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 'obese' 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.

Changing guards: time to move beyond body mass index for population monitoring of excess adiposity

With the obesity epidemic, and the effects of aging populations, human phenotypes have changed over two generations, possibly more dramatically than in other species previously. As obesity is an important and growing hazard for population health, we recommend a systematic evaluation of the optimal measure(s) for population-level excess body fat. Ideal measure(s) for monitoring body composition and obesity should be simple, as accurate and sensitive as possible, and provide good categorization of related health risks. Combinations of anthropometric markers or predictive equations may facilitate better use of anthropometric data than single measures to estimate body composition for populations. Here, we provide new evidence that increasing proportions of aging populations are at high health-risk according to waist circumference, but not body mass index (BMI), so continued use of BMI as the principal population-level measure substantially underestimates the health-burden from excess adiposity.

The Counterweight Programme: prevalence of CVD risk factors by body mass index and impact of a 10% weight change

Objectives

To examine relationships between body mass index (BMI), prevalence of physician-recorded cardiovascular disease (CVD) risk factors in primary care, and changes in risk with 10% weight change.

Methods

The Counterweight Project conducted a baseline cross-sectional survey of medical records of 6150 obese (BMI ≥ 30 kg/m2), 1150 age- and sex-matched overweight (BMI 25 to <30 kg/m2), and 1150 age- and sex-matched normal weight (BMI 18.5 to <25 kg/m2) controls, in primary care. Data were collected for the previous 18 months to examine BMI and disease prevalence, and then modelled to show the potential effect of 10% weight loss or gain on risk.

Results

Obese patients develop more CVD risk factors than normal weight controls. BMI ≥ 40 kg/m2 exhibits increased prevalence of type 2 diabetes mellitus (DM), odds ratio (OR) men: 6.16 (p < 0.001); women: 7.82 (p < 0.001) and hypertension OR men: 5.51 (p < 0.001); women: 4.16 (p < 0.001). Dyslipidaemia peaked around BMI 35 to <37.5 kg/m2, OR men: 3.26 (p < 0.001); women 3.76 (p < 0.001) and CVD at BMI 37.5 to <40 kg/m2 in men, OR 4.48 (p < 0.001) and BMI ≥ 40 kg/m2 in women, OR 3.98 (p < 0.001).

A 10% weight loss from the sample mean of 32.5 kg/m2 reduced the OR for type 2 DM by 30% and CVD by 20%, while 10% weight gain increased type 2 DM risk by more than 35% and CVD by 20%.

Conclusion

Obesity plays a fundamental role in CVD risk, which is reduced with weight loss. Weight management intervention strategies should be a public health priority to reduce the burden of disease in the population.

Influence of body mass index on prescribing costs and potential cost savings of a weight management programme in primary care

Objectives Prescribed medications represent a high and increasing proportion of UK health care funds. Our aim was to quantify the influence of body mass index (BMI) on prescribing costs, and then the potential savings attached to implementing a weight management intervention.

Methods Paper and computer-based medical records were reviewed for all drug prescriptions over an 18-month period for 3400 randomly selected adult patients (18–75 years) stratified by BMI, from 23 primary care practices in seven UK regions. Drug costs from the British National Formulary at the time of the review were used. Multivariate regression analysis was applied to estimate the cost for all drugs and the ‘top ten’ drugs at each BMI point. This allowed the total and attributable prescribing costs to be estimated at any BMI. Weight loss outcomes achieved in a weight management programme (Counterweight) were used to model potential effects of weight change on drug costs. Anticipated savings were then compared with the cost programme delivery. Analysis was carried out on patients with follow-up data at 12 and 24 months as well as on an intention-to-treat basis. Outcomes from Counterweight were based on the observed lost to follow-up rate of 50%, and the assumption that those patients would continue a generally observed weight gain of 1 kg per year from baseline.

