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The impact of eating self-regulatory skills on weight control and dietary behaviours in adults
Abstract and Figures
Recent studies suggest the ability to self-regulate eating behaviour may help people to cope with the food environment and achieve, as well as maintain, a healthy weight and diet. However, most studies exploring the relationships between eating self-regulatory skills, weight control and dietary habits in adults have used a cross-sectional design and have not accounted for the full range of eating self-regulatory skills, possibly due to the fact that no comprehensive measure of eating self-regulation exists. Furthermore, although there are indications that eating self-regulatory skills may be enhanced through practice, the most effective way to improve these skills and the impact of any changes on weight loss and dietary behaviours has not been established. Therefore, this PhD thesis developed a valid and reliable measure to assess eating self-regulatory skills in the general adult population (Study 1). Results from Study 2 showed that higher eating self-regulatory skills may help students to maintain or achieve a healthy diet and protect them against substantial weight gain (≥5% initial body weight), especially among students with higher BMIs. In Study 3, secondary analysis from the 10 Top Tips (10TT) randomised controlled trial was undertaken to test the effect of a habit-based intervention on eating self-regulatory skills. Results showed 10TT promoted greater increases in self-regulatory skills than Usual Care. Furthermore, these changes in self-regulatory skills mediated the effect of 10TT on target behaviours and weight loss. Lastly, since the use of new technology for lifestyle interventions is an emerging field in public health, two app versions of 10TT, one identical to 10TT (Top Tips ‘only’ app) and another including a self-regulatory training component for breaking unhealthy eating habits (Top Tips ‘plus’ app), were developed and piloted with overweight and obese adults (Study 4). Exploratory results from Study 4 suggest that both app interventions may promote eating self-regulatory skills, weight loss and healthy behaviours among overweight and obese adults, especially among those more engaged with the apps. However, both apps would benefit from further development work and should be evaluated by means of a randomised controlled trial.
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... Systematic reviews of GWG interventions and individual RCTs that were published since the most recent systematic review (September 2021) were examined, with the focus being on identifying BCTs used in successful behavioural interventions that included a nutritional component (see Additional File 2 for search strategy). BCTs in the original 10TT intervention materials have previously been coded [39] and whilst adapting the intervention, the operationalisation of the BCTs for a pregnant population was considered. The adapted intervention materials were coded using: the CALO-RE taxonomy; the BCT taxonomy (v1) 93-items; and, the Oxford Food and Activity Behaviours (OxFAB) taxonomy [36,40,41]. ...
... It has been used successfully in weight management interventions for various population groups [21], but has not been tested via behavioural intervention in a pregnant population. Alongside this focus on the theoretical basis for the behavioural intervention, existing evidence regarding the BCTs associated with intervention effectiveness in previous GWG studies was examined, given additional BCTs are likely to aid enactment of new, planned, healthy behaviours in the initial stages of habit-formation [36,37,39]. ...
... Of the original 10TT BCTs coded by Kliemann et al., all were retained in the adapted intervention (HHIPBe) aside from 'goal setting (outcome)' and ''prompt review of outcome goals' (see Table 1 for full details on BCTs in 10TT and HHIPBe) [39]. This was because the HHIPBe intervention focuses on turning the ten tips into habitual behaviours, rather than focusing on weight as an outcome goal, therefore women were only encouraged to set goals in relation to their behaviour. ...
Background
The number of women entering pregnancy with overweight or obesity is increasing. This can increase the risk for excessive gestational weight gain (GWG) which is associated with health complications for mother and baby. There are limited evidence-based interventions within antenatal care settings to encourage healthy eating and physical activity behaviours and support women with managing GWG.
Methods
A previous habit-based intervention ‘Ten Top Tips for a Healthy Weight’ (10TT) was adapted and made suitable for pregnancy in line with the Medical Research Council’s (MRC) complex intervention development guidelines. It involved three key activities: (1) identifying the evidence base; (2) identifying appropriate theory; and, (3) modelling processes. A core element was integrating lived experience via personal and public involvement (PPI).
