Showing papers by "Goodarz Danaei published in 2012"

National, regional, and global trends in adult overweight and obesity prevalences

Abstract: Overweight and obesity prevalence are commonly used for public and policy communication of the extent of the obesity epidemic, yet comparable estimates of trends in overweight and obesity prevalence by country are not available. We estimated trends between 1980 and 2008 in overweight and obesity prevalence and their uncertainty for adults 20 years of age and older in 199 countries and territories. Data were from a previous study, which used a Bayesian hierarchical model to estimate mean body mass index (BMI) based on published and unpublished health examination surveys and epidemiologic studies. Here, we used the estimated mean BMIs in a regression model to predict overweight and obesity prevalence by age, country, year, and sex. The uncertainty of the estimates included both those of the Bayesian hierarchical model and the uncertainty due to cross-walking from mean BMI to overweight and obesity prevalence. The global age-standardized prevalence of obesity nearly doubled from 6.4% (95% uncertainty interval 5.7-7.2%) in 1980 to 12.0% (11.5-12.5%) in 2008. Half of this rise occurred in the 20 years between 1980 and 2000, and half occurred in the 8 years between 2000 and 2008. The age-standardized prevalence of overweight increased from 24.6% (22.7-26.7%) to 34.4% (33.2-35.5%) during the same 28-year period. In 2008, female obesity prevalence ranged from 1.4% (0.7-2.2%) in Bangladesh and 1.5% (0.9-2.4%) in Madagascar to 70.4% (61.9-78.9%) in Tonga and 74.8% (66.7-82.1%) in Nauru. Male obesity was below 1% in Bangladesh, Democratic Republic of the Congo, and Ethiopia, and was highest in Cook Islands (60.1%, 52.6-67.6%) and Nauru (67.9%, 60.5-75.0%). Globally, the prevalence of overweight and obesity has increased since 1980, and the increase has accelerated. Although obesity increased in most countries, levels and trends varied substantially. These data on trends in overweight and obesity may be used to set targets for obesity prevalence as requested at the United Nations high-level meeting on Prevention and Control of NCDs.

Bias in Observational Studies of Prevalent Users: Lessons for Comparative Effectiveness Research From a Meta-Analysis of Statins

Abstract: Randomized clinical trials (RCTs) are usually the preferred strategy with which to generate evidence of comparative effectiveness, but conducting an RCT is not always feasible. Though observational studies and RCTs often provide comparable estimates, the questioning of observational analyses has recently intensified because of randomized-observational discrepancies regarding the effect of postmenopausal hormone replacement therapy on coronary heart disease. Reanalyses of observational data that excluded prevalent users of hormone replacement therapy led to attenuated discrepancies, which begs the question of whether exclusion of prevalent users should be generally recommended. In the current study, the authors evaluated the effect of excluding prevalent users of statins in a meta-analysis of observational studies of persons with cardiovascular disease. The pooled, multivariate-adjusted mortality hazard ratio for statin use was 0.77 (95% confidence interval (CI): 0.65, 0.91) in 4 studies that compared incident users with nonusers, 0.70 (95% CI: 0.64, 0.78) in 13 studies that compared a combination of prevalent and incident users with nonusers, and 0.54 (95% CI: 0.45, 0.66) in 13 studies that compared prevalent users with nonusers. The corresponding hazard ratio from 18 RCTs was 0.84 (95% CI: 0.77, 0.91). It appears that the greater the proportion of prevalent statin users in observational studies, the larger the discrepancy between observational and randomized estimates.

Estimating the global and regional burden of suboptimal nutrition on chronic disease: methods and inputs to the analysis.