Results The minimum annual cost of all drug prescriptions at BMI 20 kg/m2 was £50.71 for men and £62.59 for women. Costs were greater by £5.27 (men) and £4.20 (women) for each unit increase in BMI, to a BMI of 25 (men £77.04, women £78.91), then by £7.78 and £5.53, respectively, to BMI 30 (men £115.93 women £111.23), then by £8.27 and £4.95 to BMI 40 (men £198.66, women £160.73). The relationship between increasing BMI and costs for the top ten drugs was more pronounced. Minimum costs were at a BMI of 20 (men £8.45, women £7.80), substantially greater at BMI 30 (men £23.98, women £16.72) and highest at BMI 40 (men £63.59, women £27.16). Attributable cost of overweight and obesity accounted for 23% of spending on all drugs with 16% attributable to obesity. The cost of the programme was estimated to be approximately £60 per patient entered. Modelling weight reductions achieved by the Counterweight weight management programme would potentially reduce prescribing costs by £6.35 (men) and £3.75 (women) or around 8% of programme costs at one year, and by £12.58 and £8.70, respectively, or 18% of programme costs after two years of intervention. Potential savings would be increased to around 22% of the cost of the programme at year one with full patient retention and follow-up.

Conclusion Drug prescriptions rise from a minimum at BMI of 20 kg/m2 and steeply above BMI 30 kg/m2. An effective weight management programme in primary care could potentially reduce prescription costs and lead to substantial cost avoidance, such that at least 8% of the programme delivery cost would be recouped from prescribing savings alone in the first year.

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.

Future predictions of body mass index and overweight prevalence in Australia, 2005-2025

To predict current and future body mass index (BMI) and prevalence of overweight and obesity in Australian children and adults based on sex, age and year of birth (cohort). These predictions are needed for population health planning and evaluation. Data were drawn from 11 cross-sectional national or state population surveys conducted in Australia between 1969 and 2004. These included representative population samples of children (n= 27,635) and adults (n= 43,447) aged 5 years or older with measured height and weight data. Multiple linear regression analyses of measured log-transformed BMI data were conducted to determine the independent effects of age and year of birth (cohort) on ln(BMI) for males and females, respectively. Regression coefficients for cohort obtained from these analyses were applied to the National Nutrition Survey 1995 data set to predict mean BMI and prevalence of overweight (BMI 25-29.99 kg/m(2)) and obesity (BMI ≥ 30 kg/m(2)) in 2005, 2015 and 2025. Based on past trends, BMI is predicted to continue to increase for both males and females and across the age span. This would result in increases in the prevalence of overweight and obesity of between 0.4 and 0.8% per year, such that by 2025 around one-third of 5-19 year olds will be overweight or obese as will 83% of males and 75% of females aged 20 years and over. The increases in prevalence and mean BMI predicted in this study will have significant impacts on disease burden, healthcare costs and need for prevention and treatment programmes.

Quantifying the proportion of deaths due to body mass index- and waist circumference-defined obesity

OBJECTIVE: To determine the risk of mortality associated with and quantify the deaths attributable to combinations of body mass index (BMI) and waist circumference (WC). METHODS: This study included 41,439 participants. For the hazard ratio (HR) calculation, 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, O = obese). For the population attributable fraction analysis, obesity was classified as: (i) obese by BMI and/or WC; (ii) obese by BMI; and (iii) obese by WC. Mortality data was complete to the end of 2012. RESULTS: The prevalence of BMI(N) /WC(N) , BMI(N) /WC(O) , BMI(O) /WC(N) , and BMI(O) /WC(O) was 73%, 6%, 6%, and 15%, respectively. There was an increased risk of all-cause and cardiovascular disease (CVD) mortality in those with BMI(N) /WC(O) (HR (95% CI) 1.2 (1.2, 1.3) and 1.3 (1.1, 1.6)) and BMI(O) /WC(O) (1.3 (1.3, 1.4) and 1.7 (1.5, 1.9)) compared to those with BMI(N) /WC(N) . The estimated proportion of all-cause and CVD mortality attributable to obesity defined using WC or using BMI and/or WC was higher compared to obesity defined using BMI. CONCLUSIONS: Current population obesity monitoring misses those with BMI(N) /WC(O) who are at increased risk of mortality. By targeting reductions in population WC, the potential exists to prevent more deaths in the population than if we continue to target reductions in BMI alone.

