•Preventive measures -such as social distancing- are crucial, but can carry long-term consequences.•Terms such as ‘spatial distancing’ help avoid the contradictory interpretation of social distancing ...in times when social support is crucial.•Miscommunication, social isolation and poorer socioeconomic status can impair the wellbeing of vulnerable groups.•Vulnerable groups are indigenous, prison and homeless populations; migrants, the elderly, people with disabilities and healthcare workers.
The zoonotic virus now named SARS-CoV-2 first infected humans in China, and COVID-19 has rapidly become pandemic. To mitigate its impact on societies, health systems and economies, countries have adopted non-pharmacological preventive practices such as ‘spatial’ or ‘social’ distancing, the use of protective masks, and handwashing; these have been widely implemented. However, measures aimed at protecting physical health and healthcare systems have side-effects that might have a big impact on individuals’ wellbeing. As the pandemic reaches low- and middle-income countries, weaker health systems, limited resources and the lower socioeconomic status of their populations make halting the pandemic more challenging. In this article, we explore the impact of COVID-19 and its prevention measures on the wellbeing of vulnerable populations. Special attention must be given to homeless, indigenous, migrant and imprisoned populations, as well as people living with disabilities and the elderly. More than just resolute governmental action will be required to overcome the pandemic. Links between science and political actions have to be strengthened. Fighting COVID-19 is a collective endeavour and community action, on a global scale, is of paramount importance.
Abstract
Health-care workers (HCWs) are at the frontline of response to coronavirus disease 2019 (COVID-19), being at a higher risk of acquiring the disease and, subsequently, exposing patients and ...others. Searches of 8 bibliographic databases were performed to systematically review the evidence on the prevalence, risk factors, clinical characteristics, and prognosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among HCWs. A total of 97 studies (all published in 2020) met the inclusion criteria. The estimated prevalence of SARS-CoV-2 infection from HCWs’ samples, using reverse transcription–polymerase chain reaction and the presence of antibodies, was 11% (95% confidence interval (CI): 7, 15) and 7% (95% CI: 4, 11), respectively. The most frequently affected personnel were nurses (48%, 95% CI: 41, 56), whereas most of the COVID-19–positive medical personnel were working in hospital nonemergency wards during screening (43%, 95% CI: 28, 59). Anosmia, fever, and myalgia were the only symptoms associated with HCW SARS-CoV-2 positivity. Among HCWs positive for COVID-19 by reverse transcription–polymerase chain reaction, 40% (95% CI: 17, 65) were asymptomatic at time of diagnosis. Finally, severe clinical complications developed in 5% (95% CI: 3, 8) of the COVID-19–positive HCWs, and 0.5% (95% CI: 0.02, 1.3) died. Health-care workers suffer a significant burden from COVID-19, with those working in hospital nonemergency wards and nurses being the most commonly infected personnel.
Americans have a shorter life expectancy compared with residents of almost all other high-income countries. We aim to estimate the impact of lifestyle factors on premature mortality and life ...expectancy in the US population.
Using data from the Nurses' Health Study (1980-2014; n=78 865) and the Health Professionals Follow-up Study (1986-2014, n=44 354), we defined 5 low-risk lifestyle factors as never smoking, body mass index of 18.5 to 24.9 kg/m
, ≥30 min/d of moderate to vigorous physical activity, moderate alcohol intake, and a high diet quality score (upper 40%), and estimated hazard ratios for the association of total lifestyle score (0-5 scale) with mortality. We used data from the NHANES (National Health and Nutrition Examination Surveys; 2013-2014) to estimate the distribution of the lifestyle score and the US Centers for Disease Control and Prevention WONDER database to derive the age-specific death rates of Americans. We applied the life table method to estimate life expectancy by levels of the lifestyle score.
