Shaly Wanda Hamzah, Muhammad Nur Aidi, I Made Sumertajaya, Fitrah Ernawati
{"title":"Risk Factors for Anaemia, Iron Deficiency, and Iron Deficiency Anaemia in Women of Reproductive Age Using Logistic Regression","authors":"Shaly Wanda Hamzah, Muhammad Nur Aidi, I Made Sumertajaya, Fitrah Ernawati","doi":"10.32628/ijsrset2411260","DOIUrl":null,"url":null,"abstract":"Women of reproductive age (WRA) are vulnerable to anaemia, iron deficiency (ID), or iron deficiency anaemia (IDA). To identify the factors influencing anaemia, ID, and IDA to WRA in Indonesia, logistic regression analysis was employed. This study aims to determine the prevalence of anaemia, ID, and AID among WRA, as well as to identify influencing factors and evaluate the classification results produced by Logistic Regression methods. The data used were obtained from the Research and Development Agency, Ministry of Health of Indonesia. Haemoglobin data, demographic, and socioeconomic data were derived from the Basic Health Research 2013, and ferritin (Fe) and CRP data used stored serum samples collected in 2013 and analyzed in 2016. The results of this study found that the prevalence of anaemia among WRA in Indonesia is 11%, ID 14%, and AID 9%. Significant factors influencing health conditions include BMI, marital status, family size, malaria, and ARI. Individuals with overweight or obesity have a lower chance of experiencing anaemia, ID, and IDA compared to those who are thin, while individuals who are divorced have a higher risk than those who are unmarried. Additionally, individuals affected by malaria or ARI also have a higher risk of experiencing anaemia. Consumption of animal protein and education also emerges as significant factors affecting ID conditions. Although the model using Multinomial Logistic Regression shows higher accuracy than the binary model, both still have weaknesses in identifying cases of anaemia, ID, and IDA with low sensitivity. Model evaluation indicates that despite proficiency in recognizing normal cases, they still struggle to detect cases of anaemia, ID, and IDA.","PeriodicalId":14228,"journal":{"name":"International Journal of Scientific Research in Science, Engineering and Technology","volume":"25 10","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Scientific Research in Science, Engineering and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32628/ijsrset2411260","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Women of reproductive age (WRA) are vulnerable to anaemia, iron deficiency (ID), or iron deficiency anaemia (IDA). To identify the factors influencing anaemia, ID, and IDA to WRA in Indonesia, logistic regression analysis was employed. This study aims to determine the prevalence of anaemia, ID, and AID among WRA, as well as to identify influencing factors and evaluate the classification results produced by Logistic Regression methods. The data used were obtained from the Research and Development Agency, Ministry of Health of Indonesia. Haemoglobin data, demographic, and socioeconomic data were derived from the Basic Health Research 2013, and ferritin (Fe) and CRP data used stored serum samples collected in 2013 and analyzed in 2016. The results of this study found that the prevalence of anaemia among WRA in Indonesia is 11%, ID 14%, and AID 9%. Significant factors influencing health conditions include BMI, marital status, family size, malaria, and ARI. Individuals with overweight or obesity have a lower chance of experiencing anaemia, ID, and IDA compared to those who are thin, while individuals who are divorced have a higher risk than those who are unmarried. Additionally, individuals affected by malaria or ARI also have a higher risk of experiencing anaemia. Consumption of animal protein and education also emerges as significant factors affecting ID conditions. Although the model using Multinomial Logistic Regression shows higher accuracy than the binary model, both still have weaknesses in identifying cases of anaemia, ID, and IDA with low sensitivity. Model evaluation indicates that despite proficiency in recognizing normal cases, they still struggle to detect cases of anaemia, ID, and IDA.
育龄妇女(WRA)容易患贫血、缺铁(ID)或缺铁性贫血(IDA)。为了确定影响印度尼西亚育龄妇女贫血、缺铁和缺铁性贫血的因素,我们采用了逻辑回归分析法。本研究旨在确定 WRA 中贫血、缺铁性贫血和缺铁性贫血的患病率,并确定影响因素和评估逻辑回归方法产生的分类结果。所用数据来自印度尼西亚卫生部研究与发展局。血红蛋白数据、人口统计学和社会经济学数据来自《2013年基本健康研究》,铁蛋白(Fe)和CRP数据使用了2013年收集并在2016年分析的储存血清样本。研究结果发现,印尼妇女儿童贫血症患病率为11%,ID为14%,AID为9%。影响健康状况的重要因素包括体重指数、婚姻状况、家庭规模、疟疾和急性呼吸道感染。与瘦弱的人相比,超重或肥胖的人患贫血、ID 和 IDA 的几率较低,而离婚的人比未婚的人风险更高。此外,受疟疾或急性呼吸道感染影响的人患贫血症的风险也较高。动物蛋白摄入量和教育程度也是影响 ID 状况的重要因素。尽管使用多项式逻辑回归的模型比二元模型显示出更高的准确性,但两者在识别贫血、ID 和 IDA 病例方面仍存在弱点,灵敏度较低。模型评估表明,尽管能熟练识别正常病例,但仍难以检测出贫血、ID 和 IDA 病例。