Psychosocial General Population Job Exposure Matrix (GPJEM)


Filenames: use syntax in LASA016

Contact: Dorly Deeg

Background: development and validation
General population job-exposure matrices (GPJEMs) are population-based cross-tabulations of occupations with work exposures (work demands or resources). GPJEMS have been used successfully 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.

Physical work demands include, for example, repetitive movements, use of force, and work in uncomfortable position. Psychosocial work demands include, for example, cognitive demands (e.g., intensive thinking, need to keep focused, requiring much concentration), task requirements (e.g., work hard, hectic work), and time pressure. Psychosocial work resources include, for example, variation in activities, degree of autonomy, and social support received from supervisors or co-workers.

According to Karasek’s demands-control-support model (Karasek and Theorell 1990), work stress results from a combination of psychosocial demands and psychosocial resources. 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., Van den Berg et al 2008) and sickness absence (e.g., Lund et al 2006) and both may affect health. Physical work demands, such as using force at work, may cause wear and tear, musculoskeletal disorder, occupational injuries (Chau et al 2009), or chronic diseases (Aittomaki et al 2005). Doing heavy work or lifting heavy objects may result in knee and hip osteoarthritis (Allen et al 2010). Studies suggest that high iso-strain jobs result in cardiovascular diseases (Kivimaki et al 2012) and high blood pressure, possibly directly through repeated stress experiences or indirectly through life style behaviours (Rosenthal and Alter 2012).

A GPJEM was developed including physical and psychosocial demands as well as psychosocial resources applicable to older and retired workers, linked to the Netherlands Standard Classification of Occupations 1992 (NSCO92) (Statistics Netherlands 2001). This is the first GPJEM including physical and psychosocial work demands as well as psychosocial work resources applicable to older and retired workers (Rijs et al 2014).

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 (Koppes et al 2011) and linked to the NSCO92. A GPJEM 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 (Rijs et al 2014). 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. In addition, the ten work exposures can be used as scales 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 reliability of each scale 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 Cronbach’s Alpha’s were found of 0.88, 0.91, and 0.70, respectively, and in former workers, Cronbach’s Alpha’s of 0.89, 0.90, and 0.70, respectively.

From wave 3B onwards, respondents are also asked about their perception of work demands (see Work perception).


Availability of information per wave 1
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 is used in LASA in all waves up to wave G. From wave H onwards (2011/2012), the Netherlands Standard Classification of Occupations 2010 (NSCO10) is used. This classification of occupations is translated back to the NSCO92, using a transition matrix of both classifications, so that the GPJEM can be derived from wave H onwards. The GPJEM syntax is available upon request, please contact P. Malhoe.

Physical demands and psychosocial demands and resources

B

C

D

E


2B*

F

G

H



3B*

MB*

I

J

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

SX92

SX92

SX92

SX92

SX92

SX92

SX92

SX10

SX10

SX10

SX10

SX10

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

SX92b

-

-

-

-

-

-

-

-

-

-

-

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

-

-

-

-

SX92b

-

-

-

SX10b

-

-

-

1 More information about the LASA data collection waves is available here.

* 2B=baseline second cohort;
   3B=baseline third cohort;
   MB=migrants: baseline first cohort (under construction)

Empty cells (-): data not available in LASA

Ma: data collected during main interview

SX92: syntax is available based on NSCO92; 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).
SX10: syntax is available based on NSCO10; 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).
SX92b: syntax is available, but variable names need to be adapted from xljclass to bljclass.
SX10b: syntax is available, but variable names need to be adapted from xljclass to brlclass.

Previous use in LASA
The work exposure variables were examined as scales to determine whether they predicted drop-out from the labor force in older workers with and without chronic disease (Boot et al 2014) and self-rated health following exit from the workforce (de Breij et al 2019). In the latter study, the same analytic methods were used to examine the association of work exposures and self-rated health in four other cohorts in Northwestern Europe, in which self-reported work exposures were available. The associations studied proved to be consistent for the GPJEM-derived and the self-reported exposures. A study of health trends in workers across the three LASA-cohorts (1993-2003-2013) showed that psychosocial resources were associated with an increasing trend in cognitive health (van der Noordt et al 2019). Furthermore, psychosocial demands and iso-strain were shown to predict incidence of memory complaints in older workers (Rijs et al 2015).

References

  1. Aittomaki A, Lahlema E, Roos E, Leino-Arjas P, Martikainen P. 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 2005; 65: 438-445.
  2. Allen KD, Chen J, Calahan LF, Golightly YM, Helmick CG, Renner JB et al. Associations of occupational tasks with knee and hip osteoarthritis: The Johnston County Osteoarthritis Project. J Rheumatol 2010; 37: 842-850.
  3. Boot CRL, Deeg DJH, Abma T, Rijs KJ, Van der Pas S, Van Tilburg TG, Van der Beek A. Predictors of having paid work in older workers with and without chronic disease: a 3-year prospective cohort study. Journal of Occupational Rehabilitation 2014; 24: 563-572.
  4. De Breij S, Qvist JY, Holman D, Mäcken J, Seitsamo J, Huisman M, Deeg DJH. Educational inequalities in health after work exit: the role of work characteristics. BMC Public Health 2019; 19(1): 1515.
  5. Chau N, Khlat M; Lorhandicap group. 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 2009; 82: 857-866.
  6. Karasek RA, Theorell T. Healthy work: stress, productivity and the reconstruction of working life. New York (NY): Basic Books 1990.
  7. Kivimaki M, Nyberg ST, Batty GD et al.; IPD-Work Consortium. Job strain as a risk factor for coronary heart disease: a collaborative meta-analysis of individual participant data. Lancet 2012; 380: 1491-1497.
  8. 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]. Hoofddorp: TNO, 2011.
  9. Lund T, Labriola M, Bultmann U, Villadsen E. Physical work environment risk demands for long term sickness absence: prospective findings among a cohort of 5,357 employees in Denmark. BMJ 2006; 332: 449–452.
  10. Rijs KJ, Van der Pas S, Geuskens GA, Cozijnsen R, Koppes LLJ, Van der Beek AJ, Deeg DJH. Development and validation of a physical and psychosocial job-exposure matrix in older and retired workers. Annals of Occupational Hygiene 2014; 58, 152-170.
  11. 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. PLoS ONE 2015; 10 (3): e0119192.
  12. Rosenthal T, Alter A. Occupational stress and hypertension. J Am Soc Hypertens 2012; 6: 2–22.
  13. 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.
  14. Van den Berg TIJ, Elders LAM, De Zwart BCH, Burdorf A. The effects of work-related and individual demands on the Work Ability Index: a systematic review. Occup Environ Med 2008; 66: 211-220.
  15. Van der Noordt M, Hordijk HJ, IJzelenberg W, Van Tilburg TG, Van der Pas S, Deeg DJH. Trends in working conditions and health across three cohorts of older workers in 1993, 2003 and 2013: a cross-sequential study. BMC Public Health 2019; 19(1): 1376.