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Smoking, Drinking and Obesity

Hung-Hao Chang* David R. Just Biing-Hwan LinNational Taiwan University Cornell University ERS, USDA

Present at National Chung-Cheng University

March, 2007

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Background

Smoking, Drinking and Obesity have caused serious

public-health concern in the U.S.

-- 65% of adults aged 21 and over were eitheroverweight or obese. 30% of them were obese.

Compared to 30 years ago, it increases almost 50%.

(Hedley et al,2004)

-- Disease burden associated with obesity in the U.Sis substantial. In 1995, the cost of obesity were US$

92 billion, 10% of the total cost of illness.

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In 2000, tobacco smoking caused more than

400,000 deaths. Smoking has been a leading

preventable cause of mortality in the UnitedStates. Recently, anti-smoking has been an

important policy in U.S.

Evidence from public health has shown thatdrinking may be associated with smoking

behavior.

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Is smoking negatively associated with body weight?

From: Gruber and Frakes (2006),Journal of Health Economics.

Smoking and obesity rates are two significant trends over 30 years in U.S

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Literature Review

Study Data Method Conclusion

This Study CSFII 1994-1996 Quantile

Chen et al. (2007) CSFII 1994-1996 Censored Smoking has insignificant effect on BMI

Gruber and Frakes(2006 BRFSS 1984-2002 IV No evidence that smoking leads to weight gain

Ruidavets et al. (2002) France Survey OLS Positive of smoking and BMI

Chou et al. (2004) BRFSS 1984-2002 OLS Cigarette price (+); alcohol price (-) on BMI.

Lin et al. (2004) CSFII 1994-1996 OLS Smokers tend to be thinner than non-smokers

Wilson et al. (2004) St. Louis Survey Logit Smoking leads to low body weight

Jee et al. (2002) Korea Health Survey Logit Smoking leads to low body weight

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What do we learn from previous studies?

Association between body weight and unhealthy decisions:

The evidence whether the increased alcohol

consumption contributes to body weight is mixed.However, it may be important to distinct the effects of

drinking beer and liquor.

Smoking tends to be negatively associated with body

weight. However, the negative evidence has been re-investigated recently. (Chen et al, 2007. Gruber and

Frakes 2006).

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What may drive these inconclusive results?

Interrelationship between unhealthy decisions:

Smoking and drinking are highly correlated. Failing

to control for one in estimation may lead to seriousbias. (Kenkel and Wang 1999).

Conditional mean effect:

Most of the studies relied on the ordinary least

squares (OLS). However, this method might not besufficient in the context of obesity. (Kan and Tsai

2004).

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Research Objectives

Investigate the interrelationship among smoking,drinking beer, and drinking liquor. Determine ifthese decisions are jointly or independently

determined. Identify factors that may affect each decision.

Account explicitly for the effects of these decisionson body weight.

Test if the effects of these decisions on body weightare heterogeneous (distinction between overweightand normal weight people).

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Data

Data from Continuing Survey of Food Intakes by

Individuals (CSFII 1994-1996) is used. This data set

is conducted by USDA.

We exclude individuals under 20 years-old.

The final sample size includes 3,409 adult of this

survey.

Body weight is measured as body mass index (BMI),weight in kilograms divided by height in meters

squared.

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Distribution of BMI in our selected sample

Mean 26.5

Std. Dev. 5.7

Skewness 1.4

Kurtosis 7.1

10% 20.4

20% 21.9

25% 22.5

30% 23.2

40% 24.4

45% 25.0

50% 25.6

60% 26.6

70% 28.3

75% 29.2

78% 30.0

80% 30.3

90% 33.7

Percentile

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According to the definition of the Center forDisease Control (CDC), overweightpeopleare those whose BMI is greater than 25. If theBMI exceeds 30, the individual can beregarded as obese.

In our sample, 45% are normal weight; about

22% are identified as obese. The distribution of BMI departs from the

normal distribution.

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Sample Statistics

Variable Definition Mean Std. Dev.DSMOKE If the respondent smokes cigarette (=1) 0.3 0.4

DBEER If the respondent drinks wine (=1) 0.4 0.5

DLIQUOR If the respondent drinks liquor (=1) 0.4 0.5

BMI Body Mess Index. Weight divided by height square. 26.5 5.7

AGE Age in years 51.0 17.0

MALE If the respondent is male(=1) 0.3 0.5

EMP_STAT If the respondent is employed (=1) 0.5 0.5

PCTPOV Annual income. 211.4 95.0

NOHS If the respondent didn't finish high school(=1) 0.2 0.4

HS If the respondent finish high school(=1) 0.3 0.5

SOMECOLL If the respondent finish some colleage (=1) 0.2 0.4COLLEGE If the respondent finish colleage (=1) 0.2 0.4

WHITE Non-Hispanic White (=1) 0.8 0.4

HISPAN Respondent is Hispanic (=1) 0.1 0.3

BLACK Non-Hispanic Black (=1) 0.1 0.3

ASIAN Asian pacific islander (=1) 0.0 0.1

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Variable Definition Mean Std. Dev.NEAST Reside in the Northeast states (=1) 0.2 0.4

