Pfizer, Inc., Pharm Sci and PGS Statistics, 445 Eastern Point Rd, Groton, Connecticut, USA.
Social Policy Research Center, UNSW, Sydney, Australia.
BMC Public Health. 2023 Jul 27;23(1):1439. doi: 10.1186/s12889-023-16282-7.
Although evidence on healthcare utilization avoidance during COVID-19 pandemic is emerging, such knowledge is limited in rural settings. An effective policy to the COVID-19 shocks and stresses in rural settings require empirical evidence to inform the design of health policies and programmes. To help overcome this evidence gap and also contribute to policy decisions, this study aimed at examining COVID-19-induced healthcare utilization avoidance and associated factors in rural India.
This study used the third-round data from the COVID-19-Related Shocks in Rural India survey conducted between 20-24 September, 2020 across six states. The outcome variable considered in this study was COVID-19-induced healthcare utilization avoidance. Multivariable Binary Logistic Regression Model via Multiple Imputation was used to assess the factors influencing COVID-19-induced healthcare utilization avoidance.
Data on 4,682 respondents were used in the study. Of this, the prevalence of COVID-19-induced healthcare utilization avoidance was 15.5% in rural India across the six states. After adjusting for relevant covariates, participants from the Bihar State have significantly higher likelihood of COVID-19-induced healthcare utilization avoidance compared to those from the Andhra Pradesh. Also, participants whose educational level exceeds high school, those who use government hospital/clinic, engage in daily wage labour in agriculture have significantly higher odds of COVID-19-induced healthcare utilization avoidance compared to their counterparts.
Our study revealed that state of residence, type of health facility used, primary work activity and educational level were associated with COVID-19-induced healthcare utilization avoidance in rural India. The findings suggest that policy makers and public health authorities need to formulate policies and design interventions that acknowledge socioeconomic and demographic factors that influence healthcare use avoidance.
尽管有关 COVID-19 大流行期间医疗保健利用回避的证据正在出现，但在农村地区，此类知识有限。为了应对农村地区 COVID-19 冲击和压力，需要有有效的政策来提供实证证据，为卫生政策和方案的制定提供信息。为了帮助克服这一证据差距，并为决策提供参考，本研究旨在调查印度农村地区 COVID-19 引起的医疗保健利用回避及其相关因素。
本研究使用了 2020 年 9 月 20 日至 24 日在六个邦进行的印度农村 COVID-19 相关冲击调查的第三轮数据。本研究考虑的结果变量是 COVID-19 引起的医疗保健利用回避。采用多重插补的多变量二项逻辑回归模型来评估影响 COVID-19 引起的医疗保健利用回避的因素。
本研究使用了来自六个邦的 4682 名受访者的数据。其中，六个邦农村地区 COVID-19 引起的医疗保健利用回避率为 15.5%。在调整了相关协变量后，与来自安得拉邦的受访者相比，来自比哈尔邦的受访者更有可能回避 COVID-19 引起的医疗保健利用。此外，与具有高中以下学历的受访者相比，接受过高等教育的受访者、使用政府医院/诊所的受访者、从事农业日薪劳动的受访者更有可能回避 COVID-19 引起的医疗保健利用。
我们的研究表明，居住邦、使用的医疗设施类型、主要工作活动和教育水平与印度农村地区 COVID-19 引起的医疗保健利用回避有关。研究结果表明，政策制定者和公共卫生当局需要制定政策和设计干预措施，承认影响医疗保健使用回避的社会经济和人口因素。
