Are motivational and self-regulation factors associated with 12 months' weight regain prevention in the NoHoW study? An analysis of European adults.

PURPOSE: Preventing weight regain can only be achieved by sustained changes in energy balance-related behaviors that are associated with weight, such as diet and physical activity. Changes in motivation and self-regulatory skills can support long-term behavioral changes in the context of weight loss maintenance. We propose that experiencing a supportive climate care is associated with enhanced satisfaction of basic psychological needs, intrinsic goals, and autonomous motivation. These factors are expected to be associate with the utilization of self-regulation skills, leading to more sustained behavior changes and ultimately preventing weight regain. This hypothesis was tested in this ancillary analysis of the NoHoW trial, where the study arms were pooled and followed for 12 months. METHODS: The NoHoW was a three-center, large-scale weight regain prevention full factorial trial. In this longitudinal study, data were collected in adults who lost > 5% weight in the past year (N = 870, complete data only, 68.7% female, 44.10 ± 11.86 years, 84.47 ± 17.03 kg) during their participation in a 12-month digital behavior change intervention. Weight and validated measures of motivational- and self-regulatory skills-related variables were collected at baseline, six- and 12 months. Change variables were used in Mplus' path analytical models informed by NoHoW's logic model. RESULTS: The bivariate correlations confirmed key mediators' potential effect on weight outcomes in the expected causal direction. The primary analysis showed that a quarter of the variance (r2 = 23.5%) of weight regain prevention was achieved via the mechanisms of action predicted in the logic model. Specifically, our results show that supportive climate care is associated with needs satisfaction and intrinsic goal content leading to better weight regain prevention via improvements in self-regulatory skills and exercise-controlled motivation. The secondary analysis showed that more mechanisms of action are significant in participants who regained or maintained their weight. CONCLUSIONS: These results contribute to a better understanding of the mechanisms of action leading to behavior change in weight regain prevention. The most successful participants used only a few intrinsic motivation-related mechanisms of action, suggesting that habits may have been learned. While developing a digital behavior change intervention, researchers and practitioners should consider creating supportive climate care to improve needs satisfaction and intrinsic goal contents. TRIAL REGISTRATION: ISRCTN, ISRCTN88405328 , registered 12/22/2016.

Exploratory analysis of reflective, reactive, and homeostatic eating behaviour traits on weight change during the 18-month NoHoW weight maintenance trial.

Behaviour change interventions for weight management have found varied effect sizes and frequent weight re-gain after weight loss. There is interest in exploring whether differences in eating behaviour can be used to develop tailored weight management programs. This secondary analysis of an 18-month weight maintenance randomised controlled trial (RCT) aimed to investigate the association between individual variability in weight maintenance success and change in eating behaviour traits (EBT). Data was analysed from the NoHoW trial (Scott et al., 2019), which was designed to measure processes of change after weight loss of ≥5% body weight in the previous year. The sample included 1627 participants (mean age = 44.0 years, SD = 11.9, mean body mass index (BMI) = 29.7 kg/m2, SD = 5.4, gender = 68.7% women/31.3% men). Measurements of weight (kg) and 7 EBTs belonging to domains of reflective, reactive, or homeostatic eating were taken at 4 time points up to 18-months. Increases in measures of 'reactive eating' (binge eating, p < .001), decreases in 'reflective eating' (restraint, p < .001) and changes in 'homeostatic eating' (unlimited permission to eat, p < .001 and reliance on hunger and satiety cues, p < .05) were significantly and independently associated with concomitant weight change. Differences in EBT change were observed between participants who lost, maintained, or re-gained weight for all EBTs (p < .001) except for one subscale of intuitive eating (eating for physical reasons, p = .715). Participants who lost weight (n = 322) exhibited lower levels of reactive eating and higher levels of reflective eating than participants who re-gained weight (n = 668). EBT domains can identify individuals who need greater support to progress in weight management interventions. Increasing reflective eating and reducing reactive eating may enhance weight management success.

The association between general and central obesity and the risks of coronary heart disease in women with and without a familial predisposition to obesity: findings from the Danish Nurse Cohort.

