Dataset Information

How smoking affects the proportion of deaths attributable to obesity: assessing the role of relative risks and weight distributions.

ABSTRACT: Although ever-smokers make up the majority of the older adult population in the USA, they are often excluded from studies examining the impact of obesity on mortality. Understanding how smoking and obesity interact is critical to assessing the proportion of deaths attributable to obesity.Nationally representative sample of the non-institutionalised population of the USA. Baseline data were drawn from the National Health and Nutrition Examination Survey, 1988-1994 and 1999-2004.US adults aged 50-74 (n=9835).We used Cox models to estimate the mortality risks of obesity by smoking status. All-cause mortality was assessed prospectively through 31 December 2006 (n=1243 deaths). Maximum body mass index (BMI) was specified as the key exposure variable. We also calculated population attributable fractions (PAFs) by smoking status and investigated differences in PAFs in a decomposition analysis.The HR associated with a one-unit increment in BMI beyond 25.0 kg/m(2) was 1.057 for never-smokers (95% CI 1.033 to 1.082; p<0.001), 1.036 for former smokers (95% CI 1.015 to 1.059; p<0.01) and 1.024 for current smokers (95% CI 0.997 to 1.052).We estimated that 19.8% of deaths were attributable to excess weight. The PAFs were 31.9, 20.4 and 11.3 for never-smokers, former and current smokers, respectively. The difference in PAFs between never-smokers and current smokers was almost entirely explained by the difference in HRs.The proportion of deaths attributable to obesity is nearly 3 times as high among never-smokers compared with current smokers. This finding is consistent with the fact that smokers are subject to significant competing risks. Analyses that exclude smokers are likely to substantially overestimate the proportion of deaths attributable to obesity in the USA.

SUBMITTER: Stokes A

PROVIDER: S-EPMC4769428 | biostudies-other | 2016 Feb

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:BackgroundBrazil has reduced its smoking rate by about 50% in the last 20 y. During that time period, strong tobacco control policies were implemented. This paper estimates the effect of these stricter policies on smoking prevalence and associated premature mortality, and the effect that additional policies may have.Methods and findingsThe model was developed using the SimSmoke tobacco control policy model. Using policy, population, and smoking data for Brazil, the model assesses the effect on premature deaths of cigarette taxes, smoke-free air laws, mass media campaigns, marketing restrictions, packaging requirements, cessation treatment programs, and youth access restrictions. We estimate the effect of past policies relative to a counterfactual of policies kept to 1989 levels, and the effect of stricter future policies. Male and female smoking prevalence in Brazil have fallen by about half since 1989, which represents a 46% (lower and upper bounds: 28%-66%) relative reduction compared to the 2010 prevalence under the counterfactual scenario of policies held to 1989 levels. Almost half of that 46% reduction is explained by price increases, 14% by smoke-free air laws, 14% by marketing restrictions, 8% by health warnings, 6% by mass media campaigns, and 10% by cessation treatment programs. As a result of the past policies, a total of almost 420,000 (260,000-715,000) deaths had been averted by 2010, increasing to almost 7 million (4.5 million-10.3 million) deaths projected by 2050. Comparing future implementation of a set of stricter policies to a scenario with 2010 policies held constant, smoking prevalence by 2050 could be reduced by another 39% (29%-54%), and 1.3 million (0.9 million-2.0 million) out of 9 million future premature deaths could be averted.ConclusionsBrazil provides one of the outstanding public health success stories in reducing deaths due to smoking, and serves as a model for other low and middle income nations. However, a set of stricter policies could further reduce smoking and save many additional lives. Please see later in the article for the Editors' Summary.

Dataset Information

How smoking affects the proportion of deaths attributable to obesity: assessing the role of relative risks and weight distributions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets