time preferences and the development of obesity

Ewan Gray

University of Aberdeen

Health Economics Research Unit (HERU)

Time Preferences and the Development of Obesity

Time Preferences

Time Perspective

• Time Perspective is an equivalent psychological concept.

• Consideration of Future Consequences Scale (CFCS) is a survey instrument designed to measure time perspective/time preference. High correlation with time preference rate.

CFCS

• Examples (1-7 scale):– “I am only concerned about

the present, because I trust that things will work themselves out in the future.”

– “With everything I do, I am only concerned about the immediate consequences (say a period of a couple of days or weeks). ”

05

1015

Percent

0 20 40 60 80CFCS

Incredibly simple model

Other factors influencing intentions

Time Preferences

IntentionsHealth Behaviours

DHS

• DnB Household Survey (DHS)– Data from 1993-2009. Use 1996-2009.– 2,000 (1660 by 2009) households on CentERpanel

(representative of Netherlands population). Online, arrangements for access with no computer. Self-report.

– Includes: Basic demographic, basic health (BMI, limiting health problem, smoking, alcohol consumption), detailed income, assets, liabilities and some interesting psychological variables (time preferences, risk preferences, personality).

– Includes CFCS, height and weight. – Previous cross-sectional study found weak evidence of

association of high TP and increased BMI (Borghans and Golsteyn, 2006).

Aim

• Do time preferences (CFCS score) effect the development of obesity?

• Previous studies have not obtained a conclusive answer.– Five previous studies (4 cross-sectional, 1 ecological) have found

mixed evidence of a weak effect of time preference.

– Statistical significance only achieved for sub-groups or in some models in each cross-sectional study. Studies used moderately large data-sets from USA, Netherlands, England and Japan.

Methods

• Non-parametric– Plot Kaplan-Meier survival functions for quartiles of

CFCS distribution. Log-rank test.

• Semi-parametric– Cox regression

– CFCS score is independent.

– Controlling for age, gender, education and initial BMI.

– ).exp()(

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CFCSSecondaryUUniversityGenderageth

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Results

Log-rank test: χ2 = 14.16, p 0.0027

Results 2

Variable Model 1 2 – Quadratic Age 3 – Interactions

CFCS 0.01**(0.004) 0.011**(0.004) 0.011*** (0.004)

Age -0.01***(0.003) 0.061***(0.018) 0.067***(0.018)

Gender (Male) -0.386***(0.067) -0.385***(0.075) -1.474***(0.289)

University -1.18***(0.225) -1.104***(0.226) -1.113***(0.226)

U. Secondary -0.544***(0.097) -0.486***(0.096) -0.502***(0.099)

Age2 -0.0007***(0.0002) -0.0009***(0.0002)

Gender*Age 0.023***(0.006)

Coef. (s.e.), *P<0.1, **P<0.05, ***P<0.01

Results 3Variable 5- InitialBMI

CFCS 0.015***(0.004)

Age 0.063***(0.022)

Gender (Male) -0.221(0.333)

University 0.369(0.284)

U. Secondary 0.346***(0.126)

Age2 -0.0007***(0.0002)

Gender*Age 0.003(0.006)

Initial BMI 0.288***(0.006)

Sensitivity to Obesity BMI cut-off value

Conclusions• CFCS is significantly associated with

hazard of obesity.

• A high CFCS predicts greater hazard of obesity. Hazard ratio (for normalised CFCS): 1.151 (1.07, 1.238).

• This estimate is robust to different specifications of the control variables.

Challenges/Limitations• Data:

– Attrition/censoring is high and may be non-random

– Missing and implausible values

• Models:– Other BMI dynamics than occurrence of BMI>30 are of interest.

– Other response variables may be more appropriate such as BMI or a binary dependent with a probit or logit link function.

Questions?

Summary Statistics

Variable 1996 Mean (s.d.) or % 2009 Mean (s.d.) or %

Age 47.0(14.2) 54.9(14.4)

Female 46.3% 44.4%

BMI 24.3(3.46) 26.0(3.99)

CFCS score 41.63 (11.1) 42.95 (8.17)

University Education (2002) 2.0% 8.89%

U. Secondary Education(2002)

7.9% 26.9%