Abstract

Background: Knowledge about educational disparities in deaths from specific cancer sites is incomplete. Even more scant is information about time trends in educational patterns in specific cancer mortality. This study examines educational inequalities in Norway 1971–2002 for mortality in lung and larynx, colorectal, stomach, melanoma, prostate, breast and cervix uteri cancer. Methods: A data file encompassing all Norwegian inhabitants registered some time during 1971–2002 while aged 45–74 was constructed with linked information from administrative registers. During an exposure of more than 40 millions person-years, about 87 000 deaths in the analysed cancer types were registered. Absolute and relative inequalities during three periods were analysed by age-standardized deaths rates, hazard regression odds ratios and Relative Index of Inequality. Results: Educational inequalities in lung and related cancer mortality widened considerably from the 1970s to the 1990s for both sexes. The moderate educational gradient for stomach and cervix uteri cancer persisted, as did the weak gradient for colorectal cancer. No educational differences in prostate cancer were observed in any of the time periods. The modest inverse educational gradients in deaths from breast cancer and melanoma remained at the same level. Conclusion: Among the seven cancer types examined in this study, only lung cancer mortality showed a clear widening in educational disparities. As lung cancer mortality constitutes a large proportion of all cancer deaths, this increase may result in larger disparities for overall cancer mortality. Some explanations for the observed patterns in cancer mortality are suggested.

Introduction

Cancers cause a large proportion of the premature deaths in Europe,1 and cancers contribute to the patterns of socio-economic mortality inequalities, but in intricate and partly contradictory ways. Mortality from lung cancer in particular, but also from stomach and (among women) cervix uteri cancer have been found to be higher among low-educated persons.25 Mortality in breast cancer, a major cause of death among middle-aged women, is on the other hand usually found to be higher among the highly educated.24,6 Moreover, the socio-economic and educational gradient varies in several ways. Social differences in male lung cancer mortality appear large in Central and Eastern Europe and considerable in the Nordic countries. In several South European countries, however, studies have found a reversed educational gradient in women's lung cancer mortality.3,4,7,8 The educational gap in alcohol-related cancers seems on the other hand clearly larger in some South European countries than in North Europe.9 Adding all cancer deaths, educational disparities in overall cancer mortality during the 1990s among men were substantial in the North and West of Europe and even larger in Central and Eastern Europe,3 but in Slovenia and some Spanish provinces, overall cancer mortality among women was actually higher among the highly educated.24

A further addition to these complexities is that the socio-economic gradient changes over time, but not necessarily in a uniform manner. Increasing socio-economic disparities in lung cancer mortality have been observed in the USA,10 France,11 Norway12 and Australia,13 but not in Finland 1981–951,4 nor in Barcelona 1992–2003.15 As for breast cancer, a levelling off as regards the previous higher mortality among highly educated women has been observed in Finland16 and France.17 Among French men, increasing occupational inequalities occurred in mortality from upper aerodigestive tract cancers.11 A study from Barcelona found, on the other hand, only small changes over time in educational inequalities in mortality for a number of cancer sites.15 Several studies have suggested that socio-economic disparities in overall cancer mortality are on the increase,10,13,18,19 but a recent study from The Netherlands found actually a narrowing socio-economic gap in overall cancer incidence during 1996–2008.20

All in all, few studies have analysed how socio-economic inequalities in cancer mortality have evolved in recent decades. The aim of the present study is to increase knowledge about developments in educational inequalities in mortality from specific cancer sites. In Norway, overall cancer mortality among men increased moderately from the early 1970s to the mid-1980s, followed by a slight decline during the 1990s, while the overall cancer mortality rate among women has been quite stable during this period.21 Less is known about time trends in educational disparities for specific cancer types. Here, we analyse the three largest cancer types: lung and related sites, colorectal and prostate among men (53% of new cancer cases in 2005), and breast, colorectal and lung among women (47% of new cases in 2005).22 Furthermore, two cancers with declining incidence in recent decades (stomach, cervix uteri) and one with rising incidence (melanoma of the skin) are examined.

Methods

Data

For research purposes, a data file with anonymized individual information was constructed by Statistics Norway. Administrative registers covering the entire Norwegian population were linked by means of the personal identification number. Data utilized for this study encompass all inhabitants who were both registered as residing in Norway sometimes during 1971–2002 and aged 45–74 years sometime within that period. The Norwegian population in this age range numbered about 600 000 men and 650 000 women in the early 1970s, gradually increasing to about 640 000 men and 670 000 women in the late 1990s. For each individual, a series of 1-year observations was created, starting in 1971 or the year the person turned 45 years and ending either with the year of death, or with emigration, or by the year the person turned 75 years, or in 2002, whichever came first. Each observation included variables about the situation at the beginning of the year and an outcome variable indicating whether the person died that year from one of the seven analysed cancer types. The oldest individuals in the data were born in 1897 (i.e. age 74 in 1971), while the youngest were born in 1957 (and therefore 45 in 2002).

