The Association of Pension Income with the Incidence of Type I Obesity among Retired Israelis

Do Ultra-Orthodox Israeli Jews Suffer more than Secular Israeli Jews from Obesity? Gender, Cohort Effect and the Yule-Simpson Paradox

The Yule-Simpson paradox indicates contradicting statistical outcomes for the pooled sample and for each stratified group separately. The objective of the current study is to demonstrate this paradox. The sample is based on a 2015-2016 longitudinal survey carried out by the Israeli Central Bureau of Statistics. The sample includes 1194 individuals, where the responses of 1140 individuals were assessed twice (in 2015 and 2016) and the responses of 54 individuals were recorded only once. This gives a total sample of 2334 observations × years. The sample includes 609 females and 585 males. We use the limited dependent binary probit regression model. The dependent variable is a dummy variable that equals 1 if the individual is obese (BMI ≥ 30, where BMI = WEIGHT ÷ (HEIGHT²), WEIGHT is measured in kilograms and HEIGHT is measured in meters) and zero otherwise. The independent variables are the denomination (secular vs. ultra-Orthodox) and age in years. Findings suggest that on the one hand, for the pooled sample of 21-50-year-old females and males, results clearly support the conclusion that compared with secular Israeli Jews, projected probability of obesity (BMI ≥ 30) among ultra-Orthodox Israeli Jews is higher (p = 0.0128). On the other hand, when stratified by gender, one cannot reject the opposite conclusion, according to which projected probability of obesity is equal for all cohorts among ultra-Orthodox and secular Israeli Jews. Research findings thus stress the importance of cautious and rigorous statistical analysis and robustness tests prior to statistical inference.

Can Obesity Prevalence Explain COVID-19 Indicators (Cases, Mortality, and Recovery)? A Comparative Study in OECD Countries

SARS-CoV-2 virus disease (COVID-19) is declared a global pandemic with multiple risk factors. Obesity is considered by several researchers as one of the serious risk factors for SARS-CoV-2 virus complications based on recent empirical studies. Yet, other scholars argue in favor of the existence of an obesity survival paradox and criticize the former group of studies on the grounds that they lack controls for race, socioeconomic status, or quality of care. The objective of the current study is to analyze the potential relationships between different SARS-CoV-2 virus indicators and obesity on a country-wide level based on an OECD report. In an attempt to test the counterintuitive possibility of an obesity survival paradox, the proposed empirical model relaxes the assumption of monotonic change by applying the quadratic design and testing which one of the two competing models (i.e., quadratic or linear) better fits the data. Findings suggest more complex relationships between SARS-CoV-2 virus indices and obesity rates than previously thought. Consequently, ethical guidelines referring to priority in intubation and intensive care treatments-published by the Israeli Ministry of Health in April 2020-should account for these complex relationships between obesity and SARS-CoV-2 virus. Indeed, there is a linear increase in mortality rate from SARS-CoV-2 virus with an elevated prevalence of obesity. Yet, other indicators, such as the number of infected per 10,00,000 persons, rates of severe SARS-CoV-2 virus cases, rates of recovered SARS-CoV-2 virus patients, and SARS-CoV-2 virus, as the cause of death exhibit quadratic, rather than linear, patterns. The reasons for these nonlinear patterns might be explained by several conditions such as increased metabolic reserves, more aggressive treatment, other non-SARS-CoV-2 virus complications for obese persons, and unidentified factors that should be examined in future research.

Can reduction in infection and mortality rates from coronavirus be explained by an obesity survival paradox? An analysis at the US statewide level

Coronavirus disease 2019 (COVID-19) is a declared global pandemic with multiple risk factors. Based on recent empirical studies, obesity is considered by several researchers as one of the serious risk factors for coronavirus-related complications. Yet, other scholars argue in favor of the existence of an obesity survival paradox. The objective of the current study is to analyze the potential relationships between different corona indicators and obesity on a statewide level. Since the United States is ranked as one of the OECD countries with a high level of overweight and obesity among its citizens—the majority of US states exceed the 30% benchmark of obese population—it is an especially interesting case study to explore this issue. In an attempt to estimate projected probabilities for infection by coronavirus and mortality rates as a function of obesity prevalence, the fractional logit regression is employed. Findings may support the counter-intuitive possibility of an obesity survival paradox. Consequently, ethical guidelines referring to priority in intubation and intensive care treatments should account for these complex relationships between obesity and corona. Both projected rates of infection and mortality drop with elevated prevalence of obesity. The reasons for these findings might be explained by several conditions such as elevated social distancing from more obese persons, increased metabolic reserves, more aggressive treatment, and unidentified factors that should be examined in future research.