ObjectivesRapid review to determine the magnitude of association between potential risk factors and severity of COVID-19, to inform vaccine prioritisation in Canada.SettingOvid MEDLINE(R) ALL, Epistemonikos COVID-19 in L·OVE Platform, McMaster COVID-19 Evidence Alerts and websites were searched to 15 June 2020. Eligible studies were conducted in high-income countries and used multivariate analyses.ParticipantsAfter piloting, screening, data extraction and quality appraisal were performed by a single experienced reviewer. Of 3740 unique records identified, 34 were included that reported on median 596 (range 44–418 794) participants, aged 42–84 years. 19/34 (56%) were good quality.OutcomesHospitalisation, intensive care unit admission, length of stay in hospital or intensive care unit, mechanical ventilation, severe disease, mortality.ResultsAuthors synthesised findings narratively and appraised the certainty of the evidence for each risk factor–outcome association. There was low or moderate certainty evidence for a large (≥2-fold) magnitude of association between hospitalisation in people with COVID-19, and: obesity class III, heart failure, diabetes, chronic kidney disease, dementia, age >45 years, male gender, black race/ethnicity (vs non-Hispanic white), homelessness and low income. Age >60 and >70 years may be associated with large increases in mechanical ventilation and severe disease, respectively. For mortality, a large magnitude of association may exist with liver disease, Bangladeshi ethnicity (vs British white), age >45 years, age >80 years (vs 65–69 years) and male gender among 20–64 years (but not older). Associations with hospitalisation and mortality may be very large (≥5-fold) for those aged ≥60 years.ConclusionsIncreasing age (especially >60 years) may be the most important risk factor for severe outcomes. High-quality primary research accounting for multiple confounders is needed to better understand the magnitude of associations for severity of COVID-19 with several other factors.PROSPERO registration numberCRD42020198001.

BackgroundObesity and overweight in children and adolescents is an emerging public health concern alongside under-nutrition in low and middle income countries. Our aim was to conduct a scoping review of literature to ascertain what is known about childhood and adolescent overweight and/or obesity in Bangladesh.MethodUsing the scoping review based on York methodology, a comprehensive search of published academic articles, conference proceedings and grey literature was carried out through PubMed, BanglaJOL, Google and Google scholar limited to English-written papers. We summarized prevalence, risk factors and health outcomes of obesity/overweight in young children and adolescents aged between 0 to 19 years old in Bangladesh and highlighted use of different reference standards to measure childhood obesity.ResultsIn total 21 studies met the inclusion criteria. Nearly all of the reviewed articles used data from cross sectional studies, while only two used case–control design. Overall thirteen studies (62%) were primary research and eight (38%) included secondary data. Studies indicated an increasing trend in childhood obesity over time. Prevalence ranged from less than 1% to 17.9% based on different reference standards, with higher percentage amongst urban children across different age groups and sexes.ConclusionThis review demonstrated paucity of comprehensive literature on childhood obesity in Bangladesh, which might be explored through population-based prospective studies based on strong methodology and uniform reference standards. Sustainable and scalable preventative measures targeting high risk groups are required to avoid further rise.

