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Study Overview
Objective. To determine the impact of providing genetically tailored and population-based lifestyle advice for weight management on key constructs of the Theory of Planned Behavior (TPB), a widely accepted theory used to help predict human lifestyle-related behaviors.
Design. Pragmatic, cluster, randomized controlled trial.
Settings and participants. This study took place at the East Elgin Family Health Team, a primary care clinic in Aylmer, Ontario, Canada. Recruitment occurred between April 2017 and September 2018, with staggered intervention cohorts occurring from May 2017 to September 2019. Participants enrolled in a weight management program at the clinic were invited to participate in the study if they met the following inclusion criteria: body mass index (BMI) ≥25 kg/m2, >18 years of age, English-speaking, willing to undergo genetic testing, having access to a computer with internet at least 1 day per week, and not seeing another health care provider for weight loss advice outside of the study. Exclusion criteria included pregnancy and lactation. All participants provided written informed consent.
Interventions. At baseline, weight management program cohorts (average cohort size was 14 participants) were randomized (1:1) to receive either the standard population-based intervention (Group Lifestyle Balance, or GLB) or a modified GLB intervention, which included the provision of lifestyle genomics (LGx) information and advice (GLB+LGx). Both interventions aimed to assist participants with weight management and healthy lifestyle change, with particular focus on nutrition and physical activity (PA). Interventions were 12 months long, consisting of 23 group-based sessions and 3 one-on-one sessions with a registered dietitian after 3, 6, and 12 months (all sessions were face-to-face). To improve intervention adherence, participants were given reminder calls for their one-on-one appointments and for the start of their program. A sample size was calculated based on the primary outcome indicating that a total of 74 participants were needed (n = 37 per group) for this trial. By September 2019, this sample size was exceeded with 10 randomized groups (n = 140).
The 5 randomized standard GLB groups followed the established GLB program curriculum comprising population-based information and advice while focusing on following a calorie-controlled, moderate-fat (25% of calories) nutrition plan with at least 150 minutes of weekly moderate-intensity PA. Participants were also provided with a 1-page summary report of their nutrition and PA guidelines at the first group meeting outlining population-based targets, including acceptable macronutrient distribution ranges for protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, sodium, calories, snacking, and PA.
The 5 randomized modified GLB+LGx groups followed a modified GLB program curriculum in which participants were given genetic-based information and advice, which differed from the advice given to the standard GLB group, while focusing on following a calorie-controlled nutrition plan. The nutrition and PA targets were personalized based on their individual genetic variation. For example, participants with the AA variant of FTO (rs9939609) were advised to engage in at least 30 to 60 minutes of PA daily 6 days per week, with muscle-strengthening activities at least 2 days per week, rather than receiving the standard population-based advice to aim for 150 minutes weekly of PA with at least 2 days per week of muscle-strengthening activity. Participants were also provided with a 1-page summary report of their nutrition and PA guidelines at the first group meeting, which outlined genetic-based information and advice related to protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, sodium, calories, snacking, and PA.
Measures and analysis. Change in the TPB components (attitudes, subjective norms and perceived behavioral control) were measured via a TPB questionnaire at 5 time points: baseline (2-week run-in period), immediately after the first group session (where participants received a summary report of either population-based or genetic-based recommendations depending on group assignment), and after 3-, 6- and 12-month follow-ups. Attitudes, subjective norms, and perceived behavioral control were measured on a Likert scale from 1 through 7. Self-reported measures of actual behavioral control (including annual household income, perceptions about events arising in one’s day-to-day life that suddenly take up one’s free time, perceptions about the frequency of feeling ill or tired, and highest achieved level of education) were collected via survey questions and assessed on a Likert scale of 1 through 7. Stage of change was also measured, based on the Transtheoretical Model, using a Likert scale of 1 through 6.
Linear mixed models were used to conduct within- and between-group analyses using SPSS version 26.0, while controlling for measures of actual behavioral control. All analyses were intention-to-treat by originally assigned groups, with mean value imputation conducted for missing data. A Bonferroni correction for multiple testing was used. For all statistical analyses, the level of significance was set at P < 0.05 and trending towards significance at P = 0.05–0.06.
