BackgroundAn increasing number of systematic reviews (SRs) in the environmental field have been published in recent years as a result of the global concern about the health impacts of air pollution and temperature. However, no study has assessed and compared the methodological and reporting quality of SRs on the health effects of air pollutants and extreme temperatures. This study aims to assess and compare the methodological and reporting quality of SRs on the health effects of ambient air pollutants and extreme temperatures.MethodsPubMed, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Library, Web of Science, and Epistemonikos databases were searched. Two researchers screened the literature and extracted information independently. The methodological quality of the SRs was assessed through A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2). The reporting quality was assessed through Preferred Reporting Items of Systematic reviews and Meta-Analyses (PRISMA).ResultsWe identified 405 SRs (286 for air pollution, 108 for temperature, and 11 for the synergistic effects). The methodological and reporting quality of the included SRs were suboptimal, with major deficiencies in protocol registration. The methodological quality of SRs of air pollutants was better than that of temperature, especially in terms of satisfactory explanations for any heterogeneity (69.6% v. 45.4%). The reporting quality of SRs of air pollution was better than temperature, however, adherence to the reporting of the assessment results of risk of bias in all SRs (53.5% v. 34.3%) was inadequate.ConclusionsMethodological and reporting quality of SRs on the health effect of air pollutants were higher than those of temperatures. However, deficiencies in protocol registration and the assessment of risk of bias remain an issue for both pollutants and temperatures. In addition, developing a risk-of-bias assessment tool applicable to the temperature field may improve the quality of SRs.

Background: COVID-19 might be a risk factor for various chronic diseases. However, the association between COVID-19 and the risk of incident diabetes remains unclear. We aimed to meta-analyze evidence on the relative risk of incident diabetes in patients with COVID-19. Methods: In this systematic review and meta-analysis, the Embase, PubMed, CENTRAL, and Web of Science databases were searched from December 2019 to June 8, 2022. We included cohort studies that provided data on the number, proportion, or relative risk of diabetes after confirming the COVID-19 diagnosis. Two reviewers independently screened studies for eligibility, extracted data, and assessed risk of bias. We used a random-effects meta-analysis to pool the relative risk with corresponding 95 % confidence intervals. Prespecified subgroup and meta-regression analyses were conducted to explore the potential influencing factors. We converted the relative risk to the absolute risk difference to present the evidence. This study was registered in advance (PROSPERO CRD42022337841). Main findings: Ten articles involving 11 retrospective cohorts with a total of 47.1 million participants proved eligible. We found a 64 % greater risk (RR = 1.64, 95%CI: 1.51 to 1.79) of diabetes in patients with COVID-19 compared with non-COVID-19 controls, which could increase the number of diabetes events by 701 (558 more to 865 more) per 10,000 persons. We detected significant subgroup effects for type of diabetes and sex. Type 2 diabetes has a higher relative risk than type 1. Moreover, men may be at a higher risk of overall diabetes than women. Sensitivity analysis confirmed the robustness of the results. No evidence was found for publication bias. Conclusions: COVID-19 is strongly associated with the risk of incident diabetes, including both type 1 and type 2 diabetes. We should be aware of the risk of developing diabetes after COVID-19 and prepare for the associated health problems, given the large and growing number of people infected with COVID-19. However, the body of evidence still needs to be strengthened.

White rice is the food more than half of the world's population depends on. White rice intake can significantly increase the glycemic load of consumers and bring some adverse health effects. However, the quality of evidence implicating white rice in adverse health outcomes remains unclear. To evaluate the association between white rice consumption and the risk of cardiometabolic and cancer outcomes, a systematic review and dose-response meta-analysis of the relevant publications were performed. Twenty-three articles including 28 unique prospective cohorts with 1,527,198 participants proved eligible after a comprehensive search in four databases. For the risk of type 2 diabetes mellitus (T2DM), the pooled RR was 1.18 (16 more per 1000 persons) for comparing the highest with the lowest category of white rice intake, with moderate certainty evidence. Females presented a higher risk (23 more per 1000 persons) in subgroup analysis. And every additional 150 grams of white rice intake per day was associated with a 6% greater risk of T2DM (5 more per 1000 persons) with a linear positive trend. We found no significant associations between white rice intake and risk of cardiovascular diseases (CVD), CVD mortality, cancer, and metabolic syndrome. In conclusion, moderate certainty evidence demonstrated that white rice intake was associated with T2DM risk, with a linear positive trend. However, low to very low certainty of evidence suggested that no substantial associations were found between white rice intake and other cardiometabolic and cancer outcomes. More cohorts are needed to strength the evidence body.

Research indicates that air pollution is a risk factor of an increased occurrence of diseases. However, evidence is limited on the effects of the pollution index on disease and whether temperature modifies the effects. The objectives were (i) to explore the effects of the Air Pollution Index (API) and specific indices for pollutants (PM10, NO2, and SO2) on respiratory emergency department (ED) visits in Beijing and (ii) to investigate whether temperature modified the effects of main air pollutants on respiratory ED visits. A quasi-Poisson generalized additive model was employed to examine the association of API and indices for pollutants with respiratory disease. Bivariate response surface model and stratification model (cold days, moderately cold days, moderately hot days, and hot days) were used to analyze the modification effects of temperature on air pollution and respiratory disease. The results showed that (i) the effects of API on respiratory diseases were similar to the index for PM(10)in Beijing. (ii) API and PM(10)were associated with increased respiratory ED visits on cold days and moderately cold days. Furthermore, the effects of PM(10)on respiratory disease on moderately cold days [Relative risk (RR) = 1.006 per 10 mu g/m(3), 95% CI 1.002-1.009] were stronger than on cold days (RR = 1.004 per 10 mu g/m(3), 95% CI 1.000-1.008). (iii) PM10(API) had a greater impact on children aged 10 to 17 years and females on moderately cold days, while the elderly had an increased risk of respiratory disease to PM10(RR = 1.008 per 10 mu g/m(3), 95% CI 1.002-1.013) and API (RR = 1.013 per 10, 95% CI 1.004-1.022) on cold days. In conclusion, temperature can modify the association between API and respiratory morbidity. A stronger correlation existed between PM(10)and respiratory diseases on moderately cold days, while the effects of cold days were less than that attributable to moderately cold days.