中华疾病控制杂志

Establish a health index research and application system with Chinese characteristics

LI Shi-xue

2022, 26(10): 1117-1117. doi: 10.16462/j.cnki.zhjbkz.2022.10.001

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Concept and theoretical model of health index

CHI Wei-wei

2022, 26(10): 1118-1123. doi: 10.16462/j.cnki.zhjbkz.2022.10.002

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Objective To establish the theoretical model and paradigm of the health index, construct a theoretical and methodological system of health index, and provide a general and universal theoretical basis for construction of the health index. Methods To address the bottlenecks in construction of health index, the theoretical model and paradigm of health index were created under the guidance of the health determinants model, social ecological model, planetary health model, population health model, and one health model. Results The generalized health index model (GHIM), which integrated the real world social ecological model and the virtual world social ecological model, was constructed. Based on GHIM, a health index theoretical paradigm was developed, which included a "generalized health determinants domain, health index domain, goal-oriented domain, and technical process stack". Conclusion The theoretical model and paradigm of health index created in this model provides a general and universal theoretical model and paradigm for constructing a health index for different domain or tier.

The theoretical model of big data eco-epidemiology

XUE Fu-zhong

2022, 26(10): 1124-1128. doi: 10.16462/j.cnki.zhjbkz.2022.10.003

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Under the background of today's big data and artificial intelligence era, eco-epidemiology has entered a stage of rapid development and application, but also faces many bottlenecks in the development of theoretical paradigms, design strategies and statistical methods. It is necessary to put forward new theoretical paradigms, new design strategies and new statistical methods of eco-epidemiology that suitable for the era of digital intelligence. To this end, this paper creates a big data eco-epidemiology model of the interactive game of health determinants in many mosaic levels in the "real world" and "virtual world" that are both relatively independent and interdependent; a new etiological model of eco-epidemiology in which the genome-centric multi-omics factors, the health determinants of the real world and the virtual world interact with epigenetics as an intermediary; and under the same digital health model, digital transformation of the eco-epidemiology paradigm could be realized using two enabling keys consisted of the "one health" and "digital health", the three perspectives of the integration of "individual-population-ecosystem", and the interactive game among the five dimensions of "citizen participation, education, environment, human-animal health care and digital health", in which digital technology is the catalyst and initiator of this digital transformation. This new theoretical paradigm of eco-epidemiology and its new systematic scientific methods for design and analysis (system dynamics model, network analysis and network dynamics model, multi-agent system model, and causal inference hypergraph model) together constitute the theoretical and methodological system of big data eco-epidemiology.

Interpretation of the theoretical model of big data eco-epidemiology

XUE Fu-zhong

2022, 26(10): 1129-1136. doi: 10.16462/j.cnki.zhjbkz.2022.10.004

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Nowadays, digital technology has become a new type of health determinant, which not only changes society, economy, city and family, but also affects human health; human beings have entered a new digital virtual world. Therefore, in the theoretical paradigm of big data eco-epidemiology, the real world eco-epidemiological model and the virtual world eco-epidemiological model form a relatively independent community with mutual game interaction, both of which are mediated by epigenetics, and they play games and depend on each other among the genome-centric multi-omics factors, health determinants of real world and virtual world; thus, a new etiological framework of eco-epidemiology with interactive games of health determinants in many mosaic levels is formed. The two eco-epidemiological models of the real world and the virtual world play a role through the one health model with digital technology as a "double-edged sword".

Logical framework for health index

WANG Qing, ZONG Jing-ru, LIU Qing

2022, 26(10): 1137-1141. doi: 10.16462/j.cnki.zhjbkz.2022.10.005

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This study aims to construct a logical framework for health index to promote advance through assessment in the context of big data. Guided by the principles of goal-orientation and problem-orientation, the definition of the studied health index, including its connotation and denotation, is identified to provide basis for the construction of health index. Afterwards, in order to meet key targets, following the "input-process-outcome-impact" logic, health-related influencing factors, as well as the interaction between indicators are sorted out to form the logical framework of studied health index. The logical framework of health index is a useful tool to abstract complex health problems, and reflect the essential characteristics of the problems, which provides a guide to quantify health index, and design intervention measures.

