Objective

To understand the impact of the coronavirus disease 2019 (COVID-19) pandemic on parental perceptions of health behaviors and food insecurity among children with overweight and obesity living in San Francisco and to assess the relationship between food insecurity and dietary intake during the pandemic.

Methods

Parents of children ages 4 to 12 in San Francisco with body mass index ≥85th percentile measured at a clinic visit at a Federally Qualified Health Center or academic practice from January 1st to March 15th, 2020 were eligible to participate. Parents completed a survey reporting on child health behaviors and household food insecurity prior to and since the start of the pandemic. Survey items were abstracted from validated surveys with adaptations. Regression models evaluated associations between food insecurity and dietary intake variables.

Results

Most participants (n = 145) were publicly insured (90%), Latino (77%), and spoke Spanish at home (70%). Parents perceived that child mean daily nonacademic screen time was higher during the pandemic compared to before (3.8 hours vs 1.6 hours). Mean daily physical activity was reported to be lower compared to prior to the pandemic (1 hour vs 1.8 hours). On average, reported bedtime shifted 1.6 hours later. Food insecurity increased significantly but was not associated with intake of fruits, vegetables, sugar-sweetened beverages, or foods with added sugar during the pandemic.

Conclusions

Parents of children with overweight or obesity in San Francisco perceive increased child screen time, decreased physical activity and later bedtimes during the COVID-19 pandemic. Findings suggest a need for policies that support healthy lifestyle behaviors among low-income children during the pandemic.

Pandemic mitigation measures may lead to excess weight gain in children. Our objective was to assess weight gain during the COVID-19 pandemic in children of ages 4-12 years with overweight and obesity in San Francisco, CA. Children with BMI ≥85th percentile measured at a clinic visit from January to March 2020 were recruited. Follow-up BMI measurements were obtained between October 2020 and March 2021 from the electronic medical record or through a video study visit. Pre- and post-BMI measurements were obtained on n = 91 participants. The majority were Latino (85%) and publicly insured (91%). Mean monthly weight gain was 0.73 kg [standard deviation (SD) 0.47], equivalent to yearly weight gain of 8.8 kg. Mean monthly change in BMI z-score was 0.02 (SD 0.04) equivalent to yearly increase in BMI-z of 0.24. Weight gain among children in San Francisco with overweight and obesity during the COVID-19 pandemic far exceeded healthy weight gain for this age group.

Introduction

The regular collection of 3-dimensional (3D) imaging data is critical to the development and implementation of accurate predictive models of facial skeletal growth. However, repeated exposure to x-ray-based modalities such as cone-beam computed tomography has unknown risks that outweigh many potential benefits, especially in pediatric patients. One solution is to make inferences about the facial skeleton from external 3D surface morphology captured using safe nonionizing imaging modalities alone. However, the degree to which external 3D facial shape is an accurate proxy of skeletal morphology has not been previously quantified. As a first step in validating this approach, we tested the hypothesis that population-level variation in the 3D shape of the face and skeleton significantly covaries.

Methods

We retrospectively analyzed 3D surface and skeletal morphology from a previously collected cross-sectional cone-beam computed tomography database of nonsurgical orthodontics patients and used geometric morphometrics and multivariate statistics to test the hypothesis that shape variation in external face and internal skeleton covaries.

Results

External facial morphology is highly predictive of variation in internal skeletal shape ([Rv] = 0.56, P <0.0001; partial least squares [PLS] 1-13 = 98.7% covariance, P <0.001) and asymmetry (Rv = 0.34, P <0.0001; PLS 1-5 = 90.2% covariance, P <0.001), whereas age-related (r(2) = 0.84, P <0.001) and size-related (r(2) = 0.67, P <0.001) shape variation was also highly correlated.

Conclusions

Surface morphology is a reliable source of proxy data for the characterization of skeletal shape variation and thus is particularly valuable in research designs where reducing potential long-term risks associated with radiologic imaging methods is warranted. We propose that longitudinal surface morphology from early childhood through late adolescence can be a valuable source of data that will facilitate the development of personalized craniodental and treatment plans and reduce exposure levels to as low as reasonably achievable.