Several studies show an increased risk of coronary heart disease (CHD) among people with obesity, but it is largely unknown whether this association also depends on a familial predisposition to obesity. This study examined if associations between Body Mass Index (BMI) or waist circumference (WC) and incident CHD differed among Danish female nurses with and without familial overweight and obesity. Analyses were based on data from the Danish Nurse Cohort (n = 20,701). Self-reported height, weight and self-measured WC were assessed in 1999, as was information on familial overweight/obesity, defined as having one or both parents with overweight/obesity. Information on the development of or death from CHD was collected from nationwide Danish registries in 2015. Analyses were based on Cox proportional hazard regression models adjusted for potential confounding factors. Both BMI and WC were directly associated with CHD risk, but we found no evidence of effect modification from familial predisposition to obesity. Hence a familial predisposition to obesity does not seem to influence the risk of CHD associated with general or central obesity.

Users' Experiences With the NoHoW Web-Based Toolkit With Weight and Activity Tracking in Weight Loss Maintenance: Long-term Randomized Controlled Trial.

BACKGROUND: Digital behavior change interventions (DBCIs) offer a promising channel for providing health promotion services. However, user experience largely determines whether they are used, which is a precondition for effectiveness. OBJECTIVE: The primary aim of this study is to evaluate user experiences with the NoHoW Toolkit (TK)-a DBCI that targets weight loss maintenance-over a 12-month period by using a mixed methods approach and to identify the main strengths and weaknesses of the TK and the external factors affecting its adoption. The secondary aim is to objectively describe the measured use of the TK and its association with user experience. METHODS: An 18-month, 2×2 factorial randomized controlled trial was conducted. The trial included 3 intervention arms receiving an 18-week active intervention and a control arm. The user experience of the TK was assessed quantitatively through electronic questionnaires after 1, 3, 6, and 12 months of use. The questionnaires also included open-ended items that were thematically analyzed. Focus group interviews were conducted after 6 months of use and thematically analyzed to gain deeper insight into the user experience. Log files of the TK were used to evaluate the number of visits to the TK, the total duration of time spent in the TK, and information on intervention completion. RESULTS: The usability level of the TK was rated as satisfactory. User acceptance was rated as modest; this declined during the trial in all the arms, as did the objectively measured use of the TK. The most appreciated features were weekly emails, graphs, goal setting, and interactive exercises. The following 4 themes were identified in the qualitative data: engagement with features, decline in use, external factors affecting user experience, and suggestions for improvements. CONCLUSIONS: The long-term user experience of the TK highlighted the need to optimize the technical functioning, appearance, and content of the DBCI before and during the trial, similar to how a commercial app would be optimized. In a trial setting, the users should be made aware of how to use the intervention and what its requirements are, especially when there is more intensive intervention content. TRIAL REGISTRATION: ISRCTN Registry ISRCTN88405328; https://www.isrctn.com/ISRCTN88405328. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2019-029425.

The impact of early body-weight variability on long-term weight maintenance: exploratory results from the NoHoW weight-loss maintenance intervention.

BACKGROUND: Weight-loss programmes often achieve short-term success though subsequent weight regain is common. The ability to identify predictive factors of regain early in the weight maintenance phase is crucial. OBJECTIVE: To investigate the associations between short-term weight variability and long-term weight outcomes in individuals engaged in a weight-loss maintenance intervention. METHODS: The study was a secondary analysis from The NoHoW trial, an 18-month weight maintenance intervention in individuals who recently lost ≥5% body weight. Eligible participants (n = 715, 64% women, BMI = 29.2 (SD 5.0) kg/m2, age = 45.8 (SD 11.5) years) provided body-weight data by smart scale (Fitbit Aria 2) over 18 months. Variability in body weight was calculated by linear and non-linear methods over the first 6, 9 and 12 weeks. These estimates were used to predict percentage weight change at 6, 12, and 18 months using both crude and adjusted multiple linear regression models. RESULTS: Greater non-linear weight variability over the first 6, 9 and 12 weeks was associated with increased subsequent weight in all comparisons; as was greater linear weight variability measured over 12 weeks (up to AdjR2 = 4.7%). Following adjustment, 6-week weight variability did not predict weight change in any model, though greater 9-week weight variability by non-linear methods was associated with increased body-weight change at 12 (∆AdjR2 = 1.2%) and 18 months (∆AdjR2 = 1.3%) and by linear methods at 18 months (∆AdjR2 = 1.1%). Greater non-linear weight variability measured over 12 weeks was associated with increased weight at 12 (∆AdjR2 = 1.4%) and 18 (∆AdjR2 = 2.2%) months; and 12-week linear variability was associated with increased weight at 12 (∆AdjR2 = 2.1%) and 18 (∆AdjR2 = 3.6%) months. CONCLUSION: Body-weight variability over the first 9 and 12 weeks of a weight-loss maintenance intervention weakly predicted increased weight at 12 and 18 months. These results suggest a potentially important role in continuously measuring body weight and estimating weight variability.