Measurements

Within each category, number of deaths for each cancer type and number of person-years were summarized for 1971–79, 1980–89 and 1990–2002. The classification of causes of death followed the European shortlist, using the ninth or tenth version of the International Classification of Disease (ICD).23 The following ICD codes were used: Cancer in larynx and lung, bronchus and trachea ICD-9 161–162 and ICD-10 C32–C34; colorectal ICD-9 153–154 and ICD-10 C18–C21; stomach ICD-9 151 and ICD-10 C16; melanoma of the skin ICD-9 172 and ICD-10 C43; prostate ICD-9 185 and ICD-10 C61; breast ICD-9 174–175 and ICD-10 C50; and cervix uteri ICD-9 180 and ICD-10 C53.

In addition to sex and age, information about highest educational level was obtained from the educational register after 1980 and from censuses of 1970 and 1980 with fairly comparable information for earlier years. A large expansion in education has occurred in Norway. University and similar higher education was quite rare among the oldest cohorts, especially among women, but became much more available among those born around the mid-20th century. For the present analyses, educational information was simplified into a three-level hierarchy—basic, secondary and tertiary education—ensuring sufficient number of deaths within each category and making our findings comparable to other studies.12 Basic (compulsory) education implies up to 7 years of schooling for the older cohorts and usually 9 years for those born since the late 1940s (9-year compulsory schooling was introduced in Norway during the 1960s). Secondary education comprises additional education above the compulsory level, up to 12 years in total length of education. Tertiary education comprises all levels above secondary, often college or university education, making total education duration about 13 years and more. Those very few (less than 0.1 %) lacking codifiable educational information were excluded from the analyses.

Statistical analysis

Following common practice,9,12,15,24 both absolute and relative educational inequalities are analysed. As to absolute differences, directly age-standardized mortality, i.e. deaths per 100 000 person-years, was estimated for each time period by summing number of person-years and number of deaths during the respective periods. Calculations were made for each gender and each educational level, separately for the seven cancer sites. The European standard population23 was used for age standardization. The age span 45–74 implies six 5-year categories, which were given the following weights, from the youngest (45–49) to the oldest (70–74): 0.219, 0.219, 0.188, 0.156, 0.125 and 0.093. The size of absolute educational disparities for each time period was calculated by subtracting mortality rates for basic and secondary education, respectively, from the mortality rate of tertiary education.

As to relative disparities, odds ratios (ORs) for deaths from one of the studied cancer types were calculated for secondary and basic education, relative to the reference category of tertiary education. Calculations were performed by discrete time hazard regression analysis (i.e. for each time period, logistic models were estimated from all 1-year observations with cause-specific deaths as the outcome variable and age, calendar year and education as independent variables).25

Furthermore, the Relative Index of Inequality (RII)24 was calculated for each gender and time period. The RII takes into account not only the relative mortality differences between educational levels, but also the relative size of the educational categories. This is particularly relevant for judging changes in relative disparities when the educational distributions change considerably over time, as is the case in this study. The RII is calculated by transforming the educational variable, an ordinal scale, into a ranked interval scale with values for each educational level indicating the mean proportion with higher education than that particular educational level. Given that 20% of the population have the highest, tertiary education, 30% have secondary and 50% have basic education, those with tertiary education will be coded 0.20/2 = 0.10; those with secondary education obtain the value (0.20 + 0.30/2 =) 0.35, and those with basic education get the value (0.20 + 0.30 + 0.50/2 =) 0.75.26 This transformed education variable assumes that educational resources can be ranked from zero to unity (from 0 to 1), and the underlying assumption is that the educational hierarchy is linearly associated with the outcome. When the new education variable is used as a predictor in the hazard regression models, the exponential of the coefficient [exp(b)] will indicate the relative difference in death risk between those with the hypothetical position of being at the very lowest end of the educational scale, compared to the hypothetical position of being ‘on the very top’ of the educational hierarchy.11

Results

All in all, the material comprises nearly 50 000 male deaths and close to 37 000 female deaths in the seven cancer types during 1971–2002 (table 1). Total exposure time was more than 20 million person-years for each gender. Among men, deaths from lung cancer and related sites were by far the most common among the studied cancers. Among women, deaths from breast cancer were the most frequent (about one-third of the studied deaths), followed by colorectal cancers, but by the 1990s, lung cancer deaths had become more frequent than colorectal cancer deaths among women. As regards age-standardized mortality, also shown in table 1, the most conspicuous changes from the 1970s to the 1990s are the increase in death rates from lung cancer among women, from 15 deaths per 100 000 person-years in 1971–79 to 48 in the 1990s, and the steady decline in death rates from stomach cancer during the same period from 48 to 23 for men and 23 to 11 among women. The increase during the 1970s in lung and larynx cancer death rates among men seemed to level off after the 1980s. The rates among men for colorectal and prostate cancers suggest a slight increase (from 41 to 51 and from 33 to 39, respectively). Several main cancers among women had a considerable stability in mortality rates during the observed period: Around 35–38 deaths per 100 000 person-years for colorectal cancer, and 54–57 for breast cancer. As for the lesser cancer types among women, the death rate went slightly up for melanoma and declined somewhat for cervix uteri cancer. In addition to the cancer deaths data, table 1 also shows how the population's educational level moved ‘upwards’ during these three decades.