Main results. Participants consisted of primarily middle-age, middle-income, Caucasian females. Baseline attitudes towards the effectiveness of nutrition and PA for weight management were generally positive, and participants perceived that undergoing genetic testing would assist with weight management. Participants had overall neutral subjective norms related to friends and family consuming a healthy diet and engaging in PA, but perceived that their friends, family, and health care team (HCT) believed it was important for them to achieve their nutrition and PA recommendations. Participants overall also perceived that their HCT believed genetic testing could assist with weight management. Baseline measures of perceived behavioral control were overall neutral, with baseline stage of change between “motivation” and “action” (short-term; <3 months).
In within-group analyses, significant improvements (P < 0.05) in attitudes towards the effectiveness of nutrition and PA recommendations for weight management, subjective norms related to both friends and family consuming a healthy diet, and perceived behavioral control in changing PA/dietary intake and managing weight tended to be short-term in the GLB group and long-term for the GLB+LGx group. In all cases of between-group differences for changes in TPB components, the GLB group exhibited reductions in scores, whereas the GLB+LGx group exhibited increases or improvements. Between-group differences (short-term and long-term) in several measures of subjective norms were observed. For example, after 3 months, significant between-group differences were observed in changes in perception that friends believed LGx would help with weight management (P = 0.024). After 12 months, between-group differences trending towards significance were also observed in changes in perception that family members believed genetic testing would help with weight management (P = 0.05). Significant between-group differences and differences trending towards significance were also observed at 12 months for changes in perception that family believed it was important for the participant to achieve the PA recommendations (P = 0.049) and nutrition recommendations (P = 0.05). Between-group differences trending towards significance were also observed at 3 months in attitudes towards the effectiveness of LGx for weight management (P = 0.06). There were no significant between-group differences observed in changes in perceived behavioral control.
Conclusion. Results from this study support the hypothesis that the TPB can help provide a theoretical explanation for why genetically tailored lifestyle information and advice can lead to improvements in lifestyle behavior change.
Commentary
Because health behaviors are critical in areas such as prevention, treatment, and rehabilitation, it is important to describe and understand what drives these behaviors.1 Theories are important tools in this effort as they aim to explain and predict health behavior and are used in the design and evaluation of interventions.1 The TPB is one of the most widely accepted behavior change theories and posits that attitudes, subjective norms (or social pressures and behaviors), and perceived behavioral control are significant predictors of an individual’s intention to engage in behaviors.2 TPB has been highlighted in the literature as a validated theory for predicting nutrition and PA intentions and resulting behaviors.3,4
Motivating lifestyle behavior change in clinical practice can be challenging, but some studies have demonstrated how providing genetic information and advice (or lifestyle genomics) can help motivate changes in nutrition and PA among patients.5-7 Because this has yet to be explained using the TPB, this study is an important contribution to the literature as it aimed to determine the impact of providing genetically tailored and population-based lifestyle advice for weight management on key constructs of the TPB. Briefly, results from within-group analyses in this study demonstrated that the provision of genetically tailored lifestyle information and advice (via the GLB+LGx intervention) tended to impact antecedents of behavior change, more so over the long-term, while population-based advice (via the standard GLB intervention) tended to impact antecedents of behavior change over the short-term (eg, attitudes towards dietary fat intake, perceptions that friends and family consume a healthy diet, and perceptions about the impact of genetic-based advice for weight management). In addition, between-group differences in subjective norms observed at 12 months suggested that social pressures and norms may be influencing long-term changes in lifestyle habits.
While key strengths of this study include its pragmatic cluster randomized controlled trial design, 12-month intervention duration, and intent-to-treat analyses, there are some study limitations, which are acknowledged by the authors. Generalizability is limited to the demographic characteristics of the study population (ie, middle-aged, middle-income, Caucasian females enrolled in a lifestyle change weight management program). Thus, replication of the study is needed in more diverse study populations and with health-related outcomes beyond weight management. In addition, as the authors indicate, future research should ensure the inclusion of theory-based questionnaires in genetic-based intervention studies assessing lifestyle behavior change to elucidate theory-based mechanisms of change.
Applications for Clinical Practice
Population-based research has consistently indicated that nutrition interventions typically impact short-term dietary changes. Confronting the challenge of long-term adherence to nutrition and PA recommendations requires an understanding of factors impacting long-term motivation and behavior change. With increased attention on and research into genetically tailored lifestyle advice (or lifestyle genomics), it is important for clinical practitioners to be familiar with the evidence supporting these approaches. In addition, this research highlights the need to consider individual factors (attitudes, subjective norms, and perceived behavioral control) that may predict successful change in lifestyle habits when providing nutrition and PA recommendations, whether population-based or genetically tailored.
