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The European Journal of Public Health Advance Access published online on July 1, 2008
The European Journal of Public Health, doi:10.1093/eurpub/ckn055
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© The Author 2008. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Influence of physical, mental and intellectual development on disability in young Norwegian men

Hans Magne Gravseth1, Tor Bjerkedal2, Lorentz M. Irgens3,4, Odd O. Aalen5, Randi Selmer4 and Petter Kristensen1,6

1 National Institute of Occupational Health, Oslo, Norway
2 Institute of Epidemiology, Norwegian Armed Forces Medical Services, Oslo, Norway
3 Medical Birth Registry of Norway, Locus of Registry Based Epidemiology, Department of Public Health and Primary Health Care, University of Bergen, Bergen, Norway
4 Norwegian Institute of Public Health, Oslo, Norway
5 Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
6 Section of Preventive Medicine and Epidemiology, University of Oslo, Oslo, Norway

Correspondence: Hans Magne Gravseth, National Institute of Occupational Health, PO Box 8149 Dep, 0033 Oslo, Norway, tel: +47 23 19 51 00, fax: +47 23 19 52 00, e-mail: hmg{at}stami.no

Received February 21, 2008, accepted May 22, 2008


   Abstract
Top
 Abstract
Introduction
 Methods
 Results
 Discussion
 Supplementary material
 Acknowledgements
 References
 
Background: Few studies have examined the effects of educational level, intellectual performance, mental function, body mass index and height as well as their interrelationship on the risk of disability pension (DP), taking other life course factors into account. Methods: We linked several national registers, comprising the Medical Birth Registry, the Central Population Register, the Education Register, the Norwegian Labour and Welfare Organisation and the Norwegian Armed Forces Personnel Data Base, providing personal data on biological and social variables from childhood to young adult age. Participants were all males live born during the period 1967–76, followed up through 2003. Men were excluded who died, emigrated or were granted a DP until age 23 years (when follow-up started) and persons who did not become gainfully employed during the study period. Thus, the study population comprised 302 330 men, and the study outcome was being granted a DP after age 23 years. Results: 3651 men (1.2%) were granted a DP. The DP rate was inversely associated with both educational level and intellectual performance. The adjusted population attributable risks (PAR) values for these two variables were 47% and 35%, respectively. The effect of the other variables was modest. Over- and underweight and short stature were associated with DP, but the effect was largely reduced after adjusting for intellectual performance. Impaired mental function seemed to have an independent effect. Conclusion: Receiving an early DP is dependent on several factors acting at different stages of life, above all educational level and intellectual performance. High education can modify some of the effects of low intellectual performance.

Keywords: conscript data, disability, education, life course epidemiology, Norway


   Introduction
Top
 Abstract
 Introduction
Methods
 Results
 Discussion
 Supplementary material
 Acknowledgements
 References
 
In the Scandinavian as well as in other developed countries, the increasing incidence of disability pension (DP) among young persons has caused concern,1–3 partly due to economic considerations. Furthermore, being granted a DP (which in Norway must have a medical condition as the main cause, thus excluding primary social causes) frequently excludes the recipients permanently from normal social and productive life, causing humanitarian concerns. Disability pensioners also have a high mortality.4

In a previous study, we explored life course determinants for an early DP within a register-based cohort5 and identified low educational level as a major risk factor, but childhood factors also contributed, such as low birth weight, childhood disease, parents not being married and parental disability.

Also other factors from adolescence and early adulthood are of importance. Several studies on DP have included body mass index (BMI), and excess risk of disability has been found among obese persons6–11 and also among underweight.8,9,11 Fewer studies have included height as an independent variable, but data from the 1958 British birth cohort suggest short stature at age seven and, to a less extent, at age 33 to be a risk factor for disability in early adulthood.9 Also this relationship was found to be non-linear, with high risks for the tallest as well. A psychiatric diagnosis2 and low intellectual performance12 at conscript have also been found to be strong risk factors for a DP. However, several of the studies mentioned include only one, or, at most, two factors when explaining disability.

