Factors Associated with Mortality among Elderly People in the COVID-19 Pandemic (SARS-CoV-2): A Systematic Review and Meta-Analysis

Abstract

The objective of this meta-analysis was to evaluate the factors associated with the mortality of elderly Italians diagnosed with coronavirus who resided in institutions or who were hospitalized because of the disease.

Methods:
A systematic review following the recommendations of The Joanna Briggs Institute (JBI) was carried out, utilizing the PEO strategy, i.e., Population, Exposure and Outcome. In this case, the population was the elderly aged over 65 years old, the exposure referred to the SARS-CoV-2 pandemic and the outcome was mortality. The National Center for Biotechnology Information (NCBI/PubMed), Latin American and Caribbean Literature in Health Sciences (LILACS), Excerpta Medica Database (EMBASE) and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases were used until 31 July 2020.

Results:
Five Italian studies were included in this meta-analysis, with the number of elderly people included varying between 18 and 1591 patients. The main morbidities presented by the elderly in the studies were dementia, diabetes, chronic kidney disease and hypertension.

Conclusions:
The factors associated with the mortality of elderly Italian people diagnosed with SARS-CoV-2 who lived in institutions or who were hospitalized because of the disease were evaluated. It was found that dementia, diabetes, chronic kidney disease and hypertension were the main diagnosed diseases for mortality in elderly people with COVID-19.

Full text

International Journal of
Environmental Research
and Public Health
Review
Factors Associated with Mortality among Elderly People in the
COVID-19 Pandemic (SARS-CoV-2): A Systematic Review and
Meta-Analysis
Vicente Paulo Alves 1,2 ,* , Francine Golghetto Casemiro 3, Bruno Gedeon de Araujo 1,
Marcos Andréde Souza Lima 1, Rayssa Silva de Oliveira 1, Fernanda Tamires de Souza Fernandes 1,
Ana Vitória Campos Gomes 1and Dario Gregori 2


Citation: Alves, V.P.; Casemiro, F.G.;
Araujo, B.G.d.; Lima, M.A.d.S.;
Oliveira, R.S.d.; Fernandes, F.T.d.S.;
Gomes, A.V.C.; Gregori, D. Factors
Associated with Mortality among
Elderly People in the COVID-19
Pandemic (SARS-CoV-2): A
Systematic Review and
Meta-Analysis. Int. J. Environ. Res.
Public Health 2021,18, 8008. https://
doi.org/10.3390/ijerph18158008
Academic Editor: Paul B. Tchounwou
Received: 18 May 2021
Accepted: 22 July 2021
Published: 29 July 2021
Publisher’s Note: MDPI stays neutral
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Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1Stricto Sensu Graduate Program in Gerontology/Medicine, University Catholic of de Brasília,
Taguatinga 71966-700, Brazil
; brunogedeon@gmail.com (B.G.d.A.); marcosandreiteb@gmail.com (M.A.d.S.L.);
rayssaolimed@gmail.com (R.S.d.O.); fernandatamires.sf@gmail.com (F.T.d.S.F.);
anavitoriag@hotmail.com (A.V.C.G.)
2Unit of Biostatistics, Epidemiology and Public Health, Padova University, 35122 Padova, Italy;
dario.gregori@unipd.it
3Ribeirão Preto School of Nursing, University of São Paulo, São Paulo 14040-902, Brazil;
francine_gc@hotmail.com
*Correspondence: vicerap@gmail.com or vicente@p.ucb.br
Abstract:
The objective of this meta-analysis was to evaluate the factors associated with the mortality
of elderly Italians diagnosed with coronavirus who resided in institutions or who were hospitalized
because of the disease. Methods: A systematic review following the recommendations of The Joanna
Briggs Institute (JBI) was carried out, utilizing the PEO strategy, i.e., Population, Exposure and
Outcome. In this case, the population was the elderly aged over 65 years old, the exposure referred
to the SARS-CoV-2 pandemic and the outcome was mortality. The National Center for Biotechnology
Information (NCBI/PubMed), Latin American and Caribbean Literature in Health Sciences (LILACS),
Excerpta Medica Database (EMBASE) and Cumulative Index to Nursing and Allied Health Literature
(CINAHL) databases were used until 31 July 2020. Results: Five Italian studies were included in this
meta-analysis, with the number of elderly people included varying between 18 and 1591 patients.
The main morbidities presented by the elderly in the studies were dementia, diabetes, chronic kidney
disease and hypertension. Conclusions: The factors associated with the mortality of elderly Italian
people diagnosed with SARS-CoV-2 who lived in institutions or who were hospitalized because
of the disease were evaluated. It was found that dementia, diabetes, chronic kidney disease and
hypertension were the main diagnosed diseases for mortality in elderly people with COVID-19.
Keywords:
SARS-CoV-2; COVID-19; non-communicable chronic diseases (NCCDs); clinical features;
institutionalized or hospitalized elderly; meta-analysis
1. Introduction
One of the greatest achievements of humanity has been longevity, which—although
there are still differences between countries influenced by the socioeconomic context of
each—in general, is led by progress in the population’s health markers. Achieving old age,
which was once the privilege of a few, has now become one of the world’s main goals and
challenges [1].
In this way, aging has become a global phenomenon and a success story for public
health policies and socioeconomic development. However, there are new challenges for
society that this presents. Our society needs to adapt to this new scenario, to maximize
the functional capacity and health of the elderly and to promote their social inclusion
and safe participation [
1
]. In view of this, there are social consequences of the aging
population and new public health issues arising that affect European countries, such
Int. J. Environ. Res. Public Health 2021,18, 8008. https://doi.org/10.3390/ijerph18158008 https://www.mdpi.com/journal/ijerph

