key: cord-0020529-ww9aloag
authors: Wu, Xiaoming; Shi, Xiujing; Li, Honglei; Guo, Zhen
title: Temporal and Spatial Characteristics of Cataract Surgery Rates in China
date: 2021-08-25
journal: Risk Manag Healthc Policy
DOI: 10.2147/rmhp.s317547
sha: def9a85bbac31acf6079b29e8f642cffc4dbf95e
doc_id: 20529
cord_uid: ww9aloag

OBJECTIVE: The aim of the current study was to explore the spatial and temporal distribution characteristics of registered cases of cataract surgery in China from 2013 to 2017. METHODS: A database for spatial analysis of cataract surgery in China in 2013–2017 was established using ArcGIS10.0 software as a platform for data management and presentation. Spatial autocorrelation analysis of cataract surgery was undertaken, and temporal and spatial scan analysis was done using SaTScan 9.5 software. RESULTS: From 2013 to 2017, annual cataract surgery rates (CSRs) in China were 1200, 1400, 1782, 2070, and 2205 per 1 million population, indicating a gradually increasing trend. Local Moran’s I autocorrelation analysis showed that there was spatial clustering of CSR in China, with Anhui being a low-high clustering region. Findings of global hotspot analysis Getis-Ord General G showed that General G index of national CSR was <0.01, Z = 1.12, P = 0.26. Findings of staged spatial-temporal scan analysis indicated that 18 areas of aggregation were found in 2 stages. Observed differences in each clustering area were statistically significant (P < 0.05). CONCLUSION: CSRs in China showed increasing trend year by year and were randomly distributed, with spatial clustering, and Anhui was reported as a low-high clustering region. However, high-risk areas still persist, requiring focused attention and targeted prevention and control measures.

Cataract is the leading cause of blindness, and CSR (the number of cataract surgeries performed annually per million population) is used as a proxy indicator of access to cataract services in a country. 1, 2 Global data published by the World Health Organization (WHO) estimated that of the estimated 76 million people with visual impairment in China, 36.5% of the cases are believed to be attributed to cataract. 3 China is still among 30 countries with a high burden of cataract surgery worldwide, with new cataracts being diagnosed yearly. 2 Incidence of cataract is related to the geographical, economic, and demographic environment of the region where it is located. 1, 4 CSR varies greatly from country to country, and even within countries. 5, 6 Therefore, exploration of spatial distribution characteristics and prevalence trends of cataract surgery is important to prevent cataract blindness in China.

Geographic Information System (GIS) is a technical system based on geospatial database and supported by computer hardware and software systems to collect, store, manage, compute, analyze, display, and describe relevant geographical distribution of data in space. 7 Use of GIS enables convenient description and analysis of spatial and temporal distribution patterns of population diseases, health, and health events. 8 In addition, GIS enables exploration of factors affecting health status of specific populations, which helps in disease prevention and control, health promotion, and health services. 9, 10 In the current study, the spatial distribution and clustering of cataract surgery registrations at provincial level in China from 2013 to 2017 were analyzed using GIS technology as well as spatial and temporal scanning analyses. This provided the basis for further studies of treatment and prevention of cataract blindness as well as formulation of optimization strategies.

The national cataract surgery registration report of 2013-2017 was obtained from the China network of National Blindness Prevention and Treatment (http://www. moheyes.com/), which collected statistical data from the Cataract Revision Surgery Information Reporting System from 2013-2017 and estimated the cataract surgery rate (CSR) per 1 million population in each province (municipality directly under central government and autonomous region). Permission to conduct the current study was obtained from the China network of National Blindness Prevention and Treatment. The national provincial vector map (1:1.6 million) was used as base map, and the same number was created for each province (municipality and autonomous region) in the layer by referring to the number in attribute database. Collated CSRs were correlated and matched with numbers in the base map to create a complete spatial analysis database.

