Rates of Obesity and Obesogenic Behaviors of Rural Appalachian Adolescents: How Do They Compare to Other Adolescents or Recommendations?

in Journal of Physical Activity and Health
Restricted access

Purchase article

USD  $24.95

Student 1 year subscription

USD  $115.00

1 year subscription

USD  $153.00

Student 2 year subscription

USD  $218.00

2 year subscription

USD  $285.00

Background: To better understand the unique challenges of Appalachians, community-based studies are needed to establish benchmark rates. This study compares obesity rates and obesogenic behaviors among Appalachian adolescents to other adolescent populations or clinical recommendations. Methods: This study was conducted in 11 Appalachian schools. Body mass index, body mass index percentile, and body fat percentage were measured using a Tanita DC-430U analyzer. Physical activity was measured using Actigraph wGT3X-BT accelerometers. Sugar-sweetened beverage consumption was self-reported. Pearson’s correlations, independent t tests, and multivariate analyses with tests of between-subject effects were conducted. Results: Mean (n = 345) age was 15.23 (SD = 1.02) years. Appalachian adolescents were extremely obese (13.1%) by more than double that of national adolescent rates. Nearly 29% of males and over 55% of females were at increased cardiovascular risk. Only 15% were moderately active for at least 60 minutes a day, but only for 1 day per week. Mean afterschool sedentary time was 4.75 hours. Only 2.1% recorded vigorous activity for a minimum of 10 minutes at 1 day per week. Nearly all regularly consumed sugar-sweetened beverages. Conclusion: Obesogenic health disparities were evident in Appalachia. Rates of obesogenic factors among Appalachian adolescents exceed national rates. Appalachian adolescents were far less active, and extreme obesity is a major health concern.

Smith and Baumker are with the College of Nursing, Ohio State University, Columbus, OH. Laurent and Petosa are with the College of Education and Human Ecology, Ohio State University, Columbus, OH.

Smith (Smith.5764@osu.edu) is corresponding author.
  • 1.

    Hallal PC, Victora CG, Azevedo MR, Wells JC. Adolescent physical activity and health. A systematic review. Sports Med. 2006;36(12):1019–1030. PubMed ID: 17123326 doi:10.2165/00007256-200636120-00003

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 2.

    Iannotti RJ, Wang J. Trends in physical activity, sedentary behavior, diet, and BMI among US adolescents, 2001–2009. Pediatrics. 2013;132:606–614. PubMed ID: 24043281 doi:10.1542/peds.2013-1488

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents; National Heart, Lung, and Blood Institute. Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and adolescents: summary report. Pediatrics. 2011;128:213–256. PubMed ID: 22084329 doi:10.1542/peds.2009-2107C

    • Search Google Scholar
    • Export Citation
  • 4.

    May AL, Kukina EV, Yoon PW. Prevalence of cardiovascular disease risk factors among US adolescents, 1999–2008. Pediatrics. 2012;129(6):1035-1041. PubMed ID: 22614778 doi:10.1542/peds.2011-1082

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Iannotti RJ, Wang J. Patterns of physical activity, sedentary behavior and diet in US adolescents. J Adolesc Health. 2013;53(2):280–286.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6.

    National Advisory Council on Rural Health and Human Services. Mortality and Life Expectancy in Rural America: Connecting the Health and Human Service Safety Nets to Improve Health Outcomes Over the Life Course. Rockville, MD: National Advisory Committee on Rural Health and Human Services; 2015.

    • Search Google Scholar
    • Export Citation
  • 7.

    Kochanek KD, Murphy SL, Xu JQ, Tejada-Vera B. Deaths: final data for 2014. Natl Vital Stat Rep. 2016; 65(4):1–122.

  • 8.

    Moy E, Garcia MC, Bastian B. et al. Leading causes of death in nonmetropolitan and metropolitan areas—United States, 1999–2014. MMWR Surveillance Summaries. 2017;66(SS–1):1–8. PubMed ID: 28081058 doi:10.15585/mmwr.ss6601a1

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9.

