Acknowledgements

The work on cancer mortality in European populations was conducted as part of the Lifepath project, which benefited from financial support from the European Commission (Horizon 2020 grant no. 633666). Data were collected partly for the DEMETRIQ project, which also received support from the European Commission (grant no. FP7-CP-FP and 278511). The authors gratefully acknowledge the contribution of collaborators in the participating countries who helped to collect and harmonize the data.

Box

Key points.

Introduction

As well as the large variations in cancer incidence, survival, and mortality that are observed between countries (see Chapter 5), stark and consistent inequalities in cancer also exist between groups and individuals living within the same country. Socioeconomic inequalities in cancer incidence, survival, and mortality have been reported from all high-income countries (HICs) in which information on education level, occupational class, income, or other indicators of socioeconomic status (SES) is available and has been investigated in relation to cancer, as recorded in cancer or cause-of-death registries. These associations are subject to substantial variability, not only across the different cancer types but also between countries and over time.

In this chapter, these issues are illustrated by reviewing and analysing a unique collection of data on inequalities in cancer mortality rates by education level in 17 European countries over the period 1980–2015. In addition, a summary overview was undertaken of the literature currently available on socioeconomic inequalities in cancer in HICs and low- and middle-income countries (LMICs).

Cancer mortality data in European populations

Cancer mortality data by education level in 17 European countries were collected and harmonized within the framework of two European collaborative studies: Developing Methodologies to Reduce Inequalities in the Determinants of Health (DEMETRIQ; Gregoraci et al., 2017) and Lifepath (Stringhini et al., 2017; Vineis et al., 2017). A key feature of these data is that information on cancer mortality by education level is available for the entire population in most of the study countries. Social inequalities in cancer mortality and the corresponding 95% confidence intervals (CIs) were quantified by calculating the ratio of the age-standardized rates for individuals with a low education level (LEL) to those for individuals with a high education level (HEL) in each country. Country-specific and pooled estimates were estimated for 18 cancer types (see Box 6.1).

Box 6.1

On the mortality data (DEMETRIQ/Lifepath).

Time trends

The remarkable inequalities described above are the result of major trends over time. Cancer mortality among HEL groups of men and women has almost universally declined, but trends in cancer mortality over the past decades have generally been more favourable among HEL groups than among LEL groups, for which cancer mortality rates have often remained stable or even increased (Fig. 6.3). For all cancers combined, annual percentage declines as well as absolute declines (not shown) were considerably larger among HEL individuals versus LEL individuals, particularly among women (Fig. 6.4), meaning that both relative and absolute inequalities in cancer mortality have risen in many countries. However, inequalities in cancer mortality have reversed in some countries, for example Estonia and Hungary, from higher mortality among HEL groups in the early 1990s to higher mortality among LEL groups in the early 2010s (Fig. 6.3). Because cardiovascular disease mortality has declined at a greater rate and more uniformly than cancer mortality has (Bray et al., 2012; Torre et al., 2015; Townsend et al., 2016), among both HEL men and women and LEL men and women, inequalities in cardiovascular disease mortality have declined in many countries. Cancer has therefore become relatively more important as a cause of inequalities in total mortality in several populations, for example, among men in Austria, Belgium, England and Wales, Italy, Spain, and Switzerland, and among women in England and Wales, Italy, and Norway (results not shown).

Fig. 6.3

Trends of age-standardized all-cancer mortality rates (European Standard Population) in deaths per 100 000 person-years in 17 European countries, using data from 1990–2012. The graphs show mortality rates for men (upper) and women (lower) (more...)

Fig. 6.4

Annual percentage change in age-standardized mortality rates from all cancers and specific cancer types in 17 European countries for men (blue) and women (red) with a low education level (vertical axis) plotted against those with a high education level (more...)

The magnitude and even the direction of temporal trends for groups with different education levels differ by cancer type, however. Declines were observed in most countries for several cancer types in both HEL and LEL groups, but were often greater in HEL groups, for example, cancer of the breast in women and cancers of the prostate, colorectum, and lung in men. Cervical cancer mortality rates decreased in both HEL and LEL groups in certain countries, but also increased in LEL groups in other countries. General declines were also observed for stomach cancer mortality rates, often more favourable to LEL groups versus HEL groups in some countries, but increases were also observed in HEL groups in other countries. Mixed trends in liver cancer mortality rates were observed, with increases for both HEL and LEL groups in several countries. Lung cancer mortality has generally increased among women, but more so among LEL groups versus HEL groups. The patterns described above are quite general, however; it is important to acknowledge that trends in specific cancer types may vary in magnitude and sometimes even in direction across different countries (Fig. 6.4).

