Coupling coordination between ecological environment quality and public health of residents in the Yellow River Basin, China: A modified coupling coordination model approach

The continuous development of industrial technology has led to significant environmental pollution and climate change, both of which have severely impacted human health. Investigating the coupling coordination between ecological environment quality (EEQ) and public health of residents (PHR) is beneficial for enhancing public health and promoting sustainable development. This study uses panel data from 55 cities within urban agglomerations of the Yellow River Basin, China (YRBC) from 2011 to 2022 to construct evaluation index systems for both EEQ and PHR. The entropy method is first employed to quantify the development levels of these systems. Subsequently, a modified coupling coordination degree (CCD) model is applied to evaluate the coordination between the two systems. Furthermore, the study utilizes the Dagum Gini coefficient, Kernel density estimation, and Markov chains to analyze the spatiotemporal evolution of CCD. The Quadratic Assignment Procedure (QAP) is finally used to empirically test the factors influencing regional differences in CCD. The findings reveal that both EEQ and PHR levels in the YRBC exhibited an overall upward trend during the study period, although PHR showed declines in certain years. The CCD demonstrated a steady increase across the entire sample and within all three major regions. Analysis using the Dagum Gini coefficient indicates a narrowing disparity in CCD, with the Gini coefficient decreasing from 0.0617 in 2011 to 0.0536 in 2022. Kernel density estimation suggests that the CCD distribution curve has shifted rightward, becoming higher and steeper, indicative of reduced absolute differences in coupling coordination levels. QAP regression analysis reveals that factors such as regional disparities in per capita GDP significantly influence CCD regional disparities.