—Katrina F. Mateo, PhD, MPH
1. Lippke S, Ziegelmann JP. Theory-based health behavior change: Developing, testing, and applying theories for evidence-based interventions. Appl Psychol. 2008;57:698-716.
2. Ajzen I. The Theory of planned behaviour: reactions and reflections. Psychol Health. 2011;26:1113-1127.
3. McDermott MS, Oliver M, Simnadis T, et al. The Theory of Planned Behaviour and dietary patterns: A systematic review and meta-analysis. Prev Med (Baltim). 2015;81:150-156.
4. McEachan RRC, Conner M, Taylor NJ, Lawton RJ. Prospective prediction of health-related behaviours with the theory of planned behaviour: A meta-analysis. Health Psychol Rev. 2011;5:97-144.
5. Hietaranta-Luoma H-L, Tahvonen R, Iso-Touru T, et al A. An intervention study of individual, APOE genotype-based dietary and physical-activity advice: impact on health behavior. J Nutrigenet Nutrigenomics. 2014;7:161-174.
6. Nielsen DE, El-Sohemy A. Disclosure of genetic information and change in dietary intake: a randomized controlled trial. DeAngelis MM, ed. PLoS One. 2014;9(11):e112665.
7. Egglestone C, Morris A, O’Brien A. Effect of direct‐to‐consumer genetic tests on health behaviour and anxiety: a survey of consumers and potential consumers. J Genet Couns. 2013;22:565-575.
Study Overview
Objective. To determine the impact of providing genetically tailored and population-based lifestyle advice for weight management on key constructs of the Theory of Planned Behavior (TPB), a widely accepted theory used to help predict human lifestyle-related behaviors.
Design. Pragmatic, cluster, randomized controlled trial.
Settings and participants. This study took place at the East Elgin Family Health Team, a primary care clinic in Aylmer, Ontario, Canada. Recruitment occurred between April 2017 and September 2018, with staggered intervention cohorts occurring from May 2017 to September 2019. Participants enrolled in a weight management program at the clinic were invited to participate in the study if they met the following inclusion criteria: body mass index (BMI) ≥25 kg/m2, >18 years of age, English-speaking, willing to undergo genetic testing, having access to a computer with internet at least 1 day per week, and not seeing another health care provider for weight loss advice outside of the study. Exclusion criteria included pregnancy and lactation. All participants provided written informed consent.
Interventions. At baseline, weight management program cohorts (average cohort size was 14 participants) were randomized (1:1) to receive either the standard population-based intervention (Group Lifestyle Balance, or GLB) or a modified GLB intervention, which included the provision of lifestyle genomics (LGx) information and advice (GLB+LGx). Both interventions aimed to assist participants with weight management and healthy lifestyle change, with particular focus on nutrition and physical activity (PA). Interventions were 12 months long, consisting of 23 group-based sessions and 3 one-on-one sessions with a registered dietitian after 3, 6, and 12 months (all sessions were face-to-face). To improve intervention adherence, participants were given reminder calls for their one-on-one appointments and for the start of their program. A sample size was calculated based on the primary outcome indicating that a total of 74 participants were needed (n = 37 per group) for this trial. By September 2019, this sample size was exceeded with 10 randomized groups (n = 140).
The 5 randomized standard GLB groups followed the established GLB program curriculum comprising population-based information and advice while focusing on following a calorie-controlled, moderate-fat (25% of calories) nutrition plan with at least 150 minutes of weekly moderate-intensity PA. Participants were also provided with a 1-page summary report of their nutrition and PA guidelines at the first group meeting outlining population-based targets, including acceptable macronutrient distribution ranges for protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, sodium, calories, snacking, and PA.
The 5 randomized modified GLB+LGx groups followed a modified GLB program curriculum in which participants were given genetic-based information and advice, which differed from the advice given to the standard GLB group, while focusing on following a calorie-controlled nutrition plan. The nutrition and PA targets were personalized based on their individual genetic variation. For example, participants with the AA variant of FTO (rs9939609) were advised to engage in at least 30 to 60 minutes of PA daily 6 days per week, with muscle-strengthening activities at least 2 days per week, rather than receiving the standard population-based advice to aim for 150 minutes weekly of PA with at least 2 days per week of muscle-strengthening activity. Participants were also provided with a 1-page summary report of their nutrition and PA guidelines at the first group meeting, which outlined genetic-based information and advice related to protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, sodium, calories, snacking, and PA.
