Ready, set, go! Motivation and lifestyle habits in parents of children referred for obesity management
Summary
Background
Parents play a fundamental role in helping children with obesity to make and maintain healthy lifestyle changes.
Objective
This study aimed to characterize stages of engagement to change nutrition and physical activity habits among parents whose children with obesity were enrolled in obesity management and examine differences in parents’ own nutrition and physical activity habits according to their stage of engagement.
Methods
Medical records of 113 children (body mass index [BMI] ≥95th percentile) enrolled in an outpatient weight management clinic were reviewed for baseline (cross-sectional) data. Parents completed the Weight Loss Behavior–Stage of Change Scale to assess the degree of engagement in making healthy changes to their lifestyle behaviours. Latent class analysis was used to classify parents into distinct clusters by grouping individuals with similar ratings of stages of engagement regarding nutrition- and physical activity-related behaviours.
Results
Parents’ engagement in healthy lifestyle behaviours varied (more engaged [n = 43]; less engaged [n = 70]). A greater proportion of parents in the more engaged group was in action and/or maintenance stages of changing their lifestyle habits. The more engaged group was less overweight than the less engaged group (BMI = 28.5 vs. 33.3 kg m−2; P < 0.05). Further, the more engaged group consumed fewer total calories, calories from fat, trans fat and carbohydrates vs. their less engaged peers (P < 0.05). Compared with the less engaged group, the more engaged group consumed more daily servings of vegetables and fruits (4.9 vs. 3.9, P < 0.05) and accumulated more steps per day (9130 vs. 7225; P < 0.05). The more engaged group was also more likely to meet daily recommendations for vegetable and fruit intake (48.8 vs. 24.3%; P < 0.05) and physical activity (42.9 vs. 22.9%, P < 0.05).
Conclusions
Parents of children with obesity varied in their degree of engagement in making healthy changes to their lifestyle behaviours, and those categorized as more engaged already demonstrated positive lifestyle behaviours. Information regarding parents’ degree of engagement in healthy behaviours can inform clinical recommendations, especially when parents represent the primary agents of change in families trying to manage paediatric obesity.
Introduction
One of the universal recommendations for successfully managing paediatric obesity is to encourage parents to help their children make and maintain positive nutrition, physical activity and behavioural changes 1. This recommendation has been informed by data demonstrating that lifestyle and behavioural interventions that either include families (usually parent–child dyads) 2 or parents exclusively 3 are effective in improving paediatric obesity and obesity-related health outcomes. Children with obesity are more likely to achieve weight loss if parents are successful at losing weight as well 4, which may be explained by their shared genetic predisposition 5 and parents’ positive influence on children's dietary 6 and physical activity habits 7. Intervention curricula usually focus on family-level changes to improve children's health and well-being, but parents are primarily responsible for enacting families’ lifestyle changes. Indeed, parents have reported the valuable role they play in being both healthy role models for their children and creating healthy home environments (e.g. increasing access to vegetables and fruits, setting limits for screen time, participating in regular physical activity) 8.
Degree of engagement to improve nutrition and physical activity habits plays a key role in parents’ and children's decision to change behaviours. Clinical recommendations encourage assessing motivational factors (e.g. importance, competence) prior to initiating therapy 1. This is especially relevant as high levels of attrition from paediatric obesity interventions 9 suggest many families may not be ready, willing or able to make healthy changes. However, little is known about parents’ degree of engagement to make healthy changes to their own behaviours when initiating obesity management along with their children. In the current study, our objectives were to (i) characterize stages of engagement to change nutrition and physical activity habits among parents whose children with obesity were enrolled in obesity management and (ii) examine differences in parents’ own nutrition and physical activity habits according to their stage of engagement. We hypothesized parents who were more engaged in making healthy changes to their nutrition and physical activity behaviours would have more positive lifestyle habits compared with parents who were less engaged.