Evidence of social inequalities in cancer within HICs

This section integrates the information provided above on social inequalities in cancer mortality in Europe with the most recent and highest-quality available evidence on social inequalities in cancer incidence in countries classified as HICs by the World Bank (2018a). Several searches were undertaken in PubMed to identify key systematic reviews, meta-analyses, or significant cohort studies (published in the past 10 years) that focused on cancer incidence in relation to SES. Articles were reviewed, and data in relation to HICs or HIC groupings were abstracted.

Four cohort studies that investigated associations between SES and risk of cancer incidence (in all sites and across subsites) were identified: one in North America and three in European countries. Table 6.1 presents the data from these cohort studies on the risk associations by sex of LEL versus HEL groups (note that all cohort studies investigated multiple measures of SES; only education level is reported here). Despite the different definitions of cancer used and differences in modelling approaches, the four cohort studies observed increased risks of cancer incidence for both sexes for LEL groups relative to HEL groups (Dalton et al., 2008; Mouw et al., 2008; Spadea et al., 2010; Sharpe et al., 2014). Across all cohort studies, those with the lowest levels of education had higher risks of cancers of the lung, upper aerodigestive tract, stomach, and cervix uteri relative to those with the highest levels of education. In contrast, LEL groups generally had a lower risk of cancers of the skin, prostate, and breast.

Table 6.1

Summary of results from selected cohort studies from high-income countries: relative risk of incidence of specific cancer types for those with a low education level compared with those with a high education level.

In addition to the four large cohort studies described above, there is a large body of evidence (usually in the form of case–control studies) from HICs investigating the relationship between SES and cancer incidence by cancer site. These studies are often collated within systematic reviews and are usually combined with meta-analyses, or in pooled data consortia. Data were abstracted from these studies by cancer type for HICs (Table 6.2). Unadjusted (or minimally adjusted) pooled estimates of the risk associations for LEL groups relative to HEL groups, or other SES measure where education level was not available, are shown (note again that some of these studies reported multiple measures of SES, although only data on education level are included here). In agreement with the results from the four cohort studies described above, the incidence of cancers of the lung, head and neck, stomach, and cervix was increased for groups with lower SES relative to groups with higher SES. There was no clear relationship for cancers of the colon and rectum, and an inverse relationship was observed for breast cancer incidence (Table 6.2).

Table 6.2

Systematic reviews and meta-analyses of associations between socioeconomic status and risk of cancer incidence by site for high-income countries.

Evidence of social inequalities in cancer within LMICs

A literature review on social inequalities in cancer incidence and mortality in LMICs was conducted using PubMed, Scielo, and Bireme, and the reference lists from retrieved reports were reviewed to identify other sources. Keywords included inequalities, cancer, Latin America, Africa, Asia, and LMIC. Both ecological and individual-level indicators of inequality in cancer incidence and mortality for countries classified as LMICs by the World Bank (2018b) were included. When several studies of inequalities were reported for certain cancer types within a particular country, the most recent and/or those reporting the broadest age groups were used. Of note, most studies on social inequalities in cancer in LMICs reported only cancer mortality data; the very few publications that included individual-level data by education level almost exclusively reported mortality data (Attar et al., 2010; Dey et al., 2010a; Dikshit et al., 2012; de Vries et al., 2015, 2016, 2018; Tarupi et al., 2018). Published results are mostly limited to some countries in Latin America and a few countries in Africa and Asia, and the majority are ecological studies, comparing regions or states with different SES indicators, such as percentage of illiteracy and mortality of children younger than 5 years.

Despite these limitations (see Box 6.2), studies in LMICs combining all-cancer incidence or mortality usually show inequalities, with generally higher rates among people with lower SES (Diez Roux et al., 2007; Cavalini and de Leon, 2008; Chiavegatto Filho et al., 2012; Dikshit et al., 2012; Oguntoke, 2014; de Vries et al., 2016; Wang and Jiao, 2016). These general patterns conceal large differences in the magnitude and even the direction of inequalities by cancer type, but are consistent with those observed in HICs, described above. In general, studies based on individual SES data report the largest inequalities for smoking-related cancers and for infection-related cancers, such as those of the stomach, liver, and cervix. In contrast, breast cancer and colorectal cancer do not show a clear and consistent association with SES in LMICs (Dikshit et al., 2012; de Vries et al., 2015, 2018) (Table 6.3).

