The social isolation enforced by the COVID-19 pandemic reduces the Health-Related Quality of Life score in the adult population of Metropolitan Lima, Peru

Valeria C. Morales-Ancajima; Cinthya Vasquez-Velasquez; Melany De la Cruz; Maria Marull; Vilma Tapia; Gustavo F. Gonzales

doi:10.12688/f1000research.109836.1

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Research Article

The social isolation enforced by the COVID-19 pandemic reduces the Health-Related Quality of Life score in the adult population of Metropolitan Lima, Peru

[version 1; peer review: 2 not approved]

Valeria C. Morales-Ancajima¹, Cinthya Vasquez-Velasquez ^1,2, Melany De la Cruz¹, Maria Marull³, Vilma Tapia¹, Gustavo F. Gonzales¹

Valeria C. Morales-Ancajima¹, Cinthya Vasquez-Velasquez ^1,2, [...] Melany De la Cruz¹, Maria Marull³, Vilma Tapia¹, Gustavo F. Gonzales¹

PUBLISHED 12 Apr 2022

Author details Author details

¹ Department of Biological and Physiological Sciences, Cayetano Heredia University, Lima, Lima, Lima 36, Peru
² Research Unit. Directorate of Public Health Laboratory, Dirección Regional de Salud, Callao, Callao, Callao, Callao 70000, Peru
³ Nutrition Department, Cayetano Heredia University, Lima, Lima, Lima 36, Peru

Valeria C. Morales-Ancajima
Roles: Conceptualization, Investigation

Cinthya Vasquez-Velasquez
Roles: Conceptualization, Investigation

Melany De la Cruz
Roles: Conceptualization, Investigation

Maria Marull
Roles: Investigation

Vilma Tapia
Roles: Data Curation, Formal Analysis

Gustavo F. Gonzales
Roles: Conceptualization, Investigation, Methodology

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Emerging Diseases and Outbreaks gateway.

This article is included in the Coronavirus collection.

Abstract

Background: The objective of this study was to determine the association between health-related quality of life (HRQoL) in adults in Metropolitan Lima, Peru, with experienced social isolation during the coronavirus disease 2019 (COVID-19) pandemic regardless of if the person was infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) adjusted by age, sex and body mass index (BMI).
Methods: This cross-sectional study evaluated 256 men and 382 women living in Metropolitan Lima, who were administered the Health-Related Quality of Life (HRQoL) questionnaire (SF-20) virtually to assess their health-related quality of life.
Results: Obesity (beta coefficient, 95%CI [95% confidence interval]: -262 – -116), female sex (beta coefficient, 95%CI: -151 – -59), the longest time of mandatory social confinement (beta coefficient, 95%CI: -6.8 – -0.2), and the existence of chronic disease (beta coefficient, 95%CI: -147 – -44) were associated with a low total score of the HRQoL questionnaire.
Conclusions: Mandatory social confinement may have harmed the perception of health-related quality of life.

Keywords

COVID-19, Social isolation, Health-related quality of life

Corresponding author: Cinthya Vasquez-Velasquez

Competing interests: No competing interests were disclosed.

Grant information: Research reported in this publication was supported by the NIH Fogarty International Center, National Institutes of Environmental Health Science (NIEHS), R01ES018845, R01ES018845-S1, National Cancer Institute, National Institute for Occupational Safety and Health, and the NIH under Award Number U01 TW0101 07.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2022 Morales-Ancajima VC et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Morales-Ancajima VC, Vasquez-Velasquez C, De la Cruz M et al. The social isolation enforced by the COVID-19 pandemic reduces the Health-Related Quality of Life score in the adult population of Metropolitan Lima, Peru [version 1; peer review: 2 not approved]. F1000Research 2022, 11:415 (https://doi.org/10.12688/f1000research.109836.1) First published: 12 Apr 2022, 11:415 (https://doi.org/10.12688/f1000research.109836.1) Latest published: 30 Jan 2023, 11:415 (https://doi.org/10.12688/f1000research.109836.2)

Introduction

Coronavirus disease 2019 (COVID-19) is an infectious pathology caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). On 12 December 2019, the first case was detected in Wuhan, China,¹ and the disease spread so rapidly globally that on 11 March 2020, the World Health Organization (WHO) declared it a pandemic.² This pandemic has changed the lives of millions of people and has resulted in, as of 28 February 2022, 5,950,433 deaths around the world.³

Governments applied various public policies to reduce its spread, one of them being social isolation. This measure was applied in several countries around the world, Peru being one of them and probably the longest lasting.⁴

Trials to test the efficacy of the vaccine were reported at the end of 2020, and vaccination officially began around that time in several countries.⁵ Vaccination in Peru began on 9 February 2021 and continues in various age groups around the country.⁶ Currently, 72% of the target population is immunized with two doses of the vaccine. As of 24 December 2021, 73.94% of Lima's population has received two doses of the vaccine.

