Trends in Dietary Quality Among Adults in the United States, 1999 Through 2010
TL;DR: Although a steady improvement in AHEI-2010 was observed across the 12-year period, the overall dietary quality remains poor and the gap between low and high socioeconomic status widened with time.
Abstract: Importance Many changes in the economy, policies related to nutrition, and food processing have occurred within the United States since 2000, and the net effect on dietary quality is not clear. These changes may have affected various socioeconomic groups differentially. Objective To investigate trends in dietary quality from 1999 to 2010 in the US adult population and within socioeconomic subgroups. Design, Setting, and Participants Nationally representative sample of 29 124 adults aged 20 to 85 years from the US 1999 to 2010 National Health and Nutrition Examination Survey. Main Outcomes and Measures The Alternate Healthy Eating Index 2010 (AHEI-2010), an 11-dimension score (range, 0-10 for each component score and 0-110 for the total score), was used to measure dietary quality. A higher AHEI-2010 score indicated a more healthful diet. Results The energy-adjusted mean of the AHEI-2010 increased from 39.9 in 1999 to 2000 to 46.8 in 2009 to 2010 (linear trendP Conclusions and Relevance Although a steady improvement in AHEI-2010 was observed across the 12-year period, the overall dietary quality remains poor. Better dietary quality was associated with higher socioeconomic status, and the gap widened with time. Future efforts to improve nutrition should address these disparities.
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TL;DR: WRITING GROUP MEMBERS Emelia J. Benjamin, MD, SCM, FAHA Michael J. Reeves, PhD Matthew Ritchey, PT, DPT, OCS, MPH Carlos J. Jiménez, ScD, SM Lori Chaffin Jordan,MD, PhD Suzanne E. Judd, PhD
Abstract: WRITING GROUP MEMBERS Emelia J. Benjamin, MD, SCM, FAHA Michael J. Blaha, MD, MPH Stephanie E. Chiuve, ScD Mary Cushman, MD, MSc, FAHA Sandeep R. Das, MD, MPH, FAHA Rajat Deo, MD, MTR Sarah D. de Ferranti, MD, MPH James Floyd, MD, MS Myriam Fornage, PhD, FAHA Cathleen Gillespie, MS Carmen R. Isasi, MD, PhD, FAHA Monik C. Jiménez, ScD, SM Lori Chaffin Jordan, MD, PhD Suzanne E. Judd, PhD Daniel Lackland, DrPH, FAHA Judith H. Lichtman, PhD, MPH, FAHA Lynda Lisabeth, PhD, MPH, FAHA Simin Liu, MD, ScD, FAHA Chris T. Longenecker, MD Rachel H. Mackey, PhD, MPH, FAHA Kunihiro Matsushita, MD, PhD, FAHA Dariush Mozaffarian, MD, DrPH, FAHA Michael E. Mussolino, PhD, FAHA Khurram Nasir, MD, MPH, FAHA Robert W. Neumar, MD, PhD, FAHA Latha Palaniappan, MD, MS, FAHA Dilip K. Pandey, MBBS, MS, PhD, FAHA Ravi R. Thiagarajan, MD, MPH Mathew J. Reeves, PhD Matthew Ritchey, PT, DPT, OCS, MPH Carlos J. Rodriguez, MD, MPH, FAHA Gregory A. Roth, MD, MPH Wayne D. Rosamond, PhD, FAHA Comilla Sasson, MD, PhD, FAHA Amytis Towfighi, MD Connie W. Tsao, MD, MPH Melanie B. Turner, MPH Salim S. Virani, MD, PhD, FAHA Jenifer H. Voeks, PhD Joshua Z. Willey, MD, MS John T. Wilkins, MD Jason HY. Wu, MSc, PhD, FAHA Heather M. Alger, PhD Sally S. Wong, PhD, RD, CDN, FAHA Paul Muntner, PhD, MHSc On behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee Heart Disease and Stroke Statistics—2017 Update
7,190 citations
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TL;DR: Author(s): Writing Group Members; Mozaffarian, Dariush; Benjamin, Emelia J; Go, Alan S; Arnett, Donna K; Blaha, Michael J; Cushman, Mary; Das, Sandeep R; de Ferranti, Sarah; Despres, Jean-Pierre; Fullerton, Heather J; Howard, Virginia J; Huffman, Mark D; Isasi, Carmen R; Jimenez, Monik C; Judd, Suzanne
