International Journal of Epidemiology
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Published By Oxford University Press

1464-3685, 0300-5771
Updated Saturday, 23 October 2021

Salwa Al-eryani ◽  
Sharaf alkuhlani ◽  
Abdul Wahed Al Serouri ◽  
Yasser Ghaleb

Xavier Escriba-Montagut ◽  
Xavier Basagaña ◽  
Martine Vrijheid ◽  
Juan R Gonzalez

Abstract Motivation Studying the role of the exposome in human health and its impact on different omic layers requires advanced statistical methods. Many of these methods are implemented in different R and Bioconductor packages, but their use may require strong expertise in R, in writing pipelines and in using new R classes which may not be familiar to non-advanced users. ExposomeShiny provides a bridge between researchers and most of the state-of-the-art exposome analysis methodologies, without the need of advanced programming skills. Implementation ExposomeShiny is a standalone web application implemented in R. It is available as source files and can be installed in any server or computer avoiding problems with data confidentiality. It is executed in RStudio which opens a browser window with the web application. General features The presented implementation allows the conduct of: (i) data pre-processing: normalization and missing imputation (including limit of detection); (ii) descriptive analysis; (iii) exposome principal component analysis (PCA) and hierarchical clustering; (iv) exposome-wide association studies (ExWAS) and variable selection ExWAS; (v) omic data integration by single association and multi-omic analyses; and (vi) post-exposome data analyses to gain biological insight for the exposures, genes or using the Comparative Toxicogenomics Database (CTD) and pathway analysis. Availability The exposomeShiny source code is freely available on Github at [], Git tag v1.4. The software is also available as a Docker image [], tag v1.4. A user guide with information about the analysis methodologies as well as information on how to use exposomeShiny is freely hosted at [].

Peng Lu ◽  
Guoxin Xia ◽  
Qi Zhao ◽  
Donna Green ◽  
Youn-Hee Lim ◽  

Abstract Background Heat exposure is a risk factor for urologic diseases. However, there are limited existing studies that have examined the relationship between high temperatures and urologic disease. The aim of this study was to examine the associations between heat exposure and hospitalizations for urologic diseases in Queensland, Australia, during the hot seasons of 1995–2016 and to quantify the attributable risks. Methods We obtained 238 427 hospitalized cases with urologic diseases from Queensland Health between 1 December 1995 and 31 December 2016. Meteorological data were collected from the Scientific Information for Land Owners—a publicly accessible database of Australian climate data that provides daily data sets for a range of climate variables. A time-stratified, case-crossover design fitted with the conditional quasi-Poisson regression model was used to estimate the associations between temperature and hospitalizations for urologic diseases at the postcode level during each hot season (December–March). Attributable rates of hospitalizations for urologic disease due to heat exposure were calculated. Stratified analyses were performed by age, sex, climate zone, socio-economic factors and cause-specific urologic diseases. Results We found that a 1°C increase in temperature was associated with a 3.3% [95% confidence interval (CI): 2.9%, 3.7%] increase in hospitalization for the selected urologic diseases during the hot season. Hospitalizations for renal failure showed the strongest increase 5.88% (95% CI: 5.25%, 6.51%) among the specific causes of hospital admissions considered. Males and the elderly (≥60 years old) showed stronger associations with heat exposure than females and younger groups. The sex- and age-specific associations with heat exposure were similar across specific causes of urologic diseases. Overall, nearly one-fifth of hospitalizations for urologic diseases were attributable to heat exposure in Queensland. Conclusions Heat exposure is associated with increased hospitalizations for urologic disease in Queensland during the hot season. This finding reinforces the pressing need for dedicated public health-promotion campaigns that target susceptible populations, especially for those more predisposed to renal failure. Given that short-term climate projections identify an increase in the frequency, duration and intensity of heatwaves, this public health advisory will be of increasing urgency in coming years.

Kieran S O’Brien ◽  
Ahmed M Arzika ◽  
Ramatou Maliki ◽  
Abdou Amza ◽  
Farouk Manzo ◽  

