Effects of ambient air pollution on obesity and ectopic fat deposition: a protocol for a systematic review and meta-analysis.

INTRODUCTION: Globally, the prevalence of obesity tripled from 1975 to 2016. There is evidence that air pollution may contribute to the obesity epidemic through an increase in oxidative stress and inflammation of adipose tissue. However, the impact of air pollution on body weight at a population level remains inconclusive. This systematic review and meta-analysis will estimate the association of ambient air pollution with obesity, distribution of ectopic adipose tissue, and the incidence and prevalence of non-alcoholic fatty liver disease among adults. METHODS AND ANALYSIS: The study will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for conduct and reporting. The search will include the following databases: Ovid Medline, Embase, PubMed, Web of Science and Latin America and the Caribbean Literature on Health Sciences, and will be supplemented by a grey literature search. Each article will be independently screened by two reviewers, and relevant data will be extracted independently and in duplicate. Study-specific estimates of associations and their 95% Confidence Intervals will be pooled using a DerSimonian and Laird random-effects model, implemented using the RevMan software. The I2 statistic will be used to assess interstudy heterogeneity. The confidence in the body of evidence will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. ETHICS AND DISSEMINATION: As per institutional policy, ethical approval is not required for secondary data analysis. In addition to being published in a peer-reviewed journal and presented at conferences, the results of the meta-analysis will be shared with key stakeholders, health policymakers and healthcare professionals. PROSPERO REGISTRATION NUMBER: CRD42023423955.

Overprescription of antibiotics for treating hospitalized COVID-19 patients: A systematic review & meta-analysis.

Background: Empirical use of antibiotics was reported throughout the coronavirus disease of 2019 (COVID-19) pandemic; however, evidence of bacterial coinfection or secondary bacterial infection among COVID-19 patients was sparse. Antibiotic overprescription for COVID-19 patients without confirmed bacterial coinfection can increase antimicrobial resistance (AMR). The objective of this study is to assess the appropriateness of antibiotic use during COVID-19 by summarizing the frequency of antibiotic use among hospitalized COVID-19 and the frequency of antibiotic use in patients with COVID-19. Methods: A systematic search was conducted of the Embase, Medline, Web of Science, and Cochrane Library databases by generating search terms using the concepts of "COVID-19," "Bacterial Coinfection," "Secondary bacterial infection," and "Antimicrobial resistance" to identify studies reporting antibiotic prescription for hospitalized COVID-19 patients with or without bacterial coinfection. We excluded studies on outpatients, studies informed infection due to mechanical ventilation, and randomized controlled trials. The pooled estimate of the percentage of the total and confirmed appropriate antibiotic prescriptions provided to hospitalized COVID-19 patients was generated using a random effect meta-analysis with inverse variance weighting. The study protocol registration DOI is osf.io/d3fpm. Results: Of 157,623 participants from 29 studies (11 countries, 45 % women) included in our review, antibiotics were prescribed to 67 % of participants (CI 64 %-71 %, P < 0·001), of which 80 % (CI 76 %-83 %, P < 0·001) of prescriptions were for COVID-19 patients without confirmed bacterial coinfections. Antibiotic overprescription varied during different periods of the pandemic and between High-Income and Upper and Lower Middle-Income Countries. We found heterogeneity among the studies (I2 = 100 %). The risk of bias analysis showed that 100 % of the included studies had the proper sample framing, and we are at low risk of bias due to sampling. Discussion: We find greater than expected use of antibiotics to treat hospitalized COVID-19 patients without bacterial coinfections, which may contribute to AMR globally. Concrete guidelines for using antibiotics to treat COVID-19 patients, strict monitoring, and administering Antimicrobial Stewardship are needed to prevent overprescription.

Frequency of musculoskeletal complaints and their associated risk factors among computer workers.

BACKGROUND: Computer-related work has become a part of the daily routine of workers of many occupations which leads to pains of multiple parts of the musculoskeletal system. OBJECTIVES: To examine the frequency and severity of musculoskeletal complaints of different regions of the body, and to examine the relationship between work-related risk factors with musculoskeletal complaints. METHODS: Three hundred and twenty-six computer workers were selected by non-probability purposive sampling from three clusters of computer sectors. The study design was a descriptive cross-sectional study. Respondents were interviewed and their height and weight were measures. Confidentiality was assured. RESULTS: The most common musculoskeletal complaints were shoulder (45%), neck (43%), and upper-middle back (36%) pain. The complaints were related to the female gender, increase duration of computer and using a computer at home. CONCLUSIONS: Musculoskeletal complaints and psychosocial stresses were related to increasing the duration of computer work.