Examining the BMI-mortality relationship using fractional polynomials

<p>Abstract</p> <p>Background</p> <p>Many previous studies estimating the relationship between body mass index (BMI) and mortality impose assumptions regarding the functional form for BMI and result in conflicting findings. This study investigated a flexible data driven modelling approach to determine the nonlinear and asymmetric functional form for BMI used to examine the relationship between mortality and obesity. This approach was then compared against other commonly used regression models.</p> <p>Methods</p> <p>This study used data from the National Health Interview Survey, between 1997 and 2000. Respondents were linked to the National Death Index with mortality follow-up through 2005. We estimated 5-year all-cause mortality for adults over age 18 using the logistic regression model adjusting for BMI, age and smoking status. All analyses were stratified by sex. The multivariable fractional polynomials (MFP) procedure was employed to determine the best fitting functional form for BMI and evaluated against the model that includes linear and quadratic terms for BMI and the model that groups BMI into standard weight status categories using a deviance difference test. Estimated BMI-mortality curves across models were then compared graphically.</p> <p>Results</p> <p>The best fitting adjustment model contained the powers -1 and -2 for BMI. The relationship between 5-year mortality and BMI when estimated using the MFP approach exhibited a J-shaped pattern for women and a U-shaped pattern for men. A deviance difference test showed a statistically significant improvement in model fit compared to other BMI functions. We found important differences between the MFP model and other commonly used models with regard to the shape and nadir of the BMI-mortality curve and mortality estimates.</p> <p>Conclusions</p> <p>The MFP approach provides a robust alternative to categorization or conventional linear-quadratic models for BMI, which limit the number of curve shapes. The approach is potentially useful in estimating the relationship between the full spectrum of BMI values and other health outcomes, or costs.</p

The relationship between body size and mortality in the linked Scottish Health Surveys: cross-sectional surveys with follow-up

Objective: To investigate the relationship between body mass index (BMI), waist circumference (WC) or waist–hip ratio (WHR) and all-cause mortality or cause-specific mortality. Design: Cross-sectional surveys linked to hospital admissions and death records. Subjects: In total, 20 117 adults (aged 18–86 years) from a nationally representative sample of the Scottish population. Measurements: Cox proportional hazards models were used to estimate hazard ratios (HRs) for all-cause, or cause-specific, mortality. The three anthropometric measurements BMI, WC and WHR were the main variables of interest. The following were adjustment variables: age, gender, smoking status, alcohol consumption, survey year, social class and area of deprivation. Results: BMI-defined obesity (greater than or equal to30 kg m−2) was not associated with increased risk of mortality (HR=0.93; 95% confidence interval=0.80–1.08), whereas the overweight category (25–&#60;30 kg m−2) was associated with a decreased risk (0.80; 0.70–0.91). In contrast, the HR for a high WC (mengreater than or equal to102 cm, womengreater than or equal to88 cm) was 1.17 (1.02–1.34) and a high WHR (mengreater than or equal to1, women&#8805;0.85) was 1.34 (1.16–1.55). There was an increased risk of cardiovascular disease (CVD) mortality associated with BMI-defined obesity, a high WC and a high WHR categories; the HR estimates for these were 1.36 (1.05–1.77), 1.41 (1.11–1.79) and 1.44 (1.12–1.85), respectively. A low BMI (&#60;18.5 kg m−2) was associated with elevated HR for all-cause mortality (2.66; 1.97–3.60), for chronic respiratory disease mortality (3.17; 1.39–7.21) and for acute respiratory disease mortality (11.68; 5.01–27.21). This pattern was repeated for WC but not for WHR. Conclusions: It might be prudent not to use BMI as the sole measure to summarize body size. The alternatives WC and WHR may more clearly define the health risks associated with excess body fat accumulation. The lack of association between elevated BMI and mortality may reflect the secular decline in CVD mortality.</p

Return of naturally sourced Pb to Atlantic surface waters

Anthropogenic emissions completely overwhelmed natural marine lead (Pb) sources during the past century, predominantly due to leaded petrol usage. Here, based on Pb isotope measurements, we reassess the importance of natural and anthropogenic Pb sources to the tropical North Atlantic following the nearly complete global cessation of leaded petrol use. Significant proportions of up to 30-50% of natural Pb, derived from mineral dust, are observed in Atlantic surface waters, reflecting the success of the global effort to reduce anthropogenic Pb emissions. The observation of mineral dust derived Pb in surface waters is governed by the elevated atmospheric mineral dust concentration of the North African dust plume and the dominance of dry deposition for the atmospheric aerosol flux to surface waters. Given these specific regional conditions, emissions from anthropogenic activities will remain the dominant global marine Pb source, even in the absence of leaded petrol combustion

Linkage analysis of obesity phenotypes in pre- and post-menopausal women from a United States mid-western population

