In 2021, around 16 percent of deaths in Bahrain were attributed to obesity, while around nine percent of deaths in the United States were attributed to obesity. This statistic shows the percentage of deaths in select countries worldwide that were attributed to obesity in 2021.

In 2021, there were almost *** deaths per 100,000 population in Egypt due to obesity, while the death rate for the United States was around ** per 100,000 population. This statistic shows the rate of deaths attributed to obesity in select countries worldwide in 2021.

In 2022, the states with the highest death rates due to heart disease were Oklahoma, Mississippi, and Alabama. That year, there were around 257 deaths due to heart disease per 100,000 population in the state of Oklahoma. In comparison, the overall death rate from heart disease in the United States was 167 per 100,000 population. The leading cause of death in the United States Heart disease is the leading cause of death in the United States, accounting for 21 percent of all deaths in 2022. That year, cancer was the second leading cause of death, followed by unintentional injuries and COVID-19. In the United States, a person has a one in six chance of dying from heart disease. Death rates for heart disease are higher among men than women, but both have seen steady decreases in heart disease death rates since the 1950s. What are risk factors for heart disease? Although heart disease is the leading cause of death in the United States, the risk of heart disease can be decreased by avoiding known risk factors. Some of the leading preventable risk factors for heart disease include smoking, heavy alcohol use, physical inactivity, an unhealthy diet, and being overweight or obese. It is no surprise that the states with the highest rates of death from heart disease are also the states with the highest rates of heart disease risk factors. For example, Oklahoma, the state with the highest heart disease death rate, is also the state with the third-highest rate of obesity. Furthermore, Mississippi is the state with the highest levels of physical inactivity, and it has the second-highest heart disease death rate in the United States.

All data relating to Obesity and mortality during the coronavirus (COVID-19) pandemic, England: 24 January 2020 to 30 August 2022

ObjectiveTo investigate the potential correlation between body mass index (BMI) and the 28-day mortality rate among sepsis patients and the gender difference in this association.DesignThe current research was a retrospective cohort study.ParticipantsA total of 14,883 male and female cohorts of sepsis patients were included in the Medical Information Mart for Intensive Care IV (MIMIC-IV V2.2) database. Patients in each gender cohort were further classified as underweight, normal weight, overweight, or obese according to BMI and the World Health Organization (WHO) BMI categories.OutcomesThe 28-day mortality from the date of ICU hospitalization was the primary outcome measure.ResultsThe BMI and 28-day mortality exhibited an L-shaped relationship (p for nonlinearity

In 2021, it was estimated that the rate of premature death attributable to obesity worldwide was around 44.2 per 100,000 population. The countries/territories with the highest rates of premature death attributable to obesity included Nauru, Fiji, and the Marshall Islands. This statistic shows the countries/territories with the highest rates of premature death attributable to obesity worldwide in 2021.

Layers in this service includes: Birth, Cancer, Hospitalization Discharge, Mortality and STI Rates, as well as Demographics.

Layers in this service includes: Birth, Cancer, Hospitalization Discharge, Mortality and STI Rates, as well as Demographics.

Mutually adjusted mortality rate ratios (MRRs) with 95% confidence intervals (CIs) for all-cause mortality (n = 41,023).

BackgroundObesity affects the course of critical illnesses. We aimed to estimate the association of obesity with the severity and mortality in coronavirus disease 2019 (COVID-19) patients.Data SourcesA systematic search was conducted from the inception of the COVID-19 pandemic through to 13 October 2021, on databases including Medline (PubMed), Embase, Science Web, and Cochrane Central Controlled Trials Registry. Preprint servers such as BioRxiv, MedRxiv, ChemRxiv, and SSRN were also scanned.Study Selection and Data ExtractionFull-length articles focusing on the association of obesity and outcome in COVID-19 patients were included. Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines were used for study selection and data extraction. Our Population of interest were COVID-19 positive patients, obesity is our Intervention/Exposure point, Comparators are Non-obese vs obese patients The chief outcome of the study was the severity of the confirmed COVID-19 positive hospitalized patients in terms of admission to the intensive care unit (ICU) or the requirement of invasive mechanical ventilation/intubation with obesity. All-cause mortality in COVID-19 positive hospitalized patients with obesity was the secondary outcome of the study.ResultsIn total, 3,140,413 patients from 167 studies were included in the study. Obesity was associated with an increased risk of severe disease (RR=1.52, 95% CI 1.41-1.63, p

