Psychosocial General Population Job Exposure Matrix (GPJEM)


Filenames: use syntax in LASA016

Contact: Dorly Deeg

Background: development and validation of a General Population Job Exposure Matrix (GPJEM)
General population job-exposure matrixes (GPJEMs) are cross-tabulations of occupations in a population with a list of work exposures (work demands or resources). GPJEMS have successfully been used in the past to determine work exposures and predict health effects in population surveys. However, no GPJEM exists linked to a Dutch occupational classification that determines physical and psychosocial work demands as well as psychosocial work resources. According to Karasek’s demands-control-support model (1), work stress results from a combination of psychosocial demands (time pressure, task requirements and cognitive demands), and psychosocial resources (the degree of control at work and social support received from supervisors or co-workers). The combination of high psychosocial demands (e.g. work at high pace), low control (e.g. not being able to decide when to perform tasks) and low variety in activities (e.g. learn new things) in jobs is considered to be most stressful and therefore labelled as ‘high job strain’. The burden and health effects of performing high strain jobs is increased if little social support is experienced, which is labelled as ‘high iso-strain jobs’.

Physical work demands and iso-strain jobs have been recognised as risk factors for decreased work ability (e.g. 2) and sickness absence (e.g. 3) and both may affect health. Physical work demands, such as using force at work, may cause wear and tear, musculoskeletal disorder, occupational injuries (4), or chronic diseases (5). Doing heavy work or lifting heavy object may result in knee and hip osteoarthritis (6). Studies suggest that high iso-strain jobs result in cardiovascular diseases (7) and high blood pressure, possibly directly through repeated stress experiences or indirectly through life style behaviours (8).

A  GPJEM including physical and psychosocial demands as well as psychosocial resources applicable to older and retired workers was developed (9) which is linked to the Netherlands Standard Classification of Occupations 1992 (NSCO92). This is the first Dutch General Population Job-Exposure Matrix (GPJEM) including physical and psychosocial work demands as well as psychosocial work resources applicable to older and retired workers (9).

The NSCO92 can be linked to other occupational classifications, e.g. the internationally used International Standard Classification of Occupations 2008 (ISCO08). This allows the use of the same GPJEM in case other occupational classifications are available. More information on how the linkage between NSCO92 and ISCO08 can be accomplished is available on:
http://www.cbs.nl/nl-NL/menu/methoden/classificaties/overzicht/sbc/isco/default.htm.

Physical and psychosocial work exposures reported by 55-64-year-olds were derived from the Netherlands Working Conditions Survey (10) and linked to the NSCO92. A JEM with low, moderate, and high probability of exposure to demands and resources was developed. The validity was evaluated by examining associations of physical demands and iso-strain (combination of high psychosocial demands and low resources) with health (9) Associations with health and other indicators of functioning were examined in two groups of the Longitudinal Aging Study Amsterdam: current (i.e. at the time of the interview; 55-64 years) and former workers (55-84 years) (9).

Measurement instruments in LASA
The JEM provides data on the probability of an occupational class to be exposed to the following ten exposures (i.e. variables):


The ten work exposures can be used separately. The reliability of the individual work exposure variables have been examined in the NWCS and was shown to be acceptable (α> 0.7) (3). In addition, the ten work exposures can be used as construct variables representing physical work demands (three items), psychosocial work demands (three items) and psychosocial work resources (four items). By combining psychosocial demands and psychosocial resources, exposure to iso-strain can be determined. The scale reliability of each construct variable was found to be acceptable for current and former workers interviewed in 1992-93 and 2002-03. For physical demands, psychosocial demands and psychosocial resources in current workers a Cronbach’s Alpha of 0.88, 0.91, 0.70, respectively,  was found and in former workers a Cronbach’s Alpha of 0.89, 0.90, 0.70, respectively, was found.

Availability of information per wave1
Occupational classes were classified as having a low, moderate and/or a high probability of exposure to demands and resources using a syntax. The NSCO92 (Netherlands Standard Classification of Occupations 1992 (11)) is used in the Longitudinal Aging Study Amsterdam in all waves except in 2012/2013 (wave 3B and MB), where the Netherlands Standard Classification of Occupations 2010 (NSCO10) is used. Therefore, the syntax is applicable to all waves except in 2012/13. Information on how the NSCO92 can be linked to NSCO10 is available on:
http://www.cbs.nl/nl-NL/menu/methoden/classificaties/overzicht/sbc/2010/default.htm.

For more information on the syntax to construct the variables representing physical work demands, psychosocial work demands and psychosocial work resources, please contact S. van der Pas.

Physical demands and  psychosocial demands and  resources 

B

C

D

E


2B*

F

G

H



3B*

MB*

I*

Current job: asked in all LASA waves (variable ‘*cjclass’) during Ma.

