Background: Relations between the consumption of nuts and legumes and risk of ischemic heart disease (IHD), stroke, and diabetes have not been well established.Objective: We systematically ...investigated and quantified associations of nut and legume consumption with incident IHD, stroke, and diabetes.Design: We systematically searched multiple databases to identify randomized controlled trials or observational studies that examined the relations. Studies were excluded if they reported only intermediate physiologic measures, soft cardiovascular outcomes, or crude risk estimates. Data were extracted independently and in duplicate. We assessed pooled dose-response relations by using a generalized least-squares trend estimation, and prespecified sources of heterogeneity were assessed by using metaregression. The potential for publication bias was explored by using funnel plots, Begg's and Egger's tests, and Duval and Tweedie trim-and-fill methods.Results: Of 3851 abstracts, 25 observational studies (23 prospective and 2 retrospective studies) and 2 trial reports met inclusion criteria and comprised 501,791 unique individuals and 11,869 IHD, 8244 stroke, and 14,449 diabetes events. The consumption of nuts was inversely associated with fatal IHD (6 studies; 6749 events; RR per 4 weekly 28.4-g servings: 0.76; 95% CI: 0.69, 0.84; I2 = 28%), nonfatal IHD (4 studies; 2101 events; RR: 0.78; 0.67, 0.92; I2 = 0%), and diabetes (6 studies; 13,308 events; RR: 0.87; 0.81,0.94; I2 = 22%) but not stroke (4 studies; 5544 events). Legume consumption was inversely associated with total IHD (5 studies; 6514 events; RR per 4 weekly 100-g servings: 0.86; 0.78, 0.94; I2 = 0%) but not significantly associated with stroke (6 studies; 6690 events) or diabetes (2 studies; 2746 events). A meta-regression did not identify the effect modification by age, duration of follow-up, study location, or study quality. Mixed evidence was seen for publication bias, but analyses by using the Duval and Tweedie trim-and-fill method did not appreciably alter results.Conclusion: This systematic review supports inverse associations between eating nuts and incident IHD and diabetes and eating legumes and incident IHD.
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CMK, GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Objective To conduct a systematic review and meta-analysis of prices of healthier versus less healthy foods/diet patterns while accounting for key sources of heterogeneity. Data sources MEDLINE ...(2000–2011), supplemented with expert consultations and hand reviews of reference lists and related citations. Design Studies reviewed independently and in duplicate were included if reporting mean retail price of foods or diet patterns stratified by healthfulness. We extracted, in duplicate, mean prices and their uncertainties of healthier and less healthy foods/diet patterns and rated the intensity of health differences for each comparison (range 1–10). Prices were adjusted for inflation and the World Bank purchasing power parity, and standardised to the international dollar (defined as US$1) in 2011. Using random effects models, we quantified price differences of healthier versus less healthy options for specific food types, diet patterns and units of price (serving, day and calorie). Statistical heterogeneity was quantified using I2 statistics. Results 27 studies from 10 countries met the inclusion criteria. Among food groups, meats/protein had largest price differences: healthier options cost $0.29/serving (95% CI $0.19 to $0.40) and $0.47/200 kcal ($0.42 to $0.53) more than less healthy options. Price differences per serving for healthier versus less healthy foods were smaller among grains ($0.03), dairy (−$0.004), snacks/sweets ($0.12) and fats/oils ($0.02; p<0.05 each) and not significant for soda/juice ($0.11, p=0.64). Comparing extremes (top vs bottom quantile) of food-based diet patterns, healthier diets cost $1.48/day ($1.01 to $1.95) and $1.54/2000 kcal ($1.15 to $1.94) more. Comparing nutrient-based patterns, price per day was not significantly different (top vs bottom quantile: $0.04; p=0.916), whereas price per 2000 kcal was $1.56 ($0.61 to $2.51) more. Adjustment for intensity of differences in healthfulness yielded similar results. Conclusions This meta-analysis provides the best evidence until today of price differences of healthier vs less healthy foods/diet patterns, highlighting the challenges and opportunities for reducing financial barriers to healthy eating.
Public health is a priority for the Chinese Government. Evidence-based decision making for health at the province level in China, which is home to a fifth of the global population, is of paramount ...importance. This analysis uses data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to help inform decision making and monitor progress on health at the province level.
We used the methods in GBD 2017 to analyse health patterns in the 34 province-level administrative units in China from 1990 to 2017. We estimated all-cause and cause-specific mortality, years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), summary exposure values (SEVs), and attributable risk. We compared the observed results with expected values estimated based on the Socio-demographic Index (SDI).
