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Journal Pre-proof The mental health crisis during the COVID-19 pandemic in older adults and the role of physical distancing interventions and social protection measures in 26 European countries Ana Mendez-Lopez, David Stuckler, Martin McKee, Jan C. Semenza, Jeffrey V. Lazarus PII: S2352-8273(21)00292-5 DOI: https://doi.org/10.1016/j.ssmph.2021.101017 Reference: SSMPH 101017 To appear in: SSM - Population Health Received Date: 3 August 2021 Revised Date: 23 December 2021 Accepted Date: 23 December 2021 Please cite this article as: Mendez-Lopez A., Stuckler D., McKee M., Semenza J.C. & Lazarus J.V., The mental health crisis during the COVID-19 pandemic in older adults and the role of physical distancing interventions and social protection measures in 26 European countries, SSM - Population Health (2022), doi: https://doi.org/10.1016/j.ssmph.2021.101017. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2021 Published by Elsevier Ltd. Author statement Author contributions AML conceived the study, analysed the data, and prepared the first draft. AML and DS designed the study. All authors provided critical revisions and contributed to the interpretation of the data and writing of the manuscript. All authors read and approved the submitted manuscript. of ro -p re lP na ur Jo The mental health crisis during the COVID-19 pandemic in older adults and the role of physical distancing interventions and social protection measures in 26 European countries Ana Mendez-Lopez, MSc a, David Stuckler, PhD b, Martin McKee, MD c, Jan C Semenza, PhD d, Jeffrey V Lazarus, PhD e a Department of Preventive Medicine, Public Health and Microbiology, School of Medicine, Autonomous University of Madrid, Madrid, Spain; ana.mendezl@estudiante.uam.es of 2 Dondena Centre for Research on Social Dynamics and Public Policy and Department of ro Social & Political Sciences, Bocconi University, Milan, Italy; david.stuckler@unibocconi.it c -p Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, re London, United Kingdom; Martin.McKee@lshtm.ac.uk lP d Heidelberg Institute of Global Health, University of Heidelberg, Germany; Jan.Semenza@lateralPHC.com na e Barcelona Institute for Global Health (ISGlobal), Hospital Clínic, University of Barcelona, ur Barcelona, Spain; Jeffrey.lazarus@isglobal.org Jo Corresponding author & permanent address Ana Mendez-Lopez Calle Arzobispo Morcillo, 4, 28029 Madrid ana.mendezl@estudiante.uam.es; +34619934722 Declarations of interest None Author contributions AML conceived the study, analysed the data, and prepared the first draft. AML and DS designed the study. All authors provided critical revisions and contributed to the interpretation of the data and writing of the manuscript. All authors read and approved the submitted manuscript. of ro -p re lP na ur Jo The mental health crisis during the COVID-19 pandemic in older adults and the role of physical distancing interventions and social protection measures in 26 European countries Keywords: COVID-19, mental health, older adults, Europe, socioeconomic inequalities, containment measures, physical distancing, social protection Abstract of Background ro The COVID-19 pandemic and associated policy responses, such as physical distancing -p interventions, pose risks to mental health that could be mitigated by social support systems. re We examine associations between changes in mental health in the population aged 50 years lP and older in Europe and stringency of pandemic responses and social protection. na Methods ur We analysed data from the Survey of Health, Ageing and Retirement in Europe: n=50,278 Jo individuals aged 50 years and older in 26 European countries between June and August 2020. Linear multivariable regression models were used to evaluate potential risk factors for deterioration in self-reported mental health and investigate whether social protection systems mitigate it. Results Across the European Union, 28.1% (95% CI:27.1–29.2) of participants reported worsening mental health since the beginning of the pandemic, ranging from 16.1% in Slovakia to 54.8% in Portugal. Factors associated with increased risk of deterioration included: being female (12.7 percentage points (ppt), 95%CI:9.2–16.2); experiencing unmet healthcare needs during 1 the pandemic (14.6 ppt, 95%CI:11.2–18.1); job loss during the pandemic (6.2 ppt, 95%CI:1.1–11.8); and financial hardship (5.1 ppt, 95%CI:2.9–7.2). Greater stringency of physical distancing measures in countries was associated with worsening mental health (0.2 ppt per each one point increase on a stringency index, 95% CI:0.09–0.4); however, country- level pre-pandemic expenditures on various social protection packages was associated with decreased probability of worsening mental health (-1.3 ppt, 95%CI: -0.3– -2.3 per €1,000 increase in health care expenditures per capita and, among the unemployed, -3.8 ppt, 95%CI:- 1.6– -2.4 per €100 increase in unemployment expenditure per capita). of ro Conclusions -p The COVID-19 pandemic has been associated with substantial mental health deterioration re exhibiting social inequalities. Adverse mental health has been exacerbated by policy lP responses to the pandemic regulating physical distancing, but social protection expenditure might have helped mitigate the impact. Strengthening social protection systems might render na the mental health of the population more resilient to the consequences of crises such as the ur COVID-19 pandemic. Jo 2 1 Introduction 2 The COVID-19 pandemic and corresponding responses have massively disrupted daily life in 3 many countries, with profound consequences for mental health and wellbeing, especially 4 those whose lives were already precarious. In response, the United Nations has called for 5 mental health protection to be made a policy priority (United Nations Secretary-General 6 Policy Brief, 2020). Mental health is threatened by multiple pandemic-related stressors, 7 including insecurity of income and employment, isolation, and loss of social support, of 8 inability to access essential services such as health and education, and fear of contracting ro 9 COVID-19 and becoming severely ill or dying. 10 -p A review of the evidence on the psychological impact of quarantine found that most studies re 11 reported negative psychological effects (Brooks et al., 2020), and systematic reviews on the lP 12 specific impact of the COVID-19 pandemic on mental health found a deterioration of mental 13 health in the general population, but with significant differences among socioeconomic na 14 groups (Vindegaard & Benros, 2020; Wang et al., 2020; Xiong et al., 2020). Several more ur 15 recent studies have also found similar findings (Ettman et al., 2020; Fancourt et al., 2021; Jo 16 González-Sanguino et al., 2020; Pan et al., 2021; M. Pierce et al., 2020a). Although some of 17 these studies have used data representative of populations, many use non-representative 18 samples, such as those recruited using the internet, which can introduce bias as those who 19 experience digital exclusion, including many older or poorer people or those with mental 20 illness, and who are at increased risk from both COVID-19 and policy responses, may be 21 excluded (Sounderajah et al., 2021). As a consequence, there have been calls for greater use 22 of high-quality representative data that can provide more robust evidence on the impact of the 23 pandemic on mental health (Holmes et al., 2020; Matthias Pierce et al., 2020b). 3 24 Underrepresentation of older people is especially problematic. The World Health 25 Organization has viewed the mental health of older adults as a particular concern in the 26 COVID-19 pandemic, especially those who are isolated or experience cognitive decline 27 (World Health Organization, 2020c), as older population have been at highest risk of 28 complications and death from COVID-19 (Lloyd-Sherlock et al., 2020). On the other hand, 29 there is some evidence that older adults may be more resilient, at least in the short-term, to 30 some of the harms arising from the COVID-19 pandemic (Vahia et al., 2020). However, 31 depression outcomes among older populations are, as in all population groups, characterized of 32 by sociodemographic inequalities (Richardson et al., 2020). Additionally, the pattern of ro 33 sociodemographic inequalities varies substantially across countries (Richardson et al., 2020) . 