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BACKGROUND: The influence of home obesogenic environments, as assessed by the validated Family Nutrition and Physical Activity (FNPA) tool, and child obesity during the COVID pandemic were evaluated using electronic health records in this retrospective cohort study. METHODS: Historical data on BMI and the FNPA screening tool were obtained from annual well-child visits within the Geisinger Health System. The study examined youth ages 2-17 that had a BMI record and an FNPA assessment prior to the pandemic (BMI 3/1/19-2/29/20), 1 BMI record 3 months into the pandemic (6/1/20-12/31/20) and 1 BMI in the second year of the pandemic (1/1/21-12/31/21). Tertiles of obesity risk by FNPA score were examined. Mixed-effects linear regression was used to examine change in BMI slope (kg/m2 per month) pre-pandemic to pandemic using FNPA summary and subscales scores as predictors and adjusting for confounding factors. RESULTS: The analyses included 6,746 children (males: 51.7%, non-Hispanic white: 86.6%, overweight:14.8%, obesity:10.3%, severe obesity: 3.9%; mean(SD) age: 5.7(2.8) years). The rate of BMI change in BMI was greatest from early pandemic compared to pre-pandemic for children in lowest versus highest tertiles of FNPA summary score (0.079 vs. 0.044 kg/m2), FNPA-Eating (0.068 vs. 0.049 kg/m2), and FNPA-Activity (0.078 vs. 0.052 kg/m2). FNPA summary score was significantly associated with change in BMI from the pre-pandemic to early pandemic period (p = 0.014), but not associated with change in BMI during the later pandemic period. CONCLUSIONS: This study provides additional insight into the changes in the rate of BMI change observed among children and adolescents in the United States during the COVID-19 pandemic. The FNPA provides ample opportunity to continue our exploration of the negative impact of the COVID-19 pandemic on the longitudinal growth patterns among children and adolescents.
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Índice de Masa Corporal , COVID-19 , Ambiente en el Hogar , Obesidad Infantil , SARS-CoV-2 , Humanos , COVID-19/epidemiología , Niño , Femenino , Masculino , Obesidad Infantil/epidemiología , Estudios Retrospectivos , Adolescente , Preescolar , Ejercicio Físico , PandemiasRESUMEN
Eating competence (EatC) is an intra-individual approach to eating attitudes and behaviors associated with greater well-being. EatC research has not included persons with confirmed metabolic syndrome (MetS). Therefore, EatC of persons with MetS was explored to identify unique associations and inform implementation of MetS lifestyle interventions using baseline data from a multisite, randomized trial of a 2-year lifestyle intervention with MetS. EatC, measured with the Satter Eating Competence Inventory 2.0 (ecSI 2.0™), was examined for relationships with bioclinical measures (e.g., blood pressure, lipids), medication use, BMI, waist circumference, fruit/vegetable intake, and psychosocial factors, (e.g., stress, mindfulness). Data were collected in person and video call by trained research personnel. EatC was examined as a continuous score and as a categorical variable with ecSI 2.0™ scores ≥ 32 considered eating competent. Participants (n = 618) were predominantly female (76%), White (74%), college educated (60%). Mean age was 55.5 ± 11 y. Mean ecSI 2.0™ was 29.9 ± 7.4 and 42% were eating competent. EatC was greater for males, persons who were older and food secure. Competent eaters (vs. non-eating competent) had lower waist circumference (112.7 ± 12.5 cm vs.116.8 ± 16.0 cm; P < 0.001) and BMI (35.0 ± 6.1 vs. 37.5 ± 7.3; P < 0.001). Serum triglycerides, HDL-cholesterol, fasting blood glucose, HbA1c, and blood pressure did not differ by EatC status. Compared to non-eating competent persons, competent eaters perceived less stress, were more mindful, indicated better physical function, and more habitual vegetable intake (all P < 0.001) and sensory awareness (P < 0.05). EatC in MetS paralleled the non-MetS profile. EatC was associated with a healthier psychosocial profile, waist circumference and BMI. Findings support further research to examine the mediational or moderating influence of EatC in the treatment of MetS.
