Our findings support a positive association between waterpipe smoking and cancer risk. However, high-quality studies with standardised exposure measurements are needed to clarify the contribution of waterpipe smoking to chronic diseases. More investments in initiatives for surveillance, intervention and regulatory policy for waterpipe smoking are urgently warranted.

The CRCgene database provides the context for genetic association data to be interpreted appropriately and helps inform future research direction.

BackgroundLow back pain (LBP) as a musculoskeletal disorder is one of the most common occupational injuries in nurses but there isn’t any valid measure of the prevalence of LBP in Iranian nursing. In order to increase the power and improve the estimates of the prevalence of LBP in Iranian nurses, a comprehensive meta-analysis was carried out. A summary measure of all studies conducted in this field was found and distributions of LBP were evaluated based on different variables.MethodsInclusion criteria included articles with prevalence of LBP in Iranian nurses, who had at least six months of work experience without any trauma, injuries to spine, or any underlying disease. The keywords“prevalence, low back pain, nurses”, and “Iran” were used as part of this search. Databases such as Pubmed, Web of Science, Science direct, Scopus, IranMedex, Irandoc, Magiran, SID, CIVILICA, IMEMR and Google scholar were searched up to and including 15 June 2016. For data extraction a form was designed that included the following variables: Author names, province, sample size, age, gender, marital status, work experience, body mass index, job type, smoking status, work schedule, year of publication, type of standard questionnaire, prevalence of LBP, studies’ quality score and climate classifications. Data analysis was carried out using fixed and random effects model. Heterogeneity between studies was assessed by using the I2 and Q tests.ResultsIn all 1250 articles were identified and 22 articles with 9347 participants met the inclusion criteria for meta-analyses after filtering. The prevalence of low back pain during their working life and during the last year, was estimated at 63% (95% Confidence Interval (CI): 57.4–68.5) and 61.2% (95% CI: 55.7–66.7) respectively. The prevalence rate of this disorder was 58.7% (95% CI: 35.8–81.7) and 60.4% (95% CI: 52.2–68.6) among men and women respectively. Furthermore, prevalence’s of LBP were 59.5% in wards nurses, 50.3% in operating room technicians, and 39.4% in aid nurses.ConclusionsThe results showed the high prevalence of LBP injury in nurses, especially female nurses. The effect of musculoskeletal disorders such as LBP may be reduced by considering proper observation of the principles of ergonomics in the workplace, performing physical examinations on a regular basis, identifying risk factors in the advancement of musculoskeletal disorders and then trying to fix them.

BackgroundAsthma is a multifactorial syndrome that threatens the health of children. Body mass index (BMI) might be one of the potential factors but the evidence is controversial. The aim of this study is to perform a comprehensive meta-analysis to investigate the association between asthma and BMI.MethodsElectronic databases including, Web of Science, Pubmed, Scopus, Science Direct, ProQuest, up to April 2017, were searched by two researchers independently. The keywords “asthma, body mass index, obesity, overweight, childhood and adolescence” were used. Random and fixed effects models were applied to obtain the overall odds ratios (ORs) and standardized mean difference (SMD). Heterogeneity between the studies was examined using I2 and Cochrane Q statistics.ResultsAfter reviewing 2511 articles, 16 studies were eligible for meta-analysis according to inclusion/exclusion criteria. A meta-analysis from 11 case-control studies revealed OR of asthma and overweight as OR = 1.64; (95% Confidence Interval (CI): 1.13–2.38) and from 14 case-control studies, OR for asthma and obesity was OR = 1.92 (95% CI: 1.39–2.65), which indicated that risk of asthma in overweight and obese children and adolescence was significantly higher (1.64 and 1.92 times) than that of individuals with (p-value < 0.01 for underweight/normal weight in both cases). Furthermore, there was a significant relationship between asthma and BMI > 85 percentile according to SMD SMD = 0.21; (95%CI: 0.03–0.38; p-value = 0.021).ConclusionsThe results showed a significant relationship between BMI (obesity/overweight) and asthma among children and adolescents. It is important to study the confounding factors that affect the relationship between asthma and BMI in future epidemiological researches.Electronic supplementary materialThe online version of this article (10.1186/s12887-018-1093-z) contains supplementary material, which is available to authorized users.

