Policy Solutions to Address Obesity Colony S. Fugate, D.O., FACOP - - PowerPoint PPT Presentation

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Policy Solutions to Address Obesity Colony S. Fugate, D.O., FACOP - - PowerPoint PPT Presentation

Oct 11, 2023 351 likes •519 views

Policy Solutions to Address Obesity Colony S. Fugate, D.O., FACOP Diplomate American Board of Obesity Medicine Obesity Demographics 39.8% of Adults and 18.5% of children are obese nationally (Hales, et al) There is a significant upward

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SLIDE 1

Policy Solutions to Address Obesity

Colony S. Fugate, D.O., FACOP Diplomate American Board of Obesity Medicine

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SLIDE 2

Obesity Demographics

  • 39.8% of Adults and 18.5% of children are obese nationally (Hales, et al)
  • There is a significant upward trend in the rates of obesity between 1999-

2000 and 2015-2016 (Hales, et al)

  • Significant racial and ethnic disparities are noted with higher rates of
  • besity noted among non-Hispanic Blacks and Hispanics (Hales, et al)
  • 74.5% of men and 62.8% of women in Oklahoma are either overweight or
  • bese (KFF)
  • 12% of Oklahoma adults are diagnosed with diabetes, 36.2% have

hypertension, and 38% have elevated cholesterol (KFF)

  • Oklahoma is the has the 7th highest obesity rate, is the 4th most physically

inactive state, only 1 in 5 Oklahomans meeting fruit and vegetable consumption recommendations, and 44.6% of Oklahomans drink ≥ 1 SSB/day (Trust for America’s Health/MMWR 2010, 2016)

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SLIDE 3
  • Total cost of adult obesity is between $147 – $210 billion per year

(Cawley/Finkelstein), with $854 million per year spent in Oklahoma alone (Finkelstein 2004)

  • Obesity is associated with a 36% increase in clinical and hospital costs and

a 77% increase in medication costs (Wand and Dietz)

  • Childhood obesity is associated with $14.1 billion in additional medical

expenditures yearly (Trasande)

  • Obesity associated hospital costs in children 6-17 years of age tripled and

length of stay related to the diagnosis of obesity increased between 1979 and 1999 (Finkelstein 2003)

  • Oklahoma could save $7,444,000,000 in health care costs if the average

state BMI decreased by 5% by 2030 (F as in Fat)

Direct Medical Costs

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SLIDE 4
  • Absenteeism
  • Presenteeism (lower productivity)
  • Short-term disability
  • Disability
  • Premature mortality
  • Worker’s compensation
  • Personal costs

Indirect Costs

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SLIDE 5

Human Costs

  • Weight based stereotypes are common in our society leading to rejection,

prejudice and stigmatization. Individuals suffering from obesity suffer from bullying, physical aggression, economic inequality, psychological suffering and adverse effects on physical health. (Rebecca Puhl, PhD: Rudd Center)

  • Children who are obese have a quality of life similar to children with cancer

(Schwimmer, et al)

  • Children and adolescents who are obese and victimized due to their weight are 2

to 3 times more likely to engage in suicidal thoughts and behaviors (Rudd Center)

  • Overweight and obese adults often experience unfair treatment in the workplace

including: unfair hiring practices, lower wages, harsher discipline from employers, wrongful job termination, and negative stereotypes (Rudd Center)

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SLIDE 6

Complex Disease

  • Genetic
  • Epigenetic
  • Biologic
  • Physiologic
  • Behavioral
  • Environmental
  • Built Environment
  • Obesogenic Environment

Office of Behavioral and Social Science Research, NIH Bronfenbrenner, U. (1977).

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SLIDE 7

Sugar Sweetened Beverages

Increased levels of sugar sweetened beverage intake are associated with:

  • Childhood obesity
  • Weight gain in adults
  • Diabetes
  • Hypertension
  • Cardiovascular disease risk

Vasanti, SM et al 2010

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SLIDE 8

Food Insecurity

  • 12.3% of US households experience low or very low food security in

2016 (USDA)

  • Food insecurity is highest in households with children and greatest for

households with children headed by single females (USDA)

  • Food insecurity is positively associated with obesity in women,

though data is less consistent in other groups (Franklin, B. et al 2012, FRAC 2015)

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SLIDE 9

Supplemental Nutrition Assistance Program

  • Results reviewing the differences in dietary purchasing patterns as well as caloric, macronutrient,

micronutrient, and overall dietary quality patterns among SNAP participants, SNAP eligible non- participants, and higher income non-participants are mixed (USDA 2007, 2016/Andreyeva, et al 2015/Franckle, et al 2017)

  • SNAP participants, eligible non-participants, and non-participants are subject to the same market

forces which influence eating behaviors (USDA)

