Laden F, Schwartz J, Speizer FE, Dockery DW. 2006. Reduction in fine particulate air pollution and mortality: extended follow-up of the Harvard Six Cities study. Am J Respir Crit Care Med 173:667–672.
Klemm RJ, Mason R. 2003. Replication of reanalysis of Harvard Six-City Mortality study. In: Revised Analyses of Time-Series of Air Pollution and Health. Special Report. Boston:Health Effects Institute, 165–172. Available: [accessed 8 May 2012].
Zanobetti A, Schwartz J, Samoli E, Gryparis A, Touloumi G, Atkinson R, et al. 2002. The temporal pattern of mortality responses to air pollution: A multicity assessment of mortality displacement. Epidemiology 13(1):87–93.
Yap C, Beverland IJ, Robertson C, Heal MR, Cohen GR, Henderson DEJ, et al. 2012. Association between long-term exposure to air pollution and specific causes of mortality in Scotland. Occup Environ Med; doi:.
We observed similar effects in the main analysis as compared with the extended analysis, which included DCH and EPIC-Oxford (see Supplemental Material, Figure S2, for PM2.5, NO2, and traffic load and systolic BP; not shown for other pollutants and diastolic BP; see also forest plots in main and extended meta-analysis with PM2.5 and BP in Supplemental Material, Figure S3). When restricting the analysis to cohorts with at least three consecutive BP measurements, we observed a positive association of PM2.5 with systolic BP in medicated participants and an increased estimate in nonmedicated participants (see Supplemental Material, Figure S2). No consistent differences by body position during measurement or by the BP recording device were observed.
Temperature data. We obtained daily averages of hourly temperatures from 0700–2300 hours at the UK meteorological office site at Glasgow airport, and calculated 3-, 7-, and 31-day temperature averages as for BS. We modeled temperature effects using a bilinear model which assumed a “knot” at 11°C with differential linear effects of temperature change below and above the knot, based on a previous analysis of temperature effects on mortality in the general population of Glasgow (). We did not adjust for spatial variation in temperature when estimating long-term effects because we assumed that relatively shallow spatial gradients in long-term average temperature would not confound air pollution–mortality associations.
Models for short-term pollution effects using centrally estimated exposures. Because there was only one monitoring site with adequate data for the whole study period, a conventional survival analysis model could not be used to study short-term effects as all cohort participants would have been assigned the same values for short-term pollution exposure at a given time.
The European Study of Cohorts for Air Pollution Effects (ESCAPE) project was designed to assess the long-term exposure of the population to air pollution and to investigate exposure–response relationships and thresholds for a number of adverse health outcomes (). Our objective was to estimate the association between long-term exposure to ambient air pollution, especially PM mass, black carbon, and nitrogen oxides, and the incidence of stroke in 11 European cohorts. A companion paper focusing on incident coronary events has been recently published ().
We therefore constructed nested case–control data sets as follows. For each death in a cohort, we considered controls selected randomly from among the cohort participants who lived at least as long as the case. Each control had an associated date, namely the date when the control reached the exact age at which the case died. If the control date was outside the follow-up period of the cohort, that control could not be used. We restricted controls to persons of the same sex who lived longer than the case, whose control date was in the same calendar month as the case death, and whose date of birth was within 1 calendar year of the date of birth of the case. Up to 9 controls were randomly selected from the full set available for each case. For all-cause deaths, 96% (8, 342/8, 700) of cases in the Renfrew–Paisley cohort and 76% (1, 160/1, 524) of cases in the Collaborative cohort had the full complement of 9 controls and 99% and 92%, respectively, had at least 4 controls. Six nested case–control data sets of this type were created for three case outcomes (all-cause, cardiovascular, and respiratory mortality) in the two cohorts. We then used conditional logistic regression to compare the pollution experienced by the case immediately before death and that experienced by controls of the same age in approximately the same time period and at approximately the same time of year, with adjustment for potential confounding variables measured at baseline: smoking history (six levels), social class (six levels), body mass index (five quintiles), marital status (four levels), systolic blood pressure (linear), and total cholesterol (linear). This conditional logistic regression model does not correspond to a survival model because generally different controls are in each case–control set. However, because of the correspondence between the likelihoods for proportional hazards and conditional logistic regression modeling (), the BS effect parameter, representing the ratio between the odds of being a case versus a control for a given increment in exposure, may be interpreted as an approximate estimate of the hazard ratio in a proportional hazards survival model where the level of BS exposure is age dependent.
Models for long-term pollution effects. Long-term exposures to BS were estimated for 1970–1979 using a multilevel spatiotemporal model that used a combination of time-series and spatial smoothing techniques to model monthly BS at 181 monitoring sites (across the central part of Scotland including the Glasgow conurbation) simultaneously taking into account seasonal effects and local air quality predictors including altitude (A), household density within a 250-m radius (HD), distance to nearest major road (MR), and distance to an urban boundary (UB) ():
Biological mechanisms linking long-term air pollution exposure to chronic damage of the cardiovascular system may include endothelial dysfunction and vasoconstriction, increased blood pressure, prothrombotic and coagulant changes, systemic inflammatory and oxidative stress responses, autonomic imbalance and arrhythmias, and the progression of atherosclerosis. On these bases, the American Heart Association delivered a scientific statement concluding that the overall evidence is consistent with PM playing a causal role in cardiac morbidity and mortality (). For cerebrovascular diseases, several studies have indicated the effects of short-term exposures potentially leading to ischemic stroke (; ). However, the evidence of a link between long-term exposure to air pollution and cerebrovascular events is less developed.