Abstract: Global burdens of cardiovascular disease (CVD), diabetes and cancer are on the rise. Little quantitative data are available on the global impact of diet on these conditions. The objective of this study was to develop systematic and comparable methods to quantitatively assess the impact of suboptimal dietary habits on CVD, diabetes and cancer burdens globally and in 21 world regions. Using a comparative risk assessment framework, we developed methods to establish for selected dietary risk factors the effect sizes of probable or convincing causal diet–disease relationships, the alternative minimum-risk exposure distributions and the exposure distributions. These inputs, together with disease-specific mortality rates, allow computation of the numbers of events attributable to each dietary factor. Using World Health Organization and similar evidence criteria for convincing/probable causal effects, we identified 14 potential diet–disease relationships. Effect sizes and ranges of uncertainty will be derived from systematic reviews and meta-analyses of trials or high-quality observational studies. Alternative minimum-risk distributions were identified based on amounts corresponding to the lowest disease rates in populations. Optimal and alternative definitions for each exposure were established based on the data used to quantify harmful or protective effects. We developed methods for identifying and obtaining data from nationally representative surveys. A ranking scale was developed to assess survey quality and validity of dietary assessment methods. Multi-level hierarchical models will be developed to impute missing data. These new methods will allow, for the first time, assessment of the global impact of specific dietary factors on chronic disease mortality. Such global assessment is not only possible but is also imperative for priority setting and policy making.

Effect of physical activity on functional performance and knee pain in patients with osteoarthritis : analysis with marginal structural models.

Abstract: Background: A previous analysis of the Osteoarthritis Initiative study reported a dose-response relationship between physical activity and improved physical function in adults with knee osteoarthritis, using conventional statistical methods. These methods are subject to bias when confounders are affected by prior exposure. Methods: We used baseline and 1-, 2-, and 3-year follow-up data from the Osteoarthritis Initiative study of 2545 US adults with knee osteoarthritis recruited between 2004 and 2006 from 4 clinical sites. Physical activity was measured using the Physical Activity Scale for the Elderly, and outcomes were functional performance measured by the timed 20-meter walk test and self-reported knee pain measured by the Western Ontario and McMaster Universities Osteoarthritis Index. We estimated the effect of physical activity on each outcome using inverse probability-weighted (IPW) estimators of marginal structural models. For each outcome, we fitted 2 separate IPW models adjusting for concurrent or lagged confounders. Results: The mean differences in walking speed for the second, third, and fourth quartiles of physical activity relative to the first were 0.48 (95% confidence interval = -0.12 to 1.08), 0.45 (-0.23 to 1.13), and 0.46 (-0.29 to 1.22) meters/min based on the IPW model adjusting for concurrent confounders. When adjusting for lagged confounders, the results were 1.35 (0.64 to 2.07), 1.33 (0.54 to 2.14), and 1.26 (0.40 to 2.12). Both IPW models indicated that physical activity did not affect knee pain. Conclusions: Physical activity has no effect on knee pain and may have either a very small effect or no effect on functional performance in adults with knee osteoarthritis. Knee osteoarthritis is a leading cause of pain and disability in the elderly.1 There is no cure for osteoarthritis, and treatment is generally aimed at reducing pain and maintaining function.2 Several systematic reviews of randomized trials have demonstrated that exercise programs reduce pain and disability in the short term in patients with knee osteoarthritis.3–5 However, prospective observational studies are needed to evaluate the long-term effects of lifestyle physical activity among people with knee osteoarthritis. Using generalized estimating equations (GEE) to estimate a linear model, Dunlop et al 6 evaluated the effect of physical activity on subsequent 1-year functional performance in adults with knee osteoarthritis using 2-year follow-up data from the Osteoarthritis Initiative. The authors adjusted for the potential confounders available only at baseline, as well as the concurrent values of time-dependent confounders, and reported a dose-response relationship between physical activity and improved performance. However, standard methods for analysis of longitudinal data may lead to biased estimates when exposure affects a confounder, or when exposure is affected by prior outcome and affects future outcome.7–9 Both of these conditions are possible in the Osteoarthritis Initiative data, eg, physical activity may affect body mass index as a potential confounder and may also affect as well as be affected by functional performance. Marginal structural models overcome this problem by using inverse probability weighting.10,11 The aim of this study was to estimate the effect of physical activity on functional performance and knee pain in the Osteoarthritis Initiative cohort using inverse probability-weighted (IPW) estimators of marginal structural models.

The Age Associations of Blood Pressure, Cholesterol and Glucose: Analysis of Health Examination Surveys from International Populations

Abstract: Background—The age association of cardiovascular disease may be in part because its metabolic risk factors tend to rise with age. Few studies have analyzed age associations of multiple metabolic ri...

Cardiovascular disease prevention using fixed dose pharmacotherapy in Iran: updated meta-analyses and mortality estimation.

