METHODS: In this study, a time series analysis was used to determine the variation of variables over time. All series were seasonally adjusted and Poisson regression analysis was performed. In the analysis of meteorological data and emotional distress due to religious mourning events, the best results were obtained by autoregressive moving average (ARMA) (5,5) model.
RESULTS: It was determined that average temperature, sunshine, and rain variables had a significant effect on death. A total of 2375 AMI's were enrolled. Average temperate (°C) and sunshine hours a day (h/day) had a statistically significant relationship with the number of AMI's (β = 0.011, P = 0.014). For every extra degree of temperature increase, the risk of AMI rose [OR = 1.011 (95%CI 1.00, 1.02)]. For every extra hour of sunshine, a day a statistically significant increase [OR = 1.02 (95% CI 1.01, 1.04)] in AMI risk occurred (β = 0.025, P = 0.001). Religious mourning events increase the risk of AMI 1.05 times more. The other independent variables have no significant effects on AMI's (P > 0.05).
CONCLUSION: Results demonstrate that sunshine hours and the average temperature had a significant effect on the risk of AMI. Moreover, emotional distress due to religious morning events increases AMI. More specific research on this topic is recommended.
METHODS: 12-year observational study of a UK Fracture Liaison Service (outpatient secondary care setting). Database analyses of the records of adult outpatients aged 50 years and older with fragility fractures. Weather data were obtained from the UK's national Meteorological Office. In the seasonality analyses, we tested for the association between months and seasons (determinants), respectively, and outpatient attendances, by analysis of variance (ANOVA) and Tukey's test. In the meteorological analyses, the determinants were mean temperature, mean daily maximum and minimum temperature, number of days of rain, total rainfall and number of days of frost, per month, respectively. We explored the association of each meteorological variable with outpatient attendances, by regression models.
RESULTS: The Fracture Liaison Service recorded 25,454 fragility fractures. We found significant monthly and seasonal variation in attendances for fractures of the: radius or ulna; humerus; ankle, foot, tibia or fibula (ANOVA, all p-values <0.05). Fractures of the radius or ulna and humerus peaked in December and winter. Fractures of the ankle, foot, tibia or fibula peaked in July, August and summer. U-shaped associations were showed between each temperature parameter and fractures. Days of frost were directly associated with fractures of the radius or ulna (p-value <0.001) and humerus (p-value 0.002).
CONCLUSION: Different types of fragility fractures present different seasonal patterns. Weather may modulate their seasonality and consequent healthcare utilisation.