Lifestyle Intervention in Primary Care Settings Improves Obesity Parameters among Mexican Youth

RESEARCH Research and Professional Briefs

Lifestyle Intervention in Primary Care Settings Improves Obesity Parameters among Mexican Youth ROLANDO G. DÍAZ, MS, RD; JULIÁN ESPARZA-ROMERO, MS; SILVIA Y. MOYA-CAMARENA, PhD; ALMA E. ROBLES-SARDÍN, MS; MAURO E. VALENCIA, PhD

ABSTRACT Intervention studies in youth with obesity that can be translated into primary care are limited. We compared a lifestyle intervention to a brief intervention applied by primary care physicians (control group) for treating pediatric obesity in the primary care setting. Seventy-six youth with obesity (body mass index [BMI] ⬎95th percentile or ⬎90th percentile plus waist circumference ⬎90th percentile, aged 9 to 17 years) participated in a 12-month, randomized, controlled trial, conducted at a primary care unit in Northern México from June 2006 through October 2007. Participants randomized to lifestyle intervention attended a family-centered program consisting of 12 sessions of behavioral curriculum, dietary advice from a registered dietitian (weekly for the first 3 months and monthly thereafter), and monthly consultations with a primary care physician. Control group participants attended monthly consultations with a primary care physician who received a brief training on obesity. Forty-three (57%) participants completed the 12 months of study. After 12 months, mean changes (95% confidence interval) in body weight for the lifestyle group and the control group were ⫺0.8 kg (⫺3.2, 1.5) vs ⫹5.6 kg (3, 8.2; P⬍0.001) and mean changes in BMI were ⫺1.8 (⫺2.6, ⫺0.9) vs ⫹0.4 (⫺0.5, 1.3; P⬍0.001), respectively. Intention-to-treat analysis at 12 months confirmed significant differences in primary outcomes (weight ⫺3.5 kg, P⫽0.02; BMI ⫺1.2, P⫽0.03) in favor of the lifestyle group. This study provides preliminary evidence that primary care physicians supported by a registered dietitian and a

R. G. Díaz is a doctoral degree candidate, J. EsparzaRomero and A. E. Robles-Sardín are research associates, S. Y. Moya-Camarena is a research scientist, and M. E. Valencia is a professor of nutriton, Department of Human Nutrition, Centro de Investigación en Alimentación y Desarrollo, Sonora, México. Address correspondence to: Mauro E. Valencia, PhD, Department of Human Nutrition, Centro de Investigación en Alimentación y Desarrollo, A.C. Carretera la Victoria Km 0.6, Hermosillo, Sonora, México, Apartado Postal 1735, CP 83000. E-mail: [email protected] Manuscript accepted: August 26, 2009. Copyright © 2010 by the American Dietetic Association. 0002-8223/10/11002-0013$36.00/0 doi: 10.1016/j.jada.2009.10.042

© 2010 by the American Dietetic Association

behavioral curriculum can be a successful strategy for treating pediatric obesity in the primary care setting. J Am Diet Assoc. 2010;110:285-290.

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besity among youth is a major public health issue in both developed and developing countries (1). Data from the most recent National Nutrition Survey in México showed that overweight and obesity affects 26% of children and about 32% of adolescents (2). Obesity in youth increases the risks of multiple health problems, including hyperinsulinemia, hypertension, and dyslipidemia (3), in addition to psychosocial harms. This situation, in concert with the high persistence from childhood obesity into adulthood (4), represents a challenge. The problem is particularly worrying for developing countries where the burden of obesity-related diseases is increasing at an alarming rate (5,6). The primary care setting represents a strategic place for treating obesity among youth because primary care providers are the main source of health care for families of most social strata in many countries. Unfortunately, studies have shown that pediatric health care providers often fail to diagnose or treat obesity in children, due mainly to a lack of time and effective treatment protocols, as well as to low levels of confidence and skills for managing youth obesity (7-9). Recently, lifestyle interventions—intensive programs including frequent contacts, a behavioral curriculum, and support from other health care providers— have shown promising clinical outcomes in adults (10). It has been demonstrated that under this kind of intensive approach it is possible to treat childhood obesity with relative success (11), even in the long term (11-13). However, the validity of generalizing the results of previous studies conducted by specialty centers or research centers to primary care clinics is uncertain. In addition, some authors have emphasized the lack of interventions in the primary care setting (8,9,11). The main objective of this study was to compare a lifestyle intervention—primary care physician supported by a registered dietitian (RD) and a behavioral curriculum—to a brief primary care physician intervention for treating pediatric obesity in the primary care setting. METHODS Study Design A randomized, controlled, 12-month trial was carried out from June 2006 through October 2007. Recruitment and