Abstract Background Biannual azithromycin distribution to children 1–59 months old reduced all-cause mortality by 18% [incidence rate ratio (IRR) 0.82, 95% confidence interval (CI): 0.74, 0.90] in an intention-to-treat analysis of a randomized controlled trial in Niger. Estimation of the effect in compliance-related subgroups can support decision making around implementation of this intervention in programmatic settings. Methods The cluster-randomized, placebo-controlled design of the original trial enabled unbiased estimation of the effect of azithromycin on mortality rates in two subgroups: (i) treated children (complier average causal effect analysis); and (ii) untreated children (spillover effect analysis), using negative binomial regression. Results In Niger, 594 eligible communities were randomized to biannual azithromycin or placebo distribution and were followed from December 2014 to August 2017, with a mean treatment coverage of 90% [standard deviation (SD) 10%] in both arms. Subgroup analyses included 2581 deaths among treated children and 245 deaths among untreated children. Among treated children, the incidence rate ratio comparing mortality in azithromycin communities to placebo communities was 0.80 (95% CI: 0.72, 0.88), with mortality rates (deaths per 1000 person-years at risk) of 16.6 in azithromycin communities and 20.9 in placebo communities. Among untreated children, the incidence rate ratio was 0.91 (95% CI: 0.69, 1.21), with rates of 33.6 in azithromycin communities and 34.4 in placebo communities. Conclusions As expected, this analysis suggested similar efficacy among treated children compared with the intention-to-treat analysis. Though the results were consistent with a small spillover benefit to untreated children, this trial was underpowered to detect spillovers.

Lukoye Atwoli ◽  
Abdullah H Baqui ◽  
Thomas Benfield ◽  
Raffaella Bosurgi ◽  
Fiona Godlee ◽  

Yi Yang ◽  
Suzanne C Dixon-Suen ◽  
Pierre-Antoine Dugué ◽  
Allison M Hodge ◽  
Brigid M Lynch ◽  

Abstract Background Questions remain about the effect on mortality of physical activity and sedentary behaviour over time. We summarized the evidence from studies that assessed exposure from multiple time points and critiqued the analytic approaches used. Methods A search was performed on MEDLINE, Embase, Emcare, Scopus and Web of Science up to January 2021 for studies of repeatedly assessed physical activity or sedentary behaviour in relation to all-cause or cause-specific mortality. Relative risks from individual studies were extracted. Each study was assessed for risk of bias from multiple domains. Results We identified 64 eligible studies (57 on physical activity, 6 on sedentary behaviour, 1 on both). Cox regression with a time-fixed exposure history (n = 45) or time-varying covariates (n = 13) were the most frequently used methods. Only four studies used g-methods, which are designed to adjust for time-varying confounding. Risk of bias arose primarily from inadequate adjustment for time-varying confounders, participant selection, exposure classification and changes from measured exposure. Despite heterogeneity in methods, most studies found that being consistently or increasingly active over adulthood was associated with lower all-cause and cardiovascular-disease mortality compared with being always inactive. Few studies examined physical-activity changes and cancer mortality or effects of sedentary-behaviour changes on mortality outcomes. Conclusions Accumulating more evidence using longitudinal data while addressing the methodological challenges would provide greater insight into the health effects of initiating or maintaining a more active and less sedentary lifestyle.

2021 ◽  
Vol 50 (Supplement_1) ◽  
Amanda Lumsden ◽  
Anwar Mulugeta ◽  
Ang Zhou ◽  
Elina Hyppönen

Abstract Background The APOE gene has three main alleles; APOE-E2, E3 and E4 (global frequencies: 8%, 78%, 14%) carrying differential risk for conditions such as dementia and cardiovascular disease. Due to the clinical significance of variation at this locus, we explored disease associations of APOE genotypes using a hypothesis-free, phenome-wide association study (PheWAS) approach. Methods Utilising medical and genetic data available from the UK Biobank for 337,484 white British participants aged 37–73 years, we screened for associations between APOE genotypes (E4E4, E3E4, E2E4, E2E3 and E2E2) and ≥825 disease outcomes, using E3E3 as a reference. Results Case-control PheWAS analyses revealed associations with 37 disease outcomes from 17 distinct conditions after multiple test correction. As expected, E4E4 and E3E4 associated with risk of Alzheimer’s disease (p < 10-46 for both), hypercholesterolemia (p < 10-17), and cardiovascular diseases (p < 10-4). Novel findings included E4-associated increased risk of chondrocalcinosis (E4E4), and protection against obesity (E4E4), type 2 diabetes (E4E4, E4E3), and chronic airway obstruction (E4E4; all p ≤ 3.2 × 10-4). Notably, E2E2 homozygosity augmented risks of peripheral vascular diseases, and cervical disorders (p ≤ 1·9 × 10-5). Conclusions PheWAS assessment of APOE-associated risk for a wide spectrum of diseases amongst this large, white British population, detected well-established, and novel APOE-disease associations warranting further validation. Key messages While APOE-E4 is risky for Alzheimer’s, and cardiovascular diseases, it may be protective against some metabolic conditions. While the E2 allele is often considered beneficial, homozygosity-associated risks may contribute to its relatively low prevalence.

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