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International Journal of Adolescent Medicine and Health

Editor-in-Chief: Merrick, Joav

Editorial Board: Birch, Diana ML / Blum, Robert W. / Greydanus, MD, Dr. HC (Athens), Donald E. / Hardoff, Daniel / Kerr, Mike / Levy, Howard B / Morad, Mohammed / Omar, Hatim A. / de Paul, Joaquin / Rydelius, Per-Anders / Shek, Daniel T.L. / Sher, Leo / Silber, Tomas J. / Towns, Susan / Urkin, Jacob / Verhofstadt-Deneve, Leni / Zeltzer, Lonnie / Tenenbaum, Ariel


CiteScore 2018: 0.79

SCImago Journal Rank (SJR) 2018: 0.350
Source Normalized Impact per Paper (SNIP) 2018: 0.476

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2191-0278
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Volume 31, Issue 4

Issues

Clustering of chronic diseases risk factors among adolescents: a quasi-experimental study in Sousse, Tunisia

Emna Dendana
  • Department of Epidemiology, University Hospital Farhat Hached, Sousse, Tunisia
  • Department of Endocrinology, University Hospital Farhat Hached, Sousse, Tunisia
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Rim Ghammem / Jihene Sahli
  • Corresponding author
  • Department of Epidemiology, University Hospital Farhat Hached, Sousse, Tunisia, Phone: 00216 73 219 496, Fax: 00216 73 226 702
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Jihen Maatoug / Sihem Ben Fredj / Imed Harrabi / Molka Chaieb / Hassen Ghannem
Published Online: 2017-06-21 | DOI: https://doi.org/10.1515/ijamh-2017-0022

Abstract

Background

The objective of the study was to evaluate the effectiveness of a school-based physical activity and nutritional behavior intervention, on the reduction of clustering of chronic diseases risk factors among school children.

Materials and methods

A quasi-experimental school-based intervention was conducted with an intervention group and a control group in the region of Sousse in Tunisia. The intervention was implemented between 2010 and 2013, with data collected at pre and at post intervention. Studied risk factors were: smoking, sedentary behavior, low fruit and vegetable intake and obesity. Odds ratios (ORs) were used to calculate the clustering of two risk factors. We calculated ORs in each group before and after the intervention.

Results

In the intervention group, the prevalence of adolescents that had no risk factors has significantly increased (p = 0.004). In the control group the prevalence of adolescents carrying two or more risk factors has increased (p = 0.06). The results showed that all risk factors tended to cluster together in both groups. In the intervention group, the calculated OR for smoking and sedentary behavior decreased after assessment (OR = 5.93) as well as the OR for smoking and low fruit and vegetable intake (OR = 3.26). In the control group, all ORs increased, showing an enhancement of the association.

Conclusion

This study showed the effectiveness of a school-based intervention in reducing the clustering of chronic diseases risk factors.

Keywords: adolescent; chronic diseases; cluster analysis; risk factors

References

  • [1]

    WHO. The world health report 2002. Reducing Risks, Promoting Healthy Life. Geneva: World Health Organization, 2002.Google Scholar

  • [2]

    WHO. Preventing chronic diseases: a vital investment: WHO Global Report. Geneva: World Health Organization, 2005.Google Scholar

  • [3]

    Sanchez A, Norman GJ, Sallis JF, Calfas KJ, Cella J, Patrick K. Patterns and correlates of physical activity and nutrition behaviors in adolescents. Am J Prev Med. 2007;32(2):124–30.Web of SciencePubMedCrossrefGoogle Scholar

  • [4]

    Tercyak KP, Tyc VL. Opportunities and challenges in the prevention and control of cancer and other chronic diseases: children’s diet and nutrition and weight and physical activity. J Pediatr Psychol. 2006;31(8):750–63.CrossrefPubMedGoogle Scholar

  • [5]

    Mikkilä V, Räsänen L, Raitakari OT, Pietinen P, Viikari J. Consistent dietary patterns identified from childhood to adulthood: the cardiovascular risk in Young Finns Study. Br J Nutr. 2005;93(6):923–31.PubMedCrossrefGoogle Scholar

  • [6]

    Alamian A, Paradis G. Correlates of multiple chronic disease behavioral risk factors in Canadian children and adolescents. Am J Epidemiol. 2009;170(10):1279–89.Web of ScienceCrossrefPubMedGoogle Scholar

  • [7]

    Schuit AJ, van Loon AJ, Tijhuis M, Ocké M. Clustering of lifestyle risk factors in a general adult population. Prev Med. 2002;35(3):219–24.CrossrefGoogle Scholar

  • [8]

    Andersen LB, Wedderkopp N, Hansen HS, Cooper AR, Froberg K. Biological cardiovascular risk factors cluster in Danish children and adolescents: the European Youth Heart Study. Prev Med. 2003;37(4):363–7.CrossrefPubMedGoogle Scholar

  • [9]