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intervention were conducted in a public primary care clinic and outcome measurements were performed at the Department of Human Nutrition, Centro de Investigación en Alimentación y Desarrollo, A. C. (CIAD), Hermosillo, Sonora, México. Primary outcomes were the changes in body weight and body mass index (BMI). Secondary outcomes included changes in other obesity parameters, body composition, blood pressure, and biochemical parameters. Participants Participants were recruited over 2.5 months from a public primary care unit within a secondary care hospital for Sonora State Workers, belonging to the Institute for Social Security and Services. Recruitment was accomplished through flyers, advertisements, referrals by physicians, announcements in a local daily newspaper, radio spots, and from our previous cross-sectional study (including body composition data and blood samples) (14). The latter represented 13% [n⫽10] of randomized participants. Criteria for participation included age between 9 and 17 years, BMI ⬎95th percentile based on the Centers for Disease Control and Prevention growth chart (15) or BMI ⬎90th percentile with waist circumference ⬎90th percentile (16), caregivers interested in weight control, and willingness to attend the group educational sessions. Exclusion criteria included glucose intolerance or type 2 diabetes, psychiatric disorders, any medical condition that would preclude participation in the study, the use of medication that affected weight, or involvement in a weight loss program or structured physical activity. Participants who had lost weight during the 4 months before the study were also excluded. Written informed consent was obtained from participants and parents. Volunteers did not receive any economic incentive to take part in the study, but subjects in the control group were guaranteed their inclusion in the lifestyle intervention after the end of study. This study was approved by the CIAD Institutional Review Board. Randomization and Masking Initial evaluation of outcome parameters took place over a period of 1 month. Once measurements were completed, the study statistician randomly assigned participants 1:1 to the lifestyle intervention or the control group by simple randomization, stratified according to sex. The randomization sequence was generated by a computer. Study personnel who measured the primary outcomes were blinded to group assignments, as were personnel who measured body composition by dual-energy x-ray absorptiometry and performed blood work. Lifestyle Intervention Group Behavioral Curriculum. The behavior modification component of this lifestyle intervention was based on information contained in the workbook, Programa Cambia. This program was adapted from Mellin’s Shapedown Program (17,18), including new culturally appropriate topics focused mainly on the health belief model (19,20), and a simple food guide developed by our group. This adapta-

