Deriving an optimal threshold of waist circumference for detecting cardiometabolic risk in sub-Saharan Africa.

BACKGROUND: Waist circumference (WC) thresholds derived from western populations continue to be used in sub-Saharan Africa (SSA) despite increasing evidence of ethnic variation in the association between adiposity and cardiometabolic disease and availability of data from African populations. We aimed to derive a SSA-specific optimal WC cut-point for identifying individuals at increased cardiometabolic risk. METHODS: We used individual level cross-sectional data on 24 181 participants aged ⩾15 years from 17 studies conducted between 1990 and 2014 in eight countries in SSA. Receiver operating characteristic curves were used to derive optimal WC cut-points for detecting the presence of at least two components of metabolic syndrome (MS), excluding WC. RESULTS: The optimal WC cut-point was 81.2 cm (95% CI 78.5-83.8 cm) and 81.0 cm (95% CI 79.2-82.8 cm) for men and women, respectively, with comparable accuracy in men and women. Sensitivity was higher in women (64%, 95% CI 63-65) than in men (53%, 95% CI 51-55), and increased with the prevalence of obesity. Having WC above the derived cut-point was associated with a twofold probability of having at least two components of MS (age-adjusted odds ratio 2.6, 95% CI 2.4-2.9, for men and 2.2, 95% CI 2.0-2.3, for women). CONCLUSION: The optimal WC cut-point for identifying men at increased cardiometabolic risk is lower (⩾81.2 cm) than current guidelines (⩾94.0 cm) recommend, and similar to that in women in SSA. Prospective studies are needed to confirm these cut-points based on cardiometabolic outcomes.International Journal of Obesity advance online publication, 31 October 2017; doi:10.1038/ijo.2017.240.

Ketosis-prone atypical diabetes in Cameroonian people with hyperglycaemic crisis: frequency, clinical and metabolic phenotypes.

AIM: It is unclear whether ketosis-prone diabetes is a specific type or a subtype of Type 2 diabetes. We aimed to describe the clinical and metabolic features of ketosis-prone diabetes in a sub-Saharan population. METHODS: We consecutively enrolled and characterized 173 people with non-autoimmune diabetes admitted for hyperglycaemic crisis at the Yaoundé Central Hospital, Cameroon. Blood samples were collected for fasting glucose, HbA1c , lipid profile and C-peptide assays with insulin resistance and secretion estimation by homeostasis model assessment. People were classified as having Type 2 diabetes (n = 124) or ketosis-prone diabetes (n = 49). Ketosis-prone diabetes was sub-classified as new-onset ketotic phase (n = 34) or non-ketotic phase (n = 15). RESULTS: Ketosis-prone diabetes was found in 28.3% of the hyperglycaemic crises. Age at diabetes diagnosis was comparable in Type 2 and ketosis-prone diabetes [48 ± 14 vs 47 ± 11 years; P = 0.13] with a similar sex distribution. Overall BMI was 27.7 ± 13.4 kg/m2 and was ≥ 25 kg/m2 in 55.8% of those taking part, however, 73.5% of those with ketosis-prone diabetes reported weight loss of > 5% at diagnosis. Blood pressure and lipid profile were comparable in both types. Ketosis-prone diabetes in the ketotic phase was characterized by lower insulin secretion and higher serum triglycerides compared with non-ketotic ketosis prone and Type 2 diabetes. Type 2 and ketosis prone diabetes in the non-ketotic phase were comparable in terms of lipid profile, blood pressure, waist-to-hip ratio, BMI and fat mass, insulin secretion and insulin resistance indices. CONCLUSIONS: Ketosis-prone diabetes is likely to be a subtype of Type 2 diabetes with the potential to develop acute insulinopenic episodes.

Community-based peer support significantly improves metabolic control in people with Type 2 diabetes in Yaoundé, Cameroon.

AIMS: To examine the effectiveness of a community-based multilevel peer support intervention in addition to usual diabetes care on improving glycaemic levels, blood pressure and lipids in patients with Type 2 diabetes in Yaoundé, Cameroon. METHODS: A total of 96 subjects with poorly controlled Type 2 diabetes (intervention group) and 96 age- and sex-matched controls were recruited and followed up over 6 months. The intervention subjects underwent a peer support intervention through peer-led group meetings, personal encounters and telephone calls. Both intervention subjects and controls continued their usual clinical care. HbA1c , blood pressure, blood lipids and self-care behaviours were measured at 0 and 6 months. RESULTS: There was significant reduction in HbA1c in the intervention group [-33 mmol/mol (-3.0%)] compared with controls [-14 mmol/mol (-1.3%)]; P < 0.001. Peer support also led to significant reductions in fasting blood sugar (-0.83 g/l P < 0.001), cholesterol (-0.54 g/l P < 0.001), HDL (-0.09 g/l, P < 0.001), BMI (-2.71 kg/m² P < 0.001) and diastolic pressure (-6.77 mmHg, P < 0.001) over the 6-month period. Also, diabetes self-care behaviours in the intervention group improved significantly over the 6 months of peer support. CONCLUSION: Community-based peer support, in addition to usual care, significantly improved metabolic control in patients with uncontrolled Type 2 diabetes in Yaoundé, Cameroon. This could provide a model for optimizing diabetes care and control in other settings with limited healthcare and financial resources.

The association of intensity and overall level of physical activity energy expenditure with a marker of insulin resistance.

AIMS/HYPOTHESIS: Physical activity is important in preventing insulin resistance, but it is unclear which dimension of activity confers this benefit. We examined the association of overall level and intensity of physical activity with fasting insulin level, a marker of insulin resistance. METHODS: This was a cross-sectional analysis of the Medical Research Council Ely population-based cohort study (2000--2002). Physical activity energy expenditure (PAEE) in kJ kg(-1) min(-1) was measured by heart rate monitoring with individual calibration over a period of 4 days. The percentage of time spent above 1.5, 1.75 and 2 times resting heart rate (RHR) represented all light-to-vigorous, moderate-to-vigorous and vigorous activity, respectively. RESULTS: Data from a total of 643 non-diabetic individuals (319 men, 324 women) aged 50 to 75 years were analysed. In multivariate linear regression analyses, adjusting for age, sex and body fat percentage, PAEE was significantly associated with fasting insulin (pmol/l) (beta = -0.875, p = 0.006). Time (% of total) spent above 1.75 x RHR and also time spent above 2 x RHR were both significantly associated with fasting insulin (beta = -0.0109, p = 0.007 and beta = -0.0365, p = 0.001 respectively), after adjusting for PAEE, age, sex and body fat percentage. Time spent above 1.5 x RHR was not significantly associated with fasting insulin in a similar model (beta = -0.0026, p = 0.137). CONCLUSIONS/INTERPRETATION: The association between PAEE and fasting insulin level, a marker of insulin resistance, may be attributable to the time spent in moderate-to-vigorous and vigorous activity, but not to time spent in light-intensity physical activity.