Results
The original 10TTs were adapted with PPI in line with current advice on nutrition and physical activity in pregnancy. New intervention materials were devised, including a leaflet and a logbook and app for self-monitoring to be delivered alongside a brief 1:1 conversation. Behaviour change techniques (BCTs) included in the new materials were coded using a number of behavioural taxonomies. An E-learning resource was created to help standardise the approach to delivery of the intervention and avoid stigmatising conversations.
Conclusion
Following MRC guidance for the development of complex interventions alongside significant PPI allowed for the adaption of 10TT habit-based weight management intervention into the ‘Healthy Habits in Pregnancy and Beyond’ (HHIPBe) intervention. The feasibility and acceptability of implementing this intervention in the antenatal setting will be explored in a feasibility randomised controlled trial.
Trial Registration
This study was registered on Clinical Trials as ‘Healthy Habits in Pregnancy and Beyond (HHIPBe)’ ClinicalTrials.gov Identifier: NCT04336878. The study was registered on 07/04/2020.
Background
The number of women entering pregnancy with overweight or obesity is increasing. This can increase the risk for excessive gestational weight gain (GWG) which is associated with health complications for mother and baby. There are limited evidence-based interventions within antenatal care settings to encourage healthy eating and physical activity behaviours and support women with managing GWG.
Methods
A previous habit-based intervention ‘Ten Top Tips for a Healthy Weight’ (10TT) was adapted and made suitable for pregnancy in line with the Medical Research Council’s (MRC) complex intervention development guidelines. It involved three key activities: 1) identifying the evidence base; 2) identifying appropriate theory; and, 3) modelling processes. A core element was integrating lived experience via personal and public involvement (PPI).
Results
The original 10TTs were adapted with PPI in line with current advice on nutrition and physical activity in pregnancy. New intervention materials were devised, including a leaflet and a logbook and app for self-monitoring to be delivered alongside a brief 1:1 conversation. Behaviour change techniques (BCTs) included in the new materials were coded using a number of behavioural taxonomies. An E-learning resource was created to help standardise the approach to delivery of the intervention and avoid stigmatising conversations.
Conclusion
Following MRC guidance for the development of complex interventions alongside significant PPI allowed for the successful adaption of 10TT habit-based weight management intervention into the ‘Healthy Habits in Pregnancy and Beyond’ (HHIPBe) intervention. The feasibility and acceptability of implementing this intervention in the antenatal setting will be explored in a feasibility randomised controlled trial.
Trial Registration
This study was registered on Clinical Trials as ‘Healthy Habits in Pregnancy and Beyond (HHIPBe)’ ClinicalTrials.gov Identifier: NCT04336878. The study was registered on 07/04/2020.
BACKGROUND: Although the rising pandemic of obesity has received major attention in many countries, the effects of this attention on trends and the disease burden of obesity remain uncertain. METHODS: We analyzed data from 68.5 million persons to assess the trends in the prevalence of overweight and obesity among children and adults between 1980 and 2015. Using the Global Burden of Disease study data and methods, we also quantified the burden of disease related to high body-mass index (BMI), according to age, sex, cause, and BMI in 195 countries between 1990 and 2015. RESULTS: In 2015, a total of 107.7 million children and 603.7 million adults were obese. Since 1980, the prevalence of obesity has doubled in more than 70 countries and has continuously increased in most other countries. Although the prevalence of obesity among children has been lower than that among adults, the rate of increase in childhood obesity in many countries has been greater than the rate of increase in adult obesity. High BMI accounted for 4.0 million deaths globally, nearly 40% of which occurred in persons who were not obese. More than two thirds of deaths related to high BMI were due to cardiovascular disease. The disease burden related to high BMI has increased since 1990; however, the rate of this increase has been attenuated owing to decreases in underlying rates of death from cardiovascular disease. CONCLUSIONS: The rapid increase in the prevalence and disease burden of elevated BMI highlights the need for continued focus on surveillance of BMI and identification, implementation, and evaluation of evidence-based interventions to address this problem. (Funded by the Bill and Melinda Gates Foundation.)
