Sex differences in consequences of XXXX .

@entity4512 @entity1 @entity717 @entity158
STUDY DESIGN: Cross-sectional population-based study. OBJECTIVE: To study sex differences in consequences of @entity4512 ( @entity4512 ): limited functioning, work leave or disability, and healthcare use. SUMMARY OF BACKGROUND DATA: @entity4512 is a major public health problem in developed countries due to high prevalence rates and considerable consequences. There are indications that consequences of @entity4512 differ for @entity1 and @entity1 . METHODS: Data of a Dutch population-based study were used, limited to @entity1 25 to 64 years of age (n = 2517). Data were collected by a postal questionnaire. RESULTS: @entity1 with any @entity4512 report more healthcare use for @entity4512 , i.e., contact with a medical caregiver and use of medicines than @entity1 , while @entity1 report more @entity717 (ever in life) due to low back @entity158 only, irrespective of work status. None of the sex differences can be explained by age, household composition, educational level, smoking status, overweight, physical activity, and @entity158 catastrophizing. Older age was related to more limited functioning due to @entity4512 ( @entity1 ), @entity717 due to @entity4512 ( @entity1 ), and healthcare use due to @entity4512 ( @entity1 and @entity1 ). A one- @entity1 household was associated with @entity717 ( @entity1 ) and use of medicines ( @entity1 ). Low educational level was associated with limited functioning ( @entity1 ), work leave ( @entity1 ), contact with a medical caregiver ( @entity1 ), and @entity717 ( @entity1 and @entity1 ). Smoking was associated with limited functioning ( @entity1 ), work leave ( @entity1 ), and healthcare use ( @entity1 ). Physical inactivity was associated with limited functioning due to @entity4512 in @entity1 . @entity158 catastrophizing was associated with limited functioning, work leave, and healthcare use ( @entity1 and @entity1 ) and @entity717 ( @entity1 ). CONCLUSIONS: Consequences of @entity4512 show a slightly different pattern for @entity1 and @entity1 . @entity1 with any MPreport more healthcare use for @entity4512 , while @entity1 report more @entity717 due to low back @entity158 only. These sex differences can not be explained by general risk factors, but associations between these factors and consequences of @entity4512 show some sex differences.
