Prevalence of left ventricular systolic dysfunction and heart failure with reduced ejection fraction in men and women with type 2 diabetes

Background: Type 2 diabetes mellitus (T2D) is associated with the development of left ventricular systolic dysfunction (LVSD) and heart failure with reduced ejection fraction (HFrEF). T2D patients with LVSD are at higher risk of mortality and morbidity than patients without LVSD, while progression of LVSD can be delayed or halted by the use of proven therapies. As estimates of the prevalence are scarce and vary considerably, the aim of this study was to retrieve summary estimates of the prevalence of LVSD/HFrEF in T2D and to see if there were any sex differences. Methods: A systematic search of Medline and Embase was performed to extract the prevalence of LVSD/HFrEF in T2D (17 studies, mean age 50.1 ± 6.3 to 71.5 ± 7.5), which were pooled using random-effects meta-analysis. Results: The pooled prevalence of LVSD was higher in hospital populations (13 studies, n = 5835, 18% [95% CI 17-19%]), than in the general population (4 studies, n = 1707, 2% [95% CI 2-3%]). Seven studies in total reported sex-stratified prevalence estimates (men: 7% [95% CI 5-8%] vs. women: 1.3% [95% CI 0.0.2.2%]). The prevalence of HFrEF was available in one general population study (5.8% [95% CI 3.7.6%], men: 6.8% vs. women: 3.0%). Conclusions: The summary prevalence of LVSD is higher among T2D patients from a hospital setting compared with from the general population, with a higher prevalence in men than in women in both settings. The prevalence of HFrEF among T2D in the population was only assessed in a single study and again was higher among men than women

Head Circumference of Infants Born to Mothers with Different Educational Levels; The Generation R Study

Objective: Head circumference (HC) reflect growth and development of the brain in early childhood. It is unknown whether socioeconomic differences in HC are present in early childhood. Therefore, we investigated the association between socioeconomic position (SEP) and HC in early childhood, and potential underlying factors. Methods: The study focused on Dutch children born between April 2002 and January 2006 who participated in The Generation R Study, a population-based prospective cohort study in Rotterdam, the Netherlands. Maternal educational level was used as indicator of SEP. HC measures were concentrated around 1, 3, 6 and 11 months. Associations and explanatory factors were investigated using linear regression analysis, adjusted for potential mediators. Results: The study included 3383 children. At 1, 3 and 6 months of age, children of mothers with a low education had a smaller HC than those with a high education (difference at 1 month: -0.42 SD; 95% CI: -0.54,-0.30; at 3 months: -0.27 SD; 95% CI -0.40,-0.15; and at 6 months: -0.13 SD; 95% CI -0.24,-0.02). Child's length and weight could only partially explain the smaller HC at 1 and 3 months of age. At 6 months, birth weight, gestational age and parental height explained the HC differences. At 11 months, no HC differences were found. Conclusion: Educational inequalities in HC in the first 6 months of life can be mainly explained by pregnancy-related factors, such as birth weight and gestational age. These findings further support public health policies to prevent negative birth outcomes in lower socioeconomic groups

Reducing Binge Drinking? The Effect of a Ban on Late-Night Off-Premise Alcohol Sales on Alcohol-Related Hospital Stays in Germany

Excessive alcohol consumption among young people is a major public health concern. On March 1, 2010, the German state of Baden-Württemberg banned the sale of alcoholic beverages between 10pm and 5am at off-premise outlets (e.g., gas stations, kiosks, supermarkets). We use rich monthly administrative data from a 70 percent random sample of all hospitalizations during the years 2007-2011 in Germany in order to evaluate the short-term impact of this policy on alcohol-related hospitalizations. Applying difference-in-differences methods, we find that the policy change reduces alcohol-related hospitalizations among adolescents and young adults by about seven percent. There is also evidence of a decrease in the number of hospitalizations due to violent assault as a result of the ban

