{"title":"2006-2020年广州气象影响因素与OIDD发病特征的相关性分析","authors":"Guqian Pang, Xiaowei Ma, Jingbo Li, Jianyu Lai, Jian He, Juanhuai Wang, Xiaokun Guo, Zhoubin Zhang","doi":"10.1155/2024/9777693","DOIUrl":null,"url":null,"abstract":"<div>\n <p><i>Objectives</i>. This study is to analyze the epidemiological characteristics of other infectious diarrhea diseases (OIDDs) reported in Guangzhou in the past 15 years and the meteorological data of the city in the same period, to explore the correlation between meteorological factors and the incidence. <i>Methodology</i>. This study starts with using quartiles to test the normal distribution of case data. This study has selected five meteorological factors with the highest correlation coefficients and case data from 2006 to 2018 were used to establish a multiple linear regression equation, and the regression equation was tested with case data from 2019 to 2020. <i>Results</i>. Regression modeling based on the statistics for OIDDs during 2006 to 2018 obtained a correlation coefficient R (multiple R) value of about 0.50. The R square value, also known as the coefficient of determination or goodness of fit, was about 0.25. The adjusted R square value was about 0.25. The overall significance test value (significance F) in the regression equation was much lower than the F statistic, thereby indicating that the dependent variable and independent variable were significant. <i>Conclusion</i>. The results indicated that factors other than meteorological or social factors should be considered to understand the outbreak of OIDDs in Guangzhou.</p>\n </div>","PeriodicalId":48195,"journal":{"name":"Health & Social Care in the Community","volume":"2024 1","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/9777693","citationCount":"0","resultStr":"{\"title\":\"Correlation Analysis between Meteorological Influencing Factors and Incidence Features of OIDDs in Guangzhou from 2006 to 2020\",\"authors\":\"Guqian Pang, Xiaowei Ma, Jingbo Li, Jianyu Lai, Jian He, Juanhuai Wang, Xiaokun Guo, Zhoubin Zhang\",\"doi\":\"10.1155/2024/9777693\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n <p><i>Objectives</i>. This study is to analyze the epidemiological characteristics of other infectious diarrhea diseases (OIDDs) reported in Guangzhou in the past 15 years and the meteorological data of the city in the same period, to explore the correlation between meteorological factors and the incidence. <i>Methodology</i>. This study starts with using quartiles to test the normal distribution of case data. This study has selected five meteorological factors with the highest correlation coefficients and case data from 2006 to 2018 were used to establish a multiple linear regression equation, and the regression equation was tested with case data from 2019 to 2020. <i>Results</i>. Regression modeling based on the statistics for OIDDs during 2006 to 2018 obtained a correlation coefficient R (multiple R) value of about 0.50. The R square value, also known as the coefficient of determination or goodness of fit, was about 0.25. The adjusted R square value was about 0.25. The overall significance test value (significance F) in the regression equation was much lower than the F statistic, thereby indicating that the dependent variable and independent variable were significant. <i>Conclusion</i>. The results indicated that factors other than meteorological or social factors should be considered to understand the outbreak of OIDDs in Guangzhou.</p>\\n </div>\",\"PeriodicalId\":48195,\"journal\":{\"name\":\"Health & Social Care in the Community\",\"volume\":\"2024 1\",\"pages\":\"\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-10-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/9777693\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Health & Social Care in the Community\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1155/2024/9777693\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health & Social Care in the Community","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/2024/9777693","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Correlation Analysis between Meteorological Influencing Factors and Incidence Features of OIDDs in Guangzhou from 2006 to 2020
Objectives. This study is to analyze the epidemiological characteristics of other infectious diarrhea diseases (OIDDs) reported in Guangzhou in the past 15 years and the meteorological data of the city in the same period, to explore the correlation between meteorological factors and the incidence. Methodology. This study starts with using quartiles to test the normal distribution of case data. This study has selected five meteorological factors with the highest correlation coefficients and case data from 2006 to 2018 were used to establish a multiple linear regression equation, and the regression equation was tested with case data from 2019 to 2020. Results. Regression modeling based on the statistics for OIDDs during 2006 to 2018 obtained a correlation coefficient R (multiple R) value of about 0.50. The R square value, also known as the coefficient of determination or goodness of fit, was about 0.25. The adjusted R square value was about 0.25. The overall significance test value (significance F) in the regression equation was much lower than the F statistic, thereby indicating that the dependent variable and independent variable were significant. Conclusion. The results indicated that factors other than meteorological or social factors should be considered to understand the outbreak of OIDDs in Guangzhou.
期刊介绍:
Health and Social Care in the community is an essential journal for anyone involved in nursing, social work, physiotherapy, occupational therapy, general practice, health psychology, health economy, primary health care and the promotion of health. It is an international peer-reviewed journal supporting interdisciplinary collaboration on policy and practice within health and social care in the community. The journal publishes: - Original research papers in all areas of health and social care - Topical health and social care review articles - Policy and practice evaluations - Book reviews - Special issues