S. Allender

The economic burden of ill health due to diet, physical inactivity, smoking, alcohol and obesity in the UK: an update to 2006–07 NHS costs

BACKGROUND Estimates of the economic cost of risk factors for chronic disease to the NHS provide evidence for prioritization of resources for prevention and public health. Previous comparable estimates of the economic costs of poor diet, physical inactivity, smoking, alcohol and overweight/obesity were based on economic data from 1992-93. METHODS Diseases associated with poor diet, physical inactivity, smoking, alcohol and overweight/obesity were identified. Risk factor-specific population attributable fractions for these diseases were applied to disease-specific estimates of the economic cost to the NHS in the UK in 2006-07. RESULTS In 2006-07, poor diet-related ill health cost the NHS in the UK £5.8 billion. The cost of physical inactivity was £0.9 billion. Smoking cost was £3.3 billion, alcohol cost £3.3 billion, overweight and obesity cost £5.1 billion. CONCLUSION The estimates of the economic cost of risk factors for chronic disease presented here are based on recent financial data and are directly comparable. They suggest that poor diet is a behavioural risk factor that has the highest impact on the budget of the NHS, followed by alcohol consumption, smoking and physical inactivity.

Web search activity data accurately predict population chronic disease risk in the USA

Background The WHO framework for non-communicable disease (NCD) describes risks and outcomes comprising the majority of the global burden of disease. These factors are complex and interact at biological, behavioural, environmental and policy levels presenting challenges for population monitoring and intervention evaluation. This paper explores the utility of machine learning methods applied to population-level web search activity behaviour as a proxy for chronic disease risk factors. Methods Web activity output for each element of the WHOs Causes of NCD framework was used as a basis for identifying relevant web search activity from 2004 to 2013 for the USA. Multiple linear regression models with regularisation were used to generate predictive algorithms, mapping web search activity to Centers for Disease Control and Prevention (CDC) measured risk factor/disease prevalence. Predictions for subsequent target years not included in the model derivation were tested against CDC data from population surveys using Pearson correlation and Spearmans r. Results For 2011 and 2012, predicted prevalence was very strongly correlated with measured risk data ranging from fruits and vegetables consumed (r=0.81; 95% CI 0.68 to 0.89) to alcohol consumption (r=0.96; 95% CI 0.93 to 0.98). Mean difference between predicted and measured differences by State ranged from 0.03 to 2.16. Spearmans r for state-wise predicted versus measured prevalence varied from 0.82 to 0.93. Conclusions The high predictive validity of web search activity for NCD risk has potential to provide real-time information on population risk during policy implementation and other population-level NCD prevention efforts.

Healthy together Victoria and childhood obesity—a methodology for measuring changes in childhood obesity in response to a community-based, whole of system cluster randomized control trial

BackgroundHealthy Together Victoria (HTV) - a complex ‘whole of system’ intervention, including an embedded cluster randomized control trial, to reduce chronic disease by addressing risk factors (physical inactivity, poor diet quality, smoking and harmful alcohol use) among children and adults in selected communities in Victoria, Australia (Healthy Together Communities).ObjectivesTo describe the methodology for: 1) assessing changes in the prevalence of measured childhood obesity and associated risks between primary and secondary school students in HTV communities, compared with comparison communities; and 2) assessing community-level system changes that influence childhood obesity in HTC and comparison communities.MethodsTwenty-four geographically bounded areas were randomized to either prevention or comparison (2012). A repeat cross-sectional study utilising opt-out consent will collect objectively measured height, weight, waist and self-reported behavioral data among primary [Grade 4 (aged 9-10y) and Grade 6 (aged 11-12y)] and secondary [Grade 8 (aged 13-14y) and Grade 10 (aged 15-16y)] school students (2014 to 2018). Relationships between measured childhood obesity and system causes, as defined in the Foresight obesity systems map, will be assessed using a range of routine and customised data.ConclusionThis research methodology describes the beginnings of a state-wide childhood obesity monitoring system that can evolve to regularly inform progress on reducing obesity, and situate these changes in the context of broader community-level system change.

Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset.

For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.

A map of community-based obesity prevention initiatives in Australia following obesity funding 2009-2013.

Objective: Obesity is the single biggest public health threat to developed and developing economies. In concert with healthy public policy, multi‐strategy, multi‐level community‐based initiatives appear promising in preventing obesity, with several countries trialling this approach. In Australia, multiple levels of government have funded and facilitated a range of community‐based obesity prevention initiatives (CBI), heterogeneous in their funding, timing, target audience and structure. This paper aims to present a central repository of CBI operating in Australia during 2013, to facilitate knowledge exchange and shared opportunities for learning, and to guide professional development towards best practice for CBI practitioners.

The inter-section of political history and health policy in Asia--the historical foundations for health policy analysis.

One of the challenges for health reform in Asia is the diverse set of socio-economic and political structures, and the related variability in the direction and pace of health systems and policy reform. This paper aims to make comparative observations and analysis of health policy reform in the context of historical change, and considers the implications of these findings for the practice of health policy analysis. We adopt an ecological model for analysis of policy development, whereby health systems are considered as dynamic social constructs shaped by changing political and social conditions. Utilizing historical, social scientific and health literature, timelines of health and history for five countries (Cambodia, Myanmar, Mongolia, North Korea and Timor Leste) are mapped over a 30-50 year period. The case studies compare and contrast key turning points in political and health policy history, and examines the manner in which these turning points sets the scene for the acting out of longer term health policy formation, particularly with regard to the managerial domains of health policy making. Findings illustrate that the direction of health policy reform is shaped by the character of political reform, with countries in the region being at variable stages of transition from monolithic and centralized administrations, towards more complex management arrangements characterized by a diversity of health providers, constituency interest and financing sources. The pace of reform is driven by a countrys institutional capability to withstand and manage transition shocks of post conflict rehabilitation and emergence of liberal economic reforms in an altered governance context. These findings demonstrate that health policy analysis needs to be informed by a deeper understanding and questioning of the historical trajectory and political stance that sets the stage for the acting out of health policy formation, in order that health systems function optimally along their own historical pathways.