ObjectiveTo evaluate the association between overweight and obesity on the clinical course and outcomes in patients hospitalized with COVID-19.DesignRetrospective, observational cohort study.MethodsWe performed a multicenter, retrospective, observational cohort study of hospitalized COVID-19 patients to evaluate the associations between overweight and obesity on the clinical course and outcomes.ResultsOut of 1634 hospitalized COVID-19 patients, 473 (28.9%) had normal weight, 669 (40.9%) were overweight, and 492 (30.1%) were obese. Patients who were overweight or had obesity were younger, and there were more women in the obese group. Normal-weight patients more often had pre-existing conditions such as malignancy, or were organ recipients. During admission, patients who were overweight or had obesity had an increased probability of acute respiratory distress syndrome [OR 1.70 (1.26-2.30) and 1.40 (1.01-1.96)], respectively and acute kidney failure [OR 2.29 (1.28-3.76) and 1.92 (1.06-3.48)], respectively. Length of hospital stay was similar between groups. The overall in-hospital mortality rate was 27.7%, and multivariate logistic regression analyses showed that overweight and obesity were not associated with increased mortality compared to normal-weight patients.ConclusionIn this study, overweight and obesity were associated with acute respiratory distress syndrome and acute kidney injury, but not with in-hospital mortality nor length of hospital stay.

In 2021, it was estimated that around 5.3 percent of deaths worldwide could be attributed to obesity. The countries/territories with the highest share of deaths that could be attributed to obesity included the Cook Islands, Fiji, and American Samoa. This statistic shows the countries/territories with the highest share of deaths attributable to obesity worldwide in 2021.

Obesity traits are causally implicated with risk of cardiometabolic diseases. It remains unclear whether there are similar causal effects of obesity traits on other non-communicable diseases. Also, it is largely unexplored whether there are any sex-specific differences in the causal effects of obesity traits on cardiometabolic diseases and other leading causes of death. We constructed sex-specific genetic risk scores (GRS) for three obesity traits; body mass index (BMI), waist-hip ratio (WHR), and WHR adjusted for BMI, including 565, 324, and 337 genetic variants, respectively. These GRSs were then used as instrumental variables to assess associations between the obesity traits and leading causes of mortality in the UK Biobank using Mendelian randomization. We also investigated associations with potential mediators, including smoking, glycemic and blood pressure traits. Sex-differences were subsequently assessed by Cochran’s Q-test (Phet). A Mendelian randomization analysis of 228,466 women and 195,041 men showed that obesity causes coronary artery disease, stroke (particularly ischemic), chronic obstructive pulmonary disease, lung cancer, type 2 and 1 diabetes mellitus, non-alcoholic fatty liver disease, chronic liver disease, and acute and chronic renal failure. Higher BMI led to higher risk of type 2 diabetes in women than in men (Phet = 1.4×10−5). Waist-hip-ratio led to a higher risk of chronic obstructive pulmonary disease (Phet = 3.7×10−6) and higher risk of chronic renal failure (Phet = 1.0×10−4) in men than women. Obesity traits have an etiological role in the majority of the leading global causes of death. Sex differences exist in the effects of obesity traits on risk of type 2 diabetes, chronic obstructive pulmonary disease, and renal failure, which may have downstream implications for public health.

Data set from Ranucci M, de Vincentiis C, Menicanti L, La Rovere MT, Pistuddi V. A gender-based analysis of the obesity paradox in cardiac surgery: height for women, weight for men? Eur J Cardiothorac Surg. 2019 Jul 1;56(1):72-78. doi: 10.1093/ejcts/ezy454. PMID: 30657927.

