Obesity and depressive symptoms among Chinese people aged 45 and over

Qian, Jiahui; Li, Ningxiu; Ren, Xiubao

doi:10.1038/srep45637

Cited by 53 publications

(58 citation statements)

References 33 publications

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“…Also there are some theories about the relationship between Neuropeptide Y, leptin and depression. 25,26 Depressive symptoms decreased as BMI increased in both men and women (p<0.05) in a study from China. 26 Relationship between eating disorders and other psychiatric diseases was shown in literature.…”

Section: Discussionmentioning

confidence: 99%

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Eating disorders in bariatric surgery candidates admitted to Haydarpasa Numune Training and Research Hospital

Eroğlu¹,

Tamam²

2018

Anadolu Psikiyatri Derg

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Section: Discussionmentioning

confidence: 99%

“…25,26 Depressive symptoms decreased as BMI increased in both men and women (p<0.05) in a study from China. 26 Relationship between eating disorders and other psychiatric diseases was shown in literature. For example Müller et al reported that depressive symptoms were higher in pre-bariatric patients with comorbid binge eating disorder.…”

Section: Discussionmentioning

confidence: 99%

Eating disorders in bariatric surgery candidates admitted to Haydarpasa Numune Training and Research Hospital

Eroğlu¹,

Tamam²

2018

Anadolu Psikiyatri Derg

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“…BMI is converted into four attributes: "⩽18.5," "18.5-22.99," "23-24.99," and "⩾25." 31 During the preprocessing of categorical variables, all values for each variable generate new attributes, and then, each attribute has a value 1 in the column that corresponds to the true for this category and 0 otherwise. During this conversion of categorical variables, all null values are replaced with a 0.…”

Section: Data Preprocessingmentioning

confidence: 99%

A machine learning–based 1-year mortality prediction model after hospital discharge for clinical patients with acute coronary syndrome

Sherazi

Jeong

Jae

et al. 2019

Health Informatics J

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Cardiovascular disease is the leading cause of death worldwide so, early prediction and diagnosis of cardiovascular disease is essential for patients affected by this fatal disease. The goal of this article is to propose a machine learning–based 1-year mortality prediction model after discharge in clinical patients with acute coronary syndrome. We used the Korea Acute Myocardial Infarction Registry data set, a cardiovascular disease database registered in 52 hospitals in Korea for 1 November 2005–30 January 2008 and selected 10,813 subjects with 1-year follow-up traceability. The ranges of hyperparameters to find the best prediction model were selected from four different machine learning models. Then, we generated each machine learning–based mortality prediction model with hyperparameters completed the range fitness via grid search using training data and was evaluated by fourfold stratified cross-validation. The best prediction model with the highest performance was found, and its hyperparameters were extracted. Finally, we compared the performance of machine learning–based mortality prediction models with GRACE in area under the receiver operating characteristic curve, precision, recall, accuracy, and F-score. The area under the receiver operating characteristic curve in applied machine learning algorithms was averagely improved up to 0.08 than in GRACE, and their major prognostic factors were different. This implementation would be beneficial for prediction and early detection of major adverse cardiovascular events in acute coronary syndrome patients.

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“…Typical factors influencing the prevalence of depression include gender, stressful life events, and physical health problems (Qian, 2017). Gender is one of the most widely known factors of depression.…”

Section: Literature Reviewmentioning

confidence: 99%

Can the Internet Help Relieve Depression?

Yizhe

2019

pijss

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Depression is a very serious problem in our modern society. It can influence people negatively in many ways. Although many scientists are trying to find efficient ways to deal with depression, there are still no final conclusions. Using data from the China Health and Retirement Longitudinal Study (CHARLS), this study shows that in China, internet use among older people (aged 45 and above) helps relieve their depression symptoms. Combining this finding with steadily growing cellphone use, this suggests that developing specially APPs for older people to use smart phones can help combat depression in China. Other ways to reach the rural population via the internet can also be powerful tools to help with depression.

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Obesity and depressive symptoms among Chinese people aged 45 and over

Cited by 53 publications

References 33 publications

Eating disorders in bariatric surgery candidates admitted to Haydarpasa Numune Training and Research Hospital

Eating disorders in bariatric surgery candidates admitted to Haydarpasa Numune Training and Research Hospital

A machine learning–based 1-year mortality prediction model after hospital discharge for clinical patients with acute coronary syndrome

Can the Internet Help Relieve Depression?

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