Background
Chronic conditions are an increasing challenge for individuals and the health care system. Smartphones and health apps are potentially promising tools to change health-related behaviors and manage chronic conditions.
Objective
The aim of this study was to explore (1) the extent of smartphone and health app use, (2) sociodemographic, medical, and behavioral correlates of smartphone and health app use, and (3) associations of the use of apps and app characteristics with actual health behaviors.
Methods
A population-based survey (N=4144) among Germans, aged 35 years and older, was conducted. Sociodemographics, presence of chronic conditions, health behaviors, quality of life, and health literacy, as well as the use of the Internet, smartphone, and health apps were assessed by questionnaire at home visit. Binary logistic regression models were applied.
Results
It was found that 61.25% (2538/4144) of participants used a smartphone. Compared with nonusers, smartphone users were younger, did more research on the Internet, were more likely to work full-time and more likely to have a university degree, engaged more in physical activity, and less in low fat diet, and had a higher health-related quality of life and health literacy. Among smartphone users, 20.53% (521/2538) used health apps. App users were younger, less likely to be native German speakers, did more research on the Internet, were more likely to report chronic conditions, engaged more in physical activity, and low fat diet, and were more health literate compared with nonusers who had a smartphone. Health apps focused on smoking cessation (232/521, 44.5%), healthy diet (201/521, 38.6%), and weight loss (121/521, 23.2%). The most common app characteristics were planning (264/521, 50.7%), reminding (188/521, 36.1%), prompting motivation (179/521 34.4%), and the provision of information (175/521, 33.6%). Significant associations were found between planning and the health behavior physical activity, between feedback or monitoring and physical activity, and between feedback or monitoring and adherence to doctor’s advice.
Conclusions
Although there were many smartphone and health app users, a substantial proportion of the population was not engaged. Findings suggest age-related, socioeconomic-related, literacy-related, and health-related disparities in the use of mobile technologies. Health app use may reflect a user’s motivation to change or maintain health behaviors. App developers and researchers should take account of the needs of older people, people with low health literacy, and chronic conditions.
The objective of this study is to examine the association between impulsivity and weight status in a large sample of the adult general population in France, and the influence of gender on this relationship. A total of 11,929 men and 39,114 women participating in the NutriNet-Santé cohort were selected in this cross-sectional analysis. The Barratt Impulsiveness Scale (BIS-11) was used to assess impulsivity. Weight and height were self-reported. The association between impulsivity and BMI was estimated using logistic regressions adjusted for socio-demographic and lifestyle factors. Individuals with high impulsivity levels (BIS-11 total score >71) were more likely to be obese (Odds Ratio (OR) = 1.80, 95% Confidence Interval (CI): 1.39, 2.33 in men; OR = 1.30, 95% CI: 1.15, 1.48 in women) compared to individuals in the average range of impulsivity. The strongest associations between impulsivity and obesity were observed in men, where highly impulsive participants were more likely to be class III obese (BMI > 40 kg/m²) (OR = 3.57, 95% CI: 1.86, 6.85). This large sample analysis supports the existence of a relationship between impulsivity and weight status and the importance of psychological factors in the prevention of obesity.
Background
Obesity is a major global public health issue due to its association with a number of serious chronic illnesses and its high economic burden to health care providers. Self-monitoring of diet has been consistently linked to weight loss. However, there is limited evidence about how frequently individuals need to monitor their diet for optimal weight loss.
Objective
The aim of this paper is to describe app usage frequency and pattern in the mobile phone arm of a previously conducted randomized controlled trial. The relationship between frequency and pattern of electronic dietary self-monitoring and weight loss is also investigated.
