0001	290/1215 (23.9)	358/665 (53.8)	30.0 (23.6 –36.4)	<0.0001	37.2 (32.6–41.8)	<0.0001
Past	165/763 (21.7)	120/452 (26.6)	4.9 (−0.1 –9.9)	0.1527	285/1215 (23.5)	116/665 (17.4)	6.0 (0.2–11.8)	0.0045	4.2 (0.0–8.3)	0.1352
Exercise
None	63/744 (8.5)	165/438 (37.7)	29.2 (24.2–34.2)	<0.0001	228/1182 (19.3)	220/648 (34.0)	14.7 (8.5–20.8)	<0.0001	25.5 (21.3–29.6)	<0.0001
At least some	681/744 (91.5)	273/438 (62.3)	29.2 (24.2–34.2)	<0.0001	954/1182 (80.7)	428/648 (66.0)	14.7 (8.5–20.8)	<0.0001	25.5 (21.3–29.6)	<0.0001

Significance was assessed at α = 0.05/3 to adjust for multiple testing. Unadjusted p-values are available upon request.

^*Mean difference

^#Stroke type undetermined among 36 AA and 36 EA stroke subjects who were identified by death certificate.

Stroke types and subtypes

Stroke was hemorrhagic in 27.0% of IA compared with 9.6% among AA and 11.8% among EA (p<0.0001). Among those with ischemic stroke with single etiologic sub-type information, frequencies of cardio-embolic strokes decreased in order from EA (45.7%), AA (33.5%) and IA (9.7%). Conversely, small vessels strokes increased in order from EA (21.0%), AA (35.1%) and IA (47.1%). Large vessel strokes were more common in IA (43.1%) than EA (25.4%) and AA (22.2%).

Risk factors for Stroke

Hypertension was prevalent at frequencies of 92.8% and 82.5% among IA and AA compared with 64.2% among EA p<0.0001. Dyslipidemia was found in >80% of subjects with no significant differences among the groups. However, mean total cholesterol, LDL-cholesterol and HDL-cholesterol were significantly higher among the two black populations compared with EA (Table 1). Diabetes mellitus was present in 38.3% and 36.8% of IA and AA respectively compared with 21.0% among EA (p<0.0001.) Cardiac disorders were more prevalent among EA (31.7%) compared with AA(25.0%) and IA (12.5%) and observed to increase with increasing age of subjects regardless of ethnicity with age-adjusted estimates (Standard Error) of 29.5% (2.1), 24.2% (2.3) and 12.0% (1.2) respectively (see Supplemental Information 3).

BMI was significantly lower in IA compared to EA and AA while physical activity rates was significantly higher amongst IA (91.5%) compared to AA (62.3%) and EA (66.0%). Whereas only 2.2% of IA stroke subjects were current smokers, 18.3% of AA and 14.4% of EA stroke subjects were. Similarly, current alcohol consumption was lower among indigenous Africans, 16.6%, compared with 36.1% and 53.8% among AA and EA respectively.

Ischemic Stroke Risk Factor Profile

The prevalence of risk factors for ischemic strokes among the three groups. Diabetes mellitus was significantly more prevalent among IA (43.7%) and AA (38.1%) than EA (21.4%) with ischemic strokes, respectively.

Hemorrhagic Stroke Risk Factor Profile

Age at onset of hemorrhagic strokes ascended in the order of IA older than AA older than > EA. A male preponderance for hemorrhagic stroke was observed among EA (70.6%) and IA (60.7%) but not among AA (42.5%). Hypertension was present in 90% of hemorrhagic stroke subjects of African ancestry compared with 56% among EA. However, there were no notable differences in the frequencies of diabetes or dyslipidemia among the three groups for this stroke type.

DISCUSSION

This study is among the first to directly contrast the characteristics of the stroke type and risk factors between indigenous and diasporan Africans, and to compare these Africans to European Americans. We found significant racial and geographic differences in predisposition to stroke and its subtypes both between stroke subjects of African descent, and also between those of African descent compared with EA. Stroke subjects of African ancestry had significantly higher prevalence of hypertension and diabetes, comparable frequencies of dyslipidemia and lower prevalence of cardiac disorders in comparison with EA. Further racial variations were observed in alcohol consumption, cigarette smoking and physical inactivity, being higher among EA compared with people of African ancestry.

