1. Dietary Intake and Obesity Kiyah Duffey Department of Nutrition The University of North Carolina at Chapel Hill April 14, 2008

2. Outline Nutritional Epidemiology, at UNC Factors affecting food choice  Focus on extra-personal factors Consequences of food choice: obesity  Background  Epidemiology/ Current Trends Research at UNC  Beverages  Fast food  The food environment

3. Nutrition Epidemiology Epidemiology is the study of the distribution of disease in a population.  Population-level causes of disease At UNC, focus is on the link between diet & physical activity and obesity; nutrition transition in developing countries  US, China, Philippines, Russia, Brazil

4. Factors Influencing Dietary Intake & Food Choice

6. Food choice influenced by numerous factors- At numerous levels Developed by Dr. Penny Gordon Larsen, UNC Chapel Hill Dept of Nutrition for the NHLBI Workshop: Predictors of Obesity, Weight Gain, Diet, and Physical Activity; August 2004, Bethesda MD Food Choice Dietary Patterns & Nutrient Intake: Type, Amount, Frequency of foods eaten Biological & Demographic Age, sex, SES, genetics, disease states Psychological Preferences, emotions, body image, motivation, knowledge Social/Cultural Family factors, peer influence social norms, acculturation Physical Environment Access, urban design, transportation, advertising Policies/Incentives Cost & availability: Environmental regulation Organizational Programs & policies in schools, worksite, community orgs

7. Factors Affecting Food Choice Physical Environment: Location Social/Cultural: Visual Cues, portion size Policies: Advertising

8. Location

9. Black neighborhoods have higher density of fast food outlets Orleans Parish, LA Modeled probability of fast food outlets (FFO) given race and income Black neighborhoods had more FFO/mi 2 than White neighborhoods: 2.4 vs. 1.5 Block et al. Am. J. Preventive Med. 2004:27(3):211-7.

10. Fruit & vegetable consumption is affected 8% of Blacks vs. 31% Whites lived in census tract with ≥1 supermarket * Blacks: 1.31 and 2.18 times more likely to meet guidelines for F&V consumption if there was 1 or 2 supermarkets in their census tract * Greater no. fast food & convenience stores in their neighborhood associated with decreased F&V consumption in Australian children † *Moreland et al. Am J Public Health. 2002 Nov;92(11):1761-7 †Timperio et al. Preventive Medicine. 2008; 46:331-335

11. Location of Fast Food Outlets to Chicago Schools:  35% w/ in 400m  80% w/ in 800m 3 - 4 times more FF w/in 1.5 km from schools than expected if distributed randomly More highly clustered:  outside downtown  mid-upper income  commercialized Austin et al. American Journal of Public Health 2005; 95( 9):1575-1581 Clustering of fast food outlets around schools

12. Remaining questions… Is access equated with intake?  Do more fast food outlets mean a greater consumption of fast food? If ‘healthier’ options “move into” a neighborhood, are dietary patterns/ food choice affected? Are the observed relationships due to the fact that “healthier” people want to live in “healthier” neighborhoods?  Reverse causality and residential selection

13. Visual Cues

14. Are all containers created equal? People consumed more beverage from short fat glasses than tall thin ones 4, 2L bowls vs. 2 4L bowls  Self-serve  Serving from 4L bowls resulted in 53% more taken, 56% more calories consumed < Brian Wansink, Cornell University: Nutrition Psychology. Unpublished data <

15. Would you like popcorn with that? 158 moviegoers Popcorn buckets weighed before and after movie 2-week old popcorn tasted “stale”, “soggy”, “terrible” Fresh 240 g120 g 2-Weeks old 240 g120 g < > 33% > 41% Wansink & Kim. 2005. J Nutr Educ Behav: 37; 242-45

16. “Bottomless” bowls increase lunch calories 54 adults 20 min, free lunch Half given 18 oz, half given “bottomless” bowls 20% more soup (113 kcals) eaten from bottomless bowls No differences in estimated caloric intake or reported satiety Brian Wansink. 2005. Obesity Research: 13(1); 93-100

