Inequalities in mortality

1. Key messages

In the period 2015-2019, a strong income gradient of mortality was observed; and this was also the case with other socio-economic indicators.

During the first wave of the COVID-19 pandemic:

  • among people aged 40-64 years, mortality remained stable in each income group, resulting in no change in mortality inequalities.
  • among people aged 65+, mortality increased in all income groups, but the increase was higher among the disadvantaged groups, leading to an increase of the inequalities by income in the 65+ group.

The contribution of specific conditions to the inequalities in the premature mortality (under 75 years) among men was largest for lung cancer, ischemic heart diseases, suicide and chronic obstructive pulmonary diseases (COPD). Among women, these conditions are ischemic heart disease, lung cancer, cerebrovascular diseases and COPD.

2. Background

Socio-economic (SE) health inequalities refer to systematic disparities in health between SE groups, most often in disfavour of social groups lower on the social scale. SE health inequalities have been consistently observed throughout industrialized societies for the whole scope of health topics, ranging from health determinants to mortality [1;2]. Tackling health inequalities is a priority for the WHO [3], the European Union [4], and for Belgium [5-7]. In order to assess progress towards reducing health inequalities, it is important to measure and monitor them [8, 9].

SE inequalities can be calculated using different socio-economic markers, for instance, income level, educational level, occupation, or a multi-dimensional score combining several SE indicators. SE inequalities can be expressed in terms of absolute difference (here, the difference in mortality rates between the lowest and the highest advantaged group) or relative difference (here, the ratio of the mortality rates of the extreme groups). Methodological details are provided in this annexe.

Besides mortality rates by socio-economic groups, we also examined excess mortality rates to assess inequalities. Excess in mortality during the COVID-19 crisis compared to a reference mortality rate (e.g. the average mortality rate over the 5 previous years) can be expressed in absolute terms (as the difference in mortality rates between the COVID-19 period and the baseline period, here 2015-2019) or in relative terms, with a “p-score” (defined as the excess mortality rates divided by the baseline mortality rate). Several studies have described recent inequalities in all-cause mortality [10–12]. Results presented here mostly originate from the study of Decoster et al [11] and highlight the changes in income inequalities in mortality during the COVID-19 crisis. Inequalities in cause-specific mortality originate from previous studies [13,14].

3. Results

Inequalities in all-cause mortality

Inequalities by income
During the period 2015-2019

A strong income gradient in mortality was observed [11] in the pre-COVID-19 period (2015-2019).

For men aged 40-64 years, the absolute inequalities gradient in mortality, measured with the slope index of inequality (SII), reached 185 per 100,000 person-year, meaning that the mortality rate in the lowest income level exceeds the mortality rates of the highest income level by 185 per 100,000 person-year. The relative inequality, measured with the Relative Index of Inequality (RII), reached 5.3, meaning that the mortality rate (in this age group) was 5.3 times higher in the lowest than in the highest income level. For women aged 40-64 years, inequalities, although slightly smaller than in men, remained quite high, with the SII reaching 93 per 100,000 and the RII 3.9.

For men aged 65+, the absolute SII reached 596 per 100,000 person-year, with a RII of 1.76. For women aged 65+, the SII reached 499 per 100,000 person-year, with a RII of 2.05.

During the first wave of the COVID-19 crisis (March-May 2020)

The impact of the first wave of COVID-19 on inequalities in mortality depends on age groups.

For men and women aged 40-64 years, the mortality rates observed during the first COVID-19 wave did not change for all income groups compared with previous years, so inequalities did not change.

On the contrary, for men and women aged 65+, mortality rates increased significantly during the COVID-19 months for all income groups. This mortality jump was unequally distributed among income groups: in absolute terms, mortality rates increased more in the lowest (excess mortality of +350 per 100,000 person-year) than in the highest income level (excess mortality +150 per 100,000 person-year). At the same time, the relative excess mortality (that is the excess mortality in the studied year divided by the baseline mortality, or “P-score”) was rather similar across the different income levels, so no significant gradient could be observed. This smoother effect of unequal mortality change on relative than on absolute inequalities is expected when mortality is on the rise: indeed the proportional change is less affected by an increase in mortality rate in groups where mortality is high than in groups with a lower mortality rate.

This led to an increase of the SII, which jumped to respectively 791 and 672 per 100,000 person-year in men and women aged 65+. The increase in the RII was more modest, passing from 1.76 to 1.86 in men and from 2.05 to 2.31 in women.