Background: Identification of high-risk groups is needed to inform COVID-19 vaccine prioritization strategies in Canada. A rapid review was conducted to determine the magnitude of association between potential risk factors and risk of severe outcomes of COVID-19. Methods: Methods, inclusion criteria, and outcomes were prespecified in a protocol that is publicly available. Ovid MEDLINE(R) ALL, Epistemonikos COVID-19 in LOVE Platform, and McMaster COVID-19 Evidence Alerts, and select websites were searched to 15 June 2020. Studies needed to be conducted in Organisation for Economic Co-operation and Development countries and have used multivariate analyses to adjust for potential confounders. After piloting, screening, data extraction, and quality appraisal were all performed by a single reviewer. Authors collaborated to synthesize the findings narratively and appraise the certainty of the evidence for each risk factor-outcome association. Results: Of 3,740 unique records identified, 34 were included in the review. The studies included median 596 (range 44 to 418,794) participants with a mean age between 42 and 84 years. Half of the studies (17/34) were conducted in the United States and 19/34 (56%) were rated as good quality. There was low or moderate certainty evidence for a large (≥2-fold) association with increased risk of hospitalization in people having confirmed COVID-19, for the following risk factors: obesity class III, heart failure, diabetes, chronic kidney disease, dementia, age over 45 years (vs. younger), male gender, Black race/ethnicity (vs. non-Hispanic white), homelessness, and low income (vs. above average). Age over 60 and 70 years may be associated with large increases in the rate of mechanical ventilation and severe disease, respectively. For mortality, a large association with increased risk may exist for liver disease, Bangladeshi ethnicity (vs. British white), age over 45 years (vs. <45 years), age over 80 years (vs. 65-69 years), and male gender in those 20-64 years (but not older). Associations with hospitalization and mortality may be very large (≥5-fold increased risk) for those aged over 60 years. Conclusion: Among other factors, increasing age (especially >60 years) appears to be the most important risk factor for severe outcomes among those with COVID-19. There is a need for high quality primary research (accounting for multiple confounders) to better understand the level of risk that might be associated with immigration or refugee status, religion or belief system, social capital, substance use disorders, pregnancy, Indigenous identity, living with a disability, and differing levels of risk among children. PROSPERO registration: CRD42020198001

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BackgroundTo inform vaccine prioritization guidance by the National Advisory Committee on Immunization (NACI), we reviewed evidence on the magnitude of association between risk factors and severe outcomes of COVID-19.MethodsWe updated our existing review by searching online databases and websites for cohort studies providing multivariate adjusted associations. One author screened studies and extracted data. Two authors estimated the magnitude of association between exposures and outcomes as little-to-no (odds, risk, or hazard ratio <2.0, or >0.50 for reduction), large (2.0-3.9, or 0.50-0.26 for reduction), or very large (≥4.0, or ≤0.25 for reduction), and rated the evidence certainty using GRADE.ResultsOf 7,819 unique records we included 111 reports. There is probably (moderate certainty) at least a large increase in mortality from COVID-19 among people aged 60-69 vs. <60 years (11 studies, n=517,217), with ≥2 vs. no comorbidities (4 studies, n=189,608), and for people with (vs. without): Down syndrome (1 study, n>8 million), type 1 and 2 diabetes (1 study, n>8 million), end-stage kidney disease (1 study, n>8 million), epilepsy (1 study, n>8 million), motor neuron disease, multiple sclerosis, myasthenia gravis, or Huntington’s disease (as a grouping; 1 study, n>8 million). The magnitude of association with mortality is probably very large for Down syndrome and may (low certainty) be very large for age 60-69 years, and diabetes. There is probably little-to-no increase in severe outcomes with several cardiovascular and respiratory conditions, and for adult males vs. females.InterpretationFuture research should focus on risk factors where evidence is low quality (e.g., social factors) or non-existent (e.g., rare conditions), the pediatric population, combinations of comorbidities that may increase risk, and long-term outcomes.Systematic review registrationPROSPERO #CRD42021230185.

This systematic review examined pre-existing and clinical risk factors for post Covid-19 condition (≥12 weeks after onset), and interventions during acute and post-acute phases of illness that could potentially prevent post Covid-19 condition. The review focuses on studies collecting data during the early phases of the pandemic and prior to the emergence of variants of concern and widespread vaccination. We searched bibliographic databases and grey literature. Two investigators independently reviewed abstracts and full-text articles, and data extraction and risk of bias assessments were verified. Meta-analysis was performed when suitable and we assessed the certainty of evidence using GRADE. We included 31 studies. We found small-to-moderate associations (e.g. adjusted odds ratios 1.5 to <2.0) between female sex and higher non-recovery, fatigue, and dyspnea (moderate certainty). Severe or critical acute-phase Covid-19 severity (versus not) has probably (moderate certainty) a large association (adjusted ratio ≥2.0) with increased cognitive impairment, a small-to-moderate association with more non-recovery, and a little-to-no association with dyspnea. There may be (low certainty) large associations between hospitalization and increased non-recovery, increased dyspnea, and reduced return to work. Other outcomes had low certainty of small-to-moderate or little-to-no association or very low certainty. Several potential preventive interventions were examined, but effects are very uncertain. Guidelines in relation to surveillance, screening, and other services such as access to sickness and disability benefits, might need to focus on females and those with previously severe Covid-19 illness. Continuous assessment of emerging evidence, especially on whether different variants and vaccination impact outcomes, will be important. PROSPERO registration: CRD42021270354.

