Health and sociodemographic determinants of excess mortality in Spanish nursing homes during the COVID-19 pandemic: a 2-year prospective longitudinal study
verfasst von:
Anna Escribà-Salvans, Javier Jerez-Roig, Pau Farrés-Godayol, Dyego Leandro Bezerra de Souza, Dawn A. Skelton, Eduard Minobes-Molina
Age, multimorbidity, immunodeficiency and frailty of older people living in nursing homes make them vulnerable to COVID-19 and overall mortality.
Objective
To estimate overall and COVID-19 mortality parameters and analyse their predictive factors in older people living in nursing homes over a 2-year period.
Method
Design: A 2-year prospective longitudinal multicentre study was conducted between 2020 and 2022.
Setting: This study involved five nursing homes in Central Catalonia (Spain).
Participants: Residents aged 65 years or older who lived in the nursing homes on a permanent basis.
Measurements: Date and causes of deaths were recorded. In addition, sociodemographic and health data were collected. For the effect on mortality, survival curves were performed using the Kaplan-Meier method and multivariate analysis using Cox regression.
Results
The total sample of 125 subjects had a mean age of 85.10 years (standard deviation = 7.3 years). There were 59 (47.2%) deaths at 24 months (95% confidence interval, CI, 38.6–55.9) and 25 (20.0%) were due to COVID-19, mostly in the first 3 months. In multivariate analysis, functional impairment (hazard ratio, HR 2.40; 95% CI 1.33–4.32) was a significant risk factor for mortality independent of age (HR 1.17; 95% CI 0.69–2.00) and risk of sarcopenia (HR 1.40; 95% CI 0.63–3.12).
Conclusion
Almost half of this sample of nursing home residents died in the 2‑year period, and one fifth were attributed to COVID-19. Functional impairment was a risk factor for overall mortality and COVID-19 mortality, independent of age and risk of sarcopenia.
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Abkürzungen
AHT
Arterial hypertension
BMI
Body mass index
CFS
Clinical frailty scale
CI
Confidence interval
COVID-19
Coronavirus disease
CVA
Cerebral vascular accident
HR
Hazard ratio
ICC
Interclass correlation coefficient
MDS
Minimum data set
MNA
Mini nutritional assessment
NH
Nursing homes
PCR
C‑reactive protein
PPE
Personal protective equipment
RAT
Rapid antigen tests
SARC‑F
Questionnaire assistance in walking, rising from chair, climbing stairs and falling
SB
Sedentary behaviour
SD
Standard deviation
SPSS
Statistical Package Social Sciences
STROBE
Strengthening the Reporting of Observational Studies in Epidemiology
UI
Urinary incontinence
WTMB
Waking-time movement behaviours
Introduction
The coronavirus disease 2019 (COVID-19) pandemic began to have a major impact on society in 2019 [1] having unprecedented consequences on global health and economic systems.
In developed European countries with a very high older population the COVID-19 mortality was 83.7% for people > 70 years and 16.2% for people younger than 69 years in 2020 [2] with a higher prevalence of COVID-19 deaths in nursing homes (NH) [3]. Health problems and geriatric syndromes associated with ageing also determined the risk of mortality [4‐9].
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At the beginning of the pandemic Spain had a total of 326,613 people institutionalised in NHs [10] and a study conducted in Madrid reported a 14% mortality rate in older adults with COVID-19 in NHs [7]. The COVID-19 mortality has already been extensively studied in several countries, although most of these follow-ups have not exceeded 1 year [11]. Longer follow-ups would enable more accurate data and the identification of predictive factors that may be relevant to clinical practice.
The main aim of the study was to estimate overall and COVID-19 mortality parameters and analyse their predictive factors in older people living in NHs over a 2-year period.
Methodology
Study design and population
This is a 2-year multicentre observational cohort study. The study was conducted in five NH in Central Catalonia, Spain. It was designed following the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) standards for cohort studies [12, 13]. Residents aged 65 years and older permanently living in NH were included. Those in a coma or palliative care (short-term prognosis), those who refused (or their legal guardian) to participate in the study and those who left the NH during the 2‑year cohort period were excluded.
Sample size
For the calculation of the sample, the article by Burgaña Agoües et al. (2021) was taken as a reference due to its methodological similarity to the present article: Burgaña studied pandemic mortality due to COVID-19 in Spain, in people over 65 years of age resident in NH. Considering the findings of Burgaña Agoües et al. (2021) [14], i.e. the difference in proportions between individuals with severe functional impairment (23.0%) and deceased (11.1%), and with a confidence interval (CI) of 95% and a power of 80%, a sample size of 122 participants was estimated.
