Prioritising and tackling socio-economic inequalities in obesity

This article discusses some of the recent trends in obesity and demonstrates why deeper consideration of differences in trends and intervention effectiveness across socioeconomicgroups is critical

Obesity and Trends in Life Expectancy

Background. Increasing levels of obesity over recent decades have been expected to lead to an epidemic of diabetes and a subsequent reduction in life expectancy, but instead all-cause and cardiovascular-specific mortality rates have decreased steadily i

The effect of sugar-sweetened beverage price increases and educational messages on beverage purchasing behavior among adults

There is a paucity of evidence regarding the impact of sugar sweetened beverage (SSB) price increases on beverage consumption, using individual-level data, for the population overall and for different socioeconomic groups. This study aimed to predict the impact of altered beverage prices and educational messages on consumer purchasing behavior. 2020 adults representative of the Australian population by age, gender and income completed a discrete choice experiment online in 2016. Each subject completed 20 choice scenarios in a hypothetical convenience store setting where subjects chose between seven SSB and non-SSB beverage options or a no beverage option. Beverage prices and volumes varied between scenarios. Half of participants (n = 1012) were randomly exposed to an educational poster discouraging SSB consumption prior to completing choice scenarios. We used discrete choice models to predict purchases under several policy proposals, overall and for income and SSB consumption frequency sub-groups. Compared to baseline prices, a 10% SSB price increase was predicted to reduce SSB purchases by 15.0% [95%CI -15.2, -14.7], and increase purchases of non-SSBs by +11.0% [95%CI 10.8, 11.2] and no beverage by +15.5% [95%CI 15.1, 15.9]. Effects were greater with a 20% SSB price increase. Across all policy scenarios, the highest income quintile had a similar absolute and slightly greater relative decrease in SSB purchases compared to the lowest quintile. Educational poster exposure reduced SSB choice for all groups, with a greater reduction in the lower compared to higher income group, and additively increased response to price changes. Our results support the use of population-wide SSB pricing and educational interventions to reduce demand across all income groups.This research was funded by a Monash University Faculty of Businessand Economics Interdisciplinary Grant. MB is supported by an AustralianGovernment Research Training Program Scholarship and a MonashUniversity Departmental Scholarship. KB is supported by a post-doctoralfellowship from the National Heart Foundation of Australia (grant numberPH 12 M 6824). AP is supported by a National Health and Medical ResearchCouncil (NHMRC) fellowship. EL is supported by an Australian ResearchCouncil (ARC) fellowship (grant number DE140101260

Obesity and Trends in Life Expectancy

Background. Increasing levels of obesity over recent decades have been expected to lead to an epidemic of diabetes and a subsequent reduction in life expectancy, but instead all-cause and cardiovascular-specific mortality rates have decreased steadily in most developed countries and life expectancy has increased. Methods. This paper suggests several factors that may be masking the effects of obesity on life expectancy. Results. It is possible that health and life expectancy gains could be even greater if it was not for the increasing prevalence of extreme obesity. It is also possible that the principal impact of obesity is on disability-free life expectancy rather than on life expectancy itself. Conclusion. If the principal impact of obesity were through disability-free life expectancy rather than on life expectancy itself, this would have substantial implications for the health of individuals and the future burden on the health care system

Effects of food policy actions on Indigenous Peoples' nutrition-related outcomes: a systematic review.

INTRODUCTION: Indigenous Peoples worldwide endure unacceptable health disparities with undernutrition and food insecurity often coexisting with obesity and chronic diseases. Policy-level actions are required to eliminate malnutrition in all its forms. However, there has been no systematic synthesis of the evidence of effectiveness of food and nutrition policies for Indigenous Peoples around the world. This review fills that gap. METHODS: Eight databases were searched for peer-reviewed literature, published between 2000 and 2019. Relevant websites were searched for grey literature. Articles were included if they were original studies, published in English and included data from Indigenous Peoples from Western colonised countries, evaluated a food or nutrition policy (or intervention), and provided quantitative impact/outcome data. Study screening, data extraction and quality assessment were undertaken independently by two authors, at least one of whom was Indigenous. A narrative synthesis was undertaken with studies grouped according to the NOURISHING food policy framework. RESULTS: We identified 78 studies from Canada, Australia, Aotearoa/New Zealand and the USA. Most studies evaluated targeted interventions, focused on rural or remote Indigenous communities. The most effective interventions combined educational strategies with policies targeting food price, composition and/or availability, particularly in retail and school environments. Interventions to reduce exposure to unhealthy food advertising was the only area of the NOURISHING framework not represented in the literature. Few studies examined the impact of universal food policies on Indigenous Peoples' diets, health or well-being. CONCLUSION: Both targeted and universal policy action can be effective for Indigenous Peoples. Actions that modify the structures and systems governing food supply through improved availability, access and affordability of healthy foods should be prioritised. More high-quality evidence on the impact of universal food and nutrition policy actions for Indigenous Peoples is required, particularly in urban areas and in the area of food marketing

Influence of early-life risk factors on socioeconomic inequalities in weight gain