For the males in a previously established cohort, we have data on conscript test results, which allows an extension of our earlier analysis.5 Specifically, we have data on height and weight, intellectual performance and mental function. The purpose of the present study was to elaborate our work on determinants of an early DP. Especially, we wanted to focus on the impact of and relation between intellectual performance and educational level on DP as well as the contribution from height, BMI and mental function. Unlike in most other studies, the available data also made it possible to explore all these factors together and assess their interrelationship when taking biological and social factors from childhood into account. Figure 1 is a causal diagram showing how these factors could be interrelated.


Figure 1
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  		Figure 1 Causal diagram showing possible pathways leading to a DP

 

   Methods
Top
 Abstract
 Introduction
 Methods
Results
 Discussion
 Supplementary material
 Acknowledgements
 References
 
Participants and linking procedures
The study population included all 309 510 boys live born in Norway 1967–76, as registered by the Medical Birth Registry of Norway, who were alive and not emigrated in the year of their 23rd birthday. The Medical Birth Registry contains the 11-digit national identification number for the child (unit of analysis) and the parents, allowing linkage with the Central Population Register, the Education Register of Statistics Norway, benefit and income registries of the Norwegian Labour and Welfare Organisation and with the Norwegian Armed Forces Personnel Data Base. This linkage provided longitudinal data for the males and their parents, with annual updates through 2003. The Regional Committee for Medical Research Ethics has approved the study (Ref. no. S-06028).

We started follow-up in the calendar year of the males’ 23rd birthday. Persons excluded (N = 7180, 2.3% of the total), in categories not mutually exclusive, were persons who were granted a DP until the age of 23 years and persons not registered with an annual income above the limit entitling sickness absence compensation (corresponding to ~4000 euro in 2007) before a DP was granted or censorship occurred. This was to exclude the very youngest disability pensioners (mainly mentally retarded and multihandicapped) and other persons with no or only a marginal relation to working life. Income acquired before the age of 23 was not taken into consideration. After exclusions, 302 330 males remained for analysis.

Study outcome
The outcome variable was being granted a DP, as registered in the Norwegian Labour and Welfare Organisation 1991–2003. Thus, the recipients of a DP were 24–36 years of age, and the follow-up time was 4–13 years.

Independent variables
The registries provided information on several covariates, occurring at both early and later stages in life. From the Medical Birth Registry we had data on birth weight, birth order, birth year, mother's marital status at birth and whether father's identity was stated. Since later born babies tend to be heavier than first born, we standardized birth weight for birth order into z scores, i.e. mean birth weight for each birth order was assigned a 0 score, and the SD was 1. The Norwegian Labour and Welfare Organisation provided the following information: the persons’ basic and attendance benefits due to chronic childhood disease,13 annual income data and parental DP. The latter variable was divided into subsets according to the persons’ age when parents were granted a DP (0–6, 7–12 or 13–17 years) and into maternal or paternal disability. Income data were used for inclusion purposes only. The Central Population Register provided time of death or emigration of the persons and data on maternal marital status in the year of the persons’ 18th birthday. This information was combined with maternal marital status at birth (from the Medical Birth Registry) into the variable "Maternal marital status according to persons' age", with four categories: married both at birth and at age 18, unmarried both at birth and at age 18, divorced at age 18 (irrespective of status at birth) and one final category collapsing all other combinations. We also had information on educational level for the persons as well as for both parents, provided by the Education Register of Statistics Norway and based on the Norwegian standard classification of education NUS2000.14 In the main analyses, its nine levels were dichotomized into whether upper secondary education was completed at age 23 years or not (from now on named the high, and respectively the low-educated group). This cut-off point was chosen, as there was a quite distinct break in the DP proportion at this level, as shown in figure 1 in ref. 5. The 878 persons (0.3%) with missing data on educational level were coded as low educated. The indicated parental education refers to the parent with the highest educational level, in the year of the persons’ 16th birthday. Updates for parental and study persons’ education were available only through 2001.

