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Diabetes, Cardiovascular Risks, and Lipoproteins · Journal article
Frontiers in Epidemiology · August 6, 2026
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This cross-sectional survey of 425 women aged 20–49 in Kirinyaga County, Kenya reports a metabolic syndrome prevalence of 46.4% and high rates of obesity (68.87%), central obesity (79.3%), and low HDL cholesterol (68.6%). Logistic regression identifies increasing age, higher wealth, multiparity, and hormonal contraceptive use as associated with metabolic risk factors, but the observational design cannot establish causation and results are specific to this county.
Cross-sectional survey. Women aged 20–49 years residing in Kirinyaga County, Kenya; multi-stage sampling approach employed.. n = 425. Kirinyaga County, Kenya.
Metabolic syndrome prevalence was 46.4% (95% CI not reported) Obesity or overweight in 68.87%; central obesity by waist circumference 79.3% Low HDL cholesterol in 68.6%; elevated triglycerides in 17.2%; diabetes in 8.56%
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Clinicians should recognise the high burden of metabolic syndrome and metabolic risk factors in this Kenyan population, particularly among older and wealthier women. However, this cross-sectional study cannot guide intervention design or causality; prospective or intervention studies are needed to test whether addressing wealth-associated lifestyle behaviours reduces metabolic disease risk.
Single-centre cross-sectional survey with prevalence estimates and logistic regression associations, lacking a comparator group or randomisation; establishes local burden but cannot establish causation or guide intervention.
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Clinicians should recognise the high burden of metabolic syndrome and metabolic risk factors in this Kenyan population, particularly among older and wealthier women. However, this cross-sectional study cannot guide intervention design or causality; prospective or intervention studies are needed to test whether addressing wealth-associated lifestyle behaviours reduces metabolic disease risk.
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Introduction Globally, Noncommunicable diseases (NCDs) contribute to 75% of all deaths. The precursors to the development of NCDs include the metabolic syndrome (MetS) and key metabolic risk factors outlined by the World Health Organisation, including overweight/obesity, raised blood pressure, hyperglycemia, and hyperlipidemia. Women in Kirinyaga County in Kenya have the highest prevalence of overweight and obesity at 64.6%, and hypertension at 20%, as per the 2022 Kenyan Demographic Health survey; however, data on MetS, hyperglycemia, and hyperlipidemia in Kirinyaga is scarce. Therefore, this study aimed to determine the relationship between sociodemographic determinants and the prevalence of metabolic risk factors and the metabolic syndrome among women aged 20–49 years in Kirinyaga County, Kenya. Methods A cross-sectional study design was employed, and multi-stage sampling was used to select 425 women aged 20–49 years in Kirinyaga County, Kenya. Data were collected on sociodemographic determinants and anthropometric and biochemical measurements. Data analysis was conducted using STATA version 17, frequencies, proportions and binary logistic regression. A total of 425 women participated in the study. Results The prevalence of MetS was 46.4%; 68.87% were obese or overweight; central obesity, measured by waist circumference, was 79.3%, and by waist-hip ratio, 51.06%. Diabetes was at 8.56%, elevated blood pressure at 22.6%, elevated triglycerides at 17.2%, Low HDL-C at 68.6%, and elevated cholesterol at 7.5%. The primary determinants of metabolic health were wealth and age. Increasing age ( p 0.05) elevated the odds of having all risk factors for NCDs and metabolic syndrome, except low HDL cholesterol. Women in the highest wealth quintile had increased odds of obesity (AOR = 1.83, p = 0.036), elevated triglycerides (AOR = 2.22, p = 0.035), and metabolic syndrome (AOR = 1.79, p = 0.040). However, being a student reduced the odds of metabolic syndrome (AOR = 0.24, p = 0.047). Hormonal contraceptive use, on one hand, was associated with reductions in hypertension (AOR = 0.32, p 0.001), but was a significant risk factor for low HDL cholesterol (AOR = 2.08, p = 0.011). Conclusion The study reveals a high prevalence of both metabolic syndrome and metabolic risk factors linked to noncommunicable diseases, mainly driven by ageing, multi-parity, and economic affluence. Public health interventions need to focus on wealth-associated lifestyle behaviours.
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