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besity Research & Clinical Practice (2013) 7, e407—e413

RIGINAL ARTICLE

redictors of food and physical activity patternsmong schoolchildren in the region of Sousse,unisia

ihene Maaloul Maatouga,∗, Imed Harrabia, Cyrille Delpierreb,afika Gahaa, Hassen Ghannema

Department of Epidemiology, University Hospital Farhat Hached, Sousse 4000, TunisiaDepartment of Epidemiology and Public Health, University of Medicine, Toulouse, France

eceived 27 September 2011; accepted 29 May 2012

KEYWORDSIntervention study;Primary prevention;Motor activity;Diet

SummaryAim: To facilitate the improvement of future interventions, it’s important to knowthe determinants of healthy behaviors. Our aim was to determine the predictorsof healthy habits in a school based intervention study to promote healthy diet andphysical activity among schoolchildren in the region of Sousse, Tunisia.Methods: It was a quasi-experimental intervention study with two groups: controland intervention group with pre—post evaluation of nutrition and physical activityintention and behavior in each group. The target population was composed withstudents aged 12—16 years schooled in colleges of Sousse in Tunisia. To evaluatethe intervention, a sampling was used to include 2200 students who participated tothe questionnaire. All the students of intervention group received a standardizedprogram with information about healthy nutrition and physical activity. An Arabicpre-tested and auto-administered questionnaire was used to assess nutrition andphysical activity intention and behavior before and after the intervention.Results: The intervention group’s posttest knowledge and behavioral intention weresignificantly higher than the control group’s posttest. No significant differencesoccurred in posttest attitudes between the control and intervention groups. A mul-tivariate logistic regression models were used to identify the predictors of students’‘‘healthy behavior’’.Conclusion: This school based intervention improved eating and physical activity

intentions and behaviors among schoolchildren. ‘‘Healthy behaviors’’ were deter-mined by age, father’s profession and home characteristics. This finding could direct future interventions to disa© 2012 Asian Oceanian AssLtd. All rights reserved.

∗ Corresponding author. Tel.: +216 73219496.E-mail address: jihenmaatoug3107@gmail.com (J.M. Maatoug).

871-403X/$ — see front matter © 2012 Asian Oceanian Association for the Study of Ob

ttp://dx.doi.org/10.1016/j.orcp.2012.05.006

dvantaged categories.ociation for the Study of Obesity. Published by Elsevier

esity. Published by Elsevier Ltd. All rights reserved.

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Introduction

Overweight and obesity are major risk factors forcardiovascular disease and all-cause mortality [1].

The growth in childhood obesity is a global pub-lic health crisis, meriting a specially convenedExpert Consultation at the WHO in June 2005 [2].The prevalence of overweight and obese childrenthroughout Europe has risen from <10% in the 1980sto >20% on current estimates, with some countriesreporting prevalence rates >30% [3]. Tunisia is alsofacing the same phenomenon. Current prevalenceof overweight was 16.1% among girls and 11.6%among boys in the region of Sousse [4]. In Tunis,the overweight rate was 20.7% [5].

Furthermore, several studies demonstrated thestability of this risk factor [6]. In Tunisia, a prospec-tive study among schoolchildren demonstrated thestability of overweight at 48.9% [7].

The increase in childhood overweight and obesitycan be attributed to behavioral and social ecolog-ical factors causing long term imbalance betweenenergy intake and energy expenditure [8]. The mid-dle school years may be a critical period for thedevelopment of healthy lifestyle behaviors. Dur-ing this time frame, there are declines in healthyfood consumption [9] and physical activity [10].Evidence that behavioral decisions impact healthbehaviors and health outcomes later in life [11].

Reduced intake of dietary fat, increased intakeof fruits and vegetables, and increased physicalactivity are behaviors that have been targetedfor population-based interventions among bothchildren and adults to reduce disease risk [12].Interventions to improve health-related behaviorsshould be tailored to the most important deter-minants or mediators of these behaviors [13].Currently, interventions to improve healthy dietand physical activity among adolescents have gen-erally been only moderately successful [14]. Tofacilitate improvement of future interventions, it’simportant to know determinants of healthy behav-iors.

