Season of birth and Parkinson’s disease: possible relationship?

Seasonality of presentation and birth in catatonia

BACKGROUND

Catatonia is a neuropsychiatric syndrome associated with both psychiatric disorders and medical conditions. Understanding of the pathophysiology of catatonia remains limited, and the role of the environment is unclear. Although seasonal variations have been shown for many of the disorders underlying catatonia, the seasonality of this syndrome has not yet been adequately explored.

METHODS

Clinical records were screened to identify a cohort of patients suffering from catatonia and a control group of psychiatric inpatients, from 2007 to 2016 in South London. In a cohort study, the seasonality of presentation was explored fitting regression models with harmonic terms, while the effect of season of birth on subsequent development of catatonia was analyzed using regression models for count data. In a case-control study, the association between month of birth and catatonia was studied fitting logistic regression models.

RESULTS

In total, 955 patients suffering from catatonia and 23,409 controls were included. The number of catatonic episodes increased during winter, with a peak in February. Similarly, an increasing number of cases was observed during summer, with a second peak in August. However, no evidence for an association between month of birth and catatonia was found.

CONCLUSIONS

The presentation of catatonia showed seasonal variation in accordance with patterns described for many of the disorders underlying catatonia, such as mood disorders and infections. We found no evidence for an association between season of birth and risk of developing catatonia. This may imply that recent triggers may underpin catatonia, rather than distal events.

Season-of-birth phenomenon in health and longevity: epidemiologic evidence and mechanistic considerations

In many human populations, especially those living in regions with pronounced climatic differences between seasons, the most sensitive (prenatal and neonatal) developmental stages occur in contrasting conditions depending on the season of conception. The difference in prenatal and postnatal environments may be a factor significantly affecting human development and risk for later life chronic diseases. Factors potentially contributing to this kind of developmental programming include nutrition, outdoor temperature, infectious exposures, duration of sunlight, vitamin D synthesis, etc. Month of birth is commonly used as a proxy for exposures which vary seasonally around the perinatal period. Season-of-birth patterns have been identified for many chronic health outcomes. In this review, the research evidence for the seasonality of birth in adult-life disorders is provided and potential mechanisms underlying the phenomenon of early life seasonal programming of chronic disease and longevity are discussed.

Seasonal temperature is associated with Parkinson's disease prescriptions: an ecological study

The aim of this study is to test what effect the weather may have on medications prescribed to treat Parkinson's disease. Twenty-three years of monthly time, series data was sourced from the Pharmaceutical Benefits Scheme (PBS) and the Bureau of Meteorology (BOM). Data were available for eight states and territories and their corresponding capital cities. The dependent variable was the aggregate levodopa equivalent dose (LED) for 51 Parkinson's medications identified on the PBS. Two explanatory variables of interest, temperature and solar exposure, were identified in the BOM data set. Linear and cosinor models were estimated with fixed and random effects, respectively. The prescribed LED was 4.2% greater in January and 4.5% lower in July. Statistical analysis showed that temperature was associated with the prescription of Parkinson medications. Our results suggest seasonality exists in Parkinson's disease symptoms and this may be related to temperature. Further work is needed to confirm these findings and understand the underlying mechanisms as a better understanding of the causes of any seasonal variation in Parkinson's disease may help clinicians and patients manage the disease more effectively.