Preventing obesity among Brazilian adolescent girls: Six-month outcomes of the Healthy Habits, Healthy Girls–Brazil school-based randomized controlled trial

Preventive Medicine 86 (2016) 77–83

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Preventing obesity among Brazilian adolescent girls: Six-month outcomes of the Healthy Habits, Healthy Girls–Brazil school-based randomized controlled trial Ana Carolina Barco Leme a,⁎, David R. Lubans b, Paulo Henrique Guerra c,d, Deborah Dewar b, Erika Christiane Toassa a, Sonia Tucunduva Philippi a a

Departamento de Nutrição, Faculdade de Saúde Pública, Universidade de São Paulo, São Paulo, CEP 01246-904, Brazil Priority Research Centre in Physical Activity and Nutrition (PRC-PAN), University of Newcastle, Campus Callaghan, Callaghan, NSW 2308, Australia c Escola de Artes, Ciências e Humanidades, Universidade de São Paulo, São Paulo CEP 03828-000, Brazil d Grupo de Estudos e Pesquisas Epidemiológicas em Atividade Física (GEPAF-USP), Escola de Artes, Ciências e Humanidades, Universidade de São Paulo, São Paulo CEP 03828-000, Brazil b

a r t i c l e

i n f o

Available online 3 February 2016 Keywords: School Nutritional status Motor activity Randomized controlled trial Adolescent

a b s t r a c t Background. School-based trials to prevent and reduce prevalence of pediatric obesity in low-income countries are necessary. In Brazil, addressing adolescent obesity is a public health priority. Objective. To evaluate the impact of a group randomized controlled trial involving a 6-month multicomponent school-based obesity prevention program targeting adolescent girls. Methods. The Healthy Habits, Healthy Girls–Brazil program recruited participants (n = 253; 16.05 ± 0.05 years) from ten eligible public technical schools in São Paulo, Brazil. The program was adapted from an Australian intervention study, which is based on the Social Cognitive Theory. The primary outcome measure was body mass index (BMI), and secondary outcomes included BMI z score, waist circumference, and various sedentary and dietary health-related behaviours. Results. Although changes in BMI were not statistically significant, differences favored the intervention group (adjusted mean difference, −0.26 kg/m2,se SE = 0.018, p = 0.076). Statistically significant intervention effects were found for waist circumference (− 2.28 cm; p =, p = 0.01), computer screen time on the weekends (0.63 h/day, p; p = 0.02), total sedentary activities on the weekends (−0.92 h/day, p b 0.01), and vegetable intake (1.16 servings/day, p = 0.01). Conclusion. These findings provide some evidence for the benefit of a school-based intervention to prevent unhealthy weight gain in adolescent girls living in low-income communities. © 2016 Elsevier Inc. All rights reserved.

Introduction Recent decades have shown a substantial increase in the global prevalence of pediatric overweight and obesity (Ng et al., 2014). Brazilian youth are not impervious to this global public health crisis, with recent data showing high a prevalence of overweight (23.0%) and obesity (7.3%) among adolescents (Araújo et al., 2010). Specifically, the highest rates of obesity and overweight have been observed in the most developed region (Southeast) of Brazil (Araújo et al., 2010). This is a serious concern as unhealthy weight gain in youth can lead to a variety of adverse health outcomes (Tsiros et al., 2011) and the likelihood of pediatric obesity tracking into adulthood is high (Singh et al., 2008). There is clearly an urgent need for effective interventions that target weightrelated health behaviors in population “at risk” of obesity (Olsen et al., 2012; WHO, 2012). ⁎ Corresponding author. E-mail address: [email protected] (A.C.B. Leme).

http://dx.doi.org/10.1016/j.ypmed.2016.01.020 0091-7435/© 2016 Elsevier Inc. All rights reserved.

