Regional socioeconomic characteristics and density of general practitioners in Germany: A nationwide cross-sectional and longitudinal spatial analysis

IF 3.9 3区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
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引用次数: 0

Abstract

Objectives

Limited healthcare availability impacts population health. Regional disparities in GP density across Germany raise questions about their association with regional socioeconomic characteristics.

Study design

This longitudinal nationwide ecological German study used regional data at the county level (n = 401) from 2015 to 2019 provided by the Federal Institute for Research on Building, Urban Affairs and Spatial Development (BBSR). The outcome was general practitioners (GPs) density, defined as the number of GPs per 10,000 inhabitants.

Methods

Univariate Moran's I, cluster analysis (LISA), and spatial lag of X (SLX) models were employed to analyse the spatial distribution of GP density and its correlation with various regional socioeconomic characteristics from a cross-sectional and longitudinal perspective.

Results

In contrast to the univariate analysis, rural counties showed the highest GP density the multivariate model. Several counties were identified as embedded in low- or high-GP-density clusters. In 2015 and 2019, larger household size (2015: std. β = −2.31, p = 0.021; 2019: std. β = −4.14, p < 0.001) and higher unemployment rate (2015: std. β = −2.84, p = 0.005; 2019: std. β = −5.47, p < 0.001) were associated with lower GP density. In the longitudinal model, a greater increase in the unemployment rate was related to a greater decrease in GP density (std. β = −2.17, p = 0.030).

Conclusion

A higher regional unemployment rate is linked to lower GP availability in Germany, and a greater increase in the unemployment rate was related to a greater decrease in GP availability over time. This necessitates policy intervention to avoid socioeconomic disparities in GP care.

德国地区社会经济特征与全科医生密度:全国范围内的横截面和纵向空间分析
目标有限的医疗服务会影响人口健康。研究设计这项德国全国生态纵向研究使用了联邦建筑、城市事务和空间发展研究所(BBSR)提供的 2015 年至 2019 年县级地区数据(n = 401)。研究结果是全科医生(GPs)密度,定义为每 10,000 名居民中全科医生的数量。方法采用单变量莫兰 I、聚类分析(LISA)和 X 的空间滞后(SLX)模型,从横截面和纵向角度分析全科医生密度的空间分布及其与各种区域社会经济特征的相关性。结果与单变量分析相比,农村县在多变量模型中显示出最高的全科医生密度。有几个县被确定为低或高全科医生密度集群。在 2015 年和 2019 年,较大的家庭规模(2015 年:std. β = -2.31,p = 0.021;2019 年:std. β = -4.14,p <0.001)和较高的失业率(2015 年:std. β = -2.84,p = 0.005;2019 年:std. β = -5.47,p <0.001)与较低的 GP 密度相关。在纵向模型中,失业率的增加与全科医生密度的减少有关(std. β = -2.17,p = 0.030)。这就需要进行政策干预,以避免全科医生护理中的社会经济差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Public Health
Public Health 医学-公共卫生、环境卫生与职业卫生
CiteScore
7.60
自引率
0.00%
发文量
280
审稿时长
37 days
期刊介绍: Public Health is an international, multidisciplinary peer-reviewed journal. It publishes original papers, reviews and short reports on all aspects of the science, philosophy, and practice of public health.
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