Rosamond, Paul D. Sorlie, Randall S. Stafford, Tanya N. Turan, Melanie B. Turner, Nathan D. Dariush Mozaffarian, Michael E. Mussolino, Graham Nichol, Nina P. Paynter, Wayne D. Ariane Marelli, David B. Matchar, Mary M. McDermott, James B. Meigs, Claudia S. Moy, Lackland, Judith H. Lichtman, Lynda D. Lisabeth, Diane M. Makuc, Gregory M. Marcus, John A. Heit, P. Michael Ho, Virginia J. Howard, Brett M. Kissela, Steven J. Kittner, Daniel T. Caroline S. Fox, Heather J. Fullerton, Cathleen Gillespie, Kurt J. Greenlund, Susan M. Hailpern, Todd M. Brown, Mercedes R. Carnethon, Shifan Dai, Giovanni de Simone, Earl S. Ford, Véronique L. Roger, Alan S. Go, Donald M. Lloyd-Jones, Robert J. Adams, Jarett D. Berry, Association 2011 Update : A Report From the American Heart −− Heart Disease and Stroke Statistics

Heart Disease and Stroke Statistics—2011 Update A Report From the American Heart Association

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .e3

1. About These Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .e7

2. American Heart Association's 2020 Impact Goals. . . . . . . . . . . . . . . . .e10

3. Cardiovascular Diseases . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .e21

4. Subclinical Atherosclerosis . . . . . . . . . . . . . . . . . . . . .e45

5. Coronary Heart Disease, Acute Coronary Syndrome, and Angina Pectoris . . . . . . . . .e54

6. Stroke (Cerebrovascular Disease) . . . . . . . . . . . . . . . . . . . . . . . . . . . .e68

7. High Blood Pressure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . .e88

8. Congenital Cardiovascular Defects . . . . . . . . . . . . . . . . . . . . . . . . . . . .e97

9. Cardiomyopathy and Heart Failure . . . . . . . . . . . . . . . . . . . . . . . . . . . .e102

10. Disorders …

Heart Disease and Stroke Statistics—2012 Update A Report From the American Heart Association

Author(s): Go, Alan S; Mozaffarian, Dariush; Roger, Veronique L; Benjamin, Emelia J; Berry, Jarett D; Blaha, Michael J; Dai, Shifan; Ford, Earl S; Fox, Caroline S; Franco, Sheila; Fullerton, Heather J; Gillespie, Cathleen; Hailpern, Susan M; Heit, John A; Howard, Virginia J; Huffman, Mark D; Judd, Suzanne E; Kissela, Brett M; Kittner, Steven J; Lackland, Daniel T; Lichtman, Judith H; Lisabeth, Lynda D; Mackey, Rachel H; Magid, David J; Marcus, Gregory M; Marelli, Ariane; Matchar, David B; McGuire, Darren K; Mohler, Emile R; Moy, Claudia S; Mussolino, Michael E; Neumar, Robert W; Nichol, Graham; Pandey, Dilip K; Paynter, Nina P; Reeves, Matthew J; Sorlie, Paul D; Stein, Joel; Towfighi, Amytis; Turan, Tanya N; Virani, Salim S; Wong, Nathan D; Woo, Daniel; Turner, Melanie B; American Heart Association Statistics Committee and Stroke Statistics Subcommittee

Heart Disease and Stroke Statistics—2014 Update A Report From the American Heart Association

https://www.demogr.mpg.de/publications/files/3444_1264435180_1_Christensen%20et%20al%20Lancet%20374%209696%202009.pdf