34 -p The apparent mental health resilience of older adults to the effects of the COVID-19 re 35 pandemic may also vary across countries, as will the exposure of older adults to risk and lP 36 protective factors (World Health Organization, 2020a), plausibly because of differences in na 37 policy responses that offer protection. ur 38 Countries have adopted different responses to control of the pandemic. They entered it with Jo 39 different social support systems, with implications for their resilience to adversity, shocks, 40 and crises. Social protection policies can provide a safety net to protect against the negative 41 consequences of adverse life events and conditions, while promoting social and health equity. 42 A study from the United States found that people living in states with more supportive social 43 policies experienced less impact on mental health when exposed to COVID-19-related 44 household income shocks (Donnelly & Farina, 2021). Given the often more generous welfare 45 regimes in European countries, we might expect to see at least the same effect, but the greater 46 diversity in Europe may offer additional insights. Thus, different social protection systems 47 might be expected to offer differing levels of protection. 4 48 Here we seek a broad understanding of how older people in Europe have experienced the 49 effects of the pandemic on mental health, looking first at socioeconomic inequalities and 50 stressors placed upon the population, such as income and employment insecurity and 51 potential isolation resulting from physical and social distancing measures. Second, measures 52 that might mitigate these effects, in the form of existing social protection measures. We thus 53 use harmonised cross-national, nationally representative survey data to provide estimates of 54 the prevalence of self-reported decline in mental health during the COVID-19 pandemic. We 55 describe differences within the population aged 50 years or older and among 26 European of 56 countries, with a focus on socioeconomic characteristics of participants before and during the ro 57 pandemic, assessing whether the stringency of policy responses to the pandemic in Europe, in 58 -p terms of containment and closure measures, affected the mental health of older populations. re 59 Finally, we test whether and to what extent social protection expenditures influence their lP 60 mental health. na 61 Methods ur 62 Sources of data Jo 63 We used data from the Survey of Health, Ageing and Retirement in Europe (SHARE) 64 COVID-19 survey. Details of the dataset have been describe elsewhere (Börsch-Supan et al., 65 2013). Briefly, SHARE COVID-19 is a cross-sectional dataset with information on health, 66 social and environmental characteristics of adults aged 50 years or older in 27 European 67 countries and Israel, with samples that are nationally representative. The SHARE COVID-19 68 data were collected via computer-assisted telephone interviews between June and August 69 2020 using a survey harmonised ex-ante and translated into the national languages (Börsch- 70 Supan, 2020). 5 71 The SHARE COVID-19 cross-sectional dataset contains data on 50,278 individuals 72 (representing, when weighted, a population of 180,358,661 individuals) aged 50 years or 73 older who reported whether their mental health status had worsened from before the 74 pandemic. Information on survey non-response is currently not available. Respondents are 75 from the 26 European countries for which there are publicly available data (25 European 76 Union countries (which excludes Austria and Ireland because data were not available) and 77 Switzerland. The countries included are Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, 78 Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Italy, Lithuania, of 79 Luxembourg, Latvia, Malta, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, ro 80 Spain, Sweden, and Switzerland. Israel was not included in this study. -p 81 SHARE is a multinational survey using probability-based sampling. Because data are re 82 collected by national agencies, differences in sampling methods and resources between lP 83 countries exist, particularly in access to official person registries covering the population of na 84 interest including information on age. SHARE sampling details for each country can be ur 85 found elsewhere (Bergmann et al., 2019; Börsch-Supan, 2020; Börsch-Supan et al., 2013). Jo 86 All respondents provided informed consent. 87 Data on social protection system expenditures were taken from Eurostat for the latest 88 available year (2018) (Eurostat, 2021). Data on country-level COVID-19 incidence as of 1st 89 June of 2020 and data on the stringency of government policy measures were taken from Our 90 World in Data database, which are sourced, respectively, from Johns Hopkins University 91 (Dong et al., 2020) and the Oxford Coronavirus Government Response Tracker (OxCGRT) 92 (Hale et al., 2021). 93 Outcome measure 6 94 Worsened mental health was measured as self-reported decline in mental health between the 95 inception of the pandemic and the month prior to responding to the survey. Specifically, it 96 combined data collected in response to four questions asking: “In the last month, have you 97 been sad or depressed?” and “In the last month, have you felt nervous, anxious or on edge?”, 98 both questions followed by “Has that been more so, less so, or about the same as before the 99 outbreak of Corona?”. For the first two questions, the possible answers were either positive 100 or negative. Those who responded affirmatively were asked the last question, with possible 101 answers “More so”, “Less so” or “About the same”. We classified individuals who responded of 102 “More so” to either the question referring to sadness and/or depression or the question about ro 103 having felt nervous, anxious, and/or on edge as having experienced worsened mental health 104 -p during the outbreak; all other responses were classified as not having experienced worsened re 105 mental health. lP 106 Individual-level socio-economic and health measures na 107 To capture the socioeconomic impact of the pandemic on mental health, we included a series ur 108 of variables on demographic and socioeconomic characteristics before and during the Jo 109 pandemic that measured income insecurity, unemployment, and socialization. We also 110 capture the impact of health-related variables during the pandemic on worsened mental 111 health, including the impact of personally experiencing COVID-19 or having someone close 112 experience it, as well as the effect of foregone healthcare. Figure 1 illustrates the pathways of 113 pandemic-related stressors on mental health deterioration. 114 The included variables are age, an ordinal variable categorized in the following three groups: 115 50-64 years old, 65-79 years old, and 80 years old and older; gender, a dichotomous variable 116 with the categories male and female; self-rated health before the pandemic is an ordinal 117 variable measuring the self-reported health status of the respondent before the pandemic 7 118 including the categories excellent, very good, good, fair, and poor; COVID-19 positive is a 119 dichotomous variables measuring whether the responded had tested positive for the virus; 120 anyone known with a COVID-19 positive test is a dichotomous variable measuring whether 121 someone close to the respondent tested positive for the virus; foregone healthcare during the 122 pandemic is a dichotomous variables that measures whether the respondent had impeded 123 healthcare service access during the pandemic; household size is a dichotomous variable 124 measuring whether the respondent lives alone or in a household of two people or more; 125 working before the pandemic is a dichotomous variable capturing whether the respondent of 126 was working before the pandemic or was unemployed or retired; became unemployed during ro 127 the pandemic is a dichotomous variable measuring whether among those working, the 128 -p respondent became unemployed during the pandemic; and make ends meet is an ordinal re 129 variable measuring the ability of the household to live on their available economic resources lP 130 during the pandemic and includes the categories with great difficulty, with some difficulty, na 131 fairly easily, and easily. ur 132 Lockdown measures Jo 133 The severity of lockdown measures was captured using the Oxford Stringency Index of 134 government policy responses to the coronavirus pandemic. Details on how OxCGRT 135 constructs the Stringency Index are available elsewhere (Hale et al., 2021). Briefly, the 136 Stringency Index aggregates various measures of governments’ responses to the pandemic 137 capturing variations across countries in measures to increase physical distancing, such as 138 school and work closures, stay-at-home orders, cancelling public events and restrictions on 139 gathering sizes, public transport closures, and restrictions on internal and international travel. 