Int. J. Environ. Res. Public Health 2021,18, 8008 2 of 9
as Italy, in particular [
2
]. In Italy, the profile of the elderly population is of a group
with a high prevalence of non-communicable chronic diseases (NCCDs) and associated
comorbidities [
1
]. In Italy, aging is a common and growing phenomenon. Italy is considered
the country with the second largest number of elderly people [
2
], along with a mortality
rate that has decreased by more than 50% in the last 30 years, mainly due to the reduction
in cardiovascular diseases [3].
The COVID-19 pandemic (SARS-CoV-2) has caused considerable mortality in popula-
tions considered at risk, such as the elderly population, especially those who are institution-
alized, a scenario in which social isolation is difficult in a situation such as a pandemic. The
vulnerability of this population is linked with the physiological aspects of aging, which
impact the effectiveness of the immune system, triggering morbidity and mortality from
infectious diseases [4].
Thus, it is necessary to investigate the main factors that make institutionalized elderly
people more vulnerable to death. Fragility is a condition that worsens with advancing age
and with COVID-19 infection, especially for the hospitalized elderly, who tend to develop
a more accentuated presentation of the classic symptoms of the disease [5].
Since the onset of the COVID-19 pandemic, several studies have begun to be carried
out in different contexts, generating scientific evidence and statistical data that point in
certain directions. It has become a challenge for all related researchers to contribute to the
advancement of knowledge regarding the reach of COVID-19 and the factors associated
with mortality. In this specific case, it was proposed that we carry out a systematic
review of studies published in Italy between March and July 2020 to identify such factors.
The decision to select texts that were published from Italian research was made as local
transmission first took place in Italy before the spread of COVID-19 went on to impact
other European regions [6].
In Italy, the contagion’s outbreak started on 20 February 2020, with the number of
confirmed cases increasing by 428% in the following 30 days. Residential facilities for the
elderly were the hardest hit, according to data released by the Istituto Superiore di Sanità
(ISS) [
7
]. The elderly who died in these residential establishments due to COVID-19, who
underwent the reverse transcription-polymerase chain reaction (RT-PCR) tests to confirm
their infection, represent around 7.4% of all deaths from the period. When adding all those
who died with flu symptoms (without an objective assessment) to these data, the number
of deaths represents 41.2%. A survey was carried out by the ISS in July 2020, which sent a
questionnaire to 3417 establishments, of which 1356 responded, accounting for a total of
97,521 elderly living residents [8].
The objective of this study was to synthesize the factors associated with the mortality
of elderly Italian people diagnosed with coronavirus who lived in institutions or who were
hospitalized because of the disease.
2. Materials and Methods
2.1. Search Strategy and Selection Criteria
The systematic review format was chosen based on the recommendations of The
Joanna Briggs Institute (JBI), following the nine steps for its development: (1) construction
of the preliminary research protocol; (2) formulation of the review question; (3) definition
of inclusion and exclusion criteria; (4) search strategy; (5) selection of studies for inclusion;
(6) data extraction; (7) synthesis of the data; (8) narrative summary; (9) references [9].
This study used public, free-to-access articles located in databases of scientific litera-
ture. Primary studies on the mortality of elderly Italians with a diagnosis of coronavirus
were selected, with publications in the English, Italian and Spanish languages included,
which carried out quantitative and qualitative analyses. To formulate the research question,
the PEO strategy was used, i.e., Population, Exposure and Outcome [
10
]. It was determined
that the “Population” (P) would be the elderly aged over 65 years, the “Exposure” (E)
would be the SARS-CoV-2 pandemic and the “Outcome” (O) would be mortality. Thus, the