Abstract: Author(s): Writing Group Members; Mozaffarian, Dariush; Benjamin, Emelia J; Go, Alan S; Arnett, Donna K; Blaha, Michael J; Cushman, Mary; Das, Sandeep R; de Ferranti, Sarah; Despres, Jean-Pierre; Fullerton, Heather J; Howard, Virginia J; Huffman, Mark D; Isasi, Carmen R; Jimenez, Monik C; Judd, Suzanne E; Kissela, Brett M; Lichtman, Judith H; Lisabeth, Lynda D; Liu, Simin; Mackey, Rachel H; Magid, David J; McGuire, Darren K; Mohler, Emile R; Moy, Claudia S; Muntner, Paul; Mussolino, Michael E; Nasir, Khurram; Neumar, Robert W; Nichol, Graham; Palaniappan, Latha; Pandey, Dilip K; Reeves, Mathew J; Rodriguez, Carlos J; Rosamond, Wayne; Sorlie, Paul D; Stein, Joel; Towfighi, Amytis; Turan, Tanya N; Virani, Salim S; Woo, Daniel; Yeh, Robert W; Turner, Melanie B; American Heart Association Statistics Committee; Stroke Statistics Subcommittee
6,181 citations
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TL;DR: March 5, 2019 e1 WRITING GROUP MEMBERS Emelia J. Virani, MD, PhD, FAHA, Chair Elect On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee.
Abstract: March 5, 2019 e1 WRITING GROUP MEMBERS Emelia J. Benjamin, MD, ScM, FAHA, Chair Paul Muntner, PhD, MHS, FAHA, Vice Chair Alvaro Alonso, MD, PhD, FAHA Marcio S. Bittencourt, MD, PhD, MPH Clifton W. Callaway, MD, FAHA April P. Carson, PhD, MSPH, FAHA Alanna M. Chamberlain, PhD Alexander R. Chang, MD, MS Susan Cheng, MD, MMSc, MPH, FAHA Sandeep R. Das, MD, MPH, MBA, FAHA Francesca N. Delling, MD, MPH Luc Djousse, MD, ScD, MPH Mitchell S.V. Elkind, MD, MS, FAHA Jane F. Ferguson, PhD, FAHA Myriam Fornage, PhD, FAHA Lori Chaffin Jordan, MD, PhD, FAHA Sadiya S. Khan, MD, MSc Brett M. Kissela, MD, MS Kristen L. Knutson, PhD Tak W. Kwan, MD, FAHA Daniel T. Lackland, DrPH, FAHA Tené T. Lewis, PhD Judith H. Lichtman, PhD, MPH, FAHA Chris T. Longenecker, MD Matthew Shane Loop, PhD Pamela L. Lutsey, PhD, MPH, FAHA Seth S. Martin, MD, MHS, FAHA Kunihiro Matsushita, MD, PhD, FAHA Andrew E. Moran, MD, MPH, FAHA Michael E. Mussolino, PhD, FAHA Martin O’Flaherty, MD, MSc, PhD Ambarish Pandey, MD, MSCS Amanda M. Perak, MD, MS Wayne D. Rosamond, PhD, MS, FAHA Gregory A. Roth, MD, MPH, FAHA Uchechukwu K.A. Sampson, MD, MBA, MPH, FAHA Gary M. Satou, MD, FAHA Emily B. Schroeder, MD, PhD, FAHA Svati H. Shah, MD, MHS, FAHA Nicole L. Spartano, PhD Andrew Stokes, PhD David L. Tirschwell, MD, MS, MSc, FAHA Connie W. Tsao, MD, MPH, Vice Chair Elect Mintu P. Turakhia, MD, MAS, FAHA Lisa B. VanWagner, MD, MSc, FAST John T. Wilkins, MD, MS, FAHA Sally S. Wong, PhD, RD, CDN, FAHA Salim S. Virani, MD, PhD, FAHA, Chair Elect On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee
5,739 citations
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TL;DR: The Statistical Update represents the most up-to-date statistics related to heart disease, stroke, and the cardiovascular risk factors listed in the AHA's My Life Check - Life’s Simple 7, which include core health behaviors and health factors that contribute to cardiovascular health.
Abstract: Each chapter listed in the Table of Contents (see next page) is a hyperlink to that chapter. The reader clicks the chapter name to access that chapter.
Each chapter listed here is a hyperlink. Click on the chapter name to be taken to that chapter.
Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together in a single document the most up-to-date statistics related to heart disease, stroke, and the cardiovascular risk factors listed in the AHA’s My Life Check - Life’s Simple 7 (Figure1), which include core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure [BP], and glucose control) that contribute to cardiovascular health. The Statistical Update represents …
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TL;DR: This year's edition of the Statistical Update includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association’s 2020 Impact Goals.
Abstract: Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovas...
5,078 citations
References
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TL;DR: The increases in the prevalence of obesity previously observed do not appear to be continuing at the same rate over the past 10 years, particularly for women and possibly for men.
Abstract: Results In 2007-2008, the age-adjusted prevalence of obesity was 33.8% (95% confidence interval [CI], 31.6%-36.0%) overall, 32.2% (95% CI, 29.5%-35.0%) among men, and 35.5% (95% CI, 33.2%-37.7%) among women. The corresponding prevalence estimates for overweight and obesity combined (BMI 25) were 68.0% (95% CI, 66.3%-69.8%), 72.3% (95% CI, 70.4%-74.1%), and 64.1% (95% CI, 61.3%66.9%). Obesity prevalence varied by age group and by racial and ethnic group for both men and women. Over the 10-year period, obesity showed no significant trend among women (adjusted odds ratio [AOR] for 2007-2008 vs 1999-2000, 1.12 [95% CI, 0.89-1.32]). For men, there was a significant linear trend (AOR for 2007-2008 vs 1999-2000, 1.32 [95% CI, 1.12-1.58]); however, the 3 most recent data points did not differ significantly from each other.
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Institute for Health Metrics and Evaluation1, University of Texas Health Science Center at San Antonio2, Emory University3, Mayo Clinic4, Harvard University5, Boston University6, Michigan State University7, National Institutes of Health8, Cedars-Sinai Medical Center9, Health Effects Institute10, Loyola University Chicago11, University of Washington12, University of California, San Diego13, University of Pennsylvania14, Veterans Health Administration15, Beth Israel Medical Center16, Johns Hopkins University17, Imperial College London18, Carnegie Mellon University19, Howard University20, University of California, San Francisco21, Columbia University22, New York University23, Karolinska Institutet24, George Mason University25, Nova Southeastern University26, University of Miami27, Northwestern University28, Thomas Jefferson University29, China Medical Board30, Pacific Institute31, Duke University32, Brigham and Women's Hospital33, California Environmental Protection Agency34, Centers for Medicare and Medicaid Services35, Brigham Young University36, University of Missouri37, University of California, Los Angeles38, Vanderbilt University39, University of Maryland, College Park40, University of Alabama at Birmingham41, Brandeis University42, University of Tokyo43, The Queen's Medical Center44, Drexel University45, Cincinnati Children's Hospital Medical Center46, National Institute for Occupational Safety and Health47, Brown University48, University of Melbourne49
TL;DR: To measure the burden of diseases, injuries, and leading risk factors in the United States from 1990 to 2010 and to compare these measurements with those of the 34 countries in the Organisation for Economic Co-operation and Development (OECD), systematic analysis of descriptive epidemiology was used.
Abstract: Importance Understanding the major health problems in the United States and how they are changing over time is critical for informing national health policy. Objectives To measure the burden of diseases, injuries, and leading risk factors in the United States from 1990 to 2010 and to compare these measurements with those of the 34 countries in the Organisation for Economic Co-operation and Development (OECD) countries. Design We used the systematic analysis of descriptive epidemiology of 291 diseases and injuries, 1160 sequelae of these diseases and injuries, and 67 risk factors or clusters of risk factors from 1990 to 2010 for 187 countries developed for the Global Burden of Disease 2010 Study to describe the health status of the United States and to compare US health outcomes with those of 34 OECD countries. Years of life lost due to premature mortality (YLLs) were computed by multiplying the number of deaths at each age by a reference life expectancy at that age. Years lived with disability (YLDs) were calculated by multiplying prevalence (based on systematic reviews) by the disability weight (based on population-based surveys) for each sequela; disability in this study refers to any short- or long-term loss of health. Disability-adjusted life-years (DALYs) were estimated as the sum of YLDs and YLLs. Deaths and DALYs related to risk factors were based on systematic reviews and meta-analyses of exposure data and relative risks for risk-outcome pairs. Healthy life expectancy (HALE) was used to summarize overall population health, accounting for both length of life and levels of ill health experienced at different ages. Results US life expectancy for both sexes combined increased