Consistent sleep onset and maintenance of body weight after weight loss: An analysis of data from the NoHoW trial.

BACKGROUND: Several studies have suggested that reduced sleep duration and quality are associated with an increased risk of obesity and related metabolic disorders, but the role of sleep in long-term weight loss maintenance (WLM) has not been thoroughly explored using prospective data. METHODS AND FINDINGS: The present study is an ancillary study based on data collected on participants from the Navigating to a Healthy Weight (NoHoW) trial, for which the aim was to test the efficacy of an evidence-based digital toolkit, targeting self-regulation, motivation, and emotion regulation, on WLM among 1,627 British, Danish, and Portuguese adults. Before enrolment, participants had achieved a weight loss of ≥5% and had a BMI of ≥25 kg/m2 prior to losing weight. Participants were enrolled between March 2017 and March 2018 and followed during the subsequent 12-month period for change in weight (primary trial outcome), body composition, metabolic markers, diet, physical activity, sleep, and psychological mediators/moderators of WLM (secondary trial outcomes). For the present study, a total of 967 NoHoW participants were included, of which 69.6% were women, the mean age was 45.8 years (SD 11.5), the mean baseline BMI was 29.5 kg/m2 (SD 5.1), and the mean weight loss prior to baseline assessments was 11.4 kg (SD 6.4). Objectively measured sleep was collected using the Fitbit Charge 2 (FC2), from which sleep duration, sleep duration variability, sleep onset, and sleep onset variability were assessed across 14 days close to baseline examinations. The primary outcomes were 12-month changes in body weight (BW) and body fat percentage (BF%). The secondary outcomes were 12-month changes in obesity-related metabolic markers (blood pressure, low- and high-density lipoproteins [LDL and HDL], triglycerides [TGs], and glycated haemoglobin [HbA1c]). Analysis of covariance and multivariate linear regressions were conducted with sleep-related variables as explanatory and subsequent changes in BW, BF%, and metabolic markers as response variables. We found no evidence that sleep duration, sleep duration variability, or sleep onset were associated with 12-month weight regain or change in BF%. A higher between-day variability in sleep onset, assessed using the standard deviation across all nights recorded, was associated with weight regain (0.55 kg per hour [95% CI 0.10 to 0.99]; P = 0.016) and an increase in BF% (0.41% per hour [95% CI 0.04 to 0.78]; P = 0.031). Analyses of the secondary outcomes showed that a higher between-day variability in sleep duration was associated with an increase in HbA1c (0.02% per hour [95% CI 0.00 to 0.05]; P = 0.045). Participants with a sleep onset between 19:00 and 22:00 had the greatest reduction in diastolic blood pressure (DBP) (P = 0.02) but also the most pronounced increase in TGs (P = 0.03). The main limitation of this study is the observational design. Hence, the observed associations do not necessarily reflect causal effects. CONCLUSION: Our results suggest that maintaining a consistent sleep onset is associated with improved WLM and body composition. Sleep onset and variability in sleep duration may be associated with subsequent change in different obesity-related metabolic markers, but due to multiple-testing, the secondary exploratory outcomes should be interpreted cautiously. TRIAL REGISTRATION: The trial was registered with the ISRCTN registry (ISRCTN88405328).

Association between objectively measured sleep duration, adiposity and weight loss history.

BACKGROUND: An association between sleep and obesity has been suggested in several studies, but many previous studies relied on self-reported sleep and on BMI as the only adiposity measure. Moreover, a relationship between weight loss history and attained sleep duration has not been thoroughly explored. DESIGN: The study comprised of 1202 participants of the European NoHoW trial who had achieved a weight loss of ≥5% and had a BMI of ≥25 kg/m2 prior to losing weight. Information was available on objectively measured sleep duration (collected during 14 days), adiposity measures, weight loss history and covariates. Regression models were conducted with sleep duration as the explanatory variable and BMI, fat mass index (FMI), fat-free mass index (FFMI) and waist-hip ratio (WHR) as response variables. Analyses were conducted with 12-month weight loss, frequency of prior weight loss attempts or average duration of weight maintenance after prior weight loss attempts as predictors of measured sleep duration. RESULTS: After adjusting for physical activity, perceived stress, smoking, alcohol consumption, education, sex and age, sleep duration was associated to BMI (P < 0.001), with the highest BMI observed in the group of participants sleeping <6 h a day [34.0 kg/m2 (95% CI: 31.8-36.1)]. Less difference in BMI was detected between the remaining groups, with the lowest BMI observed among participants sleeping 8-<9 h a day [29.4 kg/m2 (95% CI: 28.8-29.9)]. Similar results were found for FMI (P = 0.008) and FFMI (P < 0.001). We found no association between sleep duration and WHR. Likewise, we found no associations between weight loss history and attained sleep duration. CONCLUSION: In an overweight population who had achieved a clinically significant weight loss, short sleep duration was associated with higher BMI, with similar associations for fat and lean mass. We found no evidence of association between weight loss history and attained sleep duration.