    Bassett DR, Conger JD, Fitzhugh EC, Coe DP. Trends in physical activity and sedentary behaviors of United States youth. J Phys Act Health. 2015;12(8):1102–1111. PubMed ID: 25347913 doi:10.1123/jpah.2014-0050

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Costigan SA, Barnett L, Plotnikoff RC, Lubans DR. The health indicators associated with screen-based sedentary behavior among adolescent girls: a systematic review. J Adolesc Health. 2013;52:382–392. PubMed ID: 23299000 doi:10.1016/j.jadohealth.2012.07.018

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Laska MN, Pelletier JE, Larson MI, Story M. Interventions for weight gain prevention during the transition to young adulthood: a review of the literature. J Adolesc Health. 2012;50(4):324–333. PubMed ID: 22443834 doi:10.1016/j.jadohealth.2012.01.016

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Hulman M, Lowry R, Lee SM, Fulton JE, Carlson SA, Patnode CD. Physical activity and screen time: trends in U.S. children aged 9–13 years, 2002–2006. J Phys Act Health. 2012;9(4):508–515. PubMed ID: 22566548 doi:10.1123/jpah.9.4.508

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13.

    Lipsky LM, Iannotti RJ. Associations of television viewing with eating behaviors in the 2009 health behavior in school-aged children study. Arch Pediatr Adolesc Med. 2012;166(5):465–472. doi:10.1001/archpediatrics.2011.1407

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Huh J, Riggs NR, Shruijt-Metz D, Chou CP, Huang Z, Pentz M. Identifying patterns of eating and physical activity in children: a latent class analysis of obesity risk. Obesity. 2011;19:652–658. PubMed ID: 20930718 doi:10.1038/oby.2010.228

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Thornton CM, Cain CL, Conway TL, et al. Relation of adolescents’ physical activity to after-school recreation environment. J Phys Act Health. 2017;7:1–21. PubMed ID: 28169572 doi:10.1123/jpah.2016-0365

    • Search Google Scholar
    • Export Citation
  • 16.

    Smith LH, Holloman C. Health status and access to health care services- a comparison between Ohio’s rural non-Appalachian and Appalachian families. Fam Community Health. 2011;34:102–110. PubMed ID: 21378506 doi:10.1097/FCH.0b013e31820de961

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    McGarvey EL, MaGuadalupe L, Killos LF, Guterbock T, Cohn WF. Health disparities between Appalachian and non-Appalachian counties in Virginia USA. J Community Health. 2011; 36:348–356. PubMed ID: 20862529 doi:10.1007/s10900-010-9315-9

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Coyne CA, Demian-Popescu C, Friend D. Social and cultural factors influencing health in southern West Virginia: a qualitative study. Prev Chronic Dis Public Health Res Practice Policy. 2006;3:A124. PubMed ID: 16978499

    • Search Google Scholar
    • Export Citation
  • 19.

    Deskins S, Harris CV, Bradlyn AS, et al. Preventive care in Appalachia: use of the theory of planned behavior to identify barriers to participation in cholesterol screening s among West Virginians. J Rural Health. 2006;22:367–374. PubMed ID: 17010036 doi:10.1111/j.1748-0361.2006.00060.x

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 20.

    Lobri-Posey B. Middle-aged Appalachians living with diabetes mellitus: a family affair. Fam Community Health. 2006;29:214–220. PubMed ID: 16775471 doi:10.1097/00003727-200607000-00008

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 21.

    Morrone M. Environmental justice and health disparities in Appalachia, Ohio: local cases with global implications. In: Liotta PH, Mouat DA, et al, eds. Environmental Change and Human Security. Dordrecht, The Netherlands: Springer; 2008:299–323.

    • Search Google Scholar
    • Export Citation
  • 22.

    Meit M, Knudson A, Gilbert T, et al. The 2014 update of the rural-urban chartbook. Grand Forks, ND: Rural Health Reform Policy Research Center; 2014.

    • Search Google Scholar
    • Export Citation
  • 23.

    Hortz B, Stevens E, Holden B, Petosa RL. Rates of physical activity among Appalachian adolescents in Ohio. J Rural Health. 2009;25:58–61. PubMed ID: 19166562 doi:10.1111/j.1748-0361.2009.00199.x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Agency for Healthcare Research and Quality. 2014 National Healthcare Quality and Disparities Report Chart Book on Rural Health Care. AHRQ Pub. No. 15-0007-9-EF. Rockville, MD: Agency for Healthcare Research and Quality; 2015.