Methods
This study was a retrospective medical record review of cross-sectional data collected from parents of children with obesity referred for obesity management from April 2005 to December 2012. The research was conducted in an outpatient, multidisciplinary paediatric obesity management clinic. For this study, parent was defined as a primary caregiver, which included biological, adoptive, step or foster mothers and fathers. For parents to be included in these analyses, all necessary demographic, anthropometric and lifestyle data must have been available in children's medical records and completed by the same parent. Exploratory analyses revealed that the subsample of parents included in this report is not dissimilar (e.g. age, weight status, ethnicity, gender) from the larger sample of parents of children with obesity enrolled in the clinic (data not shown). Data were retrieved using an information management protocol consistent with systematic medical record data extraction methodology 10. Site approval was received by Alberta Health Services (Stollery Children's Hospital), and research ethics approval was received by the Human Ethics Research Board at the University of Alberta (Edmonton, AB).
Before attending any appointments that included counselling for obesity management, demographic data were collected using a standardized self-report survey. In addition, height (to the nearest 0.1 cm using a digital stadiometer [SECA 242; Hanover, MD, USA]) and weight (to the nearest 0.1 kg using a medical digital balance scale [SECA 644]) were measured to calculate body mass index (BMI; kg m–2). Body weight categories were consistent with World Health Organization criteria 11 (underweight: <18.5 kg m−2; normal weight: 18.5–24.9 kg m−2; overweight: 25.0–29.9 kg m−2; obese class I: 30.0–34.9 kg m−2; obese class II; 35.0–39.9 kg m−2; obese class III: ≥40.0 kg m−2). In addition, waist circumference was measured (to the nearest 0.1 cm at the iliac crest using a spring-loaded Gulick anthropometric tape [FitSystems; Calgary, Alberta, Canada]).
Parents completed the Weight Loss Behavior-Stage of Change (WLB-SoC) Scale 12, a self-report measure used to quantify their own stage of change across five weight loss-related domains (e.g. increasing dietary portion control, fruit and vegetable intake, physical activity and planned exercise; decreasing dietary fat intake). Responses to survey questions on the 5-point Likert scale are linked to the transtheoretical model of behavior change 13. For example, scores ranged from 1 (I do not do this at least half of the time now and I have no plans to do this [precontemplation]) to 5 (I do this at least half the time now and I have been doing this for more than 6 months [maintenance]); higher scores indicate a higher degree of engagement to make changes to lifestyle habits associated with weight loss.
Dietary intake was measured prospectively using food records, which varied from 4 to 7 days in duration and included at least one weekend day. Completed records were reviewed by a registered dietitian to reduce the likelihood of item omissions and confirm serving sizes and brand names. Data were entered into the Food Processor Diet Analysis Software SQL program (v10.7.0, ESHA Research, Salem, OR, USA) and average daily intakes were determined. Along with manually tabulating servings per day of sugar-sweetened beverages (SSBs), the dietitian manually calculated servings per day of vegetables and fruits, milk products, meat and alternatives, and grain products according to Eating Healthy with Canada's Food Guide (CFG) 14. The number of kcal from fat, saturated fat, trans fat, carbohydrate and protein was adjusted for the total kcal consumed daily.
Pedometers (New Lifestyles Digi Walker SW 200, Lee's Summit, MO, USA) were used to quantify total physical activity (steps per day) over a 4- to 7-day period with at least one weekend day. Participants maintained a log book so that duration of wear and number of steps could be recorded daily. Over this period, a self-report physical activity record was kept to document the amount of time parents spent engaged in moderate-to-vigorous physical activity (MVPA) 15, which represents higher intensity activities and sports (e.g. running, basketball, soccer). As a proxy measure of sedentary activity, time spent viewing screens (e.g. television, video games, computer games) during leisure time periods was also collected. Upon completion, an exercise specialist reviewed completed records to confirm responses and clarify ambiguous information.
