New insights in the mechanisms of weight-loss maintenance: Summary from a Pennington symposium.

Obesity is a chronic disease that affects more than 650 million adults worldwide. Obesity not only is a significant health concern on its own, but predisposes to cardiometabolic comorbidities, including coronary heart disease, dyslipidemia, hypertension, type 2 diabetes, and some cancers. Lifestyle interventions effectively promote weight loss of 5% to 10%, and pharmacological and surgical interventions even more, with some novel approved drugs inducing up to an average of 25% weight loss. Yet, maintaining weight loss over the long-term remains extremely challenging, and subsequent weight gain is typical. The mechanisms underlying weight regain remain to be fully elucidated. The purpose of this Pennington Biomedical Scientific Symposium was to review and highlight the complex interplay between the physiological, behavioral, and environmental systems controlling energy intake and expenditure. Each of these contributions were further discussed in the context of weight-loss maintenance, and systems-level viewpoints were highlighted to interpret gaps in current approaches. The invited speakers built upon the science of obesity and weight loss to collectively propose future research directions that will aid in revealing the complicated mechanisms involved in the weight-reduced state.

Lifestyle factors and adolescent depressive symptomatology: Associations and effect sizes of diet, physical activity and sedentary behaviour.

OBJECTIVE: Depression affects many Australian adolescents. Research points to the potential of lifestyle improvement for the population-level prevention of mental disorders. However, most studies examine single relationships without considering the combined contribution of lifestyle factors to variance in depression. This study examined associations between adolescent diet, physical activity and screen time behaviours and depressive symptomatology. METHODS: A cross-sectional sample of year 8 and 10 students was recruited from 23 participating schools in 18 Victorian communities. Students were recruited using opt-out consent, resulting in 3295 participants from 4680 registered school enrolments (Participation Rate: 70.4%). Participants completed a supervised self-report questionnaire comprising Moods and Feelings Questionnaire-Short Form, an assessment of physical activity and sedentary behaviours during and outside school, and weekly food intake. Surveyed covariates included hours of sleep per night, age, socio-economic status and measured anthropometry. A hierarchical regression stratified by gender was conducted, with dichotomised Moods and Feelings Questionnaire-Short Form score as the outcome, and screen time, physical activity and dietary patterns as predictors. Nested regression analyses were then conducted to ascertain the variance in Moods and Feelings Questionnaire-Short Form score attributable to each significant predictor from the initial regression. RESULTS: Increased scores on an unhealthy dietary pattern (odds ratio = 1.18; 95% confidence interval = [1.07, 1.32]) and physical activity guideline attainment (0.91; [0.85, 0.97]) were associated with depressive symptomatology in males, while screen time guideline attainment (0.95; [0.91, 0.98]) was associated with depression in females. No association was observed between healthy diet pattern and Moods and Feelings Questionnaire-Short Form. Overall, effect sizes were generally small, and the regression model accounted for 5.22% of Moods and Feelings Questionnaire-Short Form variance. CONCLUSION: Gender-specific associations were observed between physical activity and both sedentary and dietary behaviours and depressive symptomatology among adolescents, although reverse causality cannot be refuted at this stage. Lifestyle behaviours may represent a modifiable target for the prevention of depressive symptomatology in adolescents.

Sizing the association between lifestyle behaviours and fatness in a large, heterogeneous sample of youth of multiple ethnicities from 4 countries.

BACKGROUND: The magnitude of the relationship between lifestyle risk factors for obesity and adiposity is not clear. The aim of this study was to clarify this in order to determine the level of importance of lifestyle factors in obesity aetiology. METHODS: A cross-sectional analysis was carried out on data on youth who were not trying to change weight (n = 5714), aged 12 to 22 years and from 8 ethnic groups living in New Zealand, Australia, Fiji and Tonga. Demographic and lifestyle data were measured by questionnaires. Fatness was measured by body mass index (BMI), BMI z-score and bioimpedance analysis, which was used to estimate percent body fat and total fat mass (TFM). Associations between lifestyle and body composition variables were examined using linear regression and forest plots. RESULTS: TV watching was positively related to fatness in a dose-dependent manner. Strong, dose-dependent associations were observed between fatness and soft drink consumption (positive relationship), breakfast consumption (inverse relationship) and after-school physical activity (inverse relationship). Breakfast consumption-fatness associations varied in size across ethnic groups. Lifestyle risk factors for obesity were associated with percentage differences in body composition variables that were greatest for TFM and smallest for BMI. CONCLUSIONS: Lifestyle factors were most strongly related to TFM, which suggests that studies that use BMI alone to quantify fatness underestimate the full effect of lifestyle on adiposity. This study clarifies the size of lifestyle-fatness relationships observed in previous studies.