The conditions of social confinement have had an impact on people's health, including a decrease in physical activity levels and an increase in sedentary behavior.⁷ According to a study in Chile, the increase in physical inactivity in the population could have important metabolic implications for the health of the population.⁸

On the other hand, the emergence of pandemic-related psychological reactions; cases in people without a pre-existing mental health problem have increased and pre-existing cases were accentuated by confinement.⁹ A study in China reported moderate to severe levels of stress in the population. The most emotionally affected age group according to this study was young people aged 18-30 years.¹⁰

The human response to a pandemic is not uniform and may vary by country and region within a country. Likewise, given that lethality differs by gender and age, it is possible that coping may also differ. Subjects with co-morbidities, males and older people have had higher case fatality rates.¹¹^,¹² Peru is one of the countries with the highest case fatality and currently has COVID-19 mortality of 202, 424 people.¹³

In Lima, a study by the Consortium of Universities revealed that the mental health of students has deteriorated due to the situation of confinement. Academic factors had a greater impact on mental health, which may lead to a decrease in their performance. Higher levels of anxiety, depression, and stress symptoms were also found. Other factors such as fear of contagion, hours of sleep, and demographic conditions were also assessed as influencing mental health; however, they did not present statistical results that allow further analysis.¹⁴

It is therefore important to have instruments that allow us to assess health-related quality of life (HRQoL) in pandemic circumstances. For this purpose, there are several HRQoL questionnaires,¹⁵ which have been successfully applied in different parts of the world in situations other than the COVID-19 pandemic, and which can be applied to the general population or certain pathologies. They can be used to monitor both diseases¹⁶ and interventions.¹⁷ It would therefore be of utmost importance to use an instrument that assesses HRQOL and to be able to compare it in subjects who have suffered from COVID-19 with those who have not.

The best known and most validated HRQoL questionnaire for the Spanish-speaking population is the “short form-36” (SF-36). The SF-36, which contains 36 questions, assesses the personal perception of each individual's health in three components: physical, mental and general health component. Its application has been optimal in different age groups.¹⁸ This instrument, developed in the United States, has subsequently been translated and applied in Spain.¹⁹

In Peru, a variant of this HRQoL questionnaire called SF-20, containing 20 questions, has been validated for both sea level and high-altitude populations.²⁰^,²¹ Other groups have further reduced the questionnaire and developed the SF-12.¹⁷^,²⁰

Methods

Study design

This was a cross-sectional analytical study. Participants were recruited by a convenience sample of males and females over 18 years of age and residents of Metropolitan Lima, capital of Peru for more than 1 year before the time of participation in the survey. Access to an electronic device was required. Participants who filled in the form after the established date and those who did not agree to participate in the informed consent were excluded.

This is a cross-sectional analytical study conducted during the months of October and December 2021. For data collection we worked with Google Forms, which contained the survey and informed consent form. The study was advertised on social networks and the contacts of workers from various companies were accessed with the support of the members of the study, and they were sent the link to the survey, which required access to an electronic device.

The initial sample size was calculated using a random sampling technique for a confidence level of 95% and a statistical power of 80% and was n=600 participants, however, we aimed to survey n=1000 participants. Finally, a population of 638 participants was studied, consisting of men and women aged 18 years or older who had been residents of Metropolitan Lima for more than 1 year before participation. Only 638 participants were evaluated since participants who completed the form after the established date and those who did not agree to participate in the informed consent were excluded. As well, the difficulty of the internet connection problems was a limitation to achieving the initial participant size.

Socio-demographic characteristics

The socio-demographic characteristics obtained through the survey were age, sex, level of education, place of birth, and current district of residence. Age (years completed) was analyzed as a continuous variable.

Anthropometric measures

Anthropometric measurements obtained from the survey included height (meters), weight (kg), abdominal circumference (cm), and neck circumference (cm) of each participant. Body mass index (BMI) was calculated using the formula: weight (kg) /height (m²). The calculated BMI was classified into the following categories according to the World Health Organization (WHO).¹⁸ Waist to height ratio (WHtR) and neck to height ratio (NHtR) were also calculated.

History of disease

The data obtained from the questionnaire were: having had or not had illnesses in the last 12 months other than COVID-19, hospitalizations in the last 12 months, surgeries, or medical treatments in the last 12 months before completing the survey. In addition, respondents were asked whether they currently have a chronic illness, whether they are receiving treatment for a chronic illness, and whether they are seeing a psychologist.

Data related to COVID-19

Data were obtained on the presence of illness or symptoms related to COVID-19 and the time from the occurrence until the date the survey was completed; it was also recorded whether the participant underwent compulsory social isolation as a preventive measure or quarantine as a measure to avoid new infections after contracting COVID-19.

The type of test used to diagnose COVID-19 was also recorded. 31% were diagnosed by antigen test, 46.8% by polymerase chain reaction (PCR) and 22.2% by serological test.

Information on COVID-19 hospitalization, vaccination, perceived weight gain, stress, decreased physical activity due to social isolation, and participation in clinical trials of COVID-19 vaccines was included.

Compulsory social isolation was assessed as a dichotomous variable and as a continuous variable by asking how long the respondent engaged in compulsory social isolation.

Measurement of HRQoL

The SF-20 questionnaire contains 20 questions related to 7 dimensions: general health, physical function, physical role, emotional role, bodily pain, vitality, and mental health. This survey was translated into Spanish and validated for the Spanish-speaking population,²² determining a Cronbach's alpha greater than 0.7 in all dimensions (0.71-0.94), which indicates a good correlation. In Peru, it was validated for application in populations at sea level and high altitudes.¹³^,¹⁷

The 20 questions of the questionnaire can be divided into 3 main components. The first is the physical component, which includes 8 questions corresponding to the dimensions of physical function, and bodily pain. The second is the mental component, which includes 7 questions. Finally, the third component is general health, which includes 5 questions.

Statistical analysis

The analysis was performed with the statistical package STATA version 16 (STATACorp, Texas USA, RRID:SCR_012763).

For descriptive analysis, continuous variables such as HRQoL score and its physical and mental components, anthropometric measures, and age were expressed as averages and standard deviations. Student's t-test was used to evaluate the differences between the two averages. Likewise, socio-demographic characteristics were evaluated with the Chi-square test, also by sex and COVID-19 status. Linear regression was used to determine the relationship between HRQoL with BMI and COVID-19 status. A value of p<0.05 was considered statistically significant.