Table 1

Descriptive statistics

 Men
 
Women
 
Period 1971–79 1980–89 1990–2002 1971–79 1980–89 1990–2002 
Number of person-years age 45–74 5 550 708 5 970 152 8 543 430 5 929 209 6 360 249 8 775 799 
No deaths (No), deaths per 100 000 person-years (MR), seven cancers No MR No MR No MR No MR No MR No MR 
        Lung and larynx 4794 80 7030 101 9205 103 978 15 2006 27 4542 48 
        Colorectal 2483 41 3525 50 4585 51 2382 35 3007 38 3705 38 
        Stomach 2896 48 2413 34 2050 23 1558 23 1270 16 1056 11 
        Melanoma of the skin 369 584 941 11 234 337 522 
        Prostate 2113 33 2896 38 3775 39       
        Breast       3593 57 3948 56 4928 54 
        Cervix uteri       980 16 913 13 841 
Education, percentage of person-years             
Tertiary 9.7 13.7 22.5 5.2 7.9 16.2 
Secondary 9.6 11.9 16.5 3.5 4.2 6.6 
Basic 80.8 74.4 60.9 91.3 87.9 77.3 
 Men
 
Women
 
Period 1971–79 1980–89 1990–2002 1971–79 1980–89 1990–2002 
Number of person-years age 45–74 5 550 708 5 970 152 8 543 430 5 929 209 6 360 249 8 775 799 
No deaths (No), deaths per 100 000 person-years (MR), seven cancers No MR No MR No MR No MR No MR No MR 
        Lung and larynx 4794 80 7030 101 9205 103 978 15 2006 27 4542 48 
        Colorectal 2483 41 3525 50 4585 51 2382 35 3007 38 3705 38 
        Stomach 2896 48 2413 34 2050 23 1558 23 1270 16 1056 11 
        Melanoma of the skin 369 584 941 11 234 337 522 
        Prostate 2113 33 2896 38 3775 39       
        Breast       3593 57 3948 56 4928 54 
        Cervix uteri       980 16 913 13 841 
Education, percentage of person-years             
Tertiary 9.7 13.7 22.5 5.2 7.9 16.2 
Secondary 9.6 11.9 16.5 3.5 4.2 6.6 
Basic 80.8 74.4 60.9 91.3 87.9 77.3 

Tables 2 and 3 report the time trends in educational inequalities. The most conspicuous change from the 1970s to the 1990s is the growing educational gradient in mortality for lung cancer (including larynx, bronchus, trachea). This can be seen for both sexes, both in absolute (table 2) and relative terms (table 3). In the 1970s, men with basic education had 22 more deaths per 100 000 person-years in lung and related cancers than men with tertiary education, a gap which increased to 59 in the 1990s. In the first time period, absolute inequalities in women's lung cancer deaths were negligible, but in the 1990s, women with basic education had a clearly higher death rate than women with higher education. The growing inequalities in lung cancer deaths are also reflected in relative differences. ORs for basic education were, for men and women, respectively, 1.37 and 1.12 in the 1970s and 2.02 and 2.17 in the 1990s. The RII increased from 1.17 to 2.78 for men and from 0.76 to 3.18 for women.

Table 2

Mortality rates (MRs) in each educational category and differences (Diff.) to tertiary education, men and women aged 45–74 years

 Men
 
Women
 
 1971–79
 
1980–89
 
1990–2002
 
1971–79
 
1980–89
 
1990–2002
 
 MR Diff. MR Diff. MR Diff. MR Diff. MR Diff. MR Diff. 
Lung and larynx             
    Tertiary 59  65  59  13  22  25  
    Secondary 96 +37 98 +33 92 +33 24 +11 32 +10 43 +18 
    Basic 81 +22 107 +42 118 +59 15 +2 28 +6 53 +28 
Colorectal             
    Tertiary 44  49  47  31  32  25  
    Secondary 46 +2 56 +7 55 +8 45 +14 39 +7 39 +14 
    Basic 41 −3 49 51 +4 35 +4 39 +7 39 +14 
Stomach             
    Tertiary 34  21  17  18  15   
    Secondary 40 +6 29 +8 19 +2 12 −6 11 −4 
    Basic 50 +16 37 +16 25 +8 23 +5 16 +1 11 +3 
Melanoma             
    Tertiary  11  12     
    Secondary 10 −1 13 +1 10 +6 +1 −2 
    Basic −2 −2 10 −2 −1 
Prostate             
    Tertiary 34  39  40        
    Secondary 38 +4 41 +2 37 −3       
    Basic 33 −1 37 −2 40       
Breast             
    Tertiary       62  63  59  
    Secondary       61 −1 64 +1 59 
    Basic       56 −6 55 −8 52 −7 
Cervix uteri             
    Tertiary          
    Secondary       12 +4 14 +9 +2 
    Basic       17 +9 14 +9 10 +5 
 Men
 
Women
 
 1971–79
 
1980–89
 
1990–2002
 
1971–79
 
1980–89
 
1990–2002
 
 MR Diff. MR Diff. MR Diff. MR Diff. MR Diff. MR Diff. 
Lung and larynx             
    Tertiary 59  65  59  13  22  25  
    Secondary 96 +37 98 +33 92 +33 24 +11 32 +10 43 +18 
    Basic 81 +22 107 +42 118 +59 15 +2 28 +6 53 +28 
Colorectal             
    Tertiary 44  49  47  31  32  25  
    Secondary 46 +2 56 +7 55 +8 45 +14 39 +7 39 +14 
    Basic 41 −3 49 51 +4 35 +4 39 +7 39 +14 
Stomach             
    Tertiary 34  21  17  18  15   
    Secondary 40 +6 29 +8 19 +2 12 −6 11 −4 
    Basic 50 +16 37 +16 25 +8 23 +5 16 +1 11 +3 
Melanoma             
    Tertiary  11  12     
    Secondary 10 −1 13 +1 10 +6 +1 −2 
    Basic −2 −2 10 −2 −1 
Prostate             
    Tertiary 34  39  40        
    Secondary 38 +4 41 +2 37 −3       
    Basic 33 −1 37 −2 40       
Breast             
    Tertiary       62  63  59  
    Secondary       61 −1 64 +1 59 
    Basic       56 −6 55 −8 52 −7 
Cervix uteri             
    Tertiary          
    Secondary       12 +4 14 +9 +2 
    Basic       17 +9 14 +9 10 +5 
Table 3

