Results of the FFQ (Table
) indicated that in the preceding 7
days 93% of participants had consumed sugar, 92% had whole milk, 81% had beef, 82% had kale, 80% had bananas, 77% had white rice, 76% had cabbage; 70% had sifted ugali (maize meal), 64% had dried beans, 63% had sweetened soft drinks, 61% had eggs, 57% had maize, 45% had mandazi (fried balls of bread dough). For nearly all items with exception of maize, milk, and groundnuts there were significant differences between the SE groups.
Table 1 Percent women consuming different foods in the preceding 7days by socio-economic status
presents data on weight status by selected socio-demographic characteristics. With the exception of education level and occupation there is an increase in mean BMI,% BF and WC with SE characteristics. Higher age, higher SE group, increased parity, greater number of rooms in the house, and increased expenditure showed greater mean BMI,%BF and WC at highly significant levels (p <0.001). Divorced and widowed women also have greater mean BMI and WC values.
The largest percentage women with high physical activity levels (PALs) are found in the lowest three SE groups (p <0.001) (Table
). These three groups also have the lowest levels of sedentary time (p <0.0001). There is a significant increase in mean BMI (p <0.001),% BF (p <0.01) and WC (p <0.05) as PAL levels decrease with the highest mean BMI,%BF and WC found at the lowest level of PAL (Table
). There is a similar trend with increasing sedentary time which is only significant for BMI; with the highest mean BMI having the highest level of sedentary time (p <0.05).
Percentage time spent on physical activity by the Kenyan women according to socio-economic group
Mean body mass index, percent body fat and waist circumference of women by physical activity levels
shows that the upper two SE groups have 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 have significantly higher mean fibre (p <0.001) and carbohydrate (p <0.05) intakes. This was due to a significantly more frequent consumption of beef, chicken, processed meats and eggs by the highest two SE groups; while the lowest two groups consumed significantly more dry beans and maize meal (not shown). Both BMI (p <0.05) and% BF (p <01) are significantly greater when protein intake is higher than 100% of the DRI (Table
). This is also the case for mean fat intake. A fat intake greater than 100% of the DRI has a significantly greater mean BMI (p <0.05) than a fat intake less than 100% of the DRI.
Comparison of energy and macronutrient intakes as a percentage of Dietary Reference Intakes of women in different socioeconomic groups
Mean body mass index, percent body fat and waist circumference of women by energy and macronutrient levels
Most of the variance in BMI was explained by age, total physical activity, percentage DRI of fat consumed, parity and socio-economic group, in that order, together accounting for 18.0% of the variance in BMI (Table
). The most significant predictors of overweight and obesity by fat percentage were age and the number of items/assets in the women’s households, both of which explained 17.8% of the variation in the body fat percentage of the women. With regard to WC, age, parity and the number of rooms in the houses where the women resided, were the most significant predictors of abdominal fat deposition. These three variables together accounted for 20.6% of the variation in the WC measurements. Significant variables are shown in Table
. 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.
Multiple linear regression showing the effects of selected variables on body mass index, percent body fat and waist circumference of women using the stepwise method