IntroductionObesity has emerged as one of the major risk factors of severe morbidity and cause-specific mortality among severe acute respiratory syndromes coronavirus-2 (SARS-CoV-2) infected individuals. Patients with obesity also have overlapping cardiovascular diseases and diabetes, which make them increasingly vulnerable. This novel ecological study examines the impact of obesity and/or body mass index (BMI) on rates of population-adjusted cases and deaths due to coronavirus diseases 2019 (COVID-19).Material and methodsPublicly available datasets were used to obtain relevant data on COVID-19, obesity and ecological variables. Group-wise comparisons and multivariate logistic regression analyses were performed. The receiver operating characteristic curve (ROC) was plotted to compute the area under the curve.ResultsWe demonstrate that male BMI is an independent predictor of cause-specific (COVID-19) mortality, and not of the caseload per million population. Countries with obesity rates of 20-30% had a significantly higher (approximately double) number of deaths per million population to both those in <20% and >30% slabs. We postulate that there may be a U-shaped paradoxical relationship between obesity and COVID-19 with cause-specific mortality burden more pronounced in the countries with 20-30% obesity rates. These findings are novel along with the methodological approach of doing ecological analyses on country-wide data from publicly available sources.ConclusionsWe anticipate, in light of our findings, that appropriate targeted public health approaches or campaigns could be developed to minimize risk and cause-specific morbidity burden due to COVID-19 in countries with nationwide obesity rates of 20-30%.

A total of 897 devices were implanted (22 implants were excluded due to missing information, n¼875). Baseline characteristics are shown in Table I. The mean age was 63 AE13; 82% were male; mean ejection fraction of 0.31 AE0.13 and 62% of implants were for primary prevention. Of the procedures performed, 64% were new implants, 29% were generator changes, and 10% were upgrades. The majority of ICD implants met 'appropriate' (91%) and class I indications (70%) while no procedures had a class III indications (Figure 1). Non-adherence to appropriate use criteria was demonstrated in 14% (n¼48) of implants. Reasons for non-adherence included no existing appropriate use criteria (n¼32, 67%), recent revascularization (n¼8, 17%), research participation (n¼4, 8%) and recent myocardial infarction (n¼4, 8%). CONCLUSION: In this population-based study, we found that our formal process of specialist evaluation and peerreviewed consensus was highly effective at achieving consistency with appropriate use criteria and guideline-derived recommendations.

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