@article{(Open Science Index):https://publications.waset.org/pdf/10000381,
	  title     = {Air Pollution and Respiratory-Related Restricted Activity Days in Tunisia},
	  author    = {Mokhtar Kouki Inès Rekik},
	  country	= {},
	  institution	= {},
	  abstract     = {This paper focuses on the assessment of the air
pollution and morbidity relationship in Tunisia. Air pollution is
measured by ozone air concentration and the morbidity is measured
by the number of respiratory-related restricted activity days during
the 2-week period prior to the interview. Socioeconomic data are also
collected in order to adjust for any confounding covariates. Our
sample is composed by 407 Tunisian respondents; 44.7% are women,
the average age is 35.2, near 69% are living in a house built after
1980, and 27.8% have reported at least one day of respiratory-related
restricted activity. The model consists on the regression of the
number of respiratory-related restricted activity days on the air
quality measure and the socioeconomic covariates. In order to correct
for zero-inflation and heterogeneity, we estimate several models
(Poisson, negative binomial, zero inflated Poisson, Poisson hurdle,
negative binomial hurdle and finite mixture Poisson models).
Bootstrapping and post-stratification techniques are used in order to
correct for any sample bias. According to the Akaike information
criteria, the hurdle negative binomial model has the greatest goodness
of fit. The main result indicates that, after adjusting for
socioeconomic data, the ozone concentration increases the probability
of positive number of restricted activity days.
	    journal   = {International Journal of Environmental and Ecological Engineering},
	  volume    = {9},
	  number    = {2},
	  year      = {2015},
	  pages     = {111 - 119},
	  ee        = {https://publications.waset.org/pdf/10000381},
	  url   	= {https://publications.waset.org/vol/98},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 98, 2015},