Measures and analysis. Change in the TPB components (attitudes, subjective norms and perceived behavioral control) were measured via a TPB questionnaire at 5 time points: baseline (2-week run-in period), immediately after the first group session (where participants received a summary report of either population-based or genetic-based recommendations depending on group assignment), and after 3-, 6- and 12-month follow-ups. Attitudes, subjective norms, and perceived behavioral control were measured on a Likert scale from 1 through 7. Self-reported measures of actual behavioral control (including annual household income, perceptions about events arising in one’s day-to-day life that suddenly take up one’s free time, perceptions about the frequency of feeling ill or tired, and highest achieved level of education) were collected via survey questions and assessed on a Likert scale of 1 through 7. Stage of change was also measured, based on the Transtheoretical Model, using a Likert scale of 1 through 6.
Linear mixed models were used to conduct within- and between-group analyses using SPSS version 26.0, while controlling for measures of actual behavioral control. All analyses were intention-to-treat by originally assigned groups, with mean value imputation conducted for missing data. A Bonferroni correction for multiple testing was used. For all statistical analyses, the level of significance was set at P < 0.05 and trending towards significance at P = 0.05–0.06.
Main results. Participants consisted of primarily middle-age, middle-income, Caucasian females. Baseline attitudes towards the effectiveness of nutrition and PA for weight management were generally positive, and participants perceived that undergoing genetic testing would assist with weight management. Participants had overall neutral subjective norms related to friends and family consuming a healthy diet and engaging in PA, but perceived that their friends, family, and health care team (HCT) believed it was important for them to achieve their nutrition and PA recommendations. Participants overall also perceived that their HCT believed genetic testing could assist with weight management. Baseline measures of perceived behavioral control were overall neutral, with baseline stage of change between “motivation” and “action” (short-term; <3 months).
In within-group analyses, significant improvements (P < 0.05) in attitudes towards the effectiveness of nutrition and PA recommendations for weight management, subjective norms related to both friends and family consuming a healthy diet, and perceived behavioral control in changing PA/dietary intake and managing weight tended to be short-term in the GLB group and long-term for the GLB+LGx group. In all cases of between-group differences for changes in TPB components, the GLB group exhibited reductions in scores, whereas the GLB+LGx group exhibited increases or improvements. Between-group differences (short-term and long-term) in several measures of subjective norms were observed. For example, after 3 months, significant between-group differences were observed in changes in perception that friends believed LGx would help with weight management (P = 0.024). After 12 months, between-group differences trending towards significance were also observed in changes in perception that family members believed genetic testing would help with weight management (P = 0.05). Significant between-group differences and differences trending towards significance were also observed at 12 months for changes in perception that family believed it was important for the participant to achieve the PA recommendations (P = 0.049) and nutrition recommendations (P = 0.05). Between-group differences trending towards significance were also observed at 3 months in attitudes towards the effectiveness of LGx for weight management (P = 0.06). There were no significant between-group differences observed in changes in perceived behavioral control.
Conclusion. Results from this study support the hypothesis that the TPB can help provide a theoretical explanation for why genetically tailored lifestyle information and advice can lead to improvements in lifestyle behavior change.
Commentary
Because health behaviors are critical in areas such as prevention, treatment, and rehabilitation, it is important to describe and understand what drives these behaviors.1 Theories are important tools in this effort as they aim to explain and predict health behavior and are used in the design and evaluation of interventions.1 The TPB is one of the most widely accepted behavior change theories and posits that attitudes, subjective norms (or social pressures and behaviors), and perceived behavioral control are significant predictors of an individual’s intention to engage in behaviors.2 TPB has been highlighted in the literature as a validated theory for predicting nutrition and PA intentions and resulting behaviors.3,4
Motivating lifestyle behavior change in clinical practice can be challenging, but some studies have demonstrated how providing genetic information and advice (or lifestyle genomics) can help motivate changes in nutrition and PA among patients.5-7 Because this has yet to be explained using the TPB, this study is an important contribution to the literature as it aimed to determine the impact of providing genetically tailored and population-based lifestyle advice for weight management on key constructs of the TPB. Briefly, results from within-group analyses in this study demonstrated that the provision of genetically tailored lifestyle information and advice (via the GLB+LGx intervention) tended to impact antecedents of behavior change, more so over the long-term, while population-based advice (via the standard GLB intervention) tended to impact antecedents of behavior change over the short-term (eg, attitudes towards dietary fat intake, perceptions that friends and family consume a healthy diet, and perceptions about the impact of genetic-based advice for weight management). In addition, between-group differences in subjective norms observed at 12 months suggested that social pressures and norms may be influencing long-term changes in lifestyle habits.