140 The Stringency Index measures policy responses per day since the 1st of January 2020, taking 141 a value between 1 and 100, where a higher score indicates a stricter government response. To 142 capture the stringency of lockdown measures over time, we used the average of the daily 8 143 values for the period between the day after the declaration of the outbreak as public health 144 emergency of international concern by the World Health Organization (31st January 2020) 145 (World Health Organization, 2020b) and the initiation of the SHARE COVID-19 fieldwork 146 (1st June 2020) (Börsch-Supan, 2020). Figure 2 illustrates the pathways of impact of 147 lockdown measures directly on mental health deterioration (see pandemic-related stressor in 148 Figure 1) and through the economic shock associated to physical distancing measures. 149 Social protection measures of 150 To assess the role of each country’s social protection system on the change in mental health ro 151 during the pandemic, we incorporated a series of ecologic variables measuring national 152 -p expenditure on social protection systems pre-pandemic, using data for 2018, the latest re 153 available year. These variables included spending on a full package of social protection lP 154 benefits as well as on the categories of healthcare/sickness, old-age/pensions, and 155 unemployment. The full package of social protection benefits comprises expenditures on na 156 disability, sickness/healthcare, old age, survivors, family/children, unemployment, housing, ur 157 and social exclusion not covered elsewhere. Healthcare expenditures include current Jo 158 expenditures on healthcare goods and services. Pension expenditures include disability 159 pension, early retirement due to reduced capacity to work, old-age pension, anticipated old- 160 age pension, partial pension, survivors’ pension, and early retirement due to labour market 161 factors. Unemployment expenditures include spending on benefits for unemployed persons 162 such as cash benefits, vocational training allowances, redundancy compensations, placement 163 services and job search assistance. Data are measured as expenditures per inhabitant in Euros 164 adjusted for purchasing power parities. Figure 2 illustrates the pathway by which social 165 protection expenditures might impact mental health, where social protection moderates the 166 economic shock resulting from the pandemic-related physical distancing measures. 9 167 Statistical analyses 168 First, we report estimates of the prevalence of worsened mental health overall and 169 disaggregated by mental health condition: depression and/or sadness, and feeling anxious, 170 nervous, and/or on edge. We estimated prevalence as the proportion of individuals reporting 171 having experienced an adverse mental health outcome. We also report the prevalence of 172 worsened mental health by age, sex, COVID-19 infection status, ability of the individual’s 173 household to make ends meet, and by country. Chi-square tests for proportions and linear of 174 trend were performed to explore unadjusted statistical differences between groups. We used ro 175 calibrated individual weights to adjust the prevalence estimates for the different selection 176 probabilities and non-response rates. -p re 177 Second, country fixed-effects multivariable linear probability models were used to evaluate lP 178 individual-level determinants of change in the probability of worsened mental health 179 (equation 1), as follows: na 180 (1) Worsened mental health i,c = α + β + βSocDemi,c + βHealth i,c + βCOVID-19 positive i,c + ur 181 βForegone care i,c + βHousehold size i,c + βMake ends meet i,c +βEmployment i,c + µc + ε i,c Jo 182 where i is individual and c is country. Worsened mental health measures self-reported 183 worsened mental health since the beginning of the pandemic. SocDem is a vector of 184 sociodemographic variables, including age and gender. Health measures self-rated health 185 before the pandemic and serves as an adjustment to limit the effect of confounding due to 186 previous poor health. COVID-19 positive is a vector of two variables indicating whether the 187 respondent tested positive for COVID-19 or someone close to them did. Employment is a 188 vector of two variables measuring, first, whether the respondent was working before the 189 pandemic, and, second, whether among those working, the respondent became unemployed 190 during the pandemic. The other terms in the equation correspond to the definitions provided 191 above. µ was used to capture unobserved country characteristics; ε is the error term. We 10 192 report robust standard errors clustered by country to account for within country correlation 193 and used calibrated individual weights. 194 Next, we used multivariable linear probability models to evaluate country-level determinants 195 of worsened mental health. First, we test whether, in countries with a greater toll of the 196 pandemic on population health measured as total cases per million inhabitant, mental health 197 had further deteriorated. Second, we test whether in countries with more stringent lockdown 198 response measures to the pandemic, individuals had worsened metal health. We evaluate this of 199 association with the overall stringency index as well as each of its components. Third, we test ro 200 whether more generous social protection systems, measured as higher social protection 201 -p expenditures, may mitigate mental health deterioration, for which we perform analyses for 202 the overall sample or affected population subgroups. Calibrated individual weights were used re 203 in all models. Missing data were handled with pairwise deletion. Analyses were performed lP 204 using Stata 16.1 (StataCorp, 2019). na 205 Results ur 206 Prevalence of worsened mental health during the COVID-19 pandemic Jo 207 Across all countries, the prevalence of worsened mental health during the COVID-19 208 pandemic, compared to before, was 28.1% (95% CI: 27.1–29.2), ranging from 16.1% in 209 Slovakia to 54.8% in Portugal (Figure 3). Looking at each mental health condition, 18.1% of 210 the respondents reported experiencing worsened depression and/or sadness, 22.1% worsened 211 feelings of being anxious, nervous and/or on edge, and 12.0% reported experiencing both 212 (Table 1). 213 The prevalence was higher for women, of whom 34.4% (95% CI: 33.1–35.7) reported 214 worsened mental health during the pandemic, which is 13.7 percentage points (ppt) above the 215 20.7% (95% CI: 19.2–22.3) prevalence among men (Table 2). People aged 80 years or older 11 216 reported slightly worsened mental health (30.6%, 95% CI: 29.0–32.2) compared to the age 217 group 65-79 years old (27.1%, 95% CI: 26.1–27.9) but no different from the age group 50-64 218 years old (28.1%, 95% CI: 26.2–30.1). There was no trend in the reported prevalence 219 estimates across age groups (p-value=0.261). Individuals who had been infected with 220 COVID-19 had a prevalence of worsened mental health of 41.7% (95% CI: 29.2–54.2), 221 which was 13.7 ppt above the prevalence among those who had not contracted the virus 222 (28.0%, 95% CI: 27.0–29.1). The prevalence of worsened mental health was also higher for 223 people who had someone close to them who had been infected (33.5%, 95% CI: 28.7–38.4, of 224 vs. 27.6, 95% CI: 26.6–28.6). Looking at economic status, individuals with greater capacity ro 225 to make ends meet were less likely to report worsened mental health (p-value <0.0001). 226 -p Individuals who faced great difficulty making ends meet reported a 13.9 ppt higher re 227 prevalence than individuals who easily made ends meet (25.0%, 95% CI: 23.2–26.9 and lP 228 38.9%, 95% CI: 35.6–42.4, respectively). The prevalence of worsened mental health for na 229 those facing some difficulty making ends meet was 31.9% (95% CI: 29.6–34.1) and in those 230 finding it fairly easy to make ends meet was 26.2% (95% CI: 24.5–27.8). ur Jo 231 Thus, we found that the greatest prevalence of worsened mental health occurred among 232 individuals who had tested positive for COVID-19 (41.7%, 95% CI: 29.2–54.2), those with 233 great difficulty to make ends meet (38.9%, 95% CI: 35.6–42.4), women (34.4%, 95% CI: 234 33.1–35.7), individuals who had someone close to them test positive for COVID-19 (33.5%, 235 95% CI: 28.7–38.4), individuals with some difficulty to make ends meet (31.9%, 95% CI: 236 29.6–34.1), and individuals aged 80 years old and older vs those aged 65-79 years old 237 (30.6%, 95% CI: 29.0–32.2). 