Multimorbidity patterns among COVID-19 deaths: Proposal for the construction of etiological models

Abstract

Objectives. To describe patterns of multimorbidity among fatal cases of COVID-19, and to propose a classification of patients based on age and multimorbidity patterns to begin the construction of etiological models.
Methods. Data of Colombian confirmed deaths of COVID-19 until June 11, 2020, were included in this analysis (n=1488 deaths). Relationships between COVID-19, combinations of health conditions and age were explored using locally weighted polynomial regressions.
Results. The most frequent health conditions were high blood pressure, respiratory disease, diabetes, cardiovascular disease, and kidney disease. Dyads more frequents were high blood pressure with diabetes, cardiovascular disease or respiratory disease. Some multimorbidity patterns increase probability of death among older individuals, whereas other patterns are not age-related, or decrease the probability of death among older people. Not all multimorbidity increases with age, as is commonly thought. Obesity, alone or with other diseases, was associated with a higher risk of severity among young people, while the risk of the high blood pressure/diabetes dyad tends to have an inverted U distribution in relation with age.
Conclusions. Classification of individuals according to multimorbidity in the medical management of COVID-19 patients is important to determine the possible etiological models and to define patient triage for hospitalization. Moreover, identification of non-infected individuals with high-risk ages and multimorbidity patterns serves to define possible interventions of selective confinement or special management.

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Rev Panam Salud Publica 44, 2020 | www.paho.org/journal | https://doi.org/10.26633/RPSP.2020.166 1
Original research
Multimorbidity patterns among COVID-19 deaths:
proposal for the construction of etiological models
Julián A. Fernández-Niño,1 John A. Guerra-Gómez,2 y Alvaro J. Idrovo3
Suggested citation Fernández-Niño JA, Guerra-Gómez JA, Idrovo AJ. Multimorbidity patterns among COVID-19 deaths: proposal for the con-
struction of etiological models. Rev Panam Salud Publica. 2020;44:e166. https://doi.org/10.26633/RPSP.2020.166
This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 IGO License, which permits use, distribution, and reproduction in any medium, provided the
original work is properly cited. No modications or commercial use of this article are permitted. In any reproduction of this article there should not be any suggestion that PAHO or this article endorse any specic organization
or products. The use of the PAHO logo is not permitted. This notice should be preserved along with the article’s original URL.
1 Universidad del Norte, Barranquilla, Colombia. * Julián A. Fernández-Niño,
aninoj@uninorte.edu.co
2 Northeastern University, Silicon Valley, United States of America
3 Universidad Industrial de Santander, Bucaramanga, Colombia
ABSTRACT Objectives. To describe patterns of multimorbidity among fatal cases of COVID-19, and to propose a classifi-
cation of patients based on age and multimorbidity patterns to begin the construction of etiological models.
Methods. Data of Colombian confirmed deaths of COVID-19 until June 11, 2020, were included in this analysis
(n=1488 deaths). Relationships between COVID-19, combinations of health conditions and age were explored
using locally weighted polynomial regressions.
Results. The most frequent health conditions were high blood pressure, respiratory disease, diabetes, car-
diovascular disease, and kidney disease. Dyads more frequents were high blood pressure with diabetes,
cardiovascular disease or respiratory disease. Some multimorbidity patterns increase probability of death
among older individuals, whereas other patterns are not age-related, or decrease the probability of death
among older people. Not all multimorbidity increases with age, as is commonly thought. Obesity, alone or with
other diseases, was associated with a higher risk of severity among young people, while the risk of the high
blood pressure/diabetes dyad tends to have an inverted U distribution in relation with age.
Conclusions. Classification of individuals according to multimorbidity in the medical management of COVID-19
patients is important to determine the possible etiological models and to define patient triage for hospitaliza-
tion. Moreover, identification of non-infected individuals with high-risk ages and multimorbidity patterns serves
to define possible interventions of selective confinement or special management.
Keywords Betacoronavirus; multimorbidity; medical care; mortality; Colombia.