Study on Multicenter Data Base for Health Index

JIANG Wei, QIN Kai-shi, JI Xiao-kang, DENG Xiao-ning, LIU Qing, HAN Jing, XUE Fu-zhong, CHI Wei-wei

2022, 26(10): 1142-1145. doi: 10.16462/j.cnki.zhjbkz.2022.10.006

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Objective By building Multicenter Data Base for Health Index, to realize data aggregation, thematic connection of data lake, high availability of data services, and to support health index applications. Methods It could support data governance, data management and data service applications by building multicenter data base and standardizing data processing processes, such as data preprocessing, standardization, labeling, theme, knowledge mapping, and other data processing processes. Results The quantity and quality of data have been significantly increased to achieve data resources visible, useful and manageable. Conclusions The establishment of multicenter data base for health index provides ideas for the development and utilization of healthy big data in the future.

Construction method of health index

CHI Wei-wei

2022, 26(10): 1146-1151. doi: 10.16462/j.cnki.zhjbkz.2022.10.007

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At present, there are bottlenecks in the construction of health index. On one hand, there is a lack of a general and universal theoretical model or paradigm for constructing a health index, on the other hand, a full-stack technical process of health index is lacking. Therefore it is difficult to realize large-scale, authoritative and timely release and transformation and application of health index. In this paper, under the guidance of the universal conceptual model and theoretical paradigm of health index constructed in the previous paper, a full-stack technical process of health index is developed which runs through the "Data Platform → Data Collection → Health Measurement → Theoretical Models → Evidence-based Indicators → Indicator System → Weighted Integration →Index Visualization → Index Publishing → Transformation Service", to realize large-scale, authoritative and timely release as well as transformation and application of health index.

The research design and statistical analysis strategy of eco-epidemiology

XUE Fu-zhong

2022, 26(10): 1152-1160. doi: 10.16462/j.cnki.zhjbkz.2022.10.008

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The theoretical paradigm of big data eco-epidemiology illustrates a more comprehensive perspective of eco-epidemiology, acknowledging and capturing the complex network characteristics of hierarchical mosaic and interactive games of many health determinants in the real and virtual worlds. Under the complex background of mosaic layered interaction and network-game, the traditional epidemiological sampling methods based on independent random assumptions, traditional analytical and experimental epidemiological design strategies and statistical analysis methods, all face huge challenges. Furthermore, they could be replaced by system dynamics models, network analysis and network dynamics models, multi-agent system models, and causal inference hypergraph models that need to be developed in the future. Thus, a new theoretical paradigm, new design strategy and new statistical method constitute a theoretical method system of big data eco-epidemiology.

Statistical analysis process of health index construction and its implementation

SHI Jie, TIAN Xiang, WANG Ya-qian, LU Wei, WANG Han, WANG Yue, CHI Wei-wei

2022, 26(10): 1161-1166. doi: 10.16462/j.cnki.zhjbkz.2022.10.009

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Objective Based on the comprehensive evaluation theory, this paper explores and summarizes the statistical analysis process of health index construction, and develops relevant R packages for software implementation. In this way, a set of fast and efficient evaluation tools for health index research can be further developed, and a highly integrated comprehensive index and evaluation results can be generated with one click. We hope to provide scientific and reliable evaluation information and a decision-making basis for regulatory authorities. Methods R 4.1.3 software was used to develop the EvaModels package. Combined with the statistical analysis process of health index construction, this paper introduced and explained the functions of the EvaModels package as a whole. Moreover, we analyzed and compared the applicable scenarios of various methods, and takes the construction of a sustainable development index of public hospitals as an example for demonstration and analysis. Results Health index construction included four processes. Namely, determining the research theme of the index, constructing an evaluation indicator system, multi-indicator comprehensive evaluation, and visualization of evaluation results. The developed EvaModels package has nine built-in functions to realize the functions of indicator screening, data standardization, index weighting and comprehensive evaluation through a variety of methods. Also, it can meet the analysis needs of a variety of evaluation problems and cover the statistical analysis process of health index construction. Conclusion The EvaModels package automates and simplifies the workflow involved in statistical analysis in health index construction through a set of functions. With procedures and codes that are easy to interpret and call, it can improve the convenience and operability of health index construction.

