Quality of life of informal caregivers 50 years old and older in Spain by household living status: a descriptive study

Abstract

The number of informal caregivers aged 50 and older is growing, with potential health and quality of life (QoL) impacts influenced by living conditions, such as cohabitation with care recipients. This study examines the sociodemographic and health characteristics of Spaniards aged 50 + based on caregiving and household living status (non-caregivers, non-live-in caregivers, and live-in caregivers) and explores how these factors relate to QoL. This cross-sectional observational study analyses Spanish data from wave 8 of the Survey of Health, Ageing and Retirement in Europe (SHARE). We conducted descriptive analyses by caregiving and household status and applied multivariate linear regression to assess QoL, measured by the CASP-12 scale, incorporating caregiving status, sociodemographic, and health-related variables. One in five Spaniards aged 50 + provided informal care, with women being the majority (13% non-live-in, 6% live-in). Live-in caregivers were older, had poorer health, and reported lower QoL than non-live-in caregivers. Lower QoL was associated with older age, divorce, poorer perceived health, and depression. Loneliness had a significant impact: among lonely individuals, live-in caregivers reported the worst QoL. Caregivers’ QoL varies based on living arrangements, with loneliness playing a key role. Targeted interventions should address the unique needs of caregivers according to their household status.

Introduction

Traditionally, family and close social networks meet most of the care needs of dependent people, making the so-called informal care or family care a primary source of support¹. Despite most simplistic definitions conceiving informal care (unpaid help provided by kin or friends to a person who, due to health problems, presents limitations to carry out the daily routines) as the opposite of formal care², its conceptualisation is more complex. Informal care is a relational process that involves helping in instrumental, anticipatory, preventive and protective activities, and supervisory tasks³. Moreover, informal care has a strong emotional component that has implications for the health and quality of life (QoL) of caregivers and the receptors of care. QoL is defined as the “perception an individual has of his or her place in existence, in the context of the culture and the system of values in which he or she lives, according to his or her goals, expectations, norms and concerns”⁴. For caregivers, QoL is associated with factors such as care receptors’ conditions, social or financial support, or mental and physical health^5–9. Among all these factors, loneliness has proven to be a relevant factor for the quality of life of caregivers¹⁰.

A large body of research suggests that the provision of informal care inevitably jeopardizes the caregiver’s health and related outcomes, such as mortality, morbidity, or general well-being¹¹. Higher scores in caregiving burden have a strong correlation with poorer QoL among primary informal caregivers¹², being primary caregivers the individuals who are responsible for providing care to someone who cannot take care of themselves¹³. The intensity of care has been identified as a strong predictor of a burdensome caregiving experience. Longer caregiving hours per day and duration of caregiving are associated with higher caregiver burden¹⁴ and lower levels of physical and psychological well-being¹⁵. All these factors may be influenced by the household living status of the caregiver, since live-in caregivers may be exposed to more intense caring conditions.

The impact of informal care on the health and QoL of caregivers has been profusely researched in recent decades, but less in relation to the household living status of the caregiver. Studies about caregiving often include only live-in caregivers. By examining the household living status, we also focus on those caregivers who are not considered primary live-in caregivers but perform important care tasks. Secondly, the impact of household living status on caregivers’ health and QoL is not yet established. In this regard, some studies do not find that living in the same household as the care receptor has an impact on the caregiver’s burden^16,17. Other studies, which find differences in the impact of care on caregivers’ health depending on the household living status, have addressed the issue indirectly or in specific situations. Some studies focus on the relationship between caregiver and care receptor (spouse versus non-spouse, being most spouses live-in caregivers) and are limited to specific populations (care receptors with dementia)¹⁸; others were carried out during the COVID-19 pandemic, which implies a distortion of living status due to mobility restrictions¹⁹. In Spain, the distinction among household living status of the informal caregivers is especially relevant, considering that informal care is the main source of support and the living arrangements of older people. On one hand, it is estimated that 15% of the population provided care to dependent relatives in Spain in 2016²⁰, being the archetypical informal caregiver a woman, aged 50–64 years old, married, with children, and without paid employment²¹. On the other, more than half of informal caregivers in Spain co-reside with the care receptor²². Despite that, the impact of household living status has not been deeply researched in Spain, and the existing studies rarely compare caregivers’ QoL with the QoL of the general population²³.

