Socio-economic determinants of healthcare costs in early life: a register-based study in the Netherlands

BACKGROUND: Children with low socioeconomic status (SES) have an increased risk of a suboptimal start in life with ensuing higher healthcare costs. This study aims to investigate the effects of individual- (monthly household income) and contextual-level SES (household income and neighborhood deprivation), and perinatal morbidity (preterm birth and small for gestational age ((<10th percentile), SGA)) on healthcare costs in early life (0–3 years of age). METHODS: Individual-linked data from three national registries (Perinatal Registry Netherlands, Statistics Netherlands, and Healthcare Vektis) were obtained of all children born between 2011 and 2014 (N = 480,471) in the Netherlands. Binomial logistic regression was used to model annual healthcare costs as a function of their household income (per €1000), neighborhood deprivation index (range − 13.26 – 10.70), their perinatal morbidity and demographic characteristics. Annual healthcare cost were dichotomized into low healthcare costs (Q1-Q3 below €1000) and high healthcare costs (Q4 €1000 or higher). RESULTS: Children had a median of €295 annual healthcare costs, ranging from €72 to €4299 (5–95%). Binomial logistic regression revealed that for every €1000 decrease in monthly household income, the OR for having high healthcare costs is 0.99 (0.99–0.99). Furthermore, for every one-unit increase in neighborhood deprivation the OR for having high healthcare costs increase 1.02 (1.01–1.02). Finally, the model revealed an OR of 2.55 (2.48–2.61) for preterm born children, and an OR of 1.44 (1.41–1.48) for children SGA, to have high healthcare costs compared to their healthy peers. CONCLUSION: More neighborhood deprivation was directly related to higher healthcare costs in young children. On top of this, lower household income was consistently and independently related to higher healthcare costs. By optimizing conditions for low SES populations, the impact of low SES circumstances on their healthcare costs can be positively influenced. Additionally, policies that influence more timely and appropriate healthcare use in low SES populations can reduce healthcare costs further.