While key strengths of this study include its pragmatic cluster randomized controlled trial design, 12-month intervention duration, and intent-to-treat analyses, there are some study limitations, which are acknowledged by the authors. Generalizability is limited to the demographic characteristics of the study population (ie, middle-aged, middle-income, Caucasian females enrolled in a lifestyle change weight management program). Thus, replication of the study is needed in more diverse study populations and with health-related outcomes beyond weight management. In addition, as the authors indicate, future research should ensure the inclusion of theory-based questionnaires in genetic-based intervention studies assessing lifestyle behavior change to elucidate theory-based mechanisms of change.
Applications for Clinical Practice
Population-based research has consistently indicated that nutrition interventions typically impact short-term dietary changes. Confronting the challenge of long-term adherence to nutrition and PA recommendations requires an understanding of factors impacting long-term motivation and behavior change. With increased attention on and research into genetically tailored lifestyle advice (or lifestyle genomics), it is important for clinical practitioners to be familiar with the evidence supporting these approaches. In addition, this research highlights the need to consider individual factors (attitudes, subjective norms, and perceived behavioral control) that may predict successful change in lifestyle habits when providing nutrition and PA recommendations, whether population-based or genetically tailored.
—Katrina F. Mateo, PhD, MPH
Study Overview
Objective. To determine the impact of providing genetically tailored and population-based lifestyle advice for weight management on key constructs of the Theory of Planned Behavior (TPB), a widely accepted theory used to help predict human lifestyle-related behaviors.
Design. Pragmatic, cluster, randomized controlled trial.
Settings and participants. This study took place at the East Elgin Family Health Team, a primary care clinic in Aylmer, Ontario, Canada. Recruitment occurred between April 2017 and September 2018, with staggered intervention cohorts occurring from May 2017 to September 2019. Participants enrolled in a weight management program at the clinic were invited to participate in the study if they met the following inclusion criteria: body mass index (BMI) ≥25 kg/m2, >18 years of age, English-speaking, willing to undergo genetic testing, having access to a computer with internet at least 1 day per week, and not seeing another health care provider for weight loss advice outside of the study. Exclusion criteria included pregnancy and lactation. All participants provided written informed consent.
Interventions. At baseline, weight management program cohorts (average cohort size was 14 participants) were randomized (1:1) to receive either the standard population-based intervention (Group Lifestyle Balance, or GLB) or a modified GLB intervention, which included the provision of lifestyle genomics (LGx) information and advice (GLB+LGx). Both interventions aimed to assist participants with weight management and healthy lifestyle change, with particular focus on nutrition and physical activity (PA). Interventions were 12 months long, consisting of 23 group-based sessions and 3 one-on-one sessions with a registered dietitian after 3, 6, and 12 months (all sessions were face-to-face). To improve intervention adherence, participants were given reminder calls for their one-on-one appointments and for the start of their program. A sample size was calculated based on the primary outcome indicating that a total of 74 participants were needed (n = 37 per group) for this trial. By September 2019, this sample size was exceeded with 10 randomized groups (n = 140).
The 5 randomized standard GLB groups followed the established GLB program curriculum comprising population-based information and advice while focusing on following a calorie-controlled, moderate-fat (25% of calories) nutrition plan with at least 150 minutes of weekly moderate-intensity PA. Participants were also provided with a 1-page summary report of their nutrition and PA guidelines at the first group meeting outlining population-based targets, including acceptable macronutrient distribution ranges for protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, sodium, calories, snacking, and PA.
The 5 randomized modified GLB+LGx groups followed a modified GLB program curriculum in which participants were given genetic-based information and advice, which differed from the advice given to the standard GLB group, while focusing on following a calorie-controlled nutrition plan. The nutrition and PA targets were personalized based on their individual genetic variation. For example, participants with the AA variant of FTO (rs9939609) were advised to engage in at least 30 to 60 minutes of PA daily 6 days per week, with muscle-strengthening activities at least 2 days per week, rather than receiving the standard population-based advice to aim for 150 minutes weekly of PA with at least 2 days per week of muscle-strengthening activity. Participants were also provided with a 1-page summary report of their nutrition and PA guidelines at the first group meeting, which outlined genetic-based information and advice related to protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, sodium, calories, snacking, and PA.