MethodsA randomized pilot trial comparing three methods of self-monitoring (mobile phone app, paper diary, Web-based) was previously conducted. Trial duration was 6 months. The mobile phone app My Meal Mate features an electronic food diary and encourages users to self-monitor their dietary intake. All food consumption data were automatically uploaded with a time and date stamp. Post hoc regression analysis of app usage patterns was undertaken in the My Meal Mate group (n=43; female: 77%, 33/43; white: 100%, 43/43; age: mean 41, SD 9 years; body mass index: mean 34, SD 4 kg/m2) to explore the relationship between frequency and pattern of electronic dietary self-monitoring and weight loss. Baseline characteristics of participants were also investigated to identify any potential predictors of dietary self-monitoring.
ResultsRegression analysis showed that those in the highest frequency-of-use category (recorded ≥129 days on the mobile phone app) had a −6.4 kg (95% CI −10.0 to −2.9) lower follow-up weight (adjusted for baseline weight) than those in the lowest frequency-of-use category (recorded ≤42 days; P
Background:
Primary care is the 'first port of call' for weight control advice, creating a need for simple, effective interventions that can be delivered without specialist skills. Ten Top Tips (10TT) is a leaflet based on habit-formation theory that could fill this gap. The aim of the current study was to test the hypothesis that 10TT can achieve significantly greater weight loss over 3 months than 'usual care'.
Methods:
A two-arm, individually randomised, controlled trial in primary care. Adults with obesity were identified from 14 primary care providers across England. Patients were randomised to either 10TT or 'usual care' and followed up at 3, 6, 12, 18 and 24 months. The primary outcome was weight loss at 3 months, assessed by a health professional blinded to group allocation. Difference between arms was assessed using a mixed-effect linear model taking into account the health professionals delivering 10TT, and adjusted for baseline weight. Secondary outcomes included body mass index, waist circumference, the number achieving a 5% weight reduction, clinical markers for potential comorbidities, weight loss over 24 months and basic costs.
Results:
Five-hundred and thirty-seven participants were randomised to 10TT (n=267) or to 'usual care' (n=270). Data were available for 389 (72%) participants at 3 months and for 312 (58%) at 24 months. Participants receiving 10TT lost significantly more weight over 3 months than those receiving usual care (mean difference =-0.87kg; 95% confidence interval: -1.47 to -0.27; P=0.004). At 24 months, the 10TT group had maintained their weight loss, but the 'usual care' group had lost a similar amount. The basic cost of 10TT was low, that is, around £23 ($32) per participant.
Conclusions:
The 10TT leaflet delivered through primary care is effective in the short-term and a low-cost option over the longer term. It is the first habit-based intervention to be used in a health service setting and offers a low-intensity alternative to 'usual care'.
Background:
Overweight and weight gain throughout adult life have been associated with increased risk of breast cancer after the menopause. However the role of body weight at a young age and of the timing of weight gain over the lifetime in postmenopausal breast cancer is not well documented.
Methods:
We conducted a population-based case-control study on breast cancer in France that included 739 cases and 815 population controls in postmenopausal women. Height, weight at age 20, 40 and 50 as well as weight one year before diagnosis were obtained during in-person interviews.
Results:
No association between body mass index at the age of 20 years and breast cancer after the menopause was detected. However, we found that postmenopausal breast cancer was associated with weight gain between ages 40 and 50 years (OR per 5 kg/m2 increase in BMI: 1.45 [95%ci 1.06-1.98]). The increased risk of breast cancer associated with weight gain was more consistent in leaner women at age 20, in older postmenopausal women (>65 years), and in women who did not use menopausal hormone therapy.
Conclusions:
These findings point to the importance of controlling for weight gain in middle aged-women. The role of low body weight in young adulthood in breast cancer risk after the menopause should be further scrutinized.
Background
The majority of nutrition and physical activity assessments methods commonly used in scientific research are subject to recall and social desirability biases, which result in over- or under-reporting of behaviors. Real-time mobile-based ecological momentary assessments (mEMAs) may result in decreased measurement biases and minimize participant burden.
Objective
The aim was to examine the validity of a mEMA methodology to assess dietary and physical activity levels compared to 24-hour dietary recalls and accelerometers.
