tailieunhanh - Particulate Air Pollution and Daily Mortality in Kathmandu Valley, Nepal: Associations and Distributed Lag

Osteoporosis is a complex systemic skeletal disease that leads to an increased risk of fracture, usually of the vertebra, hip, wrist and humerus. The disorder is characterized by reduced bone mineral density (BMD), disrupted bone microarchitecture and alterations in the amount and variety of proteins in bone. During the last years a better understanding of the cellular mechanisms operating in bone remodeling, both for healthy and affected bones, was gained [26]. Bone turnover is a very complex process, depending on different genes and signaling pathways that coordinate osteogenesis, but also on other environmental factors. It is estimated that more than 60% of bone mass variance is determined by genetic factors [23]. Environmental factors account. | 62 The Open Atmospheric Science Journal 2012 6 Suppl 1 M2 62-70 Open Access Particulate Air Pollution and Daily Mortality in Kathmandu Valley Nepal Associations and Distributed Lag Srijan Lal Shrestha Central Department of Statistics Tribhuvan University Kirtipur Kathmandu Nepal Abstract The distributed lag effect of ambient particulate air pollution that can be attributed to all cause mortality in Kathmandu valley Nepal is estimated through generalized linear model GLM and generalized additive model GAM with autoregressive count dependent variable. Models are based upon daily time series data on mortality collected from the leading hospitals and exposure collected from the 6 six strategically dispersed fixed stations within the valley. The distributed lag effect is estimated by assigning appropriate weights governed by a mathematical model in which weights increased initially and decreased later forming a long tail. A comparative assessment revealed that autoregressive semiparametric GAM is a better fit compared to autoregressive GLM. Model fitting with autoregressive semi-parametric GAM showed that a 10 pg m-3 rise in PM10 is associated with increase in all cause mortality accounted for 20 days lag effect which is about times higher than observed for one day lag and demonstrates the existence of extended lag effect of ambient PM10 on all cause deaths. The confounding variables included in the model were parametric effects of seasonal differences measured by Fourier series terms lag effect of mortality and nonparametric effect of temperature represented by loess smoothing. The lag effects of ambient PM10 remained constant beyond 20 days. Keywords Ambient air pollution autoregressive GAM extended lag effect Kathmandu valley loess smoothing mortality statistical modeling. 1. INTRODUCTION Particulate air pollution is a major environmental risk factor that can aggravate many health hazards to human population. This has been established in many studies .

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