Global Moran's I index and local Moran's I index were used to explore spatial autocorrelation of CSRs in the study area. 11 A spatial weight matrix was generated based on geographic proximity of the national provincial administrative divisions using the inverse distance-based spatial conceptualization method. Global Moran's I index and local Moran's I index were computed using ArcGIS 10.0 software based on defined weight matrix. 12 When the correlation is high, that is, the phenomenon of spatial aggregation and distribution is significant; I<0 indicates a negative correlation, with smaller values reflecting weak correlation. When I tend towards 0, spatial distribution shows random distribution. For statistical test of Moran's I, test statistic Z-values are used to approximate normal distribution under random conditions, with P<0.05 indicating statistically significant differences. Global spatial autocorrelation determined whether research objects showed clustering distribution in general, whereas local spatial autocorrelation described correlation between CSR in each province (municipality directly under central government or autonomous region) and its neighboring provinces (municipality directly under central government or autonomous region). Local spatial autocorrelation also identified specific clustering regions and clustering patterns, in which low-high clustering and low-low clustering were defined as a high-risk area. 13 Hotspot Analysis Getis-Ord G The presence of "positive hotspot" or "negative hotspot" in the whole study area was detected using global G statistic. G>0 and P<0.05 indicated high-value agglomerations in the study area, whereas G<0 and P<0.05 indicated low-value agglomerations in the study area. 14 Comparisons of high-value agglomerations or low-value agglomerations between each province (municipality directly under central government or autonomous region) and neighboring provinces (municipality directly under central government or autonomous region) were undertaken using Local G statistic. Z>1.96 indicated existence of high-value agglomerations in and around spatial unit I, whereas Z<-1.96 indicated existence of low-value agglomerations in and around spatial unit I. 15 Spatiotemporal Scan Analysis 16 Aggregation analysis was undertaken using SaTScan 9.5 software, whereas visualization of results was undertaken using ArcGIS 10.0 software. 17 segmentation desktop window ArcMap of ArcGIS 10.0 software was used to categorize the average annual registration rate of cataract surgery in each province, and rank classification was chosen, with color from light to dark indicating registration rates from low to high. SaTScan 9.5 software is based on statistics of spatially dynamic window scans, and applies several scanning circles to detect spatial clustering of diseases in the study area, where size and position of windows are dynamic. Log likelihood ratio (LLR) of spatial units inside and outside the dynamic window was computed to make statistical inferences. LLRs of scanned circles were ranked from largest to smallest, with larger and statistically significant LLR values indicating that the region contained under the window was the most likely region to be aggregated. 18 The first aggregated region had the largest LLR value, and the second aggregated region had smaller LLR value, indicating that it is less likely to be a spatially aggregated region compared with the first aggregated region. Spatiotemporal scan analysis in the current study used Poisson distribution model in the SaTScan 9.5 software. Scan clustering was in the form of high-value clustering, whereas number of Monte Carlo simulation tests was set at 999, and temporal clustering interval was set at 1 year. 19

Findings of the current study showed that the rates of cataract surgery for the five years during 2013-2017 were 1200, 1400, 1782, 2070, and 2205 per 1 million population nationwide (Table 1) . Anhui Province, Xinjiang Uygur Autonomous Region, Hubei Province, Ningxia Hui Autonomous Region, and Guangxi Zhuang Autonomous Region had the lowest CSR levels and were ranked in Level 1. Most other provinces (municipalities directly under the Central Government and autonomous regions) had registration levels in Levels 2 to 4, with Shanghai, Tianjin, Beijing, Jiangsu Province, Tibet Autonomous Region, Chongqing, and Sichuan Province having the highest CSR levels and ranking in Level 5 ( Figure 1 ).

(1) Global spatial autocorrelation analysis: Findings of Moran's I global spatial autocorrelation analysis of national cataract surgery CSR from 2013-2017 showed that the annual Moran's I index interval was in the range of −0.072287 to 0.04323 with mean P>0.05. Autocorrelation was not statistically significant at regional scale, indicating no positive spatial correlation among national CSR (Table 2) .