During up to 34 years of follow-up, we documented 42 167 deaths. The multivariable-adjusted hazard ratios for mortality in adults with 5 compared with zero low-risk factors were 0.26 (95% confidence interval CI, 0.22-0.31) for all-cause mortality, 0.35 (95% CI, 0.27-0.45) for cancer mortality, and 0.18 (95% CI, 0.12-0.26) for cardiovascular disease mortality. The population-attributable risk of nonadherence to 5 low-risk factors was 60.7% (95% CI, 53.6-66.7) for all-cause mortality, 51.7% (95% CI, 37.1-62.9) for cancer mortality, and 71.7% (95% CI, 58.1-81.0) for cardiovascular disease mortality. We estimated that the life expectancy at age 50 years was 29.0 years (95% CI, 28.3-29.8) for women and 25.5 years (95% CI, 24.7-26.2) for men who adopted zero low-risk lifestyle factors. In contrast, for those who adopted all 5 low-risk factors, we projected a life expectancy at age 50 years of 43.1 years (95% CI, 41.3-44.9) for women and 37.6 years (95% CI, 35.8-39.4) for men. The projected life expectancy at age 50 years was on average 14.0 years (95% CI, 11.8-16.2) longer among female Americans with 5 low-risk factors compared with those with zero low-risk factors; for men, the difference was 12.2 years (95% CI, 10.1-14.2).
Adopting a healthy lifestyle could substantially reduce premature mortality and prolong life expectancy in US adults.
Within systematic reviews, when searching for relevant references, it is advisable to use multiple databases. However, searching databases is laborious and time-consuming, as syntax of search ...strategies are database specific. We aimed to determine the optimal combination of databases needed to conduct efficient searches in systematic reviews and whether the current practice in published reviews is appropriate. While previous studies determined the coverage of databases, we analyzed the actual retrieval from the original searches for systematic reviews.
Since May 2013, the first author prospectively recorded results from systematic review searches that he performed at his institution. PubMed was used to identify systematic reviews published using our search strategy results. For each published systematic review, we extracted the references of the included studies. Using the prospectively recorded results and the studies included in the publications, we calculated recall, precision, and number needed to read for single databases and databases in combination. We assessed the frequency at which databases and combinations would achieve varying levels of recall (i.e., 95%). For a sample of 200 recently published systematic reviews, we calculated how many had used enough databases to ensure 95% recall.
A total of 58 published systematic reviews were included, totaling 1746 relevant references identified by our database searches, while 84 included references had been retrieved by other search methods. Sixteen percent of the included references (291 articles) were only found in a single database; Embase produced the most unique references (n = 132). The combination of Embase, MEDLINE, Web of Science Core Collection, and Google Scholar performed best, achieving an overall recall of 98.3 and 100% recall in 72% of systematic reviews. We estimate that 60% of published systematic reviews do not retrieve 95% of all available relevant references as many fail to search important databases. Other specialized databases, such as CINAHL or PsycINFO, add unique references to some reviews where the topic of the review is related to the focus of the database.
Optimal searches in systematic reviews should search at least Embase, MEDLINE, Web of Science, and Google Scholar as a minimum requirement to guarantee adequate and efficient coverage.
To inform evidence-based practice in health care, guidelines and policies require accurate identification, collation, and integration of all available evidence in a comprehensive, meaningful, and ...time-efficient manner. Approaches to evidence synthesis such as carefully conducted systematic reviews and meta-analyses are essential tools to summarize specific topics. Unfortunately, not all systematic reviews are truly systematic, and their quality can vary substantially. Since well-conducted evidence synthesis typically involves a complex set of steps, we believe formulating a cohesive, step-by-step guide on how to conduct a systemic review and meta-analysis is essential. While most of the guidelines on systematic reviews focus on how to report or appraise systematic reviews, they lack guidance on how to synthesize evidence efficiently. To facilitate the design and development of evidence syntheses, we provide a clear and concise, 24-step guide on how to perform a systematic review and meta-analysis of observational studies and clinical trials. We describe each step, illustrate it with concrete examples, and provide relevant references for further guidance. The 24-step guide (1) simplifies the methodology of conducting a systematic review, (2) provides healthcare professionals and researchers with methodologically sound tools for conducting systematic reviews and meta-analyses, and (3) it can enhance the quality of existing evidence synthesis efforts. This guide will help its readers to better understand the complexity of the process, appraise the quality of published systematic reviews, and better comprehend (and use) evidence from medical literature.
