Sugar-sweetened beverage intake and relative weight gain among South African adults living in resource-poor communities: longitudinal data from the STOP-SA study.

OBJECTIVES: This study examines the prospective association between sugar-sweetened beverages (SSB) consumption and change in body weight over a 4-5-year period in a socio-economically disadvantaged South African population. METHODS: This is a longitudinal study involving 800 adults (212 men, 588 women); 247 from the original METS (Modelling the Epidemiological Transition Study) cohort (N = 504) and 553 of the original 949 members of the PURE (Prospective Urban and Rural Epidemiology) Study. Both cohorts were drawn from low-income, socio-economically disadvantaged communities. Mean follow-up duration and age were 4.5 (SD 0.45) and 50.0 (SD 11.8) years, respectively. Harmonised measurements included body mass index, self-reported moderate-to-vigorous physical activity, and intake of meat, snacks and 'take-aways', fruits and vegetables and SSB (in servings/week). Multivariate logistic regression models were developed to determine the extent to which SSB consumption predicted relative weight gain, after controlling for potential confounders and known predictors. RESULTS: Nearly a third (29%) of participants had a relative weight change ≥5.0%; higher in the non-obese compared to the obese group (32% vs. 25%; p = 0.026). The average SSB consumption was 9.9 servings/week and was higher in the food insecure compared to the food secure group (11.5 vs. 9.0 servings/week; p = 0.006); but there were no differences between women and men (10.3 vs. 9.1 servings/week; p = 0.054). Mean SSB consumption was higher in the group who gained ≥5% weight compared to those who did not (11.0 vs. 8.7; p = 0.004). After adjustment, SSB consumption of 10 or more servings/week was associated with a 50% greater odds of gaining at least 5% body weight (AOR: 1.50, 95% CI (1.05-2.18)). CONCLUSION: These results show that higher intake of SSB predicts weight gain in a sample of South Africans drawn from low-income settings. Comprehensive, population-wide interventions are needed to reduce SSB consumption in these settings.

Enhanced insulin sensitivity in successful, long-term weight loss maintainers compared with matched controls with no weight loss history.

BACKGROUND: Weight gain is associated with deterioration in metabolic health, whereas weight loss improves insulin sensitivity. This study assesses the impact of long-term, successfully maintained weight loss and weight-loss relapse on measures of insulin sensitivity and identifies factors that explain variability in insulin sensitivity. METHODS: Women (20-45 years) were recruited into four groups: reduced-overweight/obese (RED, n=15); body mass index (BMI)-matched controls (stable low-weight, n=19), BMI⩽27 kg m-2; relapsed-overweight/obese subjects (REL, n=11); and BMI-matched controls (obese stable weight, n=11), BMI⩾27 kg m-2. A 75 g oral glucose tolerance test determined fasting and 2 h plasma glucose and insulin. Homeostatic Model Assessment (HOMA-IR) and insulin sensitivity index (ISI(0,120)) assessed insulin sensitivity. Anthropometric measurements, fasting resting metabolic rate (RMR) and respiratory quotient (RQ) were measured. Questionnaires and dietary intake were recorded, and physical activity was measured using accelerometers. RESULTS: RED were more insulin sensitive, characterised by lower fasting (P=0.001) and 2 h insulin (P=0.003) levels compared with all other groups. There were no significant differences in dietary intake, sedentary, light and moderate activity, RMR or RQ in the RED compared with the other three groups. % Body weight (BW) lost (P<0.001), % BW regained (P<0.05), body fat %, light activity (P<0.05, only log HOMA), vigorous activity (P<0.05) and RQ (P<0.01) predicted 61.4% and 59.7% of variability in log HOMA and log ISI(0,120), respectively, in multiple linear regression models. CONCLUSION: This study showed sustained enhanced insulin sensitivity in successful weight loss maintainers compared with BMI-matched controls with no weight loss history. Weight-loss-relapsed individuals were indistinguishable from controls. Weight loss itself was the strongest predictor of improved insulin sensitivity, whereas weight regain significantly predicted reduced insulin sensitivity. Weight-loss maintenance programs are essential to retaining metabolic benefits acquired through weight loss. Being physically active, reducing sedentary behaviour and, in particular, including small amounts of vigorous physical activity significantly predicted improved insulin sensitivity.

Prediction of fat-free mass using bioelectrical impedance analysis in young adults from five populations of African origin.

BACKGROUND/OBJECTIVES: Bioelectrical impedance analysis (BIA) is used in population and clinical studies as a technique for estimating body composition. Because of significant under-representation in existing literature, we sought to develop and validate predictive equation(s) for BIA for studies in populations of African origin. SUBJECTS/METHODS: Among five cohorts of the Modeling the Epidemiologic Transition Study, height, weight, waist circumference and body composition, using isotope dilution, were measured in 362 adults, ages 25-45 with mean body mass indexes ranging from 24 to 32. BIA measures of resistance and reactance were measured using tetrapolar placement of electrodes and the same model of analyzer across sites (BIA 101Q, RJL Systems). Multiple linear regression analysis was used to develop equations for predicting fat-free mass (FFM), as measured by isotope dilution; covariates included sex, age, waist, reactance and height(2)/resistance, along with dummy variables for each site. Developed equations were then tested in a validation sample; FFM predicted by previously published equations were tested in the total sample. RESULTS: A site-combined equation and site-specific equations were developed. The mean differences between FFM (reference) and FFM predicted by the study-derived equations were between 0.4 and 0.6 kg (that is, 1% difference between the actual and predicted FFM), and the measured and predicted values were highly correlated. The site-combined equation performed slightly better than the site-specific equations and the previously published equations. CONCLUSIONS: Relatively small differences exist between BIA equations to estimate FFM, whether study-derived or published equations, although the site-combined equation performed slightly better than others. The study-derived equations provide an important tool for research in these understudied populations.

The effect of backward locomotion training on the body composition and cardiorespiratory fitness of young women.

This study investigated the effect of a backward training program on the physical and fitness condition of young women. Twenty-six healthy female university students (aged 18 - 23 years) took part in three different baseline tests: body composition, a submaximal treadmill test, and a 20-m shuttle run test. Subjects were divided into a training group (n = 13) and a control group (n = 13). The training group completed a six-week backward run/walk training program. The control group was restricted to their daily activities similar to the four weeks prior to the onset of the baseline tests. The training group showed a significant (p = 0.01) decrease in O(2) consumption during both submaximal forward and backward exercise on the treadmill (32 % decrease during backward and 30 % decrease during forward exercise). A significant (p = 0.01) decrease in percentage body fat (2.4 %), a 19.7 % decrease in the sum of skinfolds (p = 0.001) and significantly (p = 0.013) improved predicted VO(2max) values from the forward 20-m shuttle run test (5.2 %) were also found in the case of the training group. The findings suggest that backward walk/run training improves cardiorespiratory fitness for both forward and backward exercise and causes significant changes in body composition in young women.