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tion was based on two pilot interventions (Díaz RG, et al, unpublished data, January 2006), including 31 youths with overweight/obesity and their parents with different socioeconomic status. The first part of the program was focused mainly on children’s perceptions of susceptibility, severity, benefits, and barriers. The second part of the program was centered on self-esteem, how to deal with emotions, communication skills, knowledge regarding body weight regulation, energy intake, nutrition, physical activity, and the use of behavior modification techniques. The program consisted of 12 consecutive, weekly, 2-hour group sessions in the clinic. Sessions were led by an RD with expertise in implementing the program. Each session included about 10 participants similar in age. Participants were asked to establish their own goals regarding physical activity, time spent in sedentary activities, and diet improvement. Goals were revised and renewed every session. Parents of participants received six education sessions and were encouraged to lose weight if they were overweight. For nutrition education and diet prescriptions for children, a simple food guide using different colors (red, yellow, and green) to designate different food groups was developed by our group (Health Nutrition Traffic Light). This tool uses the Mexican exchange list for meal planning (21) and integrated knowledge about the glycemic index of various foods. Fruits, vegetables, legumes, lowfat milk, lean meat/substitutes were assigned the color green, “highly recommended”; starches and fats were assigned the color yellow, “recommended but not exceeding”; and sweets, desserts, fast food, high-fat meat/substitutes, and high-fat milk were assigned the color red, “limit as much as possible.” Foods with a high glycemic index were marked and the participants were encouraged to avoid these foods as much as possible. RD Consultations. Participants and their parents attended weekly consultations with the RD during the first 12 consecutive weeks of the study and monthly thereafter. Participants were given an individualized diet of 1,200 to 1,800 kcal/day, depending on their physical activity and weight status. The diets were flexible regarding macronutrients (22). Slow weight loss was promoted or weight maintenance was emphasized while height increased, with the goal of improving food habits, not implementing a rigid diet. Physician Consultations. Participants and their parents had monthly consultations of 10 to 15 minutes with a primary care physician. The physician only monitored BMI and blood pressure and encouraged the participants to adhere to the dietary recommendation given by the RD and the physical activity goals established in the behavior program. Control Group Participants in the control group and their parents attended monthly consultations of 10 to 15 minutes in length with a primary care physician. Primary care physicians monitored BMI and encouraged youths to progressively perform 30 minutes of physical activity most days of the week, limiting sedentary time to 2 hours per day, and to follow a diet consistent with the Food Guide Pyramid (23). Physicians provided and instructed the partic-

Table 1. Baseline socioeconomic, physical, and metabolic characteristics of participants in a study of obesity among Mexican youth randomized to a lifestyle intervention and control groups in the primary care setting Characteristic Males n % Monthly income (US$b) Parents’ education (yc) Age (y) Weight (kg) Height (cm) Body mass index Body mass index z score Waist circumference (cm) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Total cholesterol (mg/dLd) Low-density lipoprotein cholesterol (mg/dLd) High-density lipoprotein cholesterol (mg/dLd) Triglycerides (mg/dLe) Fasting glucose (mg/dLf)

Lifestyle group (nⴝ21)

Control group (nⴝ22)

10 11 48 50 4™™™™™™™™™™™ mean⫾standard deviation ™™™™™™™™™™™3 1,069⫾503 906⫾772 14.5⫾3.4 13.8⫾3.2 11.6⫾2.1 11.7⫾2.2 70.3⫾17 69.2⫾15 152⫾8.5 153⫾8.2 30.2⫾5.4 29.1⫾4.2 2.12⫾0.37 2.07⫾0.25 97.5⫾11.4 96.8⫾9.7 103⫾10.2 106⫾6.4 67⫾7.4 67⫾5.9 172⫾28 179⫾36 105⫾25 109⫾33 43⫾7.2 43⫾8.7 120⫾43 125⫾50 87⫾8.2 91⫾8.4

P valuea

0.41 0.46 0.81 0.82 0.56 0.45 0.57 0.82 0.34 0.87 0.47 0.63 0.83 0.70 0.11

a

Based on independent t test. Exchange rate: 13.37 Mexican pesos per US dollar as of June 20, 2009. Parent’s education level was obtained adding the highest number of academic years of both parents and dividing by 2. d To convert mg/dL cholesterol to mmol/L, multiply mg/dL by 0.026. To convert mmol/L cholesterol to mg/dL, multiply mmol/L by 38.7. Cholesterol of 193 mg/dL⫽5.00 mmol/L. e To convert mg/dL triglyceride to mmol/L, multiply mg/dL by 0.0113. To convert mmol/L triglyceride to mg/dL, multiply mmol/L by 88.6. Triglyceride of 159 mg/dL⫽1.80 mmol/L. f To convert mg/dL glucose to mmol/L, multiply mg/dL by 0.0555. To convert mmol/L glucose to mg/dL, multiply mmol/L by 18.0. Glucose of 108 mg/dL⫽6.0 mmol/L. b c

