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Estelle Zemmour .

Are fast food restaurants responsible for diabetes epidemic ? Instantaneous cut evidence from China. Estelle Zemmour . Objective. The first time this research is conducted

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Estelle Zemmour .

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  1. Are fastfood restaurants responsible for diabetesepidemic?Instantaneouscutevidencefrom China. Estelle Zemmour.

  2. Objective • The first time thisresearchisconducted • Benchmark papers:-Kaushal, « Do foodstamps cause obesity? Evidence from immigrant experience », Journal of HealthEconomics, 2007- Davis, Carpenter, « Proximity to Fast Food Restaurants to Schools and Adolescent Obesity », American Journal of Public Health, 2009. • Raises 3 main literaturereviews: 1) impact of diabetes on the economy2) impact of nutrition on diabetes3) impact of fastfood on obesity (used for methodology).

  3. Someexplanations on Diabetes. • « Disease of the century »: touches rich over-nourished,aswell as under-nourished people.« Characterized by a disturbance in the use of sugar by the body due to a malfunction of the pancreas, whichdoes not release enoughinsulin in the body ». • International measure ( American DiabetesAsociation): Hba1c (measuresglycemic indexes over 3 pastmonths, thisis an average). -if higherthan 6,5  declared « diabetic » • 2 types: second one due to environmentalfactors: touches people after 40. Represents 95% of cases.

  4. Measuring the main key variables for Nutrition • First index « Nutrition_1 »=Body Mass Index BMI=weight/(height²) • Second index « Nutrition_2 »= AverageGlycemic Index AGI= (total servings per day* carbohydrates content of food* glycemic index)/total carbohydrates content in diet (Salmeron and al, 1981)

  5. Socio-economicdeterminants of BMI

  6. Socio-economicdeterminants of AGI

  7. Specification • 2 models:  Nutrition_1Nutrition_2 linearregressionmodels probitmodels • Problems: reverse causalitysuspectedbetween the index of Nutrition and Diabetes • Proposed solution: instrumental variable approach.

  8. Linearregressionmodels • 1rst model: Diabetes= a + b*Nutrition_1 + c*Income + d*Education+ e*Occupation + f*Healthcare + g*Insurance + h*Subsidies+ i*Media + j*Age + k*Urbanization+ l* Origin +m* Sex • 2nd model: Diabetes= a +b*Nutrition_2+ c*Income + d*Education+ e*Occupation + f*Healthcare + g*Insurance + h*Subsidies+ i*Media + j*Age + k*Urbanization+ l* Origin +m* Sex

  9. Probitmodels • Diabetes_2= 1 if Diabetes>6.5O otherwise sum Diabetes, detail hba1c(mmol/l) hemoglobin a1c - field ------------------------------------------------------------- Percentiles Smallest 1% 4.1 2.7 5% 4.7 3.1 10% 4.9 3.4 Obs 9088 25% 5.2 3.5 Sum of Wgt. 9088 50% 5.5 Mean 5.593376 Largest Std. Dev. .8566354 75% 5.8 13.3 90% 6.2 14 Variance .7338243 95% 6.7 15.2 Skewness 3.638847 99% 9.7 16.1 Kurtosis 25.81249

  10. Probitmodels • 1rst model: Diabetes_2= a + b*Nutrition_1 + c*Income + d*Education+ e*Occupation + f*Healthcare + g*Insurance + h*Subsidies+ i*Media + j*Age + k*Urbanization+ l* Origin +m* Sex • 2nd model: Diabetes_2= a + b*Nutrition_2 + c*Income + d*Education+ e*Occupation + f*Healthcare + g*Insurance + h*Subsidies+ i*Media + j*Age + k*Urbanization+ l* Origin +m* Sex

  11. Data • China Health and Nutrition Survey(CHNS) • 1989-20092009: data for Diabetes • Merge and createdelays

  12. 1rst model: Diabetes_2= a + b*∑Nutrition_1 + c*∑Income + d*Education+ e*Occupation + f*Healthcare + g*Insurance + h*Subsidies+ i*Media + j*Age + k*Urbanization+ l* Origin +m* Sex • 2nd model: Diabetes_2= a + b*Nutrition_2 + c*∑Income + d*Education+ e*Occupation + f*Healthcare + g*Insurance + h*Subsidies+ i*Media + j*Age + k*Urbanization+ l* Origin +m* Sex

  13. Data.

  14. Data

  15. Stylizedfacts

  16. Results: Estimatinglinearmodelswith Nutrition_1

  17. Results:Estimatingprobitmodelswith Nutrition_1.

  18. Results:Estimatinglinearmodelswith Nutrition_2.

  19. Results:Estimatingprobitmodelswith Nutrition_2.

  20. Investigation prospects • Try to ameliorate instrumentation includingcommunity variables as: « distance to fastfood » and « isthere a fastfood in the community? » • Createbinary variables for foodlikes and use this instrumentation instead • Create Nutrition variables by age (z-scores)

  21. Challenges ahead • Use to have some arguments to taxfastfoods in China from 2006, but nothingreallyhappened. The reasons?  high cost of taxation, whichwill damage interest groups (KFC, Mac Donald’s) mayderivefrom the unefficiency of China’shealth system • We suspect overweight and obesity to increasediabetesintensity. That’swhyfastfood are suspected to increasediabetesintensityindirectly, through BMI (we are going to use it as a possible instrument). • Thenitraisesnutritional and policitical recommandations: (1) space out fastfoodsfromschools to a sustainabledevelopment(2) why not taxingfastfood restaurants?(3) at least, changingtheirpolicies (whoknows in the USA and in China, buying a glas of water is more expensivethana Coke?)

  22. Thankyou for your attention!

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