Odds ratio (OR) for educational categories relative to tertiary education, and Relative Index of Inequality (RII)

 Men
 
Women
 
 1971–79 1980–89 1990–2002 1971–79 1980–89 1990–2002 
 OR/RII (95%CI) OR/RII (95%CI) OR/RII (95%CI) OR/RII (95%CI) OR/RII (95%CI) OR/RII (95%CI) 
Lung and larynx       
    Tertiary 
    Secondary 1.59 (1.37–1.84) 1.52 (1.35–1.79) 1.59 (1.47–1.74) 1.77 (1.16–2.70) 1.51 (1.14–2.00 1.77 (1.50–2.13) 
    Basic 1.37 (1.21–1.54) 1.66 (1.51–1.82) 2.02 (1.89–2.17) 1.12 (0.82–1.54) 1.29 (1.05–1.57) 2.17 (1.92–2.45) 
    RII 1.17 (1.00–1.37) 1.85 (1.63–2.10) 2.78 (2.52–3.07) 0.76 (0.49–1.19) 1.18 (0.88–1.59) 3.18 (2.63–3.83) 
Colorectal       
    Tertiary 
    Secondary 1.04 (0.86–1.26) 1.16 (1.00–1.33) 1.16 (1.05–1.28) 1.47 (1.10–1.97) 0.83 (0.65–1.07) 1.19 (1.01–1.41) 
    Basic 0.92 (0.80–1.05) 1.00 (0.89–1.12) 1.07 (0.99–1.16) 1.13 (0.92–1.39) 1.03 (0.88–1.20) 1.17 (1.05–1.31) 
    RII 0.81 (0.66–1.00) 0.89 (0.76–1.04) 1.04 (0.92–1.18) 0.93 (0.69–1.26) 1.19 (0.93–1.53) 1.24 (1.03–1.48) 
Stomach       
    Tertiary 
    Secondary 1.18 (0.96–1.45) 1.36 (1.11–1.67) 1.15 (0.97–1.38) 0.67 (0.41–1.09) 0.73 (0.48–1.11) 1.03 (0.71–1.48) 
    Basic 1.46 (1.25–1.71) 1.73 (1.47–2.03) 1.55 (1.36–1.77) 1.29 (0.98–1.69) 1.11 (0.87–1.42) 1.49 (1.19–1.86) 
    RII 1.82 (1.46–2.27) 2.23 (1.78–2.79) 2.14 (1.74–2.62) 2.13 (1.36–3.35) 1.50 (1.00–2.23) 2.21 (1.52–3.22) 
Melanoma       
    Tertiary 
    Secondary 1.01 (0.65–1.56) 0.94 (0.69–1.29) 1.06 (0.87–1.29) 2.29 (1.14–4.62) 1.09 (0.57–2.07) 0.81 (0.52–1.25) 
    Basic 0.83 (0.59–1.15) 0.81 (0.64–1.03) 0.82 (0.70–0.97) 0.85 (0.48–1.48) 1.01 (0.66–1.53) 0.94 (0.73–1.20) 
    RII 0.68 (0.42–1.12) 0.69 (0.49–1.01) 0.67 (0.52–0.86) 0.32 (0.15–0.68) 0.96 (0.49–1.87) 0.96 (0.62–1.48) 
Prostate       
    Tertiary    
    Secondary 1.11 (0.90–1.37) 1.06 (0.90–1.24) 0.92 (0.81–1.03)    
    Basic 0.95 (0.81–1.12) 0.94 (0.83–1.06) 0.98 (0.90–1.07)    
    RII 0.83 (0.66–1.05) 0.84 (0.70–1.01) 1.01 (0.87–1.16)    
Breast       
    Tertiary    
    Secondary    0.98 (0.78–1.23) 1.02 (0.87–1.23) 0.98 (0.86–1.12) 
    Basic    0.90 (0.78–1.04) 0.87 (0.77–0.98) 0.88 (0.81–0.95) 
    RII    0.82 (0.65–1.04) 0.75 (0.62–0.91) 0.77 (0.67–0.89) 
Cervix uteri       
    Tertiary    
    Secondary    1.48 (0.85–2.58) 2.65 (1.58–4.45) 1.27 (0.85–1.89) 
    Basic    2.03 (1.36–3.01) 2.87 (1.91–4.30) 1.98 (1.55–2.54) 
    RII    2.92 (1.65–5.19) 3.38 (1.99–5.75) 3.39 (2.25–5.11) 
 Men
 
