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  1. Rashid A, Tahir I
    J Cross Cult Gerontol, 2015 Mar;30(1):69-85.
    PMID: 25349019 DOI: 10.1007/s10823-014-9248-3
    The population of Malaysia is relatively young, due to this there is a dearth in research conducted among the elderly especially relating to depression. The aim of this study is to determine the prevalence and the predictors of severe depression among the elderly in Malaysia. A sample of 2005 older adults randomly selected from the Penang State government's list of elderly receiving aid participated in the study. The Geriatric Depression Scale was used to screen for depression. Socio-demographic, social support, disease, functional and other factors were looked at as possible predictor variables. The prevalence of severe depression was 19.2 %. Indians (aOR = 2.0), being married (aOR = 10.5), widowed & divorced (aOR = 5.2), having poor (aOR = 2.7) or moderate social support (aOR = 2.7), having no one (aOR = 2.9), relatives (aOR = 2.3) or religious figures & others (aOR = 1.9) as compared to a spouse as a source of emotional support, feeling extremely lonely (aOR = 3.4), not socially active (aOR = 2.3), cognitively impaired (aOR 2.5), activities limited due to illness or disability (aOR = 1.6) and poor sleep quality (aOR = 3.6) were significant predictor variables. The prevalence of severe depression was high. It is pertinent that older adults, especially those with risk factors identified in this study be screened for depression at every opportunity.
    Device, Questionnaire & Scale: Geriatric Depression Scale (GDS-30)
  2. Ozturk I, Sharif A, Godil DI, Yousuf A, Tahir I
    Eval Rev, 2023 Jun;47(3):532-562.
    PMID: 36632679 DOI: 10.1177/0193841X221149809
    Tourism is one of the important factors that can affect the environmental and economic situation of any economy. This study investigates the relationship between tourist arrivals and CO2 emission in the top 20 tourist destinations using data from quarterly observations from 1995 to 2018. A unique technique via quantile-on-quantile regression and Granger causality in quantiles was used. In particular, how the quantiles of tourist arrivals impact quantiles of CO2 emission was analyzed. The empirical results suggest a combination of both positive and negative effects of tourist arrivals and CO2 emission in most tourist destinations. Predominantly, at both high and low tails, in the USA, Spain, Hong Kong, and Austria, tourist arrival has a positive effect on CO2 emission, whereas in the case of Canada, France, Germany, Mexico, and Malaysia, the association was negative. On the other hand, China, Greece, Russia, Japan, Italy, South Korea, Thailand, and Turkey have both positive and negative effects of tourism on CO2 emissions at low and high tails. Tourism can be an important factor while formulating policy for environmental and climate aspects.
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