BackgroundInsulin resistance (IR) is involved in the pathogenesis of atherosclerosis. As a new indicator, the triglyceride-glucose (TyG) index has greater operability for the evaluation of insulin resistance. Previous studies have shown inconsistent results in evaluating the association between the TyG index and stroke incidence in people without stroke at baseline. Therefore, this study aimed to systematically assess this association through a meta-analysis.MethodsCohort studies with the multivariate-adjusted hazard ratio (HR) association between the TyG index and stroke were obtained by searching the PubMed, Cochrane Library, and EMBASE databases before 16 December 2021. We pooled the adjusted HR along with 95% CI using a random-effects model. The primary outcome was stroke including ischemic and hemorrhagic stroke. We conducted subgroup analyses stratified by study design, ethnicity, characteristics of participants, weight of studies, and length of follow-up duration. Review Manager 5.3 and Stata 17 were used to perform the meta-analysis.ResultsEight cohort studies with 5,804,215 participants were included. The results showed that participants with the highest TyG index category at baseline compared to those with the lowest TyG index category were independently associated with a higher risk of stroke (HR: 1.26, 95% CI: 1.24–1.29, I2 = 0%, P < 0.001). This finding was consistent with the results of the meta-analysis with the TyG index analyzed as a continuous variable (HR per each-unit increment of the TyG index: 1.13, 95% CI 1.09–1.18, I2 = 0%, P < 0.001). Subgroup analysis had no significant effects (for subgroup analysis, all P > 0.05). No significant heterogeneity was observed among the included cohort studies.ConclusionA higher TyG index may be independently associated with a higher risk of stroke in individuals without stroke at baseline. The aforementioned findings need to be verified by a large-scale prospective cohort study to further clarify the underlying pathophysiological mechanism between the TyG index and stroke.
Background Insulin resistance has been confirmed to be involved in atherosclerosis pathogenesis. As a new indicator, the triglyceride-glucose (TyG) index has greater operability in the evaluation of insulin resistance. Previous studies have shown inconsistent results in evaluating the association between TyG index and stroke incidence in people without stroke at baseline. Therefore, this study was to systematically assess the association by conducting a meta-analysis. Methods Cohort studies on TyG index and stroke were obtained by searching the PubMed, the Cochrane Library (CENTRAL) and EMBASE databases. The multivariate-adjusted correlation of end points was studied, including TyG index and stroke (including ischemic stroke and hemorrhagic stroke) or ischemic stroke. Review Manager 5.3 and Stata 16 were adopted for meta-analysis. Results Eight cohort studies with 5,719,098 participants were included in this meta-analysis. The results showed that participants with the highest TyG index category at baseline, compared to those with the lowest TyG index category, were independently associated with a higher risk of stroke [Hazard ratio (HR): 1.32, 95% confidence interval (CI): 1.22–1.43, I2 = 32%, P < 0.00001]. Subgroups analysis remained that study designs, ethnicity and characteristics of participants had no subgroup effects (for subgroup analysis, all P༞0.05), except outcome report(stroke or ischemic stroke) which suggested that it may had a stronger effect on the association(χ2 = 4.78, P = 0.03). Conclusions A higher TyG index may be independently associated with a higher risk of stroke in people without stroke at baseline. Keywords: Triglyceride-glucose index, Insulin resistance, stroke, Meta-analysis
BackgroundChina has the world’s largest diabetic population, and the cost of caring for all these people every day is substantial. Online information exchange and app usage frequency have been demonstrated to play a significant influence in the management of blood glucose and enhancement of diabetes-related quality of life. However, the association between online information exchange and app usage frequency among actual online populations remains unclear and deserves additional study. Therefore, we evaluated the factors affecting the frequency of app usage in the online glucose management population, with a particular emphasis on the connection between online information exchange and app use frequency, contributing to the expansion of the research of diabetes management models.MethodThis cross-sectional study was conducted by disseminating questionnaires in blood glucose management-related forums and WeChat groups and included 1586 online users concerned about blood glucose management. Information exchange and app usage frequency were considered as independent and dependent variables, respectively. We performed stratified and single factor analysis, multiple equation regression analysis, smooth curve fitting, and threshold effect and saturation effect analysis. R (version 4.1.3, http://www.Rproject.org) and EmpowerStats were used for data analysis.ResultAfter adjusting for other covariates, information exchange was independently and positively associated with app use frequency (β = 8.6, 95% CI: 6.5 to 11.2, p < 0.001). Through interaction analysis, the most significant interaction factors influencing the relationship between information exchange and app usage frequency were identified as health insurance status, whether living with parents, glycated hemoglobin status in the previous month, and self-monitoring of blood glucose (SMBG). The association between information exchange and app usage frequency is U-shaped, with information exchange inflection points of 3.0 and 4.2. Information exchange and app usage frequency are negatively correlated when the average information exchange score is less than 3.0, and for every point increase in the average information exchange score, the likelihood of the app high usage frequency group compared to the app low usage frequency group decreases by 70%. The relationship between information exchange and app usage frequency is strongest when it is greater than or equal to 3.0 and less than or equal to 4.2. The probability of the app high usage frequency group occurring compared to the app low usage frequency group rises 17.3 times for every 1 point increase in the average information exchange score. The probability of the app high usage frequency group occurring in comparison to the app low usage frequency group increased by 1.8 times for every 1 point rise in information exchange when the average information exchange score was higher than 4.2.ConclusionAge, body mass index, married, living with parents, hemoglobin level, SMBG, and information exchange were positively connected with app usage frequency in our study of online blood glucose management population. The link between information exchange and app use frequency was significantly U-shaped. The app usage frequency changed the most with the rise in information exchange when the information exchange score was greater than or equal to 3.0 and less than or equal to 4.2. Therefore, we ought to offer effort to concentrate on and increase the health-related behaviors and activities of those in this score interval.
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