STUDY DESIGN AND SETTING
This is a randomized controlled trial comparing two groups, the intervention group (IG) and the usual care comparison group (CG). Eligible participants were recruited from “Programa Academia da Saúde” (PAS) between March to August 2012.
The public health system in Brazil has invested heavily in primary care. The system is divided into different health services, such as basic health units and the PAS. This program aims to enhance population autonomy through actions that promote health in socially deprived areas.14 The PAS service offered, at no cost, physical exercise and food and nutrition education actions conducted by health professionals, for entire population. More than 2,900 Brazilian municipalities have a PAS unit. The participants have vulnerable situation, with low socioeconomic condition and high prevalence of NCDs15. The innovative PAS service represents an important initiative to promote health, prevent, and control prevalence of NCD in especially in populations with high social vulnerability. The Program is an important service of the Health Care Networks, including care of NCDs such as obesity, functioning as a gateway to public health system.
All participants from the PAS unit analyzed were included in the study if they met the following inclusion criteria: female (majority of users in PAS, making it possible to obtain sufficient sample for the trial),15 have participated in service activities in the previous month (which enabled the nutritional evaluation for sample selection), aged 20 years or older, and obese adult (individuals aged 20 to 59 years and body mass index - BMI ≥ 30 kg/m2) 16 or overweight elderly (individuals aged 60 years or over and BMI≥ 27 kg/m2).17 The exclusion criteria included individuals with cognitive difficulties, that made it impossible to answer the interview, or who were pregnant because they present specific recommendations for weight control.
The sample of this study included all individuals from PAS unit who met the inclusion and exclusion criteria. Of 294 individuals who were screened, 89 were eligible, and 86 consented to participate (FIGURE 1). The subsample (40%) to biochemical profiles analyses was calculated based an average of other experimental designs, and the participants were randomly selected.17 The considered sample size effect allows 80% of power to achieve 5% weight reduction as reported in the literature19 and possible attrition of 30%. A posteriori sample calculation was performed, considering a tolerable relative error of 5%, and 95% of confidence interval, obtaining an average sample size estimated at 39 participants.
RANDOMIZATION AND BLINDING
A blinded researcher performed the participant allocation for CG and IG through a random numbers table. To maximize the proportion of participants receiving the intervention and the statistical power available to compare the groups, the participants were randomized for 40% to CG and 60% to IG. Randomization resulted in the following allocation: CG = 35 and IG = 51. We used separate blocks based on the intervention group to allocate participants to blood collection (CG = 15 and IG = 20). Due to the type of intervention, it was impossible to blind the participants and investigator to the intervention. It was not possible to blind users because of the different nature of the interventions: while the usual care participated in collective activities, the IG had individual counseling. Also, one of the strategies used in the actions with the IG was the agreement of the treatment goals and clarification of the proposed objectives, which precluded its blindness. For all analyses, the participants were assigned to their original groups (IG or CG).
Intervention
Women within the CG maintained usual activities in the service, including physical exercise three times weekly and collective food and nutrition actions once per month. The nutrition actions include collective health education and workshops, with an average of 30 minutes. Women in the IG participated in the same activities as the CG, but they also received individual health counseling based on the TTM for weight management, performed once per month for 6 months.
The TTM was used with health education to foster a reflexive, proactive problem-solving and participatory approach and to consider the different aspects of eating behavior and physical activity to promote the autonomous practice of healthy habits. Therefore, the participants were instigated to identify their obstacles to weight loss and constructed (together with the health professional) possible strategies to overcome them.
Prior to the intervention development, participants were classified into SOC using Weight Loss Behavior-Stage of Change Scale regarding four habits related to obesity: portion control, dietary fat, fruit and vegetable intake, and physical activity. Intervention studies with multiple behaviors show greater compliance with body weight control than using a single behavior-based approach 5,7,10,13. Among the most evaluated behaviors are portion control, dietary fat, fruit and vegetable intake, in addition to physical activity. These behaviors are key markers for weight loss7.
To develop specific interventions, participants were classified into two groups for each habit: (i) pre-action, including women classified in the SOC (TABLE 1), pre-contemplation, contemplation, and preparation; and (ii) action, including participants who were classified in the action or maintenance stages.17 The approaches were different for the pre-action and action groups for each assessed domain. In pre-action, the IG used processes of change predominantly based on cognitive changes to increase motivation and awareness about health challenges. The action (IG) group focused on processes of change related to behavioral changes, including more detailed guidance on nutrition concepts and physical activity.9 The intervention was conducted to increase decisional balance and self-efficacy.
The intervention was conducted by a research team consisting of four dietitians. To standardize the intervention, the dietitians participated in periodic training on TTM theory and its application for weight control taught by professor and researcher of TTM. The research team developed a manual to support the implementation of the intervention with modules for the four dimensions of TTM and each food habit and physical activity related to obesity.
