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Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Obesity phenotypes in urban and rural Cameroonians: a cross-sectional study
Vivian N Mbanya1, Justin B Echouffo-Tcheugui2, Hussain Akhtar1
1Department of Community Medicine, Section of International Health, University of Oslo, Oslo, Norway.
Background:
Despite the increasing prevalence of diabetes and other health consequences of obesity, little is known on the metabolic profile across categories of body mass index (BMI) among African populations. We therefore assessed the prevalence and distribution of body size phenotypes among urban and rural Cameroonians.
Methods:
Adults (n = 1628; 41% rural dwellers) aged 24-74 years in 1994 provided data on BMI and metabolic health, defined on the basis of elevated levels of blood pressure (BP); triglycerides, fasting plasma glucose (FPG), and insulin resistance as assessed with homeostasis model assessment (HOMA). Cross-classification of BMI categories and metabolic status (healthy/unhealthy) created six groups. Metabolic measures include elevated blood pressure; elevated triglycerides (≥150 mg/dL or 1.69mmo/L), elevated fasting plasma glucose (≥100 mg/dl or 5.6 mmol/L or documented use of antidiabetic medications), and elevated homeostasis model assessment of insulin resistance value (HOMA-IR > 90(th) percentile).
Results:
A total of 25.2% of participants were overweight yet metabolically healthy (<1 abnormality) and 10.1% were obese yet metabolically healthy, whereas 1.4% were normal weight but metabolically abnormal (≥2 abnormalities). Proportion of rural dwellers with abnormal metabolic phenotype across normal-weight, overweight, obese categories were 2.9%, 0.8% and 0.3%, respectively; and 0 .3%, 2.2% and 2.6% among urban dwellers. Metabolically abnormal participants increased linearly across BMI categories (p < 0.001). BMI categories and metabolic status interacted to affect age, gender, BMI, FPG, triglycerides, and BP status distributions (all p < 0.04). Metabolic status and residence (rural vs. urban) interacted to influence the distribution across BMI categories of diastolic BP, BMI, waist circumference, fasting and 2-hour glucose, triglycerides, HOMA-IR, and prevalent diabetes (all p < 0.005), with differential occurrence of BMI categories and metabolic status among urban and rural participants.
Conclusions:
Metabolic healthy obesity and obesity with a favorable cardiometabolic profile are not uncommon among Cameroonians, including among rural dwellers; but the latter group tended to have a better profile.
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