Gender

The finding that female gender enhanced risk of depression during lockdown is consistent with other studies on the effects of the pandemic across the adult age range.^{Reference Robb, de Jager, Ahmadi-Abhari, Giannakopoulou, Udeh-Momoh and McKeand4,Reference Wang, Kala and Jafar11} This has been attributed to gender disparities in wealth, exacerbated by a disproportional economic impact of the COVID-19 pandemic on women, deriving from greater increases in childcare responsibilities, more disruption to paid work in female-dominated job sectors and greater job loss.^{Reference Andrew, Cattan, Costa Dias, Farquharson, Kraftman and Krutikova18} However, these factors might be less relevant for the age range under study here. One possible explanation relates to levels of worry, as women have been shown to generally worry more than men.^{Reference Crittendon and Hopko19} Women also have a higher likelihood of being diagnosed with depression generally, and this is well established in the literature.^{Reference Albert20} Another factor that might have contributed to the findings, stemming from the self-report nature of the data, could be a possible tendency for male participants to underreport their depression symptoms. However, this is somewhat mitigated by the longitudinal design, which allowed within-participant change to be quantified and used as the dependent variable: this mitigates potential between-gender reporting biases and is a key strength of the study.

Age

Across the whole sample, age emerged as an important predictor variable for change in depression, in that higher age was protective. This finding accords with previous studies on COVID-19-related effects on mental health in different age groups: younger age groups seem at higher risk of increased depression compared with older adults;^{Reference Wang, Kala and Jafar11} a cross-sectional study by Robb et al^{Reference Robb, de Jager, Ahmadi-Abhari, Giannakopoulou, Udeh-Momoh and McKeand4} in adults aged ≥50 years also found that younger age in their cohort was associated with higher anxiety and depression scores. One possible explanation for this is enhanced psychological resilience in older adults.^{Reference Albert20} Older adults have also been shown to worry less than younger adults,^{Reference Crittendon and Hopko19} and have superior emotion regulation and coping strategies.^{Reference Fiske, Wetherell and Gatz21, Reference Charles22} Greater resources in older adults (such as higher social status and financial stability) could also contribute to better resilience with age.^{Reference Vahia, Jeste and Reynolds10}

However, the gender-stratified analyses indicated that higher age was protective in women only, and this was confirmed by a significant interaction effect between gender and age when grouped by decade. This is a novel finding in COVID-19-related mental health studies, but is in accordance with epidemiological studies conducted before the pandemic, showing that women aged <65 years have a higher prevalence of depression compared with men; however, this pattern appears to even out or even invert from ≥65 years of age, with women at lower risk compared with men.^{Reference Bebbington, Dunn, Jenkins, Lewis, Brugha and Farrell23} This has been primarily attributed to menopause, suggesting a hormonal influence.^{Reference Faravelli, Alessandra Scarpato, Castellini and Lo Sauro24} Psychosocial factors (e.g. personality characteristics, coping styles and perceived interpersonal problems) have also been postulated.^{Reference Leach, Christensen, Mackinnon, Windsor and Butterworth25} Although higher age seemed to be protective against lockdown-related depression in women, this needs to be considered in the context of the wider study findings: significant increases in depression compared with pre-pandemic levels were observed across the cohort as a whole.

