The COVID-19 pandemic disrupted life expectancy trends in most high-income countries. In Denmark, while overall life expectancy returned to 2019 levels after the initial two pandemic years (2020 and 2021), this pattern was not observed across all the socioeconomic strata of the Danish population. Indeed, contrary to what many people outside the Nordic countries believe, large social inequalities in life expectancy persist in the Nordic countries (Brønnum-Hansen et al. 2021). In a recent publication (Strozza et al. 2024), using Danish registry data from 2014 to 2021 for all individuals aged 30 years and over, we investigated whether the COVID-19 pandemic magnified social inequalities in life expectancy in Denmark, and examined what causes of death contributed most to the observed changes. 

Life expectancy changes during the COVID-19 pandemic

Life expectancy can be calculated in different years and at various ages. Table 1, for instance, shows life expectancy at 30 years at the beginning of the period and for the first two pandemic years by sex and income quartile, used as a proxy of socioeconomic status (SES).

Life expectancy is a snapshot of mortality conditions, and not a forecast of any individual’s lifespan. Therefore, its decline does not represent the number of years that will be deducted from the lifespans of individuals; rather, it provides a comparable measure of the impact of the mortality shock generated by the pandemic. 

Table 1 shows yearly changes in life expectancy by sex and income quartile for the five years prior to the pandemic (2014-2019) and the initial two pandemic years (2020-2021).

Before the pandemic, yearly female life expectancy gains followed a social gradient. In other words, life expectancy was increasing faster for women in the highest socioeconomic groups than in the lowest. However, the confidence intervals shown in Figure 1 suggest that these results should be interpreted with caution. This was the case, to some extent, for men too, with the exception of the highest income group, where survival improvements were relatively limited. However, the differences in life expectancy changes were small, and the gap in life expectancy between the highest and lowest income groups remained large.

Figure 1 illustrates the Danish COVID-19 success story of 2020, when small gains in life expectancy were observed in the overall population (Aburto et al. 2021), as well as for most sub-populations, possibly due to the timing of policy interventions. However, the situation changed in 2021, and life expectancy losses were observed for the overall population (Schöley et al. 2022) and for most sub-populations.

Focusing on 2021, we observe a social gradient in life expectancy changes for both men and women. Among women, all sub-populations experienced a loss in life expectancy, with those in the highest income group experiencing the smallest loss, less than two and a half months, compared to those in the lowest income group, who lost almost six months. Among men, those in the highest income groups experienced gains in life expectancy, while those in the lowest income groups experienced losses, the extent of which spanned from of almost four months gained to almost four months lost between 2020 and 2021. To summarize, inequalities in life expectancy increased across socioeconomic groups for both women and men. While the confidence intervals for the 2020 results mostly overlap, in 2021 this is the case for women but not for men, at least not when the top and the bottom quartiles are compared.

Causes of death contributing to changes in life expectancy

COVID-19 was not the only factor that contributed to changes in life expectancy over this period. Mortality from other leading causes of death changed too, illustrating socioeconomic inequalities in health caused indirectly by the pandemic. 

Figures 2 and 3 show cause-specific contributions to changes in life expectancy at age 30 by income quartile for women and men, respectively. Note that individual year-on-year changes include random variability, and thus require caution in their interpretation. The positive trend in 2020 was due to a decrease in cardiovascular disease and cancer mortality across income quartiles, which counterbalanced the negative contributions of COVID-19. The smaller losses among women in the highest income group in 2021 were explained by decreases in cancer mortality and a smaller negative contribution of COVID-19 and residual causes. For those in the lowest income group, cancer mortality increased slightly, contributing to small negative changes in life expectancy. Slightly higher COVID-19 mortality, together with a high contribution from residual causes and infectious diseases accounted for the rest. Analyzing changes in other causes of death, in conjunction with COVID-19 deaths, gives a more complete picture of the indirect impacts of the pandemic.

Among men, reductions in cardiovascular disease and cancer mortality also counteracted the emergence of COVID-19 in 2020, as they did for women, although other causes, such as accidents, deaths caused by suicide, drugs, or alcohol abuse, and deaths due to respiratory diseases had negative effects on changes in life expectancy in the lowest income groups. In 2021, cardiovascular disease and cancer mortality continued to decrease in high-income groups, leading to positive contributions to changes in life expectancy, while COVID-19 had practically no impact. Low-income groups, on the other hand, experienced increased mortality from COVID-19 as well as from respiratory diseases, infectious diseases, and other residual causes. For both women and men, this shows how the direct and indirect effects of COVID-19 contributed to the increasing life expectancy gap across socioeconomic groups. 

Conclusions

Disparities in life expectancy across income groups in Denmark increased after the initial two pandemic years. The well-established mortality gaps were exacerbated by the dual impact of the pandemic, both directly through COVID-19 mortality, and indirectly through greater social inequalities in mortality from other causes of death. Our findings emphasize the critical need for more focused interventions for socially disadvantaged sub-groups during health emergencies. These interventions should not be restricted to the cause of the crisis itself, but are key to preventing a further widening of the gap between the most and least vulnerable sub-groups. Ultimately, this approach will foster a more equitable response to health crises.