Our aim was to determine the predictors ofhealthy habits in a school based intervention studyto promote healthy diet and physical activity amongschoolchildren in the region of Sousse, Tunisia.

Methods

Design

This study adopted a pre—post quasi-experimentaldesign with two groups, intervention and control.

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oth groups had an initial evaluation. Only stu-ents from the intervention group received specialourses and actions that promote healthy nutritionnd physical activity. Then, a second evaluationfter 1 school year took place in both groups inrder to compare the eventual effects of the inter-ention on knowledge, intentions, and behaviors.

opulation

he study concerned pupils of elementary publicchools in Sousse, Tunisia aged 12—16. Two districtsrom the city of Sousse (Sousse Jawhara, Sousseiadh) served respectively for the interventionnd control groups. The intervention was imple-ented in two public schools: Ezzahra and Khzemauest and concerned the totality of the pupils

total number = 1965). Two control public schoolsere selected: Ezzouhour and Essalem (total num-er = 1737). The selection of schools was basedn age, socioeconomic and demographic charac-eristics. A stratified and proportional samplingas performed in each secondary school to deter-ine the minimal required number of studentsho are going to answer the pre post evalua-

ions. It was based on these parameters: ˛ = 5%, = 20%, and an expected increase of 5% in dailyonsumption of breakfast, fruits and vegetables ofhe schoolchildren after an intervention promotingealthy nutrition and physical activity. The calcu-ated minimal sample size was 958 students in eachroup. We consciously majored this number con-idering the possible dropped out and the unequalepartition of students among classes.

Two thousand three hundred and thirty-eight stu-ents, however, participated to the first evaluation,ntervention = 1247 (39 classes) and control = 109137 classes).

At the second evaluation at the end of the schoolear, 138 students were dropped out (interven-ion = 58, control = 80). So, at final, 2200 studentsarticipated to the pre and post evaluations.

ariables and their measurement

e used a pre-tested self-administered ques-ionnaire. Data collected by the questionnaireoncerned socio-demographic variables (age, sex,arents’ education, etc.), students’ knowledge,ehaviors and intentions about dietary habits andhysical activity.

escription of the intervention

ntervention consisted in interactive lessons andctivities that were delivered by pre-formed

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redictors of food and physical activity patterns am

eachers with the collaboration of the doctor mem-ers of the project. Each class in the interventionroup received a visually supported course dur-ng biological science physical activity sessions thatrovided the main information concerning diet andhysical activity. This included:

Explaining the principles of dietary pyramid. Discussing the ideal composition of principalmeals.

Explaining the importance of breakfast and itsplace in dietary balance.

Explaining through examples the differencebetween healthy and unhealthy food.

Presenting the effects of each kind of diet onhealth, with a focus on obesity complications andcardiovascular risk factors.

Suggesting healthy habits and balanced diet. Explaining the preventive role of exercise. Discussing the benefits of regular physical activityon the physical, psychological and social plan.

Presenting the different ways to engage in physi-cal activity.

After this course, students were asked torepare productions of their choice (drawing,osters, pieces of theatre, etc.) one concerningealthy/unhealthy food and one concerning phys-cal activity. They could also take part of differentctivities such as local radio or health club wheredditional discussions and presentations took place.ural posters that promote healthy nutrition wereisplayed on the school walls. Finally, during theeremony of the end of the school year, studentsresented their productions with the presence ofarents, teachers, team of the project and otherembers of the community; and the best ones were

ewarded.

tatistical analysis

tatistical analysis was performed using the Sta-istical Package for Social Sciences (SPSS). Datare presented as frequencies, means and standardeviations. We used respectively Pearson and Macemar Chi square to compare percentages betweennd within groups. Statistical significance was set at

< 0.05.The multivariate logistic regression models

ere used to identify the predictors of students’‘healthy behavior’’. The determining factors oftudents ‘‘healthy behavior’’ in the interventionroup. The dependent variable ‘‘healthy behav-

or’’ was coded in two categories (yes — no). Itas coded, Yes, when the intervention group stu-ents declare after the intervention consume dailyreakfast, fruits and vegetables, practice 5 days per

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schoolchildren e409

eek physical activity for at least 30 min a day and sedentary activity for less than 2 h per day at thend of the study.

thical considerations

he study was conducted with the approval of thearhat Hached Hospital ethics committee. Parentsave their consent for their children’s participationnd the questionnaires were anonymous and self-dministered.

esults

ocio-demographic characteristics

he population was composed of 2200 students,ith 1189 in the intervention group and 1011 in theontrol group. Boys presented respectively 46.8%nd 46.5% of the intervention and control group.tudents were aged from 12 to 16 with a meanf 13.3 ± 1.1 years in the intervention group, and3.5 ± 1.2 years in the control group.

