E. N. Kuria

Predictors of overweight and obesity in adult women in Nairobi Province, Kenya

BackgroundSince obesity in urban women is prevalent in Kenya the study aimed to determine predictors of overweight and obesity in urban Kenyan women.MethodsA cross-sectional study was undertaken in Nairobi Province. The province was purposively selected because it has the highest prevalence of overweight and obesity in Kenya.A total of 365 women aged 25–54 years old were randomly selected to participate in the study.ResultsHigher age, higher socio-economic (SE) group, increased parity, greater number of rooms in the house, and increased expenditure showed greater mean body mass index (BMI),% body fat and waist circumference (WC) at highly significant levels (p <0.001). Most of the variance in BMI was explained by age, total physical activity, percentage of fat consumed, parity and SE group in that order, together accounting for 18% of the variance in BMI. The results suggest that age was the most significant predictor of all the dependent variables appearing first in all the models, while parity was a significant predictor of BMI and WC. The upper two SE groups had significantly higher mean protein (p <0.05), cholesterol (p <0.05) and alcohol (p <0.001) intakes than the lower SE groups; while the lower SE groups had significantly higher mean fibre (p <0.001) and carbohydrate (p <0.05) intakes. A fat intake greater than 100% of the DRI dietary reference intake (DRI) had a significantly greater mean BMI (p <0.05) than a fat intake less than the DRI.ConclusionsThe predictors of overweight and obesity showed that urbanization and the nutrition transition were well established in the sample of women studied in the high SE groups. They exhibited a sedentary lifestyle and consumed a diet high in energy, protein, fat, cholesterol, and alcohol and lower in fibre and carbohydrate compared with those in the low SE groups.

Food consumption and nutritional status of people living with HIV/AIDS (PLWHA): a case of Thika and Bungoma Districts, Kenya

OBJECTIVE To establish the food consumption, dietary habits and nutritional status of people living with HIV/AIDS (PLWHA) and adults whose HIV status is not established. DESIGN Cross-sectional descriptive survey. SETTING Thika and Bungoma Districts, Kenya. SUBJECTS A random sample of 439 adults; 174 adults living with HIV/AIDS and 265 adults whose HIV/AIDS status was not established in Thika and Bungoma Districts. RESULTS Majority of PLWHA consume foods that are low in nutrients to build up the immune system and help maintain adequate weight, and there is little variety in the foods they consume. More adults who are HIV-positive are undernourished than those whose status is not established. Of the HIV-positive adults, those with a BMI of <or=18.5 kg/m2 were 23.6 % (Thika 20.0 % and Bungoma 25.7 %) while of the adults whose status is not established those with BMI <or= 18.5 kg/m2 were 13.9 % (Thika 9.3 % and Bungoma 16.7 %). CONCLUSIONS Adults who are HIV-positive are more likely to be undernourished than those whose status is not established, as there is a significant difference (P = 0.000) between the nutritional status (BMI) of PLWHA and those whose HIV/AIDS status is not established. PLWHA consume foods that are low in nutrients to promote their nutritional well-being and health.

Adolescent elite Kenyan runners are at risk for energy deficiency, menstrual dysfunction and disordered eating

Abstract Limited data are available on the female athlete triad (Triad) in athletes from minority groups. We explored subclinical and clinical Triad components amongst adolescent elite Kenyan athletes (n = 61) and non-athletes (n = 49). Participants completed demographic, health, sport and menstrual history questionnaires as well as a 5-day weighed dietary record and exercise log to calculate energy availability (EA). Ultrasound assessed calcaneus bone mineral density (BMD). Eating Disorder Inventory subscales and the Three-Factor Eating Questionnaire’s cognitive dietary restraint subscale measured disordered eating (DE). EA was lower in athletes than non-athletes (36.5 ± 4.5 vs. 39.5 ± 5.7 kcal ∙ kg FFM−1 ∙ d−1, P = 0.003). More athletes were identified with clinical low EA (17.9% vs. 2.2%, OR = 9.5, 95% CI 1.17–77, P = 0.021) and clinical menstrual dysfunction (32.7% vs. 18.3%, χ2 = 7.1, P = 0.02). Subclinical (75.4% vs. 71.4%) and clinical DE (4.9% vs. 10.2%, P = 0.56) as well as BMD were similar between athletes and non-athletes. More athletes had two Triad components than non-athletes (8.9% vs. 0%, OR = 0.6, 95% CI 0.5–6.9, P = 0.05). Kenyan adolescent participants presented with one or more subclinical and/or clinical Triad component. It is essential that athletes and their entourage be educated on their energy needs including health and performance consequences of an energy deficiency.