Revisiting a Population-Dynamic Model of Air Pollution and Daily Mortality of the Elderly in Philadelphia: Fid-Bau Portal

Revisiting a Population-Dynamic Model of Air Pollution and Daily Mortality of the Elderly in Philadelphia

Murray, Christian J. / Lipfert, Frederick W.

Epidemiological studies find that elderly, susceptible, and previously impaired individuals are more sensitive to transient air pollution exposures than healthy persons. However, any associated changes in life expectancy remain largely unresolved. Murray and Nelson published a model of daily mortality and air pollution that addresses mortality displacement or harvesting by directly considering population dynamics on the basis of the assumption that a period of illness or frailty precedes most elderly deaths. The underlying concept is that a person’s response to an environmental exposure also depends on his/her physiological ability to withstand stress at that time. They used Kalman filtering to estimate an unobservable quantity—the size of the frail subpopulation from which elderly (ages ≥65 yr) nontraumatic deaths are assumed to derive. They found a small subpopulation, relatively robust to environmental variations over 14 yr, with remaining life expectancies of 8–31 days in this frail status. Here, this model and dataset are expanded to examine the ramifications in more detail (including seasonality), to consider peak ozone as an additional pollutant, and to consider remaining life expectancies of the this frail subpopulation on a daily basis. Previous studies of mortality displacement and of Philadelphia mortality-air-pollution associations are also summarized in general, and agreement with the Murray-Nelson model was found, thus supporting its validity. The estimated additional mortality associated with a given environmental exposure persists for a few days at most but is not always compensated by subsequent mortality deficits. It is concluded that the pollution-associated mortality increases of a few percent in this dataset are consistent with losses of remaining life expectancy of up to a few days. It is also recommended that a more complex population-dynamic model be implemented to examine the extent to which previous short-term environmental exposures and seasonal trends may also influence morbidity and thus entry into the frail at-risk subpopulation.