Ageing populations: the challenges ahead

Obese individuals are highly stigmatized and face multiple forms of prejudice and discrimination because of their weight (1,2). The prevalence of weight discrimination in the United States has increased by 66% over the past decade (3), and is comparable to rates of racial discrimination, especially among women (4). Weight bias translates into inequities in employment settings, health-care facilities, and educational institutions, often due to widespread negative stereotypes that overweight and obese persons are lazy, unmotivated, lacking in selfdiscipline, less competent, noncompliant, and sloppy (2,5–7). These stereotypes are prevalent and are rarely challenged in Western society, leaving overweight and obese persons vulnerable to social injustice, unfair treatment, and impaired quality of life as a result of substantial disadvantages and stigma. In 2001, Puhl and Brownell published the first comprehensive review of several decades of research documenting bias and stigma toward overweight and obese persons (2). This review summarized weight stigma in domains of employment, health care, and education, demonstrating the vulnerability of obese persons to many forms of unfair treatment. Despite evidence of weight bias in important areas of living, the authors noted many gaps in research regarding the nature and extent of weight stigma in various settings, the lack of science on emotional and physical health consequences of weight bias, and the paucity of interventions to reduce negative stigma. In recent years, attention to weight bias has increased, with a growing recognition of the pervasiveness of weight bias and stigma, and its potential harmful consequences for obese persons. The aim of this article is to provide an update of scientific evidence on weight bias toward overweight and obese adults through a systematic review of published literature since the 2001 article by Puhl and Brownell. This review expands upon previous findings of weight bias in major domains of living, documents new areas where weight bias has been studied, and highlights ongoing research questions that need to be addressed to advance this field of study. A systematic literature search of studies published between January 2000 and May 2008 was undertaken on computerized psychological, medical, social science, sport, and education databases including PsycINFO, PubMed, SCOPUS, ERIC, and SPORTDiscus. The following keyword combinations were used: weight, obese, obesity, overweight, BMI, fat, fatness, size, heavy, large, appearance, big, heavyweight, bias, biased, discrimination, discriminatory, discriminate, stigma, stigmatized, stigmatization, prejudice, prejudicial, stereotype(s), stereotypical, stereotyping, victimization, victimize(d), blame(d), blaming, shame(d), shaming, teasing, tease(d), unfair, bully, bullying, harassment, assumptions, attributions, education, health, health care, sales, employment, wages, promotion, adoption, jury, customer service, housing, media, television. Reference lists of retrieved articles and books were also reviewed, and manual searches were conducted in the databases and journals for authors who had published in this field. Most studies retrieved for this review were published in the United States. Any articles published internationally are noted with their country of origin. Research on weight stigma in adolescents and children was excluded from this review, as this literature was recently reviewed elsewhere (8). Unpublished manuscripts and dissertations were also excluded. In addition, issues pertaining to measurement of weight stigmatization, and demographic variables affecting vulnerability to weight bias such as gender, age, race, and body weight are not addressed in this review. This article instead primarily reviews the evidence of specific areas where weight bias occurs toward adults and its consequences for those affected. This article is organized similarly to the first review published by Puhl and Brownell (2), with sections on weight bias in settings of employment, health care, and education. New sections have been added including weight bias in interpersonal relationships and the media, as well as psychological and physical health consequences of weight bias, and the status of stigma-reduction research. As with the 2001 article, this review also provides an update on legal initiatives to combat weight discrimination, and outlines specific questions for future research.

https://www.sochob.cl/pdf/obesidad_adulto/The%20Stigma%20of%20Obesity%20%20A%20Review%20and%20Update.pdf

The stigma of obesity: a review and update.

In light of proposals to improve diets by shifting food prices, it is important to understand how price changes affect demand for various foods.We reviewed 160 studies on the price elasticity of demand for major food categories to assess mean elasticities by food category and variations in estimates by study design. Price elasticities for foods and nonalcoholic beverages ranged from 0.27 to 0.81 (absolute values), with food away from home, soft drinks, juice, and meats being most responsive to price changes (0.7–0.8). As an example, a 10% increase in soft drink prices should reduce consumption by 8% to 10%.Studies estimating price effects on substitutions from unhealthy to healthy food and price responsiveness among at-risk populations are particularly needed.

https://ajph.aphapublications.org/doi/pdfplus/10.2105/AJPH.2008.151415

The impact of food prices on consumption: a systematic review of research on the price elasticity of demand for food.

Perceptions of weight discrimination: prevalence and comparison to race and gender discrimination in America

http://www.uconnruddcenter.org/resources/upload/docs/news/IJO2008.pdf

Perceptions of weight discrimination: prevalence and comparison to race and gender discrimination in America.