238 Risk factors for worsening mental health during the COVID-19 pandemic 12 239 Table 3 shows estimates of the change in the probability of reporting worsened mental health 240 during the COVID-19 pandemic according to multiple individual-level determinants. 241 Estimates from the fully adjusted regression model show that women had a 12.7 ppt higher 242 probability than men of reporting worsened mental health (95% CI: 9.2–16.2). The 243 probability of reporting worsened mental health was lower for individuals aged 80+, 244 compared with those aged 50-65 (80+ vs 50-64 years old: -4.1 ppt, 95% CI: -0.7– -7.5; 65-79 245 years old vs 50-64: -2.9 ppt, 95% CI: -7.2–1.4). of 246 Turning to direct experience of COVID-19, those who had tested positive were 12.5 ppt ro 247 (95% CI: 0.7–24.3) more likely to report worsened mental health than those who had not but 248 -p having someone close test positive had no effect (2.9 ppt, 95% CI: -1.9–7.7). Self-rated 249 health before the pandemic showed a dose-response relationship with worsened mental re 250 health. Those whose general health had been worse were more likely to report worsening lP 251 mental health (poor vs excellent health: 21.3 ppt, 95% CI: 17.6–25.0; fair vs excellent health: na 252 14.6 ppt, 95% CI: 11.2–18.1; good vs excellent health: 5.8 ppt, 95% CI: 2.2–9.4; and very ur 253 good vs excellent health: 1.3 ppt, 95% CI: -1.9–4.5). Individuals foregoing healthcare had a Jo 254 higher probability of reporting worsened mental health, by 14.2 ppt (95% CI: 12.0–16.5). 255 Living alone was associated with an increased probability of reporting mental health 256 deterioration compared to living in a household with two or more people (1.6 ppt, 95% CI: 257 0.1–3.1). 258 Turning to economic risk factors, we observed that job loss and financial difficulty were 259 associated with worsening mental health. We estimated that those who lost their job were 6.5 260 ppt (95% CI: 1.1–11.8) more likely to report worsened mental health compared with those 261 who did not become unemployed or were already retired. We did not find that having being 262 working or not before the pandemic had an effect on worsening mental health (-1.4 ppt, 95% 13 263 CI: -3.7–0.9). Finally, those who reported some or great difficulty making ends meet had 5.1 264 ppt higher risk of worsening mental health (95% CI: 2.9–7.2) compared with those who did 265 not have problems in this regard. 266 Thus, we found that the risk factors for worsened mental health with the greatest effect sizes 267 were poor and fair self-rated health before the pandemic (21.3 ppt, 95% CI: 17.6–25.0; and 268 14.6 ppt, 95% CI: 11.2–18.1, respectively), foregone healthcare during the pandemic (14.2 269 ppt, 95% CI: 12.0–16.5), being female (12.7 ppt, 95% CI: 9.2–16.2), having tested positive of 270 for COVID-19 (12.5 ppt, 95% CI: 0.7–24.3), job loss (6.5 ppt, 95% CI: 1.1–11.8), good self- ro 271 rated health before the pandemic (5.8 ppt, 95% CI: 2.2–9.4), some/great difficulty to make 272 -p ends meet (5.1 ppt, 95% CI: 2.9–7.2), and living alone (1.6 ppt, 95% CI: 0.1–3.1). After 273 adjusting for other risk factors, we found being aged 80 years old and older vs 50-64 years re 274 old (-4.1 ppt, 95% CI: -0.7– -7.5) had a protective effect. lP 275 Country-level determinants of worsened mental health during the COVID-19 pandemic na 276 Table 4 shows estimates of the impact on worsened mental health of the national toll of ur 277 COVID-19 cases and of the stringency of policy responses to the pandemic. Countries with a Jo 278 higher number of COVID-19 cases had a greater risk of mental health deterioration (3.1 ppt, 279 95% CI: 2.3–3.9 per 1,000 cases increase). Next, we found that a higher overall stringency 280 index was associated with a 0.2 ppt (95% CI: 0.1–0.3) increase in the probability of worsened 281 mental health. Several components of the index had specific impacts on mental health 282 deterioration, including workplace closures (6.6 ppt, 95% CI: 2.2–10.9), restrictions on 283 gatherings (3.9 ppt, 95% CI: 0.8–6.9), public transportation closures (6.3 ppt; 95% CI: 2.3– 284 10.2), and stay-at-home requirements (3.1 ppt, 95% CI: 0.6–5.7). We found that greater 285 restrictions on international travel had a protective effect on mental health (-5.1 ppt, 95% CI: 286 -1.7–-8.5). No effect on mental health was found for components measuring the cancellation 14 287 of public events (2.7 ppt, 95% CI: -2.4–3.1), the level of restrictions on national travel (-0.2 288 ppt, 95% CI: -2.5–2.0) and school closures (0.1 ppt, 95% CI: -2.9–3.1). 289 Table 5 shows estimates of the association between a series of variables measuring 290 expenditures on social protection benefits and worsened mental health, adjusting for the total 291 number of COVID-19 cases and stringency of policy responses. For each additional €1,000 292 increase in expenditures on overall social protection benefits, reporting of worsened mental 293 health decreased among those who became unemployed during the pandemic (-2.3 ppt, 95% of 294 CI: -0.6–-4.1), individuals with poor/fair health (-0.8 ppt, 95% CI: -0.01–-1.5), and among individuals aged 65 years (-0.5 ppt, 95% CI: -0.2–-0.8). No effect of overall social ro 295 296 -p protection spending was observed the population in general (-0.3 ppt, 95% CI: -0.7–0.1) and 297 re those facing difficulties making ends meet (0.2 ppt, 95% CI: -0.7–1.2). The same increase in 298 spending on healthcare was associated with a protective effect on the mental health of the lP 299 general population (-1.3 ppt, 95% CI: -0.3–-2.3) and a stronger effect among those who na 300 reported poor health (-2.2 ppt, 95% CI: -0.3–-4.0). In countries with higher spending on ur 301 unemployment benefits, worsened mental health among the unemployed was ameliorated (- Jo 302 3.8 ppt, 95% CI: -0.5–-7.1 per €100 increased spending; here, as opposed to Table 5, we 303 report changes per €100 instead of €1,000 because the range of amounts paid in 304 unemployment benefits among countries is substantially lower than for other social 305 protection payments, as shown in Table 1). Differences in pension spending were not 306 associated with the probability of reporting adverse mental health among people aged 65 307 (0.4 ppt, 95% CI: -0.6–1.4 per €1,000 increase in spending). 308 Sensitivity tests 309 We ran a series of sensitivity tests using the two components of the main outcome as 310 outcome variables: worsened depression and worsened anxiety since the inception of the 15 311 COVID-19 pandemic, observing that the findings did not substantially change, although in 312 some instances the estimates’ effect sizes were smaller or greater than with the combined 313 outcome (Online supplementary material). 314 Discussion 315 We found a substantial deterioration in mental health in persons aged 50 years and older 316 between the beginning of the pandemic and June to August 2020. This was strongly 317 associated with greater severity of physical distancing measures and exhibited substantial of 318 social inequalities, with people with poor and fair health, foregoing healthcare, women, and ro 319 persons who experienced job loss and financial hardship during the pandemic suffering the 320 -p most. Importantly, however, stronger social protection systems, as measured by greater re 321 spending, appeared to mitigate the risk of worsened mental health. lP 322 We observed great differences across countries in the prevalence of worsened mental health, na 323 again consistent with previous research (Wang et al., 2020). However, a consistent finding is 324 that people in lower socioeconomic groups and women have been hardest hit. Individuals ur 325 with worse overall health status before the pandemic were substantially more likely to Jo 326 experience mental health deterioration, as were individuals with unmet healthcare needs since 327 the inception of the pandemic. This might suggest a relationship between COVID-19 328 comorbidities and deteriorating mental health . Also, those with a diagnosis of COVID-19 329 were more likely to experience further declines in mental health, which is aligned with 330 findings from previous research (Taquet et al., 2021a; Taquet et al., 2021b). This could be 331 due to, or exacerbated by, fear of becoming severely ill or dying as well as disrupted health 332 services provision (World Health Organization, 2020a), including reduced access to mental 333 health services, either for ongoing conditions or for new ones arising since the inception of 334 the pandemic. 