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女性骨质疏松症风险因素模型选择与识别,以改善其医疗保健。

Model Selection and Identification of Osteoporosis Risk Factors in Women to Improve Their Healthcare.

机构信息

Department of Statistics, Government College University, Faisalabad, Pakistan.

Center of Data Science, Government College University, Faisalabad, Pakistan.

出版信息

J Healthc Eng. 2023 Jul 4;2023:3571769. doi: 10.1155/2023/3571769. eCollection 2023.

DOI:10.1155/2023/3571769
PMID:37469790
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10352524/
Abstract

Osteoporosis is characterized by low bone mineral density leading to enhanced bone fragility and a consequent increase in fracture risk. The focus of this case-control study was to identify significant socioeconomic risk factors of osteoporosis in Pakistani women and examine how the risk increases for different levels of risk factors. A case-control study was conducted from November 2018 to August 2019 in two main hospitals in Faisalabad, Pakistan. Multiple logistic regression was used to explore the significant risk factors of osteoporosis and how the risk increases in cases (cases = 120) as compared to the control group (controls = 120) in the presence of these risk factors. The mean age ± standard deviation for cases and controls was 59.62 ± 10.75 and 54.27 ± 10.09, respectively. The minimum and maximum ages were 36 and 80 years, respectively. In addition to age, bone fracture, family history, regular physical activity, family size, use of meat, type of birth, breastfeeding, premature menopause, loss of appetite, and use of anticoagulants were significant risk factors with -values less than 0.05. The risk prediction model with significant risk factors was a good fit with a -value of 0.28, corresponding to the Hosmer-Lemeshow test value (2 = 9.78). This parsimonious model with Cox-Snell 2 = 0.50 (with a maximum value = 0.75) and Nagelkerke 2 = 0.66 showed an AUC of 0.924 as compared to the full model with all risk factors under study that exhibited an AUC of 0.949.

摘要

骨质疏松症的特征是骨密度低,导致骨骼脆弱度增加,骨折风险相应增加。本病例对照研究的重点是确定巴基斯坦女性骨质疏松症的显著社会经济风险因素,并研究不同风险因素水平下风险的增加情况。该病例对照研究于 2018 年 11 月至 2019 年 8 月在巴基斯坦费萨拉巴德的两家主要医院进行。采用多因素逻辑回归分析探讨骨质疏松症的显著风险因素,以及在存在这些风险因素的情况下,病例组(病例=120)与对照组(对照=120)相比,风险如何增加。病例组和对照组的平均年龄±标准差分别为 59.62±10.75 和 54.27±10.09。年龄最小和最大分别为 36 岁和 80 岁。除年龄外,骨折、家族史、有规律的体育活动、家庭规模、肉类摄入、分娩类型、母乳喂养、过早绝经、食欲不振和使用抗凝剂也是显著的风险因素,其 P 值均小于 0.05。具有显著风险因素的风险预测模型拟合良好,P 值为 0.28,与 Hosmer-Lemeshow 检验值(2=9.78)相对应。与纳入所有研究风险因素的全模型(AUC 为 0.949)相比,该简化模型的 Cox-Snell 2=0.50(最大值为 0.75)和 Nagelkerke 2=0.66,曲线下面积(AUC)为 0.924。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc6e/10352524/24b125518bc3/JHE2023-3571769.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc6e/10352524/24b125518bc3/JHE2023-3571769.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc6e/10352524/24b125518bc3/JHE2023-3571769.001.jpg

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