行政だより

Research on social inequalities in sports participation and unstructured physical activity among young children is scarce. This study aimed to assess the associations of family socioeconomic position (SEP) and ethnic background with children's sports participation and outdoor play. Methods: We analyzed data from 4726 ethnically diverse 6-year-old children participating in the Generation R Study. Variables were assessed by parent-reported questionnaires when the child was 6 years old. Low level of outdoor play was defined as outdoor play <1 hour per day. Series of multiple logistic regression analyses were performed to assess associations of family SEP and ethnic background with children's sports participation and outdoor play. Results: Socioeconomic inequalities in children's sports participation were found when using maternal educational level (p<0.05), paternal educational level (p<0.05), maternal employment status (p<0.05), and household income (p<0.05) as family SEP indicator (less sports participation among low SEP children). Socioeconomic inequalities in children's outdoor play were found when using household income only (p<0.05) (more often outdoor play <1 hour per day among children from low income household). All ethnic minority children were significantly more likely to not to participate in sports and play outdoor <1 hour per day compared with native Dutch children. Adjustment for family SEP attenuated associations considerably, especially with respect to sports participation. Conclusion: Low SEP children and ethnic minority children are more likely not to participate in sports and more likely to display low levels of outdoor play compared with high SEP children and native Dutch children, respectively. In order to design effective interventions, further research, including qualitative studies, is needed to explore more in detail the pathways relating family SEP and ethnic background to children's sports participation and outdoor play

Association between maternal educational level and longitudinally measured head circumference growth^a.

<p>^aResults are based on linear mixed models and reflect the standard deviation scores of head circumference (based on 16958 measurements) growth in the first postnatal year in the offspring of mothers with low, mid-low, mid-high educational levels and high educational level. High education is reference group. *P for educational level *age ≤0.001.</p

Differences in child’s head circumference at 1, 3, 6 and 11 months of age between maternal educational levels^a.

*<p>p-value <0.05,</p>**<p>p-value <0.01,</p><p>SDS  =  standard-deviation score, BMI  =  body mass index.</p>a<p>Values are regression coefficients (95% confidence interval) and reflect the differences in head circumference (in standard deviation scores) in offspring of mothers with mid-high, mid-low and low educational level relative to children of women with high educational level. The values are derived from linear regression analyses performed on the data after multiple imputation of the covariates.</p>b<p>Model 1: adjusted for maternal age and parity.</p>c<p>Fully adjusted model: adjusted for parity, maternal age, child’s height and weight (in SDS) at measurement of HC, birth weight SDS, gestational age, paternal and maternal height, pre-pregnancy BMI and breastfeeding (yes/no).</p>d<p>Fully adjusted model: adjusted for parity, maternal age, birth weight SDS, gestational age, smoking during pregnancy, paternal and maternal height and pre-pregnancy BMI.</p

General characteristics of the study population (n = 3383)^a.

<p>BMI = body mass index, SDS = standard deviation scores.</p>a<p>Values are percentages or means (SD) for the total population and by level of maternal education.</p>b<p>P-values are calculated with the Chi-square test for categorical variables and ANOVA for continuous variables.</p>c<p>Data were missing for parity (2.4%), gestational age (0.1%), smoking during pregnancy (14.5%), alcohol use during pregnancy (14.1%), gestational diabetes (3.3%), maternal height (7.9%), pre-pregnancy BMI (20%), paternal height (17.0%), psychopathology (18.2%), financial difficulties (9.9%), pregnancy planned (5.2%),height SDS at 1 (30.9%), 3 (36.2%), 6 (17.0%) and 11(14.4%) months, weight at 1 (18.0%), 3 (25.9%), 6 (6.7%) and 11 (14.2%) months and breastfeeding (5.7%).</p

Head circumference SDS characteristics in the total study population and by level of maternal education (n = 3383).

<p>HC  =  head circumference, SDS  =  standard deviation score.</p>a<p>Values are calculated with ANOVA for continuous variables and reflect means (SD) per educational level.</p