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Xu M, Peng H, Hong Q, Rao Z, Peng XE. Spatial distribution and influencing factors of thyroid cancer hospitalization rate among rural residents in Fujian Province, China from 2012 to 2016. Environ Sci Pollut Res Int 2023; 30:45171-45183. [PMID: 36705824 DOI: 10.1007/s11356-023-25463-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 01/17/2023] [Indexed: 01/28/2023]
Abstract
This study aimed to explore the spatial distribution and influencing factors of thyroid cancer hospitalization rates in Fujian Province from 2012 to 2016. Hospitalization reimbursement records for thyroid cancer were obtained from 2025 hospitals in Fujian Province from 2012 to 2016. The Moran's I method was used for spatial autocorrelation analysis and to further draw a spatial cluster map in Fujian. Geographic detectors were used to explore the effect of risk factors on spatial heterogeneity of inpatient service utilization for thyroid cancer. The study showed that there was obvious temporal and spatial heterogeneity in the utilization rate of inpatient services for thyroid cancer in Fujian Province, which were mainly concentrated in Fuzhou, with Lianjiang County as the center, and the gathering area involves 26 counties and cities. Among a variety of environmental factors, air quality index (AQI) (q = 0.481), carbon sequestration (q = 0.161), and carbon emissions (q = 0.155) were the main factors affecting the hospitalization rates. AQI and carbon emissions were generally positively correlated with hospitalization rates, and carbon sequestration was negatively correlated. After the interaction of the two factors, the interpretation of the hospitalization rate was enhanced. The obvious spatial heterogeneity will help the relevant departments to adjust measures to local conditions and allocate medical resources rationally to ease the pressure of seeking medical attention in high-demand areas.
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Affiliation(s)
- Miao Xu
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, The School of Public Health, Fujian Medical University, Fuzhou, China
| | - Hewei Peng
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, The School of Public Health, Fujian Medical University, Fuzhou, China
| | - Qizhu Hong
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, The School of Public Health, Fujian Medical University, Fuzhou, China
| | - Zhixiang Rao
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, The School of Public Health, Fujian Medical University, Fuzhou, China
| | - Xian-E Peng
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, The School of Public Health, Fujian Medical University, Fuzhou, China.
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Wang Y, Jing Z, Ding L, Tang X, Feng Y, Li J, Chen Z, Zhou C. Socioeconomic inequity in inpatient service utilization based on need among internal migrants: evidence from 2014 national cross-sectional survey in China. BMC Health Serv Res 2020; 20:984. [PMID: 33109188 PMCID: PMC7590715 DOI: 10.1186/s12913-020-05843-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 10/21/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Providing equal treatment for those who have the same need for healthcare, regardless of their socioeconomic and cultural background, has become a shared goal among policymakers who strive to improve healthcare. This study aims to identify the socioeconomic status (SES) inequities in inpatient service utilization based on need among migrants by using a nationally representative study in China. METHODS The data used in this study was derived from the 2014 National Internal Migrant Population Dynamic Monitoring Survey collected by the National Health Commission of China. The sampling frame for this study was taken using the stratified multistage random sampling method. All provincial urban belt and key cities were stratified, and 119 strata were finally determined. We used logistic regression method and Blinder-Oaxaca decomposition and calculated the concentration index to measure inequities of SES in inpatient service utilization based on need. Sample weights provided in the survey were applied in all the analysis and all standard errors in this study were clustered at the strata level. RESULTS Of the total internal migrants, 18.75% unmet the inpatient service need. Results showed that inpatient service utilization concentrated among high-SES migrants (Concentration Index: 0.036, p < 0.001) and the decomposition results suggested that about 44.16% of the total SES gap in inpatient service utilization could be attributed to the gradient effect. After adjusting for other confounding variables, those had high school degree and university degree were more likely to meet the inpatient services need, and the OR values were 1.48 (95% CI 1.07, 2.03, p = 0.017) and 2.04 (95% CI 1.45, 2.88, p = 0.001), respectively. The OR values for Quartile 3 and Quartile 4 income groups was 1.28 (95% CI 1.01, 1.62, p = 0.044) and 1.37 (95% CI 1.02, 1.83, p = 0.035), respectively. CONCLUSION This study observed an inequity in inpatient service utilization where the utilization concentrates among high SES migrants. It is important for policy makers to be aware of them and more intervention should be conducted.
