Health Education Research Advance Access published online on May 4, 2007
Health Education Research, doi:10.1093/her/cym017
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Changes in cognitive measures associated with a lifestyle program for treated hypertensives: a randomized controlled trial (ADAPT)
School of Medicine and Pharmacology, Royal Perth Hospital Unit and West Australian Institute for Medical Research, University of Western Australia, Perth, WA 6000, Australia
Correspondence to: * Correspondence to: V. Burke. School of Medicine and Pharmacology, Royal Perth Hospital Unit, GPO Box X2213, Perth, WA 6847, Australia. E-mail: vburke{at}cyllene.uwa.edu.au
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Abstract |
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Cognitive changes are reported infrequently in programs targeting cardiovascular risk. We examined self-efficacy, behavioral barriers and health beliefs in a lifestyle program for drug-treated hypertensives that aimed to reduce blood pressure, antihypertensive drug needs and cardiovascular risk. In a randomized controlled trial, we compared usual care (controls) and a 4-month program focusing on weight loss, diet and exercise. Outcomes were assessed at baseline, 4 months and 1-year follow-up. Of 241 individuals randomized, 102/123 in the program and 90/118 of controls completed follow-up. In the program group, dietary barriers fell by 14% at 4 months (controls 2%, P = 0.025) and by 8% at follow-up (controls 3%, P = 0.010). Exercise barriers fell by 11% at 4 months (controls 3%, P = 0.020) and 17% (controls 4%, P = 0.002) at follow-up. Dietary self-efficacy improved by 3% at 4 months (controls –1%, P = 0.003) and by 2% at follow-up (controls –1%, P = 0.051). Exercise self-efficacy increased by 8% at 4 months (controls 3%, P < 0.001) and by 5% at follow-up (controls 3%, P = 0.130). Changes in cognitive variables predicted changes in health-related behaviors at 4 months and follow-up. A cognitively based lifestyle program in treated hypertensives is associated with improvements in cognitive measures in the shorter and longer term.
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Introduction |
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Lifestyle modification has been applied to prevent or treat high blood pressure and lower cardiovascular risk. Weight loss, increased dietary fish, reduced sodium intake, physical activity and moderation of alcohol intake can reduce blood pressure and cardiovascular risks [1]. Trials such as the Dietary Approaches to Stop Hypertension (DASH) clearly show the benefits of an eating pattern low in fat, high in fruit, vegetables, low-fat dairy products, whole-grain foods, lean meats, fish, poultry, nuts and low in sodium and sugar [2].
Recently, trials that aim to change behavior and reduce cardiovascular risk have been based on cognitive theory [3–5]. The PREMIER trial [5], a controlled trial of multifactorial lifestyle modification derived from Social Cognitive Theory, the behavioral self-management and the transtheoretical model in individuals with high normal blood pressure, found lower blood pressure and greater weight loss after 6 months with the program, but did not report cognitive outcomes. Other cognitively based programs have achieved improved quality of life in patients with angina [6], increased physical activity [7] and enhanced weight reduction [8]. However, few trials have reported changes in cognitive measures.
It is important to document responses to cognitively based programs, as focus shifts from explaining behavior to achieving behavior change [9, 10]. For example, many interventions have had a basis in the Theory of Planned Behavior [11], a model that is useful in identifying intentions [12], but systematic review suggests little effect on promoting behavior change [13]. More information is needed to allow assessment of the possible strengths and weaknesses of such approaches [9, 10, 12]. Development of effective interventions depends critically on identifying which cognitive and behavioral strategies are mediators of change in health-related behaviors.
The Partners’ trial [3, 4] used a cognitively based multifactorial 16-week health promotion program that focused on diet and physical activity, aiming to prevent adverse changes in health-related behaviors in couples beginning to live together. There were substantial improvements in blood pressure and blood lipids, associated with improvements in self-efficacy, more positive health beliefs and a decrease in the perceived importance of barriers to behavior change for diet and physical activity [3, 4].
Few other studies have linked changes in cognitive measures and changes in behavior. Initiation and maintenance of healthy behaviors related to smoking, weight reduction, alcohol drinking and physical activity are facilitated by programs that improve self-efficacy [14]. Psychosocial and motivational predictors of quitting smoking have been identified [15] and cognitive changes were recognized as possible mediators of adherence to advice for patients with end-stage renal failure [16].
