Person:

Danaei, Goodarz

Abstract Objective: To evaluate the effect of a smoking ban in high schools on smoking behaviour among Chilean students. Methods: We conducted an interrupted time-series analysis, using repeated cross-sectional data from Chile’s school population survey (2000–2011) for high-school students aged 12–18 years and a control group of persons aged 19–24 years. Poisson regression models were used to assess trends in smoking behaviour before and after the policy changes. The outcome measures were self-reported smoking prevalence (any smoking in the past month) and high frequency of smoking (smoking 15 days or more per month). Findings: From 2005 to 2011, the prevalence of smoking declined among high-school students by 6.8% per year compared with 3.6% decline per year in the control group. The decline in the target group was 2.9% (95% confidence interval, CI: 0.18 to 5.00) greater. We estimated that 5–6 years after enforcing the law, smoking prevalence among high-school students was 13.7% lower as a result of the ban. The impact of the smoking ban was primarily driven by declines in smoking prevalence among students in grades 8 to 10. The smoking ban did not significantly alter the frequency of smoking. Conclusion: The 2005 school smoking ban reduced smoking prevalence among younger high-school students in Chile. Further interventions targeting older individuals and frequent smokers may be needed.

Background: 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. Methods: 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previous study, which used a Bayesian hierarchical model to estimate mean body mass index (BMI) based on published and unpublished health examination surveys and epidemiologic studies.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. Results: 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%). Conclusions: 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.

Background: Mass media campaigns are frequently used to influence the health behaviors of various populations. There are currently no quantitative meta-analyses of the effect of mass media campaigns on physical activity in adults. Methods: We searched six electronic databases from their inception to August 2012 and selected prospective studies that evaluated the effect of mass media campaigns on physical activity in adults. We excluded studies that did not have a proper control group or did not report the uncertainties of the effect estimates. Two reviewers independently screened the title/abstracts and full articles. We used random-effects models to pool effect estimates across studies for 3 selected outcomes. Results: Nine prospective cohorts and before-after studies that followed-up 27,601 people over 8 weeks to 3 years met the inclusion criteria. Based on the pooled results from these studies, mass media campaigns had a significant effect on promoting moderate intensity walking (pooled relative risk (RR) from 3 studies=1.53, 95% Confidence Interval: 1.25 to 1.87), but did not help participants achieve sufficient levels of physical activity [4 studies pooled RR=1.02, 95% CI: 0.91 to 1.14)]. The apparent effect of media campaigns on reducing sedentary behavior (pooled RR=1.15, 95% CI: 1.03 to 1.30) was lost when a relatively low-quality study with large effects was excluded in a sensitivity analysis. In subgroup analyses, campaigns that promoted physical activity as a ‘social norm’ seemed to be more effective in reducing sedentary behavior. Conclusion: Mass media campaigns may promote walking but may not reduce sedentary behavior or lead to achieving recommended levels of overall physical activity. Further research is warranted on different campaign types and in low- and middle- income countries.

Objectives: To estimate global, regional (21 regions) and national (187 countries) sodium intakes in adults in 1990 and 2010. Design: Bayesian hierarchical modelling using all identifiable primary sources. Data sources and eligibility We searched and obtained published and unpublished data from 142 surveys of 24 h urinary sodium and 103 of dietary sodium conducted between 1980 and 2010 across 66 countries. Dietary estimates were converted to urine equivalents based on 79 pairs of dual measurements. Modelling methods Bayesian hierarchical modelling used survey data and their characteristics to estimate mean sodium intake, by sex, 5 years age group and associated uncertainty for persons aged 20+ in 187 countries in 1990 and 2010. Country-level covariates were national income/person and composition of food supplies. Main outcome measures Mean sodium intake (g/day) as estimable by 24 h urine collections, without adjustment for non-urinary losses. Results: In 2010, global mean sodium intake was 3.95 g/day (95% uncertainty interval: 3.89 to 4.01). This was nearly twice the WHO recommended limit of 2 g/day and equivalent to 10.06 (9.88–10.21) g/day of salt. Intake in men was ∼10% higher than in women; differences by age were small. Intakes were highest in East Asia, Central Asia and Eastern Europe (mean >4.2 g/day) and in Central Europe and Middle East/North Africa (3.9–4.2 g/day). Regional mean intakes in North America, Western Europe and Australia/New Zealand ranged from 3.4 to 3.8 g/day. Intakes were lower (<3.3 g/day), but more uncertain, in sub-Saharan Africa and Latin America. Between 1990 and 2010, modest, but uncertain, increases in sodium intakes were identified. Conclusions: Sodium intakes exceed the recommended levels in almost all countries with small differences by age and sex. Virtually all populations would benefit from sodium reduction, supported by enhanced surveillance.

