Initial breastfeeding protects against obesity in later life. However, a further review including large unpublished studies exploring the effect of confounding factors in more detail is needed.

OBJECTIVES: Exposure to passive smoke is a common and avoidable risk factor for wheeze and asthma in children. Substantial growth in the prospective cohort study evidence base provides an opportunity to generate new and more detailed estimates of the magnitude of the effect. A systematic review and meta-analysis was conducted to provide estimates of the prospective effect of smoking by parents or household members on the risk of wheeze and asthma at different stages of childhood. METHODS:We systematically searched Medline, Embase, and conference abstracts to identify cohort studies of the incidence of asthma or wheeze in relation to exposure to prenatal or postnatal maternal, paternal, or household smoking in subjects aged up to 18 years old. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were estimated by using random effects model. RESULTS:We identified 79 prospective studies. Exposure to pre-or postnatal passive smoke exposure was associated with a 30% to 70% increased risk of incident wheezing (strongest effect from postnatal maternal smoking on wheeze in children aged #2 years, OR = 1.70, 95% CI = 1.24-2.35, 4 studies) and a 21% to 85% increase in incident asthma (strongest effect from prenatal maternal smoking on asthma in children aged #2 years, OR = 1.85, 95% CI = 1.35-2.53, 5 studies).CONCLUSIONS: Building upon previous findings, exposure to passive smoking increases the incidence of wheeze and asthma in children and young people by at least 20%. Preventing parental smoking is crucially important to the prevention of asthma. Pediatrics 2012;129:735-744 AUTHORS:

The aim of this review was to quantify the global variation in childhood myopia prevalence over time taking account of demographic and study design factors. A systematic review identified population-based surveys with estimates of childhood myopia prevalence published by February 2015. Multilevel binomial logistic regression of log odds of myopia was used to examine the association with age, gender, urban versus rural setting and survey year, among populations of different ethnic origins, adjusting for study design factors. 143 published articles (42 countries, 374 349 subjects aged 1–18 years, 74 847 myopia cases) were included. Increase in myopia prevalence with age varied by ethnicity. East Asians showed the highest prevalence, reaching 69% (95% credible intervals (CrI) 61% to 77%) at 15 years of age (86% among Singaporean-Chinese). Blacks in Africa had the lowest prevalence; 5.5% at 15 years (95% CrI 3% to 9%). Time trends in myopia prevalence over the last decade were small in whites, increased by 23% in East Asians, with a weaker increase among South Asians. Children from urban environments have 2.6 times the odds of myopia compared with those from rural environments. In whites and East Asians sex differences emerge at about 9 years of age; by late adolescence girls are twice as likely as boys to be myopic. Marked ethnic differences in age-specific prevalence of myopia exist. Rapid increases in myopia prevalence over time, particularly in East Asians, combined with a universally higher risk of myopia in urban settings, suggest that environmental factors play an important role in myopia development, which may offer scope for prevention.

ObjectiveWe describe in detail the burden of infections in adults with diabetes mellitus (DM) within a large national population cohort. We also compare infection rates between Type 1 (T1DM) and Type 2 (T2DM) patients. Research Design and MethodsA retrospective cohort study compared 102,493 English primary care patients aged 40-89 years with a DM diagnosis by 2008 (n=5,863 T1DM, n=96,630 T2DM) to 203,518 age-sex-practice matched controls without DM. Infection rates during 2008-15, compiled from primary care and linked hospital and mortality records, were compared across 19 individual infection categories.These were further summarised as any requiring a prescription, hospitalisation, or as cause of death. Poisson regression was used to estimate incidence rate ratios (IRRs) between: (i) people with diabetes and controls; (ii) T1DM and T2DM adjusted for age, sex, smoking, BMI and deprivation. ResultsCompared to controls without diabetes, DM patients had higher rates for all infections, with the highest IRRs seen for bone and joint infections, sepsis and cellulitis. IRRs for infectionrelated hospitalisations were 3.71 (95%CI 3.27-4.21) for T1DM and 1.88 (95%CI 1.83-1.92) for T2DM. A direct comparison of types confirmed higher adjusted risks for T1DM vs. T2DM(death from infection IRR = 2.19, 95%CI 1.75-2.74). We estimate 6% of infection-related hospitalisations and 12% of infection-related deaths were attributable to DM. Conclusions 3People with diabetes, particularly T1DM, are at increased risk of serious infection representing an important population burden. Strategies that reduce the risk of developing severe infections and poor treatment outcomes are under-researched and should be explored. Words: 2494 Diabetes mellitus (DM) is one of the leading causes of morbidity and mortality across the globe and the burden of disease is projected to increase from 415 to 642 million adults between 2015 and 2040.(1) The association between diabetes (DM) and infection is well known clinically,(2;3), and has been linked to a number of causal pathways including impaired immune responses within the hyperglycaemic environment(4), as well as potentially other abnormalities associated with diabetes such as neuropathy and altered lipid metabolism. It has been described in other studies and populations,(5-17) however not all have consistently controlled for confounding factors such as smoking, which are more common in people with diabetes and associated with infection.(18) Initially, studies mainly considered predominately common infections,(6; 8; 12) with few able to include important but rare infections,(7) such as endocarditis, or considered the whole range of infection outcomes from health service use, (17) to hospitalisation(16) and mortality.(9) Also, few studies have included large numbers of older people, for whom infections may be frequent and more serious.(5) Larger recent studies, primarily from higher income countries using national datasets have overcome some of these limitations,(7-13) but do not always separate...