Favorable responses in the Partners’ trial [3, 4] led us to modify the program for lifestyle modification in hypertensive individuals being treated with antihypertensive drugs. The Activity, Diet and Blood Pressure Trial (ADAPT) was a 16-week randomized controlled trial that aimed to reduce blood pressure, antihypertensive drug requirements and overall cardiovascular risk in overweight treated hypertensives by means of weight loss, adoption of a low-sodium DASH-type diet [2] with increased fish consumption, increased physical activity and reduction in alcohol intake. Follow-up to 1 year after completion of the program was incorporated to allow assessment of behavior change in the longer term.
The intervention was developed within the context of several established cognitive theories including the Health Belief Model [17], the Theory of Planned Behavior [14], which is an extension of the Theory of Reasoned Action [18], the Social Cognitive Theory [19, 20] and the Decisional Balance [21], which address issues of knowledge, self-efficacy and barriers to behavior change and maintenance.
Social Cognitive Theory [19, 20] includes the concept of self-efficacy, the extent to which individuals believe themselves capable of a particular behavior, leading to undertaking realistically challenging tasks and motivating progressive self-development of capabilities. The Health Belief Model focuses on the threat of illness, which considers both the individual's perceived susceptibility to an illness and its anticipated severity, and the behavioral response to that threat, which involves evaluation of the costs and benefits of engaging in behaviors likely to reduce the threat of the disease [17]. We considered this particularly appropriate in a group at increased risk of cardiovascular disease.
The Theory of Planned Behavior considers intention to engage in a specific behavior to be its primary determinant. Intention is affected by attitude to the behavior, social influence on its performance and perceived behavioral control [17], further influenced by an individual's beliefs. Provision of information is a usual component of interventions based on the Theory of Planned Behavior and, although knowledge is only weakly correlated with behavior change, it is recognized to be a predisposing factor.
Decisional Balance is closely related to Social Cognitive Theory and measures the relative importance to the individual of the pros (advantages or benefits) and the cons (disadvantages, barriers or costs) of behavior change [21]. Shifting Decisional Balance so that pros outweigh cons appears to be important in explaining why people make a commitment to change behavior [22, 23]. Aspects of the Health Belief Model, self-efficacy and Decisional Balance are relevant to overcoming perceived barriers to behavior change and were therefore considered appropriate for the ADAPT program.
In ADAPT, we aimed to examine changes in cognitive variables associated with the program and to determine whether such changes were predictive of modifications in health-related behaviors among overweight hypertensive volunteers. Cognitive measures were recorded at baseline, at the end of the 16-week intervention and at follow-up 1 year later.
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Participants
Two hundred and forty one participants were recruited by advertisement. Participants comprised men and women aged between 40 and 70 years who had been treated for at least 3 months with one or two antihypertensive medications. Volunteers were randomly allocated, using computer-generated random numbers, to either the program or usual care. Randomization and allocation were carried out by the statistician, who had no contact with volunteers entering the study. All participants provided written informed consent and the study was approved by The University of Western Australia Human Ethics Committee.
The health promotion program
Program group
The program consisted of a 4-month health promotion program, which comprised individual sessions, six interactive group workshops and five printed modules aimed at educating participants about improved lifestyle, predominantly nutrition and physical activity, with an emphasis on weight loss. The nutrition component encouraged a varied and nutritionally balanced diet recommended by the Australian National Dietary Guidelines [24] and was based on the DASH diet [2], with an additional recommendation of at least four fish meals per week. For physical activity, the aim was to encourage the accumulation of at least 30 min of moderate intensity physical activity on most days and to increase daily incidental activity [25]. The program aimed to achieve loss of 5–10% of baseline weight. Alcohol intake of not more than two standard drinks daily (one standard drink = 10 g alcohol) was recommended for both men and women, given the well-established pressor effects of alcohol [26], and is subsequently referred to as ‘safe drinking’. The five printed modules were distributed gradually over the 4 months at individual counseling sessions and group workshops.
Social support from a partner, relative or friend was implemented by encouraging their attendance during any of the contact sessions and involvement in grocery shopping, meal preparation and physical activity. Partners acted as motivators and collaborators during the program and follow-up when contact between researchers and participants was reduced.