Stroke and ischaemic heart disease were the leading causes of death and DALYs at the national level in China in 2017. Age-standardised DALYs per 100 000 population decreased by 33·1% (95% uncertainty interval UI 29·8 to 37·4) for stroke and increased by 4·6% (–3·3 to 10·7) for ischaemic heart disease from 1990 to 2017. Age-standardised stroke, ischaemic heart disease, lung cancer, chronic obstructive pulmonary disease, and liver cancer were the five leading causes of YLLs in 2017. Musculoskeletal disorders, mental health disorders, and sense organ diseases were the three leading causes of YLDs in 2017, and high systolic blood pressure, smoking, high-sodium diet, and ambient particulate matter pollution were among the leading four risk factors contributing to deaths and DALYs. All provinces had higher than expected DALYs per 100 000 population for liver cancer, with the observed to expected ratio ranging from 2·04 to 6·88. The all-cause age-standardised DALYs per 100 000 population were lower than expected in all provinces in 2017, and among the top 20 level 3 causes were lower than expected for ischaemic heart disease, Alzheimer's disease, headache disorder, and low back pain. The largest percentage change at the national level in age-standardised SEVs among the top ten leading risk factors was in high body-mass index (185%, 95% UI 113·1 to 247·7), followed by ambient particulate matter pollution (88·5%, 66·4 to 116·4).
China has made substantial progress in reducing the burden of many diseases and disabilities. Strategies targeting chronic diseases, particularly in the elderly, should be prioritised in the expanding Chinese health-care system.
China National Key Research and Development Program and Bill & Melinda Gates Foundation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Objective To quantify the dose-response associations between total physical activity and risk of breast cancer, colon cancer, diabetes, ischemic heart disease, and ischemic stroke ...events.Design Systematic review and Bayesian dose-response meta-analysis.Data sources PubMed and Embase from 1980 to 27 February 2016, and references from relevant systematic reviews. Data from the Study on Global AGEing and Adult Health conducted in China, Ghana, India, Mexico, Russia, and South Africa from 2007 to 2010 and the US National Health and Nutrition Examination Surveys from 1999 to 2011 were used to map domain specific physical activity (reported in included studies) to total activity.Eligibility criteria for selecting studies Prospective cohort studies examining the associations between physical activity (any domain) and at least one of the five diseases studied.Results 174 articles were identified: 35 for breast cancer, 19 for colon cancer, 55 for diabetes, 43 for ischemic heart disease, and 26 for ischemic stroke (some articles included multiple outcomes). Although higher levels of total physical activity were significantly associated with lower risk for all outcomes, major gains occurred at lower levels of activity (up to 3000-4000 metabolic equivalent (MET) minutes/week). For example, individuals with a total activity level of 600 MET minutes/week (the minimum recommended level) had a 2% lower risk of diabetes compared with those reporting no physical activity. An increase from 600 to 3600 MET minutes/week reduced the risk by an additional 19%. The same amount of increase yielded much smaller returns at higher levels of activity: an increase of total activity from 9000 to 12 000 MET minutes/week reduced the risk of diabetes by only 0.6%. Compared with insufficiently active individuals (total activity <600 MET minutes/week), the risk reduction for those in the highly active category (≥8000 MET minutes/week) was 14% (relative risk 0.863, 95% uncertainty interval 0.829 to 0.900) for breast cancer; 21% (0.789, 0.735 to 0.850) for colon cancer; 28% (0.722, 0.678 to 0.768) for diabetes; 25% (0.754, 0.704 to 0.809) for ischemic heart disease; and 26% (0.736, 0.659 to 0.811) for ischemic stroke.Conclusions People who achieve total physical activity levels several times higher than the current recommended minimum level have a significant reduction in the risk of the five diseases studied. More studies with detailed quantification of total physical activity will help to find more precise relative risk estimates for different levels of activity.
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BFBNIB, CMK, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
While food pricing is a promising strategy to improve diet, the prospective impact of food pricing on diet has not been systematically quantified.
To quantify the prospective effect of changes in ...food prices on dietary consumption.
We systematically searched online databases for interventional or prospective observational studies of price change and diet; we also searched for studies evaluating adiposity as a secondary outcome. Studies were excluded if price data were collected before 1990. Data were extracted independently and in duplicate. Findings were pooled using DerSimonian-Laird's random effects model. Pre-specified sources of heterogeneity were analyzed using meta-regression; and potential for publication bias, by funnel plots, Begg's and Egger's tests.
