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Background Maternal obesity is associated with adverse health consequences, including heart disease, hypertension, stroke, diabetes and premature death [1]. Obesity is also associated with reduced quality of life, social stigmatization, [...], To investigate the association between maternal pre-pregnancy obesity, race/ethnicity and prematurity. Retrospective cohort study of maternal deliveries at a single regional center from 2009 to 2010 time period (n = 11,711). Generalized linear models were used for the analysis to estimate an adjusted odds ratio with 95% confidence interval of the association between maternal pre-pregnancy obesity, race/ethnicity and prematurity. Analysis controlled for diabetes, chronic hypertension, previous preterm birth, smoking and insurance status. The demographics of the study population were as follows, race/ethnicity had predominance in the White/Non-Hispanic population with 60.1%, followed by the Black/ Non-Hispanic population 24.2%, the Hispanic population with 10.3% and the Asian population with 5.4%. Maternal pre-pregnancy weight showed that the population with a normal body mass index (BMI) was 49.4%, followed by the population being overweight with 26.2%, and last, the population which was obese with 24.4%. Maternal obesity increased the odds of prematurity in the White/Non-Hispanic, Hispanic and Asian population (aOR 1.40, CI 1.12-1.75; aOR 2.20, CI 1.23-3.95; aOR 3.07, CI 1.16-8.13, respectively). Although the Black/Non-Hispanic population prematurity rate remains higher than the other race/ethnicity populations, the Black/Non-Hispanic population did not have an increased odds of prematurity in obese mothers (OR 0.87; CI 0.68-1.19). Unlike White/ Non-Hispanic, Asian and Hispanic mothers, normal prepregnancy BMI in Black/Non-Hispanic mothers was not associated with lower odds for prematurity. The odds for mothers of the White/Non-Hispanic, Hispanic and Asian populations, for delivering a premature infant, were significantly increased when obese. Analysis controlled for chronic hypertension, diabetes, insurance status, prior preterm birth and smoking. Obesity is a risk factor for prematurity in the White/Non-Hispanic, Asian and Hispanic population, but not for the Black/Non-Hispanic population. The design and evaluation of weight-based maternal health programs that aggregate race/ethnicity may not be sufficient. The optimal method to address maternal pre-pregnancy and intra-pregnancy weight-related health disorders may need to be stratified along race/ ethnicity adjusted strategies and goals. However, a more global preventative strategy that encompasses the social determinants of health may be needed to reduce the higher rates of prematurity among the Black/Non-Hispanic population. Keywords Body mass index * Prematurity * Obesity * Racial disparities

Abstract. Our objective was to assess risk-adjusted racial and ethnic disparities in mortality following congenital heart surgery. We studied 8483 congenital heart surgical cases from the Kids' Inpatient Database 2000. [...]

Author(s): Deepak Yadav[sup.1] , Tarini Shankar Ghosh[sup.1] and Sharmila S. Mande[sup.1] Background Microbial communities residing in different ecological niches are known to play several key functions and often define the [...], Background Factors like ethnicity, diet and age of an individual have been hypothesized to play a role in determining the makeup of gut microbiome. In order to investigate the gut microbiome structure as well as the inter-microbial associations present therein, we have performed a comprehensive global comparative profiling of the structure (composition, relative heterogeneity and diversity) and the inter-microbial networks in the gut microbiomes of 399 individuals of eight different nationalities. Results The study identified certain geography-specific trends with respect to composition, intra-group heterogeneity and diversity of the gut microbiomes. Interestingly, the gut microbial association/mutual-exlusion networks were observed to exhibit several cross-geography trends. It was seen that though the composition of gut microbiomes of the American and European individuals were similar, there were distinct patterns in their microbial interaction networks. Amongst European gut-microbiomes, the co-occurrence network obtained for the Danish population was observed to be most dense. Distinct patterns were also observed within Chinese, Japanese and Indian datasets. While performing an age-wise comparison, it was observed that the microbial interactions increased with the age of individuals. Furthermore, certain bacterial groups were identified to be present only in the older age groups. Conclusions The trends observed in gut microbial networks could be due to the inherent differences in the diet of individuals belonging to different nationalities. For example, the higher number of microbial associations in the Danish population as compared to the Spanish population, may be attributed to the evenly distributed diet of the later. This is in line with previously reported findings which indicate an increase in functional interdependency of microbes in individuals with higher nutritional status. To summarise, the present study identifies geography and age specific patterns in the composition as well as microbial interactions in gut microbiomes. Keywords: Gut microbiome, Metagenomics, Interaction networks, Bioinformatics, Network analysis