Data analyses
Based on parents’ responses to the WLB-SoC Scale, two latent groupings (more engaged and less engaged) were estimated using latent class analysis (LCA) with MPlus software 16. LCA is a statistical method for identifying unobserved (latent) classes among individuals using categorical and/or continuous observed variables. LCA allowed us to categorize parents into clusters by grouping parents who shared similar ratings of stages of engagement in making healthy changes to their lifestyle behaviours. For each parent, LCA inferred class membership by estimating the probability that the parent belonged to the first or second class (grouping) and assigned each parent to the class with the highest probability. Parents’ lifestyle behaviours (means [standard deviation {SD}] for continuous variables and frequencies for categorical variables) were compared across the two groupings. Differences between means were tested using a t-test for unequal group sizes. The proportions of parents meeting the following lifestyle recommendations were also calculated: five or more daily servings of vegetables and fruits 14; less than one daily sugar-sweetened beverage 17; ≥10 000 steps daily 18; and ≥8 h of sleep nightly 19. Differences in proportions of parents meeting lifestyle recommendations for intake of vegetables and fruits, physical activity, hours spent viewing TV and sleep duration were tested using a chi-square test. Data analyses were conducted using Stata 11 (Stata Corp., College Station, TX, USA).
Results
In total, 113 parents were included in these analyses (Table 1). Parents were, on average, 41.4 years old, predominantly female (90.3%) and Caucasian (82.0%). Almost half (46.6%) were post-secondary graduates, and approximately one-third (35.6%) had household incomes ≥CAD$80 000 (Table 1). Further, approximately one-third of parents were overweight (30.4%) while one-half were obese (50.9% classes I, II and III combined).
| Total | More engaged | Less engaged | P-value | ||||
|---|---|---|---|---|---|---|---|
| n = 113 | n = 43 | n = 70 | |||||
| Parent | |||||||
| Female (%) | 90.3 | 95.4 | 87.1 | 0.153 | |||
| Age (years) | 41.4 | (5.8) | 41.8 | (5.2) | 41.2 | (6.2) | 0.687 |
| Caucasian (%) | 82.0 | 95.5 | 73.8 | 0.035 | |||
| Education – college or university graduate (%) | 46.6 | 47.6 | 40.9 | 0.609 | |||
| Total income – $80 000 and over (%) | 35.6 | 63.2 | 27.0 | 0.009 | |||
| BMI (kg m−2) | 31.5 | (6.9) | 28.5 | (6.9) | 33.3 | (6.4) | 0.000 |
| Overweight (%) | 30.4 | 31.0 | 30.0 | 0.001 | |||
| Obese class I (%) | 24.1 | 19.1 | 27.1 | – | |||
| Obese class II (%) | 12.5 | 4.8 | 17.1 | – | |||
| Obese class III (%) | 14.3 | 7.1 | 18.6 | – | |||
| Waist circumference (cm) | 93.8 | (16.0) | 86.7 | (17.0) | 98.2 | (13.8) | 0.000 |
| Child | |||||||
| Female (%) | 56.6 | 55.8 | 54.3 | 0.606 | |||
| Age (years) | 10.8 | (1.6) | 10.2 | (1.4) | 11.2 | (1.6) | 0.001 |
| BMI (kg m–2) | 29.4 | (5.2) | 28.5 | (5.2) | 29.9 | (5.1) | 0.070 |
| BMI percentile | 97.3 | (8.5) | 97.7 | (2.4) | 97.1 | (10.7) | 0.646 |
| BMI z-score | 2.2 | (0.4) | 2.2 | (0.4) | 2.2 | (0.3) | 0.182 |
| Waist circumference (cm) | 89.1 | (12.9) | 85.7 | (13.2) | 91.2 | (12.4) | 0.014 |
- Values are expressed as mean (standard deviation) for continuous variables or percentage (%) for categorical variables. Overweight: body mass index (BMI) ≥25 and <30 kg m−2; obese class I: BMI ≥30 and <35 kg m−2; obese class II: BMI ≥35 and <40 kg m−2; obese class III: BMI ≥40 kg m−2. P-value is based on a t-test for unequal group size for continuous variables and a chi-square test for categorical variables.