SX(1)

SX(1)

SX(1)

SX(1)

SX(1)

SX(1)

SX(1)

SX(1)

NSX

NSX

UC

Longest job:  asked only in LASA wave B (variable ‘bljclass’) during Ma.

SX(2)

.

.

.

.

.

.

.

.

.

UC

Last job: asked only in LASA wave 2B (variable ‘brlclass’) during Ma.

.

.

.

.

SX(3)

.

.

.

.

.

UC

1 More information is available on:   
http://www.lasa-vu.nl/data/lasa/sampleLASAdatacollection.html

* 2B=baseline second cohort;
   3B=baseline third cohort;
   MB=migrants: baseline first cohort (Under Construction);
   I=Under Construction (UC)

Empty cell: data not available in LASA

Ma: data was collected during main interview.

SX(1): syntax is available, but variable names need to be adapted depending on the wave to be examined. Names of variables in the existing syntax start with ‘x’ (i.e. xcjclass and xljclass).
NSX: syntax is not available because the Netherlands Standard Classification of Occupations 2010 (NSCO10) is used.
SX(2): syntax is available, but variable names need to be adapted from xljclass to bljclass.
SX(3): syntax is available, but variable names need to be adapted from xljclass to brlclass.

Previous use in LASA
The work demands variables have been examined as construct variables to determine whether they predict drop-out from the labor force in older workers with and without chronic disease (12). In addition, the work exposure variables may be examined separately, which has been done in a manuscript examining the relationship between work demands and memory complaints (13)

References

  1. Karasek RA, Theorell T. Healthy work: stress, productivity and the reconstruction of working life. New York (NY): Basic Books 1990.
  2. Van den Berg TIJ, Elders LAM, De Zwart BCH, Burdorf A. (2008) The effects of work-related and individual demands on the Work Ability Index: a systematic review. Occup Environ Med; 66: 211-20.
  3. Lund T, Labriola M, Bultmann U, Villadsen E. (2006) Physical work environment risk demands for long term sickness absence: prospective findings among a cohort of 5,357 employees in Denmark. BMJ; 332: 449–52.
  4. Chau N, Khlat M; Lorhandicap group. (2009) Strong association of physical job demands with functional limitations among active people: a population-based study in North-eastern France. Int Arch Occup Environ Health;82: 857–66.
  5. Aittomaki A, Lahlema E, Roos E, Leino-Arjas P, Martikainen P. (2005) Gender differences in the association of age with physical workload and functioning. Psychosocial demands at work and risk of depression: a systematic review of the epidemiological evidence. Occup Environ Med; 65: 438-45.
  6. Allen KD, Chen J, Calahan LF, Golightly YM, Helmick CG, Renner JB et al. (2010) Associations of occupational tasks with knee and hip osteoarthritis: The Johnston County Osteoarthritis Project. J Rheumatol; 37: 842-50.
  7. Kivimaki M, Nyberg ST, Batty GD et al.; IPD-Work Consortium. (2012) Job strain as a risk factor for coronary heart disease: a collaborative meta-analysis of individual participant data. Lancet; 380: 1491–7.
  8. Rosenthal T, Alter A. (2012) Occupational stress and hypertension. J Am Soc Hypertens; 6: 2–22.
  9. Rijs, K. J., Van der Pas, S., Geuskens, G. A., Cozijnsen, R., Koppes, L. L. J., van der Beek, A. J., & Deeg, D. J. H. (2014). Development and validation of a physical and psychosocial job-exposure matrix in older and retired workers. Annals of Occupational Hygiene, 58, 152-170.
  10. Koppes LLJ, de Vroome EMM, Mol MEM, et al. Nationale Enquête Arbeidsomstandigheden 2010: Methodologie en globale resultaten. [Netherlands Working Conditions Survey 2010: Methodology and overall results]. 2011. TNO, Hoofddorp.
  11. Statistics Netherlands [Centraal Bureau voor de Statistiek (CBS)] (2001). Netherlands Standard Classification of Occupations 1992. Edition 2001. [Standaard Beroepenclassificatie 1992. Editie 2001.] Heerlen; CBS, 2001.
  12. Boot, C.R.L., Deeg, D.J.H., Abma, T., Rijs, K.J., Van der Pas, S., Van Tilburg, T.G., Van der Beek, A. (2014). Predictors of having paid work in older workers with and without chronic disease: a 3-year prospective cohort study. Journal of Occupational Rehabilitation, 24, 563-572.
  13. Rijs KJ, Van den Kommer TN, Comijs HC, Deeg DJH. Prevalence and incidence of memory complaints in employed compared to non-employed aged 55-64 years and the role of employment characteristics. Submitted 2013.