    Pronk NP, Anderson LH, Crain AL, Martinson BC, O’Connor PJ, Sherwood NE, et al. Meeting recommendations for multiple healthy lifestyle factors. Prevalence, clustering, and predictors among adolescent, adult, and senior health plan members. Am J Prev Med. 2004;27(Suppl 2):25–33.CrossrefPubMedGoogle Scholar

  • [10]

    Dumith SC, Muniz LC, Tassitano RM, Hallal PC, Menezes AM. Clustering of risk factors for chronic diseases among adolescents from Southern Brazil. Prev Med. 2012;54(6):393–6.PubMedCrossrefWeb of ScienceGoogle Scholar

  • [11]

    Prochaska JJ, Spring B, Nigg CR. Multiple health behavior change research: an introduction and overview. Prev Med. 2008;46(3):181–8.Web of ScienceCrossrefPubMedGoogle Scholar

  • [12]

    Waters E, de Silva-Sanigorski A, Hall BJ, Brown T, Campbell KJ, Gao Y, et al. Interventions for preventing obesity in children. Cochrane Database Syst Rev. 2011;CD001871(12).PubMedGoogle Scholar

  • [13]

    Poortinga W. The prevalence and clustering of four major lifestyle risk factors in an English adult population. Prev Med. 2007;44(2):124–8.Web of ScienceCrossrefGoogle Scholar

  • [14]

    Maatoug J, Msakni Z, Zammit N, Bhiri S, Harrabi I, Boughammoura L, et al. School-based intervention as a component of a comprehensive community program for overweight and obesity prevention, Sousse, Tunisia, 2009–2014. Preventing Chronic Dis. 2015;12:E160.Web of ScienceGoogle Scholar

  • [15]

    Warren CW, Jones NR, Eriksen MP, Asma S. Global tobacco surveillance system (GTSS) collaborative group. Patterns of global tobacco use in young people and implications for future chronic disease burden in adults. Lancet Lond Engl. 2006;367(9512):749–53.CrossrefGoogle Scholar

  • [16]

    American Academy of Pediatrics. Children, adolescents, and television. Pediatrics. 2001;107:423–426.PubMedGoogle Scholar

  • [17]

    Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweight and obesity worldwide: international survey. Br Med J. 2000;320(7244):1240.CrossrefGoogle Scholar

  • [18]

    Alamian A, Paradis G. Clustering of chronic disease behavioral risk factors in Canadian children and adolescents. Prev Med. 2009;48(5):493–9.CrossrefPubMedWeb of ScienceGoogle Scholar

  • [19]

    Lawlor DA, O’Callaghan MJ, Mamun AA, Williams GM, Bor W, Najman JM. Socioeconomic position, cognitive function, and clustering of cardiovascular risk factors in adolescence: findings from the Mater University Study of Pregnancy and its outcomes. Psychosom Med. 2005;67(6):862–8.PubMedCrossrefGoogle Scholar

  • [20]

    Milligan RA, Thompson C, Vandongen R, Beilin LJ, Burke V. Clustering of cardiovascular risk factors in Australian adolescents: association with dietary excesses and deficiencies. J Cardiovasc Risk. 1995;2(6):515–23.PubMedGoogle Scholar

  • [21]

    Chen W, Bao W, Begum S, Elkasabany A, Srinivasan SR, Berenson GS. Age-related patterns of the clustering of cardiovascular risk variables of syndrome X from childhood to young adulthood in a population made up of black and white subjects: the Bogalusa Heart Study. Diabetes. 2000;49(6):1042–8.CrossrefGoogle Scholar

  • [22]

    Wannamethee SG, Shaper AG, Durrington PN, Perry IJ. Hypertension, serum insulin, obesity and the metabolic syndrome. J Hum Hypertens. 1998;12(11):735–41.PubMedCrossrefGoogle Scholar

  • [23]

    Wilson DB, Smith BN, Speizer IS, Bean MK, Mitchell KS, Uguy LS, et al. Differences in food intake and exercise by smoking status in adolescents. Prev Med. 2005;40(6):872–9.CrossrefPubMedGoogle Scholar

  • [24]

    Paavola M, Vartiainen E, Haukkala A. Smoking, alcohol use, and physical activity: a 13-year longitudinal study ranging from adolescence into adulthood. J Adolesc Health Off Publ Soc Adolesc Med. 2004;35(3):238–44.CrossrefGoogle Scholar

  • [25]

    Yorulmaz F, Akturk Z, Dagdeviren N, Dalkilic A. Smoking among adolescents: relation to school success, socioeconomic status nutrition and self-esteem. Swiss Med Wkly. 2002;132(31–32):449–54.PubMedGoogle Scholar

  • [26]

    Baer Wilson D, Nietert PJ. Patterns of fruit, vegetable, and milk consumption among smoking and nonsmoking female teens. Am J Prev Med. 2002;22(4):240–6.CrossrefPubMedGoogle Scholar

  • [27]

    Santaliestra-Pasías AM, Mouratidou T, Huybrechts I, Beghin L, Cuenca-García M, Castillo MJ, et al. Increased sedentary behaviour is associated with unhealthy dietary patterns in European adolescents participating in the HELENA study. Eur J Clin Nutr. 2014;68(3):300–8.CrossrefPubMedWeb of ScienceGoogle Scholar