Abstract: BACKGROUND: Short term randomized trials have shown the effectiveness of a fixed dose combination therapy (known as Polypill) on reducing blood pressure and serum cholesterol but the impact of Polypill on cardiovascular disease risk or mortality has not yet been directly investigated. Previous studies combined the effects of each component assuming a multiplicative joint risk model that may have led to overestimating the combined effects. We conducted an updated meta-analysis of randomized trials of anti-hypertensives, and aspirin. We used the estimated effect sizes applying a more conservative assumption to estimate the number of ischemic heart disease (IHD) and stroke deaths that could have been averted by Polypill in Iranians aged 55 years or older in 2006. METHODS: We searched Medline and reviewed previous meta-analyses to select randomized trials on Angiotensin Converting Enzyme-inhibitors, thiazides, aspirin, and statins. We used a random-effects model to pool relative risks for each component and estimated the joint relative risks using multiplicative and additive assumptions for 4 combinations of Polypill components. We used age- and cause-specific mortality, separately by gender, and estimated the number of preventable deaths from IHD and stroke. RESULTS: Under the additive joint RR assumption, the standard Polypill formulation was estimated to prevent 28500 (95% CI: 21700, 34100) IHD deaths and 12700 (95% CI: 8800, 15900) stroke deaths. Removing aspirin from the combination decreased preventable IHD deaths by 15% under the additive assumption (5600 deaths) and by 21% under the multiplicative assumption (6800 deaths) and reduced preventable stroke deaths under both additive and multiplicative assumptions by 3% (300 deaths). There was no significant difference between Polypill combinations with anti-hypertensive agents in full-dose or half-dose. CONCLUSIONS: Polypill can prevent a large number of IHD and stroke deaths in Iran. The cost-effectiveness, feasibility, and acceptability of this prevention strategy remain to be investigated.

Global burden of infection-related cancer revisited.

Abstract: 564 www.thelancet.com/oncology Vol 13 June 2012 There were an estimated 12·7 million new cases of cancers which accounted for 7·6 million deaths globally in 2008, with about two-thirds of cancer deaths in less developed countries. Two previous comprehensive analyses of infections and cancers reported that in 1990 and 2002 about one in six cancer cases worldwide could be attributed to infectious agents. In The Lancet Oncology, de Martel and colleagues provide an updated systematic analysis of the proportion of cancer cases attributable to infection globally and by region in 2008. Compared with the two previous analyses, the absolute number of cancer cases due to infection increased by about half a million since 1990, whereas the proportion of cancer cases attributable to infection remained stable at about 16–18%. Most of the infection-attributable cases occurred in less developed countries and were due to preventable or treatable infections (hepatitis B and C virus [HBV and HCV], human papillomavirus [HPV], and Helicobacter pylori). The estimated attributable fraction for all infections combined was 16·1%—by comparison, in 2004 WHO estimated the attributable fraction for the combined eff ect of nine lifestyle and environmental risk factors as 35%. To estimate the population attributable fractions (PAFs), de Martel and colleagues used data on cancer incidence from the GLOBOCAN project, along with the most recent epidemiological evidence on the causal eff ect of each infection on cancer and the most reliable data on prevalence of infection among cases. For HBV and HCV, where reliable data on prevalence were not available for many countries, logistic regression models were fi tted using data on cancer incidence to estimate prevalence of infection in cancer cases. This method might have led to overestimation of prevalence when cross-country variations are due to other causes of cancer (eg, alcohol use for liver cancer). Future investigations might benefi t from collating all available evidence on exposure to infection, including cancer registry data and population surveys. Such a comprehensive approach might require the use of statistical models to incorporate potential sources of bias and variability among diff erent measures of exposure. In any global analysis of risk factors and diseases, the choice of geographical regions and pooling methods can have a substantial eff ect on estimates, particularly when the data are somewhat sparse, as in the present analysis. To aggregate country-level data into regional estimates and account for missing data in some countries, the authors weighted the country-level data by sample size and incidence of corresponding cancer cases. This method gives more weight to larger studies and studies done in high-risk countries, and can lead to overestimation of regional infection prevalence. Another methodological consideration is that a case of cancer might be attributable to more than one infection. Ideally, the joint eff ect of multiple infections Global burden of infection-related cancer revisited