ipants and their parents how to use a color Food Guide Pyramid and a menu example. The original Food Guide Pyramid was adapted to include various traditional foods eaten in México. Parents were encouraged by physicians to adopt positive behaviors, for instance, reduction of sweetened beverages and increasing exercise and healthful foods to facilitate behavior change in their children. Primary Care Physician Recruitment and Training Primary care physicians who participated in the study consisted of five general practitioners and one pediatrician. This group attended a series of meetings (four to six sessions of 1.5 hours each) before the beginning of the intervention. The program included the revision and discussion of the clinical guidelines for obesity in children (23), a review of health consequences of obesity in youth, and the use of Epi Info software (version 3.3.2, 2005, Centers for Disease Control and Prevention, Atlanta, GA) for monitoring BMI and the study Food Guides. At the end of the program, all physicians answered satisfactorily an informal evaluation including 20 open questions regarding the topics mentioned above. Furthermore, physicians were provided with an algorithm to facilitate the visits. The same physicians participated in the two different group interventions and had a similar number of participants from each group. Outcome Measures Primary and secondary outcome measurements were performed by trained staff at CIAD. Weight and height were

measured with a digital scale (FV-150 KA1, A&D Company, Ltd, Tokyo, Japan) and a calibrated stadiometer (Holtain LTD, Crosswell, UK) (24). BMI and BMI z score were obtained using Epi Info software. Body fat was determined by a whole-body dual x-ray absorptiometry scan (Lunar DPX-MD, GE Lunar Corporation, Madison, WI), and waist circumference (24) and blood pressure were measured according to established guidelines (25). Glucose levels were determined by the glucose oxidase method and triglycerides, total cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol levels were measured according to standard procedures in fasting conditions (26,27). Statistical Analysis Sample size was based on information from previous studies (28,29). Assuming a two-tailed analysis with ␣ set at .05 and a standard deviation of 6 kg, 52 participants (26 per group) were estimated to provide 80% power to detect a difference of 4.7 kg between groups (30). We increased the planned number of participants to 76 (38 per group), assuming a potential drop out rate of 30%. The outcomes at 6 and 12 months were analyzed in all participants who completed the study (lifestyle group, n⫽21; control group, n⫽22) (completer’s analysis). We also applied an intention-to-treat analysis at 12 months in the primary outcomes of the study. Considering the risk of bias of procedures for analyzing incomplete data (31), we made an effort to obtain the primary outcomes (weight and BMI) of all participants who dropped out of the study (n⫽33) measuring children at their homes.

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Table 2. Change in obesity parameters for lifestyle (n⫽21) and control groups (n⫽22) at 6 and 12 months in a study of Mexican obese youth who completed the study for management of obesity in the primary care setting Outcome

Baseline

6 mo

12 mo

Change at 6 mo

Change at 12 mo

Difference at 6 moa

4™™™™™™™™™™™™™™™™™™™™™ mean⫾standard deviation ™™™™™™™™™™™™™™™™™™™™™3 Weight (kg) Lifestyle Control Body mass index Lifestyle Control Body mass index z score Lifestyle Control Waist circumference (cm) Lifestyle Control Body fatd (kg) Lifestyle Control Body fatd (%) Lifestyle Control

