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Disparities in weight changes during the COVID-19 pandemic-related lockdown in youths
dc.contributor.authorKoebnick, Corinna
dc.contributor.authorSidell, Margo A.
dc.contributor.authorLi, Xia
dc.contributor.authorResnicow, Ken
dc.contributor.authorKunani, Poornima
dc.contributor.authorYoung, Deborah R.
dc.contributor.authorWoolford, Susan J.
dc.date.accessioned2023-03-03T21:08:36Z
dc.date.available2024-04-03 16:08:35en
dc.date.available2023-03-03T21:08:36Z
dc.date.issued2023-03
dc.identifier.citationKoebnick, Corinna; Sidell, Margo A.; Li, Xia; Resnicow, Ken; Kunani, Poornima; Young, Deborah R.; Woolford, Susan J. (2023). "Disparities in weight changes during the COVID-19 pandemic-related lockdown in youths." Obesity 31(3): 789-801.
dc.identifier.issn1930-7381
dc.identifier.issn1930-739X
dc.identifier.urihttps://hdl.handle.net/2027.42/175889
dc.description.abstractObjectiveThis study evaluates whether changes in weight among school-aged youth in California due to the COVID-19 lockdown vary by social constructs of race/ethnicity and associated social factors.MethodsIncluding 160,472 youth aged 5 to 17 years enrolled at Kaiser Permanente Southern California, mixed effects models stratified by age group were fitted to estimate changes in distance from the median BMI-for-age from March 2020 to January 2021 (lockdown) compared with the same period before the pandemic.ResultsExcess pandemic weight gain was higher among Black and Hispanic youth aged 5 to 17 years than among White and Asian youth; this difference was most pronounced in those aged 5 to 11 years. In youth aged 5 to 11 years, the distance from the median BMI-for-age increased by 1.72 kg/m2 (95% CI: 1.61-1.84) in Hispanic and 1.70 kg/m2 (95% CI: 1.47-1.94) in Black youth during the lockdown compared with 1.16 kg/m2 (95% CI: 1.02-1.29) in non-Hispanic White youth. The excess weight gain was also higher in youth with fewer neighborhood parks and those with state-subsidized health insurance.ConclusionsThe COVID-19 pandemic lockdown led to a gain of excess body weight, particularly for Black and Hispanic youth; this weight gain varied by social factors associated with race and ethnicity.
dc.publisherWiley Periodicals, Inc.
dc.titleDisparities in weight changes during the COVID-19 pandemic-related lockdown in youths
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelEndocrinology
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/175889/1/oby23645_am.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/175889/2/oby23645.pdf
dc.identifier.doi10.1002/oby.23645
dc.identifier.sourceObesity
dc.identifier.citedreferenceChild I, Loza A, Doolittle B. Collateral damage from the COVID-19 pandemic: pediatric obesity. Popul Health Manag. 2022; 25: 573 - 574.
dc.identifier.citedreferenceVogel M, Geserick M, Gausche R, et al. Age- and weight group-specific weight gain patterns in children and adolescents during the 15 years before and during the COVID-19 pandemic. Int J Obes (Lond). 2022; 46: 144 - 152.
dc.identifier.citedreferenceBrooks CG, Spencer JR, Sprafka JM, et al. Pediatric BMI changes during COVID-19 pandemic: an electronic health record-based retrospective cohort study. EClinicalMedicine. 2021; 38: 101026. doi: 10.1016/j.eclinm.2021.101026
dc.identifier.citedreferenceWu AJ, Aris IM, Hivert MF, et al. Association of changes in obesity prevalence with the COVID-19 pandemic in youth in Massachusetts. JAMA Pediatr. 2021; 176: 198 - 201.
dc.identifier.citedreferenceBelanger MJ, Hill MA, Angelidi AM, Dalamaga M, Sowers JR, Mantzoros CS. Covid-19 and disparities in nutrition and obesity. N Engl J Med. 2020; 383: e69. doi: 10.1056/NEJMp2021264
dc.identifier.citedreferenceOgden CL, Fryar CD, Martin CB, et al. Trends in obesity prevalence by race and hispanic origin-1999–2000 to 2017–2018. JAMA. 2020; 324: 1208 - 1210.