Schools are well placed to deliver health promotion interventions and address health inequalities in populations “at risk” of obesity (Hills et al., 2015).For instance, schools provide access to the majority of youth and already have the necessary provisions (i.e., facilities, resources, and trained staff) in place for the safe and supportive delivery of health promotion interventions (CDC, 2011). While numerous school-based obesity prevention interventions among youth have been evaluated, recent reviews of these studies have indicated several limitations and challenges that need to be addressed to advance the field (Waters et al., 2011). The majority of youth studies have been conducted in high-income countries, predominantly in the United States. There is a lack of available evidence for effective strategies in developing countries, and quality randomized controlled studies using Brazilian adolescents are urgently needed (Guerra et al., 2014). Many studies have also revealed modest effects for interventions targeting adolescents, with greater success shown for programs designed for children (Brown and Summerbell, 2009). It has been suggested these modest effects of

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previous interventions may be explained by a lack of studies targeting the most vulnerable youth, and hence the need for programs and strategies to differentiate on the grounds of sex, cultural background, and socioeconomic position (Stamatakis et al., 2010). Research conducted in Brazil has demonstrated that girls consume more sugar and sweet food items (Levy et al., 2010), are less physically active (Hallal et al., 2010), and spend more time in small-screen recreation (Camelo et al., 2012), in comparison to boys. These findings highlight the importance of establishing effective strategies that target the health behaviors of this priority group to prevent unhealthy weight gain (Barbosa Filho et al., 2014). Therefore, the primary purpose of this study was to evaluate the effects of a culturally tailored school-based obesity prevention intervention in a sample of adolescent girls from low-income communities in the city of São Paulo, Brazil. Methods This study was registered in the ClinicalTrials.gov (NCT02228447) and reported according to the CONSORT checklist (Moher et al., 2010). Study design The design, methods, and baseline characteristics are described in details elsewhere (Leme and Philippi, 2015). In summary, The “Healthy Habits, Healthy Girls–Brazil (H3G-Brazil)” was a 6–month obesity prevention intervention evaluated using a cluster randomized controlled trial (March to September 2014). The intervention strategies were culturally adapted from “The Nutrition Enjoyable Activity for Teen Girls (NEAT Girls)” study (Dewar et al., 2013; Lubans et al., 2010, 2012). Approval was obtained from the Ethic Research Committee of the School of Public Health, University of São Paulo. Parents/caregivers, teachers, and school principals provided written informed consent. Adolescents also provided assent. Sample size and randomization The sample size was calculated to determine the necessary detectable postintervention changes in the primary outcome, body mass index (BMI) (Lubans et al., 2010; Smith et al., 2014a). The power calculation was based on power of 80% and significance level of 5% (p b 0.05) and proportion of non-exposed and exposed to the outcome. Considering potential dropout of 20%, 266 participants were necessary to detect a between-group difference in BMI of 0.4 kg/m2. Following baseline assessments, the 10 schools were match paired (i.e., 5 pairs of schools) based on their geographical location, size, and demographics. Schools within each pair were then randomized to either H3G-Brazil or control group by an individual not involved in the study. Participants and selection Technical schools in Brazil are government secondary schools (student ages range from 14 to 18 years). At these schools, part of the adolescents' school day is allocated to regular high school and the other to technical education in several different areas (e.g., mechanical, chemistry, health, and commerce). Government schools that offer nutrition and dietetic technical courses (13 of 43 schools) were selected for the current study because they provide (i) opportunities for partnership with accredited dietitian teachers and allow students to work as research assistants and (ii) infrastructure to deliver the nutrition activities (i.e., food science laboratory). Girls reported their parents/caregivers school level of education and the neighborhood they live. In Brazil, parents' education level is considered an income proxy. In agreement with the social economic level of the city of São Paulo, the schools and neighborhoods are of high vulnerability (e.g., government housing and slums demonstrating areas of low socio economic position) (SãoPaulo, 2014). Once schools agreed to participate in the study, research assistants visited the study schools and provided a presentation to the students describing the proposed intervention and assessment procedures. Study participants were then asked to complete a questionnaire regarding PA and eating behaviors to identify girls “at risk” for obesity (Plotnikoff et al., 2009). Those who were considered “at risk” of obesity based on their PA and dietary behaviors were then eligible to participate in the intervention.

