Ambient air pollution and COVID-19 risk: Evidence from 35 observational studies.

BACKGROUND AND AIMS: The coronavirus disease 2019 (COVID-19) pandemic is severely threatening and challenging public health worldwide. Epidemiological studies focused on the influence of outdoor air pollution (AP) on COVID-19 risk have produced inconsistent conclusions. We aimed to quantitatively explore this association using a meta-analysis. METHODS: We searched for studies related to outdoor AP and COVID-19 risk in the Embase, PubMed, and Web of Science databases. No language restriction was utilized. The search date entries were up to August 13, 2021. Pooled estimates and 95% confidence intervals (CIs) were obtained with random-/fixed-effects models. PROSPERO registration number: CRD42021244656. RESULTS: A total of 35 articles were eligible for the meta-analysis. For long-term exposure to AP, COVID-19 incidence was positively associated with 1 µg/m3 increase in nitrogen dioxide (NO2; effect size = 1.042, 95% CI 1.017-1.068), particulate matter with diameter <2.5 µm (PM2.5; effect size = 1.056, 95% CI 1.039-1.072), and sulfur dioxide (SO2; effect size = 1.071, 95% CI 1.002-1.145). The COVID-19 mortality was positively associated with 1 µg/m3 increase in nitrogen dioxide (NO2; effect size = 1.034, 95% CI 1.006-1.063), PM2.5 (effect size = 1.047, 95% CI 1.025-1.1071). For short-term exposure to air pollutants, COVID-19 incidence was positively associated with 1 unit increase in air quality index (effect size = 1.001, 95% CI 1.001-1.002), 1 µg/m3 increase NO2 (effect size = 1.014, 95% CI 1.011-1.016), particulate matter with diameter <10 µm (PM10; effect size = 1.005, 95% CI 1.003-1.008), PM2.5 (effect size = 1.003, 95% CI 1.002-1.004), and SO2 (effect size = 1.015, 95% CI 1.007-1.023). CONCLUSIONS: Outdoor air pollutants are detrimental factors to COVID-19 outcomes. Measurements beneficial to reducing pollutant levels might also reduce the burden of the pandemic.

Air pollution and metabolic syndrome risk: Evidence from nine observational studies.

BACKGROUND AND AIMS: Globally, the number of metabolic syndrome (MetS) cases has increased substantially over time. However, the association between air pollution (AP) and MetS risk has been contradictory in observational studies. This is the first reported meta-analysis quantitatively exploring the aforementioned association. METHODS: We searched PubMed, Embase, and Web of Science database entries up to September 14, 2020, and searches were updated up to December 6, 2020 to identify eligible articles on the AP-MetS risk association. No language restriction was imposed. Random-effects models were applied to estimate summary and subgroup effect sizes with 95% confidence intervals (CIs). PROSPERO registration number: CRD42020210431. RESULTS: Eight articles (nine studies) were eligible for the meta-analysis. Increased MetS prevalence was not found to be associated with particulate matter less than 1 µm (PM1), 2.5 µm (PM2.5), and 10 µm (PM10) in diameter or nitrogen dioxide (NO2), and the summary effect sizes were 1.33 (95% CI: 0.95-1.85), 1.34 (95% CI: 0.96-1.89), 1.18 (95% CI: 0.98-1.19), and 1.28 (95% CI: 0.89-1.82), respectively, based on cross-sectional studies. The summary results indicated no association between each 10 µg/m3 increase in PM2.5 and MetS incidence (effect size 2.78 [95% CI: 0.70-11.02]), based on cohort studies. Subgroup analysis demonstrated that MetS incidence in older men increased dramatically by 992% with each 10 µg/m3 increase in PM2.5. CONCLUSIONS: The evidence presented here suggests that although exposure to PM1, PM2.5, PM10, or NO2 was not found to have a significant association with the occurrence of MetS, the statistical significance of the relationship between exposure to PM1, PM2.5, or PM10 and MetS prevalence was approximately borderline. More studies on AP-MetS risk association in low-/middle-income countries, as well as on the association between other air pollutants and MetS risk, are warranted. A sufficient number of high-quality studies is required to perform a meaningful meta-analysis of the relationship between air pollutants and MetS.