Int. J. Environ. Res. Public Health 2021,18, 8008 3 of 9
guiding question of this study was: “What are the factors related to the mortality of Italian
elderly people diagnosed with the COVID-19 (SARS-CoV-2) disease?”
The inclusion criteria for the selection of articles were:
•Primary studies on the mortality of elderly people diagnosed with coronavirus;
•Studies in English, Spanish or Italian.
Once the inclusion criteria were established, these were set as the exclusion criteria:
•Studies that were not of Italian elderly people;
•Studies on the elderly who were not institutionalized or hospitalized;
•Studies that did not answer the guiding question of the systematic review.
2.2. Data Extraction and Analysis
The search for publications was carried out in July 2020 in the following databases:
The National Center for Biotechnology Information (NCBI/PubMed), Latin American and
Caribbean Literature in Health Sciences (LILACS), Excerpta Medica Database (EMBASE)
and Cumulative Index to Nursing and Allied Health Literature (CINAHL). The search
strategy combined controlled and uncontrolled descriptors, according to the indication
offered in each database. To search for articles on PubMed, controlled descriptors from
Medical Subject Headings (MeSH) were used; Heading-MH was consulted for the CIN-
HAL database; Embase subject headings (EMTREE) were used to search EMBASE; Health
Sciences Descriptors (DeCS) was used to search LILACS. For these searches, “aged”, “coro-
navirus infections” and “mortality” were used. The Boolean operator “AND” was used in
all combinations as follows: “aged AND mortality AND coronavirus infections”. There
was no time limit for publication. For the selection of articles, the Rayyan application,
developed by the QCRI (Qatar Computing Research Institute), was used, which helps in
systematic reviews by facilitating the selection process for reading articles. That process
took place in three stages: in the first stage, the databases were searched; secondly, the title
and abstract were read: two researchers performed a bibliographic search and indepen-
dently extracted data from the included studies, where disagreements were resolved by a
third investigator or by consensus, with the aim being to identify studies for the third stage;
thirdly, the articles were read in full, with the aim of selecting those that were in agreement
with the inclusion criteria [11].
While developing the search and selection of articles, from searching the databases to
selecting studies by reading titles and abstracts or the full text, the PRISMA protocol was
used [12] (Figure 1) to guarantee the rigor of the systematic review [11].
Int. J. Environ. Res. Public Health 2021, 18, x 4 of 10
Figure 1. Flow diagram of the number of studies selected and included in the meta-analysis.
From the findings, the results were organized by performing a descriptive synthesis
of the data, as shown in Table 1.
Table 1. Descriptive synthesis of the data.
Author/Year Journal Aim Elderly
Sample Sample Location
Bianchetti et al. (2020)
Journal of Nutri-
tion, Health and
Aging
To evaluate the prevalence,
clinical characteristics and
outcomes of dementia in
individuals hospitalized for
infection with COVID-19.
627
Hospitals and nursing
homes in the province
of Brescia, Northern
Italy.
Stroppa et al. (2020) Future Oncology
To describe the cases of 25
cancer patients who were
infected with COVID-19.
18
Piacenza’s general
hospital, Northern
Italy.
Deiana et al. (2020)
International Jour-
nal of Environmen-
tal Research and
Public Health
To describe the clinical
characteristics of patients who
died after a positive test for the
SARS-CoV-2 infection and
evaluate the influence of health
conditions associated with death
as the outcome.
573 Sardinia, Italy
Bonetti et al. (2020)
Clinical Chemistry
and Laboratory
Medicine (CCLM)
To describe laboratory findings
in a group of Italian patients
with COVID-19 in the
Valcamonica area and correlate
the abnormalities with the
severity of the disease.
518
Emergency Department
of the Valcamonica
Hospital (Esine, Brescia,
Lombardia, Italy).
Iaccarino et al. (2020) Hypertension
To check if renin and
angiotensin, the system
inhibitors, are related to serious
outcomes of COVID-19 infection.
1591 Multicenter study.
Figure 1. Flow diagram of the number of studies selected and included in the meta-analysis.