Intervention The H3G-Brazil program was a 6-month multicomponent school-based intervention guided by the social cognitive theory (SCT) (Bandura, 1986). The intervention was based on ten nutrition and physical activity (PA) messages to support healthy eating and regular PA (Lubans et al., 2010). Additional program components were designed to reinforce healthy dietary and PA behaviors and included enhanced physical education (PE) sessions, school-break PA sessions, nutrition and PA handbooks, interactive seminars, nutrition workshops, weekly nutrition and PA key messages, parental newsletters, weekly health messages using WhatsApp®, and diet and PA diaries for self-monitoring. H3G-Brazil was focused on promoting low-cost healthy dietary choices and lifelong and lifestyle physical activities. Lifelong physical activities are those that may be easily carried over into adulthood and generally require only one or two people to participate (e.g., yoga, dance, body weight resistance training) (Hulteen et al., 2015). Lifestyle activities are those performed as part of everyday life, such as walking for transport (Leme and Philippi, 2015; Lubans et al., 2010). Detailed description of intervention components and hypothesized mediators are reported in Supplementary Table 1. Since the H3G-Brazil intervention was an adaptation of the Australian NEAT Girls program (Lubans et al., 2012), modifications were necessary to make it culturally appropriate to Brazilian girls: the enhanced PE classes focused on the girls' preferred activities (e.g., dance classes, walking around the school campus, and resistance training workouts). To promote enjoyment during sessions, the girls were invited to bring their preferred music (e.g., on cell phones). Further, the intervention's nutrition component was guided by the Brazilian Food Guide Pyramid and Smart Food Choices (Leme and Philippi, 2014; Philippi, 2014; Philippi and Leme, 2015), which promotes healthy, regional, and costeffective food preparations including for example, tropical fruits (e.g., mangos and coconut), whole-wheat sandwiches and pasta, and cultural spices/herbs typically used in Brazilian cuisine (e.g., basil, bay leaves, black pepper, garlic and onion, nutmeg and mint). Research assistants delivered the ten key health messages during school breaks. PE teachers conducted the enhanced PE classes and supervised the PA sessions during school breaks. Accredited dietitians delivered the nutrition workshops and the interactive seminars, and they were responsible for sending the WhatsApp® messages and newsletters. All teachers, dieticians, and research assistants previously took part in H3G-Brazil training workshops to ensure sufficient understanding and adequate delivery of program components. To prevent resentful demoralization, the control school received a condensed version of the program after follow-up assessments. This included professional learning workshops for control school teachers and the H3G-Brazil intervention materials (Leme and Philippi, 2015). Assessments and measurements All assessments were conducted by trained research assistants blinded to groups' allocation at both time points. Physical assessments were conducted in a sensitive manner (i.e., weight measured out of the view of other students), and questionnaires were completed after the physical assessments in exam-like conditions. Socio-demographic information was collected at baseline only. Body mass index Weight was measured by the nearest 0.1 kg using a portable digital scale. A portable stadiometer was used to obtain height measurements to the nearest 0.1 cm. Body mass index (BMI) was calculated using the standard formula (kg/m2). Body mass index z score BMI z score was also calculated using the LMS method proposed by Cole (Cole, 1990). This method is used to build distribution curves of anthropometric outcomes such as weight and height (Hulteen et al., 2015). BMI percentile was used to classify weight status (i.e., underweight, normal weight, overweight, and obese) according to World Health Organization data (de Onis, 2007). Waist circumference Waist circumference was measured by the nearest 0.1 cm against the skin using extendible steel tape in line with the umbilicus (Pereira et al., 2015). Leisure-time physical activity PA was assessed using the an adapted and validated version of the Godin– Shephard Leisure-Time Physical Activity Questionnaire for use in the Brazilian

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contect (Sao-Joao et al., 2013). This measure examined PA frequency and intensity of respondents: specifically reporting the number of times 30 min blocks of PA were practiced in the last seven days. According to responses, participants were then categorized into one of three levels of PA: (i) inactive (≤ 30 min/week), (ii) insufficiently active (90–300 min/week), and (iii) active (N 300 min/week).

sweets; (viii) oils and fats (Philippi, 2014; Philippi and Leme, 2015). Where total daily energy intake for an individual b500 kcal and N 5000 kcal, cases were removed from the database (57 from baseline and 29 post-intervention) (Collins et al., 2014).

