Celia O'Hare1, Vincent O'Sullivan2, Stephen Flood3, Rose Anne Kenny4. 1. The Irish Longitudinal Study on Ageing (TILDA), Trinity College Dublin, Ireland. Electronic address: oharesh@tcd.ie. 2. Lancaster University Management School, LA1 4YX, United Kingdom. 3. New Zealand Climate Change Research Institute, School of Geography Environment and Earth Sciences, Victoria University, Wellington 6012, New Zealand. 4. The Irish Longitudinal Study on Ageing (TILDA), Trinity College Dublin, Ireland.
Abstract
BACKGROUND: Given increased social and physiological vulnerabilities, older adults may be particularly susceptible to environmental influences on mood. Whereas the impact of season on mood is well described for adults, studies rarely extend to elders or include objective weather data. We investigated the impact of seasonality and meteorological factors on risk of current depressive symptoms in older adults. METHODS: We used data on 8027 participants from the first wave of The Irish Longitudinal Study of Ageing, a population-representative cohort of adults aged 50+. Depressive symptoms were recorded using the Centre for Epidemiological Studies Depression Scale. Season was defined according to the World Meteorological Organisation. Data on climate over the preceding thirty years, and temperature and rain over the preceding month, were provided by the Irish Meteorological Service and linked using Geographic Information Systems techniques to participant's geo-coded locations at a resolution of one kilometre. RESULTS: The highest levels of depressive symptoms were reported in winter and the lowest in spring (mean 6.56 [CI95% 6.09, 7.04] vs. 5.81 [CI95%: 5.40, 6.22]). In fully adjusted linear regression models, participants living in areas with higher levels of rainfall in the preceding and/or current calendar month had greater depressive symptoms (0.04 SE 0.02; p=0.039 per 10mm additional rainfall per month) while those living in areas with sunnier climates had fewer depressive symptoms (-2.67 SE 0.88; p=0.003 for every additional hour of average annual daily sunshine). LIMITATIONS: This was a cross-sectional analysis thus causality cannot be inferred; monthly rain and temperature averages were available only on a calendar month basis while monthly local levels of sunshine data were not available. CONCLUSIONS: Environmental cues may influence mood in older adults and thus have relevance for the recognition and treatment of depression in this age group.
BACKGROUND: Given increased social and physiological vulnerabilities, older adults may be particularly susceptible to environmental influences on mood. Whereas the impact of season on mood is well described for adults, studies rarely extend to elders or include objective weather data. We investigated the impact of seasonality and meteorological factors on risk of current depressive symptoms in older adults. METHODS: We used data on 8027 participants from the first wave of The Irish Longitudinal Study of Ageing, a population-representative cohort of adults aged 50+. Depressive symptoms were recorded using the Centre for Epidemiological Studies Depression Scale. Season was defined according to the World Meteorological Organisation. Data on climate over the preceding thirty years, and temperature and rain over the preceding month, were provided by the Irish Meteorological Service and linked using Geographic Information Systems techniques to participant's geo-coded locations at a resolution of one kilometre. RESULTS: The highest levels of depressive symptoms were reported in winter and the lowest in spring (mean 6.56 [CI95% 6.09, 7.04] vs. 5.81 [CI95%: 5.40, 6.22]). In fully adjusted linear regression models, participants living in areas with higher levels of rainfall in the preceding and/or current calendar month had greater depressive symptoms (0.04 SE 0.02; p=0.039 per 10mm additional rainfall per month) while those living in areas with sunnier climates had fewer depressive symptoms (-2.67 SE 0.88; p=0.003 for every additional hour of average annual daily sunshine). LIMITATIONS: This was a cross-sectional analysis thus causality cannot be inferred; monthly rain and temperature averages were available only on a calendar month basis while monthly local levels of sunshine data were not available. CONCLUSIONS: Environmental cues may influence mood in older adults and thus have relevance for the recognition and treatment of depression in this age group.
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