Posters
Academic Level (Author 1)
Medical Student
Discipline Track
Clinical Science
Abstract
Background: The effects of the COVID-19 pandemic on mental health and body weight have been well documented, however a possible direction of the causality of the relationship between depression and weight as affected by lockdown measures has not been studied. This study examined if depression was associated with changes in BMI during the COVID-19 lockdown. We hypothesized that depressed adults (DEP) would have a greater increase in BMI than non-depressed adults (NDEP), and that greater pre-post changes in BMI would be observed among younger DEP compared to middle-aged and older DEP and NDEP.
Methods: Retrospective cohort study design using EHR from a family medicine university clinic. Included were adults > 18 years who visited the clinic within a 6-month period prior to lockdown and at least once in the 6-month post-lockdown period. Diagnosis of depression, BMI, and potential confounding variables were obtained from EHR. Mann-Whitney U was used to compare median change in BMI between DEP and NDEP. Simple linear regression was used to identify the relationship between DEP and BMI change. Multiple linear regression was used to control for age, sex, race/ethnicity, medications, and chronic conditions; and to predict age effects in BMI change while stratified by DEP and NDEP.
Results: There was a significant difference in BMI change (p=<0.001) between DEP and NDEP. DEP significantly predicted BMI change (p = <0.001]) post lockdown. This significance was maintained even while including confounding variables in the model (p=0.009). Age between 31 and 50 significantly predicted BMI change in NDEP while controlling for confounding variables (p = 0.027).
Conclusion: This study demonstrated that individuals with depression had significant changes in BMI during the COVID-19 pandemic and age predicted these changes in middle aged adults (30-50 years old). The significance of this finding places an importance in identifying and following up with individuals with a depression diagnosis given the effects on their BMI in extended isolation periods. Future studies could investigate other variables that might impact BMI change to influence the directionality of this relationship. Providing insight into this relationship could enable providers to inform patients that might be at risk for these types of changes over extended periods of isolation, and hopefully result in positive patient health outcomes.
Presentation Type
Poster
Recommended Citation
Arellano Villanueva, Elias and Fulda, Kimberly, "Bodyweight Changes During COVID-19 for Patients Diagnosed with Depression: A Retrospective Cohort Study" (2024). Research Colloquium. 13.
https://scholarworks.utrgv.edu/colloquium/2023/posters/13
Included in
Bodyweight Changes During COVID-19 for Patients Diagnosed with Depression: A Retrospective Cohort Study
Background: The effects of the COVID-19 pandemic on mental health and body weight have been well documented, however a possible direction of the causality of the relationship between depression and weight as affected by lockdown measures has not been studied. This study examined if depression was associated with changes in BMI during the COVID-19 lockdown. We hypothesized that depressed adults (DEP) would have a greater increase in BMI than non-depressed adults (NDEP), and that greater pre-post changes in BMI would be observed among younger DEP compared to middle-aged and older DEP and NDEP.
Methods: Retrospective cohort study design using EHR from a family medicine university clinic. Included were adults > 18 years who visited the clinic within a 6-month period prior to lockdown and at least once in the 6-month post-lockdown period. Diagnosis of depression, BMI, and potential confounding variables were obtained from EHR. Mann-Whitney U was used to compare median change in BMI between DEP and NDEP. Simple linear regression was used to identify the relationship between DEP and BMI change. Multiple linear regression was used to control for age, sex, race/ethnicity, medications, and chronic conditions; and to predict age effects in BMI change while stratified by DEP and NDEP.
Results: There was a significant difference in BMI change (p=<0.001) between DEP and NDEP. DEP significantly predicted BMI change (p = <0.001]) post lockdown. This significance was maintained even while including confounding variables in the model (p=0.009). Age between 31 and 50 significantly predicted BMI change in NDEP while controlling for confounding variables (p = 0.027).
Conclusion: This study demonstrated that individuals with depression had significant changes in BMI during the COVID-19 pandemic and age predicted these changes in middle aged adults (30-50 years old). The significance of this finding places an importance in identifying and following up with individuals with a depression diagnosis given the effects on their BMI in extended isolation periods. Future studies could investigate other variables that might impact BMI change to influence the directionality of this relationship. Providing insight into this relationship could enable providers to inform patients that might be at risk for these types of changes over extended periods of isolation, and hopefully result in positive patient health outcomes.