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基于Bayes时空模型分析HIV/AIDS晚发现的时空分布特征及其影响因素OA北大核心CSTPCD

Spatial-temporal Distribution and Influencing Factors of Late Diagnosis of HIV/AIDS Based on Bayes Spatial-temporal Model

中文摘要英文摘要

[目的]旨在分析兰州市HIV/AIDS晚发现的时空聚集性特征及相关影响因素,明确兰州市HIV/AIDS晚发现高风险地区和时间趋势,为兰州市因地制宜地制定HIV/AIDS防治策略措施提供参考依据.[方法]选择兰州市2011-2018年间新报告的成年HIV/AIDS病例作为研究对象,研究中所需的数据资料来自兰州市疾病预防控制中心和兰州市统计年鉴.采用Bayes时空模型分析HIV/AIDS晚发现相对风险(RR)的时空分布特征及其影响因素.[结果]2011-2018年间兰州市新报告的HIV/AIDS病例共计1984例,其中HIV/AIDS晚发现者有982例(49.5%),平均年龄为39.67岁,男性占90.9%.老年人和女性HIV/AIDS病例中晚发现的比例更高;城关区(51.1%)、安宁区(50.3%)和榆中县(51.9%)具有高于平均水平的HIV/AIDS晚发现比例;2011-2018年间兰州市总体的晚发现比例呈波动上升趋势.Bayes时空模型分析结果显示,兰州市HIV/AIDS晚发现风险在2011-2015年间波动变化,而在2015年后迅速上升,其RR(95%CI)从1.01(0.84,1.23)上升到1.11(0.77,1.97);红古区和三个县的晚发现风险变化趋势与兰州市的总体变化趋势相似,而城关区和七里河区的晚发现风险呈下降趋势;晚发现相对风险大于1的区县包括:永登县(RR=1.07,95%CI:0.55,1.96)、西固区(RR=1.04,95%CI:0.67,1.49)、城关区(RR=2.41,95%CI:0.85,6.16)和七里河区(RR=2.03,95%CI:1.10,3.27).冷热点分析结果显示城关区和七里河区为热点区.影响因素分析结果显示,随着人均GDP(RR=0.65,95%CI:0.35,0.90)和HIV/AIDS病例中的男性比例(RR=0.53,95%CI:0.19,0.92)的增高,HIV/AIDS晚发现的相对风险越低;而人口密度(RR=1.35,95%CI:1.01,1.81)越大,晚发现风险越高.[结论]兰州市的HIV/AIDS晚发现风险呈上升趋势,并且存在明显的地区差异特征;人均GDP、HIV/AIDS中男性比例和人口密度是HIV/AIDS晚发现的影响因素.因此,对于晚发现风险高和存在相关风险因素的区县,应重视并制定有针对性的HIV筛查和防治服务,降低HIV/AIDS晚发现比例和风险.

[Objectives]To analyze the spatial and temporal clustering characteristics and related influencing factors of late diagnosis of HIV/AIDS in Lanzhou,to identify its high-risk areas and time trends in Lanzhou,and to provide a theo-retical basis for developing targeted HIV/AIDS prevention and control strategies in Lanzhou.[Methods]The subjects of this study were adult HIV/AIDS cases reported in Lanzhou City between 2011 and 2018.Data used in the study were sourced from the Lanzhou Center for Disease Control and Prevention and the Lanzhou Statistical Yearbook.To analyze the spatial distribution characteristics and influencing factors of the relative risk(RR)of late HIV/AIDS diagnosis,Bayes spatial-temporal model was used.[Results]A total of 1984 new HIV/AIDS cases were reported in Lanzhou from 2011 to 2018,with an mean age of 37.51 years and predominantly male(91.8%).The number of late diagnosis cases was 982,with an mean age of 39.67 years and a predominance of males(91.8%).Late diagnosis was more common in older individuals and women with HIV/AIDS.Chengguan District(51.1%),Anning District(50.3%)and Yuzhong County(51.9%)had an above-average proportion of late diagnosis of HIV/AIDS.The proportion of late diagnosis cases in Lanzhou showed a fluctu-ating upward trend from 2011 to 2018.The results of Bayes spatial-temporal model showed that the risk of late HIV/AIDS diagnosis in Lanzhou had fluctuated from 2011 to 2015,and then increased rapidly after 2015[RR(95%credibility inter-val,95%CI)increased from 1.01(0.84,1.23)to 1.11(0.77,1.97)];the trends of risk of late diagnosis in Honggu dis-trict and three counties were similar to the overall trend in Lanzhou city,while the risk of late diagnosis in Chengguan Dis-trict and Qilihe District showed a decreasing trend.The regions with the RR for late diagnosis greater than 1 included Yong-deng County(RR=1.07,95%CI:0.55,1.96),Xigu District(RR=1.04,95%CI:0.67,1.49),Chengguan District(RR =2.41,95%CI:0.85,6.16),and Qilihe District(RR=2.03,95%CI:1.10,3.27).Besides,the heatmap analysis showed that Chengguan District and Qilihe District were the hot spots.The influencing factors analysis showed that the higher GDP per capita(RR=0.65,95%CI:0.35,0.90)and the larger proportion of males with HIV/AIDS cases(RR= 0.53,95%CI:0.19,0.92)could lead to the lower the relative risk of late HIV/AIDS diagnosis.However,the higher the population density(RR=1.35,95%CI:1.01,1.81)caused the higher the risk of late diagnosis.[Conclusion]Our study shows the risk of late diagnosis of HIV/AIDS in Lanzhou was on the rise,and there are significant regional differences.GDP per capita,the proportion of males in HIV/AIDS cases and population density are influencing factors in the late diag-nosis of HIV/AIDS.Therefore,for regions with a high risk of late diagnosis or related risk factors,targeted HIV screening and prevention services should be given priority in order to reduce the proportion and risk of late diagnosis of HIV/AIDS.

邵莉;陈继军;张宇琦;许静;栗果;高文龙

西藏民族大学医学院,陕西 咸阳 712082兰州市疾病预防控制中心性病艾滋病防制科,甘肃 兰州 730030兰州大学公共卫生学院流行病与卫生统计学系,甘肃 兰州 730000||兰州大学公共卫生学院卫生统计与智能分析研究所,甘肃 兰州 730000

预防医学

艾滋病人类免疫缺陷病毒晚发现Bayes时空模型分布特征

AIDSHIVlate diagnosisBayes spatial-temporal modeldistribution characteristics

《中山大学学报(医学科学版)》 2024 (002)

243-252 / 10

兰州市卫生健康科技发展项目(A2023004;2021018)

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