This study has a twofold objective. Firstly, to describe sociodemographic and health profiles of people 50 years old and older in Spain considering their caregiving and household living status: non-caregivers, non-live-in caregivers, and live-in caregivers. Secondly, to examine how caregiving status, sociodemographic factors, and physical and mental health are related to QoL.

Methods

Study design

This study follows an observational, cross-sectional, quantitative design.

Sample selection

We used data from the Spanish sample of the 8th wave of the Survey of Health, Ageing and Retirement in Europe (SHARE), a survey addressed to people 50 years old and older from 28 European Countries and Israel²⁴. SHARE is a publicly available data collection, funded by the European Commission. The initial Spanish SHARE sample was recruited in 2004, through a stratified two-stage sampling method that consisted of a random stratified selection of first-stage units (municipalities), using data from the National Statistics Institute, followed by a random selection of primary sampling units (individuals born in 1954 or before). The initial sample of 2,324 individuals in wave 1 was refreshed in 2006, 2010, and 2012. In wave 8, the estimated response rate was 56%^25–27.

Data collection

SHARE collected data for wave 8 between 2019 and 2020, ending in March 2020, using computer-assisted personal interviewing of participants and informants. SHARE included questions about sociodemographic data, social support, children, physical health, behavioural risks, cognitive function, mental health, health care, employment and use of new technologies. Among these, we selected our variables for study²⁶.

Variables

The dependent variable was QoL, measured by the CASP-12 scale. This is a specific QoL scale for older people validated for the Spanish population²⁸. It includes four dimensions (control, autonomy, self-realisation and pleasure) and 12 Likert-type items, rated from 1 to 4. The final score ranges between 12 and 48, with higher scores meaning better QoL²⁹.

The independent variables were caregiver status, sociodemographic, and physical and mental health variables. Caregiver status was determined by caregiving and household living status and categorised as non-caregiver, non-live-in caregiver and live-in caregiver. Non-live-in caregivers were identified by the survey question: “In the last twelve months, have you personally given any kind of help listed on this card to a family member (excluding grandchildren) from outside the household, a friend or neighbour?”. The response included three types of help: personal help (shower, dressing…), domestic help (shopping, cooking…) and bureaucratic help. Live-in caregivers were identified by the question: “Is there someone living in this household whom you have helped regularly during the last twelve months with personal care, such as washing, getting out of bed, or dressing, excluding grandchildren?”. Individuals who responded affirmatively to both questions were classified as live-in caregivers. People who did not respond affirmatively to any of these questions were considered non-caregivers.

Sociodemographic variables were sex (male, female), marital status as registered in wave 4 and updated in wave 8 (with a partner, single, divorced, widowed), age in years (both continuous and categorical based on the median of 74 years old), number of children and years of education.

Physical and mental health variables included perceived limitation, number of chronic diseases, number of different kinds of drugs taken per week, depression, self-perceived health and loneliness. Perceived limitation was measured by the Global Activity Limitation Indicator (GALI) as severely limited; limited, but not severely; and not limited³⁰ and categorised as limited and not limited. The number of chronic diseases and different kinds of drugs taken by the participant at least once a week were self-reported. The number of chronic diseases was computed as continuous and categorical, to reflect the presence of multimorbidity³¹, defined as the presence of two or more chronic diseases. Depression was measured by the EURO-D scale, specifically designed for older people and validated in the Spanish population³². It is composed of 12 items, rated 0 (absence) or 1 (presence). The final score ranges from 0 to 12 (a higher score means higher depression) and it can be categorized into no depression or depression according to a cut-off point of 4³³. Self-perceived health was measured by the self-perceived health item, United States version, which is a good indicator of health³⁴. It ranges from 1 to 5, and a higher score indicates poorer health (1: Excellent, 2: Very good, 3: Good, 4: Fair, 5: Poor)³⁵. Loneliness was assessed by the UCLA Loneliness Scale. It is rated on a Likert-type scale with items assessing frequency, ranging from 1 (never or hardly ever) to 3 (often). The total score ranges between 3 and 9, with higher scores meaning higher loneliness^36,37. It was also categorized into “not lonely” or “lonely” according to the cut-off point of 3³⁸.

Other variables related to care were type and frequency of care, only reported for non-live-in caregivers; type of care, grouped into two categories: personal or domestic help; and bureaucratic help; and frequency, registered in the survey as daily, weekly, monthly or less than monthly.