A revised Australian dietary guideline index and its association with key sociodemographic factors, health behaviors and body mass index in peri-retirement aged adults

The Dietary Guideline Index, a measure of diet quality, was updated to reflect the 2013 Australian Dietary Guidelines. This paper describes the revision of the index (DGI-2013) and examines its use in older adults. The DGI-2013 consists of 13 components reflecting food-based daily intake recommendations of the Australian Dietary Guidelines. In this cross-sectional study, the DGI-2013 score was calculated using dietary data collected via an 111-item food frequency questionnaire and additional food-related behaviour questions. The DGI-2013 score was examined in Australian adults (aged 55-65 years; n = 1667 men; 1801 women) according to sociodemographics, health-related behaviours and BMI. Women scored higher than men on the total DGI-2013 and all components except for dairy. Those who were from a rural area (men only), working full-time (men only), with lower education, smoked, did not meet physical activity guidelines, and who had a higher BMI, scored lower on the DGI-2013, highlighting a group of older adults at risk of poor health. The DGI-2013 is a tool for assessing compliance with the Australian Dietary Guidelines. We demonstrated associations between diet quality and a range of participant characteristics, consistent with previous literature. This suggests that the DGI-2013 continues to demonstrate convergent validity, consistent with the original Dietary Guideline Index.

Hair cortisol levels, perceived stress and body mass index in women and children living in socioeconomically disadvantaged neighborhoods: the READI study

Disadvantaged communities provide adverse psychosocial exposures that have been linked to high levels of stress, and this may provide one explanatory pathway linking socioeconomic disadvantage to obesity. This study used hair cortisol analysis to quantify associations between stress and body mass index (BMI), and between hair cortisol and perceived psychological stress levels, in women and children living in socioeconomically disadvantaged neighborhoods. Participants were a volunteer sample of 70 women from the Resilience for Eating and Activity Despite Inequality study, including 30 maternal-child pairs. Women self-reported body weight, height and perceived psychological stress using the Perceived Stress Scale (PSS), and provided hair samples for themselves and their child. Children's body weight and height were measured. Following extraction, hair cortisol levels were measured using enzyme-linked immunosorbent assay. Multiple linear regression models examined associations between stress and BMI, and between hair cortisol and perceived stress levels in women and children. Women's hair cortisol levels were not associated with their BMI or PSS scores. Women's PSS scores were positively associated with their BMI (p = 0.015). Within maternal-child pairs, mothers and children's hair cortisol levels were strongly positively associated (p = 0.006). Maternal hair cortisol levels and PSS scores were unrelated to their child's zBMI. Children's hair cortisol levels were not associated with their zBMI or with their mother's PSS score. Findings suggest that cortisol-based and perceived psychological measures of stress may be distinct among women and children living in disadvantaged neighborhoods. Perceived psychological measures may be more important predictors of weight-related risk.

Medical burden, body mass index and the outcome of psychosocial interventions for bipolar depression