MIDWEST Reside in the Midwest states (=1) 0.3 0.4

SOUTH Reside in the Southern states (=1) 0.3 0.5

CENTER Live in metropolitan area, central city (=1) 0.3 0.5

OUTSIDE Live in metropolitan area, outside central city (=1) 0.4 0.5WEST Reside in the Western states (=1) 0.2 0.4

DIET Family menber is on the special diet (=1) 0.3 0.4

VITAMIN Dietary recall of vitamin user (=1) 0.4 0.5

FOOD Knowledge of food guid pyramid. 2.5 1.2

IMPVF1 If consuming plenty of fruits and vegetable is import 0.7 0.4EXERONCE Respondents exercise at least once a week(=1) 0.5 0.5

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Structure of the Empirical Analysis

An innovative two-stage econometric model is proposed:

Stage 1: Three binary choices are specified: smoking,drinking beer and drinking liquor. A tri-variate

probit model is estimated to capture the correlationsamong these choices.

Stage 2: A body weight equation is estimated toaccount explicitly for the endogenous choices. We

estimate this quation with quantile regressionmethod.

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Stage 1: Modeling the joint decisions

(trivariate probit model)

RHO (S,B)

RHO (S,W) RHO (W,B)

Smoking

Drinking Wine

Drinking Beer

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Stage 1: (cont.)

1111 '* eXHI

2222 '* eXHI

3333 '* eXHI

Smoking Decision

Decision to drink beer

Decision to drink wine

)

1

1

1

;0,0,0(~),,(

3231

3221

3121

321

Neee

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Estimate the discrete choice model (MLE)

The probability of regime (1,1,1):

Log likelihood function of the entire eight regimes:

],,,',','[loglog 2332133112213332221111

kkkkkkXHkXHkXHkLn

i

)',','Pr()1,1,1Pr(33322211132111

XHeXHeXHeIIIP

),,,',','(231312332211

XHXHXH

where k1=2I1-1, k2=2I2-1, k3=2I3-1

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Statistical Evidence of the Joint Decisions

Coefficient

t-value

RHO (Smoking, Liquor)

0.16 5.20

RHO (Smoking, Beer) 0.19 6.57

RHO (Liquor, Beer) 0.56 25.03

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Correlations between smoking and drinking

Drinking beer and liquor is strongly

associated (56%).

The decisions to smoke and to drink beer aresignificantly correlated (19%). In addition, the

correlation between drinking liquor and

smoking is 16%. This is consistent with the evidence of public

health in terms of the gateway effect.

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Other Determinants of Smoking and Drinking

Variable Coef. t-value Coef. t-value Coef. t-value

FOOD -0.04 -1.96 0.01 0.54 0.03 1.52

IMPVF1 -0.27 -4.90 -0.09 -1.58 -0.05 -0.91

DIET -0.12 -2.04 -0.10 -1.91 -0.19 -3.58

VITAMIN -0.13 -2.37 -0.03 -0.67 0.00 0.02EXERONCE -0.18 -3.45 -0.01 -0.23 0.16 3.42

PCTPOV 0.00 -2.80 0.00 5.82 0.00 5.09

AGE -0.01 -7.17 -0.01 -8.38 -0.02 -10.69

MALE 0.13 2.48 0.23 4.57 0.80 15.50

EMP_STAT 0.03 0.54 0.12 2.17 0.11 2.01NOHS1 0.59 6.76 -0.53 -6.30 -0.19 -2.37

HS1 0.60 8.50 -0.28 -4.40 -0.16 -2.40

SOMECOLL 0.39 5.06 -0.09 -1.29 -0.13 -1.90

Smoking Drinking Liquor Drinking Beer

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Variable Coef. t-value Coef. t-value Coef. t-value

ASIAN -0.99 -3.24 -0.98 -4.01 -0.45 -2.17

BLACK -0.06 -0.69 -0.10 -1.17 0.14 1.91

HISPAN -0.30 -2.93 -0.43 -4.28 -0.06 -0.59

OTHER 0.33 1.69 -0.19 -0.83 -0.05 -0.21WEST 0.22 2.67 -0.01 -0.17 0.10 1.33

SOUTH 0.13 1.85 -0.43 -6.46 -0.16 -2.41

MIDWEST 0.16 2.15 -0.10 -1.51 0.05 0.69

CENTER 0.04 0.53 0.25 3.81 0.13 1.97

OUTSIDE -0.03 -0.57 0.11 1.76 0.02 0.31

Smoking Drinking Liquor Drinking Beer

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Empirical findings

Perception and knowledge of healthy foodconsumption decrease the likelihood to smoke.

Low education and income lead to high chance to

smoke, but low chance to drink wine. Male is more likely to smoke, and to drink beer.

Job status increases the propensity to drink wine.

Young generation has high probability to smoke. Other lifestyles also matter. If family members are

on diet, they are less likely to smoke, and to drinkbeer and liquor.

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How much we believe in our model specification?