Measures and analysis. Change in the TPB components (attitudes, subjective norms and perceived behavioral control) were measured via a TPB questionnaire at 5 time points: baseline (2-week run-in period), immediately after the first group session (where participants received a summary report of either population-based or genetic-based recommendations depending on group assignment), and after 3-, 6- and 12-month follow-ups. Attitudes, subjective norms, and perceived behavioral control were measured on a Likert scale from 1 through 7. Self-reported measures of actual behavioral control (including annual household income, perceptions about events arising in one’s day-to-day life that suddenly take up one’s free time, perceptions about the frequency of feeling ill or tired, and highest achieved level of education) were collected via survey questions and assessed on a Likert scale of 1 through 7. Stage of change was also measured, based on the Transtheoretical Model, using a Likert scale of 1 through 6.
Linear mixed models were used to conduct within- and between-group analyses using SPSS version 26.0, while controlling for measures of actual behavioral control. All analyses were intention-to-treat by originally assigned groups, with mean value imputation conducted for missing data. A Bonferroni correction for multiple testing was used. For all statistical analyses, the level of significance was set at P < 0.05 and trending towards significance at P = 0.05–0.06.
Main results. Participants consisted of primarily middle-age, middle-income, Caucasian females. Baseline attitudes towards the effectiveness of nutrition and PA for weight management were generally positive, and participants perceived that undergoing genetic testing would assist with weight management. Participants had overall neutral subjective norms related to friends and family consuming a healthy diet and engaging in PA, but perceived that their friends, family, and health care team (HCT) believed it was important for them to achieve their nutrition and PA recommendations. Participants overall also perceived that their HCT believed genetic testing could assist with weight management. Baseline measures of perceived behavioral control were overall neutral, with baseline stage of change between “motivation” and “action” (short-term; <3 months).
In within-group analyses, significant improvements (P < 0.05) in attitudes towards the effectiveness of nutrition and PA recommendations for weight management, subjective norms related to both friends and family consuming a healthy diet, and perceived behavioral control in changing PA/dietary intake and managing weight tended to be short-term in the GLB group and long-term for the GLB+LGx group. In all cases of between-group differences for changes in TPB components, the GLB group exhibited reductions in scores, whereas the GLB+LGx group exhibited increases or improvements. Between-group differences (short-term and long-term) in several measures of subjective norms were observed. For example, after 3 months, significant between-group differences were observed in changes in perception that friends believed LGx would help with weight management (P = 0.024). After 12 months, between-group differences trending towards significance were also observed in changes in perception that family members believed genetic testing would help with weight management (P = 0.05). Significant between-group differences and differences trending towards significance were also observed at 12 months for changes in perception that family believed it was important for the participant to achieve the PA recommendations (P = 0.049) and nutrition recommendations (P = 0.05). Between-group differences trending towards significance were also observed at 3 months in attitudes towards the effectiveness of LGx for weight management (P = 0.06). There were no significant between-group differences observed in changes in perceived behavioral control.
Conclusion. Results from this study support the hypothesis that the TPB can help provide a theoretical explanation for why genetically tailored lifestyle information and advice can lead to improvements in lifestyle behavior change.
Commentary
Because health behaviors are critical in areas such as prevention, treatment, and rehabilitation, it is important to describe and understand what drives these behaviors.1 Theories are important tools in this effort as they aim to explain and predict health behavior and are used in the design and evaluation of interventions.1 The TPB is one of the most widely accepted behavior change theories and posits that attitudes, subjective norms (or social pressures and behaviors), and perceived behavioral control are significant predictors of an individual’s intention to engage in behaviors.2 TPB has been highlighted in the literature as a validated theory for predicting nutrition and PA intentions and resulting behaviors.3,4
Motivating lifestyle behavior change in clinical practice can be challenging, but some studies have demonstrated how providing genetic information and advice (or lifestyle genomics) can help motivate changes in nutrition and PA among patients.5-7 Because this has yet to be explained using the TPB, this study is an important contribution to the literature as it aimed to determine the impact of providing genetically tailored and population-based lifestyle advice for weight management on key constructs of the TPB. Briefly, results from within-group analyses in this study demonstrated that the provision of genetically tailored lifestyle information and advice (via the GLB+LGx intervention) tended to impact antecedents of behavior change, more so over the long-term, while population-based advice (via the standard GLB intervention) tended to impact antecedents of behavior change over the short-term (eg, attitudes towards dietary fat intake, perceptions that friends and family consume a healthy diet, and perceptions about the impact of genetic-based advice for weight management). In addition, between-group differences in subjective norms observed at 12 months suggested that social pressures and norms may be influencing long-term changes in lifestyle habits.