Int. J. Environ. Res. Public Health 2021,18, 8008 4 of 9
From the findings, the results were organized by performing a descriptive synthesis
of the data, as shown in Table 1.
Table 1. Descriptive synthesis of the data.
Author/Year Journal Aim Elderly Sample Sample Location
Bianchetti et al. (2020) Journal of Nutrition,
Health and Aging
To evaluate the prevalence, clinical
characteristics and outcomes of
dementia in individuals hospitalized
for infection with COVID-19.
627
Hospitals and nursing homes
in the province of Brescia,
Northern Italy.
Stroppa et al. (2020) Future Oncology
To describe the cases of 25 cancer
patients who were infected
with COVID-19.
18 Piacenza’s general hospital,
Northern Italy.
Deiana et al. (2020) International Journal of
Environmental Research
and Public Health
To describe the clinical characteristics
of patients who died after a positive
test for the SARS-CoV-2 infection and
evaluate the influence of health
conditions associated with death as
the outcome.
573 Sardinia, Italy
Bonetti et al. (2020) Clinical Chemistry and
Laboratory Medicine
(CCLM)
To describe laboratory findings in a
group of Italian patients with
COVID-19 in the Valcamonica area and
correlate the abnormalities with the
severity of the disease.
518
Emergency Department of the
Valcamonica Hospital (Esine,
Brescia, Lombardia, Italy).
Iaccarino et al. (2020) Hypertension
To check if renin and angiotensin, the
system inhibitors, are related to serious
outcomes of COVID-19 infection.
1591 Multicenter study.
The meta-analysis was conducted using Stata software, version 16.0. Initially, the mor-
tality rate was estimated using the number of deaths as the numerator and the total number
of analyzed samples as the denominator, multiplied by the constant 100%. A grouped
meta-analysis of the mortality rate was performed using random effects models [
13
]. The
heterogeneity of the studies was assessed using the I-square (I2) statistic [14].
Next, the factors associated with mortality were analyzed, with the outcome being
death. Thus, two groups were compared (non-survivors versus survivors). The following
quantitative variables were considered as predictors: age and the Charlson Index. For
studies that presented data such as the median and interquartile range (IIQ) [
15
], these were
transformed into the mean and standard deviation (SD) [
16
]. The following qualitative
variables were considered predictors: male gender, chronic diseases, cancer, diabetes, car-
diovascular diseases, chronic obstructive pulmonary disease (COPD), immunodeficiency,
chronic kidney disease (CKD), metabolic disease, obesity, hypertension, familial hyper-
cholesterolemia (FH), dementia and smoking. Variables related to the use of drugs and
therapies were excluded from the risk factor analyses since this review does not address
clinical trials.
The effect size was reported as the standardized mean difference (SDM) for quanti-
tative variables or the relative risk (RR) for qualitative variables. All of these measures
were followed up with a 95% confidence interval [
17
]. The heterogeneity between studies
was assessed using the I-square (I
2
) statistic [
14
]. Fixed or random effects models were
used depending on the heterogeneity. Variables with a p-value < 0.05 were considered
statistically significant.
The protocol for this article was published in the International Prospective Register of
Systematic Reviews, PROSPERO, in August 2020, under the register: CRD42020201790.
3. Results
The number of elderly people included in each study varied between 18 [
18
] and
1591 [
19
] patients. The objectives of the publications were similar, i.e., conducting a
descriptive analysis of the elderly and the factors associated with coronavirus.
The main morbidities presented by the elderly in the studies were: dementia [
20
],
diabetes [
19
,
21
], chronic kidney disease [
19
] and hypertension [
21
], showing that NCCDs
had a key role to play in these cases.