Finally, the Norwegian Armed Forces Personnel Data Base provided results from conscript tests. Conscript is compulsory to all Norwegian men, usually taking place about age 18 or 19 years. However, 3–4% of the men do not meet, usually as a result of severe handicaps or congenital disorders. At conscript, men are tested for general intellectual performance, height and weight are measured, and a physician is giving an assessment of general mental function, to sort out whether the men are suited for military service or not. The test of intellectual performance that is used in Norway is highly correlated with the Wechsler Adult Intelligence Scale, the correlation was found to be 0.73 in a small sample.15 Intellectual performance is recorded in a stanine scale as single digits from 1 (lowest) to 9, the scores being normally distributed in the general population with mean = 5 and SD = 2.15 Height is measured to the nearest centimetre; we divided the population into eight height categories: ≤164, 165–169, 170–174, 175–179, 180–184, 185–189, 190–194 and ≥195 cm. From height and weight, we computed BMI, which was divided into four groups: <18.50 kg/m2 (underweight), 18.50–24.99 kg/m2 (normal weight), 25.00–29.99 kg/m2 (overweight) and ≥30.00 kg/m2 (obesity). The mental function variable was dichotomized according to whether any impairment of mental function was found or not.

The independent variables were grouped into three categories: background (year of birth, birth order), adjustment (birth weight, childhood disease benefit, maternal marital status, maternal and paternal disability and parental education) and study variables (intellectual performance, mental function, BMI and height at age 18 years and educational level at 23 years).

Statistical analysis
Stata/SE 9.2 software was used in the analysis. We considered causal pathways leading to a DP as illustrated in figure 1. Cox proportional hazards models were used for computing DP hazard ratios (HR) and the corresponding 95% confidence intervals (CI) for the study variables. According to the pathways outlined in figure 1, two different models were explored: Model 1, where we included the background variables, the adjustment variables and the conscript data, whereas in Model 2 we also included educational level. This made it possible to gauge the different factors’ mediation through education. To explore closer relations between combinations of intellectual performance and educational level and their influence on DP, we also performed a multi-variate regression analysis with a combined intellectual/educational level variable, defined by two levels of education and the nine levels of intellectual performance. ‘Delayed entry’ was used, i.e. persons entered the study in the year of their first income above the limit after start of follow-up. Individuals who died or emigrated during follow-up, which lasted until the end of 2003, were censored out. Throughout, missing values on independent variables were included in the models as separate categories.

We also computed crude and adjusted PAR and corresponding 95% CI for the study and adjustment variables. In the adjusted model, all independent variables were adjusted for. PAR is a function of the prevalence of a risk factor and of the strength of its association to the outcome and is thus an indicator of the proportional contribution to the population risk attributable to the factor, given the whole population have the risk of the reference category. PAR was computed using Poisson regression and Stata's aflogit procedure,16 the latter after excluding observations with missing data on the current variable. Dummy variables were used for all values except for the reference value.

Coefficients for the different pathways outlined in figure 1 were computed with the pathreg command in Stata.17 In this analysis, the full nine-level educational classification was used.


   Results
Top
 Abstract
 Introduction
 Methods
 Results
Discussion
 Supplementary material
 Acknowledgements
 References
 
The total number of persons with a DP in the study was 3651 (1.2%). A total of 5872 persons were censored due to emigration and 2146 due to death during follow-up. The total follow-up time was 2 516 789 person-years. The risk of DP was high at low levels of both education and intellectual performance (Supplementary figure 1). The DP proportion in the high- and low-educated groups was 0.5 and 2.6%, respectively (table 1). Of the total DPs 56% had psychiatric diagnoses.

Table 1 shows proportions and HRs for DP according to Model 1 and Model 2 for the study variables. DP was inversely associated with intellectual performance. Intellectual performance was the only conscript variable with a considerable change from Model 1 to Model 2. Impairment of mental function was identified as another important risk factor for DP. The DP proportion in men with impaired mental function (6.6%) was only exceeded by the proportion among men with the very lowest score at the intellectual performance test (6.8%). The association between BMI and DP was J-shaped, with excess risk for the underweight and the obese. Short stature also increased the risk.