Bias

The methodology of using virtual surveys limits the information to a group with the availability of electronic equipment; therefore, we tried to disseminate the survey to population groups of different ages and within the same socio-economic level.

Ethical aspects

The study was approved on 11 October 2021 by the Institutional Ethics Committee with code 206670. Each subject voluntarily accepted participation and signed an informed consent form. The data are kept confidential.

Results

Based on the inclusion criteria, data from 638 study participants (256 men, and 382 women) were analyzed.⁴⁰

The characteristics of the population are shown in Table 1. In total, 40% of participants were men and the remaining 60% were women. Of the study population 56.9% (95% CI 52-59.9%) resided in central Lima, 20.60% (17.4-23.8%) in eastern Lima, 14.1% (11.3-16.8%) in northern Lima, and 3.3% (1.9-4.7%) in western Lima.

Table 1. Description of the sex, age and anthropometric variables in the participating population of Metropolitan Lima.

Variables	Participants with COVID-19 (n=128)	Participants without COVID-19 (n=510)
Variables	mean±SD (95% CI)	mean±SD (95% CI)
Male/Female	50/78 (64.1%)	206/304 (67.7%)
Age (years)	37.9±14.04	37.3±16.92
Age (years)	(35.4 – 40.4)	(35.8 – 38.8)
Height (m)	1.65±0.09	1.64±0.09
Height (m)	(1.63 – 1.67)	(1.63 – 1.65)
Weight (kg)	69.9±14.6	69.1±14.1
Weight (kg)	(67.3 – 72.3)	(67.9 – 70.3)
BMI (kg/m²)	25.8±4.04	25.2±3.9
BMI (kg/m²)	(25.1 – 26.5)	(24.9 – 25.5)
WC	86.4±13.5 n=87	88.2±14.9 n=331
WC	(83.5 – 89.3)	(86.6 – 89.8)
NC	36.07±6.6 n=71	35.8±5.7 n=285
NC	(34.5 – 37.6)	(35.1– 36.5)
WHtR	53.9±8.6 n=86	52.1±8.6 n=331
WHtR	(52.05 – 55.7)	(51.2 – 53)
NHtR	22.04±4 n=71	21.5±3.6 n=285
NHtR	(21.1 – 23)	(21.1 – 21.9)
Total HRQoL Score, SF-20	1471.8±311.4	1473.5±261.9
Total HRQoL Score, SF-20	(1417 – 1526)	(1450 – 1496)
SF-20 physical component	1471.8±311.4	1473.5±261.9
SF-20 physical component	(1417 – 1526)	(1450 – 1496)
SF-20 Mental Component	340.2±95.1	341.2±88.3
SF-20 Mental Component	(324 – 357)	(334 – 349)

In total, 85.9% (95% CI 83.2-88.6%) of respondents performed compulsory social isolation. Quarantine, for cases where COVID-19 was detected, was performed by 96.9% (95% CI 92.1-99.1%) of those diagnosed with the disease. In the case of vaccines, 77.1% (95% CI 73.9-80.4%) of the study population had completed both doses of the vaccine.

Overall, 19.5% of male respondents studied had COVID-19 while 20.4% of women had COVID-19 (p>0.05). No significant differences were found in anthropometric measurements between the groups with or without COVID-19. The same table shows the total Health-Related Quality of Life (HRQoL) scores and the scores corresponding to the 3 components in participants who had COVID-19 and those who did not. No significant difference was found concerning the final score or any of its components in people with COVID-19 compared to people without COVID-19 (p>0.05).

Age correlated with BMI, waist circumference (WC), neck circumference (NC), HRQoL - mental component (MC) and time after vaccination (TAV); BMI with WC, NC, HRQoL - general health (GH), and time post-vaccination; WC correlated with NC, general health, and TAV (Figure 1).

Figure 1. Spearman correlation analysis between the different variables studied in the study population of Metropolitan Lima.

Spearman correlation *p<0.05, **p<0.01, BMI: body mass index, WC: Waist circumference, NC: neck circumference, HRQoL: health-related quality of life, PC: physical component, MC: mental component, GH: general health, Time of CSC: time of compulsory social confinement, TVA: time after vaccination.

The health-related quality of life (HRQoL) score correlated with the physical component (PC), mental component (MC), general health (GH) of HRQoL, and time in compulsory social confinement (CSC). The physical component (PC) of the SF-20 correlated with MC of HRQoL, GH of HRQoL, and time in compulsory social confinement (CSC); and finally, MC of HRQoL correlates with SG, time in compulsory social confinement (CSC), and TAV.

The results related to COVID-19 are presented in Table 2. Among subjects who had COVID-19 82.4% performed compulsory social isolation while in those who did not have COVID-19 86.3% performed compulsory social isolation (p>0.05). Of the subjects who had COVID-19, 96.9% (95% CI 92.1-99.1%) reported having quarantined themselves after diagnosis of the disease.

Table 2. Data related to the coronavirus disease 2019 (COVID-19) pandemic in participants from Metropolitan Lima who previously presented with COVID-19 compared to those who did not present with COVID-19.