dc.identifier.citedreferenceMorgan Hughey S, Kaczynski AT, Child S, Moore JB, Porter D, Hibbert J. Green and lean: is neighborhood park and playground availability associated with youth obesity? Variations by gender, socioeconomic status, and race/ethnicity. Prev Med. 2017; 95 ( suppl ): S101 - s108.
dc.identifier.citedreferenceMcCarthy SM, Hughey SM, Kaczynski AT. Examining sociodemographic differences in playground availability and quality and associations with childhood obesity. Child Obes. 2017; 13: 324 - 331.
dc.identifier.citedreferenceWhite MJ, McClure E, Killeen J, et al. Changes in the recreational built environment and youth body mass index. Acad Pediatr. 2021; 21: 76 - 83.
dc.identifier.citedreferenceD’Agostino EM, Patel HH, Ahmed Z, et al. Impact of change in neighborhood racial/ethnic segregation on cardiovascular health in minority youth attending a park-based afterschool program. Soc Sci Med. 2018; 205: 116 - 129.
dc.identifier.citedreferenceNardone A, Rudolph KE, Morello-Frosch R, Casey JA. Redlines and greenspace: the relationship between historical redlining and 2010 greenspace across the United States. Environ Health Perspect. 2021; 129: 17006. doi: 10.1289/EHP7495
dc.identifier.citedreferenceNobari TZ, Whaley SE, Prelip ML, Crespi CM, Wang MC. Trends in socioeconomic disparities in obesity prevalence among low-income children aged 2–4 years in Los Angeles County, 2003–2014. Child Obes. 2018; 14: 248 - 258.
dc.identifier.citedreferenceHingorani A. LA County park equity groups fight to turn park-poor community “red to green”. Catalyst California. January 22, 2019. Accessed November 29, 2021. https://www.advancementprojectca.org/blog/la-county-park-equity-groups-fight-to-turn-park-poor-communities-red-to-green.
dc.identifier.citedreferenceBailey ZD, Feldman JM, Bassett MT. How structural racism works—racist policies as a root cause of U.S. racial health inequities. N Engl J Med. 2021; 384: 768 - 773.
dc.identifier.citedreferenceBleich SN, Ard JD. COVID-19, obesity, and structural racism: understanding the past and identifying solutions for the future. Cell Metab. 2021; 33: 234 - 241.
dc.identifier.citedreferenceAmes JL, Ferrara A, Avalos LA, et al. COVID-19 prevalence, symptoms, and sociodemographic disparities in infection among insured pregnant women in Northern California. PLoS One. 2021; 16: e0256891. doi: 10.1371/journal.pone.0256891
dc.identifier.citedreferenceTracking the COVID-19 economy’s effects on food, housing, and employment hardships. Center on Budget and Policy Priorities. Updated February 10, 2022. Accessed November 10, 2021. https://www.cbpp.org/research/poverty-and-inequality/tracking-the-covid-19-economys-effects-on-food-housing-and
dc.identifier.citedreferenceJansen E, Thapaliya G, Aghababian A, Sadler J, Smith K, Carnell S. Parental stress, food parenting practices and child snack intake during the COVID-19 pandemic. Appetite. 2021; 161: 105119. doi: 10.1016/j.appet.2021.105119
dc.identifier.citedreferenceHardcastle SJ, Caraher M. The role of foodbanks in the context of food insecurity: experiences and eating behaviours amongst users. Appetite. 2021; 163: 105208. doi: 10.1016/j.appet.2021.105208
dc.identifier.citedreferenceStinson EJ, Votruba SB, Venti C, Perez M, Krakoff J, Gluck ME. Food insecurity is associated with maladaptive eating behaviors and objectively measured overeating. Obesity (Silver Spring). 2018; 26: 1841 - 1848.