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  		Table 1 Percentages and HR for DP according to educational level and various conscript data. Men born in Norway 1967–76 with follow-up from age 23 years through 2003

 
The analysis with the combined intellectual/educational level variable showed an almost 3-fold increased risk in low- vs. high-educated men with intellectual performance at the mean (score = 5). We also found that high-educated men with an intellectual performance 1 SD below the mean had similar risks as low-educated men with an almost top intellectual performance score (data not shown).

Table 2 shows the crude and adjusted PARs for the study and adjustment variables. The only two variables with any substantial contribution to the adjusted PAR were intellectual performance and educational level. Among the other study variables, mental function at conscript and height at conscript had considerable influence in the crude model, but especially for height, the influence was extensively diminished in the adjusted model. Seemingly, parental education was the most important adjustment variable according to the crude model, but the PAR appeared negative in the adjusted model. Also maternal marital status and birth weight seemed to play a role, but also their contribution to the PAR was noticeably diminished after adjustment.


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  		Table 2 Population risks of DP attributed to study factors and adjustment factors. Men born in Norway 1967–76 with follow-up from age 23 years through 2003

 
Figure 2 shows the results from the path analysis. This is a simplified model, where only the variables with a substantial contribution to the total DP burden according to the PAR estimates are included. There was a strong association between intellectual performance and educational level. Intellectual performance, mental function and educational level were negatively associated with DP. Multiplying the individual coefficients via education and comparing them with the direct pathway coefficients makes it possible to make rough assessments of degree of mediation. This shows that about one-third of the effect of intellectual performance on DP is mediated through educational level, whereas the corresponding calculation for mental function gives the result 1/35.


Figure 2
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  		Figure 2 Results of the path analysis. Men born in Norway 1967–76 with follow-up from age 23 years through 2003

 

   Discussion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
Supplementary material
 Acknowledgements
 References
 
The analyses showed that low intellectual performance and low educational level are the strongest risk factors for a DP during the first years of working life. Under- and overweight and short stature, all known risk factors, also had some importance, but their contribution to the population burden of DP was noticeably lowered when intellectual performance was adjusted for. The effect of impaired mental function was intermediate strong and seemed to be independent.

The main strengths of the study are the large size of the study population and the nearly complete follow-up. The comprehensive and high-quality Medical Birth Registry as well as other national registers, together with the national identification number assigned to all residents, make the Scandinavian countries a well suited arena for life course research with individual data. One objection against the conscript data, especially the intellectual performance test, has been that some young men might simulate, i.e. they pretend they have a low intellectual performance, in order to avoid military services. However, Supplementary figure 1 shows a reassuring and consistent pattern, contradicted by only two subgroups: those with education at the university level (Level 5) and a 1 or 2 score at the intellectual performance test. This was the case with only 44 persons, none of whom were granted a DP.

Shortcomings comprise lack of variables. There might be several other mediators, confounders and effect modifiers than those outlined in figure 1. Probably, some mediators exist on the pathway from educational level to DP, like family conditions and work conditions/occupation. Other variables on personal characteristics might be relevant, like coping behaviour, which could have shed more light on the mechanisms behind the associations. Coping could also affect—and be affected by—educational level. In a recent Norwegian study, poor mastering, a related personal characteristic, was found to be associated with DP.18 Persons with missing conscript data represent another problem and are particularly related to less favourable outcomes; thus, they represent a highly selected and vulnerable group. However, the proportion with missing data was low, except for on the intellectual performance test (7.1%).

Based on the PAR analyses, one could argue that most of the DP could be attributed to low intellectual performance, low educational level and to some extent impaired mental function. Concerning the interrelationship between intellectual performance and educational level, the findings from the analyses on intellectual performance in the two strata of educational level are interesting and might be taken advantage of in schemes of prevention. Intellectual performance, an important predictor for a professional career,19 is probably not modifiable, as opposite to educational level. In this sense, education could be looked upon as a resilience factor, i.e. a factor that reflects a positive adaptation to an adverse background,20 and an effect modifier. The results suggest that the largest part of this effect is achieved already at a completed secondary education, with only a small additional contribution from tertiary education.

