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Assessing the efficacy of a group mediated nutritional knowledge intervention for individuals with obesity.

INTRODUCTION

Obesity is a major factor in poor health and chronic disease in Canada [1]. The etiology is complex and influenced by genetics [2], environment [3], behaviour [4], social/economic conditions [3], education levels [5], income [6, 7], and other factors [3, 8-10]. Despite a complex etiology, physical activity and nutritional knowledge are considered to be good interventions for possible reduction in obesity [11-15].

The Healthy Eating Active Living for Tomorrow's Health (HEALTH) was a community-group based physical activity and nutritional education intervention aimed at helping adults with obesity manage their condition to prevent weight gain and promote healthy lifestyles geared towards weight loss [16]. The intervention was conducted at 4 sites, 2 rural and 2 urban, and consisted of 1 hour of physical activity 3 times per week led by Certified Exercise Physiologists and bi-weekly nutritional sessions led by Registered Dieticians (RDs). The same staff members were used for all sites. This study reports on the nutrition knowledge and eating habits of participants who completed the program.

METHODS

Recruitment used traditional media messages (provincial radio and regional newspapers) and physician referrals. Most participants were self-referred, with a minority being referred by a physician. Participants had to have a body mass index (BMI) between 30 and 40 and be over 18 years of age. The HEALTH study was funded by Canadian Institutes of Health Research and the New Brunswick Health Research Foundation and received ethics approval by 2 research ethics boards: #2011105 and #2011-1629.

A power calculation was performed for the study based on exercise data from a previous 8-week intervention called the "Take HEART" study using walk-time data of participants. Obesity intervention studies usually encounter high attrition rates, and thus the HEALTH study set a target goal of a minimum of 35 participants per site [17]. Overall 146 participants were recruited. Owing to attrition, at the end of the intervention, complete data were available for 59 of the 146 (40%) participants.

As reported in a previously published paper [16], blood pressure, resting heart rate, BMI, waist circumference, SF-36v2 Health Survey, physiological abilities measurements, and nutritional behaviour and knowledge measures were collected. Two of the intervention groups also received bi-weekly group mediated cognitive behaviour interventions [18], with those findings also reported elsewhere [16]. In this report we focus on the outcomes of the community group nutritional education that have not been previously reported.

Intervention

The participants were measured 3 times: at baseline (T0), after the 6-month intervention (T1), and after 12 months (including 6 months of self-management) (T2). At entry into the study, participants' physical and demographic characteristics were similar across all 4 groups, except there were more women than men (85% female) and urban participants had higher levels of education and higher incomes compared with the rural participants [16].

All participants attended bi-weekly nutritional sessions (on average 75% of the time) during the active 6-month period of the intervention. The nutritional component was comprehensive, covering topics including: how to read nutrition food labels; portion control; fat, sugar, and sodium intake; meal planning; and grocery shopping, including a grocery store tour. The measures used to assess the impact of the nutritional sessions were selected by the RDs on the team as the most reliable and valid measures that would not burden participants with too many and/or intense measures.

Measures

Three self-reported surveys were used to assess changes in nutritional knowledge and eating habits over the course of the study at T0, T1, and T2: the "Nutrition Assessment" (NA) [19], "Nutrition Knowledge Survey" (NKS) [20], and the "Factors that Influence your Choice of Food Questionnaire" (FCQ) [21]. The NA is a 22-item self-report measure that assesses the types/amount of food participants have consumed in the past week. Participants respond on a 1-5 Likert scale ranging from "less than once per week" to "twice or more per day." Categories of food include fruits, vegetables, dairy products, whole grains, fish, and red meat. The NA shows convergent validity with other measures of its kind [19].

The NKS survey consists of multiple choice and open-ended questions that assess knowledge of healthy eating, food group products, and food choices. This 30-item measure is scored out of 90 and is divided into the following subscales: (i) knowledge of dietary recommendations, (ii) knowledge of sources of foods/nutrients, and (iii) choosing everyday foods [20].

The FCQ is a 36-item measure that assesses physical, social, and psychological factors the influence decisions regarding the purchasing, preparation, and eating of foods. The questionnaire is divided into 9 subscales [21]. Two of the 9 subscales were analyzed: "choosing food for weight control" and "choosing food for health properties." These subscales were selected for their theoretical relevance to the study and, additionally, analyzing 9 subscales would increase type I error. As an example, participants responding to the "weight control" would be asked questions such as "It is important for me that the food I eat on a typical day is low in calories," to which they respond on a Likert-type scale. Other research shows this measure has acceptable test--retest reliability on the FCQ over a 2-3 week period and shows convergent validity with other nutritional measures [21].

Analysis

Repeated Measures Analysis of Covariances (ANCOVA) were conducted using SPSS 17 for Windows. The time of measurement (T0, T1, and T2) was entered as a within-subject independent variable, the location of the intervention (urban vs. rural) was entered as a between subject independent variable, and the scores for the 3 measures of nutrition and eating habits were entered as the dependent variables. Level of education (high school or less vs. post-secondary) was entered as a covariate to control for its potential confounding effects. The P value for significance was set at <0.05.

RESULTS

Analysis of the NA showed a significant main effect of time, indicating the difference across the three measuring points, T0, T1, and T2, was significant. Bonferroni post-hoc tests demonstrated that scores differed significantly from T0 to T1 and T0 to T2 (Table 1). These results show participants reported they increased consumption of healthy foods during the active intervention phase and maintained these changes during self-management.