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Study procedures
The primary outcomes were all-cause mortality and COVID-19 over the 2‑year follow-up period. The mortality registry included cause and date of death, deaths in total, deaths due to COVID-19 including confirmed cases, and deaths due to symptomatic suspicion of COVID-19 [15]. Additional COVID-19 data collected included the presence of the disease, whether they had symptoms [16], the performance of COVID-19 screening tests such as C‑reactive protein (CRP), serological tests, and/or rapid antigen tests for SARS-CoV‑2 (RAT) [17]. The information was collected through on-line interviews with NH professionals as due to COVID-19, they could not be accessed.
Sociodemographic and health information was obtained from health centre records and cross-checked with health professionals. All sociodemographic variables and those described in this article were collected at baseline (January 2020), just before the onset of the COVID-19 pandemic in Spain. Falls (number) during the last year were obtained from NH registers. Nutritional status was assessed using the mini nutritional assessment (MNA) [18]. The SARC‑F [19] was used to identify individuals at risk of developing sarcopenia. Functional capacity was measured using the modified Barthel index and results were classified according to the degree of dependency as: independent, slightly dependent, moderately dependent, severely or totally dependent [20]. Continence status was reported using section H of the minimum data set (MDS) version 3.024 [21]. Cognitive status was assessed using the Pfeiffer scale [22] and frailty using the clinical frailty scale (CFS) [23]. Sedentary behaviour (SB) and waking-time movement behaviours (WTMB) were assessed using the ActivPAL 3TM activity monitor (PAL Technologies Ltd., Glasgow, UK) [24].
The study was conducted over a 2-year period and ended in March 2022.
Statistical analysis
The nominal and ordinal quantitative variables were expressed according to frequency in percentages and the quantitative variables with mean and standard deviation (SD). Survival curves were formed using the Kaplan-Meier method and multivariate analysis was performed by Cox regression, using the hazard ratio (HR) as the measure of effect. The Statistical Package for the Social Sciences 27 (SPSS Inc., Chicago, IL, USA) was used for the analysis.
Results
We recruited 125 people, 67.6% of the total number of NH residents in the main study. Finally, 7 (3.8%) participants who left NHs to reside elsewhere were excluded (Fig. 1).
Fig. 1
Flow chart of the sampling process
×
The mean age of the participants was 85.1 years (SD = 7.3 years) and 104 (83.2%) were female. The mean number of months living in NH was 27.5 months (SD = 112.14 months). The analysis of health and sociodemographic variables is described in Table 1.
Table 1
Descriptive analysis of the sample of institutionalized older adults living in nursing homes of Central Catalonia, Spain (n = 125)
Variables
Frequency (%)/mean (SD)
NH type
State subsidized places
40 (32.0)
Private
85 (68.0)
Smoking
6 (4.8)
Drinkers
9 (12.7)
Chronic conditions
5.0 (2.46 SD)
Hypertension
80 (64.0)
Dementia
68 (54.4)
Cardiac pathology
51 (40.8)
Depression
36 (28.8)
Diabetes mellitus tape 2
36 (28.8)
Renal pathology
32 (25.6)
CVA
25 (20.0)
Cancer
23 (18.4)
Pulmonary pathology
22 (17.6)
Urinary incontinence
Yes
87 (69.6)
No
35 (28.0)
Unclassifiable
3 (2.4)
Fecal incontinence
Yes
36 (28.8)
No
87 (69.6)
Unclassifiable
2 (1.6)
Fall/s in previous year
58 (46.4)
Nutritional status
Involuntary weight loss
25 (13.5)
Risk of malnutrition or malnourished
56 (44.8)
Obesity
78 (62.4)
Risk of sarcopenia
94 (75.2)
Functional impairment
Independent
7 (5.6)
Slightly dependent
47 (37.6)
Moderately dependent
19 (15.2)
Severely or totally dependent
52 (41.6)
Cognition
No cognitive deficit
10 (8.0)
Mild cognitive deficit
20 (16.0)
Moderate cognitive deficit
24 (19.2)
Severe cognitive deficit
58 (46.4)
Unknown
13 (10.4)
SB and WTMB
Waking hours
11.0 (1.5 SD)
% of waking time in SB
82.6% (17.5 SD)
Hours in upright position (standing and walking)
1.6 (1.7 SD)
Steps per day
1.345 (2417.4 SD)
Sit to stand transitions per day
18.2 (18.3 SD)
Hospitalization
26 (0.43 SD)
SD standard deviation, NH nursing homes, CVA cerebral vascular accident, SB sedentary behaviour, WTMB waking-time movement behaviour
In the 2‑year period from baseline to the end of the study, 59 participants (47.2%) died, of whom 25 (20.0%) died from COVID-19 and 34 (27.2%) from other causes. All COVID-19 deaths occurred in the first year of the study: 44 (74.5%) of the 59 individuals had already died within the first 90 days (at the peak of COVID-19).