Data collection and edge calculation of green vegetation index based on ecological health

JIA Xian-jie, LIU Chao, JI Xiao-kang, XUE Fu-zhong

2022, 26(10): 1167-1173. doi: 10.16462/j.cnki.zhjbkz.2022.10.010

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Objective In the era of big data about health care, faster and more accurate access to environmental green space exposure level data help scholars to research on green vegetation exposure and health. Methods We use Python to design a technical process and procedure to automate the collection of green vegetation index. and also exploreand prospect the application of edge computing in green vegetation index collection based on the national health care big data platform. Results The operation of the program greatly reduced the processing time of the vegetation indices and provides a high degree of consistency in comparison with the results obtained by traditional professional software. Conclusion Automated collection of green vegetation indices based on edge computing can provide technical support for domestic research on green vegetation exposure and health.

Advance in distributed evidence-based causal inference methods

LI Hong-kai, XU Dong-hai, LIU Qing, JI Xiao-kang, XUE Fu-zhong

2022, 26(10): 1174-1179. doi: 10.16462/j.cnki.zhjbkz.2022.10.011

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It has become increasingly popular to integrate data from multiple heterogeneous sources in order to achieve larger sample sizes and diverse study populations. This paper reviews the development of causal reasoning methods to integrate databases of different designs in different populations. Additionally, this article also reviews the progress of randomized clinical trials combined with external information, as well as observational studies and historical controls. For a single sample lacking all relevant confounding variables, Mendelian randomization can be applied to two samples data integration. This distributed data design features the effectiveness and security of real-world data research.

Causal inference methodology for the screening of indicators for health indices

LIU Xin-hui, LI Hong-kai, WANG Li-jie, LIU Ai-ling, QI Yue, SUN Shan-shan, ZHANG Lan-fang, JI Huai-jun, LIU Gui-yuan, ZHAO Huan, JIANG Yi-nan, LI Jing-yi, SONG Cheng-cun, YU Xin, YANG Liu, YU Jin-chao, FENG Hu, YANG Fu-jun, XUE Fu-zhong

2022, 26(10): 1180-1186. doi: 10.16462/j.cnki.zhjbkz.2022.10.012

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The construction and development of the health index system have important strategic significance for promoting the realization of the Healthy China initiative. Starting from the real-world data, it is essential to screen indicators for health indices that are definite causes of diseases and can be prevented through a series of causal inference methods. This can provide valuable real-world evidence that is closer to the practice of health/disease management. According to the need for evidence-based medicine for health index construction, this paper introduces population-level causal effect estimation methods that are widely used in real-world studies, aiming at providing methodological support for the screen of indicators for health index.

Developments of federated learning in multi-centric genetic health index construction