Analysis of the NKS also demonstrated a significant main effect of time, indicating the difference across the 3 time points was significant. Post-hoc tests revealed that scores differed significantly from T0 to T1 and from T0 to T2, but not from T1 to T2. The findings show participants' nutritional knowledge improved during the active intervention and this knowledge was maintained during the self-management phase.

For the FCQ subscales, the "choosing food for weight-control" subscale showed a main effect of time, indicating the difference across the 3 time points was significant. Scores on the weight-subscale differed significantly between TO and T1 and between TO and T2 but not between T1 and T2. The "choosing food for health properties" subscale also showed a significant main effect of time. Specifically, scores improved between T0 and T1 and between T0 and T2, but not between T1 and T2. Results of the FCQ demonstrate that participants changed their food choices to engage in healthier eating and weight control.

DISCUSSION

The data of this 12-month, community-based intervention have demonstrated that group-based nutritional educational sessions delivered by an RD in either a rural or urban community show positive results for patients in managing their obesity. These findings are congruent with early work that suggests when it comes to healthy eating knowledge and behaviour are linked [22, 23]. Although the drop-out rate was high, the 40% of participants who remained in the intervention demonstrated that this approach can be a useful tool in the arsenal of obesity treatment strategies. Participants who completed all 3 measurements retained their new knowledge, although the gains were attenuated during the self-management period. All participants reported changing their eating habits by choosing healthier foods and/or foods for weight loss, and the participants' nutrition knowledge also improved.

This intervention was based on self-selected participants who were likely motivated to participate. Although we did not use a measure to assess their readiness to change, all studies using voluntary participation likely tend to get participants who are ready to make some changes in their lives. Results are limited by the fact that this analysis did not include a control group, but was focused on within-subject changes. Results are also limited by self-reported information on questionnaires used to assess knowledge and eating habits. It may be beneficial for future studies to examine more elaborate behavioural measures of food consumption, perhaps by corroborating self-report data with food purchasing behaviours and/or food diaries. Nonetheless this intervention has demonstrated that participants will benefit from new knowledge that is imparted to them. Additionally, these positive health outcomes can be obtained with the help of providers outside of the physician's office.

RELEVANCE TO PRACTICE

The current research informs the body of literature that suggests nutritional knowledge is related to self-reported food choice and eating habits, although its relative role/effectiveness in behaviour change has been debated [22, 23]. Our work suggests that a group-based educational intervention delivered by RDs to individuals with obesity is effective in changing nutritional behaviours during active treatment, and this can be maintained during a self-management phase in those who complete the program. Future studies should examine the longevity of these lifestyle changes as well as comparisons with a control group. Moreover, future studies can examine attrition issues in these types of programs. Generally, this approach may be cost effective compared with personal counselling sessions, although costs were not assessed.

Funding: Funding provided by CIHR (MOP110940) and New Brunswick Health Research Foundation.

Conflict of interest: The authors declare that they have no competing interests.

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BAUKJE MIEDEMA, PhD (a); ANDREA BOWES, PhD (b); RYAN HAMILTON, PhD (c); STACEY READING, PhD (d)

(a) Dalhousie University Family Medicine Teaching Unit, Dr. Everett Chalmers Regional Hospital, Fredericton, NB, Canada; (b) Department of Nursing and Health Sciences, The University of New Brunswick, Saint John, NB Canada; (c) Department of Psychology, Faculty of Arts, University of New Brunswick, Fredericton, NB, Canada; (d) department of Sport and Exercise Science, Faculty of Science, University of Auckland, Auckland, New Zealand
Table 1. Nutrition questionnaire results.

                                Post-active
                               intervention,       Post-self-
             Intake (T0) (a)   6 months (T1)   management period,
                                    (a)        6 months (T2) (a)

Nutrition     64.54 (10.70)    67.92 (9.11)      67.98 (10.58)
Knowledge
Survey
[20] (d)

Nutrition      8.54 (8.93)     12.71 (7.88)       13.54 (9.11)
Assessment
[19] (e)

Weight         2.80 (0.69)      3.07 (0.59)       3.19 (0.63)
subscale
[21] (f)

Health         2.85 (0.60)      3.20 (0.46)       3.18 (0.53)
subscale
[21] (f)

                                       Observed
              Significance test (b)    power (c)

Nutrition       [F.sub.(2112)] =         0.65
Knowledge        3.51, P = 0.03
Survey
[20] (d)

Nutrition    [F.sub.(1.62,91.16)] =      0.68
Assessment       4.37, P = 0.02
[19] (e)

Weight       [F.sub.(2,112)] = 6.62,     0.90
subscale            P = 0.002
[21] (f)

Health       [F.sub.(2,112)] = 7.07,     0.92
subscale            P = 0.01
[21] (f)

(a) Data are presented as means (SD).

(b) Significance assessed by ANCOVA with time of measurement
(T0, T1, and T2) entered as the within subjects independent variable.

(c) Observed power is the probability of finding a statistical
difference.

(d) Scores range from 0 to 90; lower scores indicate poorer
knowledge of nutritional properties of food.

(e) Scores range from 0 (or less) to 42; lower scores mean poorer
choices and a score of > 15 represents good food choices.

(f) Subscales of "Factors that Influence your Choice of Food
Questionnaire" [24]. Scores on both subscales range from 1 to 4;
1 = not important at all, 4 = very important.
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Title Annotation:Report/Rapport
Author:Miedema, Baukje; Bowes, Andrea; Hamilton, Ryan; Reading, Stacey
Publication:Canadian Journal of Dietetic Practice and Research
Geographic Code:1CANA
Date:Dec 1, 2016
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