Difference at 12 moa

4™™™™™™™ mean (95% confidence interval) ™™™™™™™3

70.3⫾17 69.2⫾15

66.6⫾16.2 71.9⫾15.2b

69.5⫾16.1 74.8⫾15.9b

⫺3.7⫾3.3 2.7⫾3.0

30.2⫾5.4 29.1⫾4.2

27.7⫾5.3b 29.1⫾4.3

28.4⫾5.5b 29.5⫾4.7

⫺2.5⫾1.3c 0.00⫾1.2

⫺1.8⫾1.9c 0.4⫾2.1

⫺2.5 (⫺3.2, ⫺1.7)***

2.12⫾0.37 2.07⫾0.25

1.81⫾0.49b 2⫾0.29b

1.83⫾0.50b 1.97⫾0.36

⫺0.31⫾0.20c ⫺0.07⫾0.12

⫺0.29⫾0.24c ⫺0.09⫾0.23

⫺0.24 (⫺0.35, ⫺0.14)***

97.5⫾11.4 96.8⫾9.7

91.9⫾11.7b 97.6⫾10.4

91.3⫾12.1b 97.4⫾11.8

⫺5.6⫾5.2c 0.8⫾5.7

⫺6.2⫾6.2c 0.6⫾6.4

⫺6.4 (⫺9.8, ⫺3)***

⫺6.8 (⫺10.8, ⫺2.9)**

33.8⫾10.5 33.4⫾10.2

28.7⫾10.6b 32.8⫾9.7

31.5⫾11b 34.7⫾10.5

⫺5⫾3.3c ⫺0.6⫾3.7

⫺2.3⫾4.8c 1.3⫾5.3

⫺4.5 (⫺6.8, ⫺2.2)***

⫺3.6 (⫺6.9, ⫺0.4)*

47.7⫾4.0 46.5⫾4.8

42.4⫾6.2b 44⫾5.3b

44.6⫾6.2b 44.9⫾5.5

⫺5.2⫾3.4c ⫺2.5⫾3.8

⫺3.1⫾4.1 ⫺1.7⫾4.5

⫺2.7 (⫺4.8, ⫺0.5)*

⫺1.4 (⫺4.2, 1.3)

b

c

c

⫺0.8⫾5.2 5.6⫾5.9

⫺6.4 (⫺8.4, ⫺4.5)***

⫺6.4 (⫺9.8, ⫺3)*** ⫺2.2 (⫺3.4, ⫺1)*** ⫺0.20 (⫺0.34, ⫺0.05)**

a

Defined as change for the Lifestyle group minus change for the control group. Significant difference (P⬍0.05) vs corresponding baseline value using paired t test. Significant difference (P⬍0.05) vs control group using independent t test. d Lifestyle group (n⫽20) and control group (n⫽20) at 6 and 12 months. *P⬍0.05. **P⬍0.01. ***P⬍0.001. b c

However, we were able to measure the primary outcomes only in 23 drop outs. Thus, intention-to-treat analysis included 66 (87%) of the original 76 randomized participants (lifestyle group, n⫽33; control group, n⫽33). Outcomes between groups were analyzed using an independent sample t test. For differences before and after intervention, a paired t test was used. A P value of 0.05 or less (two sided) indicated statistical significance. Normality was verified graphically. All analyses were performed using Number Cruncher Statistical System for Windows software (version 2001, NCSS LLC, Kaysville, UT). RESULTS Participants Of the 134 youths assessed for eligibility, 76 participants were randomized to study groups. Dropout rates for the two groups were similar: 13 (34%) vs 13 (34%) at 6 months and (17) 45% vs (16) 42% at 12 months, for lifestyle and control groups, respectively. The study groups were well balanced regarding baseline characteristics (Table 1). Attendance at intervention activities among participants in the lifestyle group were as follows: behavioral protocol, 9.3 sessions (77%); parent sessions (any of the parents), 4.0 (66%). The average attendance for the group of both parents and for the group of mothers only was 4.4 (71%) and 3.4 (60%), respectively. Attendance to RD consultations was 12.8 (67%) and physician consultations, 4.9 (45%). Control group attendance to physician consultations was 4.7 (43%). Different levels of participation of the parents in the educational sessions for parents did not affect the out-