Urban versus rural living

Living in urban (versus rural) areas was associated with a greater risk of depression during lockdown, with significance at trend for the whole sample, and significant (for women only) in the gender-stratified models. Pre-pandemic studies suggest that people living in urban areas are at higher risk of psychological distress, with increased risk likely attributable to both physical and social aspects of the urban environment. Physical aspects include less access to green areas,^{Reference Astell-Burt and Feng26} higher pollution and population density, and more physical threats (e.g. violence and crime).^{Reference Gruebner, Rapp, Adli, Kluge, Galea and Heinz27–Reference Galea, Ahern, Rudenstine, Wallace and Vlahov29} In the context of COVID-19, lockdown would likely have had more pronounced effects on those residing in urban areas, meaning extended periods of time spent indoors, with no access to a garden or green space, also limiting opportunities for physical exercise. Furthermore, those residing in urban areas report a weaker sense of belonging to their community and lower social support compared with those residing in rural areas;^{Reference Romans, Cohen and Forte30} in older adults, a sense of community and social networks with neighbours are particularly important for well-being^{Reference Zhang, Zhang, Zhou and Yu31} and reducing loneliness.^{Reference Liddle, Scharf, Bartlam, Bernard and Sim32} Thus, lockdown would have further challenged the already weak sense of belonging and perceived social support for people living in urban areas, contributing to the effects seen here. Social participation is also an important contributor to healthy ageing,^{Reference Bowling and Stafford33} and is associated with decreased mortality and depression.^{Reference Holt-Lunstad, Smith and Layton34} Studies have found that older women tend to be more socially active compared with men,^{Reference Kirkland, Griffith, Menec, Wister, Payette and Wolfson35} and are more likely to engage in organised community activities.^{Reference Gilmour36} During lockdown, community activities were prohibited, meaning that this opportunity for social participation was removed. Where people living in rural areas could potentially rely more on the local community and social engagement with neighbours to maintain some level of social participation, those living in urban areas might not have been able to. This could explain why urban living significantly affected women in particular: being more reliant on community activities for social participation, but having such opportunities removed from them, might have led to a greater impact on the mental health of women living in urban areas.

Pre-existing depression

Baseline depression scores were entered into the models to control for pre-existing depression, and this was a significant predictor, regardless of gender. Pre-existing mental health issues have been associated with an increased risk of depression during lockdown.^{Reference Wang, Kala and Jafar11} This trend likely derives from lockdown exacerbating pre-existing symptoms. Contributing factors include a pullback in community support, difficulty accessing treatment (many mental health services suspended their services, or switched to online/telephone appointments only) and reduced social contact with friends and family, as highlighted by a survey study of groups with lived experience of mental health issues.^{Reference Holmes, O'Connor, Perry, Tracey, Wessely and Arseneault6}

Employment status

Likewise, employment status was a significant predictor; the effect was driven by those on long-term sick leave. This group showed a significantly greater increase in depression scores compared with those who were employed, unemployed or retired. Being in paid employment is associated with a lower risk of depression and better self-reported health,^{Reference Di Gessa and Grundy37} compared with being on long-term sick leave.^{Reference Lee and Smith38} As with pre-existing depression, lockdown conditions have exacerbated these effects. Having a long-standing illness also increased the risk of higher depression during lockdown, consistent with Robb et al^{Reference Robb, de Jager, Ahmadi-Abhari, Giannakopoulou, Udeh-Momoh and McKeand4} who also found that subjectively reported poor health was a risk factor for depression and anxiety during lockdown. Generally, poor subjective health increases the risk of depression among older adults.^{Reference Fiske, Gatz and Pedersen39} In the context of the COVID-19 pandemic, because of the danger COVID-19 poses to those with pre-existing health conditions in particular, this likely served as a trigger for higher levels of worry and depression in these individuals.

Living alone

Living alone was a significant risk factor for increased depression during lockdown in both genders; similar results were again found by Robb et al^{Reference Robb, de Jager, Ahmadi-Abhari, Giannakopoulou, Udeh-Momoh and McKeand4} in their cross-sectional study in adults aged ≥50 years. Robb et al^{Reference Robb, de Jager, Ahmadi-Abhari, Giannakopoulou, Udeh-Momoh and McKeand4} attributed this effect to loneliness: although loneliness was not assessed in this study, it seems likely that those living alone were differentially affected by the social isolation measures, removing opportunities for social contact and placing them at higher risk of loneliness and depression; associations between loneliness and depression have been reported across the lifespan.^{Reference Holmes, O'Connor, Perry, Tracey, Wessely and Arseneault6}

Ethnicity

Interestingly, ethnicity effects were found such that non-BAME individuals reported greater change in depression compared with BAME individuals; gender-stratified analyses showed this to only be significant in women. This should be considered cautiously as BAME groups were underrepresented, comprising only 4% of the total sample. Other COVID-19-related studies found no influence of ethnicity on depression in adults across the lifespan.^{Reference Daly, Sutin and Robinson13} However, BAME groups also comprised relatively small proportions of those samples. This possibly suggests that either studies are underestimating COVID-19's effect on BAME groups because of lack of statistical power, or that BAME groups are at least equally resilient to mental health complaints during lockdown, compared with non-BAME groups. This is surprising, given that BAME groups have been disproportionately affected by COVID-19 in terms of mortality rates;^{Reference Townsend, Kyle and Stanford40} the current finding that non-BAME individuals reported greater change in depression compared with BAME individuals goes against what one would predict, and merits further investigation regarding its validity and underlying causes.

