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Using epidemiological models to estimate the health effects of diet behaviour change: the example of tailored fruit and vegetable promotion

Published online by Cambridge University Press:  02 January 2007

J Lennert Veerman ,
Jan J Barendregt ,
Johan P Mackenbach  and
Johannes Brug
J Lennert Veerman*
Affiliation:
Department of Public Health, Erasmus MC – University Medical Centre Rotterdam, PO Box 1738, 3000 DR Rotterdam, The Netherlands
Jan J Barendregt
Affiliation:
Department of Public Health, Erasmus MC – University Medical Centre Rotterdam, PO Box 1738, 3000 DR Rotterdam, The Netherlands School of Population Health, University of Queensland, Brisbane, Queensland, Australia
Johan P Mackenbach
Affiliation:
Department of Public Health, Erasmus MC – University Medical Centre Rotterdam, PO Box 1738, 3000 DR Rotterdam, The Netherlands
Johannes Brug
Affiliation:
Department of Public Health, Erasmus MC – University Medical Centre Rotterdam, PO Box 1738, 3000 DR Rotterdam, The Netherlands
*
*Corresponding author: Email [email protected]
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Abstract

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Objective

To explore the use of epidemiological modelling for the estimation of health effects of behaviour change interventions, using the example of computer-tailored nutrition education aimed at fruit and vegetable consumption in The Netherlands.

Design

The effects of the intervention on changes in consumption were obtained from an earlier evaluation study. The effect on health outcomes was estimated using an epidemiological multi-state life table model. Input data for the model consisted of relative risk estimates for cardiovascular disease and cancers, data on disease occurrence and mortality, and survey data on the consumption of fruits and vegetables.

Results

If the computer-tailored nutrition education reached the entire adult population and the effects were sustained, it could result in a mortality decrease of 0.4 to 0.7% and save 72 to 115 life-years per 100 000 persons aged 25 years or older. Healthy life expectancy is estimated to increase by 32.7 days for men and 25.3 days for women. The true effect is likely to lie between this theoretical maximum and zero effect, depending mostly on durability of behaviour change and reach of the intervention.

Conclusion

Epidemiological models can be used to estimate the health impact of health promotion interventions.

Keywords

Fruits and vegetablesEvaluationModelling
Type
Research Article
Information
Public Health Nutrition , Volume 9 , Issue 4 , June 2006 , pp. 415 - 420
Copyright
Copyright © The Authors 2006

References

1Carlson Gielen, A, McDonald, EM. The precede–proceed planning model. In: Glanz, K, Lewis, FM, Rimer, BK, eds. Health Behavior and Health Education. San Francisco, CA: Jossey-Bass, 1997; 359–83.Google Scholar
2Ezzati, M, Hoorn, SV, Rodgers, A, Lopez, AD, Mathers, CD, Murray, CJ. Estimates of global and regional potential health gains from reducing multiple major risk factors. Lancet 2003; 362(9380): 271–80.CrossRefGoogle ScholarPubMed
3Mooy, JM, Gunning-Schepers, LJ. Computer-assisted health impact assessment for intersectoral health policy. Health Policy 2001; 57(3): 169–77.CrossRefGoogle ScholarPubMed
4Naidoo, B, Thorogood, M, McPherson, K, Gunning-Schepers, LJ. Modelling the effects of increased physical activity on coronary heart disease in England and Wales. Journal of Epidemiology and Community Health 1997; 51(2): 144–50.CrossRefGoogle ScholarPubMed
5Brug, J, Oenema, A, Campbell, M. Past, present, and future of computer-tailored nutrition education. American Journal of Clinical Nutrition 2003; 77(Suppl. 4): 1028S–34S.CrossRefGoogle ScholarPubMed
6Brug, J, Glanz, K, Van Assema, P, Kok, G, Van Breukelen, GJ. The impact of computer-tailored feedback and iterative feedback on fat, fruit, and vegetable intake. Health Education & Behavior 1998; 25(4): 517–31.Google Scholar
7Barendregt, JJ, Van Oortmarssen, GJ, Van Hout, BA, Van den Bosch, JM, Bonneux, L. Coping with multiple morbidity in a life table. Mathematical Population Studies 1998; 7(1): 29–49, 109.CrossRefGoogle Scholar
8Vianio, H, Bianchini, F, ed. IARC Handbooks of Cancer Prevention. Vol. 8. Fruit and Vegetables. Lyon: IARC Press, 2003.Google Scholar
9Jansen, MCJF, Van deVijver, LPL. Fruits and Vegetables in Chronic Disease Prevention – Another Update. Zoetermeer: Holland Produce Promotion, 2004.Google Scholar
10Murray, CJ, Acharya, AK. Understanding DALYs (disability-adjusted life years). Journal of Health Economics 1997; 16(6): 703–30.CrossRefGoogle ScholarPubMed
11Dutch National Institute of Public Health and the Environment (RIVM). The National Public Health Compass. [online], 2004. Avaliable at http://www.nationaalkompas.nl. Accessed 1 October 2004.Google Scholar
12Riboli, E, Norat, T. Epidemiologic evidence of the protective effect of fruit and vegetables on cancer risk. American Journal of Clinical Nutrition 2003; 78(Suppl. 3): 559S–69S.Google Scholar
13Stouthard, MEA, Essink-Bot, M-L, Bonsel, GJ, Barendregt, JJ, Kramers, PGN, Van de Water, HPA, et al. Disability Weights for Diseases in The Netherlands. Rotterdam: Department of Public Health, Erasmus University Rotterdam, 1997.Google Scholar
14@RISK 4.0. [computer program]. London: Palisade, 2000.Google Scholar
15Selmer, RM, Kristiansen, IS, Haglerod, A, Graff-Iversen, S, Larsen, HK, Meyer, HE, et al. Cost and health consequences of reducing the population intake of salt. Journal of Epidemiology and Community Health 2000; 54(9): 697–702.CrossRefGoogle ScholarPubMed
16Bonneux, L. Mortality reduction by breast-cancer screening. Lancet 2003; 362(9379): 245.Google Scholar
17Brug, J, Campbell, M, Van Assema, P. The application and impact of computer-generated personalized nutrition education: a review of the literature. Patient Education and Counseling 1999; 36(2): 145–56.CrossRefGoogle ScholarPubMed
18Brug, J, Steenhuis, I, van Assema, P, de Vries, H. The impact of a computer-tailored nutrition intervention. Preventive Medicine 1996; 25(3): 236–42.Google Scholar
19Irvine, AB, Ary, DV, Grove, DA, Gilfillan-Morton, L. The effectiveness of an interactive multimedia program to influence eating habits. Health Education Research 2004; 19(3): 290–305.CrossRefGoogle ScholarPubMed
20De Vries, H, Brug, J. Computer-tailored interventions motivating people to adopt health promoting behaviors: introduction to a new approach. Patient Education and Counseling 1999; 36(2): 99–105.Google ScholarPubMed
21Campbell, MK, Tessaro, I, DeVellis, B, Benedict, S, Kelsey, K, Belton, L, et al. Effects of a tailored health promotion program for female blue-collar workers: health works for women. Preventive Medicine 2002; 34(3): 313–23.CrossRefGoogle ScholarPubMed
22Murray, CJ, Ezzati, M, Lopez, AD, Rodgers, A, Vander Hoorn, S. Comparative quantification of health risks conceptual framework and methodological issues. Population Health Metrics 2003; 1(1): 1.CrossRefGoogle ScholarPubMed