Objectives Regular physical activity (PA) in children is essential for their development and prevention of overweight and obesity. Little is known about the effect of day-today variations in weather conditions on PA levels in school-aged children, particularly with regard to school compared to non-school days and girls compared to boys. Methods Daily step count (7:00 a.m.-9:00 p.m.) from 972 grade 5 students aged 10-11 years from 60 schools across Alberta, Canada, was collected using time-stamped pedometers (minimum wear time of two school and one non-school days) during March-June 2013. Time-matched weather conditions (actual and feels-like temperature, cloud coverage, and precipitation amount) were obtained from local weather stations in Alberta during the same period. Multilevel mixed-effect regression models were used to estimate the effect of each weather condition on daily step count. Results A 1°C increase in feels-like temperature was associated with 26 more steps/day (p < 0.05), while 1-unit increase in cloud coverage was associated with 61 fewer steps/day (p < 0.01). Compared to no precipitation, heavy precipitation (> 5 mm/day) was associated with 1022 fewer steps/day (p < 0.01). Students' PA levels were associated with weather conditions more on nonschool vs. school days and more among girls vs. boys. Conclusion Results suggest that daily weather conditions can affect PA in school children, particularly outside school hours, and should be considered when evaluating PA levels or designing interventions to promote PA in children. Findings provide support for increased investment toward creating weather-appropriate physical activity opportunities for wet and colder days to prevent PA decline in children during inclement weather conditions.

Background We evaluated the benefits and risks of using the Abstrackr machine learning (ML) tool to semi-automate title-abstract screening and explored whether Abstrackr’s predictions varied by review or study-level characteristics. Methods For a convenience sample of 16 reviews for which adequate data were available to address our objectives (11 systematic reviews and 5 rapid reviews), we screened a 200-record training set in Abstrackr and downloaded the relevance (relevant or irrelevant) of the remaining records, as predicted by the tool. We retrospectively simulated the liberal-accelerated screening approach. We estimated the time savings and proportion missed compared with dual independent screening. For reviews with pairwise meta-analyses, we evaluated changes to the pooled effects after removing the missed studies. We explored whether the tool’s predictions varied by review and study-level characteristics. Results Using the ML-assisted liberal-accelerated approach, we wrongly excluded 0 to 3 (0 to 14%) records that were included in the final reports, but saved a median (IQR) 26 (9, 42) h of screening time. One missed study was included in eight pairwise meta-analyses in one systematic review. The pooled effect for just one of those meta-analyses changed considerably (from MD (95% CI) − 1.53 (− 2.92, − 0.15) to − 1.17 (− 2.70, 0.36)). Of 802 records in the final reports, 87% were correctly predicted as relevant. The correctness of the predictions did not differ by review (systematic or rapid, P = 0.37) or intervention type (simple or complex, P = 0.47). The predictions were more often correct in reviews with multiple (89%) vs. single (83%) research questions (P = 0.01), or that included only trials (95%) vs. multiple designs (86%) (P = 0.003). At the study level, trials (91%), mixed methods (100%), and qualitative (93%) studies were more often correctly predicted as relevant compared with observational studies (79%) or reviews (83%) (P = 0.0006). Studies at high or unclear (88%) vs. low risk of bias (80%) (P = 0.039), and those published more recently (mean (SD) 2008 (7) vs. 2006 (10), P = 0.02) were more often correctly predicted as relevant. Conclusion Our screening approach saved time and may be suitable in conditions where the limited risk of missing relevant records is acceptable. Several of our findings are paradoxical and require further study to fully understand the tasks to which ML-assisted screening is best suited. The findings should be interpreted in light of the fact that the protocol was prepared for the funder, but not published a priori. Because we used a convenience sample, the findings may be prone to selection bias. The results may not be generalizable to other samples of reviews, ML tools, or screening approaches. The small number of missed studies across reviews with pairwise meta-analyses hindered strong conclusions about the effect of missed studies on the results and conclusions of systematic reviews.