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Conducta Alimentaria , Síndrome Metabólico , Circunferencia de la Cintura , Humanos , Síndrome Metabólico/psicología , Femenino , Masculino , Persona de Mediana Edad , Adulto , Conducta Alimentaria/psicología , Anciano , Índice de Masa Corporal , Presión Sanguínea , Estilo de Vida , Verduras , FrutasRESUMEN
Introduction: Remote anthropometric surveillance has emerged as a strategy to accommodate lapses in growth monitoring for pediatricians during coronavirus disease 2019 (COVID-19). The purpose of this investigation was to validate parent-reported anthropometry and inform acceptable remote measurement practices among rural, preschool-aged children. Methods: Parent-reported height, weight, body mass index (BMI), BMI z-score, and BMI percentile for their child were collected through surveys with the assessment of their source of home measure. Objective measures were collected by clinic staff at the child's well-child visit (WCV). Agreement was assessed using correlations, alongside an exploration of the time gap (TG) between parent-report and WCV to moderate agreement. Using parent- and objectively reported BMI z-scores, weight classification agreement was evaluated. Correction equations were applied to parent-reported anthropometrics. Results: A total of 55 subjects were included in this study. Significant differences were observed between parent- and objectively reported weight in the overall group (-0.24 kg; p = 0.05), as well as height (-1.8 cm; p = 0.01) and BMI (0.4 kg/m2; p = 0.02) in the ≤7d TG + Direct group. Parental reporting of child anthropometry ≤7d from their WCV with direct measurements yielded the strongest correlations [r = 0.99 (weight), r = 0.95 (height), r = 0.82 (BMI), r = 0.71 (BMIz), and r = 0.68 (BMI percentile)] and greatest classification agreement among all metrics [91.67% (weight), 54.17% (height), 83.33% (BMI), 91.67% (BMIz), and 33.33% (BMI percentile)]. Corrections did not remarkably improve correlations. Discussion: Remote pediatric anthropometry is a valid supplement for clinical assessment, conditional on direct measurement within 7 days. In rural populations where socioenvironmental barriers exist to care and surveillance, we highlight the utility of telemedicine for providers and researchers.
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OBJECTIVE: To evaluate body mass index (BMI) change among a population of children with a high proportion residing in rural areas across two pandemic time periods. METHODS: Electronic health records were evaluated in a rural health system. INCLUSION CRITERIA: 2-17 years at initial BMI; >2 BMIs during pre-pandemic (January 1, 2018-February 29, 2020); >1 BMI in early pandemic (June 1, 2020-December 31, 2020); and >1 BMI in later pandemic (January 1, 2021-December 31, 2021). Mixed effects linear regression models were used to estimate average monthly rate of change in BMI slope (∆BMI) from pre-pandemic to pandemic and test for effect modification of sex, race/ethnicity, age, BMI, public insurance, and rural address. RESULTS: Among the 40,627 participants, 50.2% were female, 84.6% were non-Hispanic white, 34.9% used public insurance, and 42.5% resided in rural areas. The pre-pandemic proportion of children with overweight, obesity, and severe obesity was 15.6%, 12.8%, and 6.3%, respectively. The ∆BMI nearly doubled during the early pandemic period compared with the pre-pandemic period (0.102 vs 0.055 kg/m2), however, ∆BMI in the later pandemic was lower (0.040 vs 0.055 kg/m2). ∆BMI remained higher in the later pandemic for all race categories compared to Non-Hispanic white. Children with public insurance had higher ∆BMI compared to those with private insurance that remained higher in the later pandemic (0.051 vs 0.035 kg/m2). There was no significant difference between ∆BMI for rural and urban children during pandemic periods. CONCLUSIONS: Despite the decreased ∆BMI among children in the later pandemic, prevalence of obesity and severe obesity remain high. Efforts must continue to be made to limit excess weight gain during childhood and to assess the impact of forces like structural and social factors in both etiology and prevention.