Sedentary behaviors Self-reported time spent watching TV and using computers was assessed using a modified measure previously used with adolescent girls to examine sedentary behavior (Neumark-Sztainer et al., 2010). For each type of screen-time recreation, the girls were to report daily average hours during weekdays and on weekend days for the last 7 days with categorical response options ranging from zero hours/day to N5 h/day. The sum of screen-time activities was also calculated.

Several process measures were used to evaluate the program and included (i) attendance during the PE classes, PA sessions, nutrition workshops, and seminars; (ii) intervention fidelity (i.e., observational H3GBrazil checklist by the lead researcher); (iii) engagement with WhatsApp® text messages (i.e., number of girls who left the groups); iv) percentage of parents newsletters received and read; and (v) program satisfaction (rating scale, 1 = strongly disagree to 5 = strongly agree). Girls completed process evaluation questionnaires at the end of the study.

Dietary outcomes Dietary intake was measured using a validated food frequency questionnaire (FFQ) for adolescents (Martinez et al., 2013) where daily servings (e.g., for fruits and milk, cheese and yogurt groups) and total daily energy intake were examined. Items for food types and serving sizes were guided by recommendations of the Brazilian Food Pyramid for adolescents (Philippi and Leme, 2015), where foods and beverages were aggregated into eight food groups: (i) rice, bread, pasta, potato, and cassava; (ii) vegetables; (iii) fruits; (iv) milk, cheese, and yogurt; (v) meats and eggs; (vi) beans and nuts; (vii) sugars and

Statistical analyses

Process evaluation

All analyses were conducted in SPSS software 21.0 version (IBM SPSS Statistics, IBM Corporation, Armonk, NY; 2010) with significance levels set at p b 0.05. Differences between groups at baseline were examined using chi-squares and independent-samples t-tests. Data were checked for normality and log or square root transformed where appropriate. Intervention effects for anthropometric outcomes, dietary intake, and sedentary behaviors were examined using linear mixed models, which were adjusted for the clustered nature of

Fig. 1. Flow chart of the study participants. “Healthy Habits, Healthy Girls–Brazil”, São Paulo, 2014.

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the data using a random intercept (i.e., school). All analyses followed the intention-to-treat principle. The models were used to assess the impact of treatment (intervention vs. control), time (post-test minus baseline), and the groupby-time interaction, these three terms forming the base model. Sub-group analyses were conducted with participants who were classified as overweight or obese at baseline for the following outcomes: BMI, BMI z score, and waist circumference.

Results The flow of schools and participants through the study is provided in Fig. 1. From the 13 schools initially targeted, ten participated in the study. At baseline, the study sample included 253 girls (M = 16.1 years, standard error = 0.05); 62.8% described their ethnicity as Caucasian; and 26.6% were overweight or obese (Table 1). All of the 10 schools were retained in the study, but 63 girls (24.9%) did not participate in the post-intervention assessments; such that 107 (75.4%) and 83 (74.8%) girls were retained in intervention and control groups, respectively. Reasons are provided in Fig. 1. Participants in the H3GBrazil intervention group were older than those in the control group (16.3 vs. 15.7 years). In addition, H3G-Brazil girls were on average 4.5 kg heavier and 1 cm taller than the control group at baseline. Changes in primary and secondary outcomes are reported in Table 2. Changes in anthropometric outcomes were all in favor of the intervention group, but there were no statistically significant between-group differences in BMI (− 0.26 kg/m2, p = 0.08) and BMI z score, (−0.07, p = 0.14). However, a statistically significant group-by-time interaction was found for the waist circumference indicator (−2.28 cm, p = 0.01). No significant between-group differences for waist circumference, BMI, and BMI z score, for those classified as overweight/obese at baseline were observed (Supplement Table 2). However, proportional

Table 1 Characteristics of the study sample. “Healthy Habits, Healthy Girls–Brazil”, São Paulo, 2015.

