Obesity Management in Primary Care During and Beyond the COVID-19 Pandemic

Primary Care Clinicians' Perceived Role in Addressing Childhood Obesity in the Southern United States

OBJECTIVES

Primary care is an opportune setting to promote healthy behaviors for children and families. In 2007, an expert committee recommended that pediatric primary care clinicians assess nutrition and physical activity at wellness visits and offer recommendations; however, little is known about what pediatric primary care clinicians perceive their role as in childhood weight management. This qualitative study aimed to describe the perceived role of pediatric primary care clinicians in the prevention and treatment of childhood obesity in South Carolina, a state in the southern United States with high rates of childhood obesity.

METHODS

Pediatric primary care clinicians (n = 23) from South Carolina were recruited for two focus groups. Participants were asked semistructured, open-ended questions, and audio recordings were transcribed verbatim. Themes and subthemes were identified through an iterative coding and consensus-building process with two coders. Excerpts coded under the parent code of "clinician role" centered on three themes: conducting assessments, making referrals, and providing education.

RESULTS

Pediatric primary care clinicians in South Carolina coalesced around the important role of addressing childhood obesity within primary care. Notably, clinicians primarily discussed treatment rather than prevention strategies and described changes in the scope of their practice over time as a result of the increasing numbers of pediatric patients with obesity.

CONCLUSIONS

Addressing childhood obesity within primary care is a critical component of obesity prevention and treatment in the southern United States. Effective, sustainable prevention and treatment within primary care will depend on the involvement of pediatric clinicians, thus emphasizing the importance of understanding how they perceive their role within this setting.

Association of Patient Characteristics, Diabetes, BMI, and Obesity With Severe COVID-19 in Metropolitan Detroit, MI

Identification of specific risk factors for severe coronavirus disease 2019 (COVID-19) is crucial for prevention of poor outcomes and mortality. This retrospective cohort study of patients hospitalized with COVID-19 demonstrated that older age, male sex, Black race, diabetes, elevated BMI, and elevated inflammatory markers were correlated with critical illness in COVID-19. Older age, male sex, diabetes, and inflammatory markers, but not elevated BMI, were associated with mortality. Despite having greater odds of critical illness, Black patients had lower odds of death than White patients. Older age, male sex, diabetes, and elevated inflammatory markers were significantly associated with venous thromboembolism. These findings suggest a need to aggressively identify and manage modifiable risk factors (i.e., diabetes and elevated BMI) and encourage vaccination of at-risk individuals to prevent poor outcomes from COVID-19.

Impact of the COVID-19 pandemic lockdown on weight status and factors associated with weight gain among adults in Massachusetts

The study aims to examine the impact of the coronavirus disease-2019 (COVID-19) pandemic lockdown on weight, overweight and obesity, and identify factors associated with weight gain. At a safety net health system in Massachusetts, 11 534 adults were retrospectively followed within 3 months of the COVID-19 lockdown. Chi-square and 95% confidence intervals (CI) were reported for categorical and continues variables, respectively. Multivariate analyses were performed to identify factors associated with weight gain (≥0.01 kg and 5%). During the lockdown period, greater proportion of women gained weight compared to men (46.1% vs 40.6%, P < .01). The obesity rate after the lockdown increased among women (40.7%-41.7, P < .01) but decreased among men (39.6%-38.6, P < .01) compared to before the lockdown. Post-lockdown obesity rates increased among Haitian (51.2%-55.0%, P < .01) and Hispanic women (50.7%-51.8%, P < .01). More than 5% weight gain was associated with 18 to 39 vs ≥60 years of age (OR = 1.45, 95% CI = 1.07, 1.97), food and housing insecurity (OR = 1.44, 95% CI = 1.05, 1.97) and tobacco use (OR = 1.38, 95% CI = 1.07, 1.78) among men; and 18 to 39 vs ≥60 years of age (OR = 1.55, 95% CI = 1.25, 1.91), Hispanics (OR = 1.25, 95% CI = 1.01, 1.54), Brazilians (OR = 1.22, 95% CI = 1.03, 1.45), and tobacco use (OR = 1.36, 95% CI = 1.10, 1.69) among women. During the COVID-19 lockdown, significant proportion of participants gained weight, but subgroup variations existed. Our study can inform healthcare professionals about the impact of the lockdown on unhealthy weight gain and identify vulnerable populations. Strategies are needed to combat unhealthy weight gain during and beyond the pandemic.

Healthy Food on the Twitter Social Network: Vegan, Homemade, and Organic Food

Online social networks have become an everyday aspect of many people’s lives. Users spend more and more time on these platforms and, through their interactions on social media platforms, they create active and passive digital footprints. These data have a strong potential in many research areas; indeed, understanding people’s communication on social media is essential for understanding their attitudes, experiences, behaviors and values. Researchers have found that the use of social networking sites impacts eating behavior; thus, analyzing social network data is important for understanding the meaning behind expressions used in the context of healthy food. This study performed a communication analysis of data from the social network Twitter, which included 666,178 messages posted by 168,134 individual users. These data comprised all tweets that used the #healthyfood hashtag between 2019 and 2020 on Twitter. The results revealed that users most commonly associate healthy food with a healthy lifestyle, diet, and fitness. Foods associated with this hashtag were vegan, homemade, and organic. Given that people change their behavior according to other people’s behavior on social networks, these data could be used to identify current and future associations with current and future perceptions of healthy food characteristics.