ZHAO Yan-yan, WANG Jin-lan, WANG Xiao-xia, XUE Fu-zhong

2022, 26(10): 1187-1191. doi: 10.16462/j.cnki.zhjbkz.2022.10.013

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Individual health index is an important component of health index construction. Moreover, the genetic factor is an important factor in the assessment of individual health. It is well known that complex diseases do not follow Mendelian inheritance laws and are influenced by multiple genetic loci with small effect sizes. The polygenic risk score (PRS) is an individual genetic evaluation score that has been widely used in recent years. It can integrate disease-related genetic loci to achieve risk prediction and precision prevention of complex diseases. However, the ethnic imbalance can hinder the generalizability of PRS. Integrating data from multiple centers can effectively increase the sample size of different ancestries and reduce the imbalance, which is an important method to mitigate health disparity. With the increasing awareness of data privacy, security and ownership, leveraging the data and computing resources in a privacy-preserving manner have gained accumulated appreciation. The uniqueness of genomic data makes the privacy-preserving of individual data extremely important. This article will discuss privacy-preserving methods in multicenter genomic data analysis, including homomorphic encryption, secure multi-party computation, meta-analysis, federated learning, and the combination between homomorphic encryption and federated learning. We will also discuss the statistical methods of multi-center PRS construction under the framework of federated learning.

Healthy China initiative index and its applications: evidence from Shandong Province

ZONG Jing-ru, SUN Han-chen, TAN Hui, WANG Qing, CHI Wei-wei

2022, 26(10): 1192-1198. doi: 10.16462/j.cnki.zhjbkz.2022.10.014

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Objective This study aims to propose a comprehensive evaluation index system for Healthy China initiative based on 15 special campaigns. Using this index system, the study evaluated the progress of the initiative, and then identified the shortcomings, as well as put forward improvement strategies for 16 cities of Shandong Province. Methods Integrating "the Assessment implementation plan for Healthy China initiative Plan from 2021 to 2022" with multiple experts' views, indicators were identified according to indicators importance, indicators representativeness, and data availability. Technique for order preference by similarity to an ideal solution (TOPSIS) method was applied to evaluate the Healthy China initiative, and dashboard analysis was used to identify the shortcomings of each city. Results Three dimensions, including prevention and control of health risk factors, health service provision, and health outcomes, were identified. Comparing the Healthy China initiative 2030 targets and the maximum value of each indicator in 16 cities, Shandong province, when the relatively large value was taken as the ideal solution of TOPSIS, the mean value of the Healthy China initiative index in Shandong province was 0.558 in 2020. Qingdao was ranked the highest (0.696), and Heze the lowest (0.386). The coefficient of variation for dimension of prevention and control of health risk factors was the highest (0.226), the coefficient for dimension of health outcomes was the lowest (0.144). Conclusions Sixteen cities in Shandong province have basically achieved the targets required by the Healthy China initiative 2022, but there were significant gaps from the targets required to achieve by 2030. Unbalanced development across cities and dimensions was prominent, and prevention and control of health risk factors should be emphasized.

Construction and application of healthy city index in Shandong Province

ZHU Gao-pei, SUN Han-chen, YUE Zeng-yong, YAN Ran, WANG Su-zhen, WANG Qing

2022, 26(10): 1199-1204. doi: 10.16462/j.cnki.zhjbkz.2022.10.015

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Objective To construct the healthy city index with Shandong characteristics, and to realize the sustainable development of a healthy city. Methods In accordance with the Shandong multi-center health big data and multi-source socio-economic development data, the determinants and indicators of cities were screened evidence-based. Based on the conceptual framework of "driving-force-pressure-state-exposure-effect-action" (DPSEEA), we combed the indicators of healthy cities and established the indicator system of healthy cities via confirmatory factor analysis. The entropy weight-TOPSIS method was used to calculate the scores of healthy cities of Cities in Shandong Province in 2018. Results Finally, 6 dimensions and 30 indicators were determined based on health care big data and evidence-based and confirmatory factor analysis. The results of entropy weight-TOPSIS showed that the weight of health services (0.305) was the largest, and the weight of the healthy population (0.037) was the smallest. The analysis of the healthy city index in Shandong Province showed that the level of healthy cities in Shandong Province was far lower than that of standard cities, but the difference within Shandong Province was not obvious. Conclusion The DPSEEA combined with an evidence-based could be used to guide the construction of a healthy city index system.

