Cardiovascular Disease Risk Factors in Ghana during the Rural-to-Urban Transition: A Cross-Sectional Study

Abstract

Populations in sub-Saharan Africa are shifting from rural to increasingly urban. Although the burden of cardiovascular disease is expected to increase with this changing landscape, few large studies have assessed a wide range of risk factors in urban and rural populations, particularly in West Africa. We conducted a cross-sectional, population-based survey of 3317 participants from Ghana (≥18 years old), of whom 2265 (57% female) were from a mid-sized city (Sunyani, population ~250,000) and 1052 (55% female) were from surrounding villages (populations <5000). We measured canonical cardiovascular disease risk factors (BMI, blood pressure, fasting glucose, lipids) and fibrinolytic markers (PAI-1 and t-PA), and assessed how their distributions and related clinical outcomes (including obesity, hypertension and diabetes) varied with urban residence and sex. Urban residence was strongly associated with obesity (OR: 7.8, 95% CI: 5.3–11.3), diabetes (OR 3.6, 95% CI: 2.3–5.7), and hypertension (OR 3.2, 95% CI: 2.6–4.0). Among the quantitative measures, most affected were total cholesterol (+0.81 standard deviations, 95% CI 0.73–0.88), LDL cholesterol (+0.89, 95% CI: 0.79–0.99), and t-PA (+0.56, 95% CI: 0.48–0.63). Triglycerides and HDL cholesterol profiles were similarly poor in both urban and rural environments, but significantly worse among rural participants after BMI-adjustment. For most of the risk factors, the strength of the association with urban residence did not vary with sex. Obesity was a major exception, with urban women at particularly high risk (26% age-standardized prevalence) compared to urban men (7%). Overall, urban residents had substantially worse cardiovascular risk profiles, with some risk factors at levels typically seen in the developed world.

Migration and Cardiovascular Disease Risk Among Ghanaian Populations in Europe:

“…This corroborate findings from previous studies that looked at differences in CVD risk between residents in rural and urbanized cities in their respective countries or overseas. 28,29 Contributory risk factors to increased CVD risk included BP levels, diabetes mellitus, and smoking, which were higher among the male migrant populations. This is consistent with previous studies, which showed an increase in CVD risk in migrant populations compared with their counterparts in their countries of origin.…”

Socio-demographic and behavioural determinants of body mass index among an adult population in rural Northern Ghana: the AWI-Gen study

“…Major socio-demographic factors associated with adult nutritional status, measured using BMI as a proxy, include age, gender and socio-economic status [15–17]. Reported lifestyle factors include alcohol consumption, smoking [18,19] and physical inactivity [20].…”

“…The age group selected for this study were 40–60 years old as the prevalence of obesity and associated cardiometabolic diseases rises during this period [15–17]. The current study will act as a baseline time point for a longitudinal analysis of such diseases in rural Ghana.…”

Prevalence and Determinants of Adult Obesity in a Low-Income Population of Western Africa: Results from a Nationwide Cross-Sectional Survey

“…Indeed, Higher prevalence of overweight (27.2% vs 16.7%) and obesity (20.6% vs 8.0%) were estimated for urban than rural dwellers in a recent meta-analysis in Ghana [31]. In the same region, urban residence was strongly associated with obesity with an odd ratio of 7.8 (95% CI: 5.3 ± 11.3) [17].Many reasons may explain the discrepancy in the prevalence of obesity among urban and semiurban populations in Western Africa. First, physical inactivity, a high-calorie diet and low consumption of vegetables and fruits are common among urban populations in developing countries.…”

“…Some were conducted in selected outpatient cardiology departments, whereas others were restricted to urban or semi-urban settings only [10][11][12][13][14][15]. Few studies have focused on obesity in the general population, including people living in urban and semi-urban regions [16,17]. Epidemiological data could provide important information for optimizing prevention programs in these populations.…”