Paper
24 March 2023 Depression in menopausal women
Wanting Shan, Hanrui Dou, Yundi Gui
Author Affiliations +
Proceedings Volume 12611, Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022); 126114Q (2023) https://doi.org/10.1117/12.2669562
Event: International Conference on Biological Engineering and Medical Science (ICBioMed2022), 2022, Oxford, United Kingdom
Abstract
Many present studies have investigated the risk factors of depression in menopausal women; some paid attention to their living environment, and others focused on women themselves. This study will discuss the inner and outer effects that may affect depression in menopausal women in the US between 2000 and 2004. The data used in this study is from SWAN dataset. In this dataset, all participants took a 2-round cross-sectional survey from seven research centers across the US in 1994. 9 variables were selected, and eight were included in a logistic regression model, with whether the women are in depression being the dependent variable. The result(estimated coefficients, p-value) shows that the stress level(0.288, 0.000), if the participant was still upset about the illness of their family(0.657; 0.011), middle(0.504; 0.000) and high irritability level(0.991; 0.027) have a significant positive correlation with risk of depression; a little stress of being a mom(- 0.363; 0.040), extremely stressful of being a mom(-0.552; 0.048), their age(-0.052; 0.038) and if their menopausal status is posted by bilateral salpingo(-0.880; 0.011) have a significant negative correlation with risk of depression. However, further investigations on newer and broader populations need to be done to confirm the result more accurately.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wanting Shan, Hanrui Dou, and Yundi Gui "Depression in menopausal women", Proc. SPIE 12611, Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022), 126114Q (24 March 2023); https://doi.org/10.1117/12.2669562
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KEYWORDS
Binary data

Statistical analysis

Diseases and disorders

Error analysis

Statistical modeling

Associative arrays

Data modeling

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