Advertisement

Identification of Measurement Needs to Prevent Childhood Obesity in High-Risk Populations and Environments

Published:September 09, 2020DOI:https://doi.org/10.1016/j.amepre.2020.05.012

      Introduction

      Children at highest obesity risk include those from certain racial/ethnic groups, from low-income families, with disabilities, or living in high-risk communities. However, a 2013 review of the National Collaborative for Childhood Obesity Research Measures Registry identified few measures focused on children at highest obesity risk. The objective is to (1) identify individual and environmental measures of diet and physical activity added to the Measures Registry since 2013 used among high-risk populations or settings and (2) describe methods for their development, adaptation, or validation.

      Methods

      Investigators screened references in the Measures Registry from January 2013 to September 2017 (n=351) and abstracted information about individual and environmental measures developed for, adapted for, or applied to high-risk populations or settings, including measure type, study population, adaptation and validation methods, and psychometric properties.

      Results

      A total of 38 measures met inclusion criteria. Of these, 30 assessed individual dietary (n=25) or physical activity (n=13) behaviors, and 11 assessed the food (n=8) or physical activity (n=7) environment. Of those, 17 measures were developed for, 9 were applied to (i.e., developed in a general population and used without modification), and 12 were adapted (i.e., modified) for high-risk populations. Few measures were used in certain racial/ethnic groups (i.e., American Indian/Alaska Native, Hawaiian/Pacific Islander, and Asian), children with disabilities, and rural (versus urban) communities.

      Conclusions

      Since 2013, a total of 38 measures were added to the Measures Registry that were used in high-risk populations. However, many of the previously identified gaps in population coverage remain. Rigorous, community-engaged methodologic research may help researchers better adapt and validate measures for high-risk populations.
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to American Journal of Preventive Medicine
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      REFERENCES

        • Hales CM
        • Carroll MD
        • Fryar CD
        • Ogden CL
        Prevalence of obesity among adults and youth: United States, 2015‒2016.
        NCHS Data Brief. 2017; (www.cdc.gov/nchs/data/databriefs/db288.pdf. Accessed July 17, 2020): 1-8
        • Ogden CL
        • Carroll MD
        • Fakhouri TH
        • et al.
        Prevalence of obesity among youths by household income and education level of head of household - United States 2011‒2014.
        MMWR Morb Mortal Wkly Rep. 2018; 67: 186-189
        • Johnson 3rd, JA
        • Johnson AM
        Urban–rural differences in childhood and adolescent obesity in the United States: a systematic review and meta-analysis.
        Child Obes. 2015; 11: 233-241
        • Bandini L
        • Danielson M
        • Esposito LE
        • et al.
        Obesity in children with developmental and/or physical disabilities.
        Disabil Health J. 2015; 8: 309-316
        • Stewart AL
        • Thrasher AD
        • Goldberg J
        • Shea JA
        A framework for understanding modifications to measures for diverse populations.
        J Aging Health. 2012; 24: 992-1017
        • Kumanyika S
        Getting to equity in obesity prevention: a new framework.
        National Academy of Medicine, Washington, DC2017 (https://doi.org/10.31478/201701c. Published January 18, 2017. Accessed August 21, 2019)
      1. Kumanyika S. The sociocultural context for obesity prevention and treatment in children and adolescents: Influences of ethnicity and gender. In: Freemark M, ed. Pediatric Obesity. Contemporary Endocrinology. Humana Press, Cham; 2018:695–713.https://doi.org/10.1007/978-3-319-68192-4_40.

        • McKinnon RA
        • Reedy J
        • Berrigan D
        • Krebs-Smith SM
        • NCCOR Catalogue and Registry Working Groups
        The National Collaborative on Childhood Obesity Research Catalogue of Surveillance Systems and Measures Registry: new tools to spur innovation and increase productivity in childhood obesity research.
        Am J Prev Med. 2012; 42: 433-435
      2. Measures Registry. National Collaborative on Childhood Obesity Research. https://tools.nccor.org/measures. Accessed October 21, 2019.

