Development and Application of Environmental Quality of Life Scale Among People Residing Near Three Types of Industrial Areas, Southern Thailand

To compare QOL among rural people living in three different industrial areas and one non-industrial area in southern Thailand. A questionnaire based on the WHOQOL-BREF with environmental assessment was initially developed. After consultation with experts and pilot study, it was tested to check internal reliability and further modified as necessary. The final version was then used to survey residents of three rural areas close to organic industries, a gas refinery, and an electricity power plant and residents from a non-industrial area. The developed scale has acceptable reliability coefficient (0.76). The overall QOL scores among those living in all study areas were high (mean > 3.75 out of 5). Only environmental QOL domain was slightly low (mean = 3.7) among these living close to the gas refinery area where people were distinctively disturbed by various types of pollution. Unpleasant odours were reported by residents living close to the power plant and areas of organic industries. After adjustment for age, education, income level and marital status, the residents of industrial areas were more than two times likely to have an unfavorable QOL. The level of pollution in the study industrial area should be reduced.     

A modified Cp statistic in a system-of-equations model

A new statistic, SΓ(p), is developed for variable selection in a system-of-equations model. The standardized total mean square error in the SΓ(p)statistic is weighted by the covariance matrix of dependent variables instead of the error covariance matrix of the true model as in the original definition. The new statistic can be also used for model selection in the non-nested models. The estimate of SΓ(p), SC(p), is derived and shown to become SC_ε(p) in the similar form of C_p in a single-equation model when the covariance matrix of sampled dependent variables is replaced by the error covariance matrix under the full model.