Background: Child undernutrition affects millions of children globally. We investigated associations between suboptimal growth and mortality by pooling large studies. Methods: Pooled analysis involving children 1 week to 59 months old in 10 prospective studies in Africa, Asia and South America. Utilizing most recent measurements, we calculated weight-for-age, height/length-for-age and weight-for-height/length Z scores, applying 2006 WHO Standards and the 1977 NCHS/WHO Reference. We estimated all-cause and cause-specific mortality hazard ratios (HR) using proportional hazards models comparing children with mild (−2≤Z<−1), moderate (−3≤Z<−2), or severe (Z<−3) anthropometric deficits with the reference category (Z≥−1). Results: 53 809 children were eligible for this re-analysis and contributed a total of 55 359 person-years, during which 1315 deaths were observed. All degrees of underweight, stunting and wasting were associated with significantly higher mortality. The strength of association increased monotonically as Z scores decreased. Pooled mortality HR was 1.52 (95% Confidence Interval 1.28, 1.81) for mild underweight; 2.63 (2.20, 3.14) for moderate underweight; and 9.40 (8.02, 11.03) for severe underweight. Wasting was a stronger determinant of mortality than stunting or underweight. Mortality HR for severe wasting was 11.63 (9.84, 13.76) compared with 5.48 (4.62, 6.50) for severe stunting. Using older NCHS standards resulted in larger HRs compared with WHO standards. In cause-specific analyses, all degrees of anthropometric deficits increased the hazards of dying from respiratory tract infections and diarrheal diseases. The study had insufficient power to precisely estimate effects of undernutrition on malaria mortality. Conclusions: All degrees of anthropometric deficits are associated with increased risk of under-five mortality using the 2006 WHO Standards. Even mild deficits substantially increase mortality, especially from infectious diseases.

Background: Stunting affects one-third of children under 5 y old in developing countries, and 14% of childhood deaths are attributable to it. A large number of risk factors for stunting have been identified in epidemiological studies. However, the relative contribution of these risk factors to stunting has not been examined across countries. We estimated the number of stunting cases among children aged 24–35 mo (i.e., at the end of the 1,000 days’ period of vulnerability) that are attributable to 18 risk factors in 137 developing countries. Methods and Findings: We classified risk factors into five clusters: maternal nutrition and infection, teenage motherhood and short birth intervals, fetal growth restriction (FGR) and preterm birth, child nutrition and infection, and environmental factors. We combined published estimates and individual-level data from population-based surveys to derive risk factor prevalence in each country in 2010 and identified the most recent meta-analysis or conducted de novo reviews to derive effect sizes. We estimated the prevalence of stunting and the number of stunting cases that were attributable to each risk factor and cluster of risk factors by country and region. The leading risk worldwide was FGR, defined as being term and small for gestational age, and 10.8 million cases (95% CI 9.1 million–12.6 million) of stunting (out of 44.1 million) were attributable to it, followed by unimproved sanitation, with 7.2 million (95% CI 6.3 million–8.2 million), and diarrhea with 5.8 million (95% CI 2.4 million–9.2 million). FGR and preterm birth was the leading risk factor cluster in all regions. Environmental risks had the second largest estimated impact on stunting globally and in the South Asia, sub-Saharan Africa, and East Asia and Pacific regions, whereas child nutrition and infection was the second leading cluster of risk factors in other regions. Although extensive, our analysis is limited to risk factors for which effect sizes and country-level exposure data were available. The global nature of the study required approximations (e.g., using exposures estimated among women of reproductive age as a proxy for maternal exposures, or estimating the impact of risk factors on stunting through a mediator rather than directly on stunting). Finally, as is standard in global risk factor analyses, we used the effect size of risk factors on stunting from meta-analyses of epidemiological studies and assumed that proportional effects were fairly similar across countries. Conclusions: FGR and unimproved sanitation are the leading risk factors for stunting in developing countries. Reducing the burden of stunting requires a paradigm shift from interventions focusing solely on children and infants to those that reach mothers and families and improve their living environment and nutrition.