  • [28]

    Galán I, Rodríguez-Artalejo F, Tobías A, Díez-Gañán L, Gandarillas A, Zorrilla B. Clustering of behavior-related risk factors and its association with subjective health. Gac Sanit SESPAS. 2005;19(5):370–8.CrossrefGoogle Scholar

  • [29]

    Cureau FV, Duarte P, dos Santos DL, Reichert FF. Clustering of risk factors for noncommunicable diseases in Brazilian adolescents: prevalence and correlates. J Phys Act Health. 2014;11(5):942–9.Web of ScienceCrossrefPubMedGoogle Scholar

  • [30]

    Tassitano RM, Barros MV, Tenório MC, Bezerra J, Florindo AA, Reis RS. Enrollment in physical education is associated with health-related behavior among high school students. J Sch Health. 2010;80(3):126–33.CrossrefPubMedWeb of ScienceGoogle Scholar

  • [31]

    Marsh S, Foley LS, Wilks DC, Maddison R. Family-based interventions for reducing sedentary time in youth: a systematic review of randomized controlled trials. Obes Rev Off J Int Assoc Study Obes. 2014;15(2):117–33.CrossrefGoogle Scholar

  • [32]

    French SA, Story M, Jeffery RW. Environmental influences on eating and physical activity. Annu Rev Public Health. 2001;22:309–35.CrossrefPubMedGoogle Scholar

  • [33]

    Carlson JA, Crespo NC, Sallis JF, Patterson RE, Elder JP. Dietary-related and physical activity-related predictors of obesity in children: a 2-year prospective study. Child Obes Print. 2012;8(2):110–5.Google Scholar

  • [34]

    Swinburn BA, Caterson I, Seidell JC, James WP. Diet, nutrition and the prevention of excess weight gain and obesity. Public Health Nutr. 2004;7(1A):123–46.CrossrefPubMedGoogle Scholar

  • [35]

    Bayer O, von Kries R, Strauss A, Mitschek C, Toschke AM, Hose A, et al. Short- and mid-term effects of a setting based prevention program to reduce obesity risk factors in children: a cluster-randomized trial. Clin Nutr. 2009;28(2):122–8.Web of ScienceCrossrefGoogle Scholar

  • [36]

    Robinson TN, Hammer LD, Killen JD, Kraemer HC, Wilson DM, Hayward C, et al. Does television viewing increase obesity and reduce physical activity? Cross-sectional and longitudinal analyses among adolescent girls. Pediatrics. 1993;91(2):273–80.PubMedGoogle Scholar

  • [37]

    Boone JE, Gordon-Larsen P, Adair LS, Popkin BM. Screen time and physical activity during adolescence: longitudinal effects on obesity in young adulthood. Int J Behav Nutr Phys Act. 2007;4:26.PubMedCrossrefWeb of ScienceGoogle Scholar

  • [38]

    Barness LA, Opitz JM, Gilbert-Barness E. Obesity: genetic, molecular, and environmental aspects. Am J Med Genet A. 2007;143A(24):3016–34.PubMedCrossrefWeb of ScienceGoogle Scholar

  • [39]

    Maatoug J, Sahli J, Harrabi I, Chouikha F, Hmad S, Dendana E, et al. Assessment of the validity of self-reported smoking status among schoolchildren in Sousse, Tunisia. Int J Adolesc Med Health. 2015;28(2):211–216.Google Scholar

  • [40]

    Park SW, Kim JY. Validity of self-reported smoking using urinary cotinine among vocational high school students. J Prev Med Public Health Yebang Ŭihakhoe Chi. 2009;42(4):223–30.CrossrefGoogle Scholar

  • [41]

    Post A, Gilljam H, Rosendahl I, Meurling L, Bremberg S, Galanti MR. Validity of self reports in a cohort of Swedish adolescent smokers and smokeless tobacco (snus) users. Tob Control. 2005;14(2):114–7.CrossrefGoogle Scholar

  • [42]

    Steene-Johannessen J, Anderssen SA, Van Der Ploeg HP, Hendriksen IJ, Donnelly AE, Brage S, et al. Are self-report measures able to define individuals as physically active or inactive?. Med Sci Sports Exerc. 2016;48(2):235–44.CrossrefPubMedWeb of ScienceGoogle Scholar

  • [43]

    Peirson L, Fitzpatrick-Lewis D, Morrison K, Ciliska D, Kenny M, Ali MU, et al. Prevention of overweight and obesity in children and youth: a systematic review and meta-analysis. CMAJ Open. 2015;3(1):E23–33.CrossrefPubMedGoogle Scholar

About the article

Received: 2017-02-08

Accepted: 2017-03-22

Published Online: 2017-06-21


Citation Information: International Journal of Adolescent Medicine and Health, Volume 31, Issue 4, 20170022, ISSN (Online) 2191-0278, DOI: https://doi.org/10.1515/ijamh-2017-0022.

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