Father’s education level in the interventionroup was primary school in 22.7%, secondarychool in 39% and higher education in 26.9%.ercentages of mother’s education level wereespectively 30.3%, 35.3% and 19.2%. Concerningarent’s profession, 34.5% of fathers and 21% ofothers were official or senior.In the control group, father’s education level was

rimary school in 34.4%, secondary school in 40.6%nd higher education in 20.4%. Percentages con-erning mother’s education level were respectively4.3%, 27.6% and 10.9%. For parents’ profession,8.4% of fathers and 9.8% of mothers were officialr senior.

In the intervention group, 25.6% of students liven a home with three bedrooms or more versus9.7% in the control group.

esults of the intervention

oncerning ‘‘healthy behaviors’’, in the interven-ion group, children improved significantly theiraily breakfast and vegetable intake. It passedespectively from 58.2% to 67.6% and 45.4% to 56.8%p < 10—3). The proportion of children who prac-ice 5 days per week physical activity for at least

0 min a day increased significantly from 23% to 44%p < 10−3) (Table 1).

In the control group, only the proportion of chil-ren who practice 5 days per week physical activity

e410 J.M. Maatoug et al.

Table 1 Pre—post comparison of schoolchildren ‘‘good behaviors’’ in the intervention and control group. In theintervention group, 25.6% of students live in a house with more than three bedrooms versus 19.7% in the controlgroup (p = 0.001).

Intervention group, n (%) Control group, n (%)

Before Post p Before Post p

Daily breakfastintake

692 (58.2) 803 (67.6) <10−3 541 (53.5) 538 (53.2) 0.41

Daily fruits intake 716 (60.5) 703 (59.6) 0.54 691 (68.6) 544 (54.2) <10−3

Daily vegetablesintake

538 (45.4) 673 (56.8) <10−3 561 (55.5) 553 (54.7) 0.67

Less than 2 h ofsedentaryactivities perday

688 (58.5) 710 (60.4) 0.30 488 (48.6) 512 (50.9) 0.19

Practice 5days/weekphysicalactivity>30 min

269 (23.0) 521 (44.0) <10−3 350 (35.0) 440 (43.9) <10−3

Table 2 Pre—post comparison of schoolchildren eating and physical activity behaviurs in the intervention andcontrol group.

Intervention group, n (%) Control group, n (%)

Before Post p Before Post p

Snaking at theevening

703 (59.3) 615 (52.1) <10−3 624 (62.2) 591 (59.1) 0.08

Daily dairyproducts intake

727 (61.2) 879 (74.4) <10−3 519 (51.6) 573 (57.0) 0.001

Daily soft drinkintake

268 (22.6) 222 (21.9) 0.003 221 (21.9) 206 (20.5) 0.31

Fast food intakemore thantwice a week

453 (42.9) 329 (40.3) <10−3 370 (40.3) 376 (41.3) 0.76

Intend to takebreakfast everyday

983 (83.6) 1076 (91.9) <10−3 822 (81.6) 850 (84.5) 0.02

Intend to takevegetablesevery day

630 (53.2) 861 (73.0) <10−3 626 (62.0) 677 (67.1) 0.001

Intend to takefruits every day

1000 (85.0) 1092 (93.8) <10−3 897 (89.2) 906 (90.5) 0.31

Practice physicalactivity atsportassociation

121 (10.4) 132 (11.3) 0.26 218 (21.7) 222 (22.2) 0.76

Intend topracticephysicalactivity at least30 min/day 5days/week

1032 (87.1) 1143 (96.2) <10−3 912 (91.0) 935 (92.7) 0.16

Predictors of food and physical activity patterns among schoolchildren e411

Table 3 Univariate analysis: factors predicting students’ ‘‘good behaviors’’ in the intervention group at the endof the study.

