Prevention of type 2 diabetes (T2D) is a great challenge worldwide. The aim of this evidence synthesis was to summarize the available evidence in order to update the European Association for the Study of Diabetes (EASD) clinical practice guidelines for nutrition therapy. We conducted a systematic review and, where appropriate, meta-analyses of randomized controlled trials (RCTs) carried out in people with impaired glucose tolerance (IGT) (six studies) or dysmetabolism (one study) to answer the following questions: What is the evidence that T2D is preventable by lifestyle changes? What is the optimal diet (with a particular focus on diet quality) for prevention, and does the prevention of T2D result in a lower risk of late complications of T2D? The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach was applied to assess the certainty of the trial evidence. Altogether seven RCTs (N = 4090) fulfilled the eligibility criteria and were included in the meta-analysis. The diagnosis of incident diabetes was based on an oral glucose tolerance test (OGTT). The overall risk reduction of T2D by the lifestyle interventions was 0.53 (95% CI 0.41; 0.67). Most of the trials aimed to reduce weight, increase physical activity, and apply a diet relatively low in saturated fat and high in fiber. The PREDIMED trial that did not meet eligibility criteria for inclusion in the meta-analysis was used in the final assessment of diet quality. We conclude that T2D is preventable by changing lifestyle and the risk reduction is sustained for many years after the active intervention (high certainty of evidence). Healthy dietary changes based on the current recommendations and the Mediterranean dietary pattern can be recommended for the long-term prevention of diabetes. There is limited or insufficient data to show that prevention of T2D by lifestyle changes results in a lower risk of cardiovascular and microvascular complications.
1 January 2009 in The Pediatric Infectious Disease Journal
Knowledge of pathogens causing infections in young infants (up to 90 days of life) is essential for devising community-based management strategies. Most etiological data from developing countries are hospital-based and may have little relevance to communities in which most babies are born at home. We searched the literature for studies from developing countries reporting etiology of community-acquired infections (sepsis, pneumonia, meningitis) published since 1980. Hospital-based studies reporting early onset sepsis, sepsis among babies admitted from, or born at home were included. Of 63 studies, 13 focused on community-acquired infections, but limited data were available from home-born neonates. In the first week of life (3209 isolates), Klebsiella species (25%), Escherichia coli (15%), and Staphylococcus aureus (18%) were major pathogens. Group B streptococci (GBS) were relatively uncommon (7%), although regional differences existed. After the first week of life (835 isolates), S. aureus (14%), GBS (12%), Streptococcus pneumoniae (12%), and nontyphoidal Salmonella species (13%) were most frequent. S. pneumoniae (27%) was most common in the postneonatal period (among 141 isolates). Gram-negatives predominated (77%) among home-delivered babies (among 170 isolates). Limited information is available on etiology of serious bacterial infections in community settings. Hospital-based studies suggest that most infections in the first week of life are due to Gram-negative pathogens, and many may be environmentally rather than maternally-acquired, owing to unhygienic delivery practices. Such practices may also explain the predominance of Gram-negative infections among home-born infants, although data from home settings are limited. These findings have implications for developing prevention and management strategies in communities and hospitals.
5 April 2013 in International Journal of Epidemiology
Background At the APOE gene, encoding apolipoprotein E, genotypes of the ε2/ε3/ε4 alleles associated with higher LDL-cholesterol (LDL-C) levels are also associated with higher coronary risk. However, the association of APOE genotype with other cardiovascular biomarkers and risk of ischaemic stroke is less clear. We evaluated the association of APOE genotype with risk of ischaemic stroke and assessed whether the observed effect was consistent with the effects of APOE genotype on LDL-C or other lipids and biomarkers of cardiovascular risk. Methods We conducted a systematic review of published and unpublished studies reporting on APOE genotype and ischaemic stroke. We pooled 41 studies (with a total of 9027 cases and 61 730 controls) using a Bayesian meta-analysis to calculate the odds ratios (ORs) for ischaemic stroke with APOE genotype. To better evaluate potential mechanisms for any observed effect, we also conducted a pooled analysis of primary data using 16 studies (up to 60 883 individuals) of European ancestry. We evaluated the association of APOE genotype with lipids, other circulating biomarkers of cardiovascular risk and carotid intima-media thickness (C-IMT). Results The ORs for association of APOE genotypes with ischaemic stroke were: 1.09 (95% credible intervals (CrI): 0.84–1.43) for ε2/ε2; 0.85 (95% CrI: 0.78–0.92) for ε2/ε3; 1.05 (95% CrI: 0.89–1.24) for ε2/ε4; 1.05 (95% CrI: 0.99–1.12) for ε3/ε4; and 1.12 (95% CrI: 0.94–1.33) for ε4/ε4 using the ε3/ε3 genotype as the reference group. A regression analysis that investigated the effect of LDL-C (using APOE as the instrument) on ischaemic stroke showed a positive dose-response association with an OR of 1.33 (95% CrI: 1.17, 1.52) per 1 mmol/l increase in LDL-C. In the separate pooled analysis, APOE genotype was linearly and positively associated with levels of LDL-C (P-trend: 2 × 10−152), apolipoprotein B (P-trend: 8.7 × 10−06) and C-IMT (P-trend: 0.001), and negatively and linearly associated with apolipoprotein E (P-trend: 6 × 10−26) and HDL-C (P-trend: 1.6 × 10−12). Associations with lipoprotein(a), C-reactive protein and triglycerides were non-linear. Conclusions In people of European ancestry, APOE genotype showed a positive dose-response association with LDL-C, C-IMT and ischaemic stroke. However, the association of APOE ε2/ε2 genotype with ischaemic stroke requires further investigation. This cross-domain concordance supports a causal role of LDL-C on ischaemic stroke.
To determine the effect of oat β‑glucan (OBG) on acute glucose and insulin responses and identify significant effect modifiers we searched the MEDLINE, EMBASE, and Cochrane databases through October 27, 2020 for acute, crossover, controlled feeding trials investigating the effect of adding OBG (concentrate or oat-bran) to carbohydrate-containing test-meals compared to comparable or different carbohydrate-matched control-meals in humans regardless of health status. The primary outcome was glucose incremental area-under-the-curve (iAUC). Secondary outcomes were insulin iAUC, and glucose and insulin incremental peak-rise (iPeak). Two reviewers extracted the data and assessed risk-of-bias and certainty-of-evidence (GRADE). Data were pooled using generic inverse-variance with random-effects model and expressed as ratio-of-means with [95% CIs]. We included 103 trial comparisons (N = 538). OBG reduced glucose iAUC and iPeak by 23% (0.77 [0.74, 0.81]) and 28% (0.72 [0.64, 0.76]) and insulin by 22% (0.78 [0.72, 0.85]) and 24% (0.76 [0.65, 0.88]), respectively. Dose, molecular-weight, and comparator were significant effect modifiers of glucose iAUC and iPeak. Significant linear dose-response relationships were observed for all outcomes. OBG molecular-weight >300 kg/mol significantly reduced glucose iAUC and iPeak, whereas molecular-weight <300 kg/mol did not. Reductions in glucose iAUC (27 vs 20%, p = 0.03) and iPeak (39 vs 25%, p < 0.01) were significantly larger with different vs comparable control-meals. Outcomes were similar in participants with and without diabetes. All outcomes had high certainty-of-evidence. In conclusion, current evidence indicates that adding OBG to carbohydrate-containing meals reduces glycaemic and insulinaemic responses. However, the magnitude of glucose reduction depends on OBG dose, molecular-weight, and the comparator.