This is the abstract:

Objectives: In cardiac surgery, obesity is associated with a lower mortality risk. This study aims to investigate the association between body mass index (BMI) and operative mortality separately in female patients and male patients undergoing cardiac surgery and to separate the effects of weight and height in each gender-based cohort of patients.

Methods: A retrospective cohort study including 7939 consecutive patients who underwent cardiac surgery was conducted. The outcome measure was the operative mortality.

Results: In men, there was a U-shaped relationship between the BMI and the operative mortality, with the lower mortality rate at a BMI of 35 kg/m2. In women, the relationship is J-shaped, with the lower mortality at a BMI of 22 kg/m2. Female patients with obesity class II-III had a relative risk for operative mortality of 2.6 [95% confidence interval (CI) 1.37-4.81, P = 0.002]. The relationship between weight and mortality rate is a U-shaped bot in men and women, with the lower mortality rate at 100 kg for men and 70 kg for women. Height was linearly and inversely associated with the operative mortality in men and women. After correction for the potential confounders, height, but not weight, was independently associated with operative mortality in women (odds ratio 0.949, 95% CI 0.915-0.983; P = 0.004); conversely, in men, this association exists for weight (odds ratio 1.017, 95% CI 1.001-1.032; P = 0.034), but not height.

Conclusions: Contrary to men, in women obesity does not reduce the operative mortality in cardiac surgery, whereas the height seems to be associated with a lower mortality.

Layers in this service includes: Birth, Cancer, Hospitalization Discharge, Mortality and STI Rates, as well as Demographics.

BackgroundObesity is associated with increased mortality and accelerated decline in kidney function in the general population. Little is known about the effect of obesity in younger and older pre-dialysis patients. The aim of this study was to assess the extent to which obesity is a risk factor for death or progression to dialysis in younger and older patients on specialized pre-dialysis care.MethodIn a multicenter Dutch cohort study, 492 incident pre-dialysis patients (>18y) were included between 2004–2011 and followed until start of dialysis, death or October 2016. We grouped patients into four categories of baseline body mass index (BMI): <20, 20–24 (reference), 25–29, and ≥30 (obesity) kg/m2 and stratified patients into two age categories (<65y or ≥65y).ResultsThe study population comprised 212 patients younger than 65 years and 280 patients 65 years and older; crude cumulative risk of dialysis and mortality at the end of follow-up were 66% and 4% for patients <65y and 64% and 14%, respectively, for patients ≥65y. Among the <65y patients, the age-sex standardized combined outcome rate was 2.3 times higher in obese than those with normal BMI, corresponding to an excess rate of 35 events/100 patient-years. After multivariable adjustment the hazard ratios (HR) (95% CI) for the combined endpoint by category of increasing BMI were, for patients <65y, 0.92 (0.41–2.09), 1 (reference), 1.76 (1.16–2.68), and 1.81 (1.17–2.81). For patients ≥65y the BMI-specific HRs were 1.73 (0.97–3.08), 1 (reference), 1.25 (0.91–1.71) and 1.30 (0.79–1.90). In the competing risk analysis, taking dialysis as the event of interest and death as a competing event, the BMI-specific multivariable adjusted subdistribution HRs (95% CI) were, for patients <65y, 0.90 (0.38–2.12), 1 (reference), 1.47 (0.96–2.24) and 1.72 (1.15–2.59). For patients ≥65y the BMI-specific SHRs (95% CI) were 1.68 (0.93–3.02), 1 (reference), 1.50 (1.05–2.14) and 1.80 (1.23–2.65).ConclusionWe found that obesity in younger pre-dialysis patients and being underweight in older pre-dialysis patients are risk factors for starting dialysis and for death, compared with those with a normal BMI.