Variables		Participants with COVID-19 (n=128)	Participants without COVID-19 (n=510)
Variables		Frequency (%), 95% CI	Frequency (%), 95% CI
COVID-19 related data
Social isolation		108/128 (82.4), 76.9 – 90.2	440/510 (86.3), 83 – 89.1
COVID-19 symptoms		112/128 (87.5), 80.5 – 92.7	81/510 (15.9)*, 12.8 – 19.3
Hospitalization for COVID-19	No	121/128 (94.5), 89.1 – 97.8*	510/510 (100)
	No ICU	4/128 (3.1), 0.9 – 7.8
	ICU	3/128 (2.3), 0.5 – 6.7
Application of the COVID-19 vaccine		125/128 (97.7), 93.3– 99.5	492/510 (96.5), 94.5 – 97.9
COVID-19 vaccine doses	No vaccination	3/128 (2.3), 0.5 – 6.7	16/510 (3.1), 1.8 – 5
	Incomplete dose	12/128 (9.4), 4.9– 15.8	63/510 (12.4), 9.6 – 15.5
	Complete dose	97/128 (75.8), 67.4 – 82.9	395/510 (77.5), 73.6 – 81
	Adicional dose	16/128 (12.5), 7.3 – 19.5	36/510 (7.1), 5 – 9.6
Feeling that you have gained weight during social isolation		75/128 (58.6), 50 – 67.2	287/510 (56.3), 51.8 – 60.6
Feels that physical activity has decreased during social isolation		88/128 (68.8), 60 – 76.7	344/510 (67.5), 63.2 – 71.5
Has had a case of anxiety or depression during social isolation		71/128 (55.4), 46.4 – 64.3	290/510 (56.9), 52.4 – 61.2
Participation in clinical trial for COVID-19 vaccine		5/128 (3.9), 1.3 – 8.8	22/510 (4.3), IC 2.7 – 6.5

* p<0.05, Chi-square test.

Of the total subjects diagnosed with COVID-19, only 87.5% (95% CI 80.5-92.7%) had disease symptomatology. Of the subjects who were not diagnosed with COVID-19, 15.9% (95%CI 12.8-19.3%) reported having COVID-19 symptoms. Of the total subjects diagnosed with COVID-19, only 87.5% (95% CI: 80.5-92.7%) had disease symptomatology. Of the subjects who were not diagnosed with COVID-19, 15.9% (95% CI: 12.8-19.3%) reported having COVID-19 symptoms. The initial symptoms of COVID-19 infection are fever, headache, cough tiredness, absence of smell and taste; if they aggravate the disease, shortness of breath manifests.²³

The difference between the two groups is highly significant (p<0.001). Of the subjects who had COVID-19 94.5% (89.1-97.8%) did not require hospitalization while 3.1% (0.9-7.8%) were hospitalized without requiring the intensive care unit (ICU), and 2.3% (0.5-6.7%) required ICU. Of the participants without COVID-19, none were hospitalized.

In total, 97.7% of subjects with COVID-19 received the COVID-19 vaccine, and in those without COVID-19 96.5% received the vaccine (p>0.05). Overall, 88.3% of subjects with COVID-19 and 84.6% of subjects without COVID-19 received the full dose of vaccine with or without a third booster dose (p>0.05).

Regarding weight gain, 58.6% of COVID-19 subjects and 56.3% of non-COVID-19 subjects felt that they had gained weight from COVID-19 (p>0.05 between groups). Similarly, 68.85% of subjects with COVID-19 and 67.5% of subjects without COVID-19 felt that they had decreased physical activity during compulsory social isolation (p>0.05 between groups). The presence of anxiety or depression during compulsory social isolation was observed in more than half of the subjects evaluated, with no difference between the groups with or without COVID-19 (p>0.05) (Table 2).

Of the population studied, 3.9% of subjects with COVID-19 and 4.3% of subjects without COVID-19 reported having participated in a clinical trial of the COVID-19 vaccine (p>0.05 between groups) (Table 2).

Table 3 presents the results of the multivariate analysis to associate the HRQoL questionnaire total score controlling for the variables BMI, sex, age in years, whether or not hospitalized for COVID-19, time in compulsory social confinement, and history of chronic disease.

Table 3. Linear regression models for the total score of the HRQoL questionnaire (SF-20) in adult subjects in Metropolitan Lima.

HRQoL - Total score		Raw model		Adjusted model
HRQoL - Total score		Coef	95% CI	Coef	95% CI
BMI (kg/m²)	Underweight	-63.8	-301 – 173	-16	-247 – 215
	Normal weight	ref	ref	ref	ref
	Overweight	8.5	-37 – 54	-29.1	-79 – 21
	Obesity	-157.3	-223 – -91	189.4	-262 – -116
Sex (0=Male, 1=Female)		-97.8	-140 – -55	104.7	-151 – -59
Age (years)		1.6	0.3 – 2.88	2.8	1.4 – 4.2
Hospitalization for COVID-19	No hospitalized	9.2	-45 – 63	0.08	-55 – 55
	Hospitalized NOT ICU	-215.8	-484 – 53	-218.1	-477 – 40
	Hospitalized in ICU	-157.2	-467 – 152	-126.6	-427 – 174
Time of compulsory social confinement (months)		-4.7	-8 – -1.3	-3.53	-6.8 – -0.2
History of chronic disease (0=No, 1=Yes)		-108	-155 – -62	-95.2	-147 – -44

In the crude model, obesity, female sex, time in compulsory social confinement, and the presence of chronic disease are associated with lower total scores on the HRQoL questionnaire. These same variables remain significantly associated in the adjusted model.

Table 4 presents the results of the multivariate analysis to associate the physical component of the HRQoL questionnaire. Obesity, female sex, older age, hospitalization in ICU, longer time in compulsory social confinement, and pre-existence of chronic disease are associated with low values for the physical component of the HRQoL questionnaire. In the adjusted model it is observed that obesity, female sex, longer time in compulsory social confinement, and the existence of chronic disease are associated with a low score on the physical component of the HRQoL questionnaire.

