The World Health Organization has emphasized that one of the most important questions to address regarding the covid-19 pandemic is to understand risk factors for disease severity. We conducted a brief review that synthesizes the available evidence and provides a judgment on the consistency of the association between risk factors and a composite end-point of severe-fatal covid-19. Additionally, we also conducted a comparability analysis of risk factors across 17 studies. We found evidence supporting a total of 60 predictors for disease severity, of which seven were deemed of high consistency, 40 of medium and 13 of low. Among the factors with high consistency of association, we found age, C-reactive protein, D-dimer, albumin, body temperature, SOFA score and diabetes. The results suggest that diabetes might be the most consistent comorbidity predicting disease severity and that future research should carefully consider the comparability of reporting cases, factors, and outcomes along the different stages of the natural history of covid-19.

BackgroundEvidence of the association of coal mining with health outcomes such as increased mortality and morbidity in the general population has been provided by epidemiological studies in the last 25 years. Given the diverse sources of data included to investigate different health outcomes in the exposed populations, the International Classification of Diseases (ICD) can be used as a single classification standard to compare the findings of studies conducted in different socioeconomic and geographic contexts. The ICD classifies diagnoses of diseases and other disorders as codes organized by categories and chapters.ObjectivesIdentify the ICD codes found in studies of morbidity and/or mortality in populations resident or in proximity of coal mining and assess the methods of these studies conducting a systematic review.MethodsA systematic database search of PubMed, EMBASE and Scopus following the PRISMA protocol was conducted to assess epidemiological studies from 1990 to 2016. The health outcomes were mapped to ICD codes and classified by studies of morbidity and/or mortality, and the categories and chapters of the ICD.ResultsTwenty-eight epidemiological studies with ecological design from the USA, Europe and China were included. The exposed populations had increased risk of mortality and/or morbidity by 78 ICD diagnosis categories and 9 groups of ICD categories in 10 chapters of the ICD: Neoplasms, diseases of the circulatory, respiratory and genitourinary systems, metabolic diseases, diseases of the eye and the skin, perinatal conditions, congenital and chromosomal abnormalities, and external causes of morbidity. Exposed populations had non-increased risk of 9 ICD diagnosis categories of diseases of the genitourinary system, and prostate cancer.ConclusionsThere is consistent evidence of the association of coal mining with a wide spectrum of diseases in populations resident or in proximity of the mining activities. The methods of the studies included in this review can be integrated with individual-level and longitudinal studies to provide further evidence of the exposure pathways linked to increased risk in the exposed populations.Electronic supplementary materialThe online version of this article (10.1186/s12889-018-5505-7) contains supplementary material, which is available to authorized users.

No abstract

No abstract

Zoonoses impart a significant public health burden in Australia particularly in Queensland, a state with increasing environmental stress due to extreme weather events and rapid expansion of agriculture and urban developments. Depending on the organism and the environment, a proportion of zoonotic pathogens may survive from hours to years outside the animal host and contaminate the air, water, food, or inanimate objects facilitating their transmission through the environment (i.e. environmentally transmitted). Although most of these zoonotic infections are asymptomatic, severe cases that require hospitalisation are an important indicator of zoonotic infection risk. To date, no studies have investigated the risk of hospitalisation due to environmentally transmitted zoonotic diseases and its association with proxies of sociodemographic and environmental stress. In this study we analysed hospitalisation data for a group of environmentally transmitted zoonoses during a 15-year period using a Bayesian spatial hierarchical model. The analysis incorporated the longest intercensal-year period of consistent Local Government Area (LGA) boundaries in Queensland (1996–2010). Our results showed an increased risk of environmentally transmitted zoonoses hospitalisation in people in occupations such as animal farming, and hunting and trapping animals in natural habitats. This risk was higher in females, compared to the general population. Spatially, the higher risk was in a discrete set of north-eastern, central and southern LGAs of the state, and a probability of 1.5-fold or more risk was identified in two separate LGA clusters in the northeast and south of the state. The increased risk of environmentally transmitted zoonoses hospitalisations in some LGAs indicates that the morbidity due these diseases can be partly attributed to spatial variations in sociodemographic and occupational risk factors in Queensland. The identified high-risk areas can be prioritised for health support and zoonosis control strategies in Queensland.

