Startseite Clustering of chronic diseases risk factors among adolescents: a quasi-experimental study in Sousse, Tunisia
Artikel
Lizenziert
Nicht lizenziert Erfordert eine Authentifizierung

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

  • Emna Dendana , Rim Ghammem , Jihene Sahli EMAIL logo , Jihen Maatoug , Sihem Ben Fredj , Imed Harrabi , Molka Chaieb und Hassen Ghannem
Veröffentlicht/Copyright: 21. Juni 2017

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.

Acknowledgment

This paper was based on a project funded by the United Health Group and by the Research Unit “Santé UR12SP28” (Epidemiologic transition and prevention of chronic disease of the Ministry of Higher Education, Tunisia).

References

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

[2] WHO. Preventing chronic diseases: a vital investment: WHO Global Report. Geneva: World Health Organization, 2005.Suche in 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):124–30.10.1016/j.amepre.2006.10.012Suche in Google 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):750–63.10.1093/jpepsy/jsj126Suche in Google 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):923–31.10.1079/BJN20051418Suche in Google 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):1279–89.10.1093/aje/kwp284Suche in Google 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):219–24.10.1006/pmed.2002.1064Suche in Google 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):363–7.10.1016/S0091-7435(03)00145-2Suche in Google 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):25–33.10.1016/j.amepre.2004.04.022Suche in Google Scholar PubMed

[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):393–6.10.1016/j.ypmed.2012.03.014Suche in Google Scholar PubMed PubMed Central

[11] Prochaska JJ, Spring B, Nigg CR. Multiple health behavior change research: an introduction and overview. Prev Med. 2008;46(3):181–8.10.1016/j.ypmed.2008.02.001Suche in Google Scholar PubMed PubMed Central

[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).10.1002/14651858.CD001871.pub3Suche in Google Scholar PubMed

[13] Poortinga W. The prevalence and clustering of four major lifestyle risk factors in an English adult population. Prev Med. 2007;44(2):124–8.10.1016/j.ypmed.2006.10.006Suche in Google 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:E160.10.5888/pcd12.140518Suche in Google 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):749–53.10.1016/S0140-6736(06)68192-0Suche in Google Scholar

[16] American Academy of Pediatrics. Children, adolescents, and television. Pediatrics. 2001;107:423–426.10.1542/peds.107.2.423Suche in Google Scholar PubMed

[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):1240.10.1136/bmj.320.7244.1240Suche in Google Scholar PubMed PubMed Central

[18] Alamian A, Paradis G. Clustering of chronic disease behavioral risk factors in Canadian children and adolescents. Prev Med. 2009;48(5):493–9.10.1016/j.ypmed.2009.02.015Suche in Google Scholar PubMed

[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):862–8.10.1097/01.psy.0000188576.54698.36Suche in Google Scholar PubMed

[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):515–23.10.1097/00043798-199512000-00006Suche in Google 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):1042–8.10.2337/diabetes.49.6.1042Suche in Google Scholar PubMed

[22] Wannamethee SG, Shaper AG, Durrington PN, Perry IJ. Hypertension, serum insulin, obesity and the metabolic syndrome. J Hum Hypertens. 1998;12(11):735–41.10.1038/sj.jhh.1000714Suche in Google Scholar PubMed

[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):872–9.10.1016/j.ypmed.2004.10.005Suche in Google 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):238–44.10.1016/S1054-139X(04)00059-XSuche in Google 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):449–54.10.4414/smw.2002.10011Suche in Google 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):240–6.10.1016/S0749-3797(02)00418-XSuche in Google 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):300–8.10.1038/ejcn.2013.170Suche in Google Scholar PubMed

[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):370–8.10.1157/13080135Suche in Google 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):942–9.10.1123/jpah.2012-0247Suche in Google Scholar PubMed

[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):126–33.10.1111/j.1746-1561.2009.00476.xSuche in Google Scholar PubMed

[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):117–33.10.1111/obr.12105Suche in Google Scholar PubMed

[32] French SA, Story M, Jeffery RW. Environmental influences on eating and physical activity. Annu Rev Public Health. 2001;22:309–35.10.1146/annurev.publhealth.22.1.309Suche in Google Scholar PubMed

[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):110–5.10.1089/chi.2011.0071Suche in Google Scholar PubMed PubMed Central

[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):123–46.10.1079/PHN2003585Suche in Google 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):122–8.10.1016/j.clnu.2009.01.001Suche in Google Scholar PubMed

[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):273–80.10.1542/peds.91.2.273Suche in Google 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;4:26.10.1186/1479-5868-4-26Suche in Google Scholar PubMed PubMed Central

[38] Barness LA, Opitz JM, Gilbert-Barness E. Obesity: genetic, molecular, and environmental aspects. Am J Med Genet A. 2007;143A(24):3016–34.10.1002/ajmg.a.32035Suche in Google Scholar PubMed

[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):211–216.10.1515/ijamh-2015-0013Suche in Google Scholar PubMed

[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):223–30.10.3961/jpmph.2009.42.4.223Suche in Google Scholar PubMed

[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):114–7.10.1136/tc.2004.008789Suche in Google Scholar PubMed PubMed Central

[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):235–44.10.1249/MSS.0000000000000760Suche in Google Scholar PubMed PubMed Central

[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):E23–33.10.9778/cmajo.20140053Suche in Google Scholar PubMed PubMed Central

Received: 2017-02-08
Accepted: 2017-03-22
Published Online: 2017-06-21

©2019 Walter de Gruyter GmbH, Berlin/Boston

Artikel in diesem Heft

  1. Editorial
  2. Adverse effects of stimulant medications in children and adolescents: focus on drug abuse
  3. Short Communication
  4. Adolescent and parent perspectives prior to involvement in a Fontan transition program
  5. Reviews
  6. Adolescent suicide as a global public health issue
  7. (Health-related) quality of life and psychosocial factors in adolescents with chronic disease: a systematic literature review
  8. Original Articles
  9. Clustering of chronic diseases risk factors among adolescents: a quasi-experimental study in Sousse, Tunisia
  10. Blood, joy and tears: menarche narratives of undergraduate females in a selected in Nigeria Private University
  11. Renal lymphangiectasia treated with percutaneous drainage and sclerotherapy
  12. Trichotillomania in celiac disease patient refractory to iron replacement
  13. Metabolic syndrome in Iranian adolescents with polycystic ovary syndrome
  14. Looks can be deceiving: body image dissatisfaction relates to social anxiety through fear of negative evaluation
  15. Excessive exercise among adolescents with eating disorders: examination of psychological and demographic variables
  16. Diet quality of adolescents with eating disorders
  17. A picture of Indian adolescent mental health: an analysis from three urban secondary schools
  18. From child to grown up in a medical world: developing an adolescent transition programme at a Norwegian University hospital
  19. Household food insecurity and its association with morbidity report among school adolescent in Jimma zone, Ethiopia
  20. The effects of introducing Tabata interval training and stability exercises to school children as a school-based intervention program
Heruntergeladen am 27.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/ijamh-2017-0022/html
Button zum nach oben scrollen