Table 4. Linear regression models for the physical and mental component of the HRQoL questionnaire in adult subjects in Metropolitan Lima.

		HRQoL - Physical component				HRQoL - Mental component
		Raw model		Adjusted model		Raw model		Adjusted model
		Coef	95% CI	Coef	95% CI	Coef	95% CI	Coef	95% CI
BMI (kg/m²)	Underweight	22.2	-84.9 – 129.3	36.3	-68 – 141	-56.3	-164.7 – 52.1	-28.96	-131.8 – 73.9
	Normal weight	-16.2	-36.8 – 4.38	-17.2	-40 – 5	25.9	5.07 – 46.8	-0.54	-22.8 – 21.7
	Overweight	-90.4	-120.2 – -60.5	-89.8	-122 – -57	-15.5	-45.7 – 14.6	-44.87	-77.4 – -12.3
	Obesity	-33.61	-53.1 – -14.1	-44	-65 – -23	-43.56	-62.8 – -24.3	-38.01	-58.4 – -17.6
Sex (0=Male, 1=Female)		-97.8	-1.22	-1.8 – -0.63	-0.6	-97.8	2.45	1.9 – 3.01	2.73
Age (years)		-3.3	-27.8 – 21.3	-6	-31 – 19	12.04	-12.5 – 36.5	8.73	-15.8 – 33.3
Hospitalization for COVID-19	No infection and not hospitalized	-101.5	-223.2 – 20.2	-73.1	-190 – 44	-14.13	-135.7 – 107.5	-48.03	-163 – 66.9
	No hospitalized	-143	-283.4 – -2.62	-111.3	-247 – 25	41.51	-98.8 – 181.8	34.90	-98.8 – 168.6
	Hospitalized NOT ICU	- 1.76	-3.3 – -0.24	-1.2	-2.7 – -0.3	- 2.23	-3.8 – -0.71	-1.86	-3.3 – -0.4
	Hospitalized in ICU	-64.1	-85 – -43.2	-37.4	-61 – -14	-9.12	-30.5 – 12.2	-25.89	-48.7 – -3.02
Time of compulsory social confinement (months)		-4.7	22.2	-84.9 – 129.3	36.3	-4.7	-56.3	-164.7 – 52.1	-28.96
Presence of chronic disease (0=No, 1=Yes)		-108	-155 – -62	-95.2	-147 – -44	-108	25.9	5.07 – 46.8	-0.54

Table 4 also shows the analysis for the association with the mental component of the HRQoL questionnaire. In the crude model, female sex, younger age, and time in compulsory social confinement were the variables associated with lower scores on the mental component of the HRQoL questionnaire. In the adjusted model, obesity, female sex, younger age, time in compulsory social confinement, and pre-existence of chronic disease were associated with lower scores on the metal component of the HRQoL questionnaire.

Discussion

The present study aimed to determine the perception of HRQoL in the population of Metropolitan Lima according to whether or not they had COVID-19. Health-related quality of life (HRQoL) is an indicator that helps us to measure people's self-perception of their health. This can be measured with the questionnaire validated in Peru, the SF-20,¹⁶^,²⁰ used in this study. Cronbach's alpha, which is the internal consistency reliability coefficient, shows a value of 0.71, which is considered acceptable.

The HRQoL score can also be disaggregated into its physical, mental, and general health components. These can be affected by one or all of them together by different factors.

According to the results found in the present study, in a population residing in Metropolitan Lima, the capital of the country with approximately 10 million inhabitants and considered a mega-city, the main factor associated with lower HRQoL is the time of compulsory social confinement.

This variable in the crude and adjusted models showed a statistical significance where the longer the time of confinement, the lower the total HRQoL score and the lower the score in the mental and physical components of HRQoL.

Associated with this, other factors affecting HRQoL were also observed, such as obesity, female sex, and a history of chronic illness. In itself, having or not having COVID-19 did not affect the HRQoL score. This is an important finding as it is assumed that COVID-19 can lead to health impairment.²⁴ There are likely ethnic or idiosyncratic differences in the response to COVID-19 following an illness. A recent study in Peru shows that patients with COVID-19 do not have a higher rate of postoperative complications than patients without COVID-19.²⁵ Further studies will be needed to follow patients with COVID-19 for longer-term follow-up and to have a clearer conclusion on post-COVID-19 effects.

Interestingly, the health perception of the study participants is affected more by the compulsory social confinement than by the disease itself. A recent study on psychiatric teleconsultations in Peru shows that the third leading cause of psychiatric consultation was related to compulsory social isolation (19.7%), the first two being related to control, follow-up, or worsening of mental health problems before the pandemic (41.9%) and related to the appearance or increase of intrafamily conflicts (21.4%).²⁶

In similar situations, as in the case of Middle East respiratory syndrome (MERS) in 2015 in South Korea, mandatory social confinement for two weeks showed negative effects on mental health even 4-6 months after the end of social isolation.²⁷ Likewise, a study of 1008 young adult (18-35 years old) residents of the USA reported that higher the level of isolation and lack of social interaction during the context of the COVID-19 pandemic, higher mental disturbances and poorer the performance.²⁸

Several factors influence the impact that disease outbreaks can have on the mental state of the population, such as lack of knowledge of the possible means of virus transmission, uncertainty about the future, misinformation, and quarantine. These stressful events negatively affected various behaviors, such as eating habits, sleep, physical activity, and sedentary lifestyles.²⁹ They also cause an increase in anxiety and depression.³⁰

During the pandemic, an increase in sleep disturbance and insomnia has been reported, as stress and anxiety affect the quality of sleep during the night and even alter the state of energy during the day.²⁹^,³⁰ In addition, although our study has not focused on sleep disorders associated with the pandemic, this has been reported in several studies.³¹^,³² Social confinement times have been shorter than those observed in Peru.