Box 6.2

Limitations in studies of social inequalities in cancer within countries.

Table 6.3

Evidence of associations between socioeconomic status and risk of cancer incidence or mortality by cancer site for low- and middle-income countries.

Discussion

In summary, major social inequalities in cancer exist within countries, with consistent evidence from HICs and LMICs. Disadvantaged individuals and groups tend to have a different spectrum of cancers compared with people with higher socioeconomic status (SES), notably an excess of tobacco-related and infection-related cancers. Compared with groups with high SES, lower cancer incidence rates are observed in certain anatomical sites than in groups with lower SES. However, disadvantaged individuals systematically suffer from substantially higher mortality rates and lower survival rates than groups with higher SES for the large majority of cancer types. This is clearly evident in HICs where a substantial amount of data is available. Data from LMICs are more sparse, but the available evidence on social inequalities in cancer within such populations points to similar conclusions as for HICs.

Despite the many tobacco control measures and prevention campaigns, lung cancer is still among the most frequently diagnosed cancer types in most countries (Ferlay et al., 2018). On a global scale, lung cancer is mostly caused by cigarette smoke and environmental contamination, factors that are strongly related to SES; the associations observed vary by country, however, probably as a result of the varying characteristics of the smoking epidemic. A lower education level is related to higher incidence and mortality rates of lung cancer and oral cancer (Conway et al., 2008; Dikshit et al., 2012; de Vries et al., 2015); exceptions have been observed in some rural areas in LMICs where low SES has been linked to a lower incidence of lung cancer, presumably because of a lower uptake of smoking among the most deprived groups of individuals in these areas (Dikshit et al., 2012). It is important to note that in some LMIC settings the types of housing and cooking methods, which are also associated with SES, are also important contributors to lung cancer risk (Hosgood et al., 2011; Jia et al., 2018).

About 85% of the global burden of cervical cancer occurs in LMICs, where it accounts for almost 12% of all cancers in women. In addition to LMICs having a higher burden of cancer incidence, survival, and mortality compared with HICs, large inequalities are also observed for cervical cancer within both HICs and LMICs; LEL women (Martínez and Guevel, 2013; Girianelli et al., 2014; Oguntoke, 2014; de Vries et al., 2018) living in rural areas (Antunes et al., 2008; Cavalini and de Leon, 2008; Ferreira et al., 2012) and in areas of lower SES (Drumond and Barros, 1999; Sánchez-Barriga, 2012; Girianelli et al., 2014) have the highest cervical cancer incidence and mortality rates. These observations are probably explained by the lack or limited availability of and limited access to well-organized cervical cancer screening programmes (Murillo et al., 2012), and by the limited access to screening for disadvantaged individuals even in HICs (see Example 2). The large variation in the relative and absolute differences in mortality (by up to a factor of 7) represents an enormous potential for reduction of this disease, even among the groups with the lowest SES (Hall et al., 2019), particularly because of the availability of the highly effective human papillomavirus (HPV) vaccine and of HPV-based screening tests.

Incidence and mortality rates of stomach and liver cancer have been declining in many HICs but are still high in LMICs (Colquhoun et al., 2015; Petrick et al., 2016; Sierra et al., 2016), where the burden of the disease is highest (Ferlay et al., 2018). Stomach and liver cancer are also diseases of the groups of lower SES within both HICs and LMICs, with clearly increased rates among LEL groups and in rural populations (Drumond and Barros, 1999; Belon and Barros, 2011; Dikshit et al., 2012; Ferreira et al., 2012; de Vries et al., 2015; Sánchez-Barriga, 2016). The evidence of a social gradient for the infectious agents causally linked with stomach cancer (Helicobacter pylori) and liver cancer (hepatitis B and C viruses) is discussed in Chapter 7.