(2) Local spatial autocorrelation analysis: Local Moran's I autocorrelation analysis showed that there was spatial clustering of cataract surgery in China, with Anhui being a low-high clustering region ( Figure 2) .

(3) Global hotspot analysis and local hotspot analysis: Findings of global hotspot analysis Getis-Ord General G showed that General G index=0.000001, Z=1.124960, P=0.260606 for average annual registration rate of cataract surgery nationwide, indicating that cataract surgery rate was not statistically significant at regional level of correlation. Furthermore, there were no "positive hot" and "negative hot" areas, an indication that Anhui is low-high concentration area (Figures 3 and 4 ).

Time and spatial scan analysis of national cataract surgery rate from 2013 to 2017 was undertaken in two stages. 18 Clustering regions were found in the two stages. Observed differences in each clustering area were statistically significant (all P<0.05; Table 3 ). The first level of clusters from 2013 to 2025 was largest in 2015, involving only Xinjiang, whereas second and third levels of clusters were mainly distributed in northeast (Jilin) and northwest (Ningxia, Qinghai, Gansu) of China. Clustering areas of registered cases of cataract surgery in China in the 13th Five-Year Plan period varied greatly compared with the 12th Five-Year Plan period. First agglomeration areas were east and central coastal 11 provinces and cities (Shandong, Henan, Jiangsu, Anhui, Hubei, Zhejiang, Jiangxi, Fujian, Tianjin, Hebei, and Shanghai), whereas second and third agglomeration areas were three northwestern provinces and autonomous regions (Xinjiang, Qinghai, and Gansu). In summary, cataract surgery registry in China had shifted to the eastern region since the 13th Five-Year Plan ( Figure 5 ).

Previous studies reported that accurate analysis of spatial distribution characteristics can reveal the distribution patterns and factors that influence CSR, and propose effective measures to prevent and treat blindness. [16] [17] [18] Findings of the current study established that GIS uses its spatial analysis technique to explore spatial and temporal distribution patterns of cataract surgery in each province from time and space perspectives, and to explore "hotspots" where cataract surgery is undertaken. Temporal, spatial, and social factors are crucial in promotion of cataract surgery in China. Therefore, the distribution status of cataract surgery rates in different regions also shows some spatial heterogeneity. 19, 20 The current study analyzed spatial and temporal characteristics of registered cases of cataract surgery in China from 2013-2017 at provincial level. The spatial distribution map of average annual surgery rates showed that national cataract restoration surgery rates for the five years 2013-2017 were 1200, 1400, 1782, 2070, and 2205 per 1 million population, indicating a gradually increasing trend. This trend may be explained by economic development of China. Moreover, the high level of CSR in this period may be explained by the implementation of a national cataract surgery prevention and control policy. 21 The National Cataract Surgery Prevention and Treatment Plan (2001-2010) proposed that efforts for cataract surgery prevention and treatment had been intensified from national to provincial level. 22, 23 The highest CSR in each province (municipality directly under the central government and autonomous region) was observed in Shanghai, where the 5-year average CSRs value is classified into five levels according to the natural breakpoint hierarchy. Qinghai Province, Heilongjiang Province, Anhui Province, Xinjiang Uygur Autonomous Region, Hubei Province, Ningxia Hui Autonomous 