17. Portion Size

18. Portion sizes increasing, cheeseburger Calorie difference: 257 calories 590 calories 20 Years AgoToday 333 calories

19. Portion sizes increasing, bagels 140 calories 3-inch diameter Calorie Difference: 210 calories 350 calories 6-inch diameter 20 Years AgoToday

20. Effect of portion size on energy intake Rolls et al. 2004, 2005 Altered portion sizes of sandwiches, macaroni dishes & pre-packaged chips Participants free to eat at will Measured plate waste, and asked respondents about level of satiety

21. Pasta entrée size affects total caloric intake 600 400 200 Energy Intake (kcal) 600 400 Energy Intake (kcal) Diliberti et al. 2004. Obesity Research: 12(3);562-568 * *

22. Sandwich size affects energy intake Females (n=37)Males (n=38) Rolls et al. J Amer Diet Assoc. 2004; 104:367-372 0 200 400 600 800 1000 1200 681012681012 Sandwich Size (inches) Energy Intake (kcals) + 159 kcals+ 355 kcals

23. Advertising and Other Influences

24. Advertising Children (<12y) viewed ~4,900 food & restaurant commercials/year http://www.msnbc.msn.com/id/15095189/ Snickers budget alone 8 x greater than 5-a-day $11.6 billion $9.5 million http://www.consumersunion.org/pub/core_health_care/002657.html

25. Other influences Changing food supply  ~3900kcal/person available*  Significant increases in added sugars Pricing Availability at home  Carrots slices vs. Doritos Parental Influences  Overweight children are more likely to have overweight parents *Data are based on ERS estimates of per capita quantities of food available for consumption, imputed consumption data, and on estimates from USDA's. Source: USDA/Center for Nutrition Policy and Promotion. Accessed April 11, 2008. http://www.ers.usda.gov/Data/FoodConsumption/NutrientAvailIndex.htm

26. Consequences of Food Choice: Overweight & Obesity

27. Senate bill bans obesity lawsuits By Marguerite Higgins THE WASHINGTON TIMES 'Freshman 15' really 5 or 7, but the gains don't stop CNN, POSTED: 11:37 a.m. EDT, October 23, 2006,

28. Defining overweight & obesity Excess of body fat for a given height and weight For research in adults, typically defined using BMI (kg/m 2 )  % body fat, waist circumference, WHR Example  6’0”, 160 lbs, BMI=21.7; 200 lbs, BMI=27.1  5,4”, 145 lbs,BMI=24.9; 170 lbs, BMI=29.2

29. Defining adult overweight, obesity BMI (kg/m 2 ) BMIWeight Status <18.5Underweight 18.5-24.9Normal weight 25.0-29.9Overweight ≥ 30.0 30.0-34.9Obese 35.0-39.9Severe obesity ≥ 40.0Morbid obesity Adapted: National Heart, Lung, and Blood Institute Guidelines. Obes Res.1998:6(suppl 2):51S-209S.

30. BMI Correlates with % Body Fat

31. Evidence of a problem About 127 million US adults are overweight 60 million obese, 9 million severely obese (equivalent to BMI ≥40) Ogden et al. JAMA 2006: 1549-1555 Percent

32. No Data <10% 10%–14% (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 1985 http://www.cdc.gov/nccdphp/dnpa/obesity/trend/maps/

33. No Data <10% 10%–14% (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 1986

34. No Data <10% 10%–14% (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 1987

35. No Data <10% 10%–14% (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 1988

36. No Data <10% 10%–14% (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 1989

37. No Data <10% 10%–14% (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 1990

38. No Data <10% 10%–14% 15%–19% (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 1991

39. No Data <10% 10%–14% 15%–19% (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 1992

40. No Data <10% 10%–14% 15%–19% (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 1993

41. No Data <10% 10%–14% 15%–19% (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 1994

42. No Data <10% 10%–14% 15%–19% (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 1995

43. No Data <10% 10%–14% 15%–19% (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 1996

44. No Data <10% 10%–14% 15%–19% ≥20 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 1997

45. No Data <10% 10%–14% 15%–19% ≥20 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 1998

46. Obesity Trends* Among U.S. Adults BRFSS, 1999 No Data <10% 10%–14% 15%–19% ≥20 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person)