Methods
This study was a pilot test of the SPARC (Social impact of Physical Activity and nutRition in College) study, which aimed to determine the mechanism by which friendship networks impact weight-related behaviors among young people. An mEMA app, devilSPARC, was developed to assess weight-related behaviors in real time. A diverse sample of 109 freshmen and community mentors attending a large southwestern university downloaded the devilSPARC mEMA app onto their personal mobile phones. Participants were prompted randomly eight times per day over the course of 4 days to complete mEMAs. During the same 4-day period, participants completed up to three 24-hour dietary recalls and/or 4 days of accelerometry. Self-reported mEMA responses were compared to 24-hour dietary recalls and accelerometry measures using comparison statistics, such as match rate, sensitivity and specificity, and mixed model odds ratios, adjusted for within-person correlation among repeated measurements.
Results
At the day level, total dietary intake data reported through the mEMA app reflected eating choices also captured by the 24-hour recall. Entrées had the lowest match rate, and fruits and vegetables had the highest match rate. Widening the window of aggregation of 24-hour dietary recall data on either side of the mEMA response resulted in increased specificity and decreased sensitivity. For physical activity behaviors, levels of activity reported through mEMA differed for sedentary versus non-sedentary activity at the day level as measured by accelerometers.
Conclusions
The devilSPARC mEMA app is valid for assessing eating behaviors and the presence of sedentary activity at the day level. This mEMA may be useful in studies examining real-time weight-related behaviors.
Background:
Food processing alters food from its natural state for safety, convenience, taste or palatability. Previous research suggests that industrially processed foods, and diets high in these products, tend to be less healthful. However, most previous work is based on household, rather than individual-level, data. Little has been reported on the relationship between processed food consumption and markers of health; or on socio-demographic correlates of processed food consumption. Our objective was to describe: the nutritional content of foods classified according to degree of processing; the nutritional content of diets with different relative intakes of processed foods; the socio-demographic characteristics of individuals with different relative intakes of processed foods; and the association between intake of processed foods and body weight.
Methods:
Secondary analysis of data from the UK National Diet and Nutrition Survey (2008-12), a large national cross-sectional study of diet. Dietary information was collected using four-day, unweighed, food-diaries. Foods were classified as: unprocessed or minimally processed (MPF; foods with no processing or mostly physical processes applied to single whole foods), processed ingredients (PI; extracted and purified components of single whole foods), or ultra-processed food products (UPF; products produced from industrial combining of MPF and PI).
Results:
Two thousand one hundred seventy four adults were included. MPF and diets high in these foods, had the most healthful nutritional profile. UPF did not necessarily have the least healthful nutritional profile, but diets high in these foods did. Women, and older adults consumed more energy from MPF, and less from UPF. Those living in lower occupation social class households consumed less energy from MPF, but no more from UPF. Only higher intake of PI was consistently, inversely, associated with body weight.
Conclusions:
This is the first study to explore correlates of processed food consumption, using individual-level data from a large, national sample. Although higher intakes of MPF and lower intakes of UPF were associated with the most healthful dietary profiles, only intake of PI was consistently associated with body weight. Consumption of UPF varied by age and gender, but, unexpectedly, not by occupational social class. Longitudinal work is required to confirm relationships with health markers.
This study rested the idea of habits as a form of goal-directed automatic behavior. Expanding on the idea that habits are mentally represented as associations between goals and actions, it was proposed that goals are capable of activating the habitual action. More specific, when habits are established (e.g., frequent cycling to the university), the very activation of the goal to act (e.g., having to attend lectures at the university) automatically evokes the habitual response (e.g., bicycle). Indeed, it was tested and confirmed that, when behavior is habitual, behavioral responses are activated automatically. in addition, the results of 3 experiments indicated that (a) the automaticity in habits is conditional on the presence of an active goal (cf. goal-dependent automaticity; J. A. Bargh, 1989), supporting the idea that habits are mentally represented as goal-action links, and (b) the formation of implementation intentions (i.e., the creation of a strong mental link between a goal and action) may simulate goal-directed automaticity in habits.