Evidence map›Paper›PMID 37351000›Full record

ArticleFrontiers in psychiatry2023

Predicting depressive symptom by cardiometabolic indicators in mid-aged and older adults in China: a population-based cross-sectional study.

Ying Wang, Xiaoyun Zhang, Yuqing Li, Jiaofeng Gui, Yujin Mei, Xue Yang, Haiyang Liu, Lei-Lei Guo, Jinlong Li, Yunxiao Lei and 10 more

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Ying WangDepartment of Graduate School, Wannan Medical College, Wuhu, An Hui, China.
Xiaoyun ZhangDepartment of Graduate School, Wannan Medical College, Wuhu, An Hui, China.
Yuqing LiDepartment of Graduate School, Wannan Medical College, Wuhu, An Hui, China.
Jiaofeng GuiDepartment of Graduate School, Wannan Medical College, Wuhu, An Hui, China.
Yujin MeiDepartment of Graduate School, Wannan Medical College, Wuhu, An Hui, China.
Xue YangDepartment of Graduate School, Wannan Medical College, Wuhu, An Hui, China.
Haiyang LiuStudent Health Center, Wannan Medical College, Wuhu, An Hui, China.
Lei-Lei GuoDepartment of Surgical Nursing, School of Nursing, Jinzhou Medical University, Jinzhou, Liaoning, China.
Jinlong LiDepartment of Occupational and Environmental Health, Key Laboratory of Occupational Health and Safety for Coal Industry in Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan, Hebei, China.
Yunxiao LeiObstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China.
Xiaoping LiDepartment of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China.
Lu SunDepartment of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China.
Liu YangDepartment of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China.
Ting YuanObstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China.
Congzhi WangDepartment of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China.
Dongmei ZhangDepartment of Pediatric Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China.
Jing LiDepartment of Surgical Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China.
Mingming LiuDepartment of Surgical Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China.
Ying HuaRehabilitation Nursing, School of Nursing, Wanna Medical College, Wuhu, An Hui, China.
Lin ZhangDepartment of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Depressive symptom is a serious mental illness often accompanied by physical and emotional problems. The prevalence of depressive symptom in older adults has become an increasingly important public health priority. Our study used cardiometabolic indicators to predict depressive symptom in middle-aged and older adults in China. Methods: The data came from the China Health and Retirement Longitudinal Study 2011 (CHARLS2011), which was a cross-sectional study. The analytic sample included 8,942 participants aged 45 years or above. The study evaluated the relationship between cardiometabolic indicators and depression by measuring 13 indicators, including body mass index (BMI), waist circumference, waist-height ratio (WHtR), conicity index, visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), a body shape index (ABSI), body roundness index (BRI), triglyceride glucose index (TyG-index) and its correlation index (TyG-BMI, TyG-waist circumference, TyG-WHtR). Binary logistic regression analysis was used to examine the association between thirteen cardiometabolic indicators and depressive symptom. In addition, the receiver operating characteristic (ROC) curve analysis and area under curve (AUC) were used to evaluate the predictive anthropometric index and to determine the optimum cut-off value. Results: The study included 8,942 participants, of whom 4,146 (46.37%) and 4,796 (53.63%) were male and female. The prevalence of depressive symptom in mid-aged and older adults in China was 41.12% in males and 55.05% in females. The results revealed that BMI [AUC = 0.440, 95%CI: 0.422-0.457], waist circumference [AUC = 0.443, 95%CI: 0.425-0.460], WHtR [AUC = 0.459, 95%CI: 0.441-0.476], LAP [AUC = 0.455, 95%CI: 0.437-0.472], BRI [AUC = 0.459, 95%CI: 0.441-0.476], CVAI [AUC = 0.449, 95%CI: 0.432-0.467], TyG-BMI [AUC = 0.447, 95%CI: 0.429-0.465], and TyG-waist circumference [AUC =0.452, 95%CI: 0.434-0.470] were weak predictors of depressive symptom ( Conclusion: Most cardiometabolic indicators have important value in predicting depressive symptom. Our results can provide measures for the early identification of depressive symptom in middle-aged and older adults in China to reduce the prevalence of depressive symptom and improve health.

Indexed as

cardiometabolic indicatorscross-sectional studydepressive symptommiddle-aged and older adultsobesity

Identifiers

PMID37351000
PMCPMC10282944

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.