from 75.2 years in 1990 to 78.2 years in 2010; during the same period, HALE increased from 65.8 years to 68.1 years. The diseases and injuries with the largest number of YLLs in 2010 were ischemic heart disease, lung cancer, stroke, chronic obstructive pulmonary disease, and road injury. Age-standardized YLL rates increased for Alzheimer disease, drug use disorders, chronic kidney disease, kidney cancer, and falls. The diseases with the largest number of YLDs in 2010 were low back pain, major depressive disorder, other musculoskeletal disorders, neck pain, and anxiety disorders. As the US population has aged, YLDs have comprised a larger share of DALYs than have YLLs. The leading risk factors related to DALYs were dietary risks, tobacco smoking, high body mass index, high blood pressure, high fasting plasma glucose, physical inactivity, and alcohol use. Among 34 OECD countries between 1990 and 2010, the US rank for the age-standardized death rate changed from 18th to 27th, for the age-standardized YLL rate from 23rd to 28th, for the age-standardized YLD rate from 5th to 6th, for life expectancy at birth from 20th to 27th, and for HALE from 14th to 26th. Conclusions and Relevance From 1990 to 2010, the United States made substantial progress in improving health. Life expectancy at birth and HALE increased, all-cause death rates at all ages decreased, and age-specific rates of years lived with disability remained stable. However, morbidity and chronic disability now account for nearly half of the US health burden, and improvements in population health in the United States have not kept pace with advances in population health in other wealthy nations.
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TL;DR: Although the AMPM accurately reported EIs in normal-weight subjects, research is warranted to enhance its accuracy in overweight and obese persons.
1,417 citations
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TL;DR: Two large epidemiological studies have been able to substantiate the relationship between SSB consumption and long-term weight gain, T2DM, and cardiovascular risk, and it is thought that SSBs contribute to weight gain because of their high added-sugar content, low satiety, and potential incomplete compensation for total …
Abstract: Obesity has recently emerged as a major global health problem. According to World Health Organization estimates, ≈1.6 billion adults worldwide were overweight (body mass index [BMI] ≥25 kg/m2) and at least 400 million were obese (BMI ≥30 kg/m2) in 2005, numbers that are expected to reach 2.3 billion and 700 million, respectively, by 2015. In the United States, the percentage of overweight and obese adults increased markedly from 47% and 15% in 1976 to 1980 to >66% and 33% in 2005 to 2006, with the greatest proportion of increase seen among non-Hispanic black and Mexican American women.1,2 The implications of excess body weight are far-reaching. Epidemiological studies indicate that overweight and obesity are important risk factors for type 2 diabetes mellitus (T2DM), cardiovascular disease, cancer, and premature death.3 In the United States, healthcare expenditures attributable to overweight and obesity are estimated to be $147 billion or 9.1% of total healthcare costs per year.4 Such excess costs could have serious repercussions for resource-poor countries, which must manage the dual burdens of chronic and infectious disease.
In the setting of a pandemic of obesity and related chronic diseases, the American Heart Association recently released a scientific statement recommending reductions in added-sugar intake to no more than 100 to 150 kcal/d for most Americans.5 The statement identified sugar-sweetened beverages (SSBs) as the primary source of added sugars in the American diet.6 Although it has long been suspected that SSBs contribute at least in part to the obesity epidemic, only in recent years have large epidemiological studies been able to substantiate the relationship between SSB consumption and long-term weight gain, T2DM, and cardiovascular risk. It is thought that SSBs contribute to weight gain because of their high added-sugar content, low satiety, and potential incomplete compensation for total …
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TL;DR: Findings suggest the local food environment is associated with residents' recommended diets, and black Americans' fruit and vegetable intake increased for each additional supermarket in the census tract.
Abstract: Objectives. We studied the association between the local food environment and residents’ report of recommended dietary intake. Methods. Recommended intakes of foods and nutrients for 10 623 Atherosclerosis Risk in Communities participants were estimated from food frequency questionnaires. Supermarkets, grocery stores, and full-service and fast-food restaurants were geocoded to census tracts. Results. Black Americans’ fruit and vegetable intake increased by 32% for each additional supermarket in the census tract (relative risk [RR] = 1.32; 95% confidence interval [CI] = 1.08, 1.60). White Americans’ fruit and vegetable intake increased by 11% with the presence of 1 or more supermarket (RR = 1.11; 95% CI = 0.93, 1.32). Conclusions. These findings suggest the local food environment is associated with residents’ recommended diets.
1,368 citations