Odds ratio IC 95% p

Age <13 years 1.62 1.12—2.34 0.01Gender (boys) 2.37 1.65—3.40 <10−3

Father had higher education 2.67 1.87—3.82 <10−3

Mother had higher education 2.16 1.47—3.18 <10−3

Father’s profession: official orsenior

2.59 1.82—3.68 <10−3

Mother’s profession: official orsenior

1.98 1.35—2.90 <10−3

Live in a home with threebedrooms or more

2.36 1.65—3.39 <10−3

Snaking at the evening 1.16 0.81—1.66 0.40Daily dairy products intake 2.72 1.78—4.14 <10−3

Daily vegetables intake 2.28 1.59—3.26 <10−3

Daily fruits intake 3.06 1.99—4.71 <10−3

Daily soft drink intake 1.15 0.75—1.76 0.52Fast food intake more than twice a

week1.32 0.91—1.91 0.13

Daily breakfast intake 3.11 2.04—4.74 <10−3

Practice physical activity at sportassociation

1.44 0.86—2.40 0.16

Practice 5 days/week physicalactivity >30 min

4.59 3.20—6.59 <10−3

Less than 2 h of sedentary activitiesper day

1.62 1.12—2.36 0.009

Intend to take breakfast every day 3.74 1.80—7.77 <10−3

Intend to take vegetables every day 2.10 1.45—3.04 <10−3

Intend to take fruits every day 1.36 0.80—2.32 0.25Intend to practice physical activity 2.77 1.33—5.77 0.006

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at least 30 min/day 5 days/week

or at least 30 min a day increased significantly from5% to 43.9% (p < 10−3) (Table 1).

Globally, children in the intervention groupmproved their intention and behaviors. Childrenho intend to take daily fruits and vegetablesassed respectively from 85% to 93.9% and 53.2%o 73%. Intention to practice physical activity alsomproved to 96.2%. Children decreased signifi-antly snaking at the evening from 59.3% to 52.1%p < 10−3) (Table 2).

In control group, intention improved only foraily breakfast and vegetable intake which passedespectively from 81.6% to 84.5% and 62% to 67.1%.oncerning behaviors, they improved only dailyairy products intake from 51.6% to 57% (Table 2).

‘Healthy behavior’’ determinants

nivariate analysis

redictors of students ‘‘good behavior’’ in thentervention group at the end of the study were thententions to have these behaviors, age less than3 years old, boys, parents higher education level,

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arents profession as official or senior. Studentsho do not take daily soft drink and consume less

‘fast foods’’ had the best behaviors (Table 3).

ultivariate analysisredictors of ‘‘healthy behaviors’’ were: age lesshan 13 years old, father’s profession as official orenior, living in a home with three bedrooms orore and having these behaviors before the inter-

ention (Table 4).

iscussion

his school based intervention improved eating andhysical activity intentions and behaviors amongchoolchildren. Further research needs to be con-ucted to determine the long term impact. In

ahlman et al. [15] study, students in the interven-ion group demonstrated significant improvementre to post and were significantly higher thanhe controls at post in their consumption of

e412 J.M. Maatoug et al.

Table 4 Multivariate analysis: factors predicting students’ ‘‘good behaviors’’ in the intervention group at the endof the study.

Odds ratio IC 95% p

Age <13 years 1.60 1.06—2.40 0.02Father’s profession: official or senior 2.16 1.46—3.18 <10−3

Live in a home with three bedrooms or more 1.80 1.20—2.70 0.004Daily vegetables intake 1.69 1.13—2.51 0.009Daily fruits intake 1.98 1.24—3.16 0.004Daily breakfast intake 1.96 1.24—3.10 0.003

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Practice 5 days/week physical activity >30 minLess than 2 h of sedentary activities per day

fruits and vegetables. Literature reviews of schoolbased interventions to promote healthy lifestyleamong schoolchildren have provided useful infor-mation for developing and implementing successfulinterventions [16]. Interventions should be mul-ticomponent, including school based educationaimed at children’s behavioral determinants,parental involvement and changes in the schoolenvironment. In our study, we tried to involveparents by the productions that children had to pre-pare. They also had been involved in healthy clubsand participation in the ceremony in schools. Butwe could not change the school environment in thisstudy.