Women
 
 1971–79 1980–89 1990–2002 1971–79 1980–89 1990–2002 
 OR/RII (95%CI) OR/RII (95%CI) OR/RII (95%CI) OR/RII (95%CI) OR/RII (95%CI) OR/RII (95%CI) 
Lung and larynx       
    Tertiary 
    Secondary 1.59 (1.37–1.84) 1.52 (1.35–1.79) 1.59 (1.47–1.74) 1.77 (1.16–2.70) 1.51 (1.14–2.00 1.77 (1.50–2.13) 
    Basic 1.37 (1.21–1.54) 1.66 (1.51–1.82) 2.02 (1.89–2.17) 1.12 (0.82–1.54) 1.29 (1.05–1.57) 2.17 (1.92–2.45) 
    RII 1.17 (1.00–1.37) 1.85 (1.63–2.10) 2.78 (2.52–3.07) 0.76 (0.49–1.19) 1.18 (0.88–1.59) 3.18 (2.63–3.83) 
Colorectal       
    Tertiary 
    Secondary 1.04 (0.86–1.26) 1.16 (1.00–1.33) 1.16 (1.05–1.28) 1.47 (1.10–1.97) 0.83 (0.65–1.07) 1.19 (1.01–1.41) 
    Basic 0.92 (0.80–1.05) 1.00 (0.89–1.12) 1.07 (0.99–1.16) 1.13 (0.92–1.39) 1.03 (0.88–1.20) 1.17 (1.05–1.31) 
    RII 0.81 (0.66–1.00) 0.89 (0.76–1.04) 1.04 (0.92–1.18) 0.93 (0.69–1.26) 1.19 (0.93–1.53) 1.24 (1.03–1.48) 
Stomach       
    Tertiary 
    Secondary 1.18 (0.96–1.45) 1.36 (1.11–1.67) 1.15 (0.97–1.38) 0.67 (0.41–1.09) 0.73 (0.48–1.11) 1.03 (0.71–1.48) 
    Basic 1.46 (1.25–1.71) 1.73 (1.47–2.03) 1.55 (1.36–1.77) 1.29 (0.98–1.69) 1.11 (0.87–1.42) 1.49 (1.19–1.86) 
    RII 1.82 (1.46–2.27) 2.23 (1.78–2.79) 2.14 (1.74–2.62) 2.13 (1.36–3.35) 1.50 (1.00–2.23) 2.21 (1.52–3.22) 
Melanoma       
    Tertiary 
    Secondary 1.01 (0.65–1.56) 0.94 (0.69–1.29) 1.06 (0.87–1.29) 2.29 (1.14–4.62) 1.09 (0.57–2.07) 0.81 (0.52–1.25) 
    Basic 0.83 (0.59–1.15) 0.81 (0.64–1.03) 0.82 (0.70–0.97) 0.85 (0.48–1.48) 1.01 (0.66–1.53) 0.94 (0.73–1.20) 
    RII 0.68 (0.42–1.12) 0.69 (0.49–1.01) 0.67 (0.52–0.86) 0.32 (0.15–0.68) 0.96 (0.49–1.87) 0.96 (0.62–1.48) 
Prostate       
    Tertiary    
    Secondary 1.11 (0.90–1.37) 1.06 (0.90–1.24) 0.92 (0.81–1.03)    
    Basic 0.95 (0.81–1.12) 0.94 (0.83–1.06) 0.98 (0.90–1.07)    
    RII 0.83 (0.66–1.05) 0.84 (0.70–1.01) 1.01 (0.87–1.16)    
Breast       
    Tertiary    
    Secondary    0.98 (0.78–1.23) 1.02 (0.87–1.23) 0.98 (0.86–1.12) 
    Basic    0.90 (0.78–1.04) 0.87 (0.77–0.98) 0.88 (0.81–0.95) 
    RII    0.82 (0.65–1.04) 0.75 (0.62–0.91) 0.77 (0.67–0.89) 
Cervix uteri       
    Tertiary    
    Secondary    1.48 (0.85–2.58) 2.65 (1.58–4.45) 1.27 (0.85–1.89) 
    Basic    2.03 (1.36–3.01) 2.87 (1.91–4.30) 1.98 (1.55–2.54) 
    RII    2.92 (1.65–5.19) 3.38 (1.99–5.75) 3.39 (2.25–5.11) 

As regards the other cancer sites, however, changes in educational patterns were more modest. Educational differences in colorectal cancer deaths were quite small across the entire period, with a tendency, especially in the latter period, to lower death rates among tertiary educated, most visible among women. For prostate cancers, fairly stable in total death rate, educational differences were practically absent during the entire observation period and for breast cancer, the mortality disadvantages of higher educated women remained fairly unchanged. The decline in mortality from stomach cancer occurred in all educational categories. The absolute inequalities, especially for men, were slightly reduced, but the relative disadvantages of the lower educated continued by and large unchanged, indicated by the RII, which was 1.82 for men and 2.13 for women in the 1970s and 2.14 and 2.21, respectively, in the 1990s.

Estimations for cervix uteri and melanoma of the skin may be troubled by the relatively small number of deaths. During the entire period, lower educated women had higher death rates from cervix uteri cancer; the relative disparities seemed fairly stable, but a slight tendency to reduced absolute inequalities can be observed. A tendency to more unfavourable death rates from melanoma of the skin among highly educated men was observed during the entire observation period, but among women, the reversed educational gradient for melanoma which was vaguely noticeable in the 1970s, had disappeared by the 1990s.