16 335 Individuals who reported good overall health status during the pandemic also experienced 336 declines in mental health, which may be due not only to COVID-19, but also the physical 337 distancing measures and closure policies having impacted mental health, particularly through 338 job loss and difficulties to make ends meet. In this context, greater social protection 339 expenditures may have increased resilience during the pandemic as our social protection 340 variable was measured pre-pandemic. That the expenditures measures are pre-pandemic 341 might also explain why we found greater expenditures in a full package of social protection 342 protected the mental health for some population subgroups (those with poor health, of 343 unemployed, and those aged 65 and older, all of who may have benefited from a stronger ro 344 public health system, unemployment benefits, and old age pensions); however, greater 345 -p expenditures in a full package of social protection did not protect the mental health of the re 346 whole population aged 50 years old and older as many may have not been directly benefiting lP 347 from the social protection programmes until after the crisis began. na 348 Our analysis has several limitations. First, we were unable to attribute worsened mental ur 349 health with certainty to the pandemic and policy responses or some other event during this Jo 350 time frame. However, the outcome variable is based on a question inquiring whether mental 351 health had worsened since the onset of the pandemic, which is likely to anchor it to the 352 pandemic. While SHARE is a panel dataset, the timing of the wave, in summer 2020, means 353 that we have no absolute measure of mental health just prior and subsequent to the onset of 354 the pandemic but the additional question in the cross-sectional data, asking whether 355 symptoms had worsened since the inception of the pandemic partially circumvents this 356 limitation. Nonetheless, other studies using longitudinal designs have produced similar 357 findings to ours (Ettman et al., 2020; González-Sanguino et al., 2020; Pan et al., 2021; M. 358 Pierce et al., 2020a). Although we were not able to adjust for previous mental health status 359 specifically, we could adjust for prior self-reported general health status. 17 360 A second limitation is the ecologic nature of the social protection measures used in the 361 analysis. Thus, we could not include individual level data on social protection benefits 362 although we could identify those potentially eligible for pensions or unemployment benefits. 363 Third, we did not include data on other socioeconomic determinants of mental health, such as 364 experience of racism among migrants and minority ethnic groups. Also, while almost 365 everyone in Europe is affected by the pandemic, we were not able to capture aspects that may 366 have made individual exposure to it more or less intense. Fourth, mental health can be 367 complex to measure. We used self-reported data where response bias could have over or of 368 underestimated the strength of the associations. However, self-reporting is common in mental ro 369 health research. Telephone interviewing could have also made respondents hesitant to 370 -p accurately report information, particularly mental health and financial status information. re 371 Measurement of social protection systems is difficult, and our measurement approach is just lP 372 an approximation. While the Oxford COVID-19 government response tracker aims to capture na 373 how many measures a government has adopted and to what degree, the index cannot say 374 whether each has been effectively implemented and whether it is adhered to. Differences in ur 375 policy implementation and adherence could have biased our estimates, over or under- Jo 376 estimating the strength of the reported associations. Fifth, the findings herein refer to the first 377 few months of the pandemic, as the data were collected between June and August 2020 but 378 the relationship between social protection and mental health may change over time, 379 particularly when assessing social protection measures introduced during the pandemic as 380 opposed to assessing previously established social protection systems as we have done. 381 Finally, our study only included the population aged 50 and above, so the findings cannot be 382 extrapolated to the rest of the population. Most other studies have focused on younger 383 populations (adolescents, university students) and healthcare workers. Thus, our study fills an 384 important gap, capturing experiences of those hardest hit by COVID-19 illness. Although we 18 385 would expect similar findings, further research could explore the impact of the COVID-19 386 pandemic on mental health among older populations in low- and middle-income countries. 387 Our study has implications for policy. It reveals how the adverse impacts of physical 388 distancing and closures are not inevitable. Increased spending on various social protection 389 benefits, including healthcare, unemployment, and a package of social protection benefits 390 seems to ameliorate the risk of mental health deterioration. A recent study found that 391 governments in many countries were perceived to have responded poorly to the burden of of 392 mental health suffering associated with COVID-19 (Lazarus et al., 2020). Greater ro 393 expenditure on social protection may have enabled more support and acted as a safety net for 394 -p those at risk of mental health problems during what was a health and economic crisis. These 395 findings are consistent with the aforementioned study from the United States which found re 396 that stronger social support policies helped mitigate the mental health consequences of lP 397 household income shocks during the COVID-19 pandemic (Donnelly & Farina, 2021). We na 398 also found that individuals living alone had a higher risk of mental health deterioration, ur 399 which may be explained by feelings of isolation and lack of social support, particularly Jo 400 among older people who may have less access to digital communications. This highlights the 401 importance of considering emotional and social support as part of government and civil 402 society responses to the COVID-19 pandemic, bearing in mind that many of those worst 403 affected risk being further excluded from the increasingly digital delivery of services (Seifert 404 et al., 2021). Faced with a continuing COVID-19 pandemic, with more time spent under 405 physical distancing and other containment measures and further economic downturn, there is 406 a risk of further harm to mental health. It is imperative that countries build strong social 407 protection systems and resilient health systems that can protect their populations from the 408 mental health consequences of crises (Hanefeld et al., 2018; Tediosi et al., 2020; Thomas et 409 al., 2020; World Health Organization, 2020a). 19 410 Declaration of interests 411 None. 412 Data sharing 413 SHARE data is available upon registration on their website. Data from Eurostat and from the 414 Oxford COVID-19 Government Response Tracker are publicly available on their websites. 415 Financial disclosure of 416 No funding was received for this study. ro -p re lP na ur Jo 20 References Bergmann, M., Kneip, T., De Luca, G., & Scherpenzeel, A. (2019). 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(2021). A global panel database of pandemic policies (Oxford COVID-19 Government Jo Response Tracker). Nature Human Behaviour, 5, 529-538. Hanefeld, J., Mayhew, S., Legido-Quigley, H., Martineau, F., Karanikolos, M., Blanchet, K., et al. (2018). Towards an understanding of resilience: responding to health systems shocks. Health Policy Plan, 33, 355-367. Holmes, E.A., O'Connor, R.C., Perry, V.H., Tracey, I., Wessely, S., Arseneault, L., et al. (2020). Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science. Lancet Psychiatry, 7, 547-560. Lazarus, J.V., Ratzan, S., Palayew, A., Billari, F.C., Binagwaho, A., Kimball, S., et al. (2020). COVID-SCORE: A global survey to assess public perceptions of government responses to COVID-19 (COVID-SCORE-10). PLoS One, 15, e0240011. Lloyd-Sherlock, P., Ebrahim, S., Geffen, L., & McKee, M. (2020). Bearing the brunt of covid-19: older people in low and middle income countries. Bmj, 368, m1052. Pan, K.-Y., Kok, A.A.L., Eikelenboom, M., Horsfall, M., Jörg, F., Luteijn, R.A., et al. (2021). The mental health impact of the COVID-19 pandemic on people with and without depressive, anxiety, or obsessive-compulsive disorders: a longitudinal study of three Dutch case-control cohorts. The Lancet Psychiatry, 8, 121-129. Pierce, M., Hope, H., Ford, T., Hatch, S., Hotopf, M., John, A., et al. (2020a). Mental health before and during the COVID-19 pandemic: a longitudinal probability sample survey of the UK population. Lancet Psychiatry, 7, 883-892. 21 Pierce, M., McManus, S., Jessop, C., John, A., Hotopf, M., Ford, T., et al. (2020b). Says who? The significance of sampling in mental health surveys during COVID-19. The Lancet Psychiatry, 7, 567-568. Richardson, R.A., Keyes, K.M., Medina, J.T., & Calvo, E. (2020). Sociodemographic inequalities in depression among older adults: cross-sectional evidence from 18 countries. The Lancet Psychiatry, 7, 673-681. Seifert, A., Cotten, S.R., & Xie, B. (2021). A Double Burden of Exclusion? Digital and Social Exclusion of Older Adults in Times of COVID-19. The Journals of Gerontology: Series B, 76, e99-e103. Sounderajah, V., Clarke, J., Yalamanchili, S., Acharya, A., Markar, S.R., Ashrafian, H., et al. (2021). A national survey assessing public readiness for digital health strategies against COVID-19 within the United Kingdom. Sci Rep, 11, 5958. StataCorp. (2019). Stata Statistical Software: Release 16. College Station, TX: StataCorp LP. Taquet, M., Geddes, J.R., Husain, M., Luciano, S., & Harrison, P.J. (2021a). 6-month neurological and psychiatric outcomes in 236 379 survivors of COVID-19: a of retrospective cohort study using electronic health records. The Lancet Psychiatry. Taquet, M., Luciano, S., Geddes, J.R., & Harrison, P.J. (2021b). Bidirectional associations ro between COVID-19 and psychiatric disorder: retrospective cohort studies of 62354 COVID-19 cases in the USA. The Lancet Psychiatry, 8, 130-140. -p Tediosi, F., Lönnroth, K., Pablos-Méndez, A., & Raviglione, M. (2020). Build back stronger universal health coverage systems after the COVID-19 pandemic: the need for better re governance and linkage with universal social protection. BMJ Glob Health, 5. Thomas, S., Sagan, A., Larkin, J., Cylus, J., Figueras, J., & Karanikolos, M. (2020). lP Strengthening health systems resilience: Key concepts and strategies. European Observatory Policy Briefs Copenhagen (Denmark): European Observatory on Health Systems and Policies, World Health Organization 2020 (acting as the host na organization for, and secretariat of, the European Observatory on Health Systems and Policies). United Nations Secretary-General Policy Brief (2020). United Nations Policy Brief: COVID- ur 19 and the need for action on mental health. United Nations: New York, NY, USA. Vahia, I.V., Jeste, D.V., & Reynolds, C.F., 3rd (2020). Older Adults and the Mental Health Jo Effects of COVID-19. JAMA, 324, 2253-2254. Vindegaard, N., & Benros, M.E. (2020). COVID-19 pandemic and mental health consequences: Systematic review of the current evidence. Brain Behav Immun, 89, 531-542. Wang, Y., Kala, M.P., & Jafar, T.H. (2020). Factors associated with psychological distress during the coronavirus disease 2019 (COVID-19) pandemic on the predominantly general population: A systematic review and meta-analysis. PLoS One, 15, e0244630. World Health Organization. (2020a). Health inequity and the effects of COVID‑ 19: assessing, responding to and mitigating the socioeconomic impact on health to build a better future. World Health Organization. Regional Office for Europe. World Health Organization (2020b). Listings of WHO’s response to COVID-19. World Health Organization. (2020c). Mental health and psychosocial considerations during the COVID-19 outbreak, 18 March 2020. World Health Organization. Xiong, J., Lipsitz, O., Nasri, F., Lui, L.M.W., Gill, H., Phan, L., et al. (2020). Impact of COVID-19 pandemic on mental health in the general population: A systematic review. J Affect Disord, 277, 55-64. 22 List of figures and tables Figure 1. DAG of the pathways of pandemic-related stressors on mental health deterioration Figure 2. DAG of the pathways of country-level determinants of mental health deterioration Figure 3. Prevalence of worsened mental health due to the COVID-19 pandemic in 26 European countries, June-August 2020 Table 1. Descriptive statistics of study population, June-August 2020 Table 2. Prevalence of worsened mental health due to the COVID-19 pandemic in 26 European countries by sociodemographic characteristics and COVID-19 infection status, June-August 2020 of Table 3. Individual-level determinants of change in the probability of worsened mental ro health during the COVID-19 pandemic in 26 European countries, June-August 2020 Table 4. Impact of stringency of policy responses to the pandemic on the change in the -p probability of worsened mental health during the COVID-19 pandemic in 26 European re countries, June-August 2020 Table 5. Impact of social protection expenditures on the change in the probability of lP worsened mental health during the COVID-19 pandemic in 26 European countries, June- August 2020 na ur Online appendix Jo Figure A1. Prevalence of worsened depression due to the COVID-19 pandemic in 26 European countries, June-August 2020 Figure A2. Prevalence of worsened anxiety due to the COVID-19 pandemic in 26 European countries, June-August 2020 Table A1. Individual-level determinants of change in the probability of worsened depression during the COVID-19 pandemic, June-August 2020 Table A2. Impact of stringency of policy responses to the pandemic on the change in the probability of worsened depression during the COVID-19 pandemic in 26 European countries, June-August 2020 Table A3. Impact of social protection expenditures on the change in the probability of worsened depression during the COVID-19 pandemic in 26 European countries, June- August 2020 Table A4. Individual-level determinants of change in the probability of worsened anxiety during the COVID-19 pandemic, June-August 2020 23 Table A5. Impact of stringency of policy responses to the pandemic on the change in the probability of worsened anxiety during the COVID-19 pandemic in 26 European countries, June-August 2020 Table A6. Impact of social protection expenditures on the change in the probability of worsened anxiety during the COVID-19 pandemic in 26 European countries, June-August 2020 of ro -p re lP na ur Jo 24 Figure 1. DAG of the pathways of pandemic-related stressors on mental health deterioration of ro -p re lP na ur Jo 25 Figure 2. DAG of the pathways of country-level determinants of mental health deterioration of ro -p re lP na ur Jo 26 Figure 3. Prevalence of worsened mental health due to the COVID-19 pandemic in 26 European countries, June-August 2020 of ro -p re lP na ur Jo 27 Table 1. Descriptive statistics of study population, June-August 2020 Unweighted Weighted N proportion or mean proportion or mean (SD) (SD) Total sample 50,278 100.0 100.0 Total population 180,358,661 100.0 100.0 Sociodemographic variables Age groups; 50-64 14,793 29.23 48.43 65-79 26,550 52.46 35.58 80+ 9,266 18.31 15.99 Gender; Female 29,422 57.86 54.03 of Health-related variables Worsened mental health; Yes 13,504 26.69 28.14 ro Worsened depression; Yes 8,299 16.41 18.05 Worsened anxiety; Yes 10,820 21.39 22.13 Worsened depression and anxiety; Yes Self-rated health before pandemic; Excellent -p 5,615 3,377 11.04 6.68 11.97 7.18 re Very good 7,986 15.79 17.83 Good 22,455 44.39 47.01 Fair 13,155 26.01 22.06 lP Poor 3,608 7.13 5.93 COVID-19 positive test; Yes 238 0.47 0.77 Anyone known COVID-19 positive test; Yes 3,363 6.69 8.86 na Forgone healthcare during pandemic; Yes 5,991 11.85 11.57 ur Socioeconomic variables Living alone; Yes 12,301 24.19 27.07 Working before pandemic; Yes 10,744 21.25 32.88 Jo Became unemployed during pandemic; Yes 1,949 3.85 6.67 Make ends meet during pandemic; With great difficulty 4,683 9.51 8.49 With some difficulty 12,993 26.38 23.79 Fairly easily 17,233 34.99 36.18 Easily 14,346 29.13 31.55 Country-level variables Total COVID-19 cases per million inhabitants 26 countries 2,090.89 (1,690.31) 2,640.67 (1,468.72) Stringency index of policy responses to the pandemic 26 countries 56.41 (7.39) 61.15 (5.43) Social protection expenditures per capita in Euros, PPS 26 countries 6,972.92 (3,001.77) 8,161.31 (2,760.94) Healthcare expenditures per capita in Euros, PPS 26 countries 1,936.97 (908.18) 2,385.93 (1,072.76) Unemployment expenditures per capita in Euros, PPS 26 countries 291.17 (208.32) 359.77 (187.26) Old age expenditures per capita in Euros, PPS 26 countries 2,935.51 (1,116.10) 3,312.86 (923.18) SD: Standard deviation. PPS: Purchasing parity standard. 