Background: Previous research has examined the role of early-life risk factors on childhood weight gain.The extent to which these factors drive socioeconomic differences in weight is unclear. We aimed to quantify the influence of early-life risk factors on the development of socioeconomic inequalities in children''s body mass index (BMI) z-score at 10-11 years. Methods: Overall, 2186 children from the Longitudinal Study of Australian Children were examined. Socioeconomic position (SEP) was measured as a continuous composite of parent''s education, occupation and income. The Product of Coefficients mediation method was used to quantify the contribution of maternal smoking during pregnancy, gestational diabetes, prematurity, caesarean section, birthweight, not being breastfed, early introduction of solid food, maternal BMI and paternal BMI to the relationship between SEP and BMI z-score. Results: Each increasing decile of SEP (higher SEP) was associated with a 0.05 unit lower (95% CI: -0.06, -0.03) BMI z-score at 10-11 years. In total, 83.5% of these differences in BMI z-score could be explained by socioeconomic differences in maternal smoking during pregnancy (26.9%), maternal BMI (39.6%) and paternal BMI (17.0%). Conclusions: Interventions to reduce socioeconomic inequalities in excess weight gain during childhood should support the attainment of a healthy parental weight and prevent smoking during pregnancy

Age-specific trends in cardiovascular mortality rates in Australia between 1980 and 2005

Aim: Recent analyses suggest the decline in coronary heart disease (CHD) mortality rates is slowing in younger age groups in countries such as the UK and US. We aimed to assess recent mortality rate trends in all circulatory disease and its subtypes in Australia. Methods: Annual all circulatory, CHD, and cerebrovascular disease mortality rates between 1980 and 2005 for Australia were analysed. Data were stratified by sex and ten-year age group (age 35 to 85+). The annual rate of change and significant changes in trends were identified using joinpoint Poisson regression. Results: Age standardised all circulatory disease mortality rates continue to decline in Australia, falling from 441 per 100,000 in 1980 to 145 per 100,000 in 2005 for males and from 264 per 100,000 to 96 per 100,000 for females. The rate of decline from both CHD and cerebrovascular disease appears to be stable or accelerating for individuals aged 55 years and over. However, the decline in young men and women aged 35-54 years is slowing for CHD and cerebrovascular disease mortality alike (except cerebrovascular disease mortality in males aged 35-44). For females aged 35-44 and 45-54 there has been no change in the cerebrovascular mortality rate since 1993 and 1999, respectively. Conclusions: In Australia, whilst in older adults the decline in cardiovascular mortality rates is generally accelerating, in younger adults it appears to be slowing. It will be important to identify the causes of these trends

Estimating the proportion of metabolic health outcomes attributable to obesity: a cross-sectional exploration of body mass index and waist circumference combinations

BACKGROUND: Recent evidence suggests that a substantial subgroup of the population who have a high-risk waist circumference (WC) do not have an obese body mass index (BMI). This study aimed to explore whether including those with a non-obese BMI but high risk WC as \u27obese\u27 improves prediction of adiposity-related metabolic outcomes. METHODS: Eleven thousand, two hundred forty-seven participants were recruited. Height, weight and WC were measured. Ten thousand, six hundred fifty-nine participants with complete data were included. Adiposity categories were defined as: BMI(N)/WC(N), BMI(N)/WC(O), BMI(O)/WC(N), and BMI(O)/WC(O) (N = non-obese and O = obese). Population attributable fraction, area under the receiver operating characteristic curve (AUC), and odds ratios (OR) were calculated. RESULTS: Participants were on average 48 years old and 50 % were men. The proportions of BMI(N)/WC(N), BMI(N)/WC(O), BMI(O)/WC(N) and BMI(O)/WC(O) were 68, 12, 2 and 18 %, respectively. A lower proportion of diabetes was attributable to obesity defined using BMI alone compared to BMI and WC combined (32 % vs 47 %). AUC for diabetes was also lower when obesity was defined using BMI alone (0.62 vs 0.66). Similar results were observed for all outcomes. The odds for hypertension, dyslipidaemia, diabetes and CVD were increased for those with BMI(N)/WC(O) (OR range 1.8-2.7) and BMI(O)/WC(O) (OR 1.9-4.9) compared to those with BMI(N)/WC(N). CONCLUSIONS: Current population monitoring, assessing obesity by BMI only, misses a proportion of the population who are at increased health risk through excess adiposity. Improved identification of those at increased health risk needs to be considered for better prioritisation of policy and resources

The case for action on socioeconomic differences in overweight and obesity among Australian adults: modelling the disease burden and healthcare co

Objective: We aimed to quantify the extent to which socioeconomic differences in body mass index (BMI) drive avoidable deaths, incident disease cases and healthcare costs. Methods: We used population attributable fractions to quantify the annual burden of disease attributable to socioeconomic differences in BMI for Australian adults aged 20 to <85 years in 2016, stratified by quintiles of an area-level indicator of socioeconomic disadvantage (SocioEconomic Index For Areas Indicator of Relative Socioeconomic Disadvantage; SEIFA) and BMI (normal weight, overweight, obese). We estimated direct healthcare costs using annual estimates per person per BMI category. Results: We attributed $AU1.06 billion in direct healthcare costs to socioeconomic differences in BMI in 2016. The greatest number (proportion) of cases and deaths attributable to socioeconomic differences in BMI was observed for type 2 diabetes among women (8,602 total cases [16%], with 3,471 cases [22%] in the most disadvantaged quintile [SEIFA 1]) and all-cause mortality among men (2027 total deaths [4%], with 815 deaths [6%] in SEIFA 1). Conclusions: Socioeconomic differences in BMI substantially contribute to avoidable deaths, disease cases and direct healthcare costs in Australia. Implications for public health: Population-level policies to reduce socioeconomic differences in overweight and obesity must be identified and implemented