Objective: Individuals with bipolar disorder experience a disproportionately high incidence of medical co-morbidity and obesity. These health-related problems are a barrier to recovery from mood episodes and have been linked with unfavorable responses to pharmacological treatment. However, little is known about whether and how these characteristics affect responses to adjunctive psychotherapy. Method: Embedded in the Systematic Treatment Enhancement Program for Bipolar Disorder was a randomized controlled trial of psychotherapy for bipolar depression comparing the efficacy of intensive psychotherapy plus pharmacotherapy with collaborative care (a three-session psycho-educational intervention) plus pharmacotherapy. We conducted a post-hoc analysis to evaluate whether medical burden and body mass index predicted and/or moderated the likelihood of recovery and time until recovery from a depressive episode among patients in the two treatments. Results: Participants who had medical co-morbidity and body mass index data constituted 199 of the 293 patients in the original Systematic Treatment Enhancement Program for Bipolar Disorder trial. Higher medical burden predicted a lower likelihood of recovery from depression in both treatment conditions (odds ratio = 0.89), but did not moderate responses to intensive psychotherapy vs collaborative care. Intensive psychotherapy yielded superior recovery rates for individuals of normal body mass index (odds ratio= 2.39) compared with collaborative care, but not among individuals who were overweight or obese. Conclusion: Medical co-morbidity and body weight impacts symptom improvement and attention to this co-morbidity may inform the development of more personalized treatments for bipolar disorder.

Mediating effects of dietary intake on associations of TV viewing, body mass index and metabolic syndrome in adolescents

OBJECTIVE: Evidence suggests that TV viewing is associated with body mass index (BMI) and metabolic syndrome (MetS) in adolescents. However, it is unclear whether dietary intake mediates these relationships.

METHODS: A cross-sectional analysis was conducted in adolescents (12-19 years) participating in the 2003-2006 United States National Health and Nutrition Examination Survey. BMI z scores (zBMI) (n = 3,161) and MetS (n = 1,379) were calculated using age- and sex-specific criteria for adolescents. TV viewing (h/day) was measured via a self-reported questionnaire, and dietary intake was assessed using two 24-h recalls. Using the MacKinnon method, a series of mediation analyses were conducted examining five dietary mediators (total energy intake, fruit and vegetable intake, discretionary snacks, sugar-sweetened beverages and diet quality) of the relationships between TV viewing and zBMI and MetS.

RESULTS: Small positive relationships were observed between TV viewing and zBMI (β = 0.99, p < 0.001) and TV viewing and MetS (OR = 1.18, p = 0.046). No dietary element appeared to mediate the relationship between TV viewing and zBMI. However, sugar-sweetened beverage consumption and fruit and vegetable intake partially mediated the relationship between TV viewing and MetS, explaining 8.7% and 4.1% of the relationship, respectively.

CONCLUSIONS: These findings highlight the complexity of the relationships between TV viewing, dietary intake and cardiometabolic health outcomes, and that TV viewing should remain a target for interventions.

Isotemporal substitution analysis for sedentary behavior and body mass index

This study examined the prospective associations of reallocating time spent in different types of sedentary behavior, physical activity, and sleep with body mass index (BMI) in children using isotemporal substitution analysis. Methods Chinese children in grades 1-3 were recruited to a cohort study in 2009 and were followed up over a 2-yr period. Reports were gathered from the parents on children's sedentary behavior, sleep duration, and sociodemographic variables. The reported sedentary behavior types were then grouped into three categories: screen time (e.g., watching TV), academic-related activities (e.g., doing homework), and other sedentary behaviors (e.g., sitting and talking). Moderate-to-vigorous physical activity (MVPA) and light-intensity physical activity were assessed by ActiGraph accelerometry (ActiGraph, Pensacola, FL). Isotemporal substitution models were performed to examine the effects of time allocation on BMI. Results A total of 672 children (359 boys, mean age at recruitment = 7.6 yr) who had provided valid accelerometer data for at least one assessment time point were included in the analysis. Controlling for covariates and total behavior time, isotemporal substitution models indicated that the displacement of 30 min·d -1 of other sedentary behaviors with equal amounts of screen time (B = 0.12; 95% confidence interval, 0.04-0.20) or academic-related activities (B = 0.13; 95% confidence interval, 0.04-0.21) was associated with higher BMI. Reallocating 30 min·d -1 of MVPA with each of the sedentary behavior variables resulted in increased BMI. Conclusions The substitution of screen time or academic-related activities with other sedentary behaviors or MVPA was associated with lower BMI in Chinese children.