47. No Data <10% 10%–14% 15%–19% ≥20 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 2000

48. No Data <10% 10%–14% 15%–19% 20%–24% ≥25% (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) Obesity Trends* Among U.S. Adults BRFSS, 2001

49. Obesity Trends* Among U.S. Adults BRFSS, 2003 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% ≥25%

50. Obesity Trends* Among U.S. Adults BRFSS, 2004 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% ≥25%

51. Obesity Trends* Among U.S. Adults BRFSS, 2005 (*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

52. Obesity Trends* Among U.S. Adults BRFSS, 2006 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

53. Annual Absolute Change in the Prevalence of Overweight in 7 Countries, 1985-2004 Annual percentage change Source: Popkin et al, (in press) Obes. Res.

54. Health Consequences of Obesity Hypertension Dyslipidemia (for example, high total cholesterol or high levels of triglycerides) Type 2 diabetes Coronary heart disease Stroke Gallbladder disease Osteoarthritis Sleep apnea and respiratory problems Some cancers (endometrial, breast, and colon) $102.2 billion

55. Current obesity-related research at UNC

56. Beverages

57. Beverage consumption has increased Beverages account for ~21% of daily caloric intake In 2002 adults consumed 450 calories from beverages, 220 more than in 1965  No. of ounces of beverages has not changed

58. Per capita calories from whole-fat milk decline, soda and alcohol on the rise Total daily calories, per capita Duffey & Popkin, Obesity. 2007 Nov;15(11):2739-47.

59. Little change in water, major increase in calorically-sweetened beverages Ounces 79.7 101.5 Duffey & Popkin, Obesity. 2007 Nov;15(11):2739-47.

60. Beverage Guidance System Leading researchers in nutrition, obesity & physiology Designed to provide guidance on the relative health and nutritional benefits and risks of various beverage categories  Popkin et al., Am J Clin Nutr. 2006 Mar; 83(3):529-42.

61. Ideal adult beverage pattern: 2200 kcals/day, 10% energy from beverages CALORICALLY SWEETENED WITH NUTRIENTS Total 98 FL OZ NONCALORICALLY- SWEETENED BEVERAGES (0 FL OZ) LEVEL I LEVEL II LEVEL III LEVEL IV LEVEL VI LEVEL V ALCOHOL (BEER) (0 FL OZ) FRUIT JUICES (4 FL OZ) CALORICALLY-SWEETENED BEVERAGES WITHOUT NUTRIENTS (0 FL OZ) WATER (50 FL OZ) TEA/COFFEE, UNSWEETENED (28 FL OZ) LOW FAT MILK (16 FL OZ) Popkin et al., Am J Clin Nutr. 2006 Mar;83(3):529-42.

62. Beverage and food choices are linked Many studies have shown that beverages have weak satiety properties and elicit poor dietary compensation. Among consumers  greater intake of calorically-sweetened beverages (soda) than caloric beverages that contain nutrients (milk).

63. 52 22.3 25 26 12 11 21 28 0 10 20 30 40 50 60 WaterCoffeeTeaDietLow-Fat MilkFruit JuiceVegetable Juice Fruit DrinksSoda Beverages Among Consumers *, Mean Fluid Ounce Intake Greater for Calorically-Sweetened Beverages Mean Consumption (fl. oz.) Unsweetened Caloric w/ Nutrients Calorically- Sweetened * Adults 18+ years from NHANES 1999-2002 survey Diet 52 22.3 25 26 12 11 21 28 0 10 20 30 40 50 60 WaterCoffeeTeaDietLow-Fat MilkFruit Juice Vegetable Juice Fruit DrinksSoda Beverages

64. How are beverages & foods linked? Do certain beverages tend to be consumed together (are there patterns of beverage intake)? If so, how do food patterns associate with these beverage patterns?