Utility-based quality of life associated with overweight and obesity: the Australian diabetes, obesity, and lifestyle study.

OBJECTIVE: This study aimed to estimate utility-based quality of life (UQoL) differences between healthy body weight and excess body weight categories. DESIGN AND METHODS: Cross-sectional analysis of 10,959 adults, participating in baseline data collection of the nationally representative Australian Diabetes, Obesity, and Lifestyle (AusDiab) Study was undertaken. Height and weight were measured by trained personnel. Body weight categories were assigned as healthy weight, overweight, and obesity subclasses I, II and III. UQoL was assessed using the SF-6D, which captures physical functioning, role limitation, social functioning, pain, mental health, and vitality on a score of 0.00-1.00 (worst-best). The relationship between body weight categories and UQoL was assessed using linear regression, adjusting for age, sex, education, and smoking. RESULTS: Relative to the healthy weight group (mean UQoL score 0.77), mean adjusted UQoL differences (95% confidence intervals) were 0.001 (-0.008, 0.010) for overweight, -0.012 (-0.022, -0.001) for class-I obese, -0.020 (-0.041, 0.001) for class-II obese, and -0.069 (-0.099, -0.039) for class-III obese groups. Adding metabolic syndrome markers to the covariates had little impact on these differences. CONCLUSION: Results confirmed an inverse dose-response relationship between body weight and UQoL in this study of Australian adults. This highlights the need to incorporate UQoL measures which are sensitive to the subclasses of obesity when evaluating obesity interventions.

Healthcare utilization and costs in severely obese subjects before bariatric surgery.

This study examined healthcare utilization and associated costs for a severely obese population before receiving bariatric surgery relative to an age- and sex-matched sample from the Australian general population. Severely obese subjects receiving laparoscopic adjustable gastric banding (LAGB) surgery in 2009 (n = 11,769) were identified. Utilization of medical services and pharmaceuticals in the 3.5 years before surgery were ascertained for each severely obese subject through linkage with Medicare, Australia's universal health insurance scheme. Equivalent data were retrieved for each subject from the matched general population sample (n = 140,000). Severely obese subjects utilized significantly more medical services annually compared to the general population (mean: 22.8 vs. 12.1/person, standardized incidence ratio (SIR): 1.89 (95% confidence interval (CI) 1.88-1.89)), translating to twofold higher mean annual costs (Australian $1,140 vs. $567/person). The greatest excess costs in the obese related to consultations with general practitioners, psychiatrists/psychologists and other specialists, investigations for obstructive sleep apnea, and in vitro fertilization. Severely obese subjects also utilized significantly more pharmaceutical prescriptions annually (mean: 11.4 vs. 5.3/person, SIR 2.18 (95% CI: 2.17-2.19)), translating to 2.2-fold higher mean annual costs ($595/person vs. $270/person). The greatest excess costs in the obese related to diabetes drugs, lipid-modifying agents, psychoanaleptics, acid-related disorder drugs, agents acting on the rennin-angiotensin system, immunosuppressants, and obstructive airway disease drugs. Overall, healthcare costs in the severely obese population were more than double those incurred by the general population.

The global obesity pandemic: shaped by global drivers and local environments.