Associations between objective measures of physical activity, sleep and stress levels among preschool children.

BACKGROUND: Cortisol is often used as a biological marker for stress. When measured in urine or serum, representing a short-term measurement of the hormone, it has been associated with unfavorable sleep characteristics and both low and high physical activity levels. However, cortisol in hair represents a long-term stress measure and has been suggested as a promising new marker for chronic stress. Therefore, we aimed to examine the association between objectively measured sleep, physical activity and hair cortisol levels in preschool children. METHODS: In order to obtain objective measures of physical activity and sleep habits, 54 children aged 2-6 years wore an ActiGraph for 5 consecutive days and nights. For chronic stress measurements of each child, hair was cut from the back of the head close to the scalp for analysis of cortisol levels. Associations between measured sleep quality and quantity and level of physical activity and hair cortisol levels were estimated using linear regression analysis, presented as ß. Results were adjusted for sex, age and BMI z-score. RESULTS: We found no significant association between log-transformed cortisol (pg/mg) and sleep duration (hours) (ß = - 0.0016, p = 0.99), sleep efficiency (ß = - 3.1, p = 0.18), sleep latency (ß = 0.015, p = 0.16) or physical activity level (100 counts per min) (ß = 0.014, p = 0.22). However, sleep latency (min) was directly associated with physical activity (counts per min) levels (ß = 35.2, p = 0.02), while sleep duration (hours) (ß = - 142.1, p = 0.55) and sleep efficiency (%) (ß = - 4087, p = 0.26) showed no significant associations. CONCLUSIONS: In our study, a high physical activity level was associated with poorer sleep habits. Neither sleep quality nor physical activity were related to long term cortisol exposure. These results are among the first to study associations between objectively measured sleep, physical activity and chronic cortisol levels among preschool children. More and larger studies are therefore needed.

More Frequent Intake of Regular Meals and Less Frequent Snacking Are Weakly Associated with Lower Long-Term Gains in Body Mass Index and Fat Mass in Middle-Aged Men and Women.

BACKGROUND: Few studies have examined the relationship between eating frequency and long-term change in body weight, and the results have been inconsistent. OBJECTIVE: We examined the associations between eating frequency and 6-y changes in body mass index (BMI; in kg/m2), fat mass, fat-free mass, body fat percentage, and waist circumference. METHODS: The study consisted of Danish men (n = 1080) and women (n = 1044) aged 35-67 y with repeated measures of eating frequency, adiposity, and covariates during 11 y. Multiple linear regression was used to assess the associations between baseline eating frequency and subsequent change in BMI, fat mass, fat-free mass, fat percentage, and waist circumference, as well as the association between initial change in eating frequency and subsequent change in the same outcomes. RESULTS: Total baseline eating frequency was not associated with change in outcomes. However, when separately examining regular meals and snacks, each additional daily meal was associated with a subsequent 6-y change in BMI of -0.14 (95% CI: -0.27, -0.00). Similar tendencies of inverse associations were found for change in fat mass (P = 0.04), fat-free mass (P = 0.07), and waist circumference (P = 0.05). We found no association between initial change in total eating frequency and subsequent change in outcomes. However, each additional daily regular meal after 5 y was associated with a subsequent 6-y change in BMI of -0.16 (95% CI: -0.30, -0.01). Inverse associations were also seen for fat (P = 0.04) and fat-free mass (P = 0.05). In contrast, an increase in daily frequency of snacking was associated with an increase in fat mass (P = 0.04) and fat percentage (P = 0.02). CONCLUSIONS: Our results indicate that total frequency of eating has little or no influence on adiposity among middle-aged Danish men and women. Consumption of regular meals, but not snack consumption, showed a weak inverse association with longitudinal gains in BMI.

Adolescent wine consumption is inversely associated with long-term weight gain: results from follow-up of 20 or 22 years.