Delivery of the program
Facilitators, modules, individual counseling sessions and group workshops encouraged self-directed change in behavior. Modules (Table I) consisted of contents and aims pages, newsletters, worksheets and leaflets developed in the research unit of the investigators, as well as existing published information [24, 27, 28]. Individual counseling sessions assessed risk factors such as cholesterol, blood pressure, overweight and diet. Interactive workshop sessions (Table II) for the program group consisted of demonstration, discussion and practice relating to correct techniques for exercise, as well as to processes of food purchasing and preparation, including reading nutritional labels. Providing answers to questions and feedback about progress was also included and sessions generally lasted 1.5 h with 15–25 people in any one group.
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Follow-up in the program group
The 12-month follow-up began at the end of the 4-month program and included regular telephone contact with facilitators, six individual sessions to measure weight and blood pressure and six group workshops, held every second week for the first month, monthly for the next 2 months and then once every 3 months. No additional information was provided during these workshops. Further individual counseling was offered as required but none of the participants used this option. A trimonthly newsletter was issued to each participant.
Usual care group
Individuals in the usual care group were, for ethical reasons, provided with information about lifestyle available from sources such as the National Heart Foundation of Australia [24]. Any changes to lifestyle were made without influence from the program facilitators. In an effort to maintain contact and retain members of the usual care group, four seminars on topics unrelated to the ADAPT program were conducted at 2, 7, 12 and 14 months after baseline.
All participants, whether in the program or usual care group, were offered carefully supervised withdrawal or reduction in dosage of antihypertensive drugs if blood pressure at the end of 16 weeks met defined criteria [29].
Measurements
All questionnaires were self-administered. Assessment included stages of change, self-efficacy, beliefs and barriers specific for physical activity, diet and alcohol drinking using several validated instruments with sound psychometric properties, employed previously in the Partners’ study [3, 4]. Measurements were obtained before randomization at baseline, at the end of the health promotion program (4 months) and at the end of the 1-year follow-up to measure longer term maintenance of changes.
Instruments
Perceived barriers to positive health behaviors were recorded using a four-point scale; these used 18 items for dietary behavior, 16 items for physical activity and 12 items for safe drinking [3, 4]. Scales used were developed to measure self-efficacy, response efficacy and intentions with respect to low-fat diets [30]. These were used unchanged in relation to diet. For physical activity and alcohol intake, the same format was used with questions specific to each behavior replacing those specific to diet.
Beliefs about the benefits of health behaviors were elicited using a six-point scale. Six items for each behavior addressed beliefs about associations between health behavior and blood pressure, cholesterol, risk of heart disease, longevity, general health and control of weight gain. For each item, a higher score indicated a stronger belief in the benefits of the behavior.
Coping mechanisms were explored using the revised Ways of Coping Checklist [31]. Social support was assessed as described by Thoits [32] and included total support and the dimensions of support from friends, relatives, spouses and co-workers.
Three-day food and drink diaries
Diets were assessed using 3-day food records (2 weekdays and 1 weekend day), administered with detailed instructions about completion. Participants recorded individual components of a meal including brand names, exact quantity or weight of each component in household measures and cooking and preparation methods. Daily nutrient intake was calculated using Foodworks (Xyris, Brisbane, Queensland, Australia).
Physical activity
Physical activity was assessed using an interview-administered 7-day recall of both leisure-time and occupational activity [33]. Individuals were asked to recall the average amount of sleep they attained each night during the 7 days. They were then asked to consider a chart outlining moderate, hard and very hard activities, specifying which activities they performed, the frequency of that activity during the 7 days and the amount of time spent involved in that activity. The nature of the intervention prevented blinding of the interviewers.
Alcohol
Amount and type of alcohol were recorded using 7-day retrospective diaries and converted to grams per day of ethanol.
Anthropometric measures
Height was measured at baseline using a fixed stadiometer to the nearest 0.5 cm with feet shoulder width apart. Weight was measured at baseline, 4 months and follow-up using calibrated electronic scales, to the nearest 0.01 kg after removal of shoes.
Short fat-intake questionnaire
Partners completed a short questionnaire related to fat intake [34] at baseline, 4 months and at follow-up. This questionnaire allows calculation of serves per week of fat-containing foods as well as providing an overall score as a measure of total fat intake. The questionnaire also included a previously validated item [35] about adding salt to prepared foods.