Discussion

The most distinct finding in this study is that educational inequalities in mortality from lung and related cancer types increased substantially, both among men and women, from the 1970s to the late 1990s. For the six other analysed types of cancer, educational patterns in death rates changed comparatively little. As to stomach cancer for both sexes and cervix uteri cancer among women, the educational gradients in death rates continued without drastic changes. The weak educational gradient for colorectal cancer in the 1970s persisted fairly unchanged among men but with a slight widening among women. No definite educational differences for prostate cancer deaths could be established in any of the observation periods. Finally, a weak tendency to a reversed educational gradient, with higher death rates among the highly educated, was observed for breast cancer among women and for melanoma of the skin among men. Also this pattern remained fairly constant during the observation period.

Thus, only for lung and related cancer mortality could a substantial widening of inequalities be observed, but since lung cancer deaths constitute a considerable and, for women, increasing part of all cancer mortality, the growing educational gap for this death cause will tend to result in increasing educational gradients in overall cancer mortality.

The findings concur in many ways with recent results from comparable cross-sectional studies in Western Europe: very marked educational differences in lung and related cancer mortality (exception: women in parts of South Europe),24,7,8,14 moderate, but clear, disparities in deaths from stomach cancer and cervix uteri cancer,2,4,15 a quite weak educational gradient in colorectal cancer mortality,2,4,26 no inequalities in deaths from prostate cancer,2,4,15,26 and a modest reversed gradient for deaths in breast cancer.24,6 The present study found also a slight reversed educational gradient in deaths from melanoma of the skin, similar to the pattern observed in a Spanish study.27

The specific contribution of the present study is the examination of time trends. The finding of a marked widening of educational differences in lung cancer mortality is parallel to previous Norwegian12 and French observations,11 but somewhat at odds with Finnish comparisons between the 1980s and the 1990s1,4 and a Barcelona study for the 1992–2003 period.15 Our study displayed a rather stable, but modest, reversed gradient for breast cancer mortality, similar to the Finnish14and Barcelona15 studies, but deviating slightly from the French study suggesting a disappearance during 1968–96 of the reversed gradient.17 It seems that only two studies in Western Europe, from France11 and Barcelona,15 have fairly comparable data about trends in socio-economic differentials in mortality for the other cancer sites studied here. Our study confirms, by and large, their results of a considerable stability in the educational pattern of stomach, colorectal, prostate and cervix uteri mortality.

Interpretations

The main explanation for the trends in lung and related cancer mortality inequalities will most certainly be the trends in tobacco use. Since the 1970s, smoking has been reduced in Norway, but the decline started later among women than among men and has been much larger among the highly educated than among lower educated.28 The slight overall mortality increase from melanoma of the skin, as well as the modest reversed educational gradient, could well be related to the rising affluence in Norway in recent decades, which has led to more unhealthy sunbathing, first occurring among upper socio-economic strata.29 The decline in stomach cancer mortality, fairly parallel in all educational strata, could be related to historical changes in dietary factors affecting practically all social strata in the latter half of the 20th century.

The full explanation of the changes in and persistence of educational patterns in specific cancer mortality will certainly be complex. Cancer mortality is a function of incidence influenced by exposures to risk factors and perhaps some inherited factors,30 and survival that depends, among other things, on health service factors.31 Differences between educational groups in lifestyle trends may contribute to changing differentials in cancer incidence with subsequent effects on changes in mortality disparities. With respect to survival, studies from Norway32 as well as from other countries33,34 have shown socio-economic differentials, even after controls for cancer site and diagnostic severity. A possibility exists that improvements in cancer diagnostics and treatment, resulting in higher survival rates, tend to favour the more socio-economically advantaged because they are better positioned to acquire knowledge and gain access to improved medical opportunities.35 However, several patterns observed in the present study do not easily fit into such an explanation. For instance, 5-year survival in Norway for prostate cancer improved from 52% in the early 1970s to 78% in the late 1990s,22 but the present study did not find any increasing educational disparities in prostate cancer mortality during these decades.

Mass screening for cancers could potentially influence the patterns of educational inequalities in cancer deaths. In Norway, nation-wide cervix cancer screening started in 1995 and breast cancer screening was gradually implemented 1995–2004, but no other mass cancer screening programme has been introduced.36 Therefore, it is not likely that screening programmes have had any large impact on the developments of educational differentials in cancer deaths during the analysed period 1971–2002.

Strengths and limitations

This study is among the few analyses of trends since the 1970s in educational differences in specific cancer mortality, and it sheds light on some mortality patterns for which previous information is scant. The study has had access to an unusually large and unbiased material, analysing about 87 000 deaths and using register information, which covers practically every person in the selected age categories living in Norway during 1971–2002. Generally, data reliability is high and missing information is insignificant, but a possible source of error is the diagnostic information. To establish the main underlying cause of death is difficult when the disease history is complex. Sometimes, causes of death are ambiguously registered. Cervix uteri cancer deaths, for instance, poses a problem as cancers deaths classified as ‘uterus, unspecified’ are relatively frequent21 and an unknown proportion of them are probably cervix uteri. Moreover, low autopsy rates may lead to underreporting or misclassification of cancer deaths among persons who were not diagnosed when alive. In addition, diagnostic criteria will hardly remain constant across three decades.37 To what extent such bias impacts on results is difficult to estimate.