Construction and application of comprehensive evaluation index of "Internet+ Medical Health" in Shandong Province

QU Xiang, LI Juan-juan, MA Gui-feng, JING Qi, ZHANG Jian-hua, ZHENG Wen-gui, WANG Pei-cheng, LIN Yue-tong, LIU Yan, YANG Li-jun, ZHU Gao-pei, WANG Chun-ping

2022, 26(10): 1205-1209. doi: 10.16462/j.cnki.zhjbkz.2022.10.016

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Objective To evaluate the present situation of Shandong in the construction of the "Internet + Medical Health" demonstration province, to analyze the shortcomings in the development of each city, and to provide a scientific basis for the improvement of its construction level. Methods Grounding on the "General Office of the People's Government of Shandong Province on the issuance of the Shandong Province Action Plan for the Construction of "Internet + Medical Health" Demonstration Province (2019-2020)" (hereinafter referred to as "Action Plan") and the "Structure-Process-Results" model, we developed the "Internet + Medical Health" evaluation index system. The present situation of "Internet + Medical Health" construction in 16 Cities of Shandong Province was evaluated and compared through the entropy weight-TOPSIS method and comprehensive index method. Results The status quo of "Internet + Medical Health" in 16 Cities of Shandong Province is good, and significant differences were found among Cities. The average comprehensive evaluation index of municipal units was 0.545, of which the city with the best development status was H City, with an assessment index of 0.791, and the lowest was City I, whose evaluation index was 0.167. The average comprehensive evaluation index of medical institutions in various cities was 0.662, of which the best-developed city was H City, with an assessment index of 0.977, and the lowest city with an assessment index of 0.123 was City I. Conclusions The "Internet + Medical Health" evaluation index established by the "Structure-Process-Results" model combined with the entropy weight-TOPSIS method can objectively and comprehensively evaluate the development of "Internet + medical health". Our results provide the scientific basis for the construction of the "Internet + Medical Health" model province in Shandong Province.

Current status of cardiovascular health and its inprovement evaluation in Shangdong Province

ZHANG Bing-yin, LIU Dan-ru, CHU Jie, LU Zi-long, XU Xiao-hui, LIU Cai-rui, GUO Xiao-lei, MA Ji-xiang

2022, 26(10): 1210-1216. doi: 10.16462/j.cnki.zhjbkz.2022.10.017

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Objective To understand the current status and improvement of cardiovascular health in Shandong Province, and to provide basis for government departments to formulate prevention and control strategies for cardiovascular diseases. Methods The system of cardiovascular health index (CHI) in Shandong Province was constructed, which contained 52 indicators in five dimensions. The indicators were homogenized, standardized, differentiated, and weighted summation, and the weighted total score was calculated. A higher score indicated a better performance. Results Regarding the CHI total score, Weihai city was the highest (78.21), while Liaocheng city was the lowest (30.96). Weihai, Qingdao, Dongying, Jinan and Yantai ranked the top five cities, where local cardiovascular health status was relatively well. Liaocheng, Heze, Dezhou, Zaozhuang, and Binzhou ranked the last five cities, where local cardiovascular health status was relatively inferior. For the single dimension, there were also relatively weak aspects of the cities with high CHI. For example, Jinan ranked the 11th in the D dimension in terms of the treatment of cardiovascular diseases, which was at the lower level in this province. For the score ranking of the 52 indicators, all cities had specific aspects that need to be improved. For instance, the premature death rate of coronary heart disease (A03, 9th), prevalence rate of obesity (B06, 13th), diabetes (B09, 10th), and dyslipidemia (B10, 14th), detection rate of blood pressure (C01, 12th), control rate of diabetes (C08, 12th), number of cardiovascular neurologists (D01, 11th), number of cardiac catheter room (D02, 16th), use of risk factor intervention drugs (E04, 15th), and number of disease control personnel (E07, 12th) of Qingdao ranked relatively lower. The total scores of Weihai, Yantai, Rizhao, Jining, Linyi and Heze had increased to varying degrees compared with those in 2018, while the ranking of other cities had decreased or remained unchanged. Conclusions The cardiovascular health status of different cities in Shandong Province is not the same. The status in eastern and central cities are better than that of the northwestern and southwestern cities in Shandong Province, and there is room for improvement in every dimension and index of cardiovascular disease prevention and control in each city.