During social isolation, the adoption of bad habits increased, such as higher consumption of caloric and unhealthy foods; lower consumption of fresh fruit and vegetables; and a move away from the Mediterranean diet, which is considered to be healthy.²⁹

In the case of physical activity, the total blockade, the closure of sports facilities, social restriction, and the increase in hours in front of an electronic device, due to work and study, among others, has caused a decrease in physical activity, and in turn an increase in sedentary lifestyles.²⁹

Thus, although COVID-19 disease has been described as a fatal disease, it was not the main cause of the damage to the quality of life of the population, but during compulsory social confinement, health risk behaviors increased.

It can be seen from our results that compulsory social confinement was not an intervention that could have reduced SARS CoV-2 infections. Indeed, the percentage of subjects who underwent compulsory social confinement was similar in those subjects who presented COVID-19 than in those who did not. This is since compulsory social confinement was prolonged, but there was access to massive exposure, such as in the case of markets, banks (government bonds), and public transport, which allowed many people to become infected, who may have been asymptomatic and eventually carried the infection home, infecting other family members with varying degrees of severity.

In Metropolitan Lima, a greater number of food markets was associated with higher incidence and mortality of COVID-19 (p<0.01 for both); these associations persisted when cases (r=0.49; p<0.01) and deaths (r=0.58; p<0.01) were adjusted for population density.³³

In our study, obesity is a risk factor for lower HRQoL. This corroborates findings from other studies.³⁴ The results of our study show that 57% of the surveyed population perceived weight gain and 67% had a decrease in physical activity during social confinement. According to the Peruvian College of Nutritionists, during the pandemic Peruvians gained an average of 7.7 kg, the main causes being increased caloric food intake and a sedentary lifestyle.³⁵

In other pathologies, despite having the same care, women show lower HRQoL scores.³⁶ Our results show that women have lower total scores on the HRQoL questionnaire, as well as on its physical and mental components, confirming what has been observed in other pathologies.

A history of chronic illness is also associated with lower scores on the HRQoL questionnaire.³⁷^,³⁸ The same has been confirmed in our study.

Age has shown different results in our study. For the total score and the mental component, younger age is associated with lower HRQoL scores, while for the physical component older age is associated with lower HRQoL scores.

The young population in compulsory social confinement has been subjected to a high degree of stress and anxiety due to the suspension of the face-to-face university and non-university classes and the use of tele-education involving many hours of the day in front of the computer. In our study more than half of the population studied showed cases of anxiety and/or depression during the period of compulsory social confinement. This would be one of the probable conditions for lower scores on the HRQoL questionnaire.

Having been vaccinated shows a trend towards better HRQoL scores with the second and third doses of the vaccine. The non-significance may be since the number of subjects vaccinated with two or three doses is still insufficient to show statistical significance. Further studies will show whether or not this trend becomes significant.

For healthy people in mandatory social confinement, lifestyle changes, fear of contracting COVID-19 disease, young age, female sex, history of mental illness and lower coping capacity for stress appear to be risk factors for insomnia.³⁹

In Peru, the impact of social isolation may have been greater because of the time in which it has occurred. This confinement has not only been inefficient as events with crowds of people occurred simultaneously while in other situations, such as the suspension of classes for school and university students, but it has also significantly affected our educational level. In addition, the long-standing compulsory confinement has not only failed to reduce infections and deaths, but Peru has one of the highest mortality rates in the world, with more than 200,000 Peruvians having died to date.

The strength of this study was the methodology, which shows within the context of the pandemic the use of technological tools is valuable for an understanding of society and its relationship with health. The instrument used included diverse sections of information, including a validated questionnaire (SF-20) to evaluate de HRQoL, which allowed a wider perspective to analyze causes for the results obtained. This study also shows how the application of health policies or measures should be based on the evaluation and social context.

This study presents certain limitations as well. First, our database was recollected by convenience; therefore, the results present in this paper cannot be generalized for the entire Peruvian population. However, our results show tendencies consistent with other studies. Also, due to social distancing and COVID-19 regulations, the anthropometric measurements were not able to be taken by health workers but were self-reported by the participants. This is a limitation since the margin of error increases; nevertheless, the correlation between measurements was high. Another limitation present was the research tool, the electronic questionnaire, which was more often completed by respondents with higher education and residents of high-income districts, probably also due to the better quality of Internet connection. Therefore, a follow-up is recommended according to the ethnicity and culture of each country or city.

In conclusion, although it is not a study that can be extrapolated to a large population, due to the type of design, this study allows us to have prior knowledge about health-related quality of life and how it has been affected to a large or medium extent in the context of the COVID-19 pandemic. The research team proposes longitudinal follow-ups of the population to avoid adverse outcomes in later life.