Currently, the practice of medicine is complex, and it is even
more so when faced with a new infection such as COVID-19.1
Scientic knowledge provides guidelines for having an effec-
tive medicine, but when people have chronic diseases, more
than one disease (co-occurrence), and receive several medicines,
clinical practice becomes an even bigger challenge, especially
when these chronic diseases do not receive adequate care.2 In
addition, conditions such as physical disability, mostly also as a
consequence of these chronic diseases, could also increase vul-
nerability to complications from other different diseases.
Evidence shows that multimorbidity is one of the clinical
characteristics that most complicates the care of infected peo-
ple,3 which is clearly true for COVID-19 as well. Valderas et al.4
dened multimorbidity as the “presence of multiple diseases
in one individual”, where comorbidity is just one of the possi-
ble forms of multimorbidity. For these authors comorbidity is
the “presence of additional diseases in relation to an index dis-
ease in one individual”; therefore, the co-occurrence of various
pre-existing diseases with COVID-19 infection is not necessarily
comorbidity. Multimorbidity among individuals with COVID-
19 was described early among the rst reported patients in the
specialized literature,5 and it is a frequent nding in published
studies.6,7 However, the term comorbidity continues to be used
incorrectly in most published studies. A critical reading of pre-
vious studies allows us to identify that, for the most of these.
The objective of this study was to explore the effect of single
diseases on the clinical severity or the risk of fatality among
patients with diagnosis of COVID-19. This leaves out more

Original research Fernández-Niño et al. • Multimorbidity patterns among COVID-19 deaths
2 Rev Panam Salud Publica 44, 2020 | www.paho.org/journal | https://doi.org/10.26633/RPSP.2020.166
complex approaches such as those that congure vulnerability
of older adults as a construct beyond the effect of single dis-
eases or their simple sum. Therefore, it is necessary to study
multimorbidity as a multidimensional condition, which incor-
porates the joint presence and the interactions of all the health
conditions. A deeper analysis should emphasize the type of
potential relationships between health conditions, whether they
are under medical control or not, as well as other sources of
vulnerability such as disability, functional dependence on other
people, the presence of geriatric syndromes or even the social
and economic vulnerabilities, among others. Understanding
the multimorbidity associated with emerging diseases such as
COVID-19 is important to classify patients, identify possible
etiological models, and dene differential medical manage-
ment guidelines.8
In critical situations such as the COVID-19 pandemic, a good
classication of infected people is important to improve their
care. For those who can seek hospital care, this can be done in
the initial triage, and for those who are cared for at home, it will
serve to identify the risk of infection severity. In addition, recog-
nizing the multimorbidity as a multidimensional and complex
condition will allow the development of more complex risk
classications, to identify subjects who need greater vigilance
at the community and hospital level, or to formulate “telework”
recommendations in certain occupations.
The wide variety of multimorbidity patterns includes the
most frequent co-occurrences that were evident since the
beginning of the pandemic, and the co-occurrences with less
frequency that appear every time there are more cases, and per-
haps it will include orphan diseases,9,10 and those of endemic
foci.11 In these circumstances, low prevalence signies more
clinical complexity. In this study, we used Colombian data to
describe patterns or multimorbidity among individuals diag-
nosed with COVID-19.
MATERIAL AND METHODS
Ofcial nominal data of conrmed cases of COVID-19 for
Colombia, with a cutoff date of June 11, 2020 throughout the
country were included in this study. This data had a good per-
formance according to an analysis based on Bedford’s law.12
Data used in this study correspond to the ofcial report that
is constructed daily with the cases that have been conrmed
by the National Institute of Health, based on laboratory tests
(reex nasal swab reverse transcription PCR). Although it has
a lag of a few days, it is the most reliable source of data on
the SARS-CoV-2 pandemic in Colombia. The other available
sources have greater lags and may incorporate suspected cases
that did not have conrmatory laboratory tests.
By that date, 17 790 cases and 1 488 deaths by COVID-19 were
reported. This database has information on each case, speci-
cally: municipality and department of occurrence, date of onset
of symptoms, date of diagnosis, date of report, sex, and age.