Parents were categorized as either more engaged (n = 43) or less engaged (n = 70) in making healthy changes to their lifestyle habits. Compared with parents who were less engaged, parents in the more engaged group were more likely to be Caucasian, have higher family incomes, lower BMI and WC and have a child referred for weight management who was younger and with a smaller WC (Table 1).
Except for two items (Eat low fat dairy products; Don't use butter or margarine on breads, etc.), higher proportions of parents in the more engaged group reported being in action and/or maintenance stages 13 on all individual items from the WLB-SoC Scale (Table 2). Specifically, proportions of parents in the more engaged group who reported to be in action and/or maintenance stages were more than double that of parents in the less engaged group for items related to (i) contextual, psychosocial eating behaviours (i.e. Eat less at a later meal if you've eaten more earlier); (ii) items related to reducing dietary fat (i.e. Eat a low fat diet; Trim all the fat and skin off all meat); (iii) items related to the intake of vegetables and fruits (i.e. Eat at least 5 ½ cup servings of vegetables and fruits per day); and (iv) items related to increasing physical activity or reducing sedentary behaviours (i.e. Include a lot of physical activity in your daily routine).
| More engaged | Less engaged | P-value | |
|---|---|---|---|
| n = 43 | n = 70 | ||
| Eat less at a later meal if you've eaten more earlier | 43.5 | 16.7 | 0.004 |
| Stop eating before you feel stuffed | 21.4 | 7.0 | 0.042 |
| Avoid eating when you're nervous, upset or depressed | 74.3 | 35.7 | 0.000 |
| Resist eating everything on your plate if you're not hungry | 32.9 | 12.2 | 0.016 |
| Are aware of how much you eat when you snack | 39.7 | 11.6 | 0.001 |
| Eat a low-fat diet | 51.4 | 21.4 | 0.002 |
| Eat low-fat dairy products (skim or 1% milk, low-fat yogurt, light cheese) | 22.1 | 12.2 | 0.197 |
| Trim all the fat and skin off all meat | 26.1 | 4.7 | 0.004 |
| Limit meat portions to the size of a deck of cards | 47.8 | 18.6 | 0.002 |
| Avoid deep-fried foods such as fries, onion rings, chicken wings, potato chips, nachos, etc. | 64.3 | 20.9 | 0.000 |
| Don't use butter or margarine on breads, etc. | 64.3 | 47.6 | 0.084 |
| Avoid baked goods such as cake, cookies, pies, etc. | 70.0 | 31.0 | 0.000 |
| Use low-fat salad dressing | 33.3 | 14.0 | 0.023 |
| Eat at least 5 ½ cup servings of fruits and vegetables per day | 53.6 | 18.6 | 0.000 |
| When given a choice, have vegetables instead of fries | 57.1 | 7.0 | 0.000 |
| Eat fruit as a snack | 41.4 | 7.0 | 0.000 |
| Eat fruit as a dessert | 53.6 | 21.4 | 0.001 |
| Include a lot of physical activity in your daily routine | 70.0 | 23.3 | 0.000 |
| Do heavy housework, for example, washing windows, scrubbing walls or floors, etc. | 57.1 | 14.0 | 0.000 |
| Do outdoor work such as gardening, using a walking lawn mower, raking leaves or shovelling snow, etc. | 45.7 | 16.3 | 0.001 |
| Look for small ways to be active in your daily routine such as not using the TV remote, doing household chores by hand, etc. | 50.7 | 11.6 | 0.000 |
| Park car far from the entrance | 52.2 | 25.6 | 0.006 |
| Use the stairs instead of the elevator | 50.0 | 19.1 | 0.001 |
| Do active things in the evening such as walking, playing games, etc. | 67.1 | 33.3 | 0.001 |
- Responses to questions in the Weight Loss Behaviour–Stage of Change (WLB-SoC) Scale ranged from 1 to 5 (5-point Likert scale). Higher scores indicated a higher engagement to change their own lifestyle habits associated with weight loss. Proportions (%) are based on scores 4 (I do this at least half the time now and I just started doing this within the last 6 months [action]) and 5 (‘I do this at least half the time now and I have been doing this for more than 6 months’ [maintenance]). P-value is based on differences in proportions of parents in action and maintenance stages using a chi-square test.
