Quantifying the positive health impacts of increased wealth in social life cycle assessment

Other conference contribution, 2022

There is a cluster of social topics or subcategories around wealth in social life cycle assessment, including fair salaries, incomes, poverty alleviation, local employment and wealth distribution. In this contribution, the link between increased wealth (mainly increased incomes but also reduced inequality) and health is investigated. Quantifiable impact pathways are sought between wealth and health, for example enabling comparison to other health impacts in terms of disability-adjusted life years (DALY). There seems to be two main pathways between wealth and health. The first is the materialistic pathway, stating that increased incomes improve health in two ways: (i) on the individual level by enabling purchasing of personal protection from adverse health impacts, e.g. in terms of improved diet and medication, and (ii) on the societal level by enabling public investments in infrastructure, e.g. health care. The second is the non-materialistic pathway, which focuses on reduced inequality. This might lead to health benefits (i) on the individual level by reduced psychological stress, and (ii) on the societal level through increased social capital, e.g. trust among the population. These two pathways are not mutually exclusive and real-life health outcomes are often the result of both pathways. However, there is a tendency towards a materialistic focus for developing countries and a non-materialistic focus for developed countries. General quantifications of the pathways are challenging, since local conditions can provide powerful modifiers. For example, without any banking infrastructure present, poor people find it hard to save surplus income to use for medication in case of future illness, thus weakening the materialistic pathway towards improved health. Still, attempts towards general quantifications for the purpose of social life cycle assessment will be attempted, with possibilities to alter calculations based on local conditions.