-- Empirical results of statistical tests

Quantiles Test value#

Smoking 25% 10.14

Drinking Liquo 50% 20.15

Drinking Beer 75% 15.62

Quantiles Test-value##

Smoking 25% 2.73

Drinking Liquo 50% 2.15

Drinking Beer 75% 1.39

* Ho: exogeneity

**Ho: additional varialbes are valid

# Critical value isF[3,3386]

## Critical valuex

2

(0.95,3)=7.81

Overidentification Test**

Endogeneity Test*

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Findings

If binary indicators are used, they are

endogenous to the body weight. Therefore,

there is a call for instruments (IV). When instruments are used, statistical tests

show that the added restrictions are not

rejected. In other words, our selectedinstruments are not over-identified.

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Stage 2: Body Weight Equation

The body weight equation is specified as:

To avoid endogeneity,predicted probabilitiesareused as instrumentsforIj. Quantile regression is

used to estimate this equation (Koenker and Bassett

1978).

eIdIdIdXBMI 332211 ***'

332211321 ***'),,,|( IdIdIdXIIIXBMIQ

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Evidence of heterogeneous effects on BMI

Coef. t-value Coef. t-value Coef. t-value Coef. t-value

PSMOKE -4.8 -2.7 -1.4 -0.8 -2.7 -1.5 -4.7 -1.9

PLIQUOR -8.7 -3.4 -3.5 -1.2 -7.0 -2.6 -10.8 -3.0

PBEER 10.1 3.4 6.5 2.2 8.4 2.6 10.6 2.8

OLS 25% 50% 75%

F Test ** test p-value

25% vs 50% 2.72 0.01

25% vs 75% 21.43 0.00

50% vs 75% 8.98 0.00

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Effect of smoking on BMI distribution

-25

-20

-15

-10

-5

0

5

10

0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95

Percentiles

OLS

PSMOKE

PSMOKE_U

PSMOKE_L

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Effect of Drinking Liquor on BMI distribution

-35

-30

-25

-20

-15

-10

-5

0

5

10

0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95

Percentiles

OLS

PLIQUOR

PLIQUOR_U

PLIQUOR_L

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Effect of Drinking Beer on BMI distribution

-15

-10

-5

0

5

10

15

20

25

30

35

40

0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95

Percentiles

OLS

PBEER

PBEER_U

PBEER_L

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Effects of other variables

Coef. t-value Coef. t-value Coef. t-value Coef. t-value

PCTPOV 0.0 4.1 0.0 3.9 0.0 3.9 0.0 3.1

AGE -0.1 -7.4 -0.1 -2.7 -0.1 -4.2 -0.2 -6.5

MALE 4.1 5.6 3.7 5.2 4.1 4.8 4.2 4.5

IMPVF1 -1.0 -3.3 -0.5 -1.8 -0.8 -2.4 -1.1 -2.6

VITAMIN -0.6 -2.6 -0.3 -1.5 -0.4 -1.7 -0.4 -1.2

BLACK 2.8 7.2 2.1 4.2 2.9 6.2 3.7 6.7

HISPAN -1.2 -2.0 0.4 0.5 -0.2 -0.3 -1.6 -1.7

ASIAN -8.0 -6.7 -3.3 -2.8 -6.0 -5.8 -9.1 -6.1

EXERONCE -0.3 -1.1 -0.2 -0.5 -0.1 -0.2 -0.6 -1.5

WEST 0.7 1.9 0.1 0.4 0.4 1.0 0.4 0.8

SOUTH -1.4 -3.9 -0.4 -1.2 -0.9 -2.3 -1.9 -3.7

MIDWEST 0.6 2.1 0.7 2.7 1.0 3.0 0.0 0.0

CENTER 0.9 2.8 0.5 1.6 0.7 2.3 0.8 1.8

OUTSIDE 0.2 0.7 0.2 0.9 0.2 1.0 0.0 0.1

OLS 25% 50% 75%

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Empirical findings

A significant evidence supports the misspecification

of using OLS. The effects are heterogeneous across

the entire distribution of BMI.

Smoking tends to be negatively correlated with BMI.

However, it is insignificant over the entire

distribution of BMI.

Drinking beer tends to increase the body weight.However, this effect is not significant for obese

people (above 85 percentile).

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Drinking liquor is found negatively associated with

body weight. In addition, the decreasing effect is

significant for obese people (75 percentile).

Knowledge of healthy food consumption decreases

the risk of being overweight.

Higher income leads to lower body weight.

Race is also associated with body weight. Blackhave heavy weight than others, on average; Asian

are those with less weight.

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Concluding and Policy Implications

The discussion of smoking, drinking and obesity

should be interpreted with caution. We have shown:

-- strong correlations between smoking, drinking beer

and drinking liquor.

-- heterogeneous effects of these decisions on BMI.

The effect of smoking on body weight is found

insignificant. As such, anti-smoking may not be thecritical factor driving the increasing trend of body

weight over 30 years.

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Drinking liquor is found negatively associated with

body weight. Particularly, the effect is even stronger

for normal weight people.

Drinking beer tends to increase body weight

regardless of the weight status. Beer drinkers are

those in a higher risk of being overweight.

Knowledge of healthy food consumption also havedirectand indirecteffects on body weight. A well-

educated consumer has less likelihood of being

overweight.