Changes in waist circumference independent of weight: Implications for population level monitoring of obesity

Population monitoring of obesity is most commonly conducted using body mass index (BMI). We test the hypothesis that because of increases in waist circumference (WC) independent of increases in weight, BMI alone detects an increasingly smaller proportion of the population with obesity. Methods: Australian adults with measured height, weight, and WC were selected from three nationally representative cross-sectional surveys (1989, 1999–2000, 2011–12; n = 8313, 5903 & 3904). Participants were defined as having obesity using classifications for an obese BMI (≥ 30 kg·m− 2) and substantially-increased-risk WC (≥ 88 cm [women], ≥ 102 cm [men]). Age-standardised prevalence of obesity according to BMI and/or WC, and the proportion of these detected by BMI and by WC were compared across surveys. Findings: Between 1989 and 2011–12, weight and WC increased by 5.4 kg and 10.7 cm (women), and by 7.0 kg and 7.3 cm (men). For women and men, 63% and 38% of increases in WC were independent of increases in weight. Over this period, the prevalence of obesity according to BMI and/or WC increased by 25.3 percentage-points for women (18.9% to 44.3%) and 21.1 percentage-points for men (17.1% to 38.2%). The proportion of these detected by BMI decreased for women by 20 percentage-points (77% to 57%) with no change for men. The proportion of these detected by WC increased for women and men by 10 percentage-points (87% to 97%) and 6 percentage-points (85% to 91%) respectively. Conclusion: BMI alone is detecting a decreasing proportion of those considered obese by BMI and/or WC. Renewed discussion regarding how we monitor obesity at the population level is required

The mediating role of dietary factors and leisure time physical activity on socioeconomic inequalities in body mass index among Australian adults

BACKGROUND: The relationship between socioeconomic position and obesity has been clearly established, however, the extent to which specific behavioural factors mediate this relationship is less clear. This study aimed to ascertain the contribution of specific dietary elements and leisure-time physical activity (LTPA) to variations in obesity with education in the baseline (1990-1994) Melbourne Collaborative Cohort Study (MCCS). METHODS: 18, 489 women and 12, 141 men were included in this cross-sectional analysis. A series of linear regression models were used in accordance with the products of coefficients method to examine the mediating role of alcohol, soft drink (regular and diet), snacks (healthy and sweet), savoury items (healthy and unhealthy), meeting fruit and vegetable guidelines and LTPA on the relationship between education and body mass index (BMI). RESULTS: Compared to those with lowest educational attainment, those with the highest educational attainment had a 1 kg/m2 lower BMI. Among men and women, 27% and 48%, respectively, of this disparity was attributable to differences in LTPA and diet. Unhealthy savoury item consumption and LTPA contributed most to the mediated effects for men and women. Alcohol and diet soft drink were additionally important mediators for women. CONCLUSIONS: Diet and LTPA are potentially modifiable behavioural risk factors for the development of obesity that contribute substantially to inequalities in BMI. Our findings highlight the importance of specific behaviours which may be useful to the implementation of effective, targeted public policy to reduce socioeconomic inequalities in obesity

A systematic review and meta-analysis of diabetes and risk of physical disability and functional impairment - protocol

BackgroundDiabetes and increased age are known risk factors for physical disability. With the increasing prevalence of diabetes within our aging population, the future burden of disability is expected to increase. To date, there has not been a pooled estimate of the risk for disability associated with diabetes or its precursor states, impaired glucose tolerance and impaired fasting glucose. We aim to conduct a systematic review and meta-analysis of the association between prediabetes and diabetes with disability, and quantify the risk of association.Methods/designWe will search for relevant studies in Medline via Pubmed, Embase, Cochrane library and Cumulative Index to Nursing and Allied Health Literature (CINAHL), as well as scan reference lists from relevant reviews and publications included in our review. We will review all publications that include studies on human adults (18 years and older) where information is included on diabetes status and at least one measure of disability (Activities of Daily Living (ADL), Instrumental ADL (IADL) or functional/mobility limitation), and where a risk association is available for the relationship between diabetes and/or prediabetes with disability, with reference to those without diabetes.We will further conduct a meta-analysis to pool estimates of the risk of disability associated with prediabetes and diabetes. Sensitivity analysis will be conducted to assess for publication bias and study quality.Findings from this systematic review and meta-analysis will be widely disseminated through discussions with stake-holders, publication in a peer-reviewed journal and conference presentation.<br /

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

The association between socio-economic position and diet quality in Australian adults

Objective: We aimed to investigate the association between multiple measures of socio-economic position (SEP) and diet quality, using a diet quality index representing current national dietary guidelines, in the Australian adult population. Design: Cross-sectional study. Linear regression analyses were used to estimate the association between indicators of SEP (educational attainment, level of income and area-level disadvantage) and diet quality (measured using the Dietary Guideline Index (DGI)) in the total sample and stratified by sex and age (&le;55 years and &gt;55 years). Setting: A large randomly selected sample of the Australian adult population. Subjects: Australian adults (n 9296; aged &ge;25 years) from the Australian Diabetes, Obesity and Lifestyle Study. Results: A higher level of educational attainment and income and a lower level of area-level disadvantage were significantly associated with a higher DGI score, across the gradient of SEP. The association between indicators of SEP and DGI score was consistently stronger among those aged &le;55 years compared with their older counterparts. The most disadvantaged group had a DGI score between 2 and 5 units lower (depending on the marker of SEP) compared with the group with the least disadvantage. Conclusions: A higher level of SEP was consistently associated with a higher level of diet quality for all indicators of SEP examined. In order to reduce socio-economic inequalities in diet quality, healthy eating initiatives need to act across the gradient of socio-economic disadvantage with a proportionate focus on those with greater socio-economic disadvantage

Trends in the skewness of the body mass index distribution among urban Australian adults, 1980 to 2007

Purpose We analyzed the changes in the body mass index (BMI) distribution for urban Australian adults between 1980 and 2007.Methods We used data from participants of six consecutive Australian nation-wide surveys with measured weight and height between 1980 and 2007. We used quantile regression to estimate mean BMI (for percentiles of BMI) and prevalence of severe obesity, modeled by natural splines in age, date of birth, and survey date.Results Since 1980, the right skew in the BMI distribution for Australian adults has increased greatly for men and women, driven by increases in skew associated with age and birth cohort/period. Between 1980 and 2007, the average 5-year increase in BMI was 1 kg/m2 (0.8) for the 95th percentile of BMI in women (men). The increase in the median was about a third of this, and for the 10th percentile, a fifth of this. We estimated that for the cohort born in 1960 around 31% of men and women were obese by age 50 years compared with 11% of the 1930 birth cohort.Conclusions There have been large increases in the right skew of the BMI distribution for urban Australian adults between 1980 and 2007, and birth cohort effects suggests similar increases are likely to continue