ABSTRACTObjectiveTo conduct a systematic review and meta-analysis of epidemiological studies investigating the association of arsenic, lead, cadmium, mercury, and copper with cardiovascular ...disease.DesignSystematic review and meta-analysis.Data sourcesPubMed, Embase, and Web of Science searched up to December 2017.Review methodsStudies reporting risk estimates for total cardiovascular disease, coronary heart disease, and stroke for levels of arsenic, lead, cadmium, mercury, or copper were included. Two investigators independently extracted information on study characteristics and outcomes in accordance with PRISMA and MOOSE guidelines. Relative risks were standardised to a common scale and pooled across studies for each marker using random effects meta-analyses.ResultsThe review identified 37 unique studies comprising 348 259 non-overlapping participants, with 13 033 coronary heart disease, 4205 stroke, and 15 274 cardiovascular disease outcomes in aggregate. Comparing top versus bottom thirds of baseline levels, pooled relative risks for arsenic and lead were 1.30 (95% confidence interval 1.04 to 1.63) and 1.43 (1.16 to 1.76) for cardiovascular disease, 1.23 (1.04 to 1.45) and 1.85 (1.27 to 2.69) for coronary heart disease, and 1.15 (0.92 to 1.43) and 1.63 (1.14 to 2.34) for stroke. Relative risks for cadmium and copper were 1.33 (1.09 to 1.64) and 1.81 (1.05 to 3.11) for cardiovascular disease, 1.29 (0.98 to 1.71) and 2.22 (1.31 to 3.74) for coronary heart disease, and 1.72 (1.29 to 2.28) and 1.29 (0.77 to 2.17) for stroke. Mercury had no distinctive association with cardiovascular outcomes. There was a linear dose-response relation for arsenic, lead, and cadmium with cardiovascular disease outcomes.ConclusionExposure to arsenic, lead, cadmium, and copper is associated with an increased risk of cardiovascular disease and coronary heart disease. Mercury is not associated with cardiovascular risk. These findings reinforce the importance of environmental toxic metals in cardiovascular risk, beyond the roles of conventional behavioural risk factors.
AbstractObjectiveTo examine how a healthy lifestyle is related to life expectancy that is free from major chronic diseases.DesignProspective cohort study.Setting and participantsThe Nurses’ Health ...Study (1980-2014; n=73 196) and the Health Professionals Follow-Up Study (1986-2014; n=38 366).Main exposuresFive low risk lifestyle factors: never smoking, body mass index 18.5-24.9, moderate to vigorous physical activity (≥30 minutes/day), moderate alcohol intake (women: 5-15 g/day; men 5-30 g/day), and a higher diet quality score (upper 40%).Main outcomeLife expectancy free of diabetes, cardiovascular diseases, and cancer.ResultsThe life expectancy free of diabetes, cardiovascular diseases, and cancer at age 50 was 23.7 years (95% confidence interval 22.6 to 24.7) for women who adopted no low risk lifestyle factors, in contrast to 34.4 years (33.1 to 35.5) for women who adopted four or five low risk factors. At age 50, the life expectancy free of any of these chronic diseases was 23.5 (22.3 to 24.7) years among men who adopted no low risk lifestyle factors and 31.1 (29.5 to 32.5) years in men who adopted four or five low risk lifestyle factors. For current male smokers who smoked heavily (≥15 cigarettes/day) or obese men and women (body mass index ≥30), their disease-free life expectancies accounted for the lowest proportion (≤75%) of total life expectancy at age 50.ConclusionAdherence to a healthy lifestyle at mid-life is associated with a longer life expectancy free of major chronic diseases.
In low and middle-income countries (LMICs), strict social distancing measures (e.g., nationwide lockdown) in response to the COVID-19 pandemic are unsustainable in the long-term due to knock-on ...socioeconomic and psychological effects. However, an optimal epidemiology-focused strategy for ‘safe-reopening’ (i.e., balancing between the economic and health consequences) remain unclear, particularly given the suboptimal disease surveillance and diagnostic infrastructure in these settings. As the lockdown is now being relaxed in many LMICs, in this paper, we have (1) conducted an epidemiology-based “options appraisal” of various available non-pharmacological intervention options that can be employed to safely lift the lockdowns (namely, sustained mitigation, zonal lockdown and rolling lockdown strategies), and (2) propose suitable application, pre-requisites, and inherent limitations for each measure. Among these, a sustained mitigation-only approach (adopted in many high-income countries) may not be feasible in most LMIC settings given the absence of nationwide population surveillance, generalised testing, contact tracing and critical care infrastructure needed to tackle the likely resurgence of infections. By contrast, zonal or local lockdowns may be suitable for some countries where systematic identification of new outbreak clusters in real-time would be feasible. This requires a generalised testing and surveillance structure, and a well-thought out (and executed) zone management plan. Finally, an intermittent, rolling lockdown strategy has recently been suggested by the World Health Organization as a potential strategy to get the epidemic under control in some LMI settings, where generalised mitigation and zonal containment is unfeasible. This strategy, however, needs to be carefully considered for economic costs and necessary supply chain reforms. In conclusion, while we propose three community-based, non-pharmacological options for LMICs, a suitable measure should be context-specific and based on: (1) epidemiological considerations, (2) social and economic costs, (3) existing health systems capabilities and (4) future-proof plans to implement and sustain the strategy.
