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

Abstract

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.

Health, wealth, and medical expenditures among the elderly in rural Tanzania: experiences from Nzega and Igunga districts

“…In addition, the findings differ from some studies done in the United States of America and elsewhere where it was found that there is a positive relationship between SES and access to health care services and health spending [41]. On the other hand, studies done in the Netherlands found that households with low incomes had higher health expenditures compared with households with higher incomes [42,43]. The influence of social position could be clearer in the long term than in the short term.…”

Evaluation of risk adjustment performance of diagnosis-based and medication-based comorbidity indices in patients with chronic obstructive pulmonary disease

“…Firstly, medical expenditure data revealed a positively skewed distribution, and thus they were converted to natural logarithm values. For all logistic regression models, medical expenditures were then dichotomized and the threshold was set at Q3 (the 75 th percentile), with Q1-Q3 in the low-cost group whereas Q4 in the highcost group, in accordance with previous research [34,35]. Furthermore, to assess how well the added comorbidity measures would improve the fitted models, we firstly calculated the loglikelihood ratio statistic G 2 [36].…”

Research of socioeconomic status and school-based health screening results of study with children after two years of COVID-19 pandemic

“…In a study examining obesity in children aged 7-14 from different socioeconomic status in Turkey, it was stated that the prevalence of obesity was higher in students from middle and high socioeconomic status (9). In a recent study conducted in the Netherlands, it was emphasized that the children of families with low socioeconomic status had more frequent hospital admissions due to chronic diseases and growth retardation and therefore more health expenditures (10).…”