From the clinic to the community: Can health system data accurately estimate population obesity prevalence?

Impact of employment status and work setting on body weight and health behaviors among people with obesity

BACKGROUND

The impact of employment and the work-from-home (WFH) setting on body weight among people with obesity is unknown.

OBJECTIVE

This study examined the relationship between employment status, WFH setting, and change in body weight among adults with obesity during the COVID-19 pandemic.

METHODS

Patients from an obesity medicine clinic completed an online survey in 2022 to assess health, work, and lifestyle behaviors. Multiple regression models examined the association between WFH status and change in body weight.

RESULTS

The analytical sample included 380 patients (81.9% female, mean age 52.5 years, mean body mass index 43.25, 50.0% non-Hispanic White, 25.7% non-Hispanic Black, 18.7% Hispanic, 5.7% other ethnicity). During the pandemic, 28.7% were employed in a WFH setting (73.4% of this subgroup were in a WFH setting only), 36.1% were employed but not in a WFH setting, 11.8% were unemployed, and 23.4% were retired. Mean body weight change for participants who partially WFH during the pandemic was +5.4 (±7.2) % compared to those completely WFH -0.3 (±9.8) % (P = 0.006). After adjusting for key demographics, participants who were partially WFH gained 7.8% more weight compared to those completely WFH (β= 7.28, SE = 1.91, p < 0.001). The most significant predictors for weight gain after adjusting for WFH frequency (partially vs. completely) included overeating (aOR 11.07, 95% CI 3.33-36.77), more consumption of fast food (aOR 7.59, 95% 2.41-23.91), and depression (aOR 6.07, 95% CI 1.97-18.68).

CONCLUSION

These results show that during the COVID-19 pandemic, the WFH hybrid (combination of office and WFH) setting is associated with greater weight gain compared to those who completely WFH in people with obesity. Risk factors include overeating, higher fast food consumption, and depression.

Geospatial divide in real-world EHR data: Analytical workflow to assess regional biases and potential impact on health equity

Real-world data (RWD) like electronic health records (EHR) has great potential for secondary use by health systems and researchers. However, collected primarily for efficient health care, EHR data may not equitably represent local regions and populations, impacting the generalizability of insights learned from it. We assessed the geospatial representativeness of regions in a large health system EHR data using a spatial analysis workflow, which provides a data-driven way to quantify geospatial representation and identify adequately represented regions. We applied the workflow to investigate geospatial patterns of overweight/obesity and depression patients to find regional "hotspots" for potential targeted interventions. Our findings show the presence of geospatial bias in EHR and demonstrate the workflow to identify spatial clusters after adjusting for bias due to the geospatial representativeness. This work highlights the importance of evaluating geospatial representativeness in RWD to guide targeted deployment of limited healthcare resources and generate equitable real-world evidence.

Changes in body weight, health behaviors, and mental health in adults with obesity during the COVID-19 pandemic

OBJECTIVE

The aim of this study was to examine the relationships between body weight changes, health behaviors, and mental health in adults with obesity during the second year of the COVID-19 pandemic.

METHODS

Between March 1, 2021, and November 30, 2021, adults from three obesity practices completed an online survey. The primary outcomes were ≥ 5% of body weight change since March 2020 and associated health behaviors and mental health factors.

RESULTS

The sample (n = 404) was 82.6% female (mean age 52.5 years, mean BMI 43.3 kg/m² ). Mean weight change was + 4.3%. Weight gain ≥ 5% was reported by 30% of the sample, whereas 19% reported ≥ 5% body weight loss. The degree of both weight gain and weight loss correlated positively with baseline BMI. Eighty percent of the sample reported difficulties with body weight regulation. Those who gained ≥ 5% versus those who lost ≥ 5% body weight were more likely to report higher levels of stress, anxiety, and depression; less sleep and exercise; less healthy eating and home-cooked meals; and more takeout foods, comfort foods, fast foods, overeating, and binge eating.

CONCLUSIONS

Weight gain in adults with obesity during the COVID-19 pandemic is associated with higher baseline BMI, deteriorations in mental health, maladaptive eating behaviors, and less physical activity and sleep. Further research is needed to identify effective interventions for healthier minds, behaviors, and body weight as the pandemic continues.