Ohio State University, Department of Reconstructive Surgery, Columbus, Ohio, USA.
Kenyon College, Department of Political Science, Gambier, Ohio, USA.
J Glob Health. 2022 Feb 5;12:04002. doi: 10.7189/jogh.12.04002. eCollection 2022.
A significant portion of surgical aid to low- and middle-income countries (LMICs) is provided by non-governmental organizations (NGOs) in concert with surgeons, but little is known about the overall scope of this work or how it corresponds to indicators typically used to guide developmental aid distribution. The objective of this study was to characterize and investigate the collective efforts of NGOs providing reconstructive surgical aid to LMICs.
An interdisciplinary approach was taken drawing from political science to examine this issue in reconstructive surgery. NGOs providing reconstructive surgical aid were identified, and then catalogued with respect to the LMICs they serve. LMICs were characterized using 28 variables in 6 domains based on contemporary developmental theory. Univariate and multivariate regression analyses were performed.
A total of 131 reconstructive surgery NGOs were identified serving 718 sites in 136 LMICs. Univariate analysis found that LMICs that were more frequent recipients of aid were more populous ( < 0.001), had lower 'Hospital Beds Density' ( = 0.001), and had higher rates of 'Mortality by Injury' ( = 0.001). Multivariate regression analysis identified population as the sole predictor among all indicators analyzed (95% confidence interval (CI) = 1.154 to 1.469; = 0.001).
The distribution of reconstructive surgical aid by NGOs is guided most by population, but not other characteristics traditionally used to guide aid distribution. Greater coordination and data-sharing among NGOs is recommended to optimize outreach efforts.
相当一部分向中低收入国家(LMICs)提供的外科援助是由非政府组织(NGOs)与外科医生合作提供的,但人们对这项工作的总体范围及其与通常用于指导发展援助分配的指标的对应关系知之甚少。本研究的目的是描述和调查向 LMICs 提供重建外科援助的 NGO 的集体努力。
采用跨学科方法,借鉴政治学来研究重建外科中的这个问题。确定了向 LMICs 提供重建外科援助的 NGO,并根据他们所服务的 LMIC 对其进行分类。根据当代发展理论,使用 6 个领域的 28 个变量对 LMIC 进行特征描述。进行了单变量和多变量回归分析。
共确定了 131 个提供重建外科援助的 NGO,服务于 136 个 LMIC 的 718 个地点。单变量分析发现,接受援助更频繁的 LMIC 人口更多( < 0.001),“医院床位密度”更低( = 0.001),“伤害死亡率”更高( = 0.001)。多变量回归分析确定人口是所有分析指标中唯一的预测因素(95%置信区间(CI)=1.154 至 1.469; = 0.001)。
NGO 提供的重建外科援助的分布主要由人口决定,但不是传统上用于指导援助分配的其他特征。建议 NGO 之间加强协调和数据共享,以优化外展工作。