Int. J. Environ. Res. Public Health 2021,18, 8008 5 of 9
Figure 2shows the meta-analysis of the mortality rate found. A mortality rate of 27.7%
was observed (95% CI, 15.7–41.57%), with high heterogeneity between studies (I
2
, 97.71%;
p< 0.001).
Int. J. Environ. Res. Public Health 2021, 18, x 5 of 10
The meta-analysis was conducted using Stata software, version 16.0. Initially, the
mortality rate was estimated using the number of deaths as the numerator and the total
number of analyzed samples as the denominator, multiplied by the constant 100%. A
grouped meta-analysis of the mortality rate was performed using random effects models
[13]. The heterogeneity of the studies was assessed using the I-square (I2) statistic [14].
Next, the factors associated with mortality were analyzed, with the outcome being
death. Thus, two groups were compared (non-survivors versus survivors). The following
quantitative variables were considered as predictors: age and the Charlson Index. For
studies that presented data such as the median and interquartile range (IIQ) [15], these
were transformed into the mean and standard deviation (SD) [16]. The following qualita-
tive variables were considered predictors: male gender, chronic diseases, cancer, diabetes,
cardiovascular diseases, chronic obstructive pulmonary disease (COPD), immunodefi-
ciency, chronic kidney disease (CKD), metabolic disease, obesity, hypertension, familial
hypercholesterolemia (FH), dementia and smoking. Variables related to the use of drugs
and therapies were excluded from the risk factor analyses since this review does not ad-
dress clinical trials.
The effect size was reported as the standardized mean difference (SDM) for quanti-
tative variables or the relative risk (RR) for qualitative variables. All of these measures
were followed up with a 95% confidence interval [17]. The heterogeneity between studies
was assessed using the I-square (I2) statistic [14]. Fixed or random effects models were
used depending on the heterogeneity. Variables with a p-value < 0.05 were considered
statistically significant.
The protocol for this article was published in the International Prospective Register
of Systematic Reviews, PROSPERO, in August 2020, under the register: CRD42020201790.
3. Results
The number of elderly people included in each study varied between 18 [18] and 1591
[19] patients. The objectives of the publications were similar, i.e., conducting a descriptive
analysis of the elderly and the factors associated with coronavirus.
The main morbidities presented by the elderly in the studies were: dementia [20],
diabetes [19,21], chronic kidney disease [19] and hypertension [21], showing that NCCDs
had a key role to play in these cases.
Figure 2 shows the meta-analysis of the mortality rate found. A mortality rate of
27.7% was observed (95% CI, 15.7–41.57%), with high heterogeneity between studies (I2,
97.71%; p < 0.001).
Figure 2. Mortality rate in the elderly obtained in the meta-analysis.
The meta-analysis was conducted for each predictor variable, stratified into quantita-
tive and qualitative variables.
Table 2shows the descriptive analysis of the quantitative variables according to the
survivors and non-survivors, and Table 3shows the effect size, in SDM and 95% CI, of the
variables affecting mortality.
Table 2.
Descriptive analysis of quantitative variables, according to groups of survivors and non-
survivors.
Variables
Non-Survivors Survivors
N Mean SD N Mean SD
Age (years)
Iacarinno et al. (2020) 188 79.6 0.8 1304 64.7 0.4
Stroppa et al. (2020) 9 74.44 7.21 16 68.38 10.16
Bonetti et al. (2020) 70 75.4 14.99 74 62.63 14.97
Charlson Index
Iacarinno et al. (2020) 188 4.37 0.14 1403 2.63 0.05
N, sample size in each group; SD, standard deviation.
Table 3. Meta-analysis of factors (quantitative variables) associated with mortality.
Variables SMD (95% CI) I2Zp-Value
Age (years) 3.10 (2.79; 3.40) 99.9% 19.76 <0.001
Charlson Index 1.74 (1.56; 1.92) - 19.33 <0.001
SMD, standardized mean difference; Z, Z statistic of the meta-analysis; I
2
, I-square; 95% CI, 95% confidence interval.
The Analysis of quantitative variables showed that mortality increased with increasing
age (SMD, 3.10; 95% CI, 2.79; 3.40) and Charlson Index scores (SMD, 1.74; 95% CI, 1.56;
1.92) (Table 2).