Effectiveness analysis of global health security index (GHSI) assessment

HU An-qi, WANG Ding, SHI Jie, LIU Chao, SU Ping, TIAN Lei-lei, CHI Wei-wei

2022, 26(10): 1217-1223. doi: 10.16462/j.cnki.zhjbkz.2022.10.018

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Objective To investigate the correlation between Global Health Security Index (GHSI) and the epidemic situation of COVID-19 and to explore the value of GHSI. Methods A cross-sectional study of 159 countries from an open database was conducted. Analyze the correlation of GHSI with the COVID-19 pandemic with Spearman and plot the correlation matrix. Fitted multiple linear regression models controlled for variables such as socioeconomic and health conditions in countries, and further studied the association of GHSI with COVID-19 pandemic outcome indicators. Results The mean total GHSI score of the 159 countries in 2021 was (41.19±13.41), with a minimum of 16.10 (Yemen) and a maximum of 75.90 (The United States). As of 31 December 2021, the crude case fatality rate of COVID-19 in 159 countries was 0.02 (0.01, 0.03), with a minimum < 0.01 (Bhutan) and a maximum of 0.20 (Yemen). The total number of confirmed cases per million population was 50 844.42 (5 807.88, 101 572.70), with a minimum of 22.26 (Republic of Vanuatu) and a maximum of 251 608.38 (Slovakia). The total number of deaths per million population was 590.71 (105.66, 1 533.20), with a minimum of 3.10 (Burundi) and a maximum of 6 075.95 (Peru). Multiple linear regression analysis results showed that the Detect score of GHSI was negatively correlated with the total confirmed cases per million population (β=-0.34, P=0.038) and the total deaths per million population (β=-0.42, P0.025); the Norms score of GHSI was negatively correlated with the total confirmed cases per million population (β=-0.49, P0.041), and the Health score of GHSI was positively correlated with the total deaths per million population (β=0.65, P0.003). Risk score of GHSI was inversely correlated with case fatality rate(β=-0.91, P0.044). Conclusion The GHS Index has limited value in assessing a country's capacity to respond to the COVID-19 pandemic. Nevertheless, it has potential value in others.

Construction method of genetic risk score and its application in diabetes risk assessment

CHEN Xiao-lu, ZHU Yong-bao, SI Shu-cheng, WANG Hong, GAO Zhong-chun, JI Xiao-kang, XUE Fu-zhong

2022, 26(10): 1224-1228, 1234. doi: 10.16462/j.cnki.zhjbkz.2022.10.019

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Objective To construct genetic risk scores (GRS), and to provide a powerful tool for the construction of health index. Methods Using the UK Biobank (UKB), taking type 2 diabetes (T2D) as an example, the classical clump and threshold method (C+T), LDpred and DBSLMM method were used to construct GRS of T2D, and the predictive ability of GRS constructed by these three methods for T2D incidence were evaluated. Results A total of 271 282 people were included in the cohort, of which 6 047 developed T2D. The areas under the curve (AUC) (95% CI) of the three methods were 0.699 (0.692-0.705), 0.747 (0.741-0.753) and 0.745 (0.739-0.751), respectively. Compared with the C+T method, the AUC of the latter two methods increased by 4.8% and 4.6%, respectively. Differences were statistically significant (P < 0.001). Taking the low-genetic risk group as the reference, the HR (95% CI) of the high-risk group with the three methods were 2.42 (2.26-2.59), 4.43 (4.11-4.77), and 4.49 (4.16-4.84), respectively. Conclusion The GRS obtained by the DBSLMM has a good predictive ability for the risk of T2D, which provides a methodological support for the construction of genetic components of other disease health indexes.