We also demonstrated the influence of socio-demographic status on behaviors. In fact, ‘‘healthybehaviors’’ were determined by age, father’s pro-fession and home characteristics. This finding coulddirect future interventions to disadvantaged cate-gories.

Several studies tried to identify predictors ofhealthy habits like eating fruits and vegetables [17],taking breakfast [18] or doing more physical activity[19].

A review of determinants of fruit and veg-etable consumption among children and adoles-cents reveals that the determinants supportedby the greatest amount of evidence are gender,age, socioeconomic position, preferences, parentalintake, and home availability/accessibility. Girlstend to have a higher or more frequent intake offruit and vegetables than boys, and a correspondingpattern is seen for the younger age groups com-pared to the older age groups [17].

To investigate associations of daily breakfastconsumption with demographic and lifestyle fac-tors in 41 countries, a survey was been conductedincluding nationally representative samples of11—15 year olds. Daily breakfast consumption var-

ied from 33% (Greek girls) to 75% (Portuguese boys).In most countries, lower daily breakfast consump-tion was noticed in girls, older adolescents, thosewith lower family affluence and those living in

lvia

4.25 2.87—6.29 <10−3

1.75 1.16—2.65 0.007

ingle-parent families. It was positively associatedith healthy lifestyle behaviors and negatively withnhealthy lifestyle behaviors. Breakfast skippingeserves attention in preventive programs. It isommon among adolescents, especially girls, olderdolescents and those from disadvantaged families.he results indicate that daily breakfast consump-ion can serve as an indicator to identify childrent risk for unhealthy lifestyle behaviors [18].

Studies examining the relationship between psy-hosocial factors and activity levels of middlechool age girls have suggested that placing a higheralue on health, appearance, and achievement self-fficacy, self-management, and perceived barrierso activity are associated with activity levels in girls20]. Other research with youth suggests that out-ome expectancy value and enjoyment are relatedo levels of physical activity [21]. Social influenceslso appear to be associated with levels of activ-ty in youth including socio-demographic factors,arent activity level, support for activity, and par-nting style [22,23]. Others examined policy andnvironmental factors related to activity and foundhat school policies supporting physical activity andiving in a low crime neighborhood are related toevels of activity [23]. Research by Evenson et al.24] found that the number of physical activityacilities near a girl’s home was an important pre-ictor of activity levels.

The results of a survey conducted in Finland dis-inct status-specific differences in the incidencef smoking, physical inactivity, and obesity. Theseifferences can be described as a gradient: theower the social status, the higher the chance ofeing a smoker, physically inactive, or obese. Thisradient is steepest in middle age. Recommenda-ions as to behavior modification should take intoccount each patient’s individual circumstancesith regard to family, work, and other areas of

ife. Consideration of the patient’s attitude, moti-ation, and resources for change, all of which arentimately connected with their life circumstancesnd social status, is also crucial to the success of any

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edical recommendations such as health education25].

onclusion

chool based intervention to promote healthy dietnd physical activity is benefit and important athe middle age to prevent obesity and cardio-ascular disease risk factors. This interventionhould take into account each patient’s individualircumstances with regard to family, work, andther areas of life.

eferences

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[2] World Health Organisation.WHO expert meeting on child-hood obesity. 2005. Available at: http://www.who.int/nmh/media/obesity expert meeting/en/index.html.

[3] IOTF. Overweight and obesity in the European Union.Briefing paper for the European Commission platformon diet, physical activity and health; 2005. Available at:http://europa.eu.int/comm/health/ph determinants/lifestyle/nutrition/documents/iotf en.pdf.

[4] Gaha R, Ghannem H, Harrabi I, Ben Abdelaziz A, LazregF, Hadj Fredj A. Etude de la surcharge pondérale et del’obésité dans une population scolarisée en milieu urbainà Sousse en Tunisie. Arch Pédiatrie 2002;9:566—71.

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24] Evenson K, Birnbaum AS, Bedimo-Rung A, Sallis JF, VoorheesCC, Ring K, et al. Girls perceptions of physical environmen-tal factors and transportation: reliability and associationwith physical activity and active transport to school. Int JBehav Nutr Phys Activity 2006;2:28.

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