BACKGROUND: Several studies have suggested a link between the type of alcoholic beverage consumption and body weight. However, results from longitudinal studies have been inconsistent, and the association between adolescent alcohol consumption long-term weight gain has generally not been examined. METHODS: The study was based on data from 720 Danish adolescents aged between 15 to 19 years at baseline from the Danish Youth and Sports Study (YSS). Self-reported alcohol use, height, weight, smoking, social economic status (SES) and physical activity levels were assessed in baseline surveys conducted in 1983 and 1985, and in the follow up survey which was conducted in 2005. Multiple linear regression analyses were used to examine the association between alcohol consumption in adolescence and subsequent weight gain later in midlife. RESULTS: There was no significant association between total alcohol consumption during adolescence and change in BMI into midlife (P = 0.079) (ß - 0.14; 95% CI -0.28, 0.005). Wine consumption was found to be inversely associated to subsequent BMI gain (P = 0.001) (ß - 0.46; 95% CI -0.82, - 0.09) while the results were not significant for beer and spirit. The relationship did not differ by gender, but smoking status was found to modify the relationship, and the inverse association between alcohol and BMI gain was seen only among non-smokers (P = 0.01) (ß - 0.24; 95% CI -0.41, - 0.06) while no association was found among smokers. Neither adolescent nor attained socioeconomic status in adulthood modified the relationship between alcohol intake and subsequent BMI gain. CONCLUSION: Among non-smoking adolescents, consumption of alcohol, and in particular wine, seems to be associated with less weight gain until midlife. TRIAL REGISTRATION: The YSS cohort was retrospectively registered on August 2017. (Study ID number: NCT03244150 ).

Alcohol consumption and its interaction with adiposity-associated genetic variants in relation to subsequent changes in waist circumference and body weight.

BACKGROUND: Studies have suggested a link between alcohol intake and adiposity. However, results from longitudinal studies have been inconsistent, and a possible interaction with genetic predisposition to adiposity measures has often not been taken into account. OBJECTIVE: To examine the association between alcohol intake recorded at baseline and subsequent annual changes in body weight (∆BW), waist circumference (ΔWC) and WC adjusted for BMI (ΔWCBMI), and to test for interaction with genetic predisposition scores based on single nucleotide polymorphisms (SNPs) associated with various forms of adiposity. METHOD: This study included a total of 7028 adult men and women from MONICA, the Diet, Cancer and Health cohort (DCH), and the Inter99 studies. We combined 50 adiposity-associated SNPs into four scores indicating genetic predisposition to BMI, WC, WHRBMI and all three traits combined. Linear regression was used to examine the association of alcohol intake (drinks of 12 g (g) alcohol/day) with ΔBW, ΔWC, and ΔWCBMI, and to examine possible interactions with SNP-scores. Results from the analyses of the individual cohorts were combined in meta-analyses. RESULTS: Each additional drink/day was associated with a ΔBW/year of -18.0 g (95% confidence interval (CI): -33.4, -2.6, P = 0.02) and a ΔWC of -0.3 mm/year (-0.5, -0.0, P = 0.03). In analyses of women only, alcohol intake was associated with a higher ΔWCBMI of 0.5 mm/year (0.2, 0.9, P = 0.002) per drink/day. Overall, we found no statistically significant interactions between the four SNP-scores and alcohol intake in relation to changes in adiposity measures. However in analyses of women separately, we found interaction between the complete score of all 50 SNPs and alcohol intake in relation to ΔBW (P for interaction = 0.03). No significant interaction was observed among the men. CONCLUSION: Alcohol intake was associated with a decrease in BW and WC among men and women, and an increase in WCBMI among women only. We found no strong indication that these associations depend on a genetic predisposition to adiposity. TRIAL REGISTRATION: Registry: ClinicalTrials.gov Trial number: CT00289237 , Registered: 19 September 2005 retrospectively registered.

Effects of the Healthy Start randomized intervention on dietary intake among obesity-prone normal-weight children.