Age, mean (SE), y Participants born in São Paulo city, n (%)

H3G-Brazil (n = 142)

Control (n = 111)

Total (n = 253)

16.32 (0.06)

15.70 (0.07)

16.05 (0.05)

125 (92.6)

92 (86.0)

23 (16.2) 1 (0.7) 79 (55.6) 37 (26.1) 2 (1.4)

6 (5.4) 1 (0.9) 80 (72.1) 24 (21.6) –

29 (11.5) 2 (0.8) 159 (62.8) 61 (24.1) 2 (0.8)

Parent school levela, n (%) Fundamental school High school Higher education

35 (24.7) 83 (58.5) 19 (13.4)

17 (15.3) 53 (47.7) 33 (29.7)

52 (20.5) 136 (53.7) 52 (20.5)

Weight statusc, n (%) Underweight Healthy weight Overweight Obesity

6 (4.2) 91 (64.1) 29 (20.4) 16 (11.3)

1 (0.9) 87 (78.4) 18 (16.2) 5 (4.5)

Process evaluation A total of 130 girls received the intervention (91.5%). Participants' mean (SD) attendance at the enhanced PE sessions was 88.0% (± 4.9%). On average, girls attended 97.7% (± 3.9%) of the nutrition workshops, 99.1% (± 1.2%) of the interactive seminars, and 59.4% (± 10.9%) of the PA sessions during school breaks. In total, 86.2% of the girls completed the home challenges. Six observations for each of the PA sessions and PE classes and weekly nutrition and PA key messages (2 per school term) were conducted at each school. Intervention fidelity was found to be 60% for PA sessions, 53% for PE classes, and 80% for weekly nutrition and PA key messages. All four of the parental newsletters were sent to the students' addresses (i.e., provided on their school enrolment registration) and 84.4% of the girls reported that their parents had received and read it. A total of 34 Whatsapp® group text messages were sent to 73.9% of the girls in the intervention group. Only 37 (25.9%) did not have a mobile phone. For those individuals, the messages were sent by e-mail. Overall, girls were satisfied with the program (mean = 4.43; SE = 0.08). The nutrition workshop was the intervention component enjoyed most by girls (89.7%). No injuries or adverse effects were reported during the activity sessions or assessments. Discussion

217 (89.7)

Ethnic background, n (%) Afro descendent Asian Caucasian Brown Native Indian

Weight (kg), mean (SE) 59.85 (1.03) 55.29 (1.11) Height (cm), mean (SE) 1.61 (0.005) 1.60 (0.005) Waist circumference (cm), 75.93 (0.88) 71.46 (1.01) mean (SE) 22.81 (0.34) 21.48 (0.36) BMI (kg/m2), mean (SE) 0.42 (0.09) 0.16 (0.11) BMI z score,b, mean (SE)

differences for weight status demonstrated that H3G-Brazil girls presented a decrease in overweight (20.4% vs. 19.0%) and obesity (11.3% vs. 9.9%) over time, while the proportion of control girls classified as overweight were found to increase with time (16.2% vs. 18.0%) (data not shown). Self-report data show showed girls in the intervention group reported a significantly greater reduction in computer use during weekend days (−0.63 h/day, p = 0.02) and in total sedentary activities on the weekends (− 0.92 h/day, p = 0.01]. There were significant group-bytime effects for vegetable intake (1.16 servings/day, p = 0.01) and fruit intake (0.26 servings/day, p = 0.01) also favored the H3G-Brazil group. There were improvements on nutrition, physical activity, and screen-time behaviors for the intervention vs. control group over the time (Table 2).

p-value 0.003 57.85 (0.76) 0.037 1.61 (0.003) 0.001

73.97 (0.67)

0.010 0.078

22.23 (0.25) 0.31 (0.07)

7 (2.8) 178 (70.4) 47 (18.6) 21 (8.3)

Note: BMI, body mass index. a Parent school level was used as proxy measure of income. 13 girls did not answer their parent school level. b BMI z score, based on LMS method. c Weight status were categorized based on the World Health Organization percentiles for BMI/age.

