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Chained Risk Assessment for Life-Long Disease Burden of Early Exposures–Demonstration of Concept Using Prenatal Maternal Smoking

Author

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  • Isabell K. Rumrich

    (Department of Public Health Solutions, Finnish Institute for Health and Welfare (THL), P.O. Box 95, 70701 Kuopio, Finland
    Faculty of Science and Forestry, Department of Environmental and Biological Sciences, University of Eastern Finland (UEF), P.O. Box 1627, 70211 Kuopio, Finland)

  • Kirsi Vähäkangas

    (Faculty of Health Sciences, School of Pharmacy/Toxicology, University of Eastern Finland (UEF), P.O. Box 1627, 70211 Kuopio, Finland)

  • Matti Viluksela

    (Faculty of Health Sciences, School of Pharmacy/Toxicology, University of Eastern Finland (UEF), P.O. Box 1627, 70211 Kuopio, Finland
    Department of Health Security, Finnish Institute for Health and Welfare (THL), P.O. Box 95, 70701 Kuopio, Finland)

  • Otto Hänninen

    (Department of Public Health Solutions, Finnish Institute for Health and Welfare (THL), P.O. Box 95, 70701 Kuopio, Finland)

Abstract

Traditional risk factors and environmental exposures only explain less than half of the disease burden. The developmental origin of the health and disease (DOHaD) concept proposes that prenatal and early postnatal exposures increase disease susceptibility throughout life. The aim of this work is to demonstrate the application of the DOHaD concept in a chained risk assessment and to provide an estimate of later in life burden of disease related to maternal smoking. We conducted three systematic literature searches for meta-analysis and reviewed the literature reporting meta-analyses of long-term health outcomes associated with maternal smoking and intermediate risk factors (preterm birth, low birth weight, childhood overweight). In the chained model the three selected risk factors explained an additional 2% (34,000 DALY) of the total non-communicable disease burden (1.4 million DALY) in 2017. Being overweight in childhood was the most important risk factor (28,000 DALY). Maternal smoking was directly associated with 170 DALY and indirectly via the three intermediate risk factors 1000 DALY (1200 DALY in total). The results confirm the potential to explain a previously unattributed part of the non-communicable diseases by the DOHAD concept. It is likely that relevant outcomes are missing, resulting in an underestimation of disease burden.

Suggested Citation

  • Isabell K. Rumrich & Kirsi Vähäkangas & Matti Viluksela & Otto Hänninen, 2020. "Chained Risk Assessment for Life-Long Disease Burden of Early Exposures–Demonstration of Concept Using Prenatal Maternal Smoking," IJERPH, MDPI, vol. 17(5), pages 1-17, February.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:5:p:1472-:d:324842
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    References listed on IDEAS

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    1. Jieun Kim & Insook Lee & Sungwon Lim, 2017. "Overweight or obesity in children aged 0 to 6 and the risk of adult metabolic syndrome: A systematic review and meta‐analysis," Journal of Clinical Nursing, John Wiley & Sons, vol. 26(23-24), pages 3869-3880, December.
    2. Miriam Abraham & Salem Alramadhan & Carmen Iniguez & Liesbeth Duijts & Vincent W V Jaddoe & Herman T Den Dekker & Sarah Crozier & Keith M Godfrey & Peter Hindmarsh & Torstein Vik & Geir W Jacobsen & W, 2017. "A systematic review of maternal smoking during pregnancy and fetal measurements with meta-analysis," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-13, February.
    3. Notkola, V. & Punsar, S. & Karvonen, M. J. & Haapakoski, J., 1985. "Socio-economic conditions in childhood and mortality and morbidity caused by coronary heart disease in adulthood in rural Finland," Social Science & Medicine, Elsevier, vol. 21(5), pages 517-523, January.
    4. Heli Lehtomäki & Antti Korhonen & Arja Asikainen & Niko Karvosenoja & Kaarle Kupiainen & Ville-Veikko Paunu & Mikko Savolahti & Mikhail Sofiev & Yuliia Palamarchuk & Ari Karppinen & Jaakko Kukkonen & , 2018. "Health Impacts of Ambient Air Pollution in Finland," IJERPH, MDPI, vol. 15(4), pages 1-16, April.
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    Cited by:

    1. Chien-Lung Chan & Chi-Chang Chang, 2020. "Big Data, Decision Models, and Public Health," IJERPH, MDPI, vol. 17(18), pages 1-7, September.
    2. Chien-Lung Chan & Chi-Chang Chang, 2022. "Big Data, Decision Models, and Public Health," IJERPH, MDPI, vol. 19(14), pages 1-9, July.

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