OBJECTIVE: The study aimed to evaluate the impact of a 15-month intervention on dietary intake conducted among obesity-prone normal-weight pre-school children. DESIGN: Information on dietary intake was obtained using a 4 d diet record. A diet quality index was adapted to assess how well children's diet complied with the Danish national guidelines. Linear regression per protocol and intention-to-treat analyses of differences in intakes of energy, macronutrients, fruit, vegetables, fish, sugar-sweetened beverages and diet quality index between the two groups were conducted. SETTING: The Healthy Start study was conducted during 2009-2011, focusing on changing diet, physical activity, sleep and stress management to prevent excessive weight gain among Danish children. SUBJECTS: From a population of 635 Danish pre-school children, who had a high birth weight (≥4000 g), high maternal pre-pregnancy BMI (≥28·0 kg/m2) or low maternal educational level (<10 years of schooling), 285 children completed the intervention and had complete information on dietary intake. RESULTS: Children in the intervention group had a lower energy intake after the 15-month intervention (group means: 5·29 v. 5·59 MJ, P=0·02) compared with the control group. We observed lower intakes of carbohydrates and added sugar in the intervention group compared with the control group after the intervention (P=0·002, P=0·01). CONCLUSIONS: The intervention resulted in a lower energy intake, particularly from carbohydrates and added sugar after 15 months of intervention, suggesting that dietary intake can be changed in a healthier direction in children predisposed to obesity.

Intake of Total and Subgroups of Fat Minimally Affect the Associations between Selected Single Nucleotide Polymorphisms in the PPARγ Pathway and Changes in Anthropometry among European Adults from Cohorts of the DiOGenes Study.

BACKGROUND: Although the peroxisome proliferator-activated receptor γ (PPARγ) pathway is central in adipogenesis, it remains unknown whether it influences change in body weight (BW) and whether dietary fat has a modifying effect on the association. OBJECTIVES: We examined whether 27 single nucleotide polymorphisms (SNPs) within 4 genes in the PPARγ pathway are associated with the OR of being a BW gainer or with annual changes in anthropometry and whether intake of total fat, monounsaturated fat, polyunsaturated fat, or saturated fat has a modifying effect on these associations. METHODS: A case-noncase study included 11,048 men and women from cohorts in the European Diet, Obesity and Genes study; 5552 were cases, defined as individuals with the greatest BW gain during follow-up, and 6548 were randomly selected, including 5496 noncases. We selected 4 genes [CCAAT/enhancer binding protein ß (CEBPB), phosphoenolpyruvate carboxykinase 2, PPARγ gene (PPARG), and sterol regulatory element binding transcription factor 1] according to evidence about biologic plausibility for interactions with dietary fat in weight regulation. Diet was assessed at baseline, and anthropometry was followed for 7 y. RESULTS: The ORs for being a BW gainer for the 27 genetic variants ranged from 0.87 (95% CI: 0.79, 1.03) to 1.12 (95% CI: 0.96, 1.22) per additional minor allele. Uncorrected, CEBPB rs4253449 had a significant interaction with the intake of total fat and subgroups of fat. The OR for being a BW gainer for each additional rs4253449 minor allele per 100 kcal higher total fat intake was 1.07 (95% CI: 1.02, 1.12; P = 0.008), and similar associations were found for subgroups of fat. CONCLUSIONS: Among European men and women, the influence of dietary fat on associations between SNPs in the PPARγ pathway and anthropometry is likely to be absent or marginal. The observed interaction between rs4253449 and dietary fat needs confirmation.

Dietary ascorbic acid and subsequent change in body weight and waist circumference: associations may depend on genetic predisposition to obesity--a prospective study of three independent cohorts.

BACKGROUND: Cross-sectional data suggests that a low level of plasma ascorbic acid positively associates with both Body Mass Index (BMI) and Waist Circumference (WC). This leads to questions about a possible relationship between dietary intake of ascorbic acid and subsequent changes in anthropometry, and whether such associations may depend on genetic predisposition to obesity. Hence, we examined whether dietary ascorbic acid, possibly in interaction with the genetic predisposition to a high BMI, WC or waist-hip ratio adjusted for BMI (WHR), associates with subsequent annual changes in weight (∆BW) and waist circumference (∆WC). METHODS: A total of 7,569 participants' from MONICA, the Diet Cancer and Health study and the INTER99 study were included in the study. We combined 50 obesity associated single nucleotide polymorphisms (SNPs) in four genetic scores: a score of all SNPs and a score for each of the traits (BMI, WC and WHR) with which the SNPs associate. Linear regression was used to examine the association between ascorbic acid intake and ΔBW or ΔWC. SNP-score × ascorbic acid interactions were examined by adding product terms to the models. RESULTS: We found no significant associations between dietary ascorbic acid and ∆BW or ∆WC. Regarding SNP-score × ascorbic acid interactions, each additional risk allele of the 14 WHR associated SNPs associated with a ∆WC of 0.039 cm/year (P = 0.02, 95% CI: 0.005 to 0.073) per 100 mg/day higher ascorbic acid intake. However, the association to ∆WC only remained borderline significant after adjustment for ∆BW. CONCLUSION: In general, our study does not support an association between dietary ascorbic acid and ∆BW or ∆WC, but a diet with a high content of ascorbic acid may be weakly associated to higher WC gain among people who are genetically predisposed to a high WHR. However, given the quite limited association any public health relevance is questionable.