No clear social gradient is observed for breast cancer. Although incidence is much higher in HICs than in LMICs (see Chapter 5) and breast cancer is often considered a disease of the affluent, data from both HICs and LMICs do not show clear associations between breast cancer mortality rates and SES (Dikshit et al., 2012; de Vries et al., 2015; Sánchez-Barriga, 2015). In HICs, breast cancer mortality rates used to be higher among HEL women, but they are now equally high among both LEL and HEL women. This could be explained by (i) strong declines in breast cancer mortality among HEL women, as a result of improvements in screening and treatment in this group, and (ii) slower declines (or even increases in some countries) in breast cancer mortality among LEL women, which may be due to an increased incidence as a consequence of a progressive transition towards delayed childbearing in this group of women, an established risk factor for breast cancer (Logan, 1953). In LMICs, living in rural areas seems to be consistently related to lower breast cancer risk (Dey et al., 2010b; Dikshit et al., 2012; Oguntoke, 2014; Fei et al., 2015); this is probably a result of childbearing-related factors, but also lower participation in screening (see Chapters 14 and 15). Although women with lower SES in LMICs may have a lower breast cancer risk, they also have a lower breast cancer survival rate, causing their mortality rates to be similar to those of women with higher SES.

In HICs, a social gradient was also observed with colorectal cancer, which is among the most frequently diagnosed cancer types in HICs and is also increasingly common in LMICs and emerging economies (Li et al., 1997; Ferlay et al., 2018). Screening and early detection combined with timely and effective treatment can greatly improve prognosis, but 5-year survival has stagnated at about 65% in HICs and is only 30–45% in many LMICs (Allemani et al., 2015). Within LMICs, the association between colorectal cancer mortality and education level is unclear (Dikshit et al., 2012; de Vries et al., 2015; Sánchez-Barriga, 2017).

The only cancer for which mortality was higher among HEL men compared with LEL men in HICs was cutaneous melanoma, perhaps as a result of more intermittent sunlight exposure among HEL men (Fig. 6.2). For some specific cancer types, such as cancers of the thyroid, breast, and prostate, incidence was higher among people with high SES, even though mortality was not (or only to a lesser extent). The large discrepancy between incidence and mortality observed for certain cancers in HICs or emerging economies could be predominantly explained by the availability of and access to effective treatments and by the increased detection of clinically irrelevant cancers in individuals with better access to a health-care system (see Chapter 18). However, the discrepancy between incidence and mortality is smaller in LMICs than in HICs, predominantly because of lower survival rates in LMICs as a result of later diagnosis and poorer access to treatment.

Three potentially relevant arguments related to the observed patterns are proposed.

First, social inequalities in cancer mortality reflect social inequalities both in incidence and in survival. Socioeconomic inequalities in mortality from cancer types for which the effectiveness of life-prolonging treatment is still relatively low, such as lung cancer, are likely to be based on socioeconomic inequalities in incidence. However, for other cancers, such as breast cancer, the balance may be different; socioeconomic inequalities in access to care and treatment may have a larger weight.

Second, social inequalities in incidence and survival must be based on inequalities in exposure to a large array of specific determinants of incidence and survival. On the basis of the literature, it is clear that health-related behaviours (such as smoking, excessive alcohol consumption, dietary factors, unprotected sex, and delayed childbearing), occupational and other environmental factors, and access to screening and treatment all play a role (see Chapter 7).

Tobacco use is certainly one of the most important factors underlying socioeconomic inequalities in cancer: the remarkably large inequalities in cancer mortality among both Danish and Norwegian women (Fig. 6.1) would not exist without the large inequalities in smoking-related cancers that have emerged within these countries, which are otherwise characterized by egalitarian social and health-care policies. It is therefore important to control the smoking epidemic (also focusing on targeting the underlying socioeconomic determinants of smoking), especially in some emerging economies and LMICs, such as in sub-Saharan Africa and Asia, where the epidemic is currently expanding (see Chapter 11 and Example 1).

Third, current inequalities in cancer mortality rates are the result of striking differences between socioeconomic groups in cancer mortality trends. For most cancer types, the trends of the past decades have been more favourable for groups with higher SES, who have apparently benefited more from advances in prevention and treatment of cancer. This confirms the central idea of the so-called fundamental causes theory, which stipulates that, whenever opportunities for health improvement arise, groups with higher SES are in a better position to benefit, because they have greater access to an array of material and non-material resources, greater health literacy, and fewer financial barriers to health care. This suggests that redistributing specific risk factors for cancer is insufficient to eliminate inequalities in cancer, and that policies should also tackle the underlying inequality in social and economic resources.

Conclusions

The variability of inequalities in cancer incidence and mortality, both between countries and over time, is a major public health challenge. This variability clearly suggests that these inequalities are not based on immutable laws of nature but are potentially modifiable. The fact that cancer is gradually replacing cardiovascular disease as the main cause of inequalities in total mortality highlights the urgency for a stronger focus on equality in cancer prevention and treatment policies.

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