Nutrición Hospitalaria 00666 / http://dx.doi.org/10.20960/nh.666
Resumen| PDF (ENGLISH)

Trabajo Original

Risk behavior patterns for chronic diseases and associated factors among adolescents


Edilayane De Meneses Sousa Sena, Ana Paula Muraro, Paulo Rogério Melo Rodrigues, Rosemeyre França De Paula Fiuza, Márcia Gonçalves Ferreira

Logo Descargas   Número de descargas: 3919      Logo Visitas   Número de visitas: 8718      Citas   Citas: 0

Compártelo:


Background/objective: Simultaneous engagement in risk behaviors for chronic non-communicable diseases (NCDs) might exert a synergistic effect on adolescent health. This study aimed to identify risk behavior patterns for NCDs in adolescents and analyze associated factors.Methods: Cross-sectional study conducted between 2009 and 2011, with 1,716 participants aged 10-17 years of a cohort study in Central-West Region, Brazil. Demographic, economic, anthropometric, and lifestyle characteristics were collected. Risk behaviors evaluated were alcohol consumption, tobacco experimentation, insufficient physical activity, sedentary behavior, skipping breakfast, and low diet quality. Principal component analysis was used to identify patterns of risk behaviors and multiple linear regression analysis to quantify the association between independent variables and patterns of risk behavior.Results: Three patterns of risk behaviors were identified: “legal drugs”, “diet and screens”, and “silent”. After adjustment, legal drugs pattern showed direct association with age (β = 0.13; 95% CI = 0.09; 0.16) and inverse association with maternal education (β = -0.07; 95% CI = -0.14; -0.01). Diet and screens pattern were directly associated with female gender (β = 0.14; 95% CI = 0.04; 0.23), age (β = 0.11; 95% CI = 0.08; 0.14), and economic class (β = 0.15; 95% CI = 0.04; 0.25). Silent pattern was directly associated with maternal education (β = 0.09; 95% CI = 0.03; 0.15), being overweight (β = 0.17; 95% CI = 0.06; 0.28), and female gender (β = 0.32; 95% CI= 0.22; 0.41).Conclusions: Three risk behavior patterns were identified and the associated factors were socioeconomic status, age, and female gender.

Palabras Clave: Adolescent. Risk factors. Lifestyle. Adolescent behavior. Chronic disease. Factor analysis