For each dead individual, the presence or absence of a prede-
termined list of comorbidities is reported in the database: high
blood pressure (HBP), diabetes mellitus, respiratory disease,
cardiovascular disease, chronic kidney disease (CKD), cerebro-
vascular disease, smoking, cancer, thyroid disease, autoimmune
disease, and HIV. This list includes nine of the top 10 chronic
diseases identied in a systematic review of measurements of
multimorbidity.13 Although smoking is not a chronic disease, it
is a chronic health condition that has direct functional effects,
beyond being a risk factor for other diseases, reason why it is
incorporated as part of a broad denition of multimorbidity in
this analysis.
Individuals reported as hospitalized or in the Intensive Care
Unit (ICU) were not included because they were in an inter-
mediate stage of their medical treatment and the denitive
outcome was unknown (recovery or death). Information about
chronic disease among mild and moderate cases of COVID-19
is not available by the time of this analysis. The database can be
requested from the Colombian Ministry of Health and Health
Protection.
Statistical methods. First, the description of the prevalence of
each disease among fatal cases was made individually, without
considering the co-occurrence of other health conditions. These
patterns were compared between age groups using x2 test. Sub-
sequently, all possible disease dyads and triads were identied,
characterizing multimorbidity. With this procedure the 10 most
prevalent (>2%) multimorbidity patterns were recognized.
TABLE 1. Prevalence of health conditions¥ among fatal cases of
COVID-19 in Colombia
Under 60 years 60 years and more
Only one condition
co-occurrence Prevalence
(%) 95% CI Prevalence
(%) 95% CI
HBP 26.80 20.84 33.45 39.76 33.07 46.74
Respiratory disease 7.20 4.56 10.70 19.46 14.82 24.82
Diabetes 18.36 14.72 22.48 18.81 15.55 22.44
Cardiovascular disease 7.94 5.98 10.30 16.77 13.75 20.17
Kidney disease 5.71 4.58 7.57 11.86 10.20 13.69
Obesity 18.61 14.14 23.78 5.19 4.13 6.43
Smoking 3.97 1.87 7.31 5.19 3.61 7.20
Stroke 0.74 0.09 2.65 4.63 3.62 5.93
Thyroid disease 1.99 0.76 4.19 4.54 2.33 7.89
Cancer 2.48 1.07 4.87 3.89 2.38 5.97
Autoimmune disease 3.97 1.38 8.73 1.11 0.39 2.38
HIV 2.48 0.70 6.75 0.36 0.10 0.91
Two or more conditions
co-occurrence
HBP + Diabetes 9.68 7.09 12.82 11.03 8.66 13.78
HBP + Cardiovascular
disease 3.23 1.69 5.53 8.71 6.19 11.87
HBP + Respiratory
disease 2.25 1.20 3.77 7.60 5.67 9.94
HBP + Chronic Kidney
Disease 1.99 1.16 3.17 5.75 4.42 7.32
Cardiovascular disease
+ Respiratory disease 1.24 0.45 2.71 3.99 2.69 5.67
Diabetes +
Cardiovascular
disease
2.48 1.31 4.23 3.71 2.71 4.93
HBP + Obesity 5.21 3.18 7.99 2.87 2.16 3.74
Diabetes +
Cardiovascular
disease + HBP
1.49 0.54 3.25 2.50 1.76 3.45
Smoking + Respiratory
disease 0.74 0.16 2.15 2.22 1.48 3.21
Diabetes + Obesity 4.96 3.46 6.86 1.67 0.88 2.87
¥ Only dyads and triads with higher prevalences.
HBP, high blood pressure.

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For the estimation of prevalences, it was assumed that the
individuals observed were a random sample of cases from
the total population of COVID-19 cases that will be observed
in Colombia at the end of the pandemic, which is reasonable
given that the country has several weeks with sustained local
transmission. Given this assumption, and that the prevalences
are exceptionally low, exact 95% Clopper-Pearson condence
intervals were estimated.14 Cluster at the department level were
considered to consider the spatial correlation of observations.
A locally weighted polynomial regression was tted between
each morbidity and age (continuous) to identify patterns of
association. This regression was chosen because it uses a non-
parametric method, where the assumptions of conventional
regressions can be relaxed.15 This bivariate exploration included
as dependent variable the presence or not of multimorbidity,
for each type of pattern, age as the exposure variable, and sex
as confounder. Finally, we proposed three simple qualitative
models of multimorbidity for COVID-19 using congurations
described by Valderas et al.4 The analyses were performed with
the statistical software Stata 16 (Stata Corporation, USA).