The J-shaped relation between BMI and DP is in concordance with several other studies8,9,11 and seems well established. One study has claimed the relation to be linear;6 however, the lowest BMI group in that study consisted of values below 22.5, and any excess risk among underweight would probably not be recognized. Thus, the on-going worldwide increase in the prevalence of obesity21 represents a major challenge to the prevention of disability.

A moderately increased DP risk was observed for short men. The finding from the 1958 British birth cohort of high risk even for tall stature was said to need confirmation in other studies. Our data suggest that this might be the case among Norwegian men as well; we see a non-significant trend in this direction in table 1. Body height can be looked upon as a rough proxy for socio-economic conditions during childhood, whereas the higher risk in the tallest may reflect a propensity of tall persons to musculoskeletal problems and probably also to cancer.9,22,23 We made a comparison of diagnoses between the tallest disability pensioners (≥190 cm) and the rest and found a higher proportion of musculoskeletal diagnoses for the tallest group (P = 0.2, data not shown).

The negative PAR for parental educational level in the adjusted model needs some clarification. This is related to our previous finding of high DP rate in low-educated men with highly educated parents5 and could be interpreted as another example of adverse outcome related to downward intergenerational social mobility.24 It could also be interpreted as a regression towards the mean-phenomenon, analogous to Francis Galton's original example.25

The study increases our understanding of the underlying causes of an early DP. It shows that early life experience is important and so is intellectual performance, mental function and anthropometrical measures established at conscript age. The adverse effects of an unfavourable profile at this stage might however be modified through attaining a certain educational level, which together with intellectual performance constitutes the dominating predictors, most other study variables’ importance being considerably reduced in adjusted models. Due to the often-observed gender differences in DP, future research should include both genders to explore these matters further. It should also focus on the personal characteristics that might be responsible for the mechanisms.


   Supplementary material
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Supplementary material
Acknowledgements
 References
 
Supplementary material is available at eurpub online.


   Acknowledgements
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Supplementary material
 Acknowledgements
References
 
The study was supported financially by grants from the Norwegian Research Council (Project no. 161321/V50) and from The Directorate of Labour Inspection. This work should be attributed to National Institute of Occupational Health.

Conflicts of interest: None declared.


Key points

  • Low educational level and low intellectual performance have a high power of predicting DP, also after taking other risk factors, such as over- and underweight, short stature and impaired mental function, into account.
  • The effect of most other risk factors diminishes largely after adjusting for intellectual performance; however, impaired mental function seemed to have an independent effect.
  • High education can modify some of the adverse effects of low intellectual performance.
  • Low educational level, low intellectual performance and impaired mental function seem to be markers of increased risk of DP in early adulthood. Interventions for prevention should be especially targeted to these groups.

 


   References
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Supplementary material
 Acknowledgements
 References
 
1 Gjesdal S, Lie RT, Maeland JG. Variations in the risk of disability pension in Norway 1970–99. A gender-specific age-period-cohort analysis. Scand J Public Health (2004) 32:340–8.[Abstract/Free Full Text]

2 Upmark M, Hemmingsson T, Romelsjo A, et al. Predictors of disability pension among young men – the role of alcohol and psychosocial factors. Eur J Public Health (1997) 7:20–8.[Abstract/Free Full Text]

3 OECD. Transforming Disability into Ability (2003) Paris: OECD.

4 Karlsson NE, Carstensen JM, Gjesdal S, Alexanderson KAE. Mortality in relation to disability pension: Findings from a 12-year prospective population-based cohort study in Sweden. Scand J Public Health (2007) 35:341–7.[Abstract/Free Full Text]

5 Gravseth HM, Bjerkedal T, Irgens LM, et al. Life course determinants for early disability pension: a follow-up of Norwegian men and women born 1967–1976. Eur J Epidemiol (2007) 22:533–43.[CrossRef][Web of Science][Medline]