Int. J. Environ. Res. Public Health 2021,18, 8008 6 of 9
Table 4shows the descriptive analysis of qualitative variables according to the sur-
vivors and non-survivors, and Table 5shows the effect size, in RR and 95% CI, of the
variables affecting mortality.
Table 4.
Descriptive analysis of qualitative variables according to groups of survivors and non-survivors.
Variables
Non-Survivors Survivors
N n % N N %
Male
Bonetti et al. (2020) 70 45 64.3 74 51 68.9
Iacarinno et al. (2020) 188 125 66.5 1403 891 63.5
Stroppa et al. (2020) 9 5 55.6 16 15 94.8
Deiana et al. (2020) 81 40 50.6 336 89 26.6
Chronic diseases
Bonetti et al. (2020) 70 49 70.0 74 43 57.3
Cancer
Bonetti et al. (2020) 70 9 12.9 74 6 8.0
Diabetes
Bonetti et al. (2020) 70 21 30.0 74 16 21.3
Iacarinno et al. (2020) 188 61 32.4 1403 208 14.8
Stroppa et al. (2020) 9 2 22.2 16 6 37.5
Cardiovascular diseases/coronary artery disease
Bonetti et al. (2020) 70 38 54.3 74 33 44.0
Iacarinno et al. (2020) 188 56 29.8 1403 160 11.4
COPD 1
Bonetti et al. (2020) 70 14 20.5 74 6 8.0
Iacarinno et al. (2020) 188 28 14.9 1403 94 6.7
Stroppa et al. (2020) 9 3 33.3 16 4 25.0
Immunodeficiencies
Bonetti et al. (2020) 70 2 2.8 74 0 0.0
Chronic kidney disease
Bonetti et al. (2020) 70 9 12.9 74 3 4.0
Icarinno et al. (2020) 188 31 16.5 1403 56 4.0
Metabolic disease
Bonetti et al. (2020) 70 10 14.3 74 7 9.3
Obesity
Bonetti et al. (2020) 70 12 17.1 74 5 6.8
Iacarinno et al. (2020) 188 12 6.4 1403 90 6.4
Hypertension
Iacarinno et al. (2020) 188 138 72.9 1403 737 52.5
Stroppa et al. (2020) 9 5 55.6 16 11 68.8
FH 2
Iacarinno et al. (2020) 188 57 30.3 1403 130 9.3
Dementia
Bianchetti et al. (2020) 194 51 26.3 433 31 7.2
Smoking
Stroppa et al. (2020) 9 4 44.4 16 9 56.3
1
Chronic obstructive pulmonary disease (COPD).
2
Familial hypercholesterolemia (FH). N, sample size in each
group; n, absolute total number of elderly people; %, percentage of elderly people.
The analysis of quantitative variables showed that the risk of mortality was higher in
individuals with diabetes (RR, 1.90; 95% CI, 1.53; 2.37), COPD (RR, 2.19; 95% CI, 1.54; 3.10),
chronic kidney disease (RR, 3.96; 95% CI, 2.65; 5.91), hypertension (RR, 1.37; 95% CI, 1.24;
1.51), FH (RR, 3.27; 95% CI, 2.49; 4.29) or dementia (RR, 3.67; 95% CI, 2.43; 5.55) (Table 4).