Funding

The present study has been financed by the authors' employers Norwegian Social Research (NOVA), Oslo, Norway; Department of Sociology and Human Geography, University of Oslo, Norway; and Department of Economics, University of Oslo, Norway.

Conflicts of interest: None declared.

Key points

  • Cancers contribute substantially to social variations in health, and educational inequalities in overall cancer mortality in Europe appear to have increased during recent decades.

  • Some studies have examined time trends in educational disparities for lung and breast cancer, but there are very few similar analyses for other types of cancers.

  • This study shows that the fairly moderate educational disparities in lung and related cancer mortality in Norway in the 1970s increased considerably, for both sexes, during the 1980s and 1990s.

  • The moderate educational gradient for stomach and cervix uteri cancer, and the weak gradient for colorectal cancer, underwent small changes during this period.

  • No educational differences in prostate cancer deaths were observed, and the modest reversed educational gradient in breast and melanoma deaths remained at the same level.

Acknowledgements

The topic of this study was addressed by R.T. in her master thesis, supervised by J.I.E. and T.H.L. and based on aggregate data prepared by Ø.K.

References

1
Bray
F
Coleman
MP
Alexe
D-M
Albrecht
T
McKee
M
The burden of cancer in Europe
Responding to the challenge of cancer in Europe
 , 
2008
Ljubljana
Institute of Public Health of the Republic of Slovenia
(pg. 
7
-
40
)
2
Huisman
M
Kunst
AE
Bopp
M
Educational inequalities in cause-specific mortality in middle-aged and older men and women in eight western European populations
Lancet
 , 
2005
, vol. 
365
 (pg. 
493
-
500
)
3
Mackenbach
JP
Stirbu
I
Roskam
AJR
, et al.  . 
Socioeconomic inequalities in health in 22 European countries
N Engl J Med
 , 
2008
, vol. 
358
 (pg. 
2468
-
81
)
4
Menvielle
G
Kunst
A
Stirbu
I
, et al.  . 
Educational differences in cancer mortality among women and men: a gender pattern that differs across Europe
Br J Cancer
 , 
2008
, vol. 
98
 (pg. 
1012
-
19
)
5
Aarts
MJ
Lemmens
VEPP
Louwman
MWJ
, et al.  . 
Socioeconomic status and changing inequalities in colorectal cancer? A review of the associations with risk, treatment and outcome
Eur J Cancer
 , 
2010
, vol. 
46
 (pg. 
2681
-
95
)
6
Strand
BH
Kunst
A
Huisman
M
, et al.  . 
The reversed social gradient: Higher breast cancer mortality in the higher educated compared to lower educated. A comparison of 11 European populations during the 1990s
Eur J Cancer
 , 
2007
, vol. 
43
 (pg. 
1200
-
7
)
7
Van der Heydena
JHA
Schaap
MM
Kunst
AE
, et al.  . 
Socioeconomic inequalities in lung cancer mortality in 16 European populations
Lung Cancer
 , 
2009
, vol. 
63
 (pg. 
322
-
30
)
8
Mackenbach
JP
Huisman
M
Andersen
O
, et al.  . 
Inequalities in lung cancer mortality by the educational level in 10 European populations
Eur J Cancer
 , 
2004
, vol. 
40
 (pg. 
126
-
35
)
9
Menvielle
G
Kunst
AE
Stirbu
I
, et al.  . 
Socioeconomic inequalities in alcohol related cancer mortality among men: To what extent do they differ between Western European populations?
Int J Cancer
 , 
2007
, vol. 
121
 (pg. 
649
-
55
)
10
Steenland
K
Henley
J
Thun
M
All-cause and cause-specific death rates by educational status for two million people in two American Cancer Society cohorts, 1959-1996
Am J Epidemiol
 , 
2002
, vol. 
156
 (pg. 
11
-
21
)
11
Menvielle
G
Leclerc
A
Chastang
JF
, et al.  . 
Changes in socioeconomic inequalities in cancer mortality rates among French men between 1968 and 1996
Am J Public Health
 , 
2007
, vol. 
97
 (pg. 
2082
-
7
)
12
Strand
BH
Groholt
EK
Steingrimsdottir
OA
Blakely
T
Graff-Iversen
S
Naess
O
Educational inequalities in mortality over four decades in Norway: prospective study of middle aged men and women followed for cause specific mortality, 1960-2000
BMJ
 , 
2010
, vol. 
340
 pg. 
c654
 
13
Turrell
G
Mathers
C
Socioeconomic inequalities in all-cause and specific-cause mortality in Australia: 1985-1987 and 1995-1997
Int J Epidemiol
 , 
2001
, vol. 
30
 (pg. 
231
-
9
)
14
Valkonen
T
Martikainen
P
Jalovaara
M
, et al.  . 
Changes in socioeconomic inequalities in mortality during an economic boom and recession among middle-aged men and women in Finland
Eur J Public Health
 , 
2000
, vol. 
10
 (pg. 
274
-
80
)
15
Puigpinos
R
Borrell
C
Antunes
JLF
, et al.  . 
Trends in socioeconomic inequalities in cancer mortality in Barcelona: 1992-2003
BMC Public Health
 , 
2009
, vol. 
9
 pg. 
35
 