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Affiliation(s)
- Yi Wang
- Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.,NHC Key Lab of Health Economics and Policy Research (Shandong University), Jinan, 250012, China
| | - Zhengyue Jing
- Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.,NHC Key Lab of Health Economics and Policy Research (Shandong University), Jinan, 250012, China
| | - Lulu Ding
- Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.,NHC Key Lab of Health Economics and Policy Research (Shandong University), Jinan, 250012, China
| | - Xue Tang
- Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.,NHC Key Lab of Health Economics and Policy Research (Shandong University), Jinan, 250012, China
| | - Yuejing Feng
- Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.,NHC Key Lab of Health Economics and Policy Research (Shandong University), Jinan, 250012, China
| | - Jie Li
- Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.,NHC Key Lab of Health Economics and Policy Research (Shandong University), Jinan, 250012, China
| | - Zhuo Chen
- College of Public Health, University of Georgia, Athens, GA, 30606, USA.,School of Economics, University of Nottingham, Ningbo, China
| | - Chengchao Zhou
- Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China. .,NHC Key Lab of Health Economics and Policy Research (Shandong University), Jinan, 250012, China.
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Zhao M, Liu B, Shan L, Li C, Wu Q, Hao Y, Chen Z, Lan L, Kang Z, Liang L, Ning N, Jiao M. Can integration reduce inequity in healthcare utilization? Evidence and hurdles in China. BMC Health Serv Res 2019; 19:654. [PMID: 31500617 PMCID: PMC6734466 DOI: 10.1186/s12913-019-4480-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Accepted: 08/28/2019] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Integration of medical insurance schemes has been prioritized as one of the key strategies to address inequity in China's health system. The first pilot attempt to integrate started in 2003 and later expanded nationwide. This study aims to assess its intended impact on inequity in inpatient service utilization and identify the main determinants contributing to its ineffectiveness. METHODS A total of 49,365 respondents in the pilot integrated area and 77,165 respondents in the non-integration area were extracted from the Fifth National Health Services Survey. A comparative analysis was conducted between two types of areas. We calculate a concentration index (CI) and horizontal inequity index (HI) in inpatient service utilization and decompose the two indices. RESULTS Insurance integration played a positive role in reducing inequality in inpatient service utilization to some extent. A 13.23% lower in HI, a decrease in unmet inpatient care and financial barriers to inpatient care in the pilot integrated area compared with the non-integration area; decomposition analysis showed that the Urban-Rural Residents Basic Medical Insurance, a type of integrated insurance, contributed 37.49% to reducing inequality in inpatient service utilization. However, it still could not offset the strong negative effect of income and other insurance schemes that have increased inequality. CONCLUSIONS The earlier pilot attempt for integrating medical insurance was not enough to counteract the influence of factors which increased the inequality in inpatient service utilization. Further efforts to address the inequality should focus on widening access to financing, upgrading the risk pool, reducing gaps within and between insurance schemes, and providing broader chronic disease benefit packages. Social policies that target the needs of the poor with coordinated efforts from various levels and agencies of the government are urgently needed.
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Affiliation(s)
- Miaomiao Zhao
- Department of Social Medicine, School of Health Management, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China
- Department of Health Management, School of Public Health, Nantong University, 9 Seyuan Road, Chongchuan District, Nantong, 226019, Jiangsu, China
| | - Baohua Liu
- Department of Social Medicine, School of Health Management, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China
| | - Linghan Shan
- Department of Social Medicine, School of Health Management, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China
| | - Cui Li
- Department of Social Medicine, School of Health Management, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China
| | - Qunhong Wu
- Department of Social Medicine, School of Health Management, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China.
| | - Yanhua Hao
- Department of Social Medicine, School of Health Management, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China.
| | - Zhuo Chen
- Department of Health Policy and Management College of Public Health, University of Georgia, Athens, GA, 30602, USA
- School of Economics, Faculty of Humanities and Social Sciences, University of Nottingham Ningbo, 199 Taikang East Road, Ningbo, Zhejiang, 315100, China
| | - Lan Lan
- Department of Social Medicine, School of Health Management, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China
| | - Zheng Kang
- Department of Social Medicine, School of Health Management, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China
| | - Libo Liang
- Department of Social Medicine, School of Health Management, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China
| | - Ning Ning
- Department of Social Medicine, School of Health Management, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China
| | - Mingli Jiao
- Department of Social Medicine, School of Health Management, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China
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