dc.identifier.citedreferencevon Hippel PT, Workman J. From kindergarten through second grade, U.S. children’s obesity prevalence grows only during summer vacations. Obesity (Silver Spring). 2016; 24: 2296 - 2300.
dc.identifier.citedreferenceWang YC, Vine S, Hsiao A, Rundle A, Goldsmith J. Weight-related behaviors when children are in school versus on summer breaks: does income matter? J Sch Health. 2015; 85: 458 - 466.
dc.identifier.citedreferenceGhosh R, Dubey MJ, Chatterjee S, Dubey S. Impact of COVID-19 on children: special focus on the psychosocial aspect. Minerva Pediatr. 2020; 72: 226 - 235.
dc.identifier.citedreferenceEducation Commission of the States. COVID Response. FINRA. Accessed June 4, 2021. https://www.finra.org/rules-guidance/key-topics/covid-19/shelter-in-place
dc.identifier.citedreferenceDunn CG, Kenney E, Fleischhacker SE, Bleich SN. Feeding low-income children during the Covid-19 pandemic. N Engl J Med. 2020; 382: e40. doi: 10.1056/NEJMp2005638
dc.identifier.citedreferenceGundersen C, Mahatmya D, Garasky S, Lohman B. Linking psychosocial stressors and childhood obesity. Obes Rev. 2011; 12: 54 - 63.
dc.identifier.citedreferenceWoolford SJ, Sidell M, Li X, et al. Changes in body mass index among children and adolescents during the COVID-19 pandemic. JAMA. 2021; 326: 1434 - 1436.
dc.identifier.citedreferenceStierman B, Ogden CL, Yanovski JA, Martin CB, Sarafrazi N, Hales CM. Changes in adiposity among children and adolescents in the United States, 1999–2006 to 2011–2018. Am J Clin Nutr. 2021; 114: 1495 - 1504.
dc.identifier.citedreferenceHales CM, Carroll MD, Fryar CD, Ogden CL. Prevalence of obesity and severe obesity among adults: United States, 2017–2018. NCHS Data Brief, no. 360. National Center for Health Statistics; 2020.
dc.identifier.citedreferenceChildhood obesity facts: prevalence of childhood obesity in the United States. Centers for Disease Control and Prevention. Updated May 17, 2022. Accessed June 4, 2021. https://www.cdc.gov/obesity/data/childhood.html
dc.identifier.citedreferenceRisk for COVID-19 infection, hospitalization, and death by race/ethnicity. Centers for Disease Control and Prevention. Updated December 28, 2022. Accessed February 4, 2021. https://www.cdc.gov/coronavirus/2019-ncov/covid-data/investigations-discovery/hospitalization-death-by-race-ethnicity.html
dc.identifier.citedreferenceTung EL, Peek ME, Rivas MA, Yang JP, Volerman A. Association of neighborhood disadvantage with racial disparities in COVID-19 positivity in Chicago. Health Aff (Millwood). 2021; 40: 1784 - 1791.
dc.identifier.citedreferenceKoebnick C, Langer-Gould AM, Gould MK, et al. Sociodemographic characteristics of members of a large, integrated health care system: comparison with US Census Bureau data. Perm J. 2012; 16: 37 - 41.
dc.identifier.citedreferenceKoebnick C, Coleman KJ, Black MH, et al. Cohort profile: the KPSC children’s health study, a population-based study of 920 000 children and adolescents in Southern California. Int J Epidemiol. 2012; 41: 627 - 633.
dc.identifier.citedreferenceFeinstein JA, Russell S, DeWitt PE, Feudtner C, Dai D, Bennett TD. R package for pediatric complex chronic condition classification. JAMA Pediatr. 2018; 172: 596 - 598.
dc.identifier.citedreferenceFeudtner C, Feinstein JA, Zhong W, Hall M, Dai D. Pediatric complex chronic conditions classification system version 2: updated for ICD-10 and complex medical technology dependence and transplantation. BMC Pediatr. 2014; 14: 199. doi: 10.1186/1471-2431-14-199
dc.identifier.citedreferenceKuczmarski RJ, Ogden CL, Guo SS, et al. 2000 CDC growth charts for the United States: methods and development. Vital and Health Statistics, series 11, no. 246. National Center for Health Statistics; 2002.