Association between exposure to air pollution and the risk of hypertension: a cohort study based on UK Biobank

FU Ping, LI Ji-qing, SI Shu-cheng, ZHANG Kai, LIU Xiao-wen, JI Xiao-kang, XUE Fu-zhong

2022, 26(10): 1229-1234. doi: 10.16462/j.cnki.zhjbkz.2022.10.020

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Objective To study the relationship between air pollutants, such as NO₂, NO_x, PM₁₀, PM_2.5 and PM_2.5-10, and the risk of hypertension, and to provide a reference for the prevention of hypertension. Methods We constructed follow-up cohorts on the basis of UK Biobank (UKB) and used Cox proportional-hazards regression models for association analyses. We separately studied the associations of annual mean concentrations of air pollutants and cumulative daily exposures to air pollutants with the risk of hypertension. In addition, a cumulative exposure weighted score for air pollutants was created to assess the association between combined exposure to several air pollutants and the risk of hypertension. Results Cox proportional risk model results showed that only the annual mean concentration of NO_x increased the risk of hypertension when using the annual mean concentration of air pollutants as exposure. The HRs (95% CI) of hypertension for a 50 μg/m³·day increase in daily cumulative exposure to NO₂, NO_x, PM₁₀, PM_2.5 and PM_2.5-10 were 1.06 (1.04-1.08), 1.03 (1.02-1.04), 1.11 (1.07-1.14), 1.18 (1.12-1.24) and 1.26 (1.17-1.37), respectively. There was a positive dose-response relationship between the cumulative exposure weighted score of air pollutants and the risk of hypertension (P < 0.001). Conclusions Our findings suggest that long-term exposure to various air pollutants including PM_2.5, PM₁₀, PM_2.5-10, NO₂ and NO_x, either individually or jointly, were associated with an increased risk of hypertension significantly. Our study highlights the importance of a comprehensive assessment of various air pollutants in hypertension prevention.

Association study between vegetation cover and prognostic survival of acute coronary heart disease

WANG Ya-qian, CHANG Kai-feng, JIA Xian-jie, SHI Jie, LU Wei, ZHAO Yi-jun, HAN Li-ying, CHI Wei-wei

2022, 26(10): 1235-1240. doi: 10.16462/j.cnki.zhjbkz.2022.10.021

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Objective The aim was to study the association between vegetation cover and prognostic survival of acute coronary heart disease, and to explore whether air pollutants (PM_2.5, O₃) mediated this association. Methods Surveillance data of all acute coronary heart disease patients in Pingyi County from 2014 to 2020 were collected, and a case-control study design was adopted (the case group was the short-term survival group, the control group was the long-term survival group), and the normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI) were used as vegetation cover exposure measurements. Four logistic regression models were constructed to explore the association between vegetation cover and prognostic survival of acute coronary heart disease, followed by subgroup analysis and mediation analysis to evaluate the potential mediating effect of air pollutants on this association. Results Finally, a total of 1 796 patients with acute coronary heart disease were included. Logistic regression results showed that vegetation cover indicators (NDVI, SAVI) were significantly associated with prognostic survival in patients with acute coronary heart disease (P < 0.05). Subgroup analysis showed that the interaction between PM_2.5 and vegetation cover was statistically significant (all P < 0.05). When the concentration of PM_2.5 was low, the correlation between vegetation cover and prognostic long-term survival of patients with acute coronary heart disease was stronger. The mediation analysis showed that PM_2.5 as a mediator significantly mediated this association (all P < 0.05), and the proportion of NDVI and SAVI mediated was 37.0% and 30.7% respectively, while the mediation effect of O₃ was not significant. Conclusion Vegetation cover was protective for the prognostic long-term survival of patients with acute coronary heart disease, and PM_2.5 significantly mediated this association.

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2022 Vol. 26, No. 10

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Editor-in-Chief Ye Dongqing M.D.

Assistant editor Fan Yinguang M.D.

Assistant editor Pan Haifeng M.D.

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