Survival and associated factors according to the variable mortality
In the bivariate analysis, mortality was associated with functional impairment, urinary incontinence (UI), faecal continence, risk of sarcopenia, % of waking time in SB and with a p-value of less than 0.05. All other health and sociodemographic variables were not significant (Table 2).
Table 2
Association of variables to health, functional and sociodemographic1 with mortality (n = 125)
Variables
n (%)
Number of deaths
Number of survivors
Probability of death (%)
p (Log rank)
Functional impairment (n = 125)
No/mild or moderate
73 (58.4)
24
49
65.3
0.001*
Total impairment
52 (41.6)
35
17
31.6
Urinary incontinence (n = 122)
No
35 (28.0)
10
25
66.8
0.008*
Yes
87 (69.6)
49
38
43.2
Risk of sarcopenia (n = 125)
No
31 (24.8)
9
22
71.0
0.018*
Yes
94 (75.2)
50
44
45.0
% waking time in SB (n = 84)
≤ 85%
41 (48.8)
11
30
73.2
0.028*
> 85%
43 (51.2)
22
21
48.4
Fecal incontinence (n = 123)
No
87 (70.7)
35
52
57.9
0.029*
Yes
36 (29.3)
22
14
38.4
NH type (n = 125)
State subsidized places
40 (32.0)
14
26
64.8
0.076
Private
85 (68.0)
45
40
46.1
Nutritional status (n = 79)
Normal
23 (29.2)
7
16
69.6
0.082
At risk or malnourished
56 (70.8)
31
25
43.6
Drinkers (n = 71)
No
62 (87.3)
34
32
45.5
0.249
Yes
9 (12.7)
1
4
80.0
SB sedentary behaviour, NH nursing homes
1 With a p value lower than 0.250
* Statistically significant (< 0.05)
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The variables were tested for collinearity and none of them showed collinearity with each other. A multivariate analysis was performed with the model with adjusted values including the variables age with severe functional impairment and risk of sarcopenia. The result showed that functional impairment predicted mortality independently of age (which was not statistically significant) and sarcopenia risk (Table 3).
Table 3
Survival univariate and multivariate Cox analysis1 in older people living in NHs (n = 125)
Variables
HR (ref.)
CI (95%)
p (Cox)
HR (ref.)
CI (95%)
p (Cox)
Univariate analysis
Multivariate analysis
Functional impairment (n = 125)
No/mild or moderate
–
–
–
–
–
–
Total impairment
2.77
(1.64–4.67)
0.001*
2.40
(1.33–4.32)
0.003*
Urinary incontinence (n = 122)
Yes
–
–
–
–
–
–
No
2.43
(1.23–4.81)
0.010*
–
–
–
Risk of sarcopenia (n = 125)
Yes
–
–
–
–
–
–
No
2.29
(1.12–4.66)
0.022*
1.40
(0.63–3.12)
0.403
Fecal incontinence (n = 123)
No
–
–
–
–
–
–
Yes
1.80
(1.05–3.07)
0.031*
–
–
–
% waking time in SB (n = 84)
≤ 85%
–
–
–
–
–
–
> 85%
2.20
(1.07–4.55)
0.033*
–
–
–
NH type (n = 125)
Private
–
–
–
–
–
–
State subsidized places
0.85
(0.32–1.06)
0.080
–
–
–
Nutritional status (n = 79)
Normal
–
–
–
–
–
–
Risk or malnourished
2.04
(0.89–4.64)
0.089
–
–
–
Age (years, n = 125)
≤ 85
–
–
–
–
–
–
> 86
1.33
(0.78–2.26)
0.284
1.17
(0.69–2.00)
0.549
HR hazard ratio, CI confidence interval, SB sedentary behaviour, NH nursing homes
1 Variables with a p value lower than 0.250 in univariate analysis are shown
* Statistically significant (p < 0.05)
Survival and associated factors according to the variable COVID-19 or other-cause mortality
In the univariate analysis, functional impairment, living in a private NH, being older than 86 years, malnutrition and being female were risk factors for COVID-19 mortality. Functional impairment was associated with mortality from other health causes with a p-value of less than 0.050 (Tables 4 and 5; Fig. 2).