The objective of this study was to compare the effect of diabetes and pathologies potentially related to diabetes on the risk of infection and death from COVID-19 among people from Highly-Developed-Country (HDC), including Italians, and immigrants from the High-Migratory-Pressure-Countries (HMPC). Among the population with diabetes, whose prevalence is known to be higher among immigrants, we compared the effect of body mass index among HDC and HMPC populations. A population-based cohort study was conducted, using population registries and routinely collected surveillance data. The population was stratified into HDC and HMPC, according to the place of birth; moreover, a focus was set on the South Asiatic population. Analyses restricted to the population with type-2 diabetes were performed. We reported incidence (IRR) and mortality rate ratios (MRR) and hazard ratios (HR) with 95% confidence interval (CI) to estimate the effect of diabetes on SARS-CoV-2 infection and COVID-19 mortality. Overall, IRR of infection and MRR from COVID-19 comparing HMPC with HDC group were 0.84 (95% CI 0.82–0.87) and 0.67 (95% CI 0.46–0.99), respectively. The effect of diabetes on the risk of infection and death from COVID-19 was slightly higher in the HMPC population than in the HDC population (HRs for infection: 1.37 95% CI 1.22–1.53 vs. 1.20 95% CI 1.14–1.25; HRs for mortality: 3.96 95% CI 1.82–8.60 vs. 1.71 95% CI 1.50–1.95, respectively). No substantial difference in the strength of the association was observed between obesity or other comorbidities and SARS-CoV-2 infection. Similarly for COVID-19 mortality, HRs for obesity (HRs: 18.92 95% CI 4.48–79.87 vs. 3.91 95% CI 2.69–5.69) were larger in HMPC than in the HDC population, but differences could be due to chance. Among the population with diabetes, the HMPC group showed similar incidence (IRR: 0.99 95% CI: 0.88–1.12) and mortality (MRR: 0.89 95% CI: 0.49–1.61) to that of HDC individuals. The effect of obesity on incidence was similar in both HDC and HMPC populations (HRs: 1.73 95% CI 1.41–2.11 among HDC vs. 1.41 95% CI 0.63–3.17 among HMPC), although the estimates were very imprecise. Despite a higher prevalence of diabetes and a stronger effect of diabetes on COVID-19 mortality in HMPC than in the HDC population, our cohort did not show an overall excess risk of COVID-19 mortality in immigrants.

In 2019, it was estimated that the total annual disability and mortality costs attributable to obesity in Canada were around 16.1 billion Canadian dollars. The total disability and mortality costs for males was 8.4 billion Canadian dollars. This graph shows the total annual disability and mortality costs attributable to obesity in Canada in 2019, by gender.

Abstract INTRODUCTION: Severe acute respiratory syndrome coronavirus 2 has infected more than 9,834,513 Brazilians up to February 2021. Knowledge of risk factors of coronavirus disease among Brazilians remains scarce, especially in the adult population. This study verified the risk factors for intensive care unit admission and mortality for coronavirus disease among 20-59-year-old Brazilians. METHODS: A Brazilian database on respiratory illness was analyzed on October 9, 2020, to gather data on age, sex, ethnicity, education, housing area, and comorbidities (cardiovascular disease, diabetes, and obesity). Multivariate logistic regression analysis was performed to identify the risk factors for coronavirus disease. RESULTS: Overall, 1,048,575 persons were tested for coronavirus disease; among them, 43,662 were admitted to the intensive care unit, and 34,704 patients died. Male sex (odds ratio=1.235 and 1.193), obesity (odds ratio=1.941 and 1.889), living in rural areas (odds ratio=0.855 and 1.337), and peri-urban areas (odds ratio=1.253 and 1.577) were predictors of intensive care unit admission and mortality, respectively. Cardiovascular disease (odds ratio=1.552) was a risk factor for intensive care unit admission. Indigenous people had reduced chances (odds ratio=0.724) for intensive care unit admission, and black, mixed, East Asian, and indigenous ethnicity (odds ratio=1.756, 1.564, 1.679, and 1.613, respectively) were risk factors for mortality. CONCLUSIONS: Risk factors for intensive care unit admission and mortality among adult Brazilians were higher in men, obese individuals, and non-urban areas. Obesity was the strongest risk factor for intensive care unit admission and mortality.