28 Table 2. Prevalence of worsened mental health during the COVID-19 pandemic in 26 European countries by sociodemographic characteristics and COVID-19 infection status, June-August 2020 % 95%CI p-value N Gender Male 20.7 19.2–22.3 P<0.0001 * 4,278 Female 34.4 33.1–35.7 9,133 Age group 50-64 28.1 26.2–30.1 p=0.279 º 3,956 65-79 27.1 26.1–27.9 6,821 of 80+ 30.6 29.0–32.2 2,634 Respondent had a COVID-19 positive test ro Yes 41.7 29.2–54.2 p=0.021 * 95 -p No 28.0 27.0–29.1 13,314 Someone close to respondent had a COVID-19 positive test re Yes 33.5 28.7–38.4 p=0.014 * 1,118 lP No 27.6 26.6–28.6 12,204 Make ends meet during pandemic With great difficulty 38.9 35.6–42.4 P<0.0001 º 1,742 na With some difficulty 31.9 29.6–34.1 3,763 Fairly easily 26.2 24.5–27.8 4,330 ur Easily 25.0 23.2–26.9 3,276 *Chi-square test for proportions; ºChi-square test for trend. Jo 29 Table 3. Individual-level determinants of change in the probability of worsened mental health during the COVID-19 pandemic in 26 European countries, June-August 2020 Worsened mental health during the COVID-19 pandemic Model 1 Model 2 Model 3 Age group 50-64 reference reference reference 65-79 -0.00947 -0.0308* -0.0292 (-0.0481–0.0292) (-0.0615– -0.0000496) (-0.0721–0.0138) 80+ 0.00418 -0.0469*** -0.0411* (-0.0247–0.0330) (-0.0664– -0.0273) (-0.0750– -0.00719) Gender Male reference reference reference Female 0.137*** 0.129*** 0.127*** (0.106–0.169) (0.0964–0.162) (0.0922–0.162) Self-rated health before pandemic Excellent reference reference Very good 0.0176 0.0134 (-0.0103–0.0454) (-0.0185–0.0453) Good 0.0661*** 0.0579** of (0.0313–0.101) (0.0221–0.0938) Fair 0.161*** 0.146*** ro (0.129–0.193) (0.112–0.181) Poor 0.232*** 0.213*** (0.198–0.266) (0.176–0.250) -p Respondent COVID-19 positive Not positive reference reference Positive 0.112 0.125* re (-0.00427–0.229) (0.00706–0.243) Anyone known COVID-19 positive No reference reference lP Yes 0.0260 0.0288 (-0.0224–0.0743) (-0.0193–0.0769) Forgone healthcare during pandemic na No reference reference Yes 0.145*** 0.142*** (0.122–0.168) (0.120–0.165) Living alone ur 2 or more in household reference 1 person in household (living alone) 0.0162* (0.00128–0.0312) Jo Make ends meet during pandemic Easily/Fairly easily reference With some/great difficulty 0.0508*** (0.0293–0.0724) Working before pandemic No or Retired reference Yes -0.0141 (-0.0370–0.00878) Became unemployed during pandemic No or Retired reference Yes 0.0646* (0.0110–0.118) Number of individuals 50278 49856 48566 R2 0.048 0.079 0.083 95% confidence intervals in brackets. *p < 0.05, **p < 0.01, ***p < 0.001 Robust standard errors clustered by country; constant calculated but not shown; all models adjusted by country indicator variables. 30 Table 4. Impact of stringency of policy responses to the pandemic on the change in the probability of worsened mental health during the COVID-19 pandemic in 26 European countries, June-August 2020 Worsened mental health during the COVID-19 pandemic Model 1 Models 2-9 Total COVID-19 cases per million inhabitants 0.0000313*** (0.0000234–0.0000392) Stringency index of policy responses to the pandemic 0.00237** (0.000895–0.00384) Stringency index components: of C1 School closing 0.000541 (-0.0294–0.0305) ro C2 Workplace closing 0.0655** (0.0222–0.109) C3 Cancel public events -p 0.0268 re (-0.0237–0.0773) C4 Restrictions on gathering size 0.0387* lP (0.00830–0.0690) C5 Close public transport 0.0626** na (0.0232–0.102) C6 Stay at home requirements 0.0311* ur (0.00560–0.0567) Jo C7 Restrictions on internal movement -0.00248 (-0.0250–0.0200) C8 Restrictions on international travel -0.0514** (-0.0854–-0.0174) Number of individuals 48566 48566 Number of countries 26 26 R2 0.077 – 95% confidence intervals in brackets. * p < 0.05, **p < 0.01, ***p < 0.001 Constant calculated but not shown. Models 1-9 are adjusted for all variables included in Model 3, Table 2. Models 2-9 are adjusted for total COVID-19 cases per million inhabitants. C: component. 31 Table 5. Impact of social protection expenditures on the change in the probability of worsened mental health during the COVID-19 pandemic in 26 European countries, June-August 2020 Worsened mental health during the COVID-19 pandemic Models 1-9 Sample Per 1,000 € increase in social protection expenditures per capita All -0.00339 (n=49880) (-0.00760–0.000829) Poor/fair health -0.00787* (n=16523) (-0.0155– -0.000261) Unemployed -0.0233** of (n=1888) (-0.0407– -0.00592) 65 years old -0.00499** ro (n=35292) (-0.00826– -0.00172) Difficulty make ends meet 0.00198 -p (n=17423) (-0.00767–0.0116) re Per 1,000 € increase in health care/sickness expenditures per capita All -0.0130* (n=49880) (-0.0230– -0.00311) lP Poor/fair health -0.0219* (n=16523) (-0.0404– -0.00340) na Per 1,000 € increase in unemployment benefits expenditures per capita Unemployed -0.380* (n=1888) (-0.711– -0.0504) ur Per 1,000 € increase in pensions/old age expenditures per capita 65 years old 0.00375 Jo (n=35292) (-0.00598–0.0135) 95% confidence intervals in brackets. * p < 0.05, **p < 0.01, ***p < 0.001 Constant calculated but not shown. All models adjusted by age, gender, health status before the pandemic, tested positive for COVID-19 oneself or someone close, household size, total COVID-19 cases per million inhabitants, and stringency index of policy responses to the pandemic. 32 Online supplementary material Figure A1. Prevalence of worsened depression due to the COVID-19 pandemic in 26 European countries, June-August 2020 Figure A2. Prevalence of worsened anxiety due to the COVID-19 pandemic in 26 European countries, June-August 2020 Table A1. Individual-level determinants of change in the probability of worsened depression during the COVID-19 pandemic in 26 European countries, June-August 2020 Table A2. Impact of stringency of policy responses to the pandemic on the change in the probability of worsened depression during the COVID-19 pandemic in 26 European countries, June-August 2020 of Table A3. Impact of social protection expenditures on the change in the probability of ro worsened depression during the COVID-19 pandemic in 26 European countries, June- August 2020 -p Table A4. Individual-level determinants of change in the probability of worsened anxiety re during the COVID-19 pandemic in 26 European countries, June-August 2020 lP Table A5. Impact of stringency of policy responses to the pandemic on the change in the na probability of worsened anxiety during the COVID-19 pandemic in 26 European countries, June-August 2020 ur Table A6. Impact of social protection expenditures on the change in the probability of worsened anxiety during the COVID-19 pandemic in 26 European countries, June-August Jo 2020 33 Figure A1. Prevalence of worsened depression due to the COVID-19 pandemic in 26 European countries, June-August 2020 f r oo -p re lP na ur Jo 34 Figure A2. Prevalence of worsened anxiety due to the COVID-19 pandemic in 26 European countries, June-August 2020 f r oo -p re lP na ur Jo 35 Table A1. Individual-level determinants of change in the probability of worsened depression during the COVID-19 pandemic in 26 European countries, June-August 2020 Worsened depression during the COVID- 19 pandemic Age group 50-64 reference 65-79 -0.00593 (-0.0302–0.0183) 80+ -0.00206 (-0.0231–0.0190) Gender Male reference Female 0.103*** (0.0731–0.133) Self-rated health before pandemic Excellent reference Very good 0.00861 (-0.0110–0.0282) Good 0.0331** of (0.0107–0.0555) Fair 0.115*** ro (0.0802–0.149) Poor 0.195*** (0.167–0.223) -p Respondent COVID-19 positive Not positive reference Positive 0.121* re (0.00572–0.237) Anyone known COVID-19 positive No reference lP Yes -0.00655 (-0.0501–0.0370) Forgone healthcare during pandemic na No reference Yes 0.0993*** (0.0781–0.120) Living alone ur 2 or more in household reference 1 person in household (living alone) 0.0228** (0.00906–0.0365) Jo Make ends meet during pandemic Easily/Fairly easily reference With some/great difficulty 0.0492*** (0.0302–0.0682) Working before pandemic No or Retired reference Yes -0.0118 (-0.0420–0.0185) Became unemployed during pandemic No or Retired reference Yes 0.0610*** (0.0315–0.0904) Number of indivudals 48549 R2 0.074 95% confidence intervals in brackets. * p < 0.05, **p < 0.01, ***p < 0.001 Robust standard errors clustered by country; constant calculated but not shown; all models adjusted by country indicator variables. 