M. Aidi, Efriwati Efriwati, Santy Suryanty, Laode Abdul Rahman, Khalilah Nurfadilah, Fitrah Ernawati
{"title":"Identifying the Characteristics of Pregnant Women with Inflammation/Infection in Indonesia","authors":"M. Aidi, Efriwati Efriwati, Santy Suryanty, Laode Abdul Rahman, Khalilah Nurfadilah, Fitrah Ernawati","doi":"10.25182/jgp.2022.17.3.177-186","DOIUrl":null,"url":null,"abstract":"Infection in pregnant women is common and one of the highest causes of death in Indonesia. Reducing infection conditions through early infection prevention needs to be done, one of which is by knowing the characteristics that contribute to the incidence of infection in pregnant women in Indonesia. This study used the Classification and Regression Tree (CART) method to determine the pregnant women with infections and not infections characteristics and classify them. The results of the CART analysis found that seven variables contributed to separating infected and not-infected status in pregnant women, they are nutritional status based on Body Mass Index (BMI), history of anemia, pregnancy distance, Chronic Energy Deficiency (CED) status, ages, socioeconomic and gestational age. Characteristics of the highest incidence of infection, namely 79%, occurred in the group of pregnant women with overweight – obese (BMI>25.0), anemia and pregnancy distance <3 years. The classification analysis of the CART method in this study resulted in the accuracy of identification performance which was still not good, with an accuracy value of 52.78%. It is necessary analysis with other classification methods such as the Chi-square Automatic Interaction Detection (CHAID) in the future.","PeriodicalId":41982,"journal":{"name":"Jurnal Gizi dan Pangan","volume":" ","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Gizi dan Pangan","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25182/jgp.2022.17.3.177-186","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"NUTRITION & DIETETICS","Score":null,"Total":0}
引用次数: 0
Abstract
Infection in pregnant women is common and one of the highest causes of death in Indonesia. Reducing infection conditions through early infection prevention needs to be done, one of which is by knowing the characteristics that contribute to the incidence of infection in pregnant women in Indonesia. This study used the Classification and Regression Tree (CART) method to determine the pregnant women with infections and not infections characteristics and classify them. The results of the CART analysis found that seven variables contributed to separating infected and not-infected status in pregnant women, they are nutritional status based on Body Mass Index (BMI), history of anemia, pregnancy distance, Chronic Energy Deficiency (CED) status, ages, socioeconomic and gestational age. Characteristics of the highest incidence of infection, namely 79%, occurred in the group of pregnant women with overweight – obese (BMI>25.0), anemia and pregnancy distance <3 years. The classification analysis of the CART method in this study resulted in the accuracy of identification performance which was still not good, with an accuracy value of 52.78%. It is necessary analysis with other classification methods such as the Chi-square Automatic Interaction Detection (CHAID) in the future.
孕妇感染是常见的,也是印度尼西亚死亡的最高原因之一。需要通过早期感染预防来减少感染情况,其中之一是了解导致印度尼西亚孕妇感染发生率的特征。本研究采用分类回归树(Classification and Regression Tree, CART)方法确定感染和未感染孕妇的特征并进行分类。CART分析结果发现,7个变量有助于区分孕妇感染和未感染状态,它们是基于身体质量指数(BMI)的营养状况、贫血史、妊娠距离、慢性能量缺乏(CED)状态、年龄、社会经济和胎龄。感染发生率最高的特征发生在超重-肥胖(BMI为25.0)、贫血和妊娠距离<3年的孕妇组,为79%。本研究对CART方法进行分类分析,识别性能的准确率仍然不高,准确率值为52.78%。今后有必要与卡方自动交互检测(CHAID)等其他分类方法进行分析。