Gestational diabetes mellitus in Cameroon: prevalence, risk factors and screening strategies

Copyright \ua9 2024 Sobngwi, Sobngwi-Tambekou, Katte, Echouffo-Tcheugui, Balti, Kengne, Fezeu, Ditah, Tchatchoua, Dehayem, Unwin, Rankin, Mbanya and Bell.Background: The burden of gestational diabetes (GDM) and the optimal screening strategies in African populations are yet to be determined. We assessed the prevalence of GDM and the performance of various screening tests in a Cameroonian population. Methods: We carried out a cross-sectional study involving the screening of 983 women at 24-28 weeks of pregnancy for GDM using serial tests, including fasting plasma (FPG), random blood glucose (RBG), a 1-hour 50g glucose challenge test (GCT), and standard 2-hour oral glucose tolerance test (OGTT). GDM was defined using the World Health Organization (WHO 1999), International Association of Diabetes and Pregnancy Special Group (IADPSG 2010), and National Institute for Health Care Excellence (NICE 2015) criteria. GDM correlates were assessed using logistic regressions, and c-statistics were used to assess the performance of screening strategies. Findings: GDM prevalence was 5\ub79%, 17\ub77%, and 11\ub70% using WHO, IADPSG, and NICE criteria, respectively. Previous stillbirth [odds ratio: 3\ub714, 95%CI: 1\ub727-7\ub776)] was the main correlate of GDM. The optimal cut-points to diagnose WHO-defined GDM were 5\ub79 mmol/L for RPG (c-statistic 0\ub762) and 7\ub71 mmol/L for 1-hour 50g GCT (c-statistic 0\ub776). The same cut-off value for RPG was applicable for IADPSG-diagnosed GDM while the threshold was 6\ub75 mmol/L (c-statistic 0\ub761) for NICE-diagnosed GDM. The optimal cut-off of 1-hour 50g GCT was similar for IADPSG and NICE-diagnosed GDM. WHO-defined GDM was always confirmed by another diagnosis strategy while IADPSG and GCT independently identified at least 66\ub79 and 41\ub70% of the cases. Interpretation: GDM is common among Cameroonian women. Effective detection of GDM in under-resourced settings may require simpler algorithms including the initial use of FPG, which could substantially increase screening yield

Fruit and vegetable intake and cardiovascular risk factors in people with newly diagnosed type 2 diabetes.

BACKGROUND/OBJECTIVES: The cardiovascular benefit of increasing fruit and vegetable (F&V) intake following diagnosis of diabetes remains unknown. We aimed to describe how quantity and variety of F&V intake, and plasma vitamin C, change after diagnosis of type 2 diabetes and examine whether these changes are associated with improvements in cardiovascular risk factors. SUBJECTS/METHODS: A total of 401 individuals with screen-detected diabetes from the ADDITION-Cambridge study were followed up over 5 years. F&V intake was assessed by food frequency questionnaire and plasma vitamin C at baseline, at 1 year and at 5 years. Linear mixed models were used to estimate associations of changes in quantity and variety of F&V intake, and plasma vitamin C, with cardiovascular risk factors and a clustered cardiometabolic risk score (CCMR), where a higher score indicates higher risk. RESULTS: F&V intake increased in year 1 but decreased by year 5, whereas variety remained unchanged. Plasma vitamin C increased at 1 year and at 5 years. Each s.d. increase (250g between baseline and 1 year and 270g between 1 and 5 years) in F&V intake was associated with lower waist circumference (-0.92 (95% CI: -1.57, -0.27) cm), HbA1c (-0.11 (-0.20, -0.03) %) and CCMR (-0.04 (-0.08, -0.01)) at 1 year and higher high-density lipoprotein (HDL)-cholesterol (0.04 (0.01, 0.06) mmol/l) at 5 years. Increased plasma vitamin C (per s.d., 22.5 μmol/l) was associated with higher HDL-cholesterol (0.04 (0.01, 0.06) mmol/l) and lower CCMR (-0.07 (-0.12, -0.03)) between 1 and 5 years. CONCLUSIONS: Increases in F&V quantity following diagnosis of diabetes are associated with lower cardiovascular risk factors. Health promotion interventions might highlight the importance of increasing, and maintaining increases in, F&V intake for improved cardiometabolic health in patients with diabetes.The ADDITION-Cambridge study was supported by the Wellcome Trust (grant G061895), the Medical Research Council (grant G0001164), the National Institute for Health Research (NIHR) Health Technology Assessment Programme (grant 08/116/300), National Health Service R&D support funding (including the Primary Care Research and Diabetes Research Networks). SJG received support from the Department of Health NIHR Programme Grant funding scheme (grant RP-PG-0606-1259). Bio-Rad provided equipment for HbA1c testing during the screening phase

Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications.

To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases

Behavioural Risk Factors in Mid-Life Associated with Successful Ageing, Disability, Dementia and Frailty in Later Life: A Rapid Systematic Review.

BACKGROUND: Smoking, alcohol consumption, poor diet and low levels of physical activity significantly contribute to the burden of illness in developed countries. Whilst the links between specific and multiple risk behaviours and individual chronic conditions are well documented, the impact of these behaviours in mid-life across a range of later life outcomes has yet to be comprehensively assessed. This review aimed to provide an overview of behavioural risk factors in mid-life that are associated with successful ageing and the primary prevention or delay of disability, dementia, frailty and non-communicable chronic conditions. METHODS: A literature search was conducted to identify cohort studies published in English since 2000 up to Dec 2014. Multivariate analyses and a minimum follow-up of five years were required for inclusion. Two reviewers screened titles, abstracts and papers independently. Studies were assessed for quality. Evidence was synthesised by mid-life behavioural risk for a range of late life outcomes. FINDINGS: This search located 10,338 individual references, of which 164 are included in this review. Follow-up data ranged from five years to 36 years. Outcomes include dementia, frailty, disability and cardiovascular disease. There is consistent evidence of beneficial associations between mid-life physical activity, healthy ageing and disease outcomes. Across all populations studied there is consistent evidence that mid-life smoking has a detrimental effect on health. Evidence specific to alcohol consumption was mixed. Limited, but supportive, evidence was available relating specifically to mid-life diet, leisure and social activities or health inequalities. CONCLUSIONS: There is consistent evidence of associations between mid-life behaviours and a range of late life outcomes. The promotion of physical activity, healthy diet and smoking cessation in all mid-life populations should be encouraged for successful ageing and the prevention of disability and chronic disease.This work was funded by the National Institute for Health and Care Excellence (NICE), invitation to tender reference DDER 42013, and supported by the National Institute for Health Research School for Public Health Research. The scope of the work was defined by NICE and the protocol was agreed with NICE prior to the start of work. The funders had no role in data analysis, preparation of the manuscript or decision to publish.This is the final version of the article. It first appeared from PLOS via http://dx.doi.org/10.1371/journal.pone.014440

Editorial - A United Nation high level meeting on chronic non-communicable diseases: Utility for Africa?

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