Sustaining obesity prevention in communities: a systematic narrative synthesis review

Obesity is a global problem for which sustainable solutions are yet to be realized. Community‐based interventions have improved obesity‐related behaviours and obesity in the short term. Few papers have explored how to make the interventions and their intended outcomes sustainable. The aim of this paper is to identify factors that contribute to the sustainability of community‐based obesity prevention interventions and their intended outcomes.

Composition of objectively measured physical activity and sedentary behaviour participation across the school-day, influence of gender and weight status: cross-sectional analyses among disadvantaged Victorian school children

Background The after-school period has been described as the ‘critical window’ for physical activity (PA) participation. However, little is known about the importance of this window compared with the before and during-school period among socioeconomically disadvantaged children, and influence of gender and weight status. Methods 39 out of 156 (RR=25%) invited primary schools across 26 local government areas in Victoria, Australia, consented to participate with 856 children (RR=36%) participating in the wider study. The analysis sample included 298 Grade 4 and Grade 6 children (mean age: 11.2±1.1; 44% male) whom met minimum accelerometry wear-time criteria and had complete height, weight and health-behaviours questionnaire data. Accelerometry measured duration in daily light-intensity PA (LPA), moderate-to-vigorous PA (MVPA) and sedentary time (ST) was calculated for before-school=8–8:59, during-school=9:00–15:29 and after-school=15:30–18:00. Bivariate and multivariable linear regression analyses were conducted. Results During-school represented the greatest accumulation of LPA and MVPA compared with the before and after-school periods. Boys engaged in 102 min/day of LPA (95% CI 98.5 to 104.9) and 62 min/day of MVPA (95% CI 58.9 to 64.7) during-school; girls engaged in 103 min/day of LPA (95% CI 99.7 to 106.5) and 45 min/day of MVPA (95% CI 42.9 to 47.4). Linear regression models indicated that girls with overweight or obesity engaged in significantly less LPA, MVPA and more time in ST during-school. Conclusions This study highlights the importance of in-school PA compared with after-school PA among socioeconomically disadvantage children whom may have fewer resources to participate in after-school PA.

Evaluation of complex community-based childhood obesity prevention interventions: Evaluating childhood obesity prevention

Multi‐setting, multi‐component community‐based interventions have shown promise in preventing childhood obesity; however, evaluation of these complex interventions remains a challenge.

Worlds apart: active (opt-in) consent underestimates the prevalence of obesity in a school-based survey. Evidence from the healthy together Victoria and childhood obesity (HPTVCO) study

Track 5: Populations and population health Session 29: Epidemiology T5:S29:01 The implications of differential trends in weight and waist circumference on population level obesity monitoring Gearon, E.*; Tanamas, S.; Loh, V.; Stevenson, C. and Peeters, A. Monash University; Baker IDI Heart and Diabetes Institute; Queensland University of Technology; Deakin University We aimed to quantify discordance in changes to waist circumference (WC) and weight between 1989 and 2012, and implications for trends in obesity classification for urban Australian adults. Using three nationally representative surveys from 1989, 2000 and 2012, we selected urban Australian adults aged 25 to 69 years with measured height, weight and WC. Linear regression was used to quantify increases in WC over time adjusted for weight, age and smoking status, and stratified by sex. We additionally quantified age-standardised trends in obesity prevalence classified by WC and/or body mass index (BMI) for each survey, and compared the proportion of individuals captured as obese according to BMI and WC, BMI but not WC, and WC but not BMI. Between 1989 and 2012, WC increased significantly more than would be expected from increases in weight, by 6.7cm (95% CI 6.2, 7.2) and 2.8cm (1.5, 4.1) for women (W) and men (M), respectively. While the proportion of women and men identified as obese between 1989 and 2012 according to BMI but not WC did not substantially change (2% to 1% (W) and 3% to 3% (M)), we observed increases in the proportion identified as obese according to BMI and WC (12% to 24% (W) and 9% to 24%(M)), and the proportion identified as obese according to WC but not BMI (4% to 19% (W) and 5% to 11%(M)). The nature of obesity may be changing for urban Australian adults, and as a result WC may be a more comprehensive indicator of obesity for both Australia and internationally. T5:S29:02 Daytime napping and the risk of metabolic diseases: Dose-response meta-analysis Yamada, T.*; Shojima, N.; Yamauchi, T. and Kadowaki, T. Department of Diabetes and Metabolic Diseases, University of Tokyo Background: Sleep is an important component of a healthy life. The habit of napping is also widely prevalent around the world. Aims: We performed a meta-analysis to investigate the association between napping and the risk of metabolic diseases, and to quantify the potential dose-response relation. Key Methods: We searched electronic databases for articles published up to 2015. The adjusted relative risk and 95% confidence interval were calculated with the random effect model. Dose-response relations were also evaluated.