Ethical considerations. This study was carried out during a
sanitary crisis. Data was collected by territorial health secretaries
and organized by the Colombian National Institute of Health,
and it was freely available to the public in its webpage. There
was no access to personal data or variables that allowed the
identication or localization of the participants. This study was
considered as an response to the World Health Organization´s
call of “… to learn as much as possible as quickly as possible,
in order to inform the ongoing public health response, and
to allow for proper scientic evaluation of new interventions
being tested”.16 Obtained results were informed to the Colom-
bian Ministry of Health to support health policies during the
pandemic.
RESULTS
In this study, 1 488 deaths were analyzed and 61% of them
occurred in men. The mean of age of the fatal outcomes was
67.59 years (median: 69 years; percentiles: p10= 46, p25= 58, p75=
79, p90= 86 years) and only 27.19% of the deaths occurred among
people under 60 years. Table 1 shows the main health condi-
tions accompanying COVID-19 infection, with their respective
prevalences and 95% condence intervals, according to the
age groups (under 60, and 60 years and more). Prevalences of
FIGURE 1. Prevalence of the 10 main dyads and triads identified among fatal cases of COVID-19 in Colombia, by age group
HBP, high blood pressure.

Original research Fernández-Niño et al. • Multimorbidity patterns among COVID-19 deaths
4 Rev Panam Salud Publica 44, 2020 | www.paho.org/journal | https://doi.org/10.26633/RPSP.2020.166
FIGURE 2. Locally weighted polynomial regressions between COVID-19, health condition and age, among fatal cases in Colombia*
* Only includes health conditions separately.
HBP, high blood pressure.
respiratory, cardiovascular or kidney diseases, stroke, HBP +
cardiovascular disease, HBP + respiratory disease, HBP +
chronic kidney disease were higher among individuals with
60 or more years. Obesity was more frequent among under
60 years old. Figure 1 shows that multimorbidity prevalence
increases markedly among those over 80 years.
Figure 2 shows the probability of each morbidity according
to age, considered separately. In general, there is a tendency
to increase the probability of each morbidity with increasing
age, and only high blood pressure, cardiovascular disease, and
kidney chronic disease tend to be linear. In contrast, obesity
decreases the probability of occurrence with increasing age,
whereas smoking, thyroid disease, cancer, autoimmune disease,
and HIV have not a clear trend towards increase or decrease.
In short, among the fatal cases of COVID-19, the occurrence of
multimorbidities is positively associated with age, as is known.
One of the exceptions is obesity, which is more frequent in fatal
young cases. This is also shown by the fact that obesity has a
higher occurrence in fatal cases in young people.
Figure 3 shows the probability of each pattern of multi-
morbidity according to the 12 top complex health conditions
(COVID-19 + two or more health conditions) according to age. In
these cases, the relationships are heterogeneous and non-linear-
ity is common. The COVID-19 + high blood pressure + diabetes
pattern has an inverted U distribution and it is very important
due to its relative high prevalence. It contrasts with the linear
relationship of COVID-19 + high blood pressure + respiratory
disease. In summary, not all multimorbidity increases with age,
as is commonly thought.
DISCUSSION
Findings of this study indicate that multimorbidity is an
important phenomenon to consider in the context of the COVID-
19 pandemic. The co-occurrences of COVID-19 with different
combinations of diseases including high blood pressure, diabe-
tes mellitus, obesity, cardiovascular, respiratory, and CKD have
a high frequency among individuals deceased by COVID-19 in
Colombia and other countries. Identication of these multimor-
bidity patterns among individuals diagnosed with SARS-CoV-2
infection could provide insights for patient triage for hospital-
ization, and basic care at home according to the estimated risk.

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Moreover, identication of non-infected individuals with high-
risk ages and specic multimorbidity patterns could serve to
dene possible interventions of selective connement or special
management.