Region, and Guangxi Zhuang Autonomous Region had the lowest CSR levels and were classified in first level. This is mainly due to minority residential areas, whereas most of the other provinces (municipalities directly under the central government and autonomous regions) were in the second to fourth levels of registration. Shanghai, Tianjin, Beijing, Jiangsu Province, Tibet Autonomous Region, Chongqing, and Sichuan Province had the highest CSR. This fifth ranking is partly due to the high level of local economic development and policies to prevent and treat blindness. The Chinese government has recently taken a leading role in preventing and treating blindness by implementing several programs to prevent and treat cataracts, where significant progress has been made. However, prevention and treatment of blindness is a longterm task involving livelihoods of people, and it is not enough to rely only on implementation of some projects to sustainably solve the problem of blindness with cataract in China. There is a need to focus on establishing long-term mechanisms and networks for prevention and treatment of blindness, as well as promotion of ophthalmology institutions at all levels to meet challenges due to increasing cataract blindness resulting from population growth and aging. 24 The current study showed that there was no positive spatial correlation between registration rates of cataract surgery in China during 2013-2017. Local spatial 

autocorrelation analysis showed spatial clustering of cataract surgeries in China, with Anhui being a low-high clustering region. Furthermore, global hotspot analysis Getis-Ord General G showed no "positive hotspots" or "negative hotspots", whereas local autocorrelation analysis showed that Anhui was a low-high concentration region, which was attributed to the irrational allocation of ophthalmic resources in the region. The current study established that ophthalmology institutions, surgical equipment, and ophthalmology technology were not well distributed, which prevented many rural and remote areas from receiving timely cataract treatment, which is among reasons why CSR could not be improved quickly. Ophthalmology resources had been allocated rationally, and capacity of comprehensive ophthalmology services at the basic level was inadequate. 1 This is either because of lack of necessary facilities, or existing facilities were too old to be used properly. 25, 26 In addition, lack of enough skilled personnel to provide services using equipment could explain inadequate capacity of comprehensive ophthalmology services at basic levels. 26, 27 These require government and ophthalmology academic groups to urgently set standards for ophthalmology facilities and services at grassroot levels, strengthen ophthalmology human resource development and appropriate training, develop counterpart support from ophthalmology resource-rich areas to rural and remote areas, and effectively strengthen capacity of comprehensive ophthalmology services at the county level to increase CSR. Spatial autocorrelation analysis determines presence of local agglomeration around an area, but not size and extent of agglomeration. 28, 29 Spatiotemporal scan analysis compensates for this shortcoming. 29 The current study applied staged spatial and temporal scan analysis to registered cases of cataract surgery in 2013-2017. Findings showed that 18 areas of aggregation were found in 2 stages, and differences observed in each area of aggregation were statistically significant, with particularly clear scope of In addition, phased time and space scan analyses established that the number of clustering areas in the two stages tended to decrease gradually, and clustering areas in the second stage decreased significantly compared with the previous stage, which indicated that the overall burden of cataract surgery in China is decreasing, and prevention and treatment of cataract surgery has improved. This burden is related to economic level, scientific education, and social efforts to prevent blindness. 1 Many people still have misconceptions about cataracts that cause blindness, and believe that it is "natural" for the elderly to be blind, which makes them and their children reluctant to receive treatment. [24] [25] [26] Some patients believe that they need to find the best "experts" and use the best equipment and materials for the operation, reportedly because some grassroots ophthalmology institutions cannot offer adequate expertise, which has aggravated the phenomenon of "difficult and expensive medical treatment" in urban hospitals. 24, 30 However, this study also contains several limitations. Firstly, the CSR included all surgeries performed in the total population irrespective of visual acuity or degree of visual impairment prior to the surgery, and therefore CSR did not necessarily reflect a needs-based provision of services. Secondly, the CSR data did not incorporate other significant outcomes such as visual acuity restoration rate, as well as the cataract surgical coverage among the cataract blind. It did not reflect actual disease burden completely. Thirdly, CSR data in 2018-2020 were not available for the reports from the China network of National Blindness Prevention and Treatment, and most data from this organization did not specify the methodology for data collection. Although we identified established cataract surgery registry systems in China, most of these did not publish their data collection procedures. As a result of this, the accuracy of CSR data from these sources cannot be verified.