Comparing self-reported energy intake using an online dietary tool with energy expenditure by an activity tracker.

OBJECTIVE: The aim of this study was to compare self-reported total energy intake (TEI) collected using an online multiple-pass 24-h dietary recall tool (Intake24) with total energy expenditure (TEE) estimated from Fitbit Charge 2-improved algorithms in adults from the NoHoW trial (12-mo weight maintenance after free-living weight loss). METHODS: Bland-Altman plots were used to assess the level of agreement between TEI and TEE at baseline and after 12 mo. The ratio of TEI to TEE was also calculated. RESULTS: Data from 1323 participants (71% female) was included in the analysis (mean ± SD: age 45 ± 12 y, body mass index 29.7 ± 5.4 kg/m2, initial weight loss 11.5 ± 6.5 kg). The TEI was lower than TEE on average by 33%, with limits of agreement ranging from -91% to +25%. Men, younger individuals, those with higher body mass index, those with the greater weight loss before enrollment, and those who gained weight during the study underestimated to a greater extent. CONCLUSIONS: These findings contribute to the ongoing research examining the validity of technology-based dietary assessment tools.

Can change in phase angle predict the risk of morbidity and mortality during an 18-year follow-up period? A cohort study among adults.

Introduction: Phase angle (PhA, degrees), measured via bioimpedance (BIA, 50 kHz), is an index that has been used as an indicator of nutritional status and mortality in several clinical situations. This study aimed to determine the relationship between 6-year changes in PhA and total mortality as well as the risk of incident morbidity and mortality from cardiovascular disease (CVD) and coronary heart disease (CHD) during 18 years of follow-up among otherwise healthy adults. Methods: A random subset (n = 1,987) of 35-65 years old men and women was examined at the baseline in 1987/1988 and 6 years later in 1993/1994. Measures included weight, height, and whole-body BIA, from which PhA was calculated. Information on lifestyle was obtained through a questionnaire. The associations between 6-year PhA changes (ΔPhA) and incident CVD and CHD were assessed by Cox proportional hazard models. The median value of ΔPhA was used as the reference value. The hazard ratio (HR) model and confidence intervals (CIs) of incident CVD and CHD were used according to the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ΔPhA. Results: During 18 years of follow-up, 205 women and 289 men died. A higher risk of both total mortality and incident CVD was present below the 50th percentile (Δ = -0.85°). The highest risk was observed below the 5th percentile (ΔPhA = -2.60°) in relation to total mortality (HR: 1.55; 95% CI: 1.10-2.19) and incident CVD (HR: 1.52; 95% CI: 1.16-2.00). Discussion: The larger the decrease in PhA, the higher the risk of early mortality and incident CVD over the subsequent 18 years. PhA is a reliable and easy measure that may help identify those apparently healthy individuals who may be at increased risk of future CVD or dying prematurely. More studies are needed to confirm our results before it can be definitively concluded that PhA changes can improve clinical risk prediction.

Evidence for the protein leverage hypothesis in preschool children prone to obesity.

BACKGROUND & AIMS: The protein leverage hypothesis (PLH) proposed that strict regulation of protein intake drives energy overconsumption and obesity when diets are diluted by fat and/or carbohydrates. Evidence about the PLH has been found in adults, while studies in children are limited. Thus, we aimed to test the PLH by assessing the role of dietary protein on macronutrients, energy intake, and obesity risk using data from preschool children followed for 1.3 years. METHODS: 553 preschool children aged 2-6 years from the 'Healthy Start' project were included. EXPOSURES: The proportion of energy intake from protein, fat, and carbohydrates collected from a 4-day dietary record. OUTCOMES: Energy intake, BMI z-score, fat mass (FM) %, waist- (WHtR) and hip-height ratio (HHtR). Power function analysis was used to test the leverage of protein on energy intake. Mixture models were used to explore interactive associations of macronutrient composition on all these outcomes, with results visualized as response surfaces on the nutritional geometry. RESULTS: Evidence for the PLH was confirmed in preschool children. The distribution of protein intake (% of MJ, IQR: 3.2) varied substantially less than for carbohydrate (IQR: 5.7) or fat (IQR: 6.3) intakes, suggesting protein intake is most tightly regulated. Absolute energy intake varied inversely with dietary percentage energy from protein (L = -0.14, 95% CI: -0.25, -0.04). Compared to children with high fat or carbohydrate intakes, children with high dietary protein intake (>20% of MJ) had a greater decrease in WHtR and HHtR over the 1.3-year follow-up, offering evidence for the PLH in prospective analysis. But no association was observed between macronutrient distribution and changes in BMI z-score or FM%. CONCLUSIONS: In this study in preschool children, protein intake was the most tightly regulated macronutrient, and energy intake was an inverse function of dietary protein concentration, indicating the evidence for protein leverage. Increases in WHtR and HHtR were principally associated with the dietary protein dilution, supporting the PLH. These findings highlight the importance of protein in children's diets, which seems to have significant implications for childhood obesity risk and overall health.