The top six morbidities identied have a strong relationship
with age (HBP, respiratory disease, diabetes, cardiovascular
disease, CKD, and obesity). Most of these six associations were
positive but not linear, except obesity and diabetes where the
association decreases with age after a turning point. Given
that these results are conditional on death, these relationships
could mainly be explained by survivor bias, since diabetes and
obesity are not only more prevalent in young adults, but also,
in turn, this is the effect of higher mortality before 60 years of
age. However, the importance of this nding is that it precisely
identies that diseases such as obesity and diabetes are more
relevant in adults younger than 60 years as potential factors
associated with COVID-19 fatality. Other diseases such as thy-
roid disease, HIV, autoimmune disease, stroke, and cancer seem
to be important, although not age-related. These diseases seem
FIGURE 3. Locally weighted polynomial regressions between COVID-19, complex patterns of health conditions and age, among
fatal cases in Colombia*
* Includes patterns of two or more health conditions.
HBP, high blood pressure.
to be important regardless of age as factors associated with fatal
outcomes of COVID-19 infection.
With the multimorbidity classication by Valderas et al4 it
is possible to identify that among individuals diagnosed with
COVID-19 there are different types of multimorbidity. We
propose that there are least three possible models between
COVID-19 and chronic diseases (gure 4). In the rst model,
chronic disease is an effect modier of SARS-CoV-2 infection,
increasing the risk of complications and severity. The second
model incorporates the existence of common causes associated
with the chronic disease and related clinical or social factors.
Finally, in model 3 there is only a temporary concurrence of the
chronic disease and COVID-19 infection, but there is neither
relationship among them, nor they have common causes. To
determine which congurations are more frequent and which
ones apply to each chronic disease, cohort studies that consider
the nature of these relationships are required.
In response to this situation with different etiological models,
it is possible to improve the proposed guidelines for managing

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6 Rev Panam Salud Publica 44, 2020 | www.paho.org/journal | https://doi.org/10.26633/RPSP.2020.166
chronic diseases when they co-occur with COVID-19. For
instance, guidelines for COVID-19 individuals with high blood
pressure,17 diabetes,18,19 cardiovascular disease,20 kidney dis-
ease,21 metabolic and bariatric surgery,22 endocrine surgery,23
lung cancer,24 stroke,25 and systemic sclerosis.26 There are also
recommendations for older adults with multimorbidity and
polypharmacy.27,28 These types of practices and discussions
associated with the proposed changes to manage patients
are evidence of the complexity of COVID and the associated
FIGURE 4. Proposed models between chronic disease and COVID-19 infection observed among Colombian patients*
* Simple theoretical models; in the clinical practice there are many variables involved.
multimorbidity. However, the more difcult cases will be
individuals with COVID-19 and complex diseases with low
prevalence.
Multimorbidity should be understood as a vulnerability
condition itself, and more than the additive sum of chronic
diseases. Multimorbidity is like a concentration of expressions
in a unique health-disease process, which means that it’s the
joint result of the risk factors and pathophysiological changes
associated with each of the health conditions involved. Among

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older adults, this medical complexity congures the frailty
syndrome,29 that affects physiological reserves and multiple
systems, making older adults more susceptible to complica-
tions and death from COVID-19, like from other diseases. This
could explain the well-recognized relationship between age
and severity in COVID-19, which is undoubtedly measured by
multimorbidity.
For this reason, in this study multimorbidity was included
as an underlying latent variable in our analysis. Similar expe-
riences were found with the Patient-Centered Clinical Method
(PCCM) questionnaire in Canada, where the complexity of mul-
timorbidity and associated factors can be comparable.30 There
are even other analyses comparing ways of approaching mul-
timorbidity, which suggests that hierarchical cluster analysis
shows comorbidity, while exploratory factor analysis multi-
morbidity.31 Subsequent analyses can use this approach to build
scales of risk of death and complications. In addition, diseases
that co-occur in time and place congure the existence of a syn-
demic. For Singer and Clair, a syndemic occurs because there
are social characteristics that are acting as determinants, so ade-
quate management requires a more comprehensive approach.32
In this case, COVID-19 co-occurs with different multimorbidity
patterns, which is specic to a complex emergent disease.