The cause of colorectal cancer (CRC) is multifactorial, involving both genetic variants and environmental risk factors. We systematically searched the MEDLINE, EMBASE, China National Knowledge Infrastructure (CNKI) and Wanfang databases from inception to December 2016, to identify systematic reviews and meta‐analyses of observational studies that investigated gene–environment (G×E) interactions in CRC risk. Then, we critically evaluated the cumulative evidence for the G×E interactions using an extension of the Human Genome Epidemiology Network's Venice criteria. Overall, 15 articles reporting systematic reviews of observational studies on 89 G×E interactions, 20 articles reporting meta‐analyses of candidate gene‐ or single‐nucleotide polymorphism‐based studies on 521 G×E interactions, and 8 articles reporting 33 genome‐wide G×E interaction analyses were identified. On the basis of prior and observed scores, only the interaction between rs6983267 (8q24) and aspirin use was found to have a moderate overall credibility score as well as main genetic and environmental effects. Though 5 other interactions were also found to have moderate evidence, these interaction effects were tenuous due to the lack of main genetic effects and/or environmental effects. We did not find highly convincing evidence for any interactions, but several associations were found to have moderate strength of evidence. Our conclusions are based on application of the Venice criteria which were designed to provide a conservative assessment of G×E interactions and thus do not include an evaluation of biological plausibility of an observed joint effect.

ObjectiveTo provide an understanding of the role of common genetic variations in colorectal cancer (CRC) risk, we report an updated field synopsis and comprehensive assessment of evidence to catalogue all genetic markers for CRC (CRCgene2).DesignWe included 869 publications after parallel literature review and extracted data for 1063 polymorphisms in 303 different genes. Meta-analyses were performed for 308 single nucleotide polymorphisms (SNPs) in 158 different genes with at least three independent studies available for analysis. Scottish, Canadian and Spanish data from genome-wide association studies (GWASs) were incorporated for the meta-analyses of 132 SNPs. To assess and classify the credibility of the associations, we applied the Venice criteria and Bayesian False-Discovery Probability (BFDP). Genetic associations classified as ‘positive’ and ‘less-credible positive’ were further validated in three large GWAS consortia conducted in populations of European origin.ResultsWe initially identified 18 independent variants at 16 loci that were classified as ‘positive’ polymorphisms for their highly credible associations with CRC risk and 59 variants at 49 loci that were classified as ‘less-credible positive’ SNPs; 72.2% of the ‘positive’ SNPs were successfully replicated in three large GWASs and the ones that were not replicated were downgraded to ‘less-credible’ positive (reducing the ‘positive’ variants to 14 at 11 loci). For the remaining 231 variants, which were previously reported, our meta-analyses found no evidence to support their associations with CRC risk.ConclusionThe CRCgene2 database provides an updated list of genetic variants related to CRC risk by using harmonised methods to assess their credibility.

Background Low penetrance genetic variants, primarily single nucleotide polymorphisms, have substantial influence on colorectal cancer (CRC) susceptibility. Most CRCs develop from colorectal adenomas (CRA). Here, we report the first comprehensive field synopsis that catalogues all genetic association studies on CRA, with a parallel online database (http://www.chs.med.ed.ac.uk/CRAgene/). Methods We performed a systematic review, reviewing 9750 titles and then extracted data from 130 publications reporting on 181 polymorphisms in 74 genes. We conducted meta-analyses to derive summary effect estimates for 37 polymorphisms in 26 genes. We applied the Venice criteria and Bayesian False Discovery Probability (BFDP) to assess the levels of the credibility of associations. Results We considered the association with the rs6983267 variant at 8q24 as “highly credible”, reaching genome wide statistical significance in at least one meta-analysis model. We identified “less credible” associations (higher heterogeneity, lower statistical power, BFDP>0.02) with a further four variants of four independent genes: MTHFR c.677C>T p.A222V (rs1801133), TP53 c.215C>G p.R72P (rs1042522), NQO1 c.559C>T p.P187S (rs1800566), and NAT1 alleles imputed as fast acetylator genotypes. For the remaining 32 variants of 22 genes for which positive associations with CRA risk have been previously reported, the meta-analyses revealed no credible evidence to support these as true associations. Conclusions The limited number of credible associations between low penetrance genetic variants and CRA reflects the lower volume of evidence and associated lack of statistical power to detect associations of the magnitude typically observed for genetic variants and chronic diseases. The CRAgene database provides context for CRA genetic association data and will help inform future research directions.

Some results related to statistical classification in the presence of missing covariates are presented. We derive representations for the best (Bayes) classifier when some of the covariates can be missing; this is done without imposing any assumptions on the underlying missing probability mechanism. Furthermore, without assuming any missingness-at-random type of conditions, we also construct Bayes consistent classifiers that do not require any imputation-based techniques. Both parametric and non-parametric situations are considered but the emphasis is on the latter. In addition to simple missingness patterns, we also consider the full "Swiss cheese" model, where the missing covariates can be anywhere. Both mechanics and the theoretical validity of our results are discussed. Copyright 2007 Royal Statistical Society.