Attained body mass index among children attending rural outdoor or urban conventional kindergartens.

Objective: This study aimed to examine whether children in rural outdoor kindergartens had attained a lower body mass index z-score (BMIz) and were at lower risk of overweight after school entrance compared to children in urban conventional kindergartens. Methods: This is a longitudinal observational study of 1,544 children from outdoor kindergartens and 1,640 from conventional kindergartens. The mean age at kindergarten enrolment was 3.5 years (SD: 0.9) in the outdoor kindergartens and 3.6 years (SD: 1.0) in the conventional kindergartens. Anthropometry was measured after school entry by school health nurses when the children were 6 to 8 years old. Attained BMIz was included as the primary outcome. The risk of attaining overweight (including obesity) was included as a secondary outcome. Register-based information was available on potential confounding factors. Linear and logistic regression models were used to assess group differences in outcome measures. Results: Our basic models, with information on outcome, kindergarten type, and birth weight showed a borderline statistically significantly lower attained BMIz (-0.07 [95% CI: -0.14, 0.00], P = 0.060) and a lower risk of overweight (adjusted risk ratio: 0.83 [95% CI: 0.72, 0.97], P = 0.016) among children attending outdoor kindergartens. However, when adjusting for sociodemographic factors and parental BMI, there was no evidence of differences in attained BMIz (P = 0.153) or overweight (P = 0.967). Conclusion: When considering confounding factors, our findings indicate no differences in attained BMIz or risk of overweight after school entry among children attending rural outdoor kindergartens compared to those attending urban conventional kindergartens.

Testing motivational and self-regulatory mechanisms of action on device-measured physical activity in the context of a weight loss maintenance digital intervention: A secondary analysis of the NoHoW trial.

BACKGROUND: To date, few digital behavior change interventions for weight loss maintenance focusing on long-term physical activity promotion have used a sound intervention design grounded on a logic model underpinned by behavior change theories. The current study is a secondary analysis of the weight loss maintenance NoHoW trial and investigated putative mediators of device-measured long-term physical activity levels (six to 12 months) in the context of a digital intervention. METHODS: A subsample of 766 participants (Age = 46.2 ± 11.4 years; 69.1% female; original NoHoW sample: 1627 participants) completed all questionnaires on motivational and self-regulatory variables and had all device-measured physical activity data available for zero, six and 12 months. We examined the direct and indirect effects of Virtual Care Climate on post intervention changes in moderate-to-vigorous physical activity and number of steps (six to 12 months) through changes in the theory-driven motivational and self-regulatory mechanisms of action during the intervention period (zero to six months), as conceptualized in the logic model. RESULTS: Model 1 tested the mediation processes on Steps and presented a poor fit to the data. Model 2 tested mediation processes on moderate-to-vigorous physical activity and presented poor fit to the data. Simplified models were also tested considering the autonomous motivation and the controlled motivation variables independently. These changes yielded good results and both models presented very good fit to the data for both outcome variables. Percentage of explained variance was negligible for all models. No direct or indirect effects were found from Virtual Care Climate to long term change in outcomes. Indirect effects occurred only between the sequential paths of the theory-driven mediators. CONCLUSION: This was one of the first attempts to test a serial mediation model considering psychological mechanisms of change and device-measured physical activity in a 12-month longitudinal trial. The model explained a small proportion of variance in post intervention changes in physical activity. We found different pathways of influence on theory-driven motivational and self-regulatory mechanisms but limited evidence that these constructs impacted on actual behavior change. New approaches to test these relationships are needed. Challenges and several alternatives are discussed. TRIAL REGISTRATION: ISRCTN Registry, ISRCTN88405328. Registered December 16, 2016, https://www.isrctn.com/ISRCTN88405328.