ABSTRACT
Objective@# To systematically evaluate risk factors for cardiometabolic multimorbidity (CMM), so as to provide the evidence for formulating CMM prevention and control strategies.@*Methods@#Publications pertaining to the risk factors for CMM were retrieved from databases, including SinoMed, CNKI, Wanfang Data, VIP, PubMed and Cochrane Library from inception to March 31, 2023. Meta-analysis was performed using the software RevMan 5.4 and Stata 16.0, and sensitivity analysis was performed using the leave-one-out method. The publication bias was evaluated using Egger's test.@*Results@#Totally 494 publications were screened, and 20 publications were included in the final analysis, including 13 cohort studies (covering 1 940 000 participants) and 7 cross-sectional studies (covering 13 000 000 participants). Meta-analysis revealed that female (OR=1.54, 95%CI: 1.40-1.71), middle age (OR=3.80, 95%CI: 3.33-4.34), elderly (OR=2.82, 95%CI: 1.48-5.37), urban resident (OR=1.41, 95%CI: 1.27-1.57), higher education level (OR=2.01, 95%CI: 1.35-3.01), higher economic level (OR=1.21, 95%CI: 1.16-1.25), overweight (OR=1.92, 95%CI: 1.64-2.26), obesity (OR=3.01, 95%CI: 2.30-3.93), central obesity (OR=1.70, 95%CI: 1.12-2.56), smoking (OR=1.27, 95%CI: 1.07-1.51), alcohol consumption (OR=1.27, 95%CI: 1.01-1.59), irregular diet (OR=1.10, 95%CI: 1.02-1.18), insufficient intake of vegetables and fruits (OR=1.12, 95%CI: 1.07-1.17), lack of sleep at night (OR=1.17, 95%CI: 1.08-1.27), and depression (OR=1.50, 95%CI: 1.33-1.69) were risk factors for CMM. Sensitivity analysis of effects of central obesity and alcohol consumption were not robust. No publication bias was examined by Egger's test.@* Conclusions @#Female, middle age, elderly, urban resident, higher education level, higher economic level, overweight, obesity, central obesity, smoking, alcohol consumption, irregular diet, insufficient intake of vegetables and fruits, lack of sleep at night and depression are risk factors for CMM.
ABSTRACT
Multimorbidity has become a great challenge to the health service system in China,and cardiometabolic multimorbidity is one of the major multimorbidity patterns worldwide. The mechanisms of the bidirectional relationship between cardiometabolic multimorbidity and depression are complex. Their co-occurrence significantly increases the burden of diseases and the risk of adverse prognosis for patients. This review focuses on the implication of reciprocal interaction between cardiometabolic multimorbidity and depression for general practice to provide insights to the health management of multimorbidity populations.