Data analysis
All data were analyzed on an intention-to-treat basis using the Statistical Package for the Social Sciences (SPSS Version 11.5, Chicago, IL, USA). Log transformation was used as needed for variables that were not normally distributed. Principal components factor analysis was used to identify dimensions of the coping scale. This demonstrated a four-factor solution. The factors were labeled ‘avoidance’ that included items such as ‘withdrew from the problem or gave up’; ‘consumption’ that included ‘drank alcohol to help me forget my problems’; ‘external’ that included ‘discussed my feelings with someone’ and ‘solution’ that included ‘made a list or action plan and followed it’.
Treatment effects were examined using general linear models adjusted for sex and baseline values. Categorical data were compared using chi-squared tests. Relationships between changes in cognitive variables and changes in health-related behaviors (change in intake of saturated fat, time spent in exercise and weight) were first examined in univariate linear regression. All variables for which P < 0.1 were then included for stepwise selection in multivariable models adjusted for sex. P < 0.05 was considered significant.
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Figure 1 shows the flow of participants through the study. The usual care and program group were well matched at baseline (Table III). The number of smokers (n = 5) was inadequate to provide sufficient power to examine changes in behavioral variables related to smoking.
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Stages of change
Stages of change for diet, physical activity and safe drinking with the proportions of usual care and program groups in the action or maintenance stages at baseline, 4 months and follow-up are shown in Fig. 2. Groups did not differ at baseline in the proportion in action or maintenance for these behaviors. For diet, the proportion was significantly greater in the program group at 4 months (P = 0.005) and at follow-up (P < 0.001). The pattern was similar for physical activity (P
0.001 at 4 months, P = 0.042 at follow-up). For safe drinking, the proportions in action or maintenance did not differ significantly at 4 months (P = 0.154) or at follow-up (P = 0.238).
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In the usual care group at 4 months, a greater proportion of men (90%) were in action or maintenance for diet compared with 73% of women (P = 0.030) but differences were not significant at baseline or follow-up (baseline 53 versus 42%, P = 0.258; follow-up 71 versus 63%, P = 0.344). There were no significant differences between men and women in the program group for diet action or maintenance (baseline 55 and 49%, P = 0.562; 4 months 94 and 92%, P = 0.646; follow-up 87 and 88%, P = 0.749). The proportion of men and women in action or maintenance for physical activity did not differ in the usual care group (baseline 47 versus 48%, P = 0.878; 4 months 55 versus 56%, P = 0.900; follow-up 59 versus 56%, P = 0.765) or with the program (baseline 44 versus 36%, P = 0.379; 89 versus 76% at 4 months, P = 0.064; 71 versus 67% at follow-up, P = 0.657). In the usual care group, 67% of men and 87% of women were in the action or maintenance stages for safe drinking at baseline (P = 0.016), 67 and 91%, respectively, at 4 months (P = 0.003) and 65 and 87% at follow-up (P = 0.008). With the program, proportions were 64% for men and 79% for women at baseline (P = 0.077), 80 and 94% at 4 months (P = 0.035) and 80 and 90% at follow-up (P = 0.123).
Barriers to behavior change
At baseline, the barriers of greatest perceived importance for physical activity were being too busy (33%), being too tired (35%), lacking willpower (33%), having too little time to exercise (27%), having difficulty in sticking to a routine (28%), being too lazy to exercise (26%) and having poor sporting skills (23%). Less highly rated barriers were not enjoying exercise (15%), having friends (13%) or family (13%) who do not exercise, lacking facilities for exercise (12%), being unaware of how much exercise is needed (11%), lacking family support (6%), being unaware of the benefits of exercise (3%) and lacking transport (2%).
For diet, the barriers of greatest perceived importance at baseline were trouble in sticking to a healthy diet (32%), feeling hungry (32%), liking ‘junk food’ (24%), having a family that refuses to eat a healthy diet (16%) and being too busy (16%). Barriers of less perceived importance were lack of knowledge about the energy (15%), fat (14%) or fiber (14%) content of foods and lack of choice at work (14%). Barriers that were considered important by <10% of the participants were disliking the taste of healthy foods (9%), having children fussy about foods (7%), lack of family support (6%), lack of control over food at home (5%), not knowing what foods to eat (5%), not knowing the benefits of a healthy diet (4%), lack of choice in shops (4%), the expense of healthy foods (3%) and lack of cooking facilities (1%).