65. Finding patterns within individuals Cluster analysis used to find patterns in beverage (9) & food (14) variables Method places people into groups based on their intake of selected foods and beverages  Groups are named according to the foods that are contribute most to intake, differentiate one pattern from another

66. Final Food Clusters * Normal 55% Cereal & LF Meat 10% Vegetables 5% Fruit & LF Dairy 5% Snacks & HF Foods 14% Fast Food 11% *Adults, 19+

67. Final Beverage Clusters * Water & Tea 14% Coffee, Water & Tea 19% Diet 14% Coffee & Soda 22% Nutrients & Soda 14% Soda 17% *Adults, 19+

68. Fast Food Membership Linked with Decreased Probability * of Consuming Water-Containing Beverage Patterns *Predictions from mlogit results controlling for age, race, gender, income, education & overweight status 10.3 11.9 9.6 26.1 17.8 24.2 15 15.6 11.3 22.5 15.4 17.3 0 5 10 15 20 25 30 Water & TeaCoffee, Water & Tea DietCoffee & Soda Nutrients & Soda Beverage Cluster Percent of Sample Fast Food MemberFast Food Non-Member

69. Vegetable Group Membership Linked with Decreased Probability * of Consuming Soda 20.9 20.8 8.5 24 17.9 10.9 14.1 17.8 11.2 22.8 15.7 18.4 0 5 10 15 20 25 30 Water & Tea Coffee, Water & Tea DietCoffee & Soda Nutrients & Soda Beverage Clusters Percent of Sample Vegetable MemberVegetable Non-Member *Predictions from mlogit results controlling for age, race, gender, income, education & overweight status

70. Beverage calories are added calories Caloric and non-caloric beverages tend to be consumed independently Healthier diet patterns associated with healthier beverage patterns Substituting non-caloric beverages for caloric ones can help reduce total energy intake

71. Fast food and restaurant consumption Away-From-Home (AFH) eating provides >30% total daily energy intake among adolescents/adults Evidence suggests that:  AFH food typically higher in total calories, saturated fat, refined carbohydrates and cholesterol  Higher frequency of AFH consumption may be associated with BMI and weight change Little is known about nutritional differences between restaurant and fast food as they are usually studied together

72. Total energy intake by location, among adults aged 19-29 Nielsen et. Al. (2002). Obesity Research 10: 370-378. Ounces

73. Study Questions Do fast foods and restaurant foods have differential effects on weight gain? What happens to these effects if the two sources of away from home eating are combined into a single measure?

74. Study Population & Methods CARDIA: longitudinal data Study years 0 (1985-86) and 7 (1992-93); adults aged 18-30 Defined patterns of fast food and restaurant food intake Modeled the association of eating away from home with weight change and total caloric intake

75. Higher 7-year Fast Food Intake is Associated with Greater 7-year BMI Gain in White Females* *Model 1: adjusted prevalence stratified multinomial logistic regression models controlled for: age, income, education, eating pattern (maintain low, decreased, increased, maintain high fast food) and study center. ** p<0.05, compared to referent category (maintained BMI). 0 10 20 30 40 50 60 70 80 Percent of white women n=112n=363n=557 Fast Food Intake From Year 0 to 7 11 33 56 10 33 57 9 23** 11 34 55 68** Lost > 1 BMI unitMaintained BMIGained > 1 BMI unit Maintained Low Decreased Increased Maintained High

76. Higher Fast Food (versus Restaurant) Intake is Associated with Higher BMI Gains over a 7-year Period in White Females* n=112n=363n=557 *Model 2: adjusted prevalence stratified multinomial logistic regression models controlled for: age, income, education, eating pattern at time 7 (high v. low intake of restaurant, fast food or combination) and study center. ** p<0.05, compared to the referent category (maintained BMI).

77. Conclusions Increase in fast food consumption associated with greater likelihood of increase in BMI Higher restaurant (versus higher fast food) consumption is associated with greater likelihood of maintenance of BMI Combining AFH to a single measure masks the independent associations of these two food sources with long-term energy intake and BMI

78. What’s Next? How does an individual’s neighborhood impact their food choices, dietary intake, physical activity patterns and weight gain? Do changes in the environment lead to changes in these outcomes?