Compared with parents who were less engaged, parents who were more engaged consumed fewer daily servings of grain products and more daily servings of vegetables and fruits (both P < 0.05; Table 3). They also had lower intakes of total energy, energy from dietary fat, trans fat and carbohydrates (all P < 0.05) as well as fewer daily grams of dietary fat and carbohydrates (both P < 0.05). Parents in the more engaged group consumed more daily servings of vegetables and fruits (P < 0.05) and accumulated more daily steps (P < 0.05). Finally, the proportion of parents in the more engaged group who were meeting recommendations for daily vegetables and fruits intake and physical activity was almost double that of parents in the less engaged group (both P < 0.05; Table 4).
| More engaged | Less engaged | P-value | |||
|---|---|---|---|---|---|
| n = 43 | n = 70 | ||||
| Nutrition | |||||
| Servings per day | |||||
| Grain products | 5.2 | (3.5) | 7.4 | (6.0) | 0.017 |
| Meat and alternatives | 2.3 | (1.2) | 2.4 | (1.1) | 0.397 |
| Milk products | 1.5 | (0.9) | 1.5 | (0.8) | 0.433 |
| Vegetables and fruits | 4.9 | (1.9) | 3.9 | (2.2) | 0.007 |
| Sugar-sweetened beverages | 1.4 | (1.8) | 1.2 | (1.1) | 0.222 |
| Kilocalories per day | |||||
| Total energy | 1760.6 | (427.6) | 1995.7 | (761.4) | 0.033 |
| Fat | 592.0 | (205.7) | 692.0 | (324.9) | 0.037 |
| Saturated fat | 199.2 | (81.4) | 226.7 | (101.3) | 0.068 |
| Trans fat | 6.4 | (4.6) | 14.5 | (12.9) | 0.001 |
| Carbohydrate | 865.1 | (216.3) | 994.5 | (397.0) | 0.026 |
| Protein | 294.3 | (82.7) | 310.6 | (108.0) | 0.200 |
| Grams per day | |||||
| Fat | 65.8 | (22.9) | 76.9 | (36.1) | 0.037 |
| Saturated fat | 22.1 | (9.0) | 25.2 | (11.3) | 0.068 |
| Carbohydrate | 216.3 | (54.1) | 248.6 | (99.2) | 0.026 |
| Protein | 73.6 | (20.7) | 77.6 | (27.0) | 0.200 |
| Fibre | 17.5 | (6.3) | 17.8 | (9.3) | 0.443 |
| Percentages per day | |||||
| Fat | 33.1 | (5.7) | 34.3 | (5.3) | 0.140 |
| Saturated fat | 33.3 | (5.0) | 33.2 | (5.7) | 0.554 |
| Trans fat | 1.1 | (0.8) | 2.2 | (1.7) | 0.001 |
| Carbohydrate | 49.3 | (6.2) | 50.1 | (6.5) | 0.274 |
| Protein | 17.0 | (4.0) | 16.0 | (3.1) | 0.060 |
| Physical activity | |||||
| Total physical activity (steps per day) | 9129.7 | (3391.1) | 7224.7 | (3523.6) | 0.003 |
| Moderate physical activity (min day–1) | 50.8 | (13.8) | 39.0 | (8.8) | 0.228 |
| Hard physical activity (min day–1) | 17.4 | (4.6) | 9.8 | (2.4) | 0.059 |
| Very hard physical activity (min day–1) | 6.4 | (2.8) | 0.8 | (0.5) | 0.013 |
| TV viewing (h week–1) | 49.7 | (8.8) | 59.5 | (8.2) | 0.216 |
| Sleep duration (hours per night) | 8.0 | (1.1) | 8.1 | (1.1) | 0.275 |
- P-value is based on differences in means using a t-test for unequal group sizes. SD, standard deviation.