Barriers to safe drinking of greatest perceived importance related to social situations were socializing (26%), celebrations (23%), parties (23%) and eating in restaurants (23%). Other barriers included wanting to relax (18%), friends offering alcoholic drinks (15%), finding alcohol moderation difficult to maintain (14%), being unaware of benefits of limiting alcohol (13%), feeling depressed (13%), disliking non-alcoholic drinks (13%), drinking alcohol when getting to know someone (11%), seeing no benefits from alcohol moderation (11%), lacking family support (9%), limiting social life (8%) and being unaware of safe drinking limits (7%).
The total rating for perceived barriers relating to physical activity and diet showed a greater decrease in the program group both at the end of the program and at follow-up (Fig. 3a). Between-group differences in barrier scores were statistically significant at both time points for physical activity (P = 0.038 and P = 0.005) and for diet at 4 months (P = 0.037) but not at follow-up (P = 0.121). The change in perceived barriers to safe drinking did not differ significantly between groups at 4 months (P = 0.923) or at follow-up (P = 0.436).
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The only statistically significant difference between men and women in change for perceived importance of behavioral barriers was seen for dietary barriers in the control group at follow-up (men +1.2, SEM 1.3; women –2.3, SEM 0.7; P = 0.013)
Beliefs about health benefits
Scores for beliefs about the benefits of a healthy diet did not differ significantly between groups at baseline or at 4 months (P = 0.384) but were significantly greater in the program group than usual care at follow-up (P = 0.028) (Fig. 3b). Findings were similar for beliefs about the benefits of physical activity (P = 0.167, P = 0.067). Scores for beliefs about the benefits of safe drinking did not differ between groups at baseline, 4 months (P = 0.568) or at follow-up (P = 0.086). Changes in ranking of health beliefs are shown in Fig. 3b.
There were significant differences between men and women in change in scores for beliefs about the benefits of moderating alcohol intake in the control group at 4 months (men –0.5, SEM 0.2; women +1.0, SEM 0.4; P = 0.013) and in the program group at follow-up (men 0.2, SEM 0.4; women 2.1, SEM 0.6; P = 0.012). Changes in dietary and physical activity beliefs did not differ between men and women at 4 months or at follow-up in either treatment group.
Self-efficacy
At 4 months, self-efficacy for diet was significantly higher in the program group (11.2, SEM 0.1; usual care 10.8, SEM 0.1; P = 0.007) but at follow-up the difference was not statistically significant (program 11.2, SEM 0.1; usual care 10.7, SEM 0.1; P = 0.087). Similarly, self-efficacy for physical activity was greater in the program group at 4 months (11.1, SEM 0.1 versus 10.6, SEM 0.2; P = 0.001) but the difference between groups was not statistically significant at follow-up (program 11.0, SEM 0.1; usual care 10.6, SEM 0.2; P = 0.123). Self-efficacy scores for safe drinking behavior did not differ between groups at 4 months (program 10.6, SEM 0.2; usual care 10.6, SEM 0.2; P = 0.359) or at follow-up (program 10.5, SEM 0.2; usual care 10.7, SEM 0.2; P = 0.266). Self-efficacy did not differ significantly between men and women for any of these health-related behaviors. Changes in self-efficacy are shown in Fig. 3c.
Coping strategies
At baseline external coping strategies were ranked most highly, with a mean of 14.7 (SEM 0.3) with usual care and 15.6 (SEM 0.2) with the program group (P = 0.020). Other strategies did not differ significantly between groups. Respective means for seeking solutions were 13.4 (SEM 0.3) with usual care and 13.9 (SEM 0.3) with the program, 7.8 (SEM 0.1) and 8.1 (SEM 0.2) for consumption and 6.0 (SEM 0.2) and 6.3 (SEM 0.2) for avoidance. There was a decrease in scores for external coping strategies significantly greater in the program group at 4 months (P = 0.008) and at follow-up (P = 0.014). Scores for consumption strategies also showed a greater fall in the program group at 4 months (P = 0.031), but not at follow-up (P = 0.129). Other coping strategies showed no between-group differences at 4 months or at follow-up (Fig. 4).
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At baseline, scores for seeking solutions were higher in men (P < 0.001), with a mean of 14.4 (SEM 0.3) than in women (mean 13.0, SEM 0.3). No other differences were seen between men and women for coping scores or for change in these scores.
Social support
The ranking of support from relatives increased significantly (P = 0.037) in the program group at follow-up (Fig. 5). There were no other statistically significant changes in perceived support scales at 4 months or at follow-up.