  • Studies have shown that combinations of restrictions and incentives may have an impact on food

purchasing behaviors (French, et al 2017/Olsho, LEW, et al 2017)

  • Concerns exist regarding feasibility and administrative burden specifically with regard to

implementation, monitoring compliance, and enforcement of additional restrictions (USDA 2007)

  • Concerns exist regarding increased stigma associated with restrictions (USDA 2007)
  • There is bi-partisan public support among SNAP participants and non-participants for SNAP (Long,

et al 2014)

  • There is public support among SNAP participants and non-participants to improve the nutritional

impact of SNAP (Long, et al 2014)

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Considerations

  • Further data is needed in consideration of the following questions:
  • Does limiting SSB and/or other foods and beverages of poor or limited nutritive value result in a change in

purchasing behaviors?

  • Does incentivizing the purchase of fruits and vegetables and/or other nutrient dense foods result in a change in

purchasing behaviors?

  • Does restricting purchases of SSB and/or other foods and beverages of poor or limited nutritive value result in

improved health outcomes?

  • Does incentivizing the purchase of fruits and vegetables and/or other nutrient dense foods improve health
  • utcomes?
  • What is the administrative burden of implementing additional restrictions in SNAP?
  • What is the cost/benefit to the State of Oklahoma? What is the cost/effectiveness of various strategies?
  • Does limiting SSB and/or other foods and beverages of poor or limited nutritive value contribute to stigma?
  • How do proposed changes in SNAP impact access to foods and beverages of high nutritional quality?
  • How do proposed changes in SNAP impact the program’s flexibility (ability to respond to changes such as natural

disasters and economic downturns)?

  • How do proposed changes in SNAP impact poverty?
  • What is the broader impact of changes to SNAP?
  • How do proposed changes in SNAP impact retailers and distributers? What is the overall economic impact in full

consideration of the costs of obesity?

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Review

  • Overweight and obesity rates are high nationally and in the state of

Oklahoma

  • Obesity underlies many conditions including diabetes, heart disease, and

cancer

  • Obesity has significant direct medical costs, indirect costs, and human costs
  • Excess sugar sweetened beverage consumption is one factor in the

complex causes of obesity

  • A comprehensive and strategic approach is necessary to reduce the rates of
  • besity and related costs
  • It is important to consider “Health in All Polices”; thus, a review of SNAP

within a public health context is warranted

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Recommendations

  • Address the broader food environment including access, food deserts,

public knowledge (including about the harms/types of SSB) through media/innovative educational campaigns

  • Consider a study that combines restrictions on a carefully defined

group of sugar sweetened beverages and incentives for a carefully defined group of fruits and vegetables to assess impact

  • Support current incentive programs (e.g. Double Up Food Bucks)
  • Support data-driven, outcome focused SNAP-Ed
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SLIDE 13

References

  • Hales CM, Carroll MD, Fryar CD, Ogden CL. Prevalence of obesity among adults and youth: United States, 2015–2016. NCHS data brief, no 288.

Hyattsville, MD: National Center for Health Statistics. 2017.

  • Kaiser Family Foundation analysis of the Centers for Disease Control and Prevention (CDC)'s Behavioral Risk Factor Surveillance System (BRFSS) 2013-

2016 Survey Results.

  • Trust for America’s Health and the Robert Wood Johnson Foundation, the State of Obesity. Better Policies for a Healthier America 2014.
  • Grimm, KA, et al. State-Specific Trends in Fruit and Vegetable Consumption Among Adults- United States, 2000 – 2009; MMWR. Sept 10, 2010; 59

(35): 1125-1130.

  • Park A, Xu F, Town M, Blanck HM. Prevalence of Sugar-Sweetened Beverage Intake Among Adults- 23 States and the District of Columbia, 2013.

MMWR Morb Mortality Wkly Report 2016; 65: 170-174.

  • Cawley J and Meyerhoefer C. “The Medical Care Costs of Obesity: An Instrumental Variables Approach.” J Health Econ. 2012 Jan; 31 (1): 219-30. doi:

10.1016/j.healeco.2011.10.003.Epub 2011 Oct 20.

  • Finkelstein et al. Annual Medical Spending Attributable To Obesity: Payer And Service-Specific Estimates. Health Affairs; 2009; 28, 5; Proquest pg

W822.

  • Finkelstein et al. State-level estimates of annual medical expenditures attributable to obesity. Obesity Research 2004;12(1):18–24
  • Guijing Wand, PhD and William Dietz, MD, PhD. Economic Burden of Obesity in Youths Aged 6- 17 Years: 1979-1999. Pediatrics Vol. 109 No. 5 May

2002, pp.e81.

