Aim To review the prevalence of gestational diabetes mellitus (GDM) in Eastern and Southeastern Asia. Methods We systematically searched for observational studies on GDM prevalence from January 2000 to December 2016. Inclusion criteria were original English papers, with full texts published in peer-reviewed journals. The quality of included studies was evaluated using the guidelines of the National Health and Medical Research Council, Australia. Fixed effects and random effects models were used to estimate the summary prevalence of GDM and the corresponding 95% confidence intervals (CI). Results A total of 4415 papers were screened, and 48 studies with 63 GDM prevalence observations were included in the final review. The pooled prevalence of GDM was 10.1% (95% CI: 6.5%–15.7%), despite substantial variations across nations. The prevalence of GDM in lower- or upper-middle income countries was about 64% higher than in their high-income counterparts. Moreover, the one-step screening method was twice more likely to be used in diagnosing GDM when compared to the two-step screening procedure. Conclusions The prevalence of GDM in Eastern and Southeastern Asia was high and varied among and within countries. There is a need for international uniformity in screening strategies and diagnostic criteria for GDM.

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The feasibility, reliability and validity of the instrument were established in the context of rural Vietnam. Its application in evaluating other health care programmes should be an important follow-up action for the Vietnamese government.

Objective: To investigate the initiation of breast-feeding and exclusive breast-feeding within the first week after delivery for women in rural Vietnam. Design: An interviewer-administered survey was conducted on a sample of rural women who gave birth during August-October 2002. Setting: Quang Xuong District, Thanh Hoa Province of Vietnam. Subjects: Four hundred and sixty-three women participated in the study, of whom 181 delivered at the district hospital (39.1%), 229 at a commune health centre (49.5%) and 53 at home attended by a traditional birth attendant (11.4%). Results: Although the initiation and exclusive breast-feeding rates were relatively high at 98.3% and 83.6% respectively, the premature introduction of complementary food was a great concern. Logistic regression analysis showed that, together with sociocultural determinants such as feeding preferences of the husband and maternal grandmother, feeding practices of friends, factors relating to delivery methods, delivery locations and health problems could influence the initiation rate and breastfeeding patterns.Conclusions: To promote breast-feeding practices of rural mothers, health education on breast-feeding should take into account local socio-cultural features in addition to improving the counselling skills of health workers.

Providing appropriate training and supportive supervision on breast-feeding counselling to health workers and supporting working mothers to exclusively breast-feed their infants through community mobilization were recommended to improve breast-feeding in rural Vietnam.

Developing new software tools for analysis of large-scale biological data is a key component of advancing modern biomedical research. Scientific reproduction of published findings requires running computational tools on data generated by such studies, yet little attention is presently allocated to the installability and archival stability of computational software tools. Scientific journals require data and code sharing, but none currently require authors to guarantee the continuing functionality of newly published tools. We have estimated the archival stability of computational biology software tools by performing an empirical analysis of the internet presence for 36,702 omics software resources published from 2005 to 2017. We found that almost 28% of all resources are currently not accessible through uniform resource locators (URLs) published in the paper they first appeared in. Among the 98 software tools selected for our installability test, 51% were deemed “easy to install,” and 28% of the tools failed to be installed at all because of problems in the implementation. Moreover, for papers introducing new software, we found that the number of citations significantly increased when authors provided an easy installation process. We propose for incorporation into journal policy several practical solutions for increasing the widespread installability and archival stability of published bioinformatics software.

A survey on the use of antibiotics purchased through retail pharmacies was conducted in the Badinh district of Hanoi, Vietnam. The survey found that purchasers visit a pharmacy when they or those who felt they needed antibiotics had minor symptoms such as cough (34.1%), sore throat (32.5%), stomach upsets (10.0%) and diarrhoea (8.8%). The most often purchased antibiotics were ampicillin (31.1%), amoxyllin (16.7%), cotrimoxazol (11.6%), tetracycline (5.2%) and cephalexin (4.8%). The median of the purchased quantity was 10 tablets, the mean 11.34 tablets (95%CI 9.65-12.97). About 30% of the purchasers intended to take antibiotics for three days or less. The mean cost of a antibiotic purchase was US$1.27 (95%CI 1.06-1.39). The main reason for not taking a full course of antibiotics was not economic constraint, but the purchasers' poor knowledge about antibiotics. Logistic regression analysis indicates that age of purchasers, length of symptoms and kinds of treatment used before visiting a pharmacy could be used as predictive variables for the decision to buy antibiotics in preference to alternative drugs. Antibiotics are used when illness lasts longer than one week and antibiotics have not yet been taken. Antibiotics are also purchased by young rather than old people. The study documents the need for better health education about the rational use of antibiotics in the general public.

Meta-analysis strategies have become critical to augment power of genome-wide association studies (GWAS). To reduce genotyping or sequencing cost, many studies today utilize shared controls, and these individuals can inadvertently overlap among multiple studies. If these overlapping individuals are not taken into account in meta-analysis, they can induce spurious associations. In this article, we propose a general framework for adjusting association statistics to account for overlapping subjects within a meta-analysis. The key idea of our method is to transform the covariance structure of the data, so it can be used in downstream analyses. As a result, the strategy is very flexible and allows a wide range of meta-analysis methods, such as the random effects model, to account for overlapping subjects. Using simulations and real datasets, we demonstrate that our method has utility in meta-analyses of GWAS, as well as in a multi-tissue mouse expression quantitative trait loci (eQTL) study where our method increases the number of discovered eQTL by up to 19% compared with existing methods.