Data analysis

First, we performed a descriptive analysis by caregiving status. For categorical variables, we estimated proportions (%), and for continuous variables, we estimated means (M) and Standard Errors (SE). We applied the Chi-square test to detect significant differences between proportions and the adjusted Wald test to compare means. Likewise, we carried out post-hoc pairwise comparisons to examine differences between groups.

Next, we performed multiple linear regression models to explain variations in QoL by caregiver status and sociodemographic, mental, and health variables. The results are presented as unstandardised Beta regression coefficients (β) with 95% confidence intervals (CI95), indicating the strength and precision of the associations.

To determine the covariates included in the final model, we previously conducted univariate linear regressions of QoL and the potential covariates. We selected variables according to the statistically significant associations found in the univariate regression models and their theoretical meaning assessed by expert knowledge.

We also explored different interactions between caregiver status and age, perceived health, depression score and loneliness.

We evaluated the assumptions of the final multiple linear regression model, including linearity, normality, homoscedasticity, and absence of multicollinearity, to ensure the model’s validity.

For statistical analyses, we used Stata 17, applying the weights available in the SHARE database for the Spanish sample²⁶. The quality of the variables was assessed, all variables included in the study had less than 8% missing data.

Results

Descriptive analysis

The final number of participants was 2,096: 904 men and 1,192 women, with a mean age of 74.5 years.

Table 1 shows the sociodemographic distribution of the population according to caregiver status: 81% of the participants were non-caregivers, 13% were non-live-in caregivers and 6% were live-in caregivers. The general profile of the caregivers was a woman (66% of non-live-in caregivers and 75% of live-in caregivers); with a partner (56% of non-live-in caregivers and 75% of live-in caregivers); and an average of 2 children. Non-live-in caregivers were significantly younger (M: 62.9, SE: 0.94) than non-caregivers (M: 68.6, SE:1.26) and live-in-caregivers (M: 71.2, SE: 3.07) (p: 0.001). Non-live-in caregivers provided care mostly to parents (43%) and other relatives or friends (46%), while live-in caregivers provided care mostly to partners (56%) or children (20%). Most non-live-in caregivers (80%) carried out domestic or personal care, while 20% carried out only bureaucratic tasks. More than half of non-live-in caregivers provided care at least weekly (27% daily, 30% weekly). The frequency of help for live-in caregivers was not registered in SHARE.

Table 1.

Sociodemographic and care variables by caregiver status.

	Non-caregivers		Non-live-in caregivers		Live-in caregivers		P*
	n (%) M (SE)	CI 95%	n (%) M (SE)	CI 95%	n (%) M (SE)	CI 95%
	1719 (81%)		210 (13%)		167 (6%)
Sex							0.111c
Men	762 (50%)	44%;56%	80 (34%)	15%;59%	62 (25%)	15%;40%
Women	957 (50%)	44%;55%	130 (66%)	41%;84%	105 (75%)	60%;85%
Marital status							0.244
With partner	1113 (67%)	57%;55%	154 (56%)	31%;78%	117 (75%)	58%;86%
Single	88 (10%)	6%;16%	10 (4%)	1%;13%	8 (6%)	2%;13%
Divorced	60 (9%)	5%;18%	8 (22%)	6%;55%	3 (0.2%)	0.05%;0.7%
Widow/widower	316 (14%)	10%;19%	23 (18%)	5%;46%	30 (19%)	11%;34%
Number of children	2.0 (0.08)	1.9;2.2	1.9 (0.18)	1.5;2.2	2.2 (0.12)	1.9;2.5	0.194
Years of education	9.4(0.52)	8.4;10.5	11.12 (1.17)	8.8;13.4	9.1 (0.65)	7.8;10.4	0.286
Age (years)							0.001 a, b
< 74	803 (69%)	60%;77%	160(92%)	85%;96%	71 (59%)	39%;76%
≥ 74	916 (31%)	23%;40%	50 (8%)	4%;15%	96 (41%)	39%;77%
Age (years)	68.6 (1.26)	66.1;71.0	62.9 (0.94)	61.1;64.8	71.2 (3.07)	65.1;77.3	0.001 a, b
Care receptor is							< 0.001
Partner			3 (0.1%)	0.02%;0.2%	94 (56%)	35%;75%
Parent			78 (43%)	24%;63%	24 (10%)	4%;22%
Son/daughter			36(11%)	5%;22%	30 (20%)	11%;33%
Other			93(46%)	26%;65%	19 (14%)	5%;36%
Type of help
Personal/domestic			181 (80%)	48%;95%
Bureaucratic only			29 (20%)	5%;51%
Frequency of help
Daily			50 (27%)	12%;50%
Weekly			59 (30%)	17%;48%
Monthly			28 (7%)	3-15%
Less than monthly			73 (36%)	18-59%

In bold, p < 0.05.

