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Impact of Hurricane Harvey on the Growth of Low Income, Ethnic Minority Adolescents

Published online by Cambridge University Press:  09 November 2020

Katherine R. Arlinghaus Open the ORCID record for Katherine R. Arlinghaus [Opens in a new window] ,
Stacey L. Gorniak ,
Daphne C. Hernandez  and
Craig A. Johnston
Katherine R. Arlinghaus*
Affiliation:
Department of Health and Human Performance, University of Houston, Houston, Texas
Stacey L. Gorniak
Affiliation:
Department of Health and Human Performance, University of Houston, Houston, Texas
Daphne C. Hernandez
Affiliation:
Cizik School of Nursing, The University of Texas Health Science Center, Houston, Texas
Craig A. Johnston
Affiliation:
Department of Health and Human Performance, University of Houston, Houston, Texas
*
Correspondence and reprint requests to Katherine R. Arlinghaus PhD, RD, Department of Health and Human Performance, University of Houston, 3875 Holman Street, Garrison Gymnasium, Room 104, Houston, Texas, 77240 (e-mail: krarling@central.uh.edu).
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Abstract

Objective:

This study examined the differential impact of Hurricane Harvey on adolescent standardized Body Mass Index (zBMI), physical activity, diet, and perceived stress.

Methods:

Prior to Hurricane Harvey, 175 ethnic minority adolescents were recruited from an independent school district in Houston. Height and weight were directly measured. The School Physical Activity and Nutrition Questionnaire assessed diet and physical activity. Stress was assessed with the Perceived Stress Scale. High hurricane impact was classified as at least 1 affirmative response to house damage, rescue, displacement, or going without food, water, or medicine. Repeated measures such as ANCOVA models were developed to assess differences in zBMI, physical activity, diet, and stress between the hurricane impact groups. Regression models were used to assess stress as a mediator of the hurricane impact and zBMI change relationship.

Results:

Students who were highly impacted by the hurricane had a greater decrease in zBMI than those less impacted from pre-hurricane to 15 weeks post-hurricane (95% CI 0.02 to 0.25, p<0.05). Physical activity and diet did not differ by impact. Perceived stress at 3 weeks post-hurricane mediated the impact and zBMI change relationship (β=-0.04 95% CI -0.12 to -0.002).

Conclusion:

The decrease in zBMI among highly impacted students warrants further monitoring. Perceived stress, immediately following the hurricane, impacted student growth months later.

Keywords

natural disasterhispanicschoolweightsocial vulnerability
Type
Original Research
Information
Disaster Medicine and Public Health Preparedness , Volume 17 , 2023 , e9
Copyright
© Society for Disaster Medicine and Public Health, Inc. 2020

