Tarik Benmarhnia1, Nathalie Auger2, Virginie Stanislas2, Ernest Lo2, Jay S Kaufman3. 1. Institute for Health and Social Policy, McGill University, Meredith, Charles, House, 1130 Pine Avenue West, Montreal, QC, H3A 1A3, Canada. tarik.benmarhnia@mcgill.ca. 2. Institut National de Santé Publique du Québec, Montreal, QC, Canada. 3. Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, QC, Canada.
Abstract
OBJECTIVES: Temperature is a hypothesized determinant of early delivery, but seasonal and long term trends, delayed effects of temperature, and the influence of extreme cold temperatures have not yet been addressed. We aim to study the influence of apparent temperature on daily number of births, considering lag structures, seasonality and long term trends. METHODS: We used daily number of births in conjunction with apparent outdoor temperatures between 1981 and 2010 in Montreal. We used Poisson regression combined with a distributed lag nonlinear model to consider non-linear relationships between temperature and daily number of births across specific lag periods. RESULTS: We found that apparent temperature was associated with the daily number of births in Montreal, with a 1-day delay. We found an increase in births on hot days, and decrease on cold days, both offset by a harvesting effect after 4 and 5 days. CONCLUSIONS FOR PRACTICE: This study suggests that the number of births is affected by extreme temperatures. Obstetric and perinatal service providers should be prepared for spikes in the number of births caused by extreme temperatures.
OBJECTIVES: Temperature is a hypothesized determinant of early delivery, but seasonal and long term trends, delayed effects of temperature, and the influence of extreme cold temperatures have not yet been addressed. We aim to study the influence of apparent temperature on daily number of births, considering lag structures, seasonality and long term trends. METHODS: We used daily number of births in conjunction with apparent outdoor temperatures between 1981 and 2010 in Montreal. We used Poisson regression combined with a distributed lag nonlinear model to consider non-linear relationships between temperature and daily number of births across specific lag periods. RESULTS: We found that apparent temperature was associated with the daily number of births in Montreal, with a 1-day delay. We found an increase in births on hot days, and decrease on cold days, both offset by a harvesting effect after 4 and 5 days. CONCLUSIONS FOR PRACTICE: This study suggests that the number of births is affected by extreme temperatures. Obstetric and perinatal service providers should be prepared for spikes in the number of births caused by extreme temperatures.
Entities:
Keywords:
Apparent temperature; Obstetric and pediatric health planning; Time series analysis; Weather
Authors: Ashley Ward; Jordan Clark; Jordan McLeod; Rachel Woodul; Haley Moser; Charles Konrad Journal: Int J Biometeorol Date: 2019-07-31 Impact factor: 3.787