M (SE) mean (standard error), CI 95% confidence interval 95%.

*χ2 chi square test or adjusted Wald test.

^aPairwise comparison statistically significant (p < 0.05) between non-caregivers and non-live-in caregivers.

^bPairwise comparison statistically significant (p < 0.05) between non-live-in caregivers and live-in caregivers.

^cPairwise comparison statistically significant (p < 0.05) between non-caregivers and live-in caregivers.

Table 2 shows the physical and mental health characteristics of each group. Live-in caregivers showed higher scores of depression on the EuroD scale than non-live-in caregivers and non-caregivers (4.4 compared to 2.7 and 2.2 respectively, p: 0.002), had worse perceived health (3.6 compared to 3.1 and 3.3, p:0.025), and took a higher number of drugs per week (2.7 versus 1.6 and 1.9, p: 0.007). Live-in caregivers also had a worse QoL in the CASP-12 scale (M: 33.00, SE:1.25) than non-caregivers (M: 37.88, SE: 0.52) and non-live-in caregivers (M: 38.54, SE:0.97), (p: 0.002).

Table 2.

Physical and mental health variables by caregiver status.

	Non-caregivers		Non-live-in caregivers		Live-in caregivers		P*
	n (%) M (SE)	CI 95%	n (%) M (SE)	CI 95%	n (%) M (SE)	CI 95%
Perceived limitation							0.141
No	898 (57%)	49%;64%	146 (69%)	49%;83%	81 (41%)	23%;61%
Yes	808 (43%)	36%;51%	64 (31%)	17%;51%	86 (59%)	39%;77%
Chronic diseases							0.778
< 2	677 (56%)	47%;65%	101 (51%)	31%;70%	58 (53%)	33%;72%
≥ 2	1028 (44%)	35%;53%	109 (50%)	30%;69%	109 (47%)	28%;67%
N. of chronic diseases	1.6 (0.14)	1.4;1.9	1.7 (0.19)	1.4;2.1	2.0 (0.28)	1.5;2.6	0.390
Depression Euro-D							0.023 b, c
No	1116 (78%)	72%;84%	156 (75%)	55%;88%	86 (36%)	21%;56%
Yes	460 (22%)	16%;28%	50 (25%)	12%;45%	71 (64% a)	44%;79%
Depression EuroD (Range:1–12)	2.2 (0.18)	1.8;2.5	2.7 (0.20)	2.3;3.1	4.4 (0.60)	3.2;5.6	0.002 b, c
Perceived health (1: Excelent-5: Poor)	3.3 (0.09)	3.1;3.5	3.1 (0.20)	2.7;3.5	3.6 (0.11)	3.4;3.9	0.025 b, c
N. of different drugs /week	1.9 (0.16)	1.6;2.3	1.6 (0.19)	1.3;1.9	2.7 (0.29)	2.1;3.3	0.007 b, c
Loneliness UCLA LS3
Not lonely	1048 (64%)	56%;72%	157 (71%)	48%;87%	108 (53%)	30%;74%	0.578
Lonely	554 (36%)	28%;44%	52 (29%)	13%;52%	53 (47%)	26%;67%
Loneliness UCLA LS3 (Range: 3–9)	3.8 (0.10)	3.6;4.0	3.5 (0.19)	3.1;3.9	4.2 (0.39)	3.5;5.0	0.191
QoL CASP-12 (Range: 12–48)	37.9 (0.52)	36.8;38.9	38.5 (0.97)	36.6;40.4	33.0 (1.25)	30.5;35.5	0.001 b, c

In bold, p < 0.05.

M (SE) mean (standard error), CI 95% Confidence Interval 95%.

*Chi square test (categorical variables) or adjusted Wald test (continuous variables).

^aPairwise comparison statistically significant (p < 0.05) between non-caregivers and non-live-in caregivers.

^bPairwise comparison statistically significant (p < 0.05) between non-live-in caregivers and live-in caregivers.

^cPairwise comparison statistically significant (p < 0.05) between non-caregivers and live-in caregivers.