    • Search Google Scholar
    • Export Citation
  • 25.

    Centers for Disease Control and Prevention. Trends in the prevalence of physical activity and sedentary behaviors national YRBS: 1991–2015. 2016. www.cdc.gov/yrbss. Accessed August 22, 2017.

    • Export Citation
  • 26.

    Wells JC. Toward body composition reference data for infants, children, and adolescents. Adv Nutr. 2014;5(3):320S–329S. PubMed ID: 24829484 doi:10.3945/an.113.005371

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Pietrobelli A, Faith MS, Allison DB, Gallagher D, Chiumello G, Heymsfield SB. Body mass index as a measure of adiposity among children and adolescents: a validation study. J Pediatr. 1998;132:204–210. PubMed ID: 9506629 doi:10.1016/S0022-3476(98)70433-0

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    Barreira TV, Staiano AE, Katzmarzyk PT. Validity assessment of a portable bioimpedance scale to estimate body fat percentage in white and African American children and adolescents. Pediatr Obes. 2013;8(2):e29–e32. PubMed ID: 23239610 doi:10.1111/j.2047-6310.2012.00122.x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29.

    Kabiri LS, Hernandez DC, Mitchell K. Reliability, validity, and diagnostic value of a pediatric bioelectrical impedance analysis scale. Child Obes. 2015;11(5):650–655. PubMed ID: 26332367 doi:10.1089/chi.2014.0156

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30.

    Jebb S, McCarthy D, Fry T, Prentice AM. New body fat reference curves for children. Obesity Rev. 2004;12:A156–157.

  • 31.

    Tanita Corporation of America. Body Composition Analyzer DC-430U Instruction Manual. Arlington Heights, IL: Tanita Corporation; 2014.

  • 32.

    Ogden CL, Carroll MD, Lawman HG, et al. Trends in obesity prevalence among children and adolescents in the United States, 1988–1994 through 2013–2014. JAMA. 2016;315(21):2292–2299. PubMed ID: 27272581 doi:10.1001/jama.2016.6361

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 33.

    Kuczmarski RJ, Odgen CL, Grummer-Strawn LM, et al. CDC growth charts: United States. Advance Data. 2000;314(314):1–27. PubMed ID: 11183293

    • Search Google Scholar
    • Export Citation
  • 34.

    Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ. 2000;320:1240–1240. PubMed ID: 10797032 doi:10.1136/bmj.320.7244.1240

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35.

    Cole TJ, Flegal KM, Nicholls D, Jackson AA. Body mass index cut offs to define thinness in children and adolescents: international survey. BMJ. 2007;335:194. PubMed ID: 17591624

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 36.

    Actigraph Support. What’s the difference among the cut points available in Actilife? Pensacola, FL: Actigraph; 2012.

  • 37.

    Freedson PS, Melanson E, Sirard J. Calibration of the computer science and applications, Inc. (CSA) accelerometer. Med Sci Sports Exerc. 1998;30(5):777–781. PubMed ID: 9588623 doi:10.1097/00005768-199805000-00021

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38.

    Lubans D, Hesketh D, Cliff L, et al. A systematic review of the validity and reliability of sedentary behavior measures used with children and adolescents. Obes Rev. 2011;12(10):781–799. PubMed ID: 21676153

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 39.

    Rich C, Griffiths LJ, Dezateux C. Seasonal variation in accelerometer-determined sedentary behavior and physical activity in children: a review. Int J Behav Nutr Phys Act. 2012;9(9):49. PubMed ID: 22546178 doi:10.1186/1479-5868-9-49

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40.

    Warolin J, Carrico AR, Whitaker LE, et al. Effect of BMI on prediction of accelerometry-based energy expenditure in youth. Med Sci Sports Exer. 2012;44(12):2428–2435. PubMed ID: 22776880

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 41.

    Pulsford RM, Cortina-Borja M, Rich C, Kinnafick FE, Dezateux C, Griffiths LJ. Actigraph accelerometer-defined boundaries for sedentary behavior and physical activity intensities in 7 year old children. PLOS One. 2011;6(8):e2822. PubMed ID: 21853021 doi:10.1371/journal.pone.0021822

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 42.