The simultaneous increases in obesity in almost all countries seem to be driven mainly by changes in the global food system, which is producing more processed, affordable, and effectively marketed food than ever before. This passive overconsumption of energy leading to obesity is a predictable outcome of market economies predicated on consumption-based growth. The global food system drivers interact with local environmental factors to create a wide variation in obesity prevalence between populations. Within populations, the interactions between environmental and individual factors, including genetic makeup, explain variability in body size between individuals. However, even with this individual variation, the epidemic has predictable patterns in subpopulations. In low-income countries, obesity mostly affects middle-aged adults (especially women) from wealthy, urban environments; whereas in high-income countries it affects both sexes and all ages, but is disproportionately greater in disadvantaged groups. Unlike other major causes of preventable death and disability, such as tobacco use, injuries, and infectious diseases, there are no exemplar populations in which the obesity epidemic has been reversed by public health measures. This absence increases the urgency for evidence-creating policy action, with a priority on reduction of the supply-side drivers.

Reducing obesity in early childhood: results from Romp & Chomp, an Australian community-wide intervention program.

BACKGROUND: There is growing evidence that community-based interventions can reduce childhood obesity in older children. OBJECTIVE: We aimed to determine the effectiveness of the Romp & Chomp intervention in reducing obesity and promoting healthy eating and active play in children aged 0-5 y. DESIGN: Romp & Chomp was a community-wide, multisetting, multistrategy intervention conducted in Australia from 2004 to 2008. The intervention occurred in a large regional city (Geelong) with a target group of 12,000 children and focused on community capacity building and environmental (political, sociocultural, and physical) changes to increase healthy eating and active play in early-childhood care and educational settings. The evaluation was repeat cross-sectional with a quasiexperimental design and comparison sample. Main outcome measures were body mass index (BMI), standardized BMI (zBMI; according to the Centers for Disease Control and Prevention 2000 reference charts), and prevalence of overweight/obesity and obesity-related behaviors in children aged 2 and 3.5 y. RESULTS: After the intervention there was a significantly lower mean weight, BMI, and zBMI in the 3.5-y-old subsample and a significantly lower prevalence of overweight/obesity in both the 2- and 3.5-y-old subsamples (by 2.5 and 3.4 percentage points, respectively) than in the comparison sample (a difference of 0.7 percentage points; P < 0.05) compared with baseline values. Intervention child-behavioral data showed a significantly lower intake of packaged snacks (by 0.23 serving), fruit juice (0.52 serving), and cordial (0.43 serving) than that in the comparison sample (all P < 0.05). CONCLUSION: A community-wide multisetting, multistrategy intervention in early-childhood settings can reduce childhood obesity and improve young children's diets. This trial was registered with the Australian Clinical Trials Registry at anzctr.org.au as ACTRN12607000374460.

A systematic policy approach to changing the food system and physical activity environments to prevent obesity.

As obesity prevention becomes an increasing health priority in many countries, including Australia and New Zealand, the challenge that governments are now facing is how to adopt a systematic policy approach to increase healthy eating and regular physical activity. This article sets out a structure for systematically identifying areas for obesity prevention policy action across the food system and full range of physical activity environments. Areas amenable to policy intervention can be systematically identified by considering policy opportunities for each level of governance (local, state, national, international and organisational) in each sector of the food system (primary production, food processing, distribution, marketing, retail, catering and food service) and each sector that influences physical activity environments (infrastructure and planning, education, employment, transport, sport and recreation). Analysis grids are used to illustrate, in a structured fashion, the broad array of areas amenable to legal and regulatory intervention across all levels of governance and all relevant sectors. In the Australian context, potential regulatory policy intervention areas are widespread throughout the food system, e.g., land-use zoning (primary production within local government), food safety (food processing within state government), food labelling (retail within national government). Policy areas for influencing physical activity are predominantly local and state government responsibilities including, for example, walking and cycling environments (infrastructure and planning sector) and physical activity education in schools (education sector). The analysis structure presented in this article provides a tool to systematically identify policy gaps, barriers and opportunities for obesity prevention, as part of the process of developing and implementing a comprehensive obesity prevention strategy. It also serves to highlight the need for a coordinated approach to policy development and implementation across all levels of government in order to ensure complementary policy action.