Tampa Prep 2009-2010 Impact Defense File
Ext #3 – Obesity Doesn’t Kill
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Ext #3 – Obesity Doesn’t KillObesity doesn’t kill. Clare HERRICK Geography @ University College (London) ‘7 “Risky Bodies: Public health, social marketing, and the governance of obesity” Geoforum 38 (1) //AR Andrew Prentice and Susan Jebb’s landmark paper ‘Obesity in Britain: gluttony or sloth?’ argues that obesity prevention is “handicapped by uncertainty as to the aetiology of the problem” (1995, p. 437). Taken from a public health perspective, obesity is “one of the most important and avoidable risk factors for a number of life threatening diseases and for serious morbidity” (Prentice and Jebb, 1995, p. 437). However, the link between obesity and mortality has recently come under intense scrutiny after two conflicting articles were published in the same year in the Journal of the American Medical Association (JAMA) proposing a definitive obesity-related mortality rate in the United States. The US Surgeon General’s, 2001 Call to Action to prevent obesity is based on two rationales: that overweight and obesity are associated with an increased risk of disease and death and that weight loss reduces the incidence of risk factors for some diseases. These public health rationales have also been the foundation of social marketing campaign development. However, I suggest that the recently published papers have eroded this justificatory base and, in so doing, de-legitimised public health intervention permitting critical anti-obesity discourses to infiltrate the public realm. Writing in Science in April 2005, Jennifer Couzin suggests that the central question for obesity as a public health issue is how many people it kills. Since public health, as Brown and Duncan (2002) suggest, is the name given to a set of collective processes to ensure the good health of a given population, it is necessary to know disease prevalence and mortality rates so that these can be reduced by interventions such as social marketing or health promotion. As Michel Foucault (1976) has famously asserted, statistics have long been essential to the development of public health as they provide the basis for action (to reduce the disparity between the norm and the reality of statistics) and a measure of success (or how closely the new statistics match the norm). Health statistics are a powerful political tool, in that they provide quantitative proof of governments’ success in improving the wellbeing of the nation, in itself a central constituent of social rights. On the other hand, such statistics also expose the limits of government when it comes to reducing the risk of and vulnerability to conditions such as obesity. However, away from the question of success or failure, statistics also hold the potential to justify or destabilise policy priorities, especially when they appear flawed, uncertain or untenable. The US Centers for Disease Control (CDC) published a study in March 2004 using National Health and Nutrition Examination Survey (NHANES) data from the 1970s that put the death rate for obesity at 400,000 in 2000 in the US (Mokdad et al., 2004, p. 1238). This figure meant that obesity was poised to become the number one cause of death (above smoking) in the United States, and the news unsurprisingly made headlines across the nation. After the figures were published in JAMA, an article in Science questioned the validity of the methodology used. Then, in November 2004, The Wall Street Journal also attacked the validity of the figures. Dissent at the CDC provoked an internal inquiry, and the figure was subsequently revised downward by 9% to 365,000 deaths a year following a correction issued by Ali Mokdad and his colleagues in January 2005 (Mokdad et al., 2005, p. 291). This mortality rate still put obesity as the number two cause of death after smoking. With the health risks of smoking well accepted in both the US and UK, and smoker numbers falling year on year as a result, this death rate for obesity seemed to present unparalleled evidence that public health intervention was needed quickly. The media was swift to highlight the scale of the obesity epidemic and, in the UK, similar studies provoked the Department of Health to release the White Paper and start the process of NHS reforms needed to facilitate obesity prevention measures. On April 20, 2005, another paper using CDC data was published by Katherine Flegal et al. in JAMA. This study, using the same CDC NHANES data set but from later years, calculated that the number of annual deaths attributable to a BMI greater than 30.0 was 112,000. Of these, the authors calculated that 82,066 were among those with a BMI greater than 35.0. The authors also proposed that the risk of mortality among the overweight (BMI 25.0–29.9) was lower than those classified as underweight (BMI less than 18.5), relative to those of normal weight (BMI 18.5– 25.0). Flegal and colleagues concluded that while obesity prevalence was rising, death rates were in fact falling, most probably as a result of better treatment for coronary heart disease. Both studies used the ‘population attributable’ or ‘etiologic fraction’ (Mark, 2005, p. 1918) to calculate deaths from obesity. In brief, this is the proportion of morbidity in a population that can be attributed to a particular risk factor, such that the burden of disease from a risk factor is a function of the prevalence of that risk factor and the magnitude of its causal association with the disease (expressed as a relative risk). The greater the prevalence of the risk factor (i.e. obesity), the greater the relative risk and the greater the population attributable fraction. Since the population attributable fraction is “one of the most empowering concepts of the public health perspective on health” (Mark, 2005, p. 1918) as it assigns a numerical value to risk and probability of death, it is essential that this does not come into question. Statistics proclaiming the increased risk of death at higher body weights justify public health intervention to reduce the magnitude of the burden of disease. However, in this case, the justificatory basis for a public health discourse that constructs obesity as a disease or epidemic is eroded by statistics that show that being overweight could actually reduce mortality risk. Directory: files -> documents documents -> North Mankato Taylor Library documents -> In the Red and Brown Water documents -> - documents -> I. Disaster Summary Sheet II. Tropical Cyclones documents -> Cbp and Trade Automated Interface Requirements Appendix: pga december 22, 2015 documents -> Ace abi catair customs and Trade Automated Interface Requirements documents -> Ace abi catair customs and Trade Automated Interface Requirements documents -> Mobile audio/video recording systems documents -> Cartographic Concepts for Realizing a Location Based umts service documents -> 1/ Background Statistics Human development index rank Download 2.71 Mb. Share with your friends:
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