6 Rissanen A, Heliovaara M, Knekt P, et al. Risk of disability and mortality due to overweight in a Finnish population. Br Med J (1990) 301:835–7.[Abstract/Free Full Text]

7 Narbro K, Jonsson E, Larsson B, et al. Economic consequences of sick-leave and early retirement in obese Swedish women. Int J Obes Relat Metab Disord (1996) 20:895–903.[Web of Science][Medline]

8 Mansson NO, Eriksson KF, Israelsson B, et al. Body mass index and disability pension in middle-aged men—non-linear relations. Int J Epidemiol (1996) 25:80–5.[Abstract/Free Full Text]

9 Power C, Li L, Manor O. A prospective study of limiting longstanding illness in early adulthood. Int J Epidemiol (2000) 29:131–9.[Abstract/Free Full Text]

10 Mansson NO, Merlo J. The relation between self–rated health, socioeconomic status, body mass index and disability pension among middle-aged men. Eur J Epidemiol (2001) 17:65–9.[CrossRef][Web of Science][Medline]

11 Karnehed N, Rasmussen F, Kark M. Obesity in young adulthood and later disability pension: a population-based cohort study of 366,929 Swedish men. Scand J Public Health (2007) 35:48–54.[Abstract/Free Full Text]

12 Upmark M, Lundberg I, Sadigh J, Bigert C. Conditions during childhood and adolescence as explanations of social class differences in disability pension among young men. Scand J Public Health (2001) 29:96–103.[Abstract/Free Full Text]

13 Bjerkedal T, Thune O. Grunn- og hjelpestønad til barn – omfang og medisinske årsaker (Basic and attendance benefits to children – extent and medical causes). Tidsskr Nor Laegeforen (1994) 114:1941–5. (in Norwegian with English abstract).[Medline]

14 Statistics Norway. Norsk standard for utdanningsgruppering (Norwegian standard classification of education) (in Norwegian). (2003) Oslo-Kongsvinger: Statistics Norway. Revised 2000.

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16 Greenland S, Drescher K. Maximum likelihood estimation of the attributable fraction from logistic models. Biometrics (1993) 49:865–72.[CrossRef][Web of Science][Medline]

17 Stata. (accessed on 21 April 2008). http://www.ats.ucla.edu/stat/Stata/faq/pathreg.htm.

18 Valset K, Naper SO, Claussen B, Dalgard OS. Does mastering have an effect on disability pensioning independent of health, and may it explain divides of education in the Oslo Health Survey? Scand J Public Health (2007) 35:157–63.[Abstract/Free Full Text]

19 Nettle D. Intelligence and class mobility in the British population. Br J Psychol (2003) 94:551–61.[CrossRef][Web of Science][Medline]

20 Luthar SS. Resilience in development: a synthesis of research across five decades. In: Developmental psychopathology: risk, disorder, and adaption—Cicchetti D, Cohen DJ, eds. (2006) Vol. 3, 2nd. New York: Wiley. 739–95.

21 Visscher TL, Seidell JC. The public health impact of obesity. Annu Rev Public Health (2001) 22:355–75.[CrossRef][Web of Science][Medline]

22 Dempsey PG, Burdorf A, Webster BS. The influence of personal variables on work-related low-back disorders and implications for future research. J Occup Environ Med (1997) 39:748–59.[CrossRef][Web of Science][Medline]

23 Gunnell DJ, Davey SG, Frankel S, et al. Childhood leg length and adult mortality: follow up of the Carnegie (Boyd Orr) Survey of Diet and Health in Pre-war Britain. J Epidemiol Community Health (1998) 52:142–52.[Abstract]

24 Glendinning A, Love JG, Hendry LB, Shucksmith J. Adolescence and health inequalities: extensions to Macintyre and West. Soc Sci Med (1992) 35:679–87.[CrossRef][Web of Science][Medline]

25 Galton F. Regression towards mediocrity in hereditary stature. J Anthropol Inst (1886) 15:246–63.


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