Int. J. Environ. Res. Public Health 2021,18, 8008 7 of 9
Table 5. Meta-analysis of factors associated (quantitative variables) with mortality.
Variables RR (95% CI) I2Zp-Value
Male 0.98 (0.67; 1.43) 89.3 0.10 0.919
Chronic diseases 1.20 (0.94; 1.54) - 1.48 0.139
Cancer 1.60 (0.60; 4.23) - 0.92 0.356
Diabetes 1.90 (1.53; 2.37) 62.7 5.73 <0.001
Cardiovascular diseases/coronary artery disease 1.80 (0.85; 3.80) 92.0 1.53 0.125
COPD 12.19 (1.54; 3.10) 0.0 4.39 <0.001
Immunodeficiencies 5.28 (0.26; 108.12) - 1.08 0.280
Chronic kidney disease 3.96 (2.65; 5.91) 0.0 6.73 <0.001
Metabolic disease 1.51 (0.60;3.75) - 0.89 0.374
Obesity 1.28 (0.78; 2.10) 60.8 0.99 0.322
Hypertension 1.37 (1.24; 1.51) 69.3 6.25 <0.001
FH 23.27 (2.49; 4.29) - 8.55 <0.001
Dementia 3.67 (2.43; 5.55) - 6.17 <0.001
Smoking 0.74 (0.32;1.71) - 0.70 0.483
1
Chronic obstructive pulmonary disease (COPD).
2
Familial hypercholesterolemia (FH). RR, relative risk; Z,
Z statistic of meta-analysis; I2, I-square; 95% CI, 95% confidence interval.
4. Discussion
This study aimed to synthesize the factors associated with the mortality of elderly
Italians diagnosed with coronavirus who were institutionalized or hospitalized. The data
show that diabetes, chronic obstructive pulmonary disease, hypertension and dementia
were morbidities that considerably increased the risk of death in the elderly. This asso-
ciation is presumed to be related to the high prevalence of these diseases in the elderly
population [22].
The Instituto Nazionale di Statistica (ISTAT) of Italy, in its 4 May 2020 report, states
that the impact of COVID-19 is greater in people with extremely compromised health
conditions, causing the mortality of these people to occur in a shorter time. The document
also reports that, in some cases, COVID-19 may not be the leading cause of death, but a
contributing factor to overall mortality [
7
]. There are a series of phenomena and dynamics
that affect the current state of health of Italians, such as the aging of the population, the
increase in risk factors (including NCCDs), “the phenomenon of vaccination hesitation, the
threat of antimicrobial resistance, the difficulties of access to innovation, the shortage of
doctors, the lack of regional homogeneity and the delay in digitizing the health system that
affect the system as a whole” [23].
Italy has the lowest prevalence rate, by age, for chronic obstructive pulmonary disease
and cardiovascular diseases [
23
]. This may be fortunate as these were the diseases that
increased mortality among the elderly in the articles analyzed. This link is supported by a
review that described the association between cardiovascular diseases and an increased
risk of complications from COVID-19 [24].
On the other hand, the country has the highest prevalence rate, by age, for dementia.
As aging progresses, the risk of this diagnosis increases. It is a progressive neurodegenera-
tive syndrome characterized by a cognitive decline that limits social functions and activities
of daily living [
25
]. In addition to having an important impact on the quality of life of these
people, dementia was also shown to be a risk factor for mortality in elderly people with
COVID-19.
5. Conclusions
We conclude with the belief that the objective proposed for this study had been
achieved, i.e., to synthesize the factors associated with the mortality of elderly Italians
diagnosed with coronavirus who lived in institutions or were hospitalized because of the
disease. Looking ahead, it is expected that public policies will be developed for the new
reality of humanity profoundly marked by the pandemic.
NCCDs, when associated with SARS-CoV-2, are factors in the deaths of the elderly.
Data relating to NCCDs are, therefore, fundamental for the elaboration of public policies
and health promotion practices and the prevention of chronic diseases throughout aging. In
addition, prevention strategies against coronavirus for the elderly population with NCCDs,

Int. J. Environ. Res. Public Health 2021,18, 8008 8 of 9
such as chronic obstructive pulmonary disease or dementia, must be planned with a clear
and precise target to prevent so many deaths from occurring among the elderly.
Certainly, we should not create more institutions that house elderly people without
taking into account the greater risks that life in a large community has for the coexistence
with and contagion of these diseases. It will be necessary to think creatively about new
living spaces and new ways of handling work as health professionals and operators in
these establishments.
The vaccination priorities for the institutionalized elderly, as established by all gov-
ernments, were touched by the social movement that reverberated around the world when
several army trucks transported burial coffins in the Italian city of Bergamo in March 2020.
The mortality of the elderly who lived in socio-sanitary care institutions or who were taken
into hospitals showed the true danger of NCCDs meeting SARS-CoV-2.
With vaccination slowly arriving in each country, as the pharmaceutical industry
works to deliver enough doses and countries strive to implement efficient logistics for
the distribution and application of the drug, it is hoped that all of this will pass, and that
this time of great pain and suffering for many families will facilitate our learning and the
growth of authorities and new public policies aimed at protecting the elderly.
The most important limitation of this research is the small number of articles found
in Italy, which prevented further analysis. In future studies, factors related to chronic
diseases should be considered since these aspects impact the mortality of elderly people
with COVID-19.
Author Contributions:
Conceptualization, V.P.A. and D.G.; methodology, F.G.C.; software, B.G.d.A.;
validation, M.A.d.S.L., R.S.d.O., F.T.d.S.F. and A.V.C.G.; formal analysis, D.G.; in-investigation, V.P.A.;
resources, D.G.; data curation, F.G.C.; writing—original draft preparation, B.G.d.A.; writing—review
and editing, V.P.A.; visualization, M.A.d.S.L.; supervise, D.G.; project administration, B.G.d.A.; fund-
ing acquisition, V.P.A. All authors have read and agreed to the published version of the manuscript.
Funding:
This study was funded by the Research Support Foundation of the Federal District by
postdoctoral fellowship (FAP-DF—Brazil). Process n◦00193.00002100/2018-51.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Conflicts of Interest: The authors declare no conflict of interest.
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