16
Martikainen
P
Valkonen
T
Diminishing educational differences in breast cancer mortality among Finnish women: a register-based 25-year follow-up
Am J Public Health
 , 
2000
, vol. 
90
 (pg. 
277
-
80
)
17
Menvielle
G
Leclerc
A
Chastang
JF
Luce
D
for the EDISC group
Social inequalities in breast cancer mortality among French women: disappearing educational disparities from 1968 to 1996
Br J Cancer
 , 
2006
, vol. 
94
 (pg. 
152
-
5
)
18
Marang-van de Mheen
PJ
Smith
GD
Hart
CL
Gunning-Schepers
LJ
Socioeconomic differentials in mortality among men within Great Britain: time trends and contributory causes
J Epidemiol Community Health
 , 
1998
, vol. 
52
 (pg. 
214
-
8
)
19
Jemal
A
Ward
E
Anderson
RN
, et al.  . 
Widening of socioeconomic inequalities in US death rates, 1993-2001
PloS One
 , 
2008
, vol. 
3
 pg. 
e2181
 
20
Aarts
MJ
van der Aa
MA
Coebergh
JWW
Louwman
WJ
Reduction of socioeconomic inequality in cancer incidence in the South of the Netherlands during 1996-2008
Eur J Cancer
 , 
2010
, vol. 
46
 (pg. 
2633
-
46
)
21
CRN
Cancer in Norway 2009 - Cancer incidence, mortality, survival and prevalence in Norway
2011
Oslo
Cancer Registry of Norway
 
Available at: www.kreftregisteret.no/ (8 September 2011, date last accessed)
22
CRN
Cancer in Norway 2005 - Cancer incidence, mortality, survival and prevalence in Norway
2006
Oslo
Cancer Registry of Norway
23
Eurostat. Health statistics. Annex 1 Standard European population. Annex 2 Causes of death (European shortlist)
 
Available at: http://epp.eurostat.ec.europa.eu/ (28 December 2010, date last accessed)
24
Mackenbach
JP
Kunst
AE
Measuring the magnitude of socio-economic inequalities in health: an overview of available measures illustrated with two examples from Europe
Soc Sci Med
 , 
1997
, vol. 
44
 (pg. 
757
-
71
)
25
Allison
PD
Event history analysis. Regression for longitudinal event data
1984
Beverly Hills
Sage Publications
26
Menvielle
G
Leclerc
A
Chastang
JF
Luce
D
Socioeconomic inequalities in cause specific mortality among older people in France
BMC Public Health
 , 
2010
, vol. 
10
 pg. 
260
 
27
Fernandez
E
Borrell
C
Cancer mortality by educational level in the city of Barcelona
Br J Cancer
 , 
1999
, vol. 
79
 (pg. 
684
-
9
)
28
Lund M, Lindbak RL
Norwegian Tobacco Statistics 1973-2006. SIRUS Publications 3/2007
2007
Oslo
SIRUS - Norwegian Institute for Alcohol and Drug Research
29
Aase
A
Bentham
G
Gender, geography and socio-economic status in the diffusion of malignant melanoma risk
Soc Sci Med
 , 
1996
, vol. 
42
 (pg. 
1621
-
37
)
30
Martin-Moreno
JM
Magnusson
G
Coleman
MP
Alexe
D-M
Albrecht
T
McKee
M
The causes of cancer and policies for prevention
Responding to the challenge of cancer in Europe
 , 
2008
Ljubljana
Institute of Public Health of the Republic of Slovenia
(pg. 
41
-
68
)
31
Berrino
F
Capocaccia
R
Coleman
MP
Alexe
D-M
Albrecht
T
McKee
M
Survival of European cancer patients
Responding to the challenge of cancer in Europe
 , 
2008
Ljubljana
Institute of Public Health of the Republic of Slovenia
(pg. 
151
-
76
)
32
Kravdal
O
Social inequalities in cancer survival
Population Studies
 , 
2000
, vol. 
54
 (pg. 
1
-
18
)
33
Woods
LM
Rachet
B
Coleman
MP
Origins of socio-economic inequalities in cancer survival: a review
Ann Oncol
 , 
2006
, vol. 
17
 (pg. 
5
-
19
)
34
Kogevinas
M
Marmot
MG
Fox
AJ
Goldblatt
PO
Socioeconomic differences in cancer survival
J Epidemiol Community Health
 , 
1991
, vol. 
45
 (pg. 
216
-
9
)
35
Tehranifar
P
Neugut
AI
Phelan
JC
, et al.  . 
Medical advances and racial/ethnic disparities in cancer survival
Cancer Epidemiol Biomarkers Prev
 , 
2009
, vol. 
18
 (pg. 
2701
-
8
)
36
Haldorsen
T
Cancer in Norway 2009. Special issue: Cancer screening in Norway
2011
Oslo
Cancer Registry of Norway
 
Available at: www.kreftregisteret.no/ (8 September 2011, date last accessed)
37
Tretli
S
Robsahm
TE
Svensson
E
Trender i insidens og mortalitet av kreft i Norge: Beskrivelse og diskusjon [Time trends in cancer incidence and mortality in Norway]
Norsk Epidemiologi [Norwegian Journal of Epidemiology]
 , 
2001
, vol. 
11
 (pg. 
177
-
85
)

Comments

0 Comments