The potential impacts of coal mining on health have been addressed by the application of impact assessment methodologies that use the results of qualitative and quantitative analyses to support their conclusions and recommendations. Although human epidemiological analyses can provide the most relevant measures of risk of health outcomes in populations exposed to coal mining by-products, this kind of studies are seldom implemented as part of the impact assessment methods. To review the use of human epidemiological analyses in the methods used to assess the impacts of coal mining, a systematic search in the peer review literature was implemented following the PRISMA protocol. A synthesis analysis identified the methods and the measures used in the selected publications to develop a thematic review and discussion. The major methodological approaches to assess the impacts of coal mining are environmental impact assessment (EIA), health impact assessment (HIA), social impact assessment (SIA) and environmental health impact assessment (EHIA). The measures used to assess the impacts of coal mining on health were classified as the estimates from non-human-based studies such as health risk assessment (HRA) and the measures of risk from human epidemiological analyses. The inclusion of human epidemiological estimates of the populations exposed, especially the general populations in the vicinity of the mining activities, is seldom found in impact assessment applications for coal mining. These methods rather incorporate HRA measures or other sources of evidence such as qualitative analyses and surveys. The implementation of impact assessment methods without estimates of the risk of health outcomes relevant to the potentially exposed populations affects their reliability to address the environmental and health impacts of coal mining. This is particularly important for EIA applications because these are incorporated in regulatory frameworks globally. The effective characterization of the impacts of coal mining on health requires quantitative estimates of the risk, including the risk measures from epidemiological analyses of relevant human health data.

Children are more vulnerable to environmental exposures determinant of respiratory diseases due to their dynamic developmental physiology. Whereas social determinants of health are also associated with a higher risk of these diseases in children exposed to environmental risk factors, most studies incorporate them as covariates in the statistical analysis rather than focusing on specific vulnerable populations. In this study a systematic review searched and selected studies of respiratory diseases in children with socioeconomic disadvantage to identify the environmental risk factors associated with these diseases. The review followed the PRISMA protocol to identify eleven eligible studies of children with socioeconomic conditions that included low income and low socioeconomic status, overcrowding, adults with low education level and Indigenous status. Infectious respiratory diseases, asthma, rhinitis and mortality due to respiratory diseases were associated with risk factors such as biomass fuel use, tobacco smoking, particulate matter, coal dust and other pollutants including ozone, nitrogen dioxide and sulphur dioxide. The most common associations were between respiratory infections and household air pollution and asthma with indoor and outdoor air pollution. The findings support previous reports on these associations and suggest that specific vulnerabilities such as indigenous children and living with adults with low socioeconomic status and education level increase the risk of respiratory diseases. These populations can be given special attention to prioritize public health interventions to lower the burden of disease of respiratory diseases in children.

Electronic waste management is a global rising concern that is primarily being handled by informal recycling practices. These release a mix of potentially hazardous chemicals, which is an important public health concern. These chemicals include polybrominated diphenyl ethers (PBDEs), used as flame retardants in electronic parts, which are persistent in nature and show bioaccumulative characteristics. Although PBDEs are suspected endocrine disruptors, particularly targeting thyroid and reproductive hormone functions, the relationship of PBDEs with these health effects are not well established. We used the Navigation Guide methodology to conduct a systematic review of studies in populations exposed to e-waste to better understand the relationships of these persistent flame retardants with hormonal and reproductive health. We assessed nineteen studies that fit our pre-determined inclusion criteria for risk of bias, indirectness, inconsistency, imprecision, and other criteria that helped rate the overall evidence for its quality and strength of evidence. The studies suggest PBDEs may have an adverse effect on thyroid hormones, reproductive hormones, semen quality, and neonatal health. However, more research is required to establish a relationship of these effects in the e-waste-exposed population. We identified the limitations of the data available and made recommendations for future scientific work.