Objective: Little is known about the prevalence and patterns of weight discrimination in the United States. This study examined the trends in perceived weight/height discrimination among a nationally representative sample of adults aged 35–74 years, comparing experiences of discrimination based on race, age, and gender.

Methods and Procedures: Data were from the two waves of the National Survey of Midlife Developmentin the United States (MIDUS), a survey of community-based English-speaking adults initially in 1995–1996 and a follow-up in 2004– 2006. Reported experiences of weight/height discrimination included a variety of settings in major lifetime events and interpersonal relationships.

Results: The prevalence of weight/height discrimination increased from 7% in 1995–1996 to 12% in 2004–2006, affecting all population groups but the elderly. This growth is unlikely to be explained by changes in obesity rates.

Discussion: Weight/height discrimination is highly prevalent in American society and increasing at disturbing rates. Its prevalence is relatively close to reported rates of race and age discrimination, but virtually no legal or social sanctions against weight discrimination exist.

https://onlinelibrary.wiley.com/doi/pdf/10.1038/oby.2008.35

Changes in perceived weight discrimination among Americans, 1995-1996 through 2004-2006.

A B S T R A C T There is insufficient research on the direct effects of food advertising on children’s diet and diet-related health, particularly in non-experimental settings. We employ a nationallyrepresentative sample from the Early Childhood Longitudinal Survey–Kindergarten Cohort (ECLS-K) and the Nielsen Company data on spot television advertising of cereals, fast food restaurants and soft drinks to children across the top 55 designated-market areas to estimate the relation between exposure to food advertising on television and children’s food consumption and body weight. Our results suggest that soft drink and fast food television advertising is associated with increased consumption of soft drinks and fast food among elementary school children (Grade 5). Exposure to 100 incremental TV ads for sugar-sweetened carbonated soft drinks during 2002–2004 was associated with a 9.4% rise in children’s consumption of soft drinks in 2004. The same increase in exposure to fast food advertising was associated with a 1.1% rise in children’s consumption of fast food. There was no detectable link between advertising exposure and average body weight, but fast food advertising was significantly associated with body mass index for overweight and obese children (85th BMI percentile), revealing detectable effects for a vulnerable group of children. Exposure to advertising for calorie-dense nutrient-poor foods may increase overall consumption of unhealthy food categories.

/pdf/exposure-to-food-advertising-on-television-associations-with-3q3qq39sda.pdf

Exposure to food advertising on television: associations with children's fast food and soft drink consumption and obesity.

Objective: To analyze health care use and expenditures associated with varying degrees of obesity for a nationally representative sample of individuals 54 to 69 years old.

Research Methods and Procedures: Data from the Health and Retirement Study, a nationwide biennial longitudinal survey of Americans in their 50s, were used to estimate multivariate regression models of the effect of weight class on health care use and costs. The main outcomes were total health care expenditures, the number of outpatient visits, the probability of any inpatient stay, and the number of inpatient days.

Results: The results indicated that there were large differences in obesity-related health care costs by degree of obesity. Overall, a BMI of 35 to 40 was associated with twice the increase in health care expenditures above normal weight (about a 50% increase) than a BMI of 30 to 35 (about a 25% increase); a BMI of over 40 doubled health care costs (∼100% higher costs above those of normal weight). There was a difference by gender in how health care use and costs changed with obesity class. The primary effect of increasing weight class on health care use appeared to be through elevated use of outpatient health care services.

Discussion: Obesity imposes an increasing burden on the health care system, and that burden grows disproportionately large for the most obese segment of the U.S. population. Because the prevalence of severe obesity is increasing much faster than that of moderate obesity, average estimates of obesity effects obscure real consequences for individuals, physician practices, hospitals, and health plans.

https://onlinelibrary.wiley.com/doi/pdf/10.1038/oby.2004.243

Tatiana Andreyeva

Papers

The impact of food prices on consumption: a systematic review of research on the price elasticity of demand for food.

Perceptions of weight discrimination: prevalence and comparison to race and gender discrimination in America.

Changes in perceived weight discrimination among Americans, 1995-1996 through 2004-2006.

Exposure to food advertising on television: associations with children's fast food and soft drink consumption and obesity.

Moderate and severe obesity have large differences in health care costs.