The individual sessions generally lasted at least 30 min and focused on individualized goal setting, based on the patient’s SOC assessed at the baseline, and problem-solving. Verbal and written guidelines through simple language – according to individual participant needs – were used for guidance. Monthly visits assessed participant adherence to the agreed changes and identified the need for treatment revision. When a participant had difficulty following the treatment, discussions about adherence and barriers were reinforced, and new strategies were developed.
MEASURES
Data were obtained from face-to-face interviews in two times: (1) after randomization and before the beginning of the intervention; (2) after 6 months of MTT intervention. The questionnaire included socio-demographic, economic (age, income, education, occupation), and health information (diabetes mellitus, arterial hypertension, self-health perception, body satisfaction, attempted to lose weight in the last month, physical exercise), dietary behaviors (number of daily meals, daily per capita sugar), and food intake (two 24-h dietary recalls), as well as measuring anthropometry (weight, height, waist - WC and hip circumferences). In addition, biochemical parameters [glucose, adiponectin, resistin serum levels] were obtained by blood tests. Inflammatory parameters were chosen for their relationship with obesity.
To analyze the food intake, the mean consumption from the two 24-h dietary recalls were calculated. The 24-h recall examined consumption over two distinct and nonconsecutive days, including weekend or holidays. A kit of homemade measures was provided to improve the estimation of the food quantities. Data obtained from 24-h recall were analyzed with Diet Win® Professional version 2.0, and the caloric and macronutrient intakes were classified according to gender and age recommendations.19, 20 The subsample participants fasted when blood was collated for biochemical measurements. Blood collection was performed by nurses in the first and last week of the study, always in the morning, with the individual fasting for 12h. For analysis of the biochemical measures, blood was collected and stored in a freezer at -80°C.
The version of the Weight Loss Behavior-Stage of Change Scale algorithm (validated5, translated, back-translated, and adapted for use in Brazil) was used to identify the stages of change for weight management.21 The instrument was also previously tested in PAS users to verify its applicability. The instrument assesses four habits related to weight management: (i) portion control, (ii) dietary fat intake, (iii) fruit and vegetable intake, and (iv) usual physical activity. For each habit evaluated, the participant evaluated their behavior according to statements ranging from 9 to 11 affirmatives . For each statement, the participant indicated the option that best described their behavior among the five available phrases, each referring to SOC, ranging from “I do not do this at least half the time now and I have no plans to do this” (precontemplation) to “I do this at least half the time now and have been doing it regularly for more than 6 months” (maintenance). The food portion control evaluated the amount of food consumed during a meal, and throughout the day, day-to-day eating control, and impulse to eat control into situations such as stress and depression. The dietary fat intake had information regarding consumption of chicken skin, meat with apparent fat, fat milk, fried foods, fast food, biscuits, butter or margarine, and sauces. The fruit and vegetable intake evaluated the portions consumed throughout the day, as well as their consumption in snacks or substitution for other food, such as sweets. The SOC for physical activity focused on evaluating domestic activities and active daily routines.
To identify the participant's SOC for each of the evaluated habits, the option with the highest number of answers within the questions included in the evaluation was verified, and in case of a tie, the least advanced stage of behavior was considered.
At the 3- and 6-month follow-ups, the IG participants were evaluated for health counseling adherence, including identifying perceived barriers, benefits, and social support to make changes. This information was obtained through the participants’ self-report who completed the follow-up.
The primary outcome was changes in weight from baseline to 6 months. Secondary outcomes included BMI, WC, energy consumption, glucose, adiponectin, and resistin. Other measures collected at baseline and 6 months were described. All data were collected by healthcare professionals who were properly trained and supervised by the researchers.
STATISTICAL ANALYSIS
The Shapiro-Wilk test was used to evaluate the distributions of the variables. Variables with normal distribution were presented as means and standard deviations (SDs), and asymmetric variables were presented as medians and interquartile ranges (P25 - P75). The inter-group differences at the baseline were evaluated using the independent sample t-test, chi-square, and Fisher’s exact test for socioeconomic variables, health variables and stages of change. The paired Student t-, Wilcoxon, and McNemar tests were used to evaluate intra-group differences for dieting habits, food intake, anthropometry and biochemical parameters over the study period. The test of homogeneity was performed for each of the primary and secondary outcomes. Analysis of covariance (ANCOVA) was used to assess intervention effectiveness to primary and secondary outcomes, adjusted for age, education, and baseline measurements. The adjustment measures were determined considering important factors associated with the outcomes according to a literature review and the groups differences at baseline. The results of the comparisons were corrected using the Bonferroni method.
Intention-to-treat analysis was performed to determine the effectiveness of the intervention and to keep all participants with non-missing baseline outcome measurements. In case of missing values at 6-month (32.5%), imputation was used by replacing the baseline value following the Baseline Observation Carried Forward approach.
Statistical significance was attributed when p-values were less than 0.05. Analyses were performed using SPSS Statistics for Windows, version 17.0.
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