Yu Cuiting, Li Tianrun, Wan Qin
School of Economics and Management, Southwest Petroleum University, Chengdu, China.
Front Public Health. 2025 Apr 11;13:1580069. doi: 10.3389/fpubh.2025.1580069. eCollection 2025.
Energy poverty significantly affects the well-being of vulnerable populations, particularly middle-aged and older adult individuals in rural China. This study investigates how energy poverty impacts health capital, using data from the China Health and Retirement Longitudinal Study (CHARLS).
We employed the Multidimensional Energy Poverty Index (MEPI) to measure energy poverty and used an ordered logit model to analyze its effects on self-rated health (SRH) as a proxy for health capital. The study utilized longitudinal data from 2013, 2015, 2018, and 2020, covering 9,464 observations, and included control variables such as age, gender, and chronic disease status. Endogeneity was addressed using instrumental variables and propensity score matching.
The findings indicate that energy poverty has a significant negative impact on health capital, with a regression coefficient of -0.221(p<0.01), lowering self-rated health levels. This effect is consistent across physical health, mental health, and daily functioning. Heterogeneity analysis reveals that individuals with lower education levels and those in southern rural areas experience more severe health impacts. Mediation tests confirm that indoor environmental conditions partially mediate this relationship.
The study underscores the urgent need for targeted interventions to mitigate energy poverty in rural China. Expanding access to clean energy, improving rural infrastructure, and providing financial subsidies are critical. Education and regional policies should also be prioritized to address disparities.
能源贫困严重影响弱势群体的福祉，尤其是中国农村地区的中年及老年人群体。本研究利用中国健康与养老追踪调查（CHARLS）的数据，探讨能源贫困如何影响健康资本。
我们采用多维能源贫困指数（MEPI）来衡量能源贫困，并使用有序逻辑回归模型分析其对作为健康资本代理指标的自评健康（SRH）的影响。该研究利用了2013年、2015年、2018年和2020年的纵向数据，涵盖9464个观测值，并纳入了年龄、性别和慢性病状况等控制变量。使用工具变量和倾向得分匹配法解决内生性问题。
研究结果表明，能源贫困对健康资本有显著的负面影响，回归系数为-0.221（p<0.01），降低了自评健康水平。这种影响在身体健康、心理健康和日常功能方面是一致的。异质性分析表明，教育水平较低的个体以及中国南方农村地区的个体受到的健康影响更为严重。中介检验证实，室内环境条件部分中介了这种关系。
该研究强调了在中国农村地区采取针对性干预措施以减轻能源贫困的迫切需求。扩大清洁能源的获取、改善农村基础设施以及提供财政补贴至关重要。还应优先考虑教育和区域政策以解决差异问题。