WHO | Global status report on noncommunicable diseases 2014. World Health Organization; [cited 2016 Mar 29]; Available from: http://www.who.int/nmh/publications/ncd-status-report-2014/en/#.VvntV3jU_0I.mendeley
Steinberg L. Risk taking in adolescence: What changes, and why? Ann. N. Y. Acad. Sci. 2004. p. 51–8.
Proimos J, Klein JD. Noncommunicable Diseases in Children and Adolescents. Pediatrics [Internet]. 2012;130:379–81. Available from: http://pediatrics.aappublications.org/cgi/doi/10.1542/peds.2012-1475
Mikkilä V, Räsänen L, Raitakari OT, Pietinen P, Viikari J. Longitudinal changes in diet from childhood into adulthood with respect to risk of cardiovascular diseases: The Cardiovascular Risk in Young Finns Study. Eur. J. Clin. Nutr. [Internet]. 2004;58:1038–45. Available from: http://www.ncbi.nlm.nih.gov/pubmed/15220946
van Nieuwenhuijzen M, Junger M, Velderman MK, Wiefferink KH, Paulussen TWGM, Hox J, et al. Clustering of health-compromising behavior and delinquency in adolescents and adults in the Dutch population. Prev. Med. (Baltim). 2009;48:572–8.
DOI: 10.1016/j.ypmed.2009.04.008
Busch V, Van Stel HF, Schrijvers AJP, de Leeuw JRJ. Clustering of health-related behaviors, health outcomes and demographics in Dutch adolescents: a cross-sectional study. BMC Public Health [Internet]. 2013;13:1118. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3890495&tool=pmcentrez&rendertype=abstract
de Winter AF, Visser L, Verhulst FC, Vollebergh WA, Reijneveld SA. Longitudinal patterns and predictors of multiple health risk behaviors among adolescents: The TRAILS study. Prev Med. 2015;
Rodrigues PRM, CMP; P, MG; F, RMV; G-S, RA P. Multiple risk behaviors for noncommunicable diseases and associated factors in adolescents. Rev Nutr. 2016;
Longshore D, Ghosh-Dastidar B, Ellickson PL. National Youth Anti-Drug Media Campaign and school-based drug prevention: Evidence for a synergistic effect in ALERT Plus. Addict. Behav. 2006;31:496–508.
Gonçalves-Silva RMV, Sichieri R, Ferreira MG, Pereira RA, Muraro AP, Moreira NF, et al. O censo escolar como estratégia de busca de crianças e adolescentes em estudos epidemiológicos. Cad. Saude Publica. 2012;28:400–4.
DOI: 10.1590/S0102-311X2012000200019
Abep. Critério Padrão de Classificação Econômica Brasil. From http//www.abep.org/codigosguias/Criterio_Brasil_2008.pdf. 2008;
AF GCCWR. Stature, recumbent length, and weight. In: Lohman, TG; Roche AM, R, editors. Antropometric Stand. Ref. Man. Illinois: Human Kinetics Books; 1988. p. 3–8.
WHO WHO-. Growth reference data for 5-19 years: body mass index-for-age, length/height-for-age and weight-for-height. Geneva-Switzerland; 2007.
Currie, C; Roberts, C; Morgan, A; Smith, R; Settertobulte, W; Samdal O, Barnekow Rasmussen V. Young people’s health in context. Health Behaviour in School-aged Children (HBSC) study: international report from the 2001/2002 survey [Internet]. WHO. 2004. Available from: http://www.euro.who.int/__data/assets/pdf_file/0008/110231/e82923.pdf
Currie C, Gabhainn SN, Godeau E, Roberts C, Smith R, Currie D, et al. Inequalities in young people’s health. HBSC international report from the
2005/2006 survey. Heal. policy Child. Adolesc. Ser. No 5. 2008.
Wendpap LL, Ferreira MG, Rodrigues PRM, Pereira RA, Loureiro A da S, Gonçalves-Silva RMV. [Adolescents’ diet quality and associated factors]. Cad. Saude Publica [Internet]. 2014;30:97–106. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24627017
Kaiser HF. An index of factorial simplicity. Psychometrika. 1974;39:31–6.
DOI: 10.1007/BF02291575
Olinto M. Padrões alimentares: análise de componentes principais. In: Kac, G; Sichieri, R; Gigante D, editor. Epidemiol. Nutr. Rio de Janeiro; 2007. p. 213–25.
Cattell RB. The Scree Test For The Number Of Factors. Multivariate Behav. Res. 1966;1:245–76.
Kontogianni MD, Farmaki AE, Vidra N, Sofrona S, Magkanari F, Yannakoulia M. Associations between Lifestyle Patterns and Body Mass Index in a Sample of Greek Children and Adolescents. J. Am. Diet. Assoc. 2010;110:215–21.
Moschonis G, Kalliora AC, Costarelli V, Papandreou C, Koutoukidis D, Lionis C, et al. Identification of lifestyle patterns associated with obesity and fat mass in children: the Healthy Growth Study. Public Health Nutr. [Internet]. 2014;17:614–24. Available from: http://www.ncbi.nlm.nih.gov/pubmed/23531449
Barreto SM, Giatti L, Oliveira-Campos M, Andreazzi MA, Malta DC. Experimentation and use of cigarette and other tobacco products among adolescents in the Brazilian state capitals (PeNSE 2012). Rev. Bras. Epidemiol. [Internet]. 2014;17:62–76. Available from: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2014000500062&lng=en&nrm=iso&tlng=en
Rhee SH, Hewitt JK, Young SE, Corley RP, Crowley TJ, Stallings MC. Genetic and environmental influences on substance initiation, use, and problem use in adolescents. Arch. Gen. Psychiatry [Internet]. 2003;60:1256–64. Available from: http://www.ncbi.nlm.nih.gov/pubmed/14662558
MacArthur GJ, Smith MC, Melotti R, Heron J, Macleod J, Hickman M, et al. Patterns of alcohol use and multiple risk behaviour by gender during early and late adolescence: the ALSPAC cohort. J Public Heal. 2012;34 Suppl 1:i20–30.
Malta DC, Mascarenhas MDM, Porto DL, Barreto SM, De Morais Neto OL. Exposure to alcohol among adolescent students and associated factors. Rev. Saude Publica. 2014;48:52–62.
DOI: 10.1590/S0034-8910.2014048004563
Narain R, Sardana S, Gupta S, Sehgal A. Risk factors associated with tobacco habits among adolescents: A cross-sectional school-based study. Natl. Med. J. India. 2013;26:197–202.
Matos AM, Carvalho RC, Conceição M, Costa O, Santos LM. Frequent consumption of alcohol by school age adolescents: study of associated factors. Rev Bras Epidemiol. 2010;13:1–12.