Smoking and alcohol use

Analyses found that smoking was not a significant predictor of change in depression for either gender. Alcohol consumption acted as a protective factor against the increased risk of depression in men only. In contrast, Robb et al^{Reference Robb, de Jager, Ahmadi-Abhari, Giannakopoulou, Udeh-Momoh and McKeand4} reported that increased alcohol consumption in women contributed to depression during lockdown, with no effect in men. The current finding that alcohol consumption was protective in men might reflect greater social integration in men who drink. Studies have reported that in older adults, alcohol consumption is mostly socially motivated,^{Reference Sacco, Burruss, Smith, Kuerbis, Harrington and Moore41} particularly for men.^{Reference Gilson, Bryant, Bei, Komiti, Jackson and Judd42}

Socioeconomic factors

Finally, analyses revealed neither household income nor level of education significantly predicted change in depression. In contrast, other studies have identified education and income effects on risk of depression during lockdown, but in samples across the adult age range.^{Reference Shevlin, McBride, Murphy, Miller, Hartman and Levita12–Reference O'Connor, Wetherall, Cleare, McClelland, Melson and Niedzwiedz14} However, these socioeconomic factors are perhaps less pertinent to adults ≥aged 50 years who (compared with younger age groups) have higher levels of accrued wealth and financial stability: 69% of our sample were retirees. Thus, socioeconomic status does not seem to have influenced depression risk in this age range; instead, negative effects seem to have been widespread regardless of education and income class.

Strengths, limitations and future directions

The longitudinal nature of this study allowed temporal changes in depression to be considered, contrasting pre-lockdown with lockdown data. The overwhelming majority of comparable work has been cross-sectional in design; thus, the current study represents a valuable contribution to the literature. The study also utilised a robust outcome measure, the CES-D-SF, a seven-item screening tool for clinical depression, derived from the 20-item CES-D.^{Reference Radloff43}

Study limitations include a reliance on self-report data. In addition, the lack of full health data on participants meant additional health-related factors could not be incorporated in the models; further, measures of isolation, social connectedness and loneliness would have been beneficial. These would provide further insights into the social factors that influenced risk for depression during lockdown, but were not available. Likewise, information on the quantity (rather than just frequency) of alcohol use was not collected, which limits the interpretation of the alcohol-related effects observed in men. Also, although the longitudinal design is a key strength of this study, we only included data from two time points; future work assessing longitudinal change over a longer timeframe would be beneficial.

To summarise, this study identified risk factors that predicted change in depression in older adults as a result of COVID-19-related lockdown. Analyses suggested that depression in older adults significantly increased during lockdown compared with pre-pandemic levels in the UK. Risk factors included lower age, female gender, living alone and having a long-standing health condition. Gender-stratified analyses revealed effects unique to each gender: in women only, being younger and living in an urban area was associated with higher risk. More frequent alcohol usage acted as a protective factor, but only in men. These findings advance the literature by providing vital information regarding risk factors for poorer mental health during lockdown conditions, in an understudied age range; inferences are more robust compared with other studies because the current study utilised longitudinal data. Findings have important implications for risk stratification and intervention strategies, pointing to the demographic groups that should be prioritised for support, and those that are most at risk of poor mental health if a return to lockdown conditions is required in future. Specifically, the study findings suggest that women, particularly those that are younger and live in an urban area, are at highest risk. Thus, resources to combat COVID-19-related mental health issues might be best directed toward these individuals. Given the intense demands that the COVID-19 pandemic has placed on mental health services worldwide, this information is particularly important for allowing limited resources to be allocated more effectively.