The aim of this study was to evaluate the impact a 6–month multicomponent school-based obesity prevention program targeting adolescent girls. Although the intervention effect for the primary outcome BMI was not statistically significant, a significant group-by-time interaction was observed for waist circumference. Moreover, adolescents in the intervention group reported significantly less sedentary activity and consumed more fruit and vegetables than those in the control group at post-test. Taken together, these findings highlight the potential efficacy of school-based intervention targeting Brazilian adolescent girls “at risk” of obesity. Similar to previous school-based obesity prevention programs in adolescent girls (Bayne-Smith et al., 2004; Lubans et al., 2012; Neumark-Sztainer et al., 2010; Young et al., 2006), HG3-Brazil was not successful in reducing BMI. However, the current intervention was not a weight loss intervention, but was designed to minimize unhealthy weight gain. In the current study, both groups decreased their BMI over the 6-month study period and the group-by-time effect was not statistically significant. Of note, the adjusted difference in waist circumference was −2.28, suggesting a small intervention effect among H3GBrazil girls. In addition, the H3G-Brazil study demonstrated a favorable change in the weight status of intervention girls compared to control girls, providing additional support for the efficacy of the intervention. The majority of study participants was classified as having a healthy weight at baseline and remained so for the study period. For this reason, researchers from the HEALTHY diabetes prevention study (Marcus et al., 2013) have argued that primary prevention programs should continue

Table 2 Baseline, post-intervention, and changes in outcomes. “Healthy Habits, Healthy Girls – Brazil”, São Paulo, 2015. Outcomes

ICC Values

H3G-Brazil

Control

Median (95% CI)

0.016 0.006 0.062 0.13 0.046 0.092 0.083 0.101 0.048 0.027 0.000 0.011 0.000 0.044 0.030 0.022 0.017 0.027

Median (95% CI)

Baseline

Post-intervention

(n = 142)

(n = 111)

22.81 (22.15–23.47) 0.42 (0.24–0.61) 75.93 (73.78–78.07) 1.35 (0.92–1.78) 2.09 (1.82–2.35) 2.36 (1.92–2.81) 3.03 (2.61–3.45) 3.69 (2.91–4.47) 5.12 (4.56–5.67) 9.74 (8.91–10.59) 4.87 (4.19–5.55) 0.71 (0.56–0.85) 2.06 (1.72–2.39) 2.19 (1.78–2.59) 1.82 (1.49–2.14) 4.86 (4.41–5.30) 5.50 (4.79–6.22) 9.74 (8.91–10.59)

21.48 (20.73–22.23) 0.42 (0.23–0.60) 75.80 (73.66–77.95) 1.13 (0.69–1.57) 2.47 (2.18–2.75) 1.60 (1.16–2.04) 2.12 (1.69–2.54) 4.24 (3.45–5.03) 3.82 (3.26–4.37) 8.58 (7.74–9.42) 5.27 (4.59–5.95) 1.12 (0.98–1.27) 1.65 (1.32–1.99) 1.84 (1.43–2.25) 1.76 (1.43–2.09) 3.87 (3.42–4.32) 3.45 (2.74–4.16) 8.58 (7.74–9.42)

p-value

0.061 0.784 0.114 0.182 0.012 0.000 0.000 0.000 0.000 0.004 0.041 0.000 0.187 0.193 0.825 0.007 0.000 0.000

Baseline

Post-intervention

(n = 107)

(n = 83)