  • Men
  • Women

Mortality rates by income deciles among men aged 65+, period 2015-2019 versus the first wave of COVID-19 crisis, Belgium
Source: Decoster et al. [11] 

Mortality rates by income deciles among women aged 65+, period 2015-2019 versus the first wave of COVID-19 crisis, Belgium
Source: Decoster et al. [11] 

  • Men
  • Women

Absolute excess mortality by income deciles among men aged 65+, period 2015-2019 versus the first wave of COVID-19 crisis, Belgium
Source: Decoster et al. [11] 

Absolute excess mortality by income deciles among women aged 65+, period 2015-2019 versus the first wave of COVID-19 crisis, Belgium
Source: Decoster et al. [11] 

  • Men
  • Women

Relative excess mortality (p-scores) by income deciles among men aged 65+, period 2015-2019 versus the first wave of COVID-19 crisis, Belgium
Source: Decoster et al. [11] 

Relative excess mortality (p-scores) by income deciles among women aged 65+, period 2015-2019 versus the first wave of COVID-19 crisis, Belgium
Source: Decoster et al. [11] 

Other socio-economic determinants

In this section, we present results highlighting the changes observed during the first wave of the COVID-19 crisis (compared to previous years) in all-cause mortality inequalities according to other SE determinants.

For the 2011-2015 period, inequalities in all-cause mortality according to several SE determinants have been calculated by Aerden et al. and summarized as inequalities in life expectancy [10].

Change in inequalities by educational level, first COVID-19 wave (March-May 2020)

According to Decoster et al. [11], educational inequalities in mortality among people younger than 65 years, similarly to income inequality, remained unchanged during the COVID-19 pandemic.

For people aged 65+, the well-known negative educational gradient in mortality became stronger during the COVID-19 crisis and the change was even more pronounced than for the income gradient. The increase in educational inequalities was observed for both absolute and relative inequalities.

Change in inequalities by a multi-dimensional indicator, first two COVID-19 waves (March-May & October-November 2020)

Bourguignon et al. [12] looked at the relationship between excess mortality among the 80+ and a multi-dimensional SE status during the first two COVID-19 waves; she came to a different conclusion for people aged 80+ than for younger people, with a larger mortality increase in the advantaged than in the disadvantaged group. This observation might partly result from a health selection effect – hypothesizing that people in the lowest SE group who have reached older age are less vulnerable, resulting consequently in a reduction or even an inversion of health inequality – and partly because people with an undetermined SE status presented the highest mortality rate and are likely to pertain to the most disadvantaged group.

Inequalities in cause-specific mortality

During the period 2011-2015

A study by Eggerickx et al. [14] presents inequalities by groups of cause of death (COD) and age in the period 2011-2015, expressed as the ratio of the probability of dying in the different SE groups (those groups are derived from a multi-dimensional SE score distributed in quartiles) as compared to the highest SE group. This is a relative measure of inequality.

For each COD group and at each age, a social gradient in the mortality risk is observed: the higher the social group, the lower the risk of dying. The relative SE inequalities by COD groups were the highest for diseases linked to the respiratory system and the circulatory system.

The relative SE inequalities in mortality decrease with age. A health selection effect – hypothesizing that people in the lowest SE group who have reached older age are less vulnerable, reducing mortality inequality – might play a role. The age pattern in absolute and relative inequalities can partly be explained by the small number of deaths at young ages in both groups, which would always yield a small absolute difference, but might yield a large relative difference.

Contribution of specific causes of deaths to the inequality in premature mortality, period 2001-2006

A previous study by Renard et al. [13] examined the contribution of specific causes of deaths to the total inequality in mortality below 75 years at the level of the population. The contribution was highest in men for lung cancer, ischemic heart diseases, suicide and chronic obstructive pulmonary diseases (COPD); in women, the contribution of ischemic heart disease, lung cancer, cerebrovascular diseases and COPD was highest. This points out the causes of deaths for which the reduction in inequality would most benefit the whole population, by reducing the global premature mortality level.

  • Men
  • Women

Ranking of the causes of deaths by their contribution to the inequalities in premature mortality, measured as Population attributable fraction, men, Belgium, 2001
Source: Own calculations based on census 2001 linked with a 5-years' mortality follow-up

Ranking of the causes of deaths by their contribution to the inequalities in premature mortality, measured as Population attributable fraction, women, Belgium, 2001
Source: Own calculations based on census 2001 linked with a 5-years' mortality follow-up

4. Read more

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References

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