References

Aburto JM, Schöley J, Kashnitsky I, Zhang L, Rahal C, Missov TI, et al. Quantifying impacts of the COVID-19 pandemic through life-expectancy losses: a population-level study of 29 countries. Int J Epidemiol. 2021;51(1):63-74. https://doi.org/10.1093/ije/dyab207 

Brønnum-Hansen H, Östergren O, Tarkiainen L, Hermansen Å, Martikainen P, van der Wel KA, et al. Changes in life expectancy and lifespan variability by income quartiles in four Nordic countries: a study based on nationwide register data. BMJ Open. 2021;11(6): e048192. doi.org/10.1136/jech-2020-214108

Schöley J, Aburto JM, Kashnitsky I, Kniffka MS, Zhang L, Jaadla H, et al. Life expectancy changes since COVID-19. Nat Hum Behav. 2022;6(12):1649–59. doi.org/10.1038/s41562-022-01450-3

Strozza, C., Vigezzi, S., Callaway, J., and Aburto J.M. (2024). The impact of COVID-19 on life expectancy across socioeconomic groups in Denmark. Population Health Metrics 22, 3. doi.org/10.1186/s12963-024-00323-3

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Introduction

The COVID-19 pandemic has caused enormous psychological, social, and economic harm worldwide. Public health measures adopted to fight the spread of the virus, such as limitations of social and physical contacts, may have exacerbated loneliness and social isolation among younger and older adults. Loneliness is a state of emotional distress arising from a discrepancy between desired and actual social interactions. It should not be confused with social isolation, as not all individuals with limited social interactions feel lonely.

Several studies suggest that older adults, despite a higher risk of social isolation, were more resilient to loneliness during the COVID-19 outbreak than younger people (Arpino et al., 2020; Luchetti et al., 2020). However, research is needed to correctly identify who felt lonely during the COVID-19 pandemic and who felt lonely because of the COVID-19 pandemic.

Who feels lonely?

To provide a clearer picture of this issue, we exploited data collected by the Survey of Health, Ageing and Retirement in Europe (SHARE) before and during the COVID-19 outbreak. More specifically, we analysed data collected in the eighth wave of SHARE, carried out in 2019/2020 (Börsch-Supan, 2022a), the first SHARE Corona survey, carried out in 2020 (Börsch-Supan, 2022b), and the second SHARE Corona survey, carried out in 2021 (Börsch-Supan, 2022c).

In these waves, the same question (“How often do you feel lonely?”) was asked with three possible answers:

1) Often
2) Some of the time
3) Hardly ever or never.

Figure 1 displays the distribution of self-reported loneliness before and during the COVID-19 pandemic, selecting only the respondents who participated in all of these waves (n=31,250). It shows that the proportion of individuals never (or hardly ever) reporting loneliness was very large (more than two thirds of respondents) and declined over time. However, while this comparison highlights who feels lonely in different periods of time, it cannot be conclusive about the role of the pandemic in causing loneliness.

To further investigate this issue, we exploited the additional question asked in both SHARE Corona surveys: “Has that been more so, less so or about the same [as before the outbreak of Corona/than during the first wave]?”. Here, the possible answers were:

1) Less so
2) About the same
3) More so. 

Unfortunately, this question was asked only to those who reported feeling lonely “often” or “some of the time” in the first SHARE Corona survey and to all respondents (whatever their feeling) in the second Corona survey, so the results cannot be compared. Moreover, they should be interpreted with caution since these are self-assessments of loneliness status and answers may suffer from individual heterogeneity in reporting feelings.

A different view: changes in loneliness

To identify those who felt lonely because of the COVID-19 pandemic, we focused on respondents who reported a change with respect to their pre-pandemic status, although even this strategy may not be flawless, as for some of these respondents the change may be due to other reasons (e.g., the loss of a loved one). However, this approach has the advantage of removing individual heterogeneity and allows us to identify both deterioration and improvement of self-reported loneliness resulting from different reactions to the measures put in place to contain the virus.

Tables 1 and 2 summarise the results obtained with our strategy. More than 70% of the older respondents show no change in loneliness with respect to the 2019 evaluation (the total percentages in the main diagonal). This does not mean that they did not feel lonely, but rather that their reported level of loneliness did not change during the pandemic period. Indeed, it is interesting to note that about 2.7% of the respondents (combining the two surveys) rated themselves as often lonely both before and during the COVID-19 outbreak.

The proportion of individuals who reported any type of deterioration of their status (14.5% and 16.7%, respectively, during the first and the second COVID-19 waves) is somewhat low and comparable with the proportion of those reporting improvement (13.2% during the first wave and 12.4% in the second wave). Moreover, only about 2% of respondents (slightly more in the second wave) reported a strong increase in their feelings of loneliness.

Summing up, this brief discussion can help to identify people whose feelings of loneliness really changed during the COVID-19 outbreak. In future research, we will investigate the characteristics of those who did not report any change. Our conjecture is that they represent a group of individuals whose feelings were barely affected by the pandemic, and this could provide a first step towards studying resilience to the COVID-19 crisis among older people.

References

Arpino B, Mair CA, Quashie NT, Antczak R (2022). Loneliness before and during the COVID-19 pandemic – are unpartnered and childless older adults at higher risk? European Journal of Ageing 19, 1327-1338

Börsch-Supan A (2022a). Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 8. Release version: 8.0.0. SHARE-ERIC. Data set. DOI: 10.6103/SHARE.w8.800

Börsch-Supan A (2022b). Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 8. COVID-19 Survey 1. Release version: 8.0.0. SHARE-ERIC. Data set. DOI: 10.6103/SHARE.w8ca.800

Börsch-Supan A (2022c). Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 9. COVID-19 Survey 2. Release version: 8.0.0. SHARE-ERIC. Data set. DOI: 10.6103/SHARE.w9ca.800

Luchetti M, Lee JH, Aschwanden D, Sesker A, Strickhouser JE, Terracciano A, Sutin AR (2020). The trajectory of loneliness in response to COVID-19. American Psychologist 75, 897-908

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