In conclusion, the current study established that CSR in China from 2013 to 2017 showed an increasing trend year by year. Average annual cataract surgery rates in all provinces (autonomous regions and municipalities directly under the central government) were randomly distributed, with some degree of spatial aggregation. Staged spatiotemporal scan aggregation area decreased gradually, and cataract surgery prevention and control work has made some progress. However, high-risk areas still persisted, requiring focused attention and targeted prevention and control measures. Therefore, government should further strengthen prevention and treatment of blindness, especially prevention and treatment of cataract blindness. In addition, government should further improve rational allocation of ophthalmology resources (ophthalmology institutions, surgical equipment, and ophthalmology technology), and strengthen scientific propaganda and education. The current study also recommends that CSR should be focused on as an important indicator to evaluate progress of prevention and treatment of cataract blindness in each region, and seek support from all social services (Red Cross, private eye care institutions, Lions Clubs) to form 

government-led, multi-agency coordination mechanisms. Moreover, government should implement financial compensation mechanisms such as government remission. Non-governmental organizations, charitable groups, enterprises, and individuals should be lobbied to participate in various ways. In addition, hospitals, at all levels, should be encouraged to offer appropriate reductions or waivers within their means, in order to build more sustainable, low-cost and high-efficiency blindness prevention and treatment systems.

Cataract surgical rate and socioeconomics: a Global Study

Vision Loss Expert Group of the Global Burden of Disease, S. Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: the right to sight: an analysis for the Global Burden of Disease Study

Global estimates of visual impairment: 2010

View on output and outcomes of cataract surgery with national indices of socioeconomic development

Global burden of eye and vision disease as reflected in the cochrane database of systematic reviews

Eliminating cataract blindness -how do we apply lessons from Asia to Sub-Saharan Africa?

Using a geographic information system as a management tool for tuberculosis control

Application of GIS technology in public health: successes and challenges

Application of GIS in modern medicine

Applications and perspectives of GIS in public health and military guard

GIS-based analysis of the spatial distribution of diabetes and its influencing factors among the elderly in China

Zhejiang provence spatial scanning study of tuberculosis registries

Zhejiang provence characterization of the spatial distribution of patients with multidrug-resistant tuberculosis

Figure 5 Scope of time and space scan clustering area for cataract surgery in China

Spatial analysis of the prevalence of viral hepatitis B in Jiangsu Province (GIS)

Spatial distribution characteristics of residential drinking water iodine in Shandong province

Study of quantitative indicators of disease distribution status based on spatial point pattern analysis

Space epidemiology plays an important role in disease prevention and control

Current status and outlook of public health research based on spatial statistics

The application and development of GIS in disease prevention and control

A study on the allocation needs of tertiary blindness prevention health resources in Hainan Province in the context of a hierarchical diagnosis and treatment system

Seize the opportunity to take our country's eye health to a new level

Exploring the spatial analysis method and significance of public health resource allocation: the case of Qingdao City

Study on the spatial distribution and forecast of government health investment by province. China Health Econ

Ten-Year HM. Incidence of cataract surgery in urban southern China: the Liwan Eye Study

Willingness to pay for cataract surgery in rural southern China

A two-site, population-based study of barriers to cataract surgery in rural china

Cataract surgical coverage and visual acuity outcomes in rural China in 2014 and comparisons with the 2006 China nine-province survey

Spatial analysis and GIS in the study of COVID-19. A review

Spatial and temporal epidemiological analysis in the big data era

Outcomes of cataract surgery in urban southern China: the Liwan Eye Study

The authors report no conflicts of interest in this work.

Risk Management and Healthcare Policy is an international, peerreviewed, open access journal focusing on all aspects of public health, policy, and preventative measures to promote good health and improve morbidity and mortality in the population. The journal welcomes submitted papers covering original research, basic science, clinical & epidemiological studies, reviews and evaluations, guidelines, expert opinion and commentary, case reports and extended reports. The manuscript management system is completely online and includes a very quick and fair peer-review system, which is all easy to use. Visit http://www.dovepress.com/testimonials.php to read real quotes from published authors.