While key strengths of this study include its pragmatic cluster randomized controlled trial design, 12-month intervention duration, and intent-to-treat analyses, there are some study limitations, which are acknowledged by the authors. Generalizability is limited to the demographic characteristics of the study population (ie, middle-aged, middle-income, Caucasian females enrolled in a lifestyle change weight management program). Thus, replication of the study is needed in more diverse study populations and with health-related outcomes beyond weight management. In addition, as the authors indicate, future research should ensure the inclusion of theory-based questionnaires in genetic-based intervention studies assessing lifestyle behavior change to elucidate theory-based mechanisms of change.
Applications for Clinical Practice
Population-based research has consistently indicated that nutrition interventions typically impact short-term dietary changes. Confronting the challenge of long-term adherence to nutrition and PA recommendations requires an understanding of factors impacting long-term motivation and behavior change. With increased attention on and research into genetically tailored lifestyle advice (or lifestyle genomics), it is important for clinical practitioners to be familiar with the evidence supporting these approaches. In addition, this research highlights the need to consider individual factors (attitudes, subjective norms, and perceived behavioral control) that may predict successful change in lifestyle habits when providing nutrition and PA recommendations, whether population-based or genetically tailored.
—Katrina F. Mateo, PhD, MPH
1. Lippke S, Ziegelmann JP. Theory-based health behavior change: Developing, testing, and applying theories for evidence-based interventions. Appl Psychol. 2008;57:698-716.
2. Ajzen I. The Theory of planned behaviour: reactions and reflections. Psychol Health. 2011;26:1113-1127.
3. McDermott MS, Oliver M, Simnadis T, et al. The Theory of Planned Behaviour and dietary patterns: A systematic review and meta-analysis. Prev Med (Baltim). 2015;81:150-156.
4. McEachan RRC, Conner M, Taylor NJ, Lawton RJ. Prospective prediction of health-related behaviours with the theory of planned behaviour: A meta-analysis. Health Psychol Rev. 2011;5:97-144.
5. Hietaranta-Luoma H-L, Tahvonen R, Iso-Touru T, et al A. An intervention study of individual, APOE genotype-based dietary and physical-activity advice: impact on health behavior. J Nutrigenet Nutrigenomics. 2014;7:161-174.
6. Nielsen DE, El-Sohemy A. Disclosure of genetic information and change in dietary intake: a randomized controlled trial. DeAngelis MM, ed. PLoS One. 2014;9(11):e112665.
7. Egglestone C, Morris A, O’Brien A. Effect of direct‐to‐consumer genetic tests on health behaviour and anxiety: a survey of consumers and potential consumers. J Genet Couns. 2013;22:565-575.
1. Lippke S, Ziegelmann JP. Theory-based health behavior change: Developing, testing, and applying theories for evidence-based interventions. Appl Psychol. 2008;57:698-716.
2. Ajzen I. The Theory of planned behaviour: reactions and reflections. Psychol Health. 2011;26:1113-1127.
3. McDermott MS, Oliver M, Simnadis T, et al. The Theory of Planned Behaviour and dietary patterns: A systematic review and meta-analysis. Prev Med (Baltim). 2015;81:150-156.
4. McEachan RRC, Conner M, Taylor NJ, Lawton RJ. Prospective prediction of health-related behaviours with the theory of planned behaviour: A meta-analysis. Health Psychol Rev. 2011;5:97-144.
5. Hietaranta-Luoma H-L, Tahvonen R, Iso-Touru T, et al A. An intervention study of individual, APOE genotype-based dietary and physical-activity advice: impact on health behavior. J Nutrigenet Nutrigenomics. 2014;7:161-174.
6. Nielsen DE, El-Sohemy A. Disclosure of genetic information and change in dietary intake: a randomized controlled trial. DeAngelis MM, ed. PLoS One. 2014;9(11):e112665.
7. Egglestone C, Morris A, O’Brien A. Effect of direct‐to‐consumer genetic tests on health behaviour and anxiety: a survey of consumers and potential consumers. J Genet Couns. 2013;22:565-575.