Burden of disease of heavy metals in population clusters: towards targeted public health strategies

Sofie Theresa Thomsen*, J. A. R. Herrera, Lea Sletting Jakobsen, Sisse Fagt, Sara Monteiro Pires

*Corresponding author for this work

Research output: Contribution to journalConference abstract in journalResearchpeer-review

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Abstract

Background: Humans are exposed to heavy metals from certain foods, thus specific dietary patterns may lead to high burden of disease (BoD). By identifying diet, lifestyle and socio-demographic characteristics of population groups with highest BoD, targeted preventive strategies can be developed. We aimed at identifying clusters and characteristics of Danish individuals with highest BoD due to food exposure to three heavy metals: methylmercury (MeHg), cadmium and inorganic arsenic.MethodsWe collected diet, lifestyle and socio-demographic information of 3,946 individuals in the Danish National Survey of Diet and Physical Activity. Occurrence of heavy metals in food was obtained from Danish food monitoring. We applied machine learning self-organizing maps to group individuals according to similarities in diet, lifestyle and socio-demographics, and estimated BoD due to metal exposure in terms of Disease-Adjusted Life Years (DALY). We will present calculation steps of our approach in a tutorial-like way and demonstrate its applicability to other cases.ResultsWe identified 13 population subgroups with distinct dietary and lifestyle characteristics. The estimated BoD varied largely between subgroups, with five subgroups experiencing a BoD > 10 DALY/100,000. The cluster bearing the highest BoD (26.2 (95% uncertainty interval (UI): 10.3, 50.6) DALY/100,000) was significantly different from the cluster with the lowest BoD (5.1 (95% UI: 2.5, 9.2) DALY/100,000) (preliminary). BoD was higher in subgroups with diet and lifestyle considered healthy. Most of the BoD was due to MeHg, particularly in female-dominant subgroups.ConclusionsLinking machine learning, exposure assessment and burden of disease metrics, this novel approach identified population subgroups with higher BoD due to exposure to three heavy metals. It can be expanded to estimate BoD of other chemicals, and used to develop targeted preventive strategies to reduce BoD in more affected subgroups.
Original languageEnglish
Article numberckz185.658
JournalEuropean Journal of Public Health
Volume29
Issue numberSupplement 4
Pages (from-to)242-242
ISSN1101-1262
DOIs
Publication statusPublished - 2019
Event12th European Public Health Conference : Building bridges for solidarity and public health - Marseille, France
Duration: 20 Nov 201923 Nov 2019
Conference number: 12

Conference

Conference12th European Public Health Conference
Number12
CountryFrance
CityMarseille
Period20/11/201923/11/2019

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