OBJECTIVES: Regional differences in sick leave frequency and duration determinants were studied between different professions (sale and cleaning) in different regions in the Netherlands (Utrecht and South Limburg) and the influence of socio-cultural factors on those determinants was explored. MATERIALS AND METHODS: Employees in Utrecht and South Limburg were interviewed on work, individual and health characteristics. Sick leave data were obtained from the social fund. RESULTS: A statistic comparison of sick leave frequency and duration figures between the two professions in the two regions showed that for a part similar, and for another part different determinants were associated with sick leave. CONCLUSION: In Utrecht, socio-cultural influence was assumed for the perception of autonomy and in South Limburg for health complaints. As a consequence, nationwide interventions to reduce sick leave should take into account the potential effects of sociocultural factors on the type of sick leave determinants that predict sick leave per region.
OBJECTIVES: Regional differences in sick leave frequency and duration determinants were studied between different professions (sale and cleaning) in different regions in the Netherlands (Utrecht and South Limburg) and the influence of socio-cultural factors on those determinants was explored. MATERIALS AND METHODS: Employees in Utrecht and South Limburg were interviewed on work, individual and health characteristics. Sick leave data were obtained from the social fund. RESULTS: A statistic comparison of sick leave frequency and duration figures between the two professions in the two regions showed that for a part similar, and for another part different determinants were associated with sick leave. CONCLUSION: In Utrecht, socio-cultural influence was assumed for the perception of autonomy and in South Limburg for health complaints. As a consequence, nationwide interventions to reduce sick leave should take into account the potential effects of sociocultural factors on the type of sick leave determinants that predict sick leave per region.
Authors: Erik L Werner; Suzanne L Merkus; Silje Mæland; Maud Jourdain; Frederieke Schaafsma; Jean Paul Canevet; Kristel H N Weerdesteijn; Cédric Rat; Johannes R Anema Journal: BMJ Open Date: 2016-07-14 Impact factor: 2.692
Authors: Charlotte Björkenstam; Krisztina D László; Cecilia Orellana; Ulrik Lidwall; Petra Lindfors; Margaretha Voss; Pia Svedberg; Kristina Alexanderson Journal: BMC Public Health Date: 2020-05-14 Impact factor: 3.295