Background: Refined grains and white rice have been associated with elevated risk of type 2 diabetes mellitus (T2DM). In this study, we sought to quantify the effect of white rice intake on incident T2DM in two prospective population-based cohort studies from Iran, where white rice is one of the main staple. Methods: We used follow-up data from 9,182 participants from Golestan Cohort Study (GCS, 2004–2007, conducted mainly in rural areas) and 2,173 from Tehran Lipid and Glucose Study (TLGS, 2004–2006) who did not have T2DM and other chronic diseases at baseline. Diet was assessed using validated food frequency questionnaires. Multivariable logistic regression models were used to estimate adjusted odds ratios (ORs) for incident T2DM. Results: We documented 902 new cases of T2DM in GCS and 81 in TLGS. Age-standardized cumulative incidence of T2DM was 9.9% in Golestan and 8.0% in Tehran. Daily white rice intake was significantly higher among residents of Tehran compared to Golestan (median daily intake: 250 vs. 120 grams; P-value < 0.001). After adjustment for potential confounders, there was no significant association between daily white rice intake and incident T2DM in GCS. In TLGS, the adjusted OR (95% confidence interval (CI)) was 2.1 (1.1, 3.9) comparing participants with daily white rice intake of >250 grams/day to those with <250. Conclusions: We observed an increased lieklihood of T2DM associated with high white rice intake among residents of Tehran and no association in Golestan. Our findings, if further supported by other studies, have important public health implications especially for countries where white rice is a major staple and diabetes is increasing rapidly incidence is high. Further research is needed to investigate lack of an association between lower levels of white rice intake and T2DM. Electronic supplementary material The online version of this article (doi:10.1186/s12889-016-3999-4) contains supplementary material, which is available to authorized users.

Background: Deaths from cardiovascular disease (CVD), including coronary heart disease (CHD) and stroke are expected to increase in Latin America. Moderate and regular alcohol consumption confers cardiovascular protection, while binge drinking increases risk. We estimated the effects of alcohol use on the number of annual CHD and stroke deaths and disability-adjusted life years (DALYs) in Argentina. Methods: Alcohol use data were obtained from a nationally representative survey (EnPreCosp 2011), and etiological effect sizes from meta-analyses of epidemiological studies. Cause-specific mortality rates were from the vital registration system. Results: There were 291,475 deaths in 2010 including 24,893 deaths from CHD and 15,717 from stroke. 62.7% of men and 38.7% of women reported drinking alcohol in the past year. All heavy drinkers (i.e. women who drank >20g/day and men who drank >40g/day of alcohol) met the definition of binge drinking and therefore did not benefit from cardioprotective effects. Alcohol drinking prevented 1,424 CHD deaths per year but caused 935 deaths from stroke (121 ischemic and 814 hemorrhagic), leading to 448 CVD deaths prevented (58.3% in men). Alcohol use was estimated to save 85,772 DALYs from CHD, but was responsible for 52,171 lost from stroke. Conclusions: In Argentina, the cardioprotective effect of regular and moderate alcohol drinking is slightly larger than the harmful impact of binge drinking on CVD. However, considering global deleterious effects of alcohol in public health, policies to reduce binge drinking should be enforced, especially for young people. Studies are still needed to elucidate effects on cardiovascular health.