Ottevaere C, Huybrechts I, Benser J, De Bourdeaudhuij I, Cuenca-Garcia M, Dallongeville J, et al. Clustering patterns of physical activity, sedentary and dietary behavior among European adolescents: The HELENA study. BMC Public Health [Internet]. 2011;11:328. Available from: http://www.biomedcentral.com/1471-2458/11/328
Vereecken C a, Todd J, Roberts C, Mulvihill C, Maes L. Television viewing behaviour and associations with food habits in different countries. Public Health Nutr. 2006;9:244–50.
Allafi A, Al-Haifi AR, Al-Fayez MA, Al-Athari BI, Al-Ajmi FA, Al-Hazzaa HM, et al. Physical activity, sedentary behaviours and dietary habits among Kuwaiti adolescents: gender differences. Public Health Nutr. [Internet]. 2014;17:2045–52. Available from: http://www.journals.cambridge.org/abstract_S1368980013002218
Dias PJP, Domingos IP, Ferreira MG, Muraro AP, Sichieri R, Gonçalves-Silva RMV. Prevalence and factors associated with sedentary behavior in adolescents. Rev. Saude Publica. 2014;48:266–74.
DOI: 10.1590/S0034-8910.2014048004635
Neutzling MB, Assunção MCF, Malcon MC, Hallal PC, Menezes AMB. Hábitos alimentares de escolares adolescentes de Pelotas, Brasil. Rev. Nutr. 2010;23:379–88.
Matthews CE, Chen KY, Freedson PS, Buchowski MS, Beech BM,
Pate RR, et al. Amount of time spent in sedentary behaviors in the United States, 2003-2004. Am. J. Epidemiol. 2008;167:875–81.
Corte-Real N, Balaguer I, Dias C, Corredeira R, Fonseca A. Actividade física, prática desportiva, consumo de alimentos, de tabaco e de álcool dos adolescentes portugueses. Rev. Port. Saúde Pública. 2008;26:17–25.
Azeredo CM, de Rezende LF, Canella DS, Claro RM, de Castro IR, Luiz O do C, et al. Dietary intake of Brazilian adolescents. Public Health Nutr. 2015;18:1215–24.
DOI: 10.1017/S1368980014001463
Lucena JMS, Cheng LA, Cavalcante TLM, Silva VA, Farias Júnior C. Prevalência de tempo excessivo de tela e fatores associados em adolescentes. Rev. Paul. Pediatr. [Internet]. Sociedade de Pediatria de São Paulo; 2015;33:1–8. Available from: http://dx.doi.org/10.1016/j.rpped.2015.04.001
DOI: 10.1016/j.rpped.2015.04.001
Barreto Neto AC, De Andrade MaIS, Lima VL de M, Diniz A da S. Peso corporal e escores de consumo alimentar em adolescentes no nordeste brasileiro. Rev. Paul. Pediatr. [Internet]. Associação de Pediatria de São Paulo; 2015;33:318–25. Available from: http://dx.doi.org/10.1016/j.rpped.2015.01.002
DOI: 10.1016/j.rpped.2015.01.002
IBGE. Pesquisa de Orçamentos Familiares: 2008-2009. Análise do Consumo Alimentar Pessoal no Brasil [Internet]. Bibl. do Minist. do Planejamento, Orçamento e Gestão. 2010. Available from: http://www.ibge.gov.br/home/estatistica/populacao/condicaodevida/pof/2008_2009_analise_consumo/pofanalise_2008_2009.pdf
Arora M, Nazar GP, Gupta VK, Perry CL, Reddy KS, Stigler MH. Association of breakfast intake with obesity, dietary and physical activity behavior among urban school-aged adolescents in Delhi, India: results of a cross-sectional study. BMC Public Health [Internet]. 2012;12:881. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3549919&tool=pmcentrez&rendertype=abstract
Nasreddine L, Naja F, Akl C, Chamieh MC, Karam S, Sibai AM, et al. Dietary, lifestyle and socio-economic correlates of overweight, obesity and central adiposity in lebanese children and adolescents. Nutrients. 2014;6:1038–62.
DOI: 10.3390/nu6031038
Corder K, van Sluijs EMF, Steele RM, Stephen a M, Dunn V, Bamber D, et al. Breakfast consumption and physical activity in British adolescents. Br. J. Nutr. 2011;105:316–21.
DOI: 10.1017/S0007114510003272
Farias Júnior JC de, Lopes A da S, Mota J, Hallal PC. Prática de atividade física e fatores associados em adolescentes no Nordeste do Brasil. Rev. Saude Publica [Internet]. 2012;46:505–15. Available from: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102012000300013&lng=pt&nrm=iso&tlng=en
Barufaldi LA, Abreu G de A, Oliveira JS, Santos DF Dos, Fujimori E, Vasconcelos SML, et al. ERICA: prevalence of healthy eating habits among Brazilian adolescents. Rev. Saude Publica. 2016;50 Suppl 1:1–9.
Rampersaud GC, Pereira MA, Girard BL, Adams J, Metzl JD. Breakfast habits, nutritional status, body weight, and academic performance in children and adolescents. J. Am. Diet. Assoc. 2005. p. 743–60.
Hallal PC, Wells JCK, Reichert FF, Anselmi L, Victora CG. Early determinants of physical activity in adolescence: prospective birth cohort study. BMJ. 2006;332:1002–7.
DOI: 10.1136/bmj.38776.434560.7C
Sjöberg a, Hallberg L, Höglund D, Hulthén L. Meal pattern, food choice, nutrient intake and lifestyle factors in The Göteborg Adolescence Study. Eur. J. Clin. Nutr. 2003;57:1569–78.
Ahadi Z, Qorbani M, Kelishadi R, Ardalan G, Motlagh ME, Asayesh H, et al. Association between breakfast intake with anthropometric measurements, blood pressure and food consumption behaviors among Iranian children and adolescents: The CASPIAN-IV study. Public Health. 2015;129:740–7.
DOI: 10.1016/j.puhe.2015.03.019
Silva KS, Nahas M V, Borgatto AF, Oliveira ES, Del Duca GF, Lopes AS. Factors associated with active commuting to school and to work among Brazilian adolescents. J. Phys. Act. Health [Internet]. 2011;8:926–
Available from: http://www.ncbi.nlm.nih.gov/pubmed/21885883
Lipsky LM, Haynie DL, Liu D, Chaurasia A, Gee B, Li K, et al. Trajectories of eating behaviors in a nationally representative cohort of U.S. adolescents during the transition to young adulthood. Int. J. Behav. Nutr. Phys. Act. [Internet]. 2015;12:138. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4632654&tool=pmcentrez&rendertype=abstract
Gigante DP, Reichert FF, Hallal PC, Souza R V, Neutzling MB, Vieira Mde F, et al. Dietary assessment in the 1993 Pelotas (Brazil) birth cohort study: comparing energy intake with energy expenditure. Cad Saude Publica. 2010;26:2080–9.
DOI: 10.1590/S0102-311X2010001100009