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Changes in diet among partners
In the usual care group, 63 partners completed the short fat-intake questionnaire at baseline, 49 at 4 months and 38 at follow-up. In the program group corresponding numbers were 71, 59 and 52. At 4 months total fat score fell by 1.2 (SEM 0.5) in partners from the program group and increased by 0.3 (SEM 0.4) with usual care (P = 0.031). At follow-up, there was no significant difference between groups with a fall of 0.3 (SEM 0.4) with the program and an increase of 0.3 (SEM 0.5) with usual care (P = 0.531).
Increased fish and reduced sodium intake were emphasized in the ADAPT program. At baseline, 71% of partners in the program group ate fish at least weekly compared with 49% in the usual care group (P = 0.035). The proportion increased in both groups at 4 months (92 versus 75%, P = 0.038) but a significant difference did not persist to follow-up (88 versus 77%, P = 0.223). At baseline, 47% of partners from the program group never added salt to prepared food compared with 40% of those from the usual care group (P = 0.408). At 4 months, the proportion had changed to 61% of the program group and 42% with usual care (P = 0.039). At follow-up, the respective proportions were 59 and 48% (P = 0.453).
Associations between health-related behaviors and cognitive variables
At 4 months (Table IV), increased dietary self-efficacy and increased support from relatives predicted a decrease in saturated fat intake. Only dietary self-efficacy was predictive of change in saturated fat intake in a stepwise model adjusted for sex. Beliefs about physical activity and self-efficacy for physical activity were positive predictors of change in time spent in physical activity and remained independent predictors in a stepwise model. Change in weight was predicted positively by change in diet barriers and exercise barriers and negatively by change in exercise beliefs, safe drinking beliefs, self-efficacy for safe drinking and support from relatives. Safe drinking beliefs and safe drinking self-efficacy remained independent predictors in stepwise regression. Change in alcohol intake was predicted positively by change in barriers to safe drinking and negatively by support from relatives. Change in barriers to safe drinking was the only predictor in the stepwise model.
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At follow-up (Table V), change in dietary self-efficacy, change in support from relatives and total social support score predicted change in saturated fat intake. In the stepwise model, only support from relatives was an independent predictor. Change in time spent in physical activity was positively predicted by change in self-efficacy for physical activity and by support from relatives; these variables remained independent predictors in the stepwise model. Weight change was predicted negatively by dietary self-efficacy, beliefs about physical activity, self-efficacy for safe drinking and support from relatives; change in barriers to physical activity was a positive predictor. In the stepwise model, change in barriers to physical activity and beliefs about physical activity were independent predictors. Change in alcohol intake was predicted only by change in perceived barriers to safe drinking.
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Coping styles at baseline or change in these variables were not significant predictors of change in health behaviors.
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Discussion |
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This study has shown cognitive changes and modification of behaviors associated with a lifestyle program designed to promote weight loss, increase physical activity, improve diet and moderate alcohol intake in treated hypertensives. While various health behaviors associated with programs for lifestyle modification have been reported [36], few studies have examined the changes in these variables in relation to behavior change [12, 13, 37].
Our findings confirm the suggestion that improvements in health behaviors are associated with improvements in self-efficacy [9] and are consistent with the outcome of a similar program that targeted young couples [3, 4]. Previous trials have shown a weak relationship between health beliefs and behavior change [38, 39]. Although in the present study changes in health belief scores did not differ significantly between treatment groups, changes in exercise beliefs predicted change in physical activity at 4 months and weight change at follow-up while change in beliefs about safe drinking predicted weight change at follow-up. Interventions based on the Theory of Planned Behavior may therefore be relevant to behavior change, although systematic review indicates that these effects are weak [16].
Change in scores for barriers to dietary behavior was a significant predictor of weight change at both 4 months and at follow-up. Ranking of perceived barriers to change relating to diet and physical activity decreased significantly in the program group relative to usual care and for physical activity differences were sustained to follow-up, similar to the results of the partners’ study [3, 4]. We found that knowledge of the barriers perceived as most important was useful in developing strategies designed to assist individuals in changing behavior.