Data availability

Underlying data

Figshare: The social isolation enforced by the COVID-19 pandemic reduces the Health-Related Quality of Life score in the adult population of Metropolitan Lima. https://doi.org/10.6084/m9.figshare.19248635.⁴⁰

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

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Author details Author details

¹ Department of Biological and Physiological Sciences, Cayetano Heredia University, Lima, Lima, Lima 36, Peru
² Research Unit. Directorate of Public Health Laboratory, Dirección Regional de Salud, Callao, Callao, Callao, Callao 70000, Peru
³ Nutrition Department, Cayetano Heredia University, Lima, Lima, Lima 36, Peru

Valeria C. Morales-Ancajima
Roles: Conceptualization, Investigation

Cinthya Vasquez-Velasquez
Roles: Conceptualization, Investigation

Melany De la Cruz
Roles: Conceptualization, Investigation

Maria Marull
Roles: Investigation

Vilma Tapia
Roles: Data Curation, Formal Analysis

Gustavo F. Gonzales
Roles: Conceptualization, Investigation, Methodology

Competing interests

No competing interests were disclosed.

Grant information

Research reported in this publication was supported by the NIH Fogarty International Center, National Institutes of Environmental Health Science (NIEHS), R01ES018845, R01ES018845-S1, National Cancer Institute, National Institute for Occupational Safety and Health, and the NIH under Award Number U01 TW0101 07.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Article Versions (2)

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Published: 30 Jan 2023, 11:415

https://doi.org/10.12688/f1000research.109836.2

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https://doi.org/10.12688/f1000research.109836.1

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© 2022 Morales-Ancajima VC et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Morales-Ancajima VC, Vasquez-Velasquez C, De la Cruz M et al. The social isolation enforced by the COVID-19 pandemic reduces the Health-Related Quality of Life score in the adult population of Metropolitan Lima, Peru [version 1; peer review: 2 not approved] F1000Research 2022, 11:415 (https://doi.org/10.12688/f1000research.109836.1)

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ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions

Version 1

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Reviewer Report 19 Oct 2022

Bruna Brondani, Department of Pediatric Dentistry and Orthodontics, School of Dentistry, Universidade de Sao Paulo, São Paulo, State of São Paulo, Brazil

Not Approved

https://doi.org/10.5256/f1000research.121387.r152677

Comments to the Author
This cross-sectional study evaluated the association between social isolation due COVID-19 and HRQoL in 638 adults in Lima, Peru. Sociodemographic characteristics and anthropometric measures were also collected. As the main result, obesity, female sex, the ... Continue reading

Comments to the Author
This cross-sectional study evaluated the association between social isolation due COVID-19 and HRQoL in 638 adults in Lima, Peru. Sociodemographic characteristics and anthropometric measures were also collected. As the main result, obesity, female sex, the longest time of mandatory social confinement, and the existence of chronic disease were associated with a low total score of the HRQoL questionnaire.

While the study addressed an interesting topic, there are issues that need to be clarified and improved. In my opinion, the authors fail to present a more sophisticated rationale for the study, since similar articles have been recently published. In this sense, the authors should state what the new information provided and the innovation for international dentistry. I suggest detailing some methodological points that were not addressed or were not clear. Also, it is necessary to rethink the conduct of statistical analysis. Further insights into the text should be provided as follow:

Comments

Abstract

In the methods section of the abstract, I find it interesting to mention the age group of the evaluated participants and the statistical analysis conducted.
I suggest including the names of the effect measures obtained by the statistical analysis in the methodology section of the abstract [i.e. "Beta coefficient (β) and 95% confidence intervals (CI) were calculated"].

Introduction

In the sentence “This pandemic has changed the lives of millions of people and has resulted in, as of 28 February 2022, 5,950,433 deaths around the world.³”, I suggest that the author update this data.
In my opinion, the description of SF-20 in the introduction of the manuscript is not necessary. This information could be more useful in the methods section.
The introduction would benefit from a contextualization of what is already known about social isolation due to COVID-19 and HRQoL. In this sense, the authors could state more clearly what this study adds to the existing literature. Previous studies have already evaluated the impact of COVID-19 on psychosocial outcomes. Therefore, it is questioned why this study become special compared to others already published. The authors should justify more clearly what is the differential of this article.
At the end of the introduction section, I suggest the insertion of the aim of the study and the conceptual hypothesis, as it guides the investigation itself and is recommended by STROBE guidelines.

Material and methods

I recommend using the STROBE guideline checklist, as well as mentioning its use in the manuscript¹.
Some information should be given about the context (Lima, Peru). How many inhabitants are in total in Lima? How many citizens over 18 years of age live in the city? We can see a part of this information in the discussion session. However, this should be clarified in the methods.
In addition, some information should be given about the study population. What age group is covered in the study? How were participants selected for the survey? How did the researchers find and select the participants?
The sample calculation provided lacks additional information necessary for its understanding. Were similar parameters used in studies conducted in the literature? Why did the authors want to evaluate 1000 participants?
In data collection and management, the authors must comment on how the variables were collected, categorized, and worked on in the analysis. For example, it is not possible to understand how the level of education was measured and categorized. Authors must provide response options for each variable collected before reporting how they were categorized for analysis.
Since the participants were supposed to take their own anthropometric measurements, were they given any instructions on how the measurement should be taken?
In the sentence “Data were obtained on the presence of illness or symptoms related to COVID-19 and the time from the occurrence until the date the survey was completed”, how to know if it was really COVID-19? Symptoms are common to other infectious diseases, such as influenza, for example.
Regarding the SF-20 questionnaire, some additional information should be provided for readers' better understanding. For example, what are the response options for this questionnaire? What is the score variance? Does a higher score indicate a worse HRQoL?
“The methodology of using virtual surveys limits the information to a group with the availability of electronic equipment; therefore, we tried to disseminate the survey to population groups of different ages and within the same socio-economic level.” I believe that the attempt to include a larger sample number compromised the external validity of the results, since representativeness, already limited by non-probability sampling, was already a factor that compromised the representative sample.
Were the participants selected according to the city areas? If that’s the case, a correction factor for this type of sample should be considered to perform the descriptive analysis (sample weight).
In the statistical analysis, the authors used a multiple linear regression analysis to assess the predictors in the outcome. Again, I recommend that statistical analyses should consider the sample weight or the multilevel structure: participants (level 1) nested into a neighborhood or city area (level 2). Multilevel models take into account the spatial clustering of individuals within areas [Snijders; Boske, 2003]. In this sense, the social isolation due to COVID-19 in HRQoL can be influenced by the environment. The analysis should consider this factor².
The data analysis description lacks a clear theoretical framework and referenced to explain the relationship between exposures and outcomes, which are mediated and confounded. Did the authors build this statistical model based on any previous theoretical model? This explanation should be strengthened and need a broad and consistent theoretical framework.