Stroke type

In spite of the dissimilarities in risk factor profiles between stroke subjects of African and European origins, stroke types appeared to be more strongly influenced by geographic location. The frequencies of ischemic and hemorrhagic strokes were similar among AA and EA compared with IA. However, subtle but significant differences emerged in ischemic stroke etiologic sub-types among the three groups. Small-vessel (lacunar) strokes whose pathophysiology is underpinned by hypertension and diabetes were observed at high frequencies among IA and AA compared with EA. In the South London Ethnicity and Stroke Study (SLESS), small vessel stroke was 2.6 times more common in black patients compared with whites after controlling for risk factors.²¹ Most but not all previous studies have found an increased predilection of small-vessel stroke among blacks^21–25 and epidemiological studies among black individuals in the US and UK have reported higher frequencies of sub-clinical markers of small vessel disease including small deep infarcts and white matter hyperintensities.^26–28 It is unclear whether there are ethnic differences in the impact of elevated blood pressure on stroke risk or that genetic factors account for these differences.

Cardio-embolic strokes were more frequent among EA than among African descendants probably due to older age of EA as reflected in the age-adjusted analysis conducted in the present study and the reported lower frequency of atrial fibrillation among blacks.²⁹ We observed a higher frequency of large-vessel disease amongst IA in SIREN compared with AA and EA in the REGARDS cohort. Other studies have found a higher frequency of intracranial large-vessel disease among blacks whereas extra-cranial large-vessel disease was more common among whites.^{21, 25}

Hemorrhagic strokes, were more than twice as frequent among IA than AA and EA stroke subjects reflecting the global trends in stroke type distribution.^7,8 We observed that the mean systolic blood pressure of IA with hemorrhagic stroke of 168mmHg was ≈35mmHg and 40mmHg higher than that among AA and EA respectively, clearly supporting the notion that low levels of awareness and control of blood pressure may be a key driver of this stroke type in LMICs. However, whereas 90% of hemorrhagic stroke subjects of African ancestry shared the commonality of hypertension as the dominant risk factor for this stroke variety, only 56% of EA had hypertension also suggesting that biologic factors may be at play here as well.

Stroke Risk Factors

Consistent with findings from the GBD and INTERSTROKE studies^7,8, hypertension was the most prevalent vascular risk factor identified among stroke subjects, lending itself as a prime target for public health interventions particularly among subjects of African descent. Achieving and sustaining blood pressure (BP) control is a global challenge, particularly in LMICs with substantial regional differences in levels of awareness and control of this most potent vascular risk factor.³⁰ Again we found a substantially higher prevalence of diabetes among stroke subjects of African descent which agrees with data from the US where these two group comparisons (AA vs EA) have been performed.^{21, 31–33} The higher rate of physical activity in IA may account for their lower BMI compared with AA and EA.³⁴ Rates of use of alcohol and cigarette smoking were significantly lower in IA compared to AA or EA suggesting an environmental effect.

A few limitations in our study are worth noting. The current analysis was restricted to stroke subjects ≥55 years because REGARDS initially recruited subjects ≥55 years (expanding to the inclusion of those 45–54 approximately a year into recruitment). It is known that strokes among blacks (particularly IA) tend to occur at younger ages hence the risk factor profile explored in the present study may not be generalizable to subjects <55 years. Because of differences in study design, as a case/control study the assessment of risk factors was performed post-stroke in SIREN, but was also based on reported pre-stroke conditions; while as a prospective study the risk factor assessment was performed solely pre-stroke in REGARDS. So, for example, part of the higher blood pressure levels in SIREN may be attributable to post-stroke increases in blood pressure (compared to the pre-stroke blood pressure levels in REGARDS). In addition, data collection in REGARDS is protocol-driven where each of the risk factors were systematically assessed, while data in SIREN were clinically-driven with greater variation in the approach. Strokes were defined in REGARDS using the World Health Organization (WHO) criteria, while in SIREN strokes were defined using clinical criteria. As a longitudinal study, there could be changes in the risk factor status of participants between the time of assessment and the stroke event (averaging approximately 4years, with a maximum of 11 years). Nevertheless, differences occurring consistently both in IA vs EA and AA vs EA can be attributed to race and not study design or timing of assessment since the timing of assessment and study design are identical for AA and EA.

Conclusions and Implications

Race appears to play a major role in predisposition to vascular risk factors for stroke among subjects of African descent, while geographical location potentially influences stroke type occurrence. It is possible that the genetic ensemble of the two racial groups plays a greater role in predisposition to vascular risk factors for stroke but ultimately environmental factors modulate the expression of end-organ disease.

This finding needs to be explored further with genomic and epidemiological tools to unravel the precise genomic variants that predispose Africans to these unique vascular risk factors as well as quantify the environmental factors that modulate risk factor effect. Meanwhile, vascular risk factors to which people of African descent are predisposed should be targeted to control the burden of stroke in this population.