Regression model

Table 3 presents the associations between QoL and caregiving status, sociodemographic and health-related variables. The factors that showed a significant negative association with QoL were age (β: -0.1, p:0.003), being divorced (β: -4.6, p < 0.001), perceived health (β: -1.3, p < 0.001) and depression (β: -1.0, p < 0.001). Among the various interactions examined for caregiver status, only loneliness showed a significant association and was included in the regression (p < 0.01). In the group of participants who felt lonely, non-live-in caregivers had better QoL than non-caregivers (β: 3.6, p < 0.001), and live-in caregivers had worse QoL than non-caregivers (β: -2.6, p:0.001) (Fig. 1). This linear regression model explained 51% of the variance in QoL (R2 = 0.51).

Table 3.

Multiple linear regression model showing association between QoL, measured by CASP, and caregiving status, sociodemographic and health-related variables.

	β	CI95	p-value
Sex: women	0.6	0.5;1.7	0.287
Age*	−0.1	−0.1;−0.02	0.003
Marital status (Ref. with partner)
Single	1.0	−0.8;2.8	0.288
Divorced	−4.6	−6.9;−2.3	< 0.001
Widow/widower	−0.1	−1.1;0.9	0.856
Years of education*	0.03	0.3;2.5	0.574
Perceived health*	−1.3	−1.9;−0.7	< 0.001
Perceived limitation: limited	−1.2	−2.5;0.1	0.077
Number of chronic diseases*	0.2	−0.1;0.4	0.246
Depression*	−1.0	−1.22;−0.72	< 0.001
Loneliness: not lonely	2.0	1.0;3.0	< 0.001
Caregiving status (Ref. non-caregiver)
Non-live-in	3.6	2.1; 5.1	< 0.001
Live-in	−2.6	−4.1;−1.1	0.001
Loneliness # caregiver status
Lonely # non-live-in	4.1	2.0;6.1	< 0.001
Lonely # live-in	−0.4	−2.9;2.0	0.729

In bold, p < 0.05.

R-squared: 0.5127.

β unstandardised beta regression coefficient, CI95 confidence interval at 95% level.

*Indicates continuous variables.

Fig. 1.

Prediction of QoL by loneliness according to caregiver status.

Discussion

The objective of this study was to describe the sociodemographic and health profiles of people aged 50 years old and older in Spain, considering their household living and caregiving status and to examine how caregiving status, sociodemographic factors, and physical and mental health were related to QoL. In general terms, the profile of the informal caregiver in our study was a woman, with a partner and 2 children. This profile is in line with previous studies^39,40.

Also in line with previous research, we found a high proportion of non-live-in informal caregivers, although the methodological differences between the surveys on informal care in Europe make it difficult to compare the figures⁴¹. We also observed differences in socio-demographic and health-related variables between non-live-in and live-in caregivers, as shown in previous studies: Non-live-in caregivers were younger and had better-perceived health than live-in caregivers and non–caregivers²³. The relationships between the caregiver and the care receptor also varied: live-in caregivers were mostly spouses, while non-live-in caregivers were mostly children or friends of the care receptors. Live-in caregivers presented higher levels of depression and worse QoL than non-live-in caregivers and non-caregivers. However, to understand these results, we must consider that only 27% of non-live-in caregivers provided care daily. Although the frequency of care for live-in caregivers is not provided, live-in caregivers likely provide mostly daily care, which could lead to a higher caregiver burden and a higher impact of caregiving on their health and QoL⁴². When comparing the health status of non-living caregivers and non-caregivers, we must also consider the healthy caregiver bias, especially among non-live-in caregivers. The healthy caregiver bias refers to the fact that being a healthy individual increases the probability of taking on caregiving responsibilities, in a similar way to the healthy worker bias⁴³. Furthermore, part of the differences between both profiles could be explained by the distinctive perceived capacity of choice that they experience. Live-in caregivers, often spouses, are deeply involved in caring activities and may have more difficulty accessing leisure activities outside the home. So, the caregiver burden may be higher, with more limited mechanisms to compensate burden^44,45. Non-live-in caregivers can possibly assume caring tasks at specific times, maintaining certain freedom of choice (when to care) and greater access to leisure and recreational activities.

In the regression model, the factors related to worse QoL in this study were age, being divorced, worse perceived health, depression, and the interaction between household living status and loneliness. The relationship between these socioeconomic and health-related variables reproduces previous findings^43,46,47.