| More engaged | Less engaged | P-value | |
|---|---|---|---|
| n = 43 | n = 70 | ||
| Vegetable and fruit intake | 48.8 | 24.3 | 0.007 |
| Sugar-sweetened beverages | 29.0 | 14.5 | 0.072 |
| Total physical activity | 42.9 | 22.9 | 0.026 |
| Sleep duration | 56.1 | 50.7 | 0.585 |
- Participants were considered to meet recommendations for lifestyle behaviours if they consumed five or more daily servings of vegetables and fruits (yes/no) 14; less than one daily sugar-sweetened beverages (yes/no) 17; attained ≥10 000 steps per day (yes/no) 18; and ≥8 h of sleep nightly (yes/no) 19. P-value is based on differences in proportions of parents meeting the recommendations using a chi-square test.
Discussion
Among parents initiating obesity management with their children, we characterized the degree of engagement in making healthy changes to their nutrition and physical activity habits. We also examined differences in parents’ lifestyle behaviours according to their stage of engagement. Two key findings emerge from this study. First, although parents varied in their reported stage of engagement in making healthy lifestyle changes, most parents were in lower stages of engagement in healthy lifestyle behaviours. Second, parents who were at higher stages of engagement presented with positive nutrition and physical activity habits relating to portion sizes, dietary fat consumption, fruit and vegetable consumption, and physical activity, suggesting that parents may already be employing healthy choices that can have a positive influence on their children's lifestyle habits and weight management.
Our results provide empirical evidence that at presentation for weight management with their children, approximately two-thirds of parents were in lower stages of engagement in making healthy changes to their lifestyle habits, changes that could potentially serve to role model and reinforce healthy habits for children. Given the high degree to which parents are included in their children's care, this low level of engagement may contribute to programme attrition 9. Indeed, the phenomenon of attrition is at the crux of providing efficient and effective health services for managing obesity as attrition can minimize therapeutic benefits for families, discourage families from seeking treatment in the future, lead to clinician inefficiency and take resources away from families engaged in care 20.
Tailoring interventions that account for parents’ engagement in making changes to their nutrition and physical activity habits is dependent on completing an accurate assessment of the engagement stage 12. Although we applied a validated tool in the current study to assess parents’ stage of engagement to change their own lifestyle habits, there are few well-established tools that can be applied in the field of paediatric weight management. For example, in a sample (n = 76) of parents of children with behavioural problems (e.g. oppositional, aggressive or antisocial behavior) who were referred for outpatient care, Nock and Photos 21 examined parents’ motivation to participate in a group-based, parent management training programme. Researchers evaluated the Parent Motivation Inventory, a tool that revealed parental motivation in the early phase of treatment predicted parents’ barriers to treatment, which subsequently predicted treatment attendance. Because behavioural disorders and obesity have different causes and consequences, the PMI is not directly applicable to our population. A practical tool that complements client-centred counselling techniques of motivational interviewing 22, Motivation to Change Rulers are used clinically to examine motivational constructs, including clients’ importance and confidence to change lifestyle habits. Rulers present a continuum of values (e.g. 0 = not at all ready to change; 10 = could not be more ready to change) that individuals can choose to represent their current motivation level. Although motivation rulers are practical, adaptable and easily understood, to our knowledge, they have not been evaluated psychometrically to determine reliability and validity for application in managing paediatric obesity.