        • Institute of Medicine
        Evaluating obesity prevention efforts: a plan for measuring progress.
        National Academies Press, Washington, DC2013 (https://doi.org/10.17226/18334. Published August 2, 2013. Accessed June 29, 2018)
        • Finkelstein D
        • Fox MK
        Development of the database for the National Collaborative on Childhood Obesity Research Measures Registry: final report.
        Mathematica Policy Research, Inc., Princeton, NJJanuary 11, 2011 (PublishedAccessed January 9, 2020)
        • Lora KR
        • Davy B
        • Hedrick V
        • Ferris AM
        • Anderson MP
        • Wakefield D
        Assessing initial validity and reliability of a beverage intake questionnaire in Hispanic preschool-aged children.
        J Acad Nutr Diet. 2016; 116: 1951-1960
        • O'Connor TM
        • Cerin E
        • Hughes SO
        • et al.
        Psychometrics of the Preschooler Physical Activity Parenting Practices instrument among a Latino sample.
        Int J Behav Nutr Phys Act. 2014; 11: 3
        • Hearst MO
        • Fulkerson JA
        • Parke M
        • Martin L
        Validation of a home food inventory among low-income Spanish- and Somali-speaking families.
        Public Health Nutr. 2013; 16: 1151-1158
        • Lee C
        • Kim HJ
        • Dowdy DM
        • Hoelscher DM
        • Ory MG
        TCOPPE school environmental audit tool: assessing safety and walkability of school environments.
        J Phys Act Health. 2013; 10: 949-960
        • Pan L
        • Freedman DS
        • Park S
        • Galuska DA
        • Potter A
        • Blanck HM
        Changes in obesity among U.S. children aged 2 through 4 years enrolled in WIC during 2010‒2016.
        JAMA. 2019; 321: 2364-2366
      3. Asian & Pacific Islander American Health Forum. Obesity and overweight among Asian American children and adolescents.www.apiahf.org/wp-content/uploads/2016/04/2016.04.28_OBESITY-AND-OVERWEIGHT-AMONG-AA-CHILDREN-AND-ADOLESCENTS_Data-Brief-1.pdf. Published 2016. Accessed January 16, 2020.

        • Quader ZS
        • Gazmararian JA
        • McCullough LE
        Obesity and understudied minority children: existing challenges and opportunities in epidemiology.
        BMC Pediatr. 2019; 19: 103
        • National Academies of Sciences, Engineering, and Medicine
        Rationalizing rural area classifications for the Economic Research Service: a workshop summary.
        National Academies Press, Washington, DC2016 (https://doi.org/10.17226/21843. Published 2016. Accessed November 25, 2019)
        • Bender MS
        • Clark MJ
        Cultural adaptation for ethnic diversity: a review of obesity interventions for preschool children.
        Calif J Health Promot. 2011; 9: 40
        • Frongillo EA
        • Baranowski T
        • Subar AF
        • Tooze JA
        • Kirkpatrick SI
        Establishing validity and cross-context equivalence of measures and indicators.
        J Acad Nutr Diet. 2019; 119: 1817-1830
        • López N
        • Gadsen VL
        Health inequities, social determinants, and intersectionality.
        National Academy of Medicine, Washington, DC2016 (https://doi.org/10.31478/201612a. Published December 5, 2016. Accessed November 25, 2019)
        • Park SH
        • Park CG
        • McCreary L
        • Norr KF
        Cognitive interviews for validating the Family Nutrition Physical Activity instrument for Korean-American families with young children.
        J Pediatr Nurs. 2017; 36: 1-6
        • Boles RE
        • Burdell A
        • Johnson SL
        • Gavin WJ
        • Davies PL
        • Bellows LL
        Home food and activity assessment. Development and validation of an instrument for diverse families of young children.
        Appetite. 2014; 80: 23-27
        • Hartman TJ
        • Elliott AJ
        • Angal J
        • et al.
        Relative validation of a short questionnaire to assess the dietary habits of pregnant American Indian women.
        Food Sci Nutr. 2017; 5: 625-632
        • Palacios C
        • Rivas-Tumanyan S
        • Santiago-Rodríguez EJ
        • et al.
        A semi-quantitative food frequency questionnaire validated in Hispanic infants and toddlers aged 0 to 24 months.
        J Acad Nutr Diet. 2017; 117 (e9.https://doi.org/10.1016/j.jand.2016.12.010): 526-535
        • Matthews-Ewald MR
        • Posada A
        • Wiesner M
        • Olvera N
        An exploratory factor analysis of the Parenting Strategies for Eating and Physical Activity Scale (PEAS) for use in Hispanic mothers of adolescent and preadolescent daughters with overweight.
        Eat Behav. 2015; 19: 193-199
        • Baxter SD
        • Smith AF
        • Hitchcock DB
        • et al.
        Test–retest reliability of the National Health and Nutrition Examination Survey's 5-item Food Insecurity Questionnaire completed by fourth-grade children.
        J Nutr Educ Behav. 2015; 47 (e1.https://doi.org/10.1016/j.jneb.2015.06.006): 459-464
        • Lee JE
        • Sung JH
        • Malouhi M
        Statistical validation of a web-based GIS application and its applicability to cardiovascular-related studies.
        Int J Environ Res Public Health. 2015; 13 (https://doi.org/10.3390/ijerph13010002)ijerph13010002
        • Byker Shanks C
        • Jilcott Pitts S
        • Gustafson A
        Development and validation of a farmers’ market audit tool in rural and urban communities.
        Health Promot Pract. 2015; 16: 859-866
        • Arcan C
        • Hannan PJ
        • Fulkerson JA
        • et al.
        Associations of home food availability, dietary intake, screen time and physical activity with BMI in young American-Indian children.
        Public Health Nutr. 2013; 16: 146-155