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comes, since there was no difference between the highattendance group (ⱖ5 out of six sessions) vs low attendance group (⬍5 sessions) in the outcomes of the children (ranging of P value 0.54 to 0.65). Four (5%) volunteers from our previous cross-sectional study completed the 12-month period and they did not affect conclusions from this study. Similar significant results in primary outcomes were found after excluding this group of participants from both the intention-to-treat and completers analysis (data not shown). Study Outcomes Completers analysis showed significant changes in primary outcomes and other obesity parameters in favor of the lifestyle group at both 6 and 12 months (Table 2). Although the lifestyle participants had only a slight nonsignificant mean weight loss at 12 months (⫺0.8 kg) while still growing (⫹4.1 cm, P⬍0.001), the control group significantly gained weight (mean, ⫹5.6 kg) and height (⫹5.2 cm, P⬍0.001), representing a significant betweengroup difference in body weight (⫺6.4 kg) and BMI (⫺2.2). Between-group difference in height (⫺1.1 cm, P⫽0.21) was not significant. Intention-to-treat analysis showed significant differences between the groups in body weight and BMI at 12 months. Lifestyle group participants had a slight nonsignificant increase in body weight (⫹2.1 [95% confidence interval [CI] ⫺0.06, 4.3] kg, P⫽0.06), whereas the control group participants had a much greater mean increase in body weight (⫹5.6 [95% CI 3.5, 7.7] kg, P⬍0.001), and the difference between the groups was ⫺3.5 kg (95% CI ⫺6.5, ⫺0.5, P ⫽ 0.02). In addition, mean BMI had a nonsignif-

icant decrease in the lifestyle group (⫺0.6 [95% CI ⫺1.4, 0.2], P⫽0.14) and a nonsignificant increase in the control group (⫹0.6 [95% CI ⫺0.1, 1.3], P⫽0.08), and the difference between the groups was significant (⫺1.2 [95% CI ⫺2.3, ⫺0.2], P⫽0.02). There were significant between-group differences in systolic (⫺6.3 [95% CI ⫺10.5, ⫺2.1] mm Hg, P⬍0.01) and diastolic (⫺4.9 [95% CI ⫺8.8, ⫺1] mm Hg, P⫽0.01) blood pressures only at 6 months in favor of the lifestyle intervention. There were no significant between-group differences in changes in fasting glucose, triglyceride, highdensity lipoprotein, low-density lipoprotein, or total cholesterol levels at 6 or 12 months (data not shown). DISCUSSION To our knowledge, this is the first long-term (ⱖ1 year) study to show significant results on obesity parameters among youth in the primary care setting as well as the first effective lifestyle intervention among Mexican youth. Previous studies of primary-care– based programs include the use of telephone calls (or mail) by an RD or a psychologist and a tailored behavior program or consultations with a general practitioner with tailored materials (32,33). Differences relative to the control groups in Saelens’ and McCallum’s studies (32,33) for BMI z score were, respectively, ⫺0.11, (P⬍0.02) and 0.0, (P⫽1.0) vs ⫺0.20 (P⬍0.01) in our study. The BMI z score changes of experimental groups from baseline were ⫺0.05 (P⫽0.07) and ⫺0.03 (P⫽0.62) vs ⫺0.29 (P⬍0.001) in our study. The mentioned studies had low rates of attrition (10% and 16%) compared with present study (43%). However, the BMI z score changes from baseline in the intention-totreat analysis of our experimental group (⫺0.18, P⬍0.001, with an attrition rate of 13%) remained greater than the comparison studies. It is possible that only comprehensive high-intensity programs, such as the lifestyle intervention used in our study, can produce changes in obesity parameters given our obesogenic environment. A comprehensive lifestyle intervention can enhance motivation and awareness (perceptions) and improve feedback, skills, knowledge, and social support, which are some of the key factors to achieve behavior change and weight loss (19,20,34,35). Therefore, our study highlights a theory-based potential strategy for treating youth obesity in the primary care setting. However, it is clear that implementing a comprehensive lifestyle intervention represents a challenge, and cost-effectiveness analyses are needed to assess the usefulness of these programs in primary care. In contrast, the results for the control group in our study and those reported by others confirm that clinical weight management counseling programs that lack a more comprehensive lifestyle program have poor outcomes (32,33,36). This finding is particularly noteworthy because most public clinic-based programs for treating obesity in many countries, especially in developing countries, do not include comprehensive lifestyle interventions. A limitation of this study was the high attrition rates. High attrition from programs aiming to treat obesity in young people is a known problem (37-39); however, the number of drop outs was similar in both study groups and did not alter significance on primary outcomes, as shown by intention-to-treat analysis.