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References

REFERENCES

Carroll, AE, Frakt, AB. Children’s health must remain a focus in the recovery from Hurricane Harvey. JAMA Pediatr. 2017;171(11):1029–1030.CrossRefGoogle ScholarPubMed
Substance Abuse and Mental Health Services Administration. Greater impact: How disasters affect people of low socioeconomic status. Department of Health and Human Services; 2017. https://www.samhsa.gov/sites/default/files/programs_campaigns/dtac/srb-low-ses.pdf. Accessed September 25, 2018.Google Scholar
Cutter, SL, Boruff, BJ, Shirley, WL. Social vulnerability to environmental hazards. Soc SciQ. 2003;84(2):242–261.Google Scholar
Masozera, M, Bailey, M, Kerchner, C. Distribution of impacts of natural disasters across income groups: A case study of New Orleans. Ecol Econ. 2007;63(2-3):299–306.CrossRefGoogle Scholar
Yap, F, Lee, YS, Aw, MMH. Growth Assessment and Monitoring during Childhood. Ann Acad Med Singap. 2018;47(4):149–155.CrossRefGoogle ScholarPubMed
Homan, GJ. Failure to thrive: A practical guide. Am Fam Physician. 2016;94(4):295–299.Google ScholarPubMed
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. Morb Mortal Wkly Rep. 2018;67(6):186–189.CrossRefGoogle ScholarPubMed
Benjamin, EJ, Virani, SS, Callaway, CW, et al. Heart disease and stroke statistics-2018 update: a report from the American Heart Association. Circulation. 2018;137(12):e67–e492.CrossRefGoogle ScholarPubMed
Baranowski, T, O’Connor, T, Johnston, C, et al. School year versus summer differences in child weight gain: A narrative review. [Published online ahead of print December 24, 2013] Child Obes. 2014;10(1):18–24.Google Scholar
Brazendale, K, Beets, MW, Weaver, RG, et al. Understanding differences between summer vs. school obesogenic behaviors of children: The structured days hypothesis. Int J Behav Nutr Phys Act. 2017;14(1):100.CrossRefGoogle ScholarPubMed
Branscum, P, Kaye, G, Succop, P, Sharma, M. An evaluation of holiday weight gain among elementary-aged children. J Clin Med Res. 2010;2(4):167–171.Google ScholarPubMed
Smith, DT, Bartee, RT, Dorozynski, CM, Carr, LJ. Prevalence of overweight and influence of out-of-school seasonal periods on body mass index among American Indian school children. Prev Chronic Dis. 2009;6(1):20.Google Scholar
Moreno, JP, Johnston, CA, Woehler, D. Changes in weight over the school year and summer vacation: Results of a 5-year longitudinal study. J Sch Health. 2013;83(7):473–477.CrossRefGoogle ScholarPubMed
Kirizuka, K, Nishizaki, H, Kohriyama, K, et al. Influences of The Great Hanshin-Awaji Earthquake on glycemic control in diabetic patients. Diabetes Res Clin Pract. 1997;36(3):193–196.CrossRefGoogle ScholarPubMed
Stults-Kolehmainen, MA, Sinha, R. The effects of stress on physical activity and exercise. Sports Med. 2014;44(1):81–121.CrossRefGoogle ScholarPubMed
Michels, N, Sioen, I, Braet, C, et al. Stress, emotional eating behaviour and dietary patterns in children. Appetite. 2012;59(3):762–769.CrossRefGoogle ScholarPubMed
Balantekin, KN, Roemmich, JN. Children coping after psychological stress. Choices among food, physical activity, and television. Appetite. 2012;59(2):298–304.CrossRefGoogle ScholarPubMed
Michaud, C, Kahn, JP, Musse, N, Burlet, C, Nicolas, JP, Mejean, L. Relationships between a critical life event and eating behaviour in high-school students Stress Med. 1990;6(1):57–64.CrossRefGoogle Scholar
Glaser, R, Kiecolt-Glaser, JK. Stress-induced immune dysfunction: Implications for health. Nat Rev Immunol. 2005;5(3):243–251.CrossRefGoogle ScholarPubMed
Sawyer, SM, Afifi, RA, Bearinger, LH, et al. Adolescence: A foundation for future health. Lancet. 2012;379(9826):1630–1640.CrossRefGoogle ScholarPubMed
Chulani, VL, Gordon, LP. Adolescent growth and development. Prim Care. 2014;41(3):465–487.CrossRefGoogle ScholarPubMed
Kikuya, M, Matsubara, H, Ishikuro, M, et al. Alterations in physique among young children after the Great East Japan Earthquake: Results from a nationwide survey. J Epidemiol. 2017;27(10):462–468.CrossRefGoogle ScholarPubMed
Yokomichi, H, Zheng, W, Matsubara, H, et al. Impact of the great east Japan earthquake on the body mass index of preschool children: a nationwide nursery school survey. BMJ Open. 2016;(6):e010978.CrossRefGoogle Scholar
Zheng, W, Yokomichi, H, Matsubara, H, et al. Longitudinal changes in body mass index of children affected by the Great East Japan Earthquake. Int J Obes. 2017;41(4):606–612.CrossRefGoogle ScholarPubMed
Yamamura, E. Impact of the Fukushima nuclear accident on obesity of children in Japan (2008-2014). Econ Hum Biol. 2016;21:110–121.CrossRefGoogle Scholar
Nomura, S, Blangiardo, M, Tsubokura, M, Ochi, S, Hodgson, S. School restrictions on outdoor activities and weight status in adolescent children after Japan’s 2011 Fukushima Nuclear Power Plant disaster: A mid-term to long-term retrospective analysis. BMJ Open. 2016;6(9):e013145.CrossRefGoogle ScholarPubMed