Associations between access to recreational physical activity facilities and body mass index in Scottish adults

BACKGROUND: The aim of this country-wide study was to link individual health and behavioural data with area-level spatial data to examine whether the body mass index (BMI) of adults was associated with access to recreational physical activity (PA) facilities by different modes of transport (bus, car, walking, cycling) and the extent to which any associations were mediated by PA participation. METHODS: Data on individual objectively-measured BMI, PA (number of days of (a) ≥20 min of moderate-to-vigorous PA, and (b) ≥15 min of sport or exercise, in previous 4 weeks), and socio-demographic characteristics were obtained from a nationally representative sample of 6365 adults. The number of accessible PA facilities per 1,000 individuals in each small area (data zones) was obtained by mapping a representative list of all fixed PA facilities throughout mainland Scotland. A novel transport network was developed for the whole country, and routes on foot, by bike, by car and by bus from the weighted population centroid of each data zone to each facility were calculated. Separate multilevel models were fitted to examine associations between BMI and each of the 24 measures of accessibility of PA facilities and BMI, adjusting for age, gender, longstanding illness, car availability, social class, dietary quality and urban/rural classification. RESULTS: We found associations (p < 0.05) between BMI and 7 of the 24 accessibility measures, with mean BMI decreasing with increasing accessibility of facilities-for example, an estimated decrease of 0.015 BMI units per additional facility within a 20-min walk (p = 0.02). None of these accessibility measures were found to be associated with PA participation. CONCLUSIONS: Our national study has shown that some measures of the accessibility of PA facilities by different modes of transport (particularly by walking and cycling) were associated with BMI; but PA participation, as measured here, did not appear to play a part in this relationship. Understanding the multi-factorial environmental influences upon obesity is key to developing effective interventions to reduce it.

Association of birth weight and current body size to blood pressure in female twins

It has been proposed that low birth weight is associated with high levels of blood pressure in later life. The aim of this study was to assess the relationship of blood pressure to birth weight and current body size during growth and adulthood. A total of 711 female multiple births, with one group of 244 in their growth phase mean age 12.0 (2.3)(SD) years and the other of 467 adults (mean age 35.2 (12.6) years), had height, weight and both systolic (SBP) and diastolic (DBP) blood pressures measured, and self-reported their birth weight. Regression analyses were performed to assess the cross-sectional and within-pair associations of blood pressure to birth weight, with and without adjustments for current body size. Within-pair analysis was based on 296 twin pairs. Cross-sectionally, a reduction in birth weight of 1 kg was associated with 2 to 3 mm Hg higher age-adjusted SBP, which was of marginal significance and explained about 2% of the population variance. Adjustment for body mass index did not significantly change this association. Within-pair analyses found no association between birth weight and SBP or DBP,even after adjusting for current body size. After age, current body size was the strongest predictor of systolic BP. The weak association of blood pressure to birth weight cross-sectionally is of interest, but any within-pair effect of birth weight on blood pressure must be minimal compared with the effect of current body size.

Parent, peer and media influences on body image and strategies to both increase and decrease body size among adolescent boys and girls

This study investigated the nature of body image and body change strategies, as well as the sociocultural influences on these variables, among a group of 1,266 adolescents (622 males, 644 females). In particular, it investigated weight gain and increased muscle, as well as weight loss. It was found that females were less satisfied with their bodies and were more likely to adopt strategies to lose weight, whereas males were more likely to adopt strategies to increase weight and muscle tone. Respondents with higher body mass index (BMI) evidenced greater body dissatisfaction and more weight loss strategies, but there were no differences between BMI groups in weight gain or strategies to increase muscles. Weight gain and strategies to increase muscles were more likely to be undertaken by older adolescents, but there were no grade level differences in weight loss. Media influences to alter weight, as well as feedback from mother, father, and both male and female peers, were greater for females. There were few grade level or BMI differences in regard to any of the sociocultural influences. The importance of these findings in terms of providing a better understanding of factors which may lead to a disturbed body image and body change disorders, particularly among adolescent boys, is discussed.