CONCLUSIONS There is a lack of solution-oriented research assessing pediatric treatments for obesity in primary care settings, in both developing and developed countries. This study provides preliminary evidence that primary care physicians supported by an RD and a behavior program can be a successful strategy for treating pediatric obesity in primary care settings. Further interventions are essential to verify the generalizability of this approach. STATEMENT OF POTENTIAL CONFLICT OF INTEREST: No potential conflict of interest was reported by the authors. FUNDING/SUPPORT: This work was supported by a grant from the International Atomic Energy Agency (ARCAL 6/059) and CONACyT (R/182996). ACKNOWLEDGEMENTS: The authors thank the families who participated in this study and Rodolfo Cisneros, MS, MD, for his help in implementing the study. The authors also thank Floria Juarez, MD; Griselda García Amavizca, MD; Alejandrina Santacruz, MD; Marco Antonio Corrales, MD; Francisco Casillas, MS, MD; and Cruz Ausencio Gómez, MD, for their participation in the study, and Isabel Gardea, RD, for her assistance in data collection and technical support. In addition, the authors thank Rosa Consuelo Villegas, MS, and Ana Cristina Gallegos, MS, for their technical support. References 1. Ebbeling CB, Pawlak DB, Ludwig DS. Childhood obesity: Publichealth crisis, common sense cure. Lancet. 2002;360:473-482. 2. Olaiz-Fernández G, Rivera-Dommarco J, Shamah-Levy T, Rojas R, Villalpando-Hernández S, Hernández-Ávila M, Sepúlveda-Amor J. Encuesta Nacional de Salud y Nutrición 2006. Instituto Nacional de Salud Pública. [National Health and Nutrition Survey 2006. National Institute of Public Health]. Cuernavaca, México; 2006. 3. Freedman DS, Dietz WH, Srinivasan SR, Berenson GS. The relation of overweight to cardiovascular risk factors among children and adolescents: The Bogalusa Heart Study. Pediatrics. 1999;103:1175-1182. 4. Whitaker RC, Wright JA, Pepe MS, Seidel KD, Dietz WH. Predicting obesity in young adulthood from childhood and parental obesity. N Engl J Med. 1997;337:869-873. 5. Rivera JA, Barquera S, Campirano F, Campos I, Safdie M, Tovar V. Epidemiological and nutritional transition in Mexico: Rapid increase of non-communicable chronic diseases and obesity. Public Health Nutr. 2002;5:113-122. 6. Hossain P, Kawar B, El Nahas M. Obesity and diabetes in the developing world—A growing challenge. N Engl J Med. 2007;356:213-215. 7. Cook S, Weitzman M, Auinger P, Barlow SE. Screening and counseling associated with obesity diagnosis in a national survey of ambulatory pediatric visits. Pediatrics. 2005;116:112-116. 8. Dietz WH, Nelson A. Barriers to the treatment of childhood obesity: A call to action [editorial]. J Pediatr. 1999;134:535-536. 9. Robinson TN. Obesity prevention in primary care [editorial]. Arch Pediatr Adolesc Med. 2006;160:217-218. 10. Diabetes prevention program research G. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002;346:393-403. 11. Oude Luttikhuis H, Baur L, Jansen H, Shrewsbury V, O’Malley C, Stolk R, Summerbell C. Interventions for treating obesity in children. Cochrane Database Syst Rev. 2009;1:CD001872. 12. Epstein LH, Valoski A, Wing RR, McCurley J. Ten-year follow-up of behavioral, family-based treatment for obese children. JAMA. 1990; 264:2519-2523. 13. Epstein LH, Valoski A, Wing RR, McCurley J. Ten year outcomes of behavioral family-based treatment for childhood obesity. Health Psychol. 1994;13:373-383. 14. Cisneros-Tapia R, Navarrete FA, Gallegos AC, Robles-Sardin AE, Mendez RO, Valencia ME. Insulin sensitivity and associated risk factors in Mexican children and adolescents. Diabetes Care. 2005;28: 2546-2547.

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