Kuczmarski, RJ, Ogden, CL, Guo, SS, et al. 2000 CDC Growth Charts for the United States: methods and development. Vital Health Stat. 2002(246):1–190.Google Scholar
Hoelscher, DM, Day, RS, Kelder, SH, Ward, JL. Reproducibility and validity of the secondary level School-Based Nutrition Monitoring student questionnaire. J Am Diet Assoc. 2003;103(2):186–194.CrossRefGoogle ScholarPubMed
Penkilo, M, George, GC, Hoelscher, DM. Reproducibility of the school-based nutrition monitoring questionnaire among fourth-grade students in Texas. J Nutr Educ Behav. 2008;40(1):20–27.CrossRefGoogle ScholarPubMed
Ranjit, N, Evans, MH, Byrd-Williams, C, Evans, AE, Hoelscher, DM. Dietary and activity correlates of sugar-sweetened beverage consumption among adolescents. Pediatrics. 2010;126(4):e754–e761.CrossRefGoogle ScholarPubMed
Davison, KK, Falbe, J, Taveras, EM, et al. Evaluation overview for the Massachusetts Childhood Obesity Research Demonstration (MA-CORD) project. Child Obes. 2015;11(1):23–36.CrossRefGoogle ScholarPubMed
Larsen, AL, McArdle, JJ, Robertson, T, Dunton, G. Four dietary items of the School Physical Activity and Nutrition (SPAN) Questionnaire form a robust latent variable measuring healthy eating patterns. J Nutr Educ Behav. 2015;47(3):253–258.CrossRefGoogle Scholar
Brodie, M, Weltzien, E, Altman, D, Blendon, RJ, Benson, JM. Experiences of hurricane Katrina evacuees in Houston shelters: Implications for future planning. Am J Public Health. 2006;96(8):1402–1408.CrossRefGoogle ScholarPubMed
Hansel, TC, Osofsky, JD, Osofsky, HJ. Louisiana State University Health Sciences Center Katrina Inspired Disaster Screenings (KIDS): Psychometric testing of the National Child Traumatic Stress Network Hurricane Assessment and Referral Tool. Child Youth Care Forum. 2015;44(4):567–582.CrossRefGoogle Scholar
The National Child Traumatic Stress Network. National Child Traumatic Stress Network (NCTSN) Hurricane and Assessment Referral Tool 2005; http://www.nctsnet.org/. Accessed September 13, 2017.Google Scholar
Cohen, S, Kamarck, T, Mermelstein, R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385–396.CrossRefGoogle ScholarPubMed
van Jaarsveld, CH, Fidler, JA, Steptoe, A, Boniface, D, Wardle, J. Perceived stress and weight gain in adolescence: A longitudinal analysis. Obesity. 2009;17(12):2155–2161.CrossRefGoogle ScholarPubMed
Cartwright, M, Wardle, J, Steggles, N, Simon, AE, Croker, H, Jarvis, MJ. Stress and dietary practices in adolescents. Health Psychol. 2003;22(4):362–369.CrossRefGoogle ScholarPubMed
Plachta-Danielzik, S, Landsberg, B, Lange, D, Seiberl, J, Muller, MJ. Eight-year follow-up of school-based intervention on childhood overweight- the Kiel Obesity Prevention Study. Obes Facts. 2011;4(1):35–43.CrossRefGoogle ScholarPubMed
Preacher, KJ, Hayes, AF. SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behav Res Methods Instrum Comput. 2004;36(4):717–731.CrossRefGoogle ScholarPubMed
Wong, CJ. Involuntary weight loss. Med Clin North Am. 2014;98(3):625–643.CrossRefGoogle ScholarPubMed
Academy of Nutrition and Dietetics. Pediatric Nutrition Care Manual. Failure to Thrive Nutritional Indicators. http://www.nutritioncaremanual.org. Accessed March 26, 2018.Google Scholar
Al-Khudairy, L, Loveman, E, Colquitt, JL, et al. Diet, physical activity and behavioural interventions for the treatment of overweight or obese adolescents aged 12 to 17 years. Cochrane Database Syst Rev. 2017;6(6):Cd012691.Google ScholarPubMed
Mullins, CD, Blatt, L, Gbarayor, CM, Yang, HW, Baquet, C. Health disparities: A barrier to high-quality care. Am J Health Syst Pharm. 2005;62(18):1873–1882.CrossRefGoogle ScholarPubMed
Drenick, EJ, Johnson, D. Weight reduction by fasting and semi-starvation in morbid obesity: Long-term follow-up. Int J Obes. 1978;2(2):123–132.Google Scholar
Gorin, AA, Phelan, S, Wing, RR, Hill, JO. Promoting long-term weight control: Does dieting consistency matter? Int J Obes Relat Metab Disord. 2004;28(2):278–281.CrossRefGoogle ScholarPubMed
Paisey, RB, Frost, J, Harvey, P, et al. Five year results of a prospective very low calorie diet or conventional weight loss programme in type 2 diabetes. J Hum Nutr Diet. 2002;15(2):121–127.CrossRefGoogle ScholarPubMed
Banasik, JL, Walker, MK, Randall, JM, Netjes, RB, Foutz, MS. Low-calorie diet induced weight loss may alter regulatory hormones and contribute to rebound visceral adiposity in obese persons with a family history of type-2 diabetes. J Am Assoc Nurse Pract. 2013;25(8):440–448.Google ScholarPubMed
Liu, J, Fox, CS, Hickson, DA, et al. Impact of abdominal visceral and subcutaneous adipose tissue on cardiometabolic risk factors: The Jackson Heart Study. J Clin Endocrinol Metab. 2010;95(12):5419–5426.CrossRefGoogle ScholarPubMed
Wang, Y, Rimm, EB, Stampfer, MJ, Willett, WC, Hu, FB. Comparison of abdominal adiposity and overall obesity in predicting risk of type 2 diabetes among men. Am J Clin Nutr. 2005;81(3):555–563.CrossRefGoogle ScholarPubMed