<p>Abstract</p> <p>Background</p> <p>Obesity has a strong genetic influence, with some variants showing stronger associations among women than men. Women are also more likely to distribute weight in the abdomen following menopause. We investigated whether genetic loci link with obesity-related phenotypes differently by menopausal status.</p> <p>Methods</p> <p>We performed univariate and bivariate linkage analysis for the phenotypes of body mass index (BMI), waist (W) and hip (H) circumferences (WC, HC), and WH ratio (WHR) separately among 172 pre-menopausal and 405 post-menopausal women from 90 multigenerational families using a genome scan with 403 microsatellite markers. Bivariate analysis used pair-wise combinations of obesity phenotypes to detect linkage at loci with pleiotropic effects for genetically correlated traits. BMI was adjusted in models of WC, HC and WHR.</p> <p>Results</p> <p>Pre-menopausal women, compared to post-menopausal women, had higher heritability for BMI (<it>h</it>²= 94% versus <it>h</it>²= 39%, respectively) and for HC (<it>h</it>²= 99% versus <it>h</it>²= 43%, respectively), and lower heritability for WC (<it>h</it>²= 29% versus <it>h</it>²= 61%, respectively) and for WHR (<it>h</it>²= 39% versus <it>h</it>²= 57%, respectively). Among pre-menopausal women, the strongest evidence for linkage was for the combination of BMI and HC traits at 3p26 (bivariate LOD = 3.65) and at 13q13-q14 (bivariate LOD = 3.59). Among post-menopausal women, the highest level of evidence for genetic linkage was for HC at 4p15.3 (univariate LOD = 2.70) and 14q13 (univariate LOD = 2.51). WC was not clearly linked to any locus.</p> <p>Conclusions</p> <p>These results support a genetic basis for fat deposition that differs by menopausal status, and suggest that the same loci encode genes that influence general obesity (BMI) and HC, specifically, among pre-menopausal women. However, lower heritability among pre-menopausal women for WC and WHR suggests that pre-menopausal waist girth may be influenced to a greater extent by controllable environmental factors than post-menopausal waist girth. Possibly, targeted interventions for weight control among pre-menopausal women may prevent or attenuate post-menopausal abdominal weight deposition.</p

Childhood obesity, prevalence and prevention

Childhood obesity has reached epidemic levels in developed countries. Twenty five percent of children in the US are overweight and 11% are obese. Overweight and obesity in childhood are known to have significant impact on both physical and psychological health. The mechanism of obesity development is not fully understood and it is believed to be a disorder with multiple causes. Environmental factors, lifestyle preferences, and cultural environment play pivotal roles in the rising prevalence of obesity worldwide. In general, overweight and obesity are assumed to be the results of an increase in caloric and fat intake. On the other hand, there are supporting evidence that excessive sugar intake by soft drink, increased portion size, and steady decline in physical activity have been playing major roles in the rising rates of obesity all around the world. Consequently, both over-consumption of calories and reduced physical activity are involved in childhood obesity. Almost all researchers agree that prevention could be the key strategy for controlling the current epidemic of obesity. Prevention may include primary prevention of overweight or obesity, secondary prevention or prevention of weight regains following weight loss, and avoidance of more weight increase in obese persons unable to lose weight. Until now, most approaches have focused on changing the behaviour of individuals in diet and exercise. It seems, however, that these strategies have had little impact on the growing increase of the obesity epidemic. While about 50% of the adults are overweight and obese in many countries, it is difficult to reduce excessive weight once it becomes established. Children should therefore be considered the priority population for intervention strategies. Prevention may be achieved through a variety of interventions targeting built environment, physical activity, and diet. Some of these potential strategies for intervention in children can be implemented by targeting preschool institutions, schools or after-school care services as natural setting for influencing the diet and physical activity. All in all, there is an urgent need to initiate prevention and treatment of obesity in children

Estimating the burden of disease attributable to four selected environmental risk factors in South Africa

The first South African National Burden of Disease study quantified the underlying causes of premature mortality and morbidity experienced in South Africa in the year 2000. This was followed by a Comparative Risk Assessment to estimate the contributions of 17 selected risk factors to burden of disease in South Africa. This paper describes the health impact of exposure to four selected environmental risk factors: unsafe water, sanitation and hygiene; indoor air pollution from household use of solid fuels; urban outdoor air pollution and lead exposure.The study followed World Health Organization comparative risk assessment methodology. Population-attributable fractions were calculated and applied to revised burden of disease estimates (deaths and disability adjusted life years, [DALYs]) from the South African Burden of Disease study to obtain the attributable burden for each selected risk factor. The burden attributable to the joint effect of the four environmental risk factors was also estimated taking into account competing risks and common pathways. Monte Carlo simulation-modeling techniques were used to quantify sampling, uncertainty.Almost 24 000 deaths were attributable to the joint effect of these four environmental risk factors, accounting for 4.6% (95% uncertainty interval 3.8-5.3%) of all deaths in South Africa in 2000. Overall the burden due to these environmental risks was equivalent to 3.7% (95% uncertainty interval 3.4-4.0%) of the total disease burden for South Africa, with unsafe water sanitation and hygiene the main contributor to joint burden. The joint attributable burden was especially high in children under 5 years of age, accounting for 10.8% of total deaths in this age group and 9.7% of burden of disease.This study highlights the public health impact of exposure to environmental risks and the significant burden of preventable disease attributable to exposure to these four major environmental risk factors in South Africa. Evidence-based policies and programs must be developed and implemented to address these risk factors at individual, household, and community levels

Racial difference in Acylation Stimulating Protein (ASP) correlates to triglyceride in non-obese and obese African American and Caucasian women

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