From 3,163 identified abstracts, 23 interventional studies and 7 prospective cohorts with 37 intervention arms met inclusion criteria. In pooled analyses, a 10% decrease in price (i.e., subsidy) increased consumption of healthful foods by 12% (95%CI = 10-15%; N = 22 studies/intervention arms) whereas a 10% increase price (i.e. tax) decreased consumption of unhealthful foods by 6% (95%CI = 4-8%; N = 15). By food group, subsidies increased intake of fruits and vegetables by 14% (95%CI = 11-17%; N = 9); and other healthful foods, by 16% (95%CI = 10-23%; N = 10); without significant effects on more healthful beverages (-3%; 95%CI = -16-11%; N = 3). Each 10% price increase reduced sugar-sweetened beverage intake by 7% (95%CI = 3-10%; N = 5); fast foods, by 3% (95%CI = 1-5%; N = 3); and other unhealthful foods, by 9% (95%CI = 6-12%; N = 3). Changes in price of fruits and vegetables reduced body mass index (-0.04 kg/m2 per 10% price decrease, 95%CI = -0.08-0 kg/m2; N = 4); price changes for sugar-sweetened beverages or fast foods did not significantly alter body mass index, based on 4 studies. Meta-regression identified direction of price change (tax vs. subsidy), number of intervention components, intervention duration, and study quality score as significant sources of heterogeneity (P-heterogeneity<0.05 each). Evidence for publication bias was not observed.
These prospective results, largely from interventional studies, support efficacy of subsidies to increase consumption of healthful foods; and taxation to reduce intake of unhealthful beverages and foods. Use of subsidies and combined multicomponent interventions appear most effective.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
The prevalence of obesity, measured by body mass index, has risen to unacceptable levels in both men and women in the United States and worldwide with resultant hazardous health ...implications. Genetic, environmental, and behavioral factors influence the development of obesity, and both the general public and health professionals stigmatize those who suffer from the disease. Obesity is associated with and contributes to a shortened life span, type 2 diabetes mellitus, cardiovascular disease, some cancers, kidney disease, obstructive sleep apnea, gout, osteoarthritis, and hepatobiliary disease, among others. Weight loss reduces all of these diseases in a dose-related manner-the more weight lost, the better the outcome. The phenotype of "medically healthy obesity" appears to be a transient state that progresses over time to an unhealthy phenotype, especially in children and adolescents. Weight loss is best achieved by reducing energy intake and increasing energy expenditure. Programs that are effective for weight loss include peer-reviewed and approved lifestyle modification programs, diets, commercial weight-loss programs, exercise programs, medications, and surgery. Over-the-counter herbal preparations that some patients use to treat obesity have limited, if any, data documenting their efficacy or safety, and there are few regulatory requirements. Weight regain is expected in all patients, especially when treatment is discontinued. When making treatment decisions, clinicians should consider body fat distribution and individual health risks in addition to body mass index.
This Scientific Statement critically reviews the definition of obesity, providing a list of assessment methods, obesity-related diseases, and prevention measures.
Background
Novel interventions are needed to improve lifestyle and prevent noncommunicable diseases, the leading cause of death and disability globally. This study aimed to systematically review, ...synthesize, and grade scientific evidence on effectiveness of novel information and communication technology to reduce noncommunicable disease risk.
Methods and Results
We systematically searched PubMed for studies evaluating the effect of Internet, mobile phone, personal sensors, or stand‐alone computer software on diet, physical activity, adiposity, tobacco, or alcohol use. We included all interventional and prospective observational studies conducted among generally healthy adults published between January 1990 and November 2013. American Heart Association criteria were used to evaluate and grade the strength of evidence. From 8654 s, 224 relevant reports were identified. Internet and mobile interventions were most common. Internet interventions improved diet (N=20 studies) (Class IIa A), physical activity (N=33), adiposity (N=35), tobacco (N=22), and excess alcohol (N=47) (Class I A each). Mobile interventions improved physical activity (N=6) and adiposity (N=3) (Class I A each). Evidence limitations included relatively brief durations (generally <6 months, nearly always <1 year), heterogeneity in intervention content and intensity, and limited representation from middle/low‐income countries.
Conclusions
Internet and mobile interventions improve important lifestyle behaviors up to 1 year. This systematic review supports the need for long‐term interventions to evaluate sustainability.
The aim of this study was to estimate the economic burden of diabetes mellitus (DM) in Iran from 2009 to 2030.
A Markov micro-simulation (MM) model was developed to predict the DM population size and ...associated economic burden. Age- and sex-specific prevalence and incidence of diagnosed and undiagnosed DM were derived from national health surveys. A systematic review was performed to identify the cost of diabetes in Iran and the mean annual direct and indirect costs of patients with DM were estimated using a random-effect Bayesian meta-analysis. Face, internal, cross and predictive validity of the MM model were assessed by consulting an expert group, performing sensitivity analysis (SA) and comparing model results with published literature and national survey reports. Sensitivity analysis was also performed to explore the effect of uncertainty in the model.
