Cíntya do Nascimento Pereira, T. A. Maranhão, Isaac Gonçalves da Silva, T. L. Silva, G. J. B. Sousa, José Cláudio Garcia Lira Neto, M. L. D. Pereira
{"title":"与自杀相关的时空格局和指标","authors":"Cíntya do Nascimento Pereira, T. A. Maranhão, Isaac Gonçalves da Silva, T. L. Silva, G. J. B. Sousa, José Cláudio Garcia Lira Neto, M. L. D. Pereira","doi":"10.15253/2175-6783.20222370998","DOIUrl":null,"url":null,"abstract":"Objective: to analyze the spatiotemporal pattern and indicators associated with the occurrence of suicide. Methods: ecological study that analyzed the deaths by suicide repor- ted in the Mortality Information System. For temporal and spatial analysis, the Joinpoint and Scan methods were employed, respectively. Multivariate analysis was performed by the Ordinary Least Squares Estimation model, considering p<0.05. Results: significant growth in suicide mortality of 4.2% per year was observed. The highest Bayesian mortality rates ranged from 8.90 to 13.49 deaths per 100,000 population. Five statistically significant spatial clusters were identified (p<0.050). The primary cluster encompassed 64 municipalities, with a suicide risk 1.38 times higher (p<0.001). The indicators associated with suicide were Urbanization rate (β=0.07; p=0.020) and Employment & income (β=-9.40; p=0.030). Conclusion: there was a significant increase in suicide, and five spatial clusters were identified. The indicators Urbanization rate and Employment & income were associated with the grievance.","PeriodicalId":45440,"journal":{"name":"Rev Rene","volume":"63 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2022-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatiotemporal pattern and indicators associated with suicide\",\"authors\":\"Cíntya do Nascimento Pereira, T. A. Maranhão, Isaac Gonçalves da Silva, T. L. Silva, G. J. B. Sousa, José Cláudio Garcia Lira Neto, M. L. D. Pereira\",\"doi\":\"10.15253/2175-6783.20222370998\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Objective: to analyze the spatiotemporal pattern and indicators associated with the occurrence of suicide. Methods: ecological study that analyzed the deaths by suicide repor- ted in the Mortality Information System. For temporal and spatial analysis, the Joinpoint and Scan methods were employed, respectively. Multivariate analysis was performed by the Ordinary Least Squares Estimation model, considering p<0.05. Results: significant growth in suicide mortality of 4.2% per year was observed. The highest Bayesian mortality rates ranged from 8.90 to 13.49 deaths per 100,000 population. Five statistically significant spatial clusters were identified (p<0.050). The primary cluster encompassed 64 municipalities, with a suicide risk 1.38 times higher (p<0.001). The indicators associated with suicide were Urbanization rate (β=0.07; p=0.020) and Employment & income (β=-9.40; p=0.030). Conclusion: there was a significant increase in suicide, and five spatial clusters were identified. The indicators Urbanization rate and Employment & income were associated with the grievance.\",\"PeriodicalId\":45440,\"journal\":{\"name\":\"Rev Rene\",\"volume\":\"63 1\",\"pages\":\"\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2022-01-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Rev Rene\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15253/2175-6783.20222370998\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"NURSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Rev Rene","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15253/2175-6783.20222370998","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"NURSING","Score":null,"Total":0}
Spatiotemporal pattern and indicators associated with suicide
Objective: to analyze the spatiotemporal pattern and indicators associated with the occurrence of suicide. Methods: ecological study that analyzed the deaths by suicide repor- ted in the Mortality Information System. For temporal and spatial analysis, the Joinpoint and Scan methods were employed, respectively. Multivariate analysis was performed by the Ordinary Least Squares Estimation model, considering p<0.05. Results: significant growth in suicide mortality of 4.2% per year was observed. The highest Bayesian mortality rates ranged from 8.90 to 13.49 deaths per 100,000 population. Five statistically significant spatial clusters were identified (p<0.050). The primary cluster encompassed 64 municipalities, with a suicide risk 1.38 times higher (p<0.001). The indicators associated with suicide were Urbanization rate (β=0.07; p=0.020) and Employment & income (β=-9.40; p=0.030). Conclusion: there was a significant increase in suicide, and five spatial clusters were identified. The indicators Urbanization rate and Employment & income were associated with the grievance.