36 Table A2. Impact of stringency of policy responses to the pandemic on the change in the probability of worsened depression during the COVID-19 pandemic in 26 European countries, June-August 2020 Worsened depression during the COVID-19 pandemic Model 1 Models 2-9 Total COVID-19 cases per million inhabitants 0.0000256*** (0.0000188–0.0000325) Stringency index of policy responses to the pandemic 0.00190** (0.000660–0.00314) Stringency index components: of C1 School closing 0.0203 (-0.00470–0.0453) ro C2 Workplace closing 0.0476* (0.0108–0.0843) C3 Cancel public events -p 0.00426 re (-0.0351–0.0436) lP C4 Restrictions on gathering size 0.00200 (-0.0224–0.0264) na C5 Close public transport 0.0235 (-0.00530–0.0524) 0.0240* ur C6 Stay at home requirements (0.00408–0.0439) Jo C7 Restrictions on internal movement 0.0143 (-0.00198–0.0307) C8 Restrictions on international travel -0.00944 (-0.0356–0.0167) Number of individuals 48549 48549 Number of countries 26 26 R2 0.074 – 95% confidence intervals in brackets. * p < 0.05, **p < 0.01, ***p < 0.001 Constant calculated but not shown. Models 1-9 are adjusted for all variables included in Model 3, Table 2. Models 2-9 are adjusted for total COVID-19 cases per million inhabitants. C: component. 37 Table A3. Impact of social protection expenditures on the change in the probability of worsened depression during the COVID-19 pandemic in 26 European countries, June-August 2020 Worsened depression during the COVID-19 pandemic Models 1-9 Sample Per 1,000 € increase in social protection expenditures per capita All -0.00532** (n=49862) (-0.00864–-0.00200) Poor/fair health -0.00585 (n=16513) (-0.0119–0.000209) Unemployed -0.0165* of (n=1888) (-0.0318–-0.00121) 65 years old -0.00439** ro (n=35283) (-0.00723–-0.00154) Difficulty make ends meet 0.00219 -p (n=17416) (-0.00595–0.0103) re Per 1,000 € increase in health care/sickness expenditures per capita All -0.0160*** (n=49862) (-0.0237–-0.00830) lP Poor/fair health -0.0184* (n=16513) (-0.0335–-0.00340) na Per 1,000 € increase in unemployment benefits expenditures per capita Unemployed -0.139 (n=1888) (-0.447–0.168) ur Per 1,000 € increase in pensions/old age expenditures per capita 65 years old 0.0000348 Jo (n=35283) (-0.00849–0.00856) 95% confidence intervals in brackets. * p < 0.05, **p < 0.01, ***p < 0.001 Constant calculated but not shown. All models adjusted by age, gender, health status before the pandemic, tested positive for COVID-19 oneself or someone close, household size, total COVID-19 cases per million inhabitants, and stringency index of policy responses to the pandemic. 38 Table A4. Individual-level determinants of change in the probability of worsened anxiety during the COVID-19 pandemic in 26 European countries, June-August 2020 Worsened anxiety during the COVID-19 pandemic Age group 50-64 reference 65-79 -0.0282* (-0.0548,-0.00165) 80+ -0.0570*** (-0.0718,-0.0423) Gender Male reference Female 0.0944*** (0.0643,0.124) Self-rated health before pandemic Excellent reference Very good 0.0254 (-0.00133,0.0521) Good 0.0692*** (0.0342,0.104) of Fair 0.144*** (0.114,0.174) ro Poor 0.201*** (0.157,0.244) Respondent COVID-19 positive -p Not positive reference Positive 0.0670 (-0.0456,0.179) re Anyone known COVID-19 positive No reference Yes 0.0296 lP (-0.0161,0.0754) Forgone healthcare during pandemic No reference na Yes 0.128*** (0.0905,0.165) Living alone 2 or more in household reference ur 1 person in household (living alone) 0.000318 (-0.0168,0.0175) Make ends meet during pandemic Jo Easily/Fairly easily reference With some/great difficulty 0.0495*** (0.0339,0.0651) Working before pandemic No or Retired reference Yes -0.00499 (-0.0180,0.00802) Became unemployed during pandemic No or Retired reference Yes 0.0725* (0.0157,0.129) Number of individuals 48560 R2 0.074 95% confidence intervals in brackets. * p < 0.05, **p < 0.01, ***p < 0.001 Robust standard errors clustered by country; constant calculated but not shown; all models adjusted by country indicator variables. 39 Table A5. Impact of stringency of policy responses to the pandemic on the change in the probability of worsened anxiety during the COVID-19 pandemic in 26 European countries, June-August 2020 Worsened anxiety during the COVID-19 pandemic Model 1 Models 2-9 Total COVID-19 cases per million inhabitants 0.0000314*** (0.0000239–0.0000390) Stringency index of policy responses to the pandemic 0.000975 (-0.000396–0.00235) Stringency index components: of C1 School closing -0.0189 (-0.0471–0.00925) ro C2 Workplace closing 0.0183 -p (-0.0231–0.0598) C3 Cancel public events -0.00549 re (-0.0528–0.0418) lP C4 Restrictions on gathering size 0.0370* (0.00817–0.0659) 0.0450* na C5 Close public transport (0.00522–0.0848) 0.0306* ur C6 Stay at home requirements (0.00653–0.0547) Jo C7 Restrictions on internal movement -0.00585 (-0.0277–0.0160) C8 Restrictions on international travel -0.0579*** (-0.0897–-0.0260) Number of individuals 48560 48560 Number of countries 26 26 R2 0.068 – 95% confidence intervals in brackets. * p < 0.05, **p < 0.01, ***p < 0.001 Constant calculated but not shown. Models 1-9 are adjusted for all variables included in Model 3, Table 2. Models 2-9 are adjusted for total COVID-19 cases per million inhabitants. C: component. 40 Table A6. Impact of social protection expenditures on the change in the probability of worsened anxiety during the COVID-19 pandemic in 26 European countries, June-August 2020 Worsened anxiety during the COVID-19 pandemic Models 1-9 Sample Per 1,000 € increase in social protection expenditures per capita All -0.00527* (n=49871) (-0.00932–-0.00121) Poor/fair health -0.0127*** (n=16516) (-0.0201–-0.00528) Unemployed -0.0244** (n=1888) (-0.0415–-0.00726) of 65 years old -0.00713*** (n=35286) (-0.0101–-0.00413) ro Difficulty make ends meet -0.00238 (n=17421) (-0.0118–0.00707) Per 1,000 € increase in health care/sickness expenditures per capita -p All -0.0161*** re (n=49871) (-0.0255–-0.00665) lP Poor/fair health -0.0305*** (n=16516) (-0.0483–-0.0127) Per 1,000 € increase in unemployment benefits expenditures per capita na Unemployed -0.414* (n=1888) (-0.742–-0.0857) ur Per 1,000 € increase in pensions/old age expenditures per capita 65 years old -0.00820 (n=35286) (-0.0173–0.000897) Jo 95% confidence intervals in brackets. * p < 0.05, **p < 0.01, ***p < 0.001 Constant calculated but not shown. All models adjusted by age, gender, health status before the pandemic, tested positive for COVID-19 oneself or someone close, household size, total COVID-19 cases per million inhabitants, and stringency index of policy responses to the pandemic. 41 Highlights * Multi-country study on mental health in the population aged 50 years and older in Europe during the COVID-19 pandemic * Mental health decline among older adults varies by socioeconomic group * More stringent physical distancing increases mental health decline in older adults * Stronger social protection might have mitigated risk of worse mental health in older adults of ro -p re lP na ur Jo Ethical Statement Hereby, I, Ana Méndez López, consciously assure that for the manuscript submitted the following is fulfilled: 1) This material is the authors' own original work, which has not been previously published elsewhere. 2) The paper is not currently being considered for publication elsewhere. 3) The paper reflects the authors' own research and analysis in a truthful and complete manner. 4) The paper properly credits the meaningful contributions of co-authors and co-researchers. 5) The results are appropriately placed in the context of prior and existing research. of 6) All sources used are properly disclosed (correct citation). Literally copying of text must be indicated as ro such by using quotation marks and giving proper reference. -p 7) All authors have been personally and actively involved in substantial work leading to the paper, and will take public responsibility for its content. re lP 3rd August 2021 Ana Méndez López na ur Jo