    Alhassan S, Lyden K, Howe C, Keadle SK, Ogechi N, Freedson PS. Accuracy of accelerometer regression models in predicting energy expenditure and METs in children and youth. Pediatr Exerc Sci. 2012;24(4):519–536. PubMed ID: 23196761 doi:10.1123/pes.24.4.519

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 43.

    Smith LH, Holloman C. Piloting “Sodabriety:” a school-based intervention to impact sugar-sweetened beverage consumption in rural Appalachian high schools. J Sch Health. 2014;84(3):177–184. PubMed ID: 24443779 doi:10.1111/josh.12134

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 44.

    Wang YC, Bleich SN, Gortmacker SL. Increasing caloric contribution from sugar-sweetened beverages and 100% fruit juices among US children and adolescents: 1998–2004. Pediatrics. 2008;121(6):e1604–e1614. PubMed ID: 18519465 doi:10.1542/peds.2007-2834

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 45.

    Dwyer T, Blizzard CL. Defining obesity in children by biological endpoint rather population distribution. Int J Obes Related Metab Dis. 1996;20(5):472–480. PubMed ID: 8696427

    • Search Google Scholar
    • Export Citation
  • 46.

    Williams DP, Going SB, Lohman TG, et al. Body fatness and risk for elevated blood pressure, total cholesterol, and serum lipoprotein ratios in children and adolescents. Am J Public Health. 1992;82(3):358–363. PubMed ID: 1536350 doi:10.2105/AJPH.82.3.358

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 47.

    Laurson KR, Eisenmann JC, Welk GJ. Body fat percentile curves for U.S. children and adolescents. Am J Prev Med. 2011; 41(4 Suppl 2):S87–S92. PubMed ID: 21961617 doi:10.1016/j.amepre.2011.06.044

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 48.

    Ogden CL, Li Y, Freedman DS, et al. Smoothed Percentage Body Fat Percentiles for U.S. Children and Adolescents, 1999–2004. National Health Statistics Report, No. 43. Hyattsville, MD: National Center for Health Statistics; 2011.

    • Search Google Scholar
    • Export Citation
  • 49.

    United States Department of Health and Human Services. Physical Activity Guidelines for Americans. Washington, DC: Author; 2008.

  • 50.

    Centers for Disease Control and Prevention. Youth risk behavior surveillance—United States, 2013. MMWR Morb Wkly Rep. 2014;63(4):1–168. PubMed ID: 24918634

    • Search Google Scholar
    • Export Citation
  • 51.

    Rosinger A, Herrick K, Gahche J, Park S. Sugar-sweetened beverage consumption among U.S. youth, 2011–2014. NCHS Data Brief. 2017;27(271):1–8. PubMed ID: 28135184

    • Search Google Scholar
    • Export Citation
  • 52.

    Kitahara CM, Flint AJ, Berrington de Gonzalez A, et al. Association between class III obesity (BMI of 40–59 kg/m2) and mortality: a pooled analysis of 20 prospective studies. PLoS Med. 2014;11(7):e1001673. PubMed ID: 25003901 doi:10.1371/journal.pmed.1001673

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 53.

    Centers for Disease Control and Prevention (CDC). About Child & Teen BMI. May 2015. http://www.cdc.gov/healthyweight/assessing/bmi/childrens_bmi/about_childrens_bmi.ht ml.

    • Export Citation
  • 54.

    Deshmukh-Taskar PR, O’Neil CE, Nicklas NA, et al. Dietary patterns associated with metabolic syndrome SES and lifestyle factors in young adults– the Bogalusa heart study. Public Health Nutr. 2009;12(12):2493–2503. PubMed ID: 19744354 doi:10.1017/S1368980009991261

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 55.

    Li K, Haynie D, Lipsky L, Iannotti RJ, Pratt C, Simons-Morton B. Changes in moderate-to-vigorous physical activity among older adolescents. Pediatrics. 2016;138(4):e20161372. PubMed ID: 27669737 doi:10.1542/peds.2016-1372

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 128 128 31
Full Text Views 8 8 1
PDF Downloads 3 3 0