79. Derived Measures Distance Matrices, Network Calculations, Connectivity, Community Classifications GIS Database Respondent Locations PA Resources Contextual Data Land Use Ancillary Data (Roads, Administrative Boundaries, etc.) GPS Data

80. Obesity & The Environmnt The University of North Carolina at Chapel Hill Respondents Block Group Boundary Residential Neighborhoods

81. Obesity & The Environment The University of North Carolina at Chapel Hill Respondents Individual Buffer Community Study Area Sampled Block Group Create Buffer Zones, 5 Mile from Residential Location

82. Obesity & The Environment The University of North Carolina at Chapel Hill Respondents Individual Buffer Community Study Area Sampled Block Group Block Group Boundary Food Sources Measures Food Sources in 5 Mile Buffers

83. Intended Analysis Examine average distance to and count of fast food and restaurant places within buffers around residential locations Determine if proximity → times/week consumption Determine if consumption → weight gain 8

84. For consideration… For obesity prevention continued need for unified, simple message Conventional vs. Organic  Whole Foods & Michael Pollan  http://gristmill.grist.org/story/2006/6/29/143121/559?source=weekly Local vs. long-distance foods  Upcoming class, April 23rd Acceptable interventions?  Nutrition labeling at point of purchase; restaurant menus, menu boards NY City Health Department Proposed Regulation

85. Selected References Books:  Food Politics, Marion Nestle  The Hungry Gene Ellen Ruppel Shell  Food Fight, Kelly Brownell  The Omnivore’s Dilemma and In Defense of Food, Michael Pollan Websites  http://www.consumersunion.org/pub/core_health_care/002657.html http://www.consumersunion.org/pub/core_health_care/002657.html  http://www.cdc.gov/nccdphp/dnpa/obesity/trend/maps/ http://www.cdc.gov/nccdphp/dnpa/obesity/trend/maps/  The Food Trust: http://www.thefoodtrust.org/php/programs/farmers.market.program.phphttp://www.thefoodtrust.org/php/programs/farmers.market.program.php  Food Policy Institute: http://www.preventioninstitute.org/npp.htmlhttp://www.preventioninstitute.org/npp.html  Pro Restaurant/Food producers: http://www.consumerfreedom.com/http://www.consumerfreedom.com/  American Obesity Association: http://www.obesity.org/http://www.obesity.org/  North American Association for the Study of Obesity (NAASO): http://www.naaso.org/http://www.naaso.org/  Center for Science in the Public Interest: http://www.cspinet.org/http://www.cspinet.org/  Whole Foods vs. Pollan blog: http://gristmill.grist.org/story/2006/6/29/143121/559?source=weeklyhttp://gristmill.grist.org/story/2006/6/29/143121/559?source=weekly  Tufts University, Professor of Food Policy- blog :http://www.usfoodpolicy.blogspot.com/  Rudd Center for Food Policy, Yale: http://www.yaleruddcenter.org/home.aspxhttp://www.yaleruddcenter.org/home.aspx Articles:  Young & Nestle. Am J Pub Health 2002: 246-47  Gordon-Larsen et al. Obes Res. 2003;11(1):121-129.  Albright et al. Health Educ Q. 1990;17(2):157-167.  Weinsier et al. Am J Med. Aug 1998;105(2):145-150.  Fiske & Cullen. J Am Diet Assoc. 2004;104(1):90-93.  Diez Roux et al. N Engl J Med. 2001;345(2):99-106.  Jeffery & Utter. Obes Res. 2003;11:12S-22S.  Nielsen S et al. Obes Res. 2002;10(5):370-378.  French S et al. Annu Rev Public Health. 2001;22:309-335.  Rolls et al. Appetite. 2004;42(1):63-69.  Block et al. Am J Prev Med. 2004;27(3):211-217.  Gordon-Larsen et al. Pediatrics. Feb 2006;117(2):417-424. My Contact Information: kduffey@unc.edu

86. Vote with your fork