OBJECTIVES: Our objectives were to describe the QOL and its determinants among software professionals of Kolkata, and to compare the same according to information technology (IT) and IT-enabled services (ITeS) sub-sectors. METHODS: An institution-based cross-sectional study was conducted among software professionals of Kolkata applying a two-stage stratified random sampling technique. The WHO QOL BREF questionnaire was administered along with a list of pertinent variables. RESULTS: Overall, the analysis for 338 software professionals (177 IT and 161 ITeS) clearly demonstrated significant differences between mean scores of these two sectors for each of the six outcome domains of WHO QOL BREF. Multilevel multivariate analysis outlined 13 significant predictors of QOL-four positive (age, regular fitness regimes, foreign placements and changing companies frequently) and the rest of the nine, negative (multiple sex partners, multiple addictions, extended working hours, night-shift duties, income, expenditure, carrying office work home, current illness and ITeS company type). CONCLUSIONS: Our study helps in obtaining a clear understanding of the multifaceted risk factors prevailing in this sector, the majority of which can be effectively addressed by specific health promotional interventions. A dedicated health policy is mandated at both government and company levels.
OBJECTIVES: Our objectives were to describe the QOL and its determinants among software professionals of Kolkata, and to compare the same according to information technology (IT) and IT-enabled services (ITeS) sub-sectors. METHODS: An institution-based cross-sectional study was conducted among software professionals of Kolkata applying a two-stage stratified random sampling technique. The WHO QOL BREF questionnaire was administered along with a list of pertinent variables. RESULTS: Overall, the analysis for 338 software professionals (177 IT and 161 ITeS) clearly demonstrated significant differences between mean scores of these two sectors for each of the six outcome domains of WHO QOL BREF. Multilevel multivariate analysis outlined 13 significant predictors of QOL-four positive (age, regular fitness regimes, foreign placements and changing companies frequently) and the rest of the nine, negative (multiple sex partners, multiple addictions, extended working hours, night-shift duties, income, expenditure, carrying office work home, current illness and ITeS company type). CONCLUSIONS: Our study helps in obtaining a clear understanding of the multifaceted risk factors prevailing in this sector, the majority of which can be effectively addressed by specific health promotional interventions. A dedicated health policy is mandated at both government and company levels.
Authors: Christopher W Herman; Shirley Musich; Chifung Lu; Stewart Sill; Joyce M Young; Dee W Edington Journal: J Occup Environ Med Date: 2006-09 Impact factor: 2.162
Authors: Galateja Jordakieva; Lovro Markovic; Walter Rinner; Isabel Santonja; Seungjune Lee; Alexander Pilger; Thomas Perkman; Igor Grabovac; Eva Schernhammer; Richard Crevenna; Kyriaki Papantoniou; Jasminka Godnic-Cvar Journal: Wien Klin Wochenschr Date: 2021-09-06 Impact factor: 2.275
Authors: Giridhara R Babu; Paulomi M Sudhir; Tanmay Mahapatra; Aritra Das; Mohanbabu Rathnaiah; Indiresh Anand; Roger Detels Journal: Indian J Occup Environ Med Date: 2016 May-Aug