  • Finkelstein et al. National Medical Expenditures Attributable to Overweight and Obesity: How much, and who’s paying? Health Affairs 2003; 22:8
  • F as in Fat: How Obesity Threatens America’s Future 2012. Trust for American’s Health and Robert Wood Johnson Foundation.

http://healthyamericans.org/report/100/

  • Finkelstein, E. A., Graham, W. C. K., & Malhotra, R. (2014). Lifetime direct medical costs of childhood obesity. Pediatrics, 133, 854-862. doi:

10.1542/peds.2014-0063

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SLIDE 14

References

  • Trasande L. and Chatterjee S. “The Impact of Obesity on Health Service Utilization and Costs in Childhood.” Obesity. 2009 Sept;

17(9):1749–54. doi: 10.1038/oby.2009.67. Epub 2009 Mar 19.

  • Annual Medical Spending Attributable To Obesity: Payer-And Service-Specific Estimates Eric A. Finkelstein, Justin G. Trogdon, Joel
  • W. Cohen, and William Dietz Health Aff September/October 2009 28:5 w822-w831; published ahead of print July 27, 2009,

doi:10.1377/hlthaff.28.5.w822

  • Trasande L, Liu Y, Fryer G, et al. Effects of Childhood Obesity On Hospital Care and Costs, 1999-2005. Health Affairs, 28(4): w751-60,

2009.

  • UConn Rudd Center (formerly Yale Rudd Center): http://www.yaleruddcenter.org/
  • Schwimmer JB, Burwinkle TM, Varni JW. Health-Related Quality of Life of Severely Obese Children and Adolescents. JAMA.

2003;289(14):1813-1819. doi:10.1001/jama.289.14.1813.

  • Office of Behavioral and Social Science Research, National Institutes of Health

http://www.esourceresearch.org/Default.aspx?TabId=736 Source: Bronfenbrenner, U. (1977). Toward an experimental ecology of human development. American Psychologist, 32(7), 513-531

  • Vasanti, SM, Popkin, BM, Bray, GA, Despres, JP, and Hu FB. Sugar-Sweetened Beverages, Obesity, Type 2 Diabetes Mellitus, and

Cardiovascular Disease Risk. Circulation 2010; 121: 1356-1364. doi:10.1161/circulationaha.109.876185

  • Household Food Security in the United States. USDA ERS. https://www.ers.usda.gov/topics/food-nutrition-assistance/food-

security-in-the-us/key-statistics-graphics.aspx#trends Accessed November 6, 2017.

  • Franklin, B., Jones, A., Love D., Puckett S., Macklin J., White-Means S. Exploring Mediators of Food Insecurity and Obesity: A

Review of Recent Literature. J Community Health2012. Feb 37(1): 253-264. doi: 10.1007/s10900-011-9420-4

  • Understanding the Connections: Food Insecurity and Obesity. Food Action Research Center Research Brief 2015
  • Implications of Restricting the Use of Food Stamp Benefits-Summary. USDA Food and Nutrition Service. March 1, 2007.
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SLIDE 15

References

  • Foods Typically Purchased By Supplemental Nutrition Assistance Program (SNAP) Households (Summary). USDA Food and

Nutrition Service November 2016.

  • Andreyeva, T., Tripp AS., Schwartz MB. Dietary Quality of Americans by Supplemental Nutrition Assistance Program Participation

Status A Systematic Review. Am J Prev Med 2015; 49(4):594-604. doi:10.1016/j.ampere.2015.04.035

  • Franckle, RL., Moran A., Blue D., et al. Transactions at a Northeastern Supermarket Chain: Differences by Supplemental Nutrition

Assistance Program Use. Am J Prev Med 2017; 53(4):e131-138. doi:10.1016/j.ameprev.2017.06.019

  • French SA., Rydell SA., Mitchell NR., et al. Financial incentives and purchase restrictions in a food benefit program affect the types
  • f foods and beverages purchased: results from a randomized trial. Int J of Beh Nutri and Phys Activity. 2017; 14:127. doi:

10.1186/s12966-017-0585-9.

  • Olsho LEW., Klerman JA., Bartlett SH., Logan CW. Rebates to Incentivize Healthy Nutrition Choices in the Supplemental Nutrition

Assistance Program. Am J Prev Med 2017; 52(2S2): S161-S170. doi: 10.1016/j.ampere.2016.08.023

  • Long MW., Leung CW., Cheung LWY., et al. Public Support for Policies to Improve the Nutritional Impact of the Supplemental

Nutritional Assistance Program (SNAP). Public Health Nutr. 2014 January; 17(1): 219-224. doi:10.1017/S136898001200506X

  • Health in All Policies A Guide for State and Local Governments. http://www.phi.org/resources/?resource=hiapguide