Seasonal patterns of sickness absence due to diagnosed mental disorders: a nationwide 12-year register linkage study.

AIMS: Although seasonality has been documented for mental disorders, it is unknown whether similar patterns can be observed in employee sickness absence from work due to a wide range of mental disorders with different severity level, and to what extent the rate of change in light exposure plays a role. To address these limitations, we used daily based sickness absence records to examine seasonal patterns in employee sickness absence due to mental disorders. METHODS: We used nationwide diagnosis-specific psychiatric sickness absence claims data from 2006 to 2017 for adult individuals aged 16-67 (n = 636,543 sickness absence episodes) in Finland, a high-latitude country with a profound variation in daylength. The smoothed time-series of the ratio of observed and expected (O/E) daily counts of episodes were estimated, adjusted for variation in all-cause sickness absence rates during the year. RESULTS: Unipolar depressive disorders peaked in October-November and dipped in July, with similar associations in all forms of depression. Also, anxiety and non-organic sleep disorders peaked in October-November. Anxiety disorders dipped in January-February and in July-August, while non-organic sleep disorders dipped in April-August. Manic episodes reached a peak from March to July and dipped in September-November and in January-February. Seasonality was not dependent on the severity of the depressive disorder. CONCLUSIONS: These results suggest a seasonal variation in sickness absence due to common mental disorders and bipolar disorder, with high peaks in depressive, anxiety and sleep disorders towards the end of the year and a peak in manic episodes starting in spring. Rapid changes in light exposure may contribute to sickness absence due to bipolar disorder. The findings can help clinicians and workplaces prepare for seasonal variations in healthcare needs.

Climatic, ecological and socioeconomic factors as predictors of Sindbis virus infections in Finland.

Mosquito-borne Sindbis virus (SINV) causes rash-arthritis syndrome in Finland. Major outbreaks with approximately 7-year cycles have caused substantial burden of illness. Forest dwelling grouse are suspected to be amplifying hosts, with the infection transmitted to humans by mosquito bites. SINV infection surveillance data for 1984­2010 were used to create a negative binomial hurdle model, with seasonality, long-term cycles, climatic, ecological and socioeconomic variables. Climatic factors during early summer and amount of snow in April described the occurrence and incidence of SINV infections. Regulated water shore and hatch-year black grouse density described the occurrence, while population working in agriculture, agricultural land(negative) and income (negative) described the incidence of the disease. The prediction for 2009 was 85 cases (95% prediction interval 2-1187), while the actual occurrence was 106. We identified novel and known risk factors. The prevention of SINV infections in regulated water areas by infected mosquito populations should be targeted.

Epidemiology and seasonal variation of distal radius fractures in Oulu, Finland.

UNLABELLED: The purpose of this study was to assess changes in epidemiology and reasons for wintertime excess of distal radius fractures in Oulu, Finland. Our results showed that age-specific incidence of distal radius fractures in elderly women in Finland has increased compared with a previous study. Slippery pavement surfaces assessed by a new meteorological model partly explained wintertime excess of fractures, but factors beyond weather are contributing to seasonality. INTRODUCTION: In this report, we describe the epidemiology and seasonal variation of distal radius fractures in Oulu, Finland, with a focus on the effect of weather and slippery pavement conditions. METHODS: Records of patients aged ≥16 years living in Oulu with a distal radius fracture during the year 2008 were reviewed. Demographic data and details of the injury were assessed from medical records, and fractures were classified according to AO classification. Population data for Oulu during the year 2008 were used to calculate crude incidence as well as sex- and age-specific incidence rates. The number of wintertime fractures was compared with those related to pavement surface slipperiness using a unique weather and pavement condition model of the Finnish Meteorological Institute. RESULTS: The crude incidence was 258/100,000 person-years. Sex- and age-specific incidence rates rose to 1,107/100,000 person-years for females and 466/100,000 person-years for males aged ≥80 years. Poisson regression analysis showed that the number of fractures was 2.5 (95% confidence interval (CI), 1.6 to 4.0; P < 0.001) times greater on slippery winter days compared with non-winter days whereas on normal winter days fractures were 1.4 (95% CI, 1.1 to 1.9; P = 0.01) times greater. Both low- and high-energy injuries resulted in similar fracture patterns by AO classification. CONCLUSIONS: Our results suggest that the epidemiology of distal radius fractures in elderly women in Finland has changed compared with a previous study. Weather analysis showed that the slipperiness of the pavement could partly explain the wintertime excess of distal radius fractures.