Analysis of influencing factors in chronic kidney disease incidence in Indonesia

Meilinah Hidayat, Fabiola Motulo, Santoso Chandra, Stephanie Andamari, J. Sulungbudi, Ronny Lesmana
{"title":"Analysis of influencing factors in chronic kidney disease incidence in Indonesia","authors":"Meilinah Hidayat, Fabiola Motulo, Santoso Chandra, Stephanie Andamari, J. Sulungbudi, Ronny Lesmana","doi":"10.20885/jkki.vol14.iss3.art10","DOIUrl":null,"url":null,"abstract":"Background: The incidence of chronic kidney disease (CKD) continues to increase from year to year. There was an increase in CKD rates in the 2013 and 2018 basic health research or Riset kesehatan dasar (Riskesdas). Several provinces in Indonesia show a high incidence of CKD and require hemodialysis. As the incidence of CKD increases, it is important to investigate the influencing factors.Objective: To identify the influencing factors of CKD incidence in Indonesia.Methods: Data from 11 provinces with the highest incidence of CKD and hemodialysis were obtained from the Indonesian Ministry of Health through the Riskesdas 2018 survey. For comparison, the incidence of hemodialysis patients in 2020 at Immanuel Hospital Bandung was included in the investigation. All data were analysed using a Python software program, and a decision tree was determined. The results of the decision tree were analysed using Chi-square. Subject profiles were descriptively analysed for some Riskesdas 2018 data and medical records at Immanuel Hospital. Results: The total data from Riskesdas was 130,787 subjects, among those, there were 610 people with CKD/hemodialysis, meanwhile data of 79 people with hemodialysis were obtained from Immanuel Hospital. The odds ratios of diabetes mellitus was 4.54 (p=0.000), hypertension was 3.00 (p=0.000), salty food was 2.26 (p=0.000), waist circumference (WC) was 1.35 (p=0.025), and body mass index (BMI) was 1.06 (p=0.605). Conclusion: Diabetes, hypertension, salty foods, WC and BMI are the five most important factors influencing the incidence of CKD in Indonesia. These variables need to be managed properly to reduce the incidence of CKD.","PeriodicalId":508182,"journal":{"name":"Jurnal Kedokteran dan Kesehatan Indonesia","volume":" 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Kedokteran dan Kesehatan Indonesia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20885/jkki.vol14.iss3.art10","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

Background: The incidence of chronic kidney disease (CKD) continues to increase from year to year. There was an increase in CKD rates in the 2013 and 2018 basic health research or Riset kesehatan dasar (Riskesdas). Several provinces in Indonesia show a high incidence of CKD and require hemodialysis. As the incidence of CKD increases, it is important to investigate the influencing factors.Objective: To identify the influencing factors of CKD incidence in Indonesia.Methods: Data from 11 provinces with the highest incidence of CKD and hemodialysis were obtained from the Indonesian Ministry of Health through the Riskesdas 2018 survey. For comparison, the incidence of hemodialysis patients in 2020 at Immanuel Hospital Bandung was included in the investigation. All data were analysed using a Python software program, and a decision tree was determined. The results of the decision tree were analysed using Chi-square. Subject profiles were descriptively analysed for some Riskesdas 2018 data and medical records at Immanuel Hospital. Results: The total data from Riskesdas was 130,787 subjects, among those, there were 610 people with CKD/hemodialysis, meanwhile data of 79 people with hemodialysis were obtained from Immanuel Hospital. The odds ratios of diabetes mellitus was 4.54 (p=0.000), hypertension was 3.00 (p=0.000), salty food was 2.26 (p=0.000), waist circumference (WC) was 1.35 (p=0.025), and body mass index (BMI) was 1.06 (p=0.605). Conclusion: Diabetes, hypertension, salty foods, WC and BMI are the five most important factors influencing the incidence of CKD in Indonesia. These variables need to be managed properly to reduce the incidence of CKD.
印度尼西亚慢性肾病发病率的影响因素分析
背景:慢性肾脏病(CKD)的发病率逐年上升。在2013年和2018年的基础健康研究或Riset kesehatan dasar(Riskesdas)中,CKD的发病率有所上升。印尼多个省份的CKD发病率较高,需要进行血液透析。随着慢性肾脏病发病率的增加,研究其影响因素非常重要:确定印度尼西亚慢性肾脏病发病率的影响因素:通过 2018 年 Riskesdas 调查,从印尼卫生部获得了 CKD 和血液透析发病率最高的 11 个省份的数据。为便于比较,调查还包括万隆伊曼纽尔医院 2020 年血液透析患者的发病率。所有数据均使用 Python 软件程序进行分析,并确定了一个决策树。决策树的结果使用Chi-square进行分析。对2018年Riskesdas的部分数据和伊曼纽尔医院的医疗记录进行了受试者概况描述性分析。结果:来自Riskesdas的总数据为130 787名受试者,其中有610人患有慢性肾脏病/血液透析,同时从伊曼纽尔医院获得了79名血液透析患者的数据。糖尿病的几率比为 4.54(P=0.000),高血压的几率比为 3.00(P=0.000),吃咸的几率比为 2.26(P=0.000),腰围的几率比为 1.35(P=0.025),体重指数的几率比为 1.06(P=0.605)。结论糖尿病、高血压、含盐食物、腹围和体重指数是影响印度尼西亚慢性肾脏病发病率的五个最重要因素。要降低慢性肾脏病的发病率,就必须对这些变量进行适当管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信