Background: Food insecurity is a growing global issue driven by income inequality, food price fluctuations, and unequal access to essential resources. However, the interrelations among income distribution, real income, food prices, food insecurity, and health expenditure are not well understood, especially in terms of indirect and mediated effects. Materials and methods: We used a longitudinal dataset to build vector autoregression models and applied the Toda–Yamamoto causality approach to examine direct and mediated pathways. The augmented Dickey–Fuller test assessed stationarity, and optimal lag lengths were selected using the Akaike information criterion. We used the K-means algorithm for income group classification and the Wald test for comparing findings across groups, based on data from 99 countries. Structural stability was tested using CUSUM test for parameter stability and CUSUMSQ test for variance stability of recursive residuals and Bai–Perron for multiple breakpoints. Results: Income distribution and real income directly influenced food prices. In turn, food prices significantly impacted both food insecurity and health expenditure. In high-income countries, food insecurity was found to play a partial mediating role in the relationship between food prices and health expenditure. Importantly, in the global sample, income inequality mediated the relationship between food prices and food insecurity. The joint analysis of all variables revealed causal pathways that were not evident in isolated models. Conclusion: These findings highlight the critical role of income inequality in worsening food insecurity and increasing health burdens. The observed mediation mechanisms also suggest that targeted, income group–specific interventions are needed to effectively mitigate the compounded impacts of food inflation on health systems. Addressing economic disparities, stabilizing food prices, and enhancing welfare systems could reduce both food-related and healthcare challenges. Future research should explore regional patterns and broader socioeconomic indicators to support sustainable policy design.

Sağlık sisteminin etkinliği son yıllarda sıklıkla tartışılan konulardan birisidir. Sağlık harcamalarının artış eğilimi içinde olması kaynakların etkin kullanılıp kullanılmadığını sorgulamamızı gerektirmektedir. Bu çalışmanın amacı da OECD (Ekonomik İşbirliği ve Kalkınma Örgütü) ülkelerinin sağlık sisteminin etkinlik analizini gerçekleştirmektir. Çalışmada öncellikle kapsamlı bir literatür taraması ile sağlık sisteminin etkinliğinin değerlendirilmesinde kullanılan değişkenler belirlenmiştir. Bazı sağlık harcaması değişkenleri girdi olarak bazı sağlık statüsü göstergeleri de çıktı olarak belirlendikten sonra Veri Zarflama Analizi (VZA) ile 34 OECD ülkesinin hem 2000 hem de 2013 yılı verilerine göre etkinlik analizi gerçekleştirilmiştir. Ayrıca analizin son aşamasında 34 OECD ülkesi Mahalanobis Uzaklıklarına göre yapılan eleme sonucunda 27 ülkeye indirilerek bu ülkelerin etkinliği yeniden analiz edilmiştir. 34 OECD üyesi ülkeden 2000 yılında 15 ülkenin etkin olduğu, 2013 yılında ise bu sayının 13’e düştüğü tespit edilmiştir. Sağlık sisteminde etkinliğe ulaşabilmek için ülkeler kendi modellerini geliştirmenin yanı sıra birbirlerinin deneyimlerinden de yararlanmalıdırlar.

Objectives: The main purpose of this study is to investigate the factors affecting health expenditure levels through a panel data analysis. Methods: The study includes data from 35 OECD member countries between 2005 and 2015. We carried out panel regression analysis using STATA 13.0 econometric program. In the study, we used per capita health expenditure figures according to purchasing power parity as the dependent variable and we searched the impact of aging, urbanization and income on health expenditures with fixed effects panel regression model. Findings: The regression model indicates that aging, urbanization and income have positive effects on health expenditures per capita. For instance, a 1% increase in population ages 65+ causes an increase in health expenditures by $165 per capita. Conclusion: Although health expenditures are influenced by many factors, demographic structures and demographic changes, such as aging, urbanization and income, have a significant impact on health expenditures.

Analyzing the prevalence of neurological disorders (NDs) is crucial to understand health expenditures and economic outcomes as they change over time and have significant economic effects. Diseases, particularly those involving neuron damage, can have an economic impact. This study aims to quantify the effects of NDs on health expenditure and economic output for OECD countries from 2000 to 2021 using a dual-model dynamic panel data approach. Also, this study uniquely highlights the dual economic burden of neurological disorders by examining their simultaneous impact on both health expenditures and economic output using dynamic panel data methods. We used both Arellano–Bond and Blundell–Bond estimation methods. The results indicate that an increase in ND prevalence significantly impacts both health expenditures and economic output. While NDs substantially raise health expenditures, they also decrease income levels, underscoring their dual economic burden. Overall, the rise in NDs in society drives up healthcare spending and underscores their significant economic burden. Policymakers should prioritize preventive strategies and early interventions for neurological disorders to mitigate their rising economic and healthcare costs on a societal level.