22.98 (22.32–23.65) 0.16 (−0.04–0.37) 71.46 (69.19–73.73) 1.76 (1.32–2.19) 1.69 (1.43–1.96) 2.45 (1.99–2.89) 2.68 (2.25–3.12) 2.71 (1.93–3.49) 5.13 (4.55–5.70) 9.30 (8.42–10.18) 5.19 (4.42–5.97) 0.81 (0.65–0.97) 2.23 (1.87–2.58) 2.06 (1.65–2.48) 1.70 (1.36–2.04) 4.63 (4.15–5.11) 5.32 (4.59–6.05) 9.30 (8.42–10.18)

21.77 (21.02–22.52) 0.20 (−0.006–0.41) 72.43 (70.16–74.71) 1.32 (0.88–1.76) 2.33 (2.04–2.61) 2.08 (1.62–2.53) 2.32 (1.88–2.75) 3.43 (2.64–4.22) 4.62 (4.04–5.19) 8.00 (7.12–8.88) 4.44 (3.67–5.21) 1.00 (0.84–1.16) 2.24 (1.88–2.59) 1.93 (1.52–2.35) 1.62 (1.28–1.96) 4.16 (3.68–4.64) 3.94 (3.21–4.68) 8.00 (7.12–8.88)

p-value

0.000 0.028 0.011 0.015 0.776 0.132 0.358 0.015 0.415 0.003 0.460 0.012 0.918 0.136 0.497 0.439 0.001 0.000

Adjusted mean difference (standard error)

–0.26 (0.18) –0.07 (0.05) –2.28 (0.77) 0.16 (0.16) –0.29 (0.19) –0.36 (0.23) –0.63 (0.24) –0.19 (0.31) –0.92 (0.35) 0.22 (0.59) 1.16 (0.60) 0.26 (0.13) –0.17 (0.21) –0.46 (0.23) 0.07 (0.19) –0.48 (0.39) –0.62 (0.39) –112.89 (134.78)

p-value

0.076 0.140 0.014 0.286 0.158 0.129 0.015 0.595 0.005 0.563 0.009 0.010 0.508 0.077 0.569 0.229 0.109 0.417

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BMI (kg/m2)b BMI z score Waist circumference (cm)b,c TV weekb (hours/day) TV weekendb (hours/day) Computer weekb (hours/day) Computer weekendb,c (hours/day) Sedentary activies weekb (hours/day) Sedentary activies weekendb,c (hours/day) Rice groupb (servings/day) Vegetables groupb,c (servings/day) Fruits groupb,c(servings/day) Meat groupb (servings/day) Milk groupb (servings/day) Beans groupb (servings/day) Oils groupb (servings/day) Sweets groupb (servings/day) Total energy intakeb (kcal)

Group-by-time a

Note: 95%CI = 95% confidence interval, SE = standard error. a Adjusted mean difference and standard error between H3G-Girls and control groups after intervention (intervention minus control) using transformed data. b Data transformed using the log/square root function owing to non-normality; median and interquartile range provided. Non-transformed data mean and 95%CI was used. c Significance values generated using the transformed data.