Long-term PM2.5 exposure and various health outcomes: An umbrella review of systematic reviews and meta-analyses of observational studies.

Adverse effects from exposure to particulate matter <2.5 µm in diameter (PM2.5) on health-related outcomes have been found in a range of experimental and epidemiological studies. This study aimed to assess the significance, validity, and reliability of the relationship between long-term PM2.5 exposure and various health outcomes. The Embase, PubMed, Web of Science, CNKI, WANFANG, VIP, and SinoMed databases and reference lists of the retrieved review articles were searched to obtain meta-analysis and systematic reviews focusing on PM2.5-related outcomes as of August 31, 2021. Random-/fixed-effects models were applied to estimate summary effect size and 95% confidence intervals (CIs). The quality of included meta-analyses was evaluated based on the AMSTAR 2 tool. Small-study effect and excess significance bias studies were conducted to further assess the associations. Registered PROSPERO number: CRD42020200606. This included 24 articles involving 71 associations between PM2.5 exposure and the health outcomes. The evidence for the positive association of 10 µg/m3 increments of long-term exposure to PM2.5 and stroke incidence in Europe was convincing (effect size = 1.07, 95% CI: 1.05-1.10). There was evidence that was highly suggestive of a positive association between 10 µg/m3 increments of long-term exposure to PM2.5 and the following health-related outcomes: mortality of lung cancer (effect size = 1.11, 95% CI: 1.08-1.13) and Alzheimer's disease (effect size = 4.79, 95% CI: 2.79-8.21). There was highly suggestive evidence that chronic obstructive pulmonary disease risk is positively associated with higher long-term PM2.5 exposure versus lower long-term PM2.5 exposure (effect size = 2.32, 95% CI: 1.88-2.86). In conclusion, the positive association of long-term exposure to PM2.5 and stroke incidence in Europe was convincing. Given the validity of numerous associations of long-term exposure to PM2.5 and health-related outcomes is subject to biases, more robust evidence is urgently needed.

Dietary protein and multiple health outcomes: An umbrella review of systematic reviews and meta-analyses of observational studies.

BACKGROUND & AIMS: Numerous studies have evaluated the effects of dietary protein on specific health outcomes. The aim of our umbrella review was to summarize the existing evidence between the intake of dietary proteins and multiple health outcomes, and assess their strength and validity. METHODS: Our study was registered at PROSPERO (No. CRD42021255938). We systematically searched PubMed, Embase, and Web of Science databases from inception to May 18, 2021, to identify relevant systematic reviews and meta-analyses of observational studies. The validated "A Measurement Tool to Assess Systematic Reviews" for assessing the methodological quality of included systematic reviews was utilized. For each association, we estimated the summary effect size using fixed and random effects methods, and the 95% confidence and prediction intervals. We also evaluated heterogeneity, evidence of small-study effects, and excess significance bias. RESULTS: Overall, 16 articles with 58 meta-analyses were included. All studies were categorized as over moderate quality. On employing the random-effects model, fourteen (24.1%) meta-analyses were found to be significant at P < 0.05, whereas only one (1.7%) remained significant at P < 10-6. Twenty-two (37.9%) meta-analyses had large or very large heterogeneity. Evidence of small-study effects and excess significance bias was found for three (5.2%) meta-analyses, respectively. One meta-analysis was supported by highly suggestive evidence, indicating that a 5% increase in energy intake from animal protein was associated with 12% higher risk of type 2 diabetes (95% confidence interval [CI]: 1.08-1.17). Of note, the intake of animal and plant proteins had different health effects on type 2 diabetes, all-cause mortality, and risk of cardiovascular disease mortality. CONCLUSIONS: Although the intake of dietary protein was associated with certain health outcomes, the strength of evidence was limited for most outcomes. Moreover, the source of dietary protein is an important factor that requires better consideration in future studies.