dc.identifier.citedreferenceRyder JR, Kelly AS, Freedman DS. Metrics matter: toward consensus reporting of BMI and weight-related outcomes in pediatric obesity clinical trials. Obesity (Silver Spring). 2022; 30: 571 - 572.
dc.identifier.citedreferenceFreedman DS, Butte NF, Taveras EM, et al. BMI z-scores are a poor indicator of adiposity among 2- to 19-year-olds with very high BMIs, NHANES 1999–2000 to 2013–2014. Obesity (Silver Spring). 2017; 25: 739 - 746.
dc.identifier.citedreferenceFreedman DS, Woo JG, Ogden CL, Xu JH, Cole TJ. Distance and percentage distance from median BMI as alternatives to BMI z score. Br J Nutr. 2020; 124: 493 - 500.
dc.identifier.citedreferenceFreedman DS, Berenson GS. Tracking of BMI z scores for severe obesity. Pediatrics. 2017; 140: e20217107. doi: 10.1542/peds.2017-1072
dc.identifier.citedreferenceClaritas LLC. Claritas Demographic Update 2022 Methodology. Published July 2021. Access June 4, 2022. https://environicsanalytics.com/docs/default-source/us---data-product-support-documents/claritas-demographic-update-methodology-ea.pdf
dc.identifier.citedreferenceAndrade C. Mean difference, standardized mean difference (SMD), and their use in meta-analysis: as simple as it gets. J Clin Psychiatry. 2020; 81: 20f13681. doi: 10.4088/JCP.20f13681
dc.identifier.citedreferenceBeech BM, Ford C, Thorpe RJ Jr, Bruce MA, Norris KC. Poverty, racism, and the public health crisis in America. Front Public Health. 2021; 9: 699049. doi: 10.3389/fpubh.2021.699049
dc.identifier.citedreferenceAcosta AM, Garg S, Pham H, et al. Racial and ethnic disparities in rates of COVID-19-associated hospitalization, intensive care unit admission, and in-hospital death in the United States from March 2020 to February 2021. JAMA Netw Open. 2021; 4: e2130479. doi: 10.1001/jamanetworkopen.2021.30479
dc.identifier.citedreferenceMagesh S, John D, Li WT, et al. Disparities in COVID-19 outcomes by race, ethnicity, and socioeconomic status: a systematic-review and meta-analysis. JAMA Netw Open. 2021; 4: e2134147. doi: 10.1001/jamanetworkopen.2021.34147
dc.identifier.citedreferenceAzar KMJ, Shen Z, Romanelli RJ, et al. Disparities in outcomes among COVID-19 patients in a large health care system in California. Health Aff (Millwood). 2020; 39: 1253 - 1262.
dc.identifier.citedreferenceEscobar GJ, Adams AS, Liu VX, et al. Racial disparities in COVID-19 testing and outcomes: retrospective cohort study in an integrated health system. Ann Intern Med. 2021; 174: 786 - 793.
dc.identifier.citedreferenceNau C, Bruxvoort K, Navarro RA, et al. COVID-19 inequities across multiple racial and ethnic groups: results from an integrated health care organization. Ann Intern Med. 2021; 174: 1183 - 1186.
dc.identifier.citedreferenceBrowne NT, Snethen JA, Greenberg CS, et al. When pandemics collide: the impact of COVID-19 on childhood obesity. J Pediatr Nurs. 2021; 56: 90 - 98.
dc.identifier.citedreferenceLange SJ, Kompaniyets L, Freedman DS, et al. Longitudinal trends in body mass index before and during the COVID-19 pandemic among persons aged 2–19 years-United States, 2018–2020. MMWR Morb Mortal Wkly Rep. 2021; 70: 1278 - 1283.
dc.working.doiNOen
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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