Obesity is an Independent Risk Factor for In-Hospital Mortality among Patients Admitted for Heart Failure: A National Study

Background Obesity is a major risk factor for developing chronic conditions such as cardiovascular disease and diabetes. However, the phenomenon of "obesity paradox" has been reported over the past two decades which makes the relationship between BMI and inpatient mortality unclear. Methods This study identified adult patients (aged 18 years or older) who were admitted to hospitals for the primary cause of heart failure during 2017-2019 from the Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) database. Baseline characteristics (i.e., weight status, age, gender, race, Elixhauser score) at the time of admission and the comorbidities were collected. Associations between weight status and in-hospital mortality were examined using logistic regression models that adjusted for individual comorbidities and global risk measures. The likelihood of patients developing each disease comorbidity under different obesity states was examined using logistic regression and the odds were compared across all the disease comorbidities. Results The study identified 204,970 hospital admissions with 4,290 (2.1%) deaths during the hospitalization and 200,680 (97.9%) live discharges. Analysis that did not adjust for individual comorbidities demonstrated the paradox. However, when adjusting for individual comorbidities and global risk measures and compared to the normal-weight patients, those who had higher BMI had an increased risk for in-hospital mortality. BMI of 35-39.9 group had a 26.5% higher likelihood of in-hospital mortality (OR=1.265, 95% CI: 1.066 - 1.503); BMI of 40-69.9 groups was 61.0% to 83.8% higher odds to die in hospital (OR ranged from 1.610 to 1.838, 95% CI varied); patients with a BMI of 70 and above had higher odds of in-hospital mortality (OR=3.144, 95%CI: 2.351 - 4.203). Conclusion Obesity is an independent risk factor for in-hospital mortality among patients who were admitted for heart failure. Adjustment for individual comorbidities resolves the obesity paradox. Patients with obesity have a different spectrum of diseases compared to non-obese patients, which may lead to the obesity paradox and bias in the inpatient outcome evaluation. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement No external funding was received. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Health Care Cost and Utilization Project (H-CUP) at AHRQ approved usage of the data for the research. The data was de-identified. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The data that support the findings of this study are available from Health Care Cost and Utilization Project (H-CUP) at AHRQ. Restrictions apply to the availability of these data, which were used under approval for this study. Data are available https://hcup-us.ahrq.gov/db/nation/nis/nisdbdocumentation.jsp with the permission of AHRQ.