ADAPT focused on weight reduction, diet and physical activity but included information about moderation of alcohol intake. However, no significant between-group differences were seen in cognitive variables related to alcohol intake. In regression models, a decrease in alcohol intake was predicted by a decrease in the perceived importance of barriers to safe drinking at 4 months and follow-up and by social support from relatives at 4 months. However, only the change in barriers entered the stepwise model. Safe drinking beliefs and self-efficacy predicted weight loss in univariate models at 4 months and were the only variables to enter the stepwise model with change in weight as the dependent variable. Self-efficacy for safe drinking was also predictive of weight loss at follow-up but did not enter the stepwise model. These associations between variables related to alcohol intake and weight change are consistent with the role of alcohol in contributing to obesity [40].
There were some differences between men and women for ratings of cognitive variables in ADAPT and it may be that men and women have different needs for intervention strategies. Higher ratings for cognitive and behavioral variables have been reported in women, particularly in relation to diet [41], possibly because of their greater interest in nutrition and lifestyle [42, 43]. Ratings may also differ between men and women with respect to specific behaviors. Milligan et al. [44] reported that women had greater scores for self-efficacy related to diet and moderation of alcohol consumption, while men had higher self-efficacy scores for physical activity.
Perceived social support from relatives increased significantly in the program group. Greater support from relatives significantly predicted reduction in saturated fat intake, weight loss and decreased alcohol consumption at 4 months. At follow-up, support from relatives predicted lower saturated fat intake, greater time spent in physical activity and weight loss. In focus groups, participants in the program group appreciated the contribution of their families in providing encouragement as well as practical support by making sure that foods appropriate for their dietary guidelines were available at family gatherings. The significant associations between behaviors and support from relatives at follow-up are consistent with social support being useful in maintenance of behavior change [45]. Support from co-workers was not ranked highly by participants but only 63% of the usual care group and 64% in the program were in full- or part-time employment.
The individual who provides support may benefit from their participation either through changes in their own behavior or through greater feelings of self-worth [46]. In the present study, information about behavior change in partners was limited to a simple dietary frequency questionnaire. However, at 4 months this showed reduction in fat consumption, greater intake of fish and a decrease in the habit of adding salt to prepared food. These changes in dietary behavior were not maintained to follow-up.
Maintenance of weight loss is considered more likely in individuals with problem-solving coping styles [47, 48]. An external coping style, that is, seeking assistance, showed a significant decrease in the program group at the end of the program and at follow-up. There was also a fall in consumption strategies in the program group at 4 months, but not at follow-up. However, changes in health-related behaviors were not significantly associated with coping styles at baseline or with changes in these measures.
There are limitations to extrapolating our findings to the wider community. The ‘healthy volunteer’ phenomenon is well recognized [49]. Participants had already attempted to modify their lifestyle; baseline data showed that, even in the usual care group, fat consumption was within the national guideline of providing <30% energy. The Hawthorne effect, whereby participation in a study, even in as a control, results in improved outcomes [50], is also likely to influence results. Participants in ADAPT, both in the usual care and program groups, were offered carefully supervised withdrawal of antihypertensive drugs if their blood pressure at the end of 4 months reached criteria considered safe for discontinuation. This incentive was recognized in the TONE study, where weight loss and sodium restriction were used in patients with hypertension, to be a strong motivation for lifestyle modification [51]. Furthermore, at-risk groups are recognized to be more likely to change health-related behaviors [52]. Interviewers who elicited information about physical activity were not blinded to treatment allocation and there is, therefore, the possibility of bias in these data.
In summary, we have shown that a multifactorial program for lifestyle modification in hypertension, based on cognitive models, is associated with changes in cognitive measures as well as in health-related behaviors. Cognitive changes significantly predict behavior change in the shorter and longer term and may be mediators of change. The strategies used in ADAPT are likely to be applicable to achieving behavior change in other at-risk groups.
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Conflict of interest statement |
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None declared.
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Acknowledgements |
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The study was funded by the Australian National Health and Medical Research Council and the Australian Fisheries Research and Development Corporation. We thank Lawrence J. Appel for advice in establishing a protocol for drug withdrawal, Lyn McCahon for expert technical help and Jackie Ritchie for her contribution to data collection and organization of the study. Mr Richard Stevens of the West Australian Fishing Industries Council Inc. provided helpful advice. We are grateful to Catalano Seafoods, Global Seafoods Distributors Australia Pty Ltd and Austral Fisheries Pty Ltd, all of Perth Western Australia, for donations of fish.
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References |
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