We estimated 3.78 million cases of DM (2.74 million diagnosed and 1.04 million undiagnosed) in Iran in 2009. This number is expected to rise to 9.24 million cases (6.73 million diagnosed and 2.50 million undiagnosed) by 2030. The mean annual direct and indirect costs of patients with DM in 2009 were US$ 556 (posterior standard deviation, 221) and US$ 689 (619), respectively. Total estimated annual cost of DM was $3.64 (2009 US$) billion (including US$1.71 billion direct and US$1.93 billion indirect costs) in 2009 and is predicted to increase to $9.0 (in 2009 US$) billion (including US$4.2 billion direct and US$4.8 billion indirect costs) by 2030.
The economic burden of DM in Iran is predicted to increase markedly in the coming decades. Identification and implementation of effective strategies to prevent and manage DM should be considered as a public health priority.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The Australian Government recently established sodium targets for packaged foods to encourage voluntary reformulation to reduce population sodium consumption and related diseases. We modeled the ...health impact of Australia's sodium reformulation targets and additional likely health gains if more ambitious, yet feasible sodium targets had been adopted instead.
Using comparative risk assessment models, we estimated the averted deaths, incidence, and disability-adjusted life years (DALYs) from cardiovascular disease (CVD), chronic kidney disease (CKD) and stomach cancer after implementation of (a) Australia's sodium targets (overall and by individual companies); (b) United Kingdom's targets (that covers more product categories); and (c) an optimistic scenario (sales-weighted 25th percentile sodium content for each food category included in the UK program). We used nationally representative data to estimate pre- and post-intervention sodium intake, and other key data sources from the Global Burden of Disease study. Full compliance with the Australian government's sodium targets could prevent approximately 510 deaths/year (95% UI, 335 to 757), corresponding to about 1% of CVD, CKD, and stomach cancer deaths, and prevent some 1,920 (1,274 to 2,600) new cases and 7,240 (5,138 to 10,008) DALYs/year attributable to these diseases. Over half (59%) of deaths prevented is attributed to reformulation by 5 market-dominant companies. Compliance with the UK and optimistic scenario could avert approximately an additional 660 (207 to 1,227) and 1,070 (511 to 1,856) deaths/year, respectively, compared to Australia's targets. The main limitation of this study (like other modeling studies) is that it does not prove that sodium reformulation programs will prevent deaths and disease events; rather, it provides the best quantitative estimates and the corresponding uncertainty of the potential effect of the different programs to guide the design of policies.
There is significant potential to strengthen Australia's sodium reformulation targets to improve its health impact. Promoting compliance by market-dominant food companies will be critical to achieving the potential health gains.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Few data are available on the supply and consumption of nutrients at the country level. To address this data gap, we aimed to create a database that provides information on availability (ie, supply) ...of 156 nutrients across 195 countries and territories from 1980 to 2013.
We matched 394 food and agricultural commodities from the Food and Agriculture Organization of the United Nations Supply and Utilization Accounts (SUAs) to food items in the United States Department of Agriculture Food Composition Database and obtained data on nutrient composition of the SUAs' food items. Then, after adjusting for inedible portion of each food item, we added the contributions of individual food items to the availability of each nutrient and estimated the national availability of macronutrients and micronutrients in each year. We validated our estimates by comparing our results with those of national nutrition surveys from three countries (the USA, South Korea, and Ecuador). Using dietary consumption data from the Global Burden of Disease study and two popular machine learning algorithms (Random Forest and XGBoost extreme gradient boosting), we developed predictive models to estimate the consumption of each nutrient based on their national availability.
Globally 2710 kcal (95% UI 2660–2770) were available per person per day in 2013. Carbohydrates were the major contributor to energy availability (70·5%), followed by fats (17·4%), and protein (10·5%). The energy availability and the contribution of macronutrients to total energy widely varied across levels of development. Countries at the higher level of development (high Socio-demographic Index countries) had more energy available per person per day (3270 kcal, 3220–3310); greater contributions from fats (26·0%) and proteins (11·9%) to total energy availability; and lower contributions from carbohydrate (54·8%). During 1980–2013, energy availability and the contributions of protein and fats to energy availability have increased globally and across levels of development while the contribution of carbohydrates to total energy availability has decreased. The supply of the micronutrients has also increased during the same period globally and across levels of development. Our validation analysis showed that, after accounting for waste at the retail and household level, our estimates of macronutrient availability were very close to the consumption data in nationally representative surveys. Our machine-learning models closely predicted the observed intake of nutrients with the out-of-sample correlation of greater than 0·8 between predicted and observed intake for the nutrients included in the analysis.
Our global nutrient database provides a picture of the supply of various nutrients at the country level and can be useful to assess the performance of national food systems in addressing the nutritional needs of their population.
Bill & Melinda Gates Foundation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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