Background: The effects of systolic blood pressure (SBP), serum total cholesterol (TC), fasting plasma glucose (FPG), and body mass index (BMI) on the risk of cardiovascular diseases (CVD) have been established in epidemiological studies, but consistent estimates of effect sizes by age and sex are not available. Methods: We reviewed large cohort pooling projects, evaluating effects of baseline or usual exposure to metabolic risks on ischemic heart disease (IHD), hypertensive heart disease (HHD), stroke, diabetes, and, as relevant selected other CVDs, after adjusting for important confounders. We pooled all data to estimate relative risks (RRs) for each risk factor and examined effect modification by age or other factors, using random effects models. Results: Across all risk factors, an average of 123 cohorts provided data on 1.4 million individuals and 52,000 CVD events. Each metabolic risk factor was robustly related to CVD. At the baseline age of 55–64 years, the RR for 10 mmHg higher SBP was largest for HHD (2.16; 95% CI 2.09–2.24), followed by effects on both stroke subtypes (1.66; 1.39–1.98 for hemorrhagic stroke and 1.63; 1.57–1.69 for ischemic stroke). In the same age group, RRs for 1 mmol/L higher TC were 1.44 (1.29–1.61) for IHD and 1.20 (1.15–1.25) for ischemic stroke. The RRs for 5 kg/m2 higher BMI for ages 55–64 ranged from 2.32 (2.04–2.63) for diabetes, to 1.44 (1.40–1.48) for IHD. For 1 mmol/L higher FPG, RRs in this age group were 1.18 (1.08–1.29) for IHD and 1.14 (1.01–1.29) for total stroke. For all risk factors, proportional effects declined with age, were generally consistent by sex, and differed by region in only a few age groups for certain risk factor-disease pairs. Conclusion: Our results provide robust, comparable and precise estimates of the effects of major metabolic risk factors on CVD and diabetes by age group.

Background: Current US surveillance data provide estimates of diabetes using laboratory tests at the national level as well as self-reported data at the state level. Self-reported diabetes prevalence may be biased because respondents may not be aware of their risk status. Our objective was to estimate the prevalence of diagnosed and undiagnosed diabetes by state. Methods: We estimated undiagnosed diabetes prevalence as a function of a set of health system and sociodemographic variables using a logistic regression in the National Health and Nutrition Examination Survey (2003-2006). We applied this relationship to identical variables from the Behavioral Risk Factor Surveillance System (2003-2007) to estimate state-level prevalence of undiagnosed diabetes by age group and sex. We assumed that those who report being diagnosed with diabetes in both surveys are truly diabetic.Results The prevalence of diabetes in the U.S. was 13.7% among men and 11.7% among women ≥ 30 years. Age-standardized diabetes prevalence was highest in Mississippi, West Virginia, Louisiana, Texas, South Carolina, Alabama, and Georgia (15.8 to 16.6% for men and 12.4 to 14.8% for women). Vermont, Minnesota, Montana, and Colorado had the lowest prevalence (11.0 to 12.2% for men and 7.3 to 8.4% for women). Men in all states had higher diabetes prevalence than women. The absolute prevalence of undiagnosed diabetes, as a percent of total population, was highest in New Mexico, Texas, Florida, and California (3.5 to 3.7 percentage points) and lowest in Montana, Oklahoma, Oregon, Alaska, Vermont, Utah, Washington, and Hawaii (2.1 to 3 percentage points). Among those with no established diabetes diagnosis, being obese, being Hispanic, not having insurance and being ≥ 60 years old were significantly associated with a higher risk of having undiagnosed diabetes. Conclusion: Diabetes prevalence is highest in the Southern and Appalachian states and lowest in the Midwest and the Northeast. Better diabetes diagnosis is needed in a number of states.