The association between loneliness and QoL was modified by caregiver status: live-in caregivers who feel lonely experienced lower levels of QoL than lonely non-live-in caregivers and lonely non-caregivers. Previous studies have observed that the association between loneliness and QoL may relate to social and cultural contexts and specific situations, like social connectedness⁴⁸. In Spain, live-in caregivers aged 50 years and older would experience a combination of circumstances, like insufficient role adoption⁴⁹, the feeling of having no choice⁵⁰ or less social connectedness⁴⁸ that lead to poor QoL. In contrast, non-live-in caregivers would compensate for their feelings of loneliness, so that their QoL would not be impacted.

Regarding the limitations of our study, this is a cross-sectional study; a longitudinal study would help to fully understand the associations found in our work. Although the Spanish sample is representative of the Spanish population 50 years old and older, the sample of caregivers is relatively small, and this may limit the statistical power of some of the analyses. Another limitation is that we do not have the same information about live-in and not-live-in caregivers, which conditions our analyses. SHARE is a general survey and does not measure the frequency and type of care provided by live-in caregivers, nor does it provide information about the characteristics of the care receptor if not in the same household as the caregiver, which are known to be determinant factors of caregivers’ QoL⁷.

Among the strengths of this work, it is worth highlighting the representativeness of the sample. SHARE database is a specific database for people 50 years old and older. The majority of informal caregivers in Spain belong to this age group (up to 61% of caregivers are between 45 and 64 years old⁵¹), so we believe that our results reflect the situation of informal care in Spain. The differential analysis performed between live-in caregivers, non-live-in caregivers and non-caregivers is often absent in studies on caregiving but had a deep impact on our findings^52,53. Also, the statistical analysis, incorporating interaction terms between caregiving status and health-related variables, revealed effect modification in the impact of loneliness, showing that its effect on quality of life differed between live-in caregivers, non-live-in caregivers, and the general population.

The results of this study contribute to advancing the knowledge about the relationship between informal caregiving and QoL in several directions. The research exploring the effect of informal care on health and QoL is mostly based on clinical or convenience samples. Population-based studies, as is the case of our study, are rare, but permit to control some of the problems related to convenience samples by comparing caregivers with non-caregivers recruited and enrolled with similar procedures. Previous studies encourage to carry out population-based studies to approach informal caregivers’ health and QoL to obtain a more realistic overview⁵⁴.

Conclusions

The present study suggests that, in Spain, a significant percentage of the population aged 50 years old and older, mainly women, carries out informal care tasks, most of them as non-live-in caregivers. There were important differences in terms of age, physical and mental health and QoL between caregivers depending on their household living status. Loneliness had a differential effect on QoL between caregivers according to household living status: live-in caregivers who feel lonely experience lower levels of QoL than lonely non-live-in caregivers and lonely non-caregivers.

The findings of this study have important implications for public health. When planning interventions for caregivers, we must consider non-live-in caregivers due to their significant number. However, due to their worse health conditions and quality of life, we must prioritize live-in caregivers. Interventions for live-in caregivers should address loneliness as a requisite, as it is related to lower QoL. The effect modification between loneliness and household living status points out the need to explore the caregiver’s QoL according to household living status, as there might be other factors that behave differently among live-in caregivers and non-live-in caregivers. More research is needed to understand the factors associated with caregivers’ QoL and the impact of household living status on the health and QoL of caregivers.

Abbreviations

QoL

Quality of life

SHARE

Survey of Health, Ageing and Retirement in Europe

GALI

Global activity limitation indicator

M

Means

SE

Standard error

β

Unstandardised beta regression coefficient

CI95

95% confidence intervals

Author contributions

ABA made the data analysis and wrote the manuscript. CFC contributed to the writing and critically reviewed the manuscript. CRB and MJF mentored and supervised the research, writing and publication process. AA prepared the dataset and contributed to the statistical analysis. ACL critically reviewed the manuscript.

Funding

This study was partially funded by Instituto Mixto de Investigación – Escuela Nacional de Sanidad (IMIENS) (Ref IMIENS-2021-001-PII), the Institute of Health Carlos III, Spain (Ref: PI22CIII/00043) and RICAPPS (Ref: RD21CIII/0003/0002).

Data availability

SHARE database is available via the SHARE Research Data Center website https://share-eric.eu/ .

Declarations

Competing interests

The authors declare no competing interests.

Ethics approval

The present study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of Carlos III Institute of Health (reference: CEI PI 62-2019). The SHARE project was reviewed and approved by the Ethics Council of the Max Planck Society.

Consent for publication

The manuscript has not been published elsewhere and is not under consideration by another publication. Each author has reviewed the manuscript and consents to its publication.