Armut, öffentliche Sozialtransfers und Gesundheit: Eine Analyse zur subjektiven Gesundheit von Sozialleistungsbeziehern in Deutschland

Pförtner, Timo-Kolja; Schumann, Nadine

doi:10.1055/s-0035-1564206

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…Unhealthy behaviors like poor diet, smoking, or a lack of physical activity ( 3 ) can lead to lower levels of health, which are significantly associated with poverty. Structural factors such as the local economic development and social security systems ( 19 – 23 ), the risk of fuel scarcity and climate ( 24 ), social transfers ( 25 ), and other related constructs like social cohesion, social capital, and social exclusion ( 11 ) also impact health poverty. Furthermore, considerable literature has begun to explore relative standards of health poverty, such as using specific proportions of the median income to calculate relative poverty thresholds ( 26 , 27 ).…”

Section: Introductionmentioning

confidence: 99%

Analysis of medical impoverishment and its influencing factors among China's rural near-poor, 2016–2020

Feng,

Che,

et al. 2024

Front. Public Health

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ObjectiveThis study investigates the determinants of medical impoverishment among China's rural near-poor, aiming to enhance public health services and establish preventative and monitoring systems.MethodsUsing China Family Panel Studies and World Bank methods, we categorized rural populations and calculated their 2020 Poverty Incidence (PI) and Poverty Gap (PG), with impoverishing health expenditures (IHE) as the primary indicator. We analyzed the data from 2016 to 2020 using a conditional fixed-effects multinomial logit model and 2020 logistic regression to identify factors influencing medical impoverishment risk.Results(1) In 2020, the near-poor in China faced a PI of 16.65% post-health expenditures, 8.63 times greater than the non-poor's PI of 1.93%. The near-poor's Average Poverty Gap (APG) was CNY 1,920.67, notably surpassing the non-poor's figure of CNY 485.58. Health expenses disproportionately affected low-income groups, with the near-poor more prone to medical impoverishment. (2) Disparities in medical impoverishment between different economic household statuses were significant (P < 0.001), with the near-poor being particularly vulnerable. (3) For rural near-poor households in China, those with over six members faced a lower risk of medical impoverishment compared to those with three or fewer. Unmarried individuals had a 7.1% reduced risk of medical impoverishment relative to married/cohabiting counterparts. Unemployment was associated with a 9% increased risk. A better self-rated health status was linked to a lower probability of IHE, with the “very healthy” reporting a 25.8% lower risk than those “unhealthy.” Chronic disease sufferers in the near-poor and non-poor categories were at an increased risk of 12 and 1.4%, respectively. Other surveyed factors, including migrant status, age, insurance type, gender, educational level, and recent smoking or drinking, were not statistically significant (P > 0.05).ConclusionRural near-poor in China are much more susceptible to medical impoverishment, influenced by specific socio-economic factors. The findings advocate for policy enhancements and health system reforms to mitigate health poverty. Further research should extend to urban areas for comprehensive health poverty strategy development.

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