The aim of this study was to determine the extent to which adherence to individual vascular medications, assessed by different methods, influences the absolute and relative risks (RRs) of ...cardiovascular disease (CVD) and all-cause mortality.
We performed a systematic review and meta-analysis of prospective epidemiological studies (cohort, nested case-control, or clinical trial) identified through electronic searches using MEDLINE, Web of Science, EMBASE, and Cochrane databases, involving adult populations (≥ 18 years old) and reporting risk estimates of cardiovascular medication adherence with any CVD (defined as any fatal or non-fatal coronary heart disease, stroke or sudden cardiac death) and/or all-cause mortality (defined as mortality from any cause) outcomes. Relative risks were combined using random-effects models. Forty-four unique prospective studies comprising 1 978 919 non-overlapping participants, with 135 627 CVD events and 94 126 cases of all-cause mortality. Overall, 60% (95% CI: 52-68%) of included participants had good adherence (adherence ≥ 80%) to cardiovascular medications. The RRs (95% CI) of development of CVD in those with good vs. poor (<80%) adherence were 0.85 (0.81-0.89) and 0.81 (0.76-0.86) for statins and antihypertensive medications, respectively. Corresponding RRs of all-cause mortality were 0.55 (0.46-0.67) and 0.71 (0.64-0.78) for good adherence to statins and antihypertensive agents. These associations remained consistent across subgroups representing different study characteristics. Estimated absolute risk differences for any CVD associated with poor medication adherence were 13 cases for any vascular medication, 9 cases for statins and 13 cases for antihypertensive agents, per 100 000 individuals per year.
A substantial proportion of people do not adhere adequately to cardiovascular medications, and the prevalence of suboptimal adherence is similar across all individual CVD medications. Absolute and relative risk assessments demonstrate that a considerable proportion of all CVD events (~9% in Europe) could be attributed to poor adherence to vascular medications alone, and that the level of optimal adherence confers a significant inverse association with subsequent adverse outcomes. Measures to enhance adherence to help maximize the potentials of effective cardiac therapies in the clinical setting are urgently required.
Limited evidence is available about the association between serum uric acid and sub-stages of the spectrum from normoglycaemia to type 2 diabetes mellitus. We aimed to investigate the association ...between serum uric acid and risk of prediabetes and type 2 diabetes mellitus.
Eligible participants of the Rotterdam Study (n = 8,367) were classified into mutually exclusive subgroups of normoglycaemia (n = 7,030) and prediabetes (n = 1,337) at baseline. These subgroups were followed up for incident prediabetes (n = 1,071) and incident type 2 diabetes mellitus (n = 407), respectively. We used Cox proportional hazard models to determine hazard ratios (HRs) for incident prediabetes among individuals with normoglycaemia and incident type 2 diabetes mellitus among individuals with prediabetes.
The mean duration of follow-up was 7.5 years for incident prediabetes and 7.2 years for incident type 2 diabetes mellitus. A standard deviation increment in serum uric acid was significantly associated with incident prediabetes among individuals with normoglycaemia (HR 1.10, 95% confidence interval (CI) 1.01; 1.18), but not with incident type 2 diabetes mellitus among individuals with prediabetes (HR 1.07, 95% CI 0.94; 1.21). Exclusion of individuals who used diuretics or individuals with hypertension did not change our results. Serum uric acid was significantly associated with incident prediabetes among normoglycaemic women (HR 1.13, 95% CI 1.02; 1.25) but not among normoglycaemic men (HR 1.08, 95% CI 0.96; 1.21). In contrast, serum uric acid was significantly associated with incident type 2 diabetes mellitus among prediabetic men (HR 1.23, 95% CI 1.01; 1.48) but not among prediabetic women (HR 1.00, 95% CI 0.84; 1.19).
Our findings agree with the notion that serum uric acid is more closely related to early-phase mechanisms in the development of type 2 diabetes mellitus than late-phase mechanisms.
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