RESUMEN
OBJECTIVE: We aimed to investigate the potential environmental risk factors, protective factors, and biomarkers of hearing loss (HL), and establish a hierarchy of evidence. DATA SOURCES: Embase, PubMed, Cochrane Library, and Web of Science electronic database from inception to June 1, 2023. REVIEW METHODS: We included meta-analyses of observational studies of associations between HL and environmental risk factors, protective factors, or biomarkers. We calculated summary effect estimates, 95% confidence interval, heterogeneity I2 statistic, 95% prediction interval, small study effects, and excess significance biases. RESULTS: Of the 9211 articles retrieved, 60 eligible articles were included. The 60 eligible articles identified 47 potential environmental risk and protective factors (N = 4,123,803) and 46 potential biomarkers (N = 173,701). Evidence of association was convincing (class I) for rheumatoid arthritis (RA) and every 1 cm increase in height. Evidence of association was highly suggestive (class II) for human immunodeficiency virus (HIV), diabetes, cumulative noise exposure (CNE), smoking, congenital cytomegalovirus (CMV) infection, combined exposure to organic solvents and noise, non-Gaussian noise exposure, each 1 kg increase in birth weight, noise exposure, and alopecia areata (AA). CONCLUSION: In this umbrella review, RA, every 1 cm increase in height, HIV, diabetes, CNE, smoking, congenital CMV infection, combined exposure to organic solvents and noise, non-Gaussian noise exposure, each 1 kg increase in birth weight, noise exposure, and AA were strongly associated with HL.
Asunto(s)
Biomarcadores , Pérdida Auditiva , Factores Protectores , Humanos , Factores de Riesgo , Biomarcadores/sangre , Pérdida Auditiva/etiología , Exposición a Riesgos Ambientales/efectos adversosRESUMEN
OBJECTIVE: To investigate the relationship of dyslipidemia and menopausal symptoms in Chinese menopausal women. MATERIAL AND METHODS: A total of 989 eligible participants with menopausal syndrome were recruited from outpatient clinics in several cities in China. Menopausal symptoms were assessed using the Chinese Menopause Rating Scale (CMRS), the Self-rating Depression Scale (SDS), and the Self-rating Anxiety Scale (SAS). Serum lipid profile was measured using enzyme colorimetry. The relationship between lipid profile and menopausal symptoms was assessed using Student's t test/nonparametric Mann-Whitney U test, Spearman's correlation test, and binary logistic regression analysis. RESULTS: Among the 989 patients, 527 had dyslipidemia while 462 did not. Patients with dyslipidemia had significantly higher Self-rating Anxiety Scale (SAS) scores than those without (p < 0.001), while there was no significant difference in Self-rating Depression Scale (SDS) scores. Patients without dyslipidemia had higher scores on the Chinese Menopause Rating Scale (CMRS) vascular dimension compared to those with dyslipidemia (p = 0.003). The correlation test revealed that variables associated with dyslipidemia included age (p = 0.031), CMRS hot flashes dimension score (P = 0.003), and SAS score (p < 0.001). Regression analysis demonstrated that BMI (OR: 1.08, 95% CI: 1.01-1.16, p = 0.027), SAS scores (OR = 1.10, 95% CI = 1.07-1.13), vasomotor dimension (OR = 0.89, 95% CI = 0.83-0.95), physical dimension (OR = 0.96, 95% CI = 0.93-1.00), and social dimension (OR = 0.84, 95% CI = 0.74-0.95) were independently associated with an increased risk of dyslipidemia. CONCLUSIONS: This study showed that anxiety was associated with an unfavorable lipid profile, and menopausal depression seemed to have no relationship with lipid profile, while vasomotor symptoms appeared to be a favorable factor for dyslipidemia in Chinese menopausal women.