气象因素对不同年龄段良性阵发性位置性眩晕发病影响的临床分析

Clinical Analysis of the Association Between Meteorological Factors and the Incidence of Benign Paroxysmal Positional Vertigo Across Different Age Groups

摘要:

目的：分析大样本量良性阵发性位置性眩晕（BPPV）患者的流行病学特征，探讨不同年龄组BPPV发病与气象参数的相关性，为临床预防和干预提供依据。方法：回顾性收集4972例确诊为BPPV的患者临床资料，统计分析其年龄、性别及受累半规管类型的分布特征。结合同期气象数据，采用Spearman相关性分析及负二项回归/泊松回归模型，分别探讨全年龄段人群及青年、中年、老年亚组BPPV发病例数与气压、气温、湿度、风速及大气污染物等因子的关联。结果：共纳入BPPV患者4972例，男女比例为1:2.29，女性居多。后半规管型最常见（3051例，61.37%）。中年组发病数最多，青年组发病率呈逐年上升趋势。季节分布显示，春冬季为发病高峰，夏季最低。BPPV发病与平均气压、气压差、最高气压呈正相关，与平均水汽压、气温、CO呈负相关。回归分析显示，气压差对发病影响最大（Exp(B)=2.16），气压差每增加1单位，患病风险增加116%。各年龄组关键影响因子存在差异。青年组和中年组均以气压差为首要风险因素（Exp(B)分别为1.078和2.01），老年组则对最高气压（Exp(B)=1.222）和最低气温（Exp(B)=0.891）更为敏感。平均水汽压在各年龄组中均表现为保护性因素。结论：BPPV发病具有明显的季节性，且与气象因素密切相关。气压变化（特别是气压差）是诱发BPPV的重要环境因素，但其影响程度存在年龄异质性。针对不同年龄段的关键气象风险因子采取差异化预防措施，或有助于降低BPPV的发病率。

Abstract:

Objective: To analyze the epidemiological characteristics of a large cohort of patients with benign paroxysmal positional vertigo (BPPV) and to investigate the correlation between BPPV incidence and meteorological parameters across different age groups, thereby providing a basis for clinical prevention and intervention. Methods: Clinical data from 4,972 patients diagnosed with BPPV were retrospectively collected. The distribution characteristics of age, gender, and affected semicircular canals were analyzed. Using concurrent meteorological data, Spearman correlation analysis and negative binomial/Poisson regression models were performed to explore the associations between the number of BPPV cases (in the total population and subgroups: youth, middle-aged, and elderly) and meteorological variables, including atmospheric pressure, temperature, humidity, wind speed, and air pollutants. Results: A total of 4,972 BPPV patients were enrolled, with a male-to-female ratio of 1:2.29, indicating a female predominance. The posterior semicircular canal type was the most common (3,051 cases, 61.37%). The middle-aged group had the highest number of cases, while the incidence in the youth group increased over the study period. Seasonal distribution revealed peaks in spring and winter and a nadir in summer. BPPV incidence was positively correlated with mean atmospheric pressure, atmospheric pressure difference, and maximum pressure, but negatively correlated with mean water vapor pressure, temperature, and CO levels. Regression analysis identified atmospheric pressure difference as the most significant influencing factor (Exp(B) = 2.16); specifically, each unit increase in pressure difference was associated with a 116% increase in the incidence of BPPV. Key influencing factors varied among age groups: pressure difference was the primary risk factor in both the youth(Exp(B) = 1.078) and middle-aged (Exp(B) = 2.01) groups, whereas the elderly group was more susceptible to maximum pressure (Exp(B) = 1.222) and minimum temperature (Exp(B) = 0.891). Mean water vapor pressure acted as a protective factor across all age groups. Conclusion: BPPV incidence exhibits distinct seasonality and is closely associated with meteorological factors. Atmospheric pressure variation (particularly pressure difference) is a crucial environmental trigger for BPPV; however, its impact demonstrates age-related heterogeneity. Targeted preventive measures based on key meteorological risk factors specific to different age groups may help reduce the incidence of BPPV.