Another evidence gap that impacts motivation and paediatric obesity management is a lack of an integrative approach to quantify children's and parents’ motivation, and this gap has both conceptual and clinical implications. Conceptually, instruments that assess family members’ motivation independently are misaligned with the dominant theories that underpin paediatric obesity management (e.g. family systems theory 23). Clinically, a reliable and valid measure of family motivation is vital as it can inform clinical decision-making (e.g. high family motivation = initiate intensive therapy; low family motivation = work to raise awareness and improve self-efficacy). In addition, there may be value in characterizing the degree of concordance between youth and parent motivation to change lifestyle habits as similarities or differences can impact families’ participation in treatment and adherence to clinical recommendations 24. If parents and youth present with different levels of motivation to change lifestyle habits, clinicians can direct treatment to those family members who are most ready to participate in care 25. A framework including practical insights and heuristics is available for clinicians to apply when tailoring individual approaches for families based on their motivation to change lifestyle and behavioural habits 26, which can help to reduce the complexity of managing obesity and optimize efficient and effective health services for families. It is possible that parents may be motivated to help their children make lifestyle changes to enable weight management but lack the motivation to make similar changes for themselves. Hampl et al. 27 reported that low patient/family motivation played a role in attrition, although they did not specify whether parent or child motivation levels were most influential. Because high motivation is linked to treatment adherence 28, and because motivation is dynamic 29 and malleable 22, clinicians can play a valuable role in measuring and enhancing families’ motivational factors, which may help to increase engagement and decrease the likelihood of attrition.
Further study is warranted to determine if parent, child or family attributes predict the degree of engagement and if parental self-reported SoC at paediatric obesity management initiation influences weight management outcomes. Of the available evidence, a recent study of 40 adolescent girls with obesity and polycystic ovary syndrome and their parents enrolled in a weight management intervention reported that BMI reductions in girls were associated with parents’ stages of change weight control behaviours, but not with adolescents’ stage of change 30. Parents have described the direct and indirect effects they have on their children's nutrition and physical activity habits and highlighted the importance of being healthy role models (e.g. eating vegetables and fruits themselves) and creating healthy home environments (e.g. making vegetables and fruits available in home; removing sugar-sweetened beverages) 8. Results of our study corroborate the concept of tailoring interventions in order to align treatment plans according to family degree of engagement in making healthy changes to lifestyle habits 30.
It is important to acknowledge the limitations of our research. First, the cross-sectional nature of our data prevents us from making causal inferences. Second, because this study included a group of parents attending a weight management clinic, our sample may have possessed a higher degree of parental engagement to make changes to their nutrition and physical activity habits than would be expected of parents recruited from other settings and may limit the external generalizability of the results. Third, nutrition and physical activity are complex behaviours, so there may have been other elements of these habits (e.g. meal preparation, sleep hygiene) that went unmeasured and were more relevant to parents’ degree of engagement. Fourth, the retrospective nature of this study limited our ability to use data from the WLB-SoC Scale to inform clinical decision-making. Future analyses will explore the degree to which parental engagement to make changes to their own habits influence both children's and parents’ obesity management. Finally, because most parents included in our study were mothers and Caucasian, our ability to generalize our findings to other groups is limited.
In our study, parents of children with obesity varied in their degree of engagement in making healthy changes to their nutrition and physical activity-related behaviours. At presentation for weight management with their children, the majority of parents were in lower stages of engagement in healthy lifestyle behaviours and were more likely to be overweight or obese themselves. Parents who were at higher stages of engagement already had more positive lifestyle habits compared with parents who were less engaged, suggesting that some parents were already employing healthy choices that can have a positive influence on children's lifestyle habits and weight management. Our data highlight the importance of individualizing obesity management counselling strategies and lifestyle recommendations according to parents’ degree of engagement and current lifestyle habits, which can influence the lifestyle changes they are willing and able to do for themselves and their children.
Conflict of Interest Statement
GDCB is the director of the weight management clinic from which study data were derived. All other authors have no conflicts of interest to declare.
Acknowledgements
The authors wish to thank the families whose data were included in this report, the clinicians and administrative support staff at the Pediatric Centre for Weight and Health (Stollery Children's Hospital, Edmonton, Alberta, Canada) for enabling this research, and Ms Allison Rasquinha for her administrative research support.
Author contributions
KM conceived the study (with GDCB), led all data analyses and wrote the first draft of the manuscript (with GDCB). KAA, JNR and NC assisted with data collection and management. GDCB conceived the study and wrote the first draft of the manuscript (with KM). All authors reviewed and approved the manuscript prior to submission. Each of our authors meets the standard criteria for authorship.