Table 4
Analysis of the association of health and sociodemographic variables1 NH residents with mortality (COVID-19 or other causes) (n = 59)
Variables
n (%)
Deaths for covid-19 (number of events)
Deaths due to other causes
(number of events)
Probability of death (%)
p (Log rank)
Nutritional status (n = 38)
Normal
7 (18.4)
5
2
28.6
0.022*
Risk or malnourished
31 (81.6)
10
21
61.8
Sex (n = 59)
Male
9 (15.2)
6
3
14.6
0.041*
Female
50 (84.7)
19
31
29.8
Functional impairment (n = 59)
No/mild or moderate
24 (40.6)
15
9
26.1
0.045*
Total impairment
35 (59.3)
10
25
63.5
% waking time in SB (n = 33)
≤ 85%
11 (33.3)
7
4
36.4
0.082
> 85%
22 (66.6)
6
16
68.7
Fecal incontinence (n = 57)
No
35 (61.4)
18
17
37.6
0.132
Yes
22 (38.6)
6
16
68.2
Hospitalizations (n = 46)
No
34 (73.9)
17
17
32.0
0.194
Yes
12 (26.1)
4
8
58.2
SB sedentary behaviour, NH nursing homes
1 With a p value lower than 0.250
* Statistically significant (< 0.05)
Table 5
Univariate Cox analysis: association of COVID-19 mortality with other causes of death in relation to covariables1 in older people living in NHs (n = 59)
1 Variables with a p value lower than 0.250 are shown
* Statistically significant (< 0.05)
Fig. 2
Kaplan-Meier survival estimates
×
We tested for collinearity between the variables and none of them were collinear with each other. The number of individuals in this variable is 59. Different combinations of significant variables, such as functionality, age and type of NH among others, were tested by multivariate analysis, but no significant results were found (Table 5).
Discussion
The main objective of this study was to examine the incidence of all-cause and COVID-19 mortality and to analyse the predictive factors in older NH residents over a 2-year period since the onset of the pandemic.
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The results indicate that almost half of participants died with 20% being attributed to COVID-19. Most of the deaths (74.5%) were in the first 3 months of the study, coinciding with the outbreak of the COVID-19 pandemic in Spain. In the second year of the study, the survival curve became horizontal again, after the implementation of preventive measures. This study shows a higher incidence of mortality in the 1‑year period than other studies. Several articles on the pandemic phase report data on excess mortality [11]. A study in Barcelona reported a 3-month COVID-19 mortality rate of 11.1% in institutionalised older people [14]. For deaths from other causes, they reported excess mortality among institutionalised cases (34.8%) [14].
We also report the association of health, social and demographic variables with mortality: functional impairment, UI, sarcopenia risk and % of waking time in SB were found to be factors associated with mortality and functional impairment, type of NH and age were associated with COVID-19 mortality. The literature shows that UI and risk of sarcopenia are associated with mortality [25‐27] and those who spent more time in SB had a higher risk of mortality [28].
Unlike other studies, our data show an increase of mortality in private NHs [29]. The NH type and size influenced mortality during the COVID-19 pandemic in other studies [29]. Braun et al. (2020) attributed these results to the lack of organisation and shortage of personal protective equipment (PPE) in private NHs [29].
This study has the limitation of the COVID-19 pandemic, which impeded access to NHs, increased deaths in older people and did not enable us to have a larger sample.
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The strength of the study lies in the telematic data collection in NHs. This enabled us to extract real information on the health and social status of residents. The fact that we collected data prior to the start of the pandemic allowed us to make a comparison of the health and sociodemographic status of institutionalised older people. By having a cross-sectional analysis of the prepandemic sample, we provide data on the factors that predicted the risk of dying in a 2-year follow-up.
Conclusion
Almost half of this sample of NH residents died during the 2‑year observation period. One fifth of deaths were attributed to COVID-19 mostly in the first quarter, coinciding with the peak of the pandemic. Functional impairment was a risk factor for overall mortality and COVID-19 mortality, independent of age and risk of sarcopenia.
Acknowledgements
We thank all the members of the study NH for their contribution to this work and the older adults who participated in the study.
Funding
This work was supported by the Hestia Chair from Universitat Internacional de Catalunya (grant number BI-CHAISS-2019/003) and the research grant from the Catalan Board of Physiotherapists Code R03/19.
Dyego Leandro Bezerra de Souza thank CNPq (Brazilian National Council for Scientific and Technological Development) productivity grants 315962/2023-2.
Declarations
Conflict of interest
A. Escribà-Salvans, J. Jerez-Roig, P. Farrés-Godayol, D.L. Bezerra de Souza, D.A. Skelton and E. Minobes-Molina declare that they have no competing interests.
Ethical approval was obtained from the Ethics and Research Committee of the University of Vic—Central University of Catalonia (registration number 92/2019 and 109/2020). Signed informed consent was obtained from the residents or the legal guardians. The project meets the criteria required in the Helsinki Declaration as well as the Organic Law 3/2018 (5 December) on the Protection of Personal Data and Guarantee of Digital Rights.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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Health and sociodemographic determinants of excess mortality in Spanish nursing homes during the COVID-19 pandemic: a 2-year prospective longitudinal study
verfasst von
Anna Escribà-Salvans Javier Jerez-Roig Pau Farrés-Godayol Dyego Leandro Bezerra de Souza Dawn A. Skelton Eduard Minobes-Molina