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to target all students, but the primary outcomes analysis should focus on students who started the study in the overweight or obese ranges. In the current study, in the subset of girls who were overweight or obese at baseline, small differences were found for the outcomes favoring H3GBrazil, but effects were not statistically significant. Similar findings were observed in the ATLAS obesity prevention intervention, in which the largest effects were observed among boys who were overweight or obese at baseline (Smith et al., 2014b). It is important for school-based obesity prevention programs to target health-related behaviors that are implicated in unhealthy weight gain, including improving PA and dietary behaviors and reducing time in sedentary activities (Lubans et al., 2012; Neumark-Sztainer et al., 2010; Robinson et al., 2010). Indeed interventions designed to improve these health behaviors have the potential to reduce the incidence of weight-related morbidity and mortality (Moreno, 2013; Plotnikoff et al., 2009). However, it may take time before small behavioral changes impact upon weight status in obesity prevention trials, which often do not include long-term follow-up (Jones et al., 2011). This was observed in the original NEAT Girls study, in which there were no significant intervention effects on body composition after 12-months (end of intervention), but after 24-months there was a clinically significant between-group difference of 2% body fat in favor of the intervention group (Dewar et al., 2013). The small reduction in screen-time among girls from the intervention group was a positive change. Screen behaviors have been widely discussed in randomized controlled trials with adolescents from highincome countries (Lubans et al., 2012; Neumark-Sztainer et al., 2010; Robinson et al., 2010). Sedentary behaviors during adolescence has been associated with increased body weight, which is concerning because sedentary habits established during adolescence are likely to track into adulthood (Costigan et al., 2013). Similar, to the NEAT Girls study (Collins et al., 2014), daily energy intake from energy-dense nutrient poor foods was high among study participants. This is against to the recommendations of the Brazilian Food Pyramid, which recommends 1 daily serving of oils/fats (73 kcal) and sugars/sweets (110 kcal) groups (Philippi, 2014). Longterm intake of those foods is associated with diet-related chronic conditions (Moore et al., 2015; Zhang et al., 2015). Changes were in favor for all the food groups, with significant effects for fruits, vegetables, and sweets. It is plausible to suggest that participants in the intervention group replaced sweet consumption with fruits and vegetables. However, given that data was assessed immediately after intervention, it requires follow-up and further examination in future studies (Collins et al., 2014). Strength and Limitations The strengths of this study include the cluster RCT study design, statistical analyses that followed the intention-to-treat principle, the unique study population and monitoring of intervention fidelity. However, there are some limitations that should be noted, including the self-report measures of PA, screen time, and dietary intake. In addition, an inclusion of 12-month assessments would provide evidence for the distal impact of the 6-month intervention. Indeed, while it is possible that the H3G-Brazil intervention on body composition and health behaviors may strengthen over time, the opposite may also be true. Although groups were randomized after baseline assessments, there were statistically significant differences between groups at baseline that may have influenced the study findings. Finally, although the schools were randomized into intervention and control groups, the study participants were not randomized. Teachers and coordinators invited the girls from the courses that have a great number of female adolescents to voluntarily participate on the study. Future studies in other low-and-middle-income countries might use objective measures as complementary to the questionnaire, report 12-month follow-up assessments and randomly selected the study girls.

Conclusion The intervention H3G-Brazil resulted in significant improvements waist circumference dietary intake and leisure-time sedentary behaviors in a sample of adolescent girls “at risk” of obesity. These findings have potential clinical and public health importance. The findings showed the potential of school-based interventions with multiple components to be conducted in middle-income countries such as Brazil. Nevertheless, it is necessary to identify strategies to retain participants in obesity preventive interventions, especially among individuals from low socioeconomic strata and those living in developing countries. Authorship statement All authors support and agree with the information presented in this study. Author contribution statement All authors truly contributed to the development of this study. AL: participated on study concept and design, acquisition of data, analysis and interpretation of data, drafting the manuscript, critical revision of the manuscript for important intellectual content, statistical analysis and administrative, technical and material support. DL: senior researcher of this project, participated on study concept and design, analysis and interpretation of data, drafting of manuscript, and statistical analysis. PG: participate on analysis and interpretation of data, drafting the manuscript, statistical analysis, and critical revision of the manuscript for important intellectual content. DD: Participated on study concept and design, critical revision of the manuscript for important intellectual content and statistical analysis. ET: Participated on acquisition of data, critical revision of the manuscript for important intellectual content and administrative, technical, and material support. SP: senior researcher of this project, participated on study concept and design, acquisition of data, interpretation of data, drafting the manuscript, administrative, technical and material support, and study supervision. Conflict of interest statement The authors do not hold any particular conflict of interest. Author ACBL received a scholarship from the Brazilian Federal Agency for Evaluation and Support of Graduate Education (Coordenação De Aperfeiçoamento de Pessoal de Nível Superior—CAPES). Author PG holds a postdoctoral scholarship from the São Paulo Research Foundation (Fundação de Amparo à Pesquisa do Estado de São Paulo—FAPESP) process no.: 2013/22,204–7.

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