Imaging characteristics of coronavirus disease 2019 (COVID-19) in pediatric cases: a systematic review and meta-analysis.

BACKGROUND: The confirmed coronavirus disease 2019 (COVID-19) cases, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), have exceeded 21 million (with more than 775,000 fatalities), and the number of children with COVID-19 is also increasing. This study aimed to summarize the chest imaging characteristics of pediatric COVID-19 cases and provide a reference for the diagnosis and control of pediatric COVID-19. METHODS: The study protocol was registered in PROSPERO, number CRD42020177391. Studies related to pediatric COVID-19 imaging manifestations were accessed from PubMed, Web of Science, and the Cochrane library databases, without language limitations. The publication date was limited to April 1, 2020, and it was updated on May 1 and May 27, 2020. Data normalization was determined with the Freeman-Tukey double arcsine transformation. Summarized incidences with 95% confidence intervals of various imaging manifestations were assessed by random-effects models. Heterogeneity was assessed with meta-regression and subgroup analyses, robustness with sensitivity analyses; and publication biases with Egger's test. RESULTS: Twenty-three with 517 cases were included in this study. The summarized incidence of chest computed tomography abnormalities in pediatric COVID-19 cases was 70%, which was lower than what has been seen in adults. The incidence of halo signs in pediatric COVID-19 cases was 26%, which is rarely seen in adult COVID-19 cases. The incidences of ground-glass opacities (GGOs), GGOs and consolidations, consolidations, reverse halo signs, crazy paving signs, pleural effusion, bronchopneumonia-like signs, air bronchograms, and increased lung markings were 40%, 25%, 10%, 2%, 4%, 1%, 15%, 12%, and 31%, respectively. Pericardial effusions were found in the computed tomography images of adult COVID-19 cases but were scarcely seen in the computed tomography images of pediatric COVID-19 cases. The incidences of bilateral lesions, unilateral lesions, and peripheral lesions were 35%, 22%, and 26%, respectively. CONCLUSIONS: Chest computed tomography imaging of pediatric COVID-19 cases resulted in various abnormalities that were milder than those of adults. This study will hopefully provide a reference to help identify pediatric COVID-19 cases.

Association between maternal antenatal depression and neonatal Apgar score: A systematic review and meta-analysis of prospective cohort studies.

INTRODUCTION: Antenatal depression is common, but most women with the condition choose to remain untreated. The Apgar score, an important indicator of newborn health, has been reported to be influenced by antenatal depression; thus, maternal antenatal depression, as reflected by a poor Apgar score, may harm children's health. AIM: To conduct a systematic review and meta-analysis to explore whether maternal antenatal depression is associated with the neonatal Apgar score. METHODS: We registered the protocol for this study with PROSPERO (CRD42019137585). We searched PubMed, Embase, Web of Science, and the Cochrane Library for published papers that reported the association between depression and Apgar score from inception to December 4, 2019. Two reviewers independently screened and selected the studies according to the inclusion and exclusion criteria, and extracted data according to the predesigned table. Stata version 12.0 software was used to analyze data. RESULTS: We finally identified 13 studies for inclusion, including a total of 12017 women. We did not find an association between antenatal depression and the 1 min Apgar score of neonates (mean difference= -0.03, 95% CI= -0.15-0.09) or the risk of a low Apgar score (OR=1.82, 95% CI=0.51 to 3.13). We found that antenatal depression increased the risk of a low Apgar score at 5 min (OR= 1.91, 95% CI= 1.23-2.59), but the association between the 5 min Apgar score and antenatal depression was not significant (mean difference= -0.001, 95% CI= -0.07-0.07). The results of the subgroup analyses also indicated that there was no association between the 5 min Apgar score and antenatal depression. CONCLUSIONS: Antenatal depression increased the risk of a low 5 min Apgar score; however, we did not find a difference in the mean and distribution of neonatal Apgar scores of mothers with depression and mothers without depression.