Artículos más populares

Revisión: Ayuno intermitente: efectos en diversos escenarios clínicos

Introducción: los esquemas de ayuno intermitente (...

Publicado: 2023-05-24

Trabajo Original: Body mass index and risk of inflammatory breast disease: a Mendelian randomization study

Introduction: in previous studies, obesity was ide...

Publicado: 2023-04-22

Revisión: Relación entre la dieta, aspectos nutricionales y la calidad del sueño en población pediátrica

.La relación entre la dieta y el sueño ha sido esc...

Publicado: 2023-06-08

Una cookie o galleta informática es un pequeño archivo de información que se guarda en su navegador cada vez que visita nuestra página web. La utilidad de las cookies es guardar el historial de su actividad en nuestra página web, de manera que, cuando la visite nuevamente, ésta pueda identificarle y configurar el contenido de la misma en base a sus hábitos de navegación, identidad y preferencias. Las cookies pueden ser aceptadas, rechazadas, bloqueadas y borradas, según desee. Ello podrá hacerlo mediante las opciones disponibles en la presente ventana o a través de la configuración de su navegador, según el caso. En caso de que rechace las cookies no podremos asegurarle el correcto funcionamiento de las distintas funcionalidades de nuestra página web. Más información en el apartado “POLÍTICA DE COOKIES” de nuestra página web.