ABSTRACT
BACKGROUND: The epidemic rise of diabetes carries major negative public health and economic consequences particularly for low and middle-income countries. The highest predicted percentage growth in diabetes is in the sub-Saharan Africa (SSA) region where to date there has been no data on the incidence of diabetic retinopathy from population-based cohort studies and minimal data on incident diabetes. The primary aims of this study were to estimate the cumulative six-year incidence of Diabetes Mellitus (DM) and DR (Diabetic Retinopathy), respectively, among people aged ≥50 years in Kenya. METHODS: Random cluster sampling with probability proportionate to size were used to select a representative cross-sectional sample of adults aged ≥50 years in 2007-8 in Nakuru District, Kenya. A six-year follow-up was undertaken in 2013-14. On both occasions a comprehensive ophthalmic examination was performed including LogMAR visual acuity, digital retinal photography and independent grading of images. Data were collected on general health and risk factors. The primary outcomes were the incidence of diabetes mellitus and the incidence of diabetic retinopathy, which were calculated by dividing the number of events identified at 6-year follow-up by the number of people at risk at the beginning of follow-up. Age-adjusted risk ratios of the outcomes (DM and DR respectively) were estimated for each covariate using a Poisson regression model with robust error variance to allow for the clustered design and including inverse-probability weighting. RESULTS: At baseline, 4414 participants aged ≥50 years underwent complete examination. Of the 4104 non-diabetic participants, 2059 were followed-up at six-years (50 · 2%). The cumulative incidence of DM was estimated at 61 · 0 per 1000 (95% CI: 50 · 3-73 · 7) in people aged ≥50 years. The cumulative incidence of DR in the sample population was estimated at 15 · 8 per 1000 (95% CI: 9 · 5-26 · 3) among those without DM at baseline, and 224 · 7 per 1000 (116.9-388.2) among participants with known DM at baseline. A multivariable risk factor analysis demonstrated increasing age and higher body mass index to be associated with incident DM. DR incidence was strongly associated with increasing age, and with higher BMI, urban dwelling and higher socioeconomic status. CONCLUSIONS: Diabetes Mellitus is a growing public health concern with a major complication of diabetic retinopathy. In a population of 1 · 6 million, of whom 150,000 are ≥50 years, we estimated that 1650 people aged ≥50 develop DM per year, and 450 develop DR. Strengthening of health systems is necessary to reduce incident diabetes and its complications in this and similar settings.
Subject(s)
Diabetes Mellitus/diagnosis , Diabetes Mellitus/epidemiology , Diabetic Retinopathy/diagnosis , Diabetic Retinopathy/epidemiology , Population Surveillance , Cohort Studies , Cross-Sectional Studies , Female , Follow-Up Studies , Humans , Incidence , Kenya/epidemiology , Male , Middle Aged , Population Surveillance/methods , Random AllocationABSTRACT
BACKGROUND/OBJECTIVES: To develop age- and sex-specific centile reference curves for fat-free mass (FFM) and fat mass (FM) adjusted for height in an adult Kenyan population and to investigate the association between FM, FFM and blood pressure (BP). SUBJECTS/METHODS: Measures of body composition from bioimpedance analyses and BP were collected in 1995 participants aged ≥50 years in Nakuru County, Kenya. Reference curves were produced using the LMS method. Multivariable linear regression models were used to test the cross-sectional association between body composition indexes and BP. RESULTS: The age- and sex-specific reference curves for body composition (FMI and FFMI) confirmed that FFMI is lower in both men and women with increasing age. FMI declines with age in women while among men the decline starts after 70 years. FFM was higher in men (47.4 ± 7.2 kg) than in women (38.8 ± 5.5 kg), while FM was lower in men (17.3 ± 8.1 kg) than in women (24.4 ± 10.2 kg). FMI, FFMI and BMI were all positively associated with systolic and diastolic BP, and after adjusting for body weight, FFMI remained positively associated with systolic BP and the FMI remained positively associated with diastolic BP. There was no evidence to suggest that FMI and FFMI were superior to measurement of BMI alone. CONCLUSIONS: These body composition reference curves provide normative data on body composition for older adults in Kenya. Further research should consider the prospective associations with health, including frailty-related outcomes.