Results presented here should be interpreted taking into
account some methodological limitations. First, in this study
other conditions that have been used in multimorbidity
indices were not available: (osteo)arthritis, hearth failure,
depression, osteoporosis, peripheral arterial occlusive dis-
ease, vision problems, dementia, hearing problems and angina
pectoris13. Colombian ofcial database only includes the 10
conditions reported in this study. However, with the exception
of heart failure and angina, all other conditions have higher
prevalences among older adults. For this reason, they would
not be directly associated with the risk of becoming infected
or dying from COVID-19. Heart failure and angina would be
covered by the label “cardiovascular disease”, so we consider
that the most relevant morbidities associated with COVID-19
severity were considered. Another limitation is related to the
non-inclusion of socioeconomic health conditions, disability
and functional dependence, geriatric syndromes, and mental
health problems (mainly depression and dementia). Although
their relationship with the probability of death is more direct,
if they are theoretically part of multimorbidity from a broader
perspective8, and could indirectly affect the clinical outcome
of the disease, by affecting access to health services, adherence
to treatment or its effectiveness, as well as the biological inter-
action of the underlying conditions. Although the analyses
presented here are limited to the patterns of multimorbidity
with the highest occurrence, it is important to note that this
situation can occur with diseases of lesser occurrence (includ-
ing neglected diseases) which could be important in some
regions. In this case, the medical care becomes a big challenge
for clinicians.
In conclusion, in this study the patterns of multimorbidity
among people diagnosed with COVID-19 in Colombia during
the acute period of infection were presented. Undoubtedly, in
the future, more multimorbidity patterns will be known. Sim-
ilar analyses in different regions that incorporate the different
epidemiological patterns33 may facilitate the care of people with
COVID-19, and the prevention of transmission among high-
risk populations.
Author contributions. JAFN designed the study and the sta-
tistical analysis; AJI wrote the rst draft of the manuscript. All
authors discussed the results and reviewed and approved the
nal version.
Funding. None declared.
Conflicts of interest. None declared.
Disclaimer. Authors hold sole responsibility for the views
expressed in the manuscript, which may not necessarily reect
the opinion or policy of the RPSP/PAJPH and/or PAHO.
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Patrones de multimorbilidad entre los casos fatales de COVID-19: propuesta
para la construcción de modelos etiológicos
RESUMEN Objetivos. Describir los patrones de multimorbilidad entre los casos fatales de COVID-19, y proponer una
clasificación de los pacientes basada en la edad y los patrones de multimorbilidad para iniciar la construcción
de modelos etiológicos.
Métodos. Se incluyeron los datos de las muertes confirmadas por COVID-19 en Colombia hasta el 11 de junio
de 2020 (n=1 488 muertes). Se exploraron las relaciones entre la COVID-19, las combinaciones de enferme-
dades y la edad utilizando regresiones polinómicas con ponderación local.
Resultados. Las enfermedades más frecuentes fueron la hipertensión arterial, las enfermedades respirato-
rias, la diabetes, las enfermedades cardiovasculares y las enfermedades renales. Las díadas más frecuentes
fueron la hipertensión arterial combinada con diabetes, enfermedades cardiovasculares o enfermedades
respiratorias. Algunos patrones de multimorbilidad aumentan la probabilidad de morir en las personas may-
ores, mientras que otros no están relacionados con la edad o disminuyen la probabilidad de morir en las
personas mayores. A diferencia de lo que con frecuencia se considera, no toda la multimorbilidad aumenta
con la edad. La obesidad, aislada o combinada con otras enfermedades, se asocia con un mayor riesgo de
enfermedad grave en los jóvenes, mientras que el riesgo de la díada hipertensión arterial/diabetes tiende a
tener una distribución en U invertida en relación con la edad.
Conclusiones. La clasificación de los individuos según la multimorbilidad en el manejo médico de los paci-
entes con COVID-19 es importante para determinar los posibles modelos etiológicos y definir el triaje de los
pacientes para su hospitalización. Además, la identificación de los individuos no infectados con edades y
patrones de multimorbilidad de alto riesgo sirve para definir posibles intervenciones de confinamiento selec-
tivo o manejo especial.
Palabras clave Betacoronavirus; multimorbilidad; atención médica; mortalidad; Colombia.