Results

“Based on the inclusion criteria, data from 638 study participants (256 men, and 382 women) were analyzed.⁴⁰” What were the inclusion criteria adopted This information must be clarified in the methods section.
In all tables, add captions for the terms used in the abbreviated form [i.e. “BMI, SD, 95% CI”]. Enter information about the missing data [i.e. "Unmatched values due to missing data"].
Some variables are not seen in the tables. For example - socioeconomic level is a factor that can influence the outcome. Also, why didn't the authors collect income? It is also something that can influence. The authors say that individuals belonging to higher socioeconomic levels responded more to the questionnaires. But where is this information?
Table 2 is not clear. For each variable, it must have the category - yes or no - and the values expressed in their respective lines. Thus, the reader cannot interpret the table without having to look for help in the text of the article.
“In the crude model, obesity, female sex, time in compulsory social confinement, and the presence of chronic disease are associated with lower total scores on the HRQoL questionnaire. These same variables remain significantly associated in the adjusted model.” According to table 3, age was also significantly associated with the outcome, right?
Why did the authors decide to individually assess only the physical dimension of the FS-20 questionnaire?

Discussion

I suggest introducing in the first paragraph of the discussion the confirmation/rejection of the hypothesis described in the introduction, as well as reinforcing the originality and contribution of the study to the literature.
“The strength of this study was the methodology, which shows within the context of the pandemic the use of technological tools is valuable for an understanding of society and its relationship with health. The instrument used included diverse sections of information, including a validated questionnaire (SF-20) to evaluate de HRQoL, which allowed a wider perspective to analyze causes for the results obtained.” Are there any studies that prove that this method adopted is reliable and as good as face-to-face interviews and assessments? The fact that participants must measure their own anthropometric measurements is a limitation for me. I question the claim that methodology is a strong point of this study.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

No
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Yes

References

1. Cuschieri S: The STROBE guidelines.Saudi J Anaesth. 2019; 13 (Suppl 1): S31-S34 PubMed Abstract | Publisher Full Text
2. Snijders TAB, Bosker RJ: Multilevel analysis: An introduction to basic and advanced multilevel modeling. London:SAGE Publications Ltd. 2003.

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Epidemiology. Public Health. Pediatric Dentistry. Quality of Life. Social Determinants of Health. Iniquities.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

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Reviewer Report 16 Aug 2022

Lucie Ecker-Ledesma, Instituto de Investigación Nutricional, Lima, Peru, Lima, Peru

Not Approved

https://doi.org/10.5256/f1000research.121387.r146543

This work is important but an improvement of some aspects have to be done in order to present the data in the best way. Additionally, spelling should be checked across the whole document.

The importance of this ... Continue reading

This work is important but an improvement of some aspects have to be done in order to present the data in the best way. Additionally, spelling should be checked across the whole document.

The importance of this work needs to be better explained. Why is this important? Conclusion of the abstract mentions that: "Mandatory social confinement may have harmed the perception of health related quality of life". Is the message that the perception is harmed, or the quality of life?

What is the relation of obesity and HRQoL? This has to be described more deeply.

References are missing in some parts of the document:
"Currently, 72% of the target population is immunized with two doses of the vaccine...."Ref.
"For this purpose, there are several HRQoL questionnaires" only one is referenced.

Reference for SF-20 questionnaire mentions Nottingham questionnaire, not SF-20.

Sample size calculation is not clearly defined. Population has to be defined more precisely. It mentions random sampling technique, however participants were selected by convenience.

Anthropometric measures are presented, however it is not mentioned how they were obtained in methods (if this was an online survey, were they taken by the participants?) This has to be mentioned and the limitation of not having a standardized method to obtain those has to be assessed.

The modified SF-20 questionnaire has to be attached as complementary web appendix.

The result section mentions inclusion criteria, these have to be mentioned before.

Tables and figures have to be improved:

Table 1. mentions as description of the values presented mean+/- SD(95% CI), however it seems that ranges are also included? Please clarify. Comparison of the two groups can be made in table 1 in order to see if they are comparable.
In table 2, the p-value should be included. It is unclear if the question answer is yes/no for the the questions that involves "feelings" presented in table 2, or is it a likelihood scale?
p-values should be added in table3. Coefficient of sex in the adjusted model is wrong it should be negative (according to the CI)? Residuals should be discussed.
Table 4: please review, some coefficients and CI are mixed up.

Discussion should mention all the limitations, and this data cannot be generalized for the 10 million inhabitants of Lima, Perú, at the beginning of the discussion, it seems that the study refers to this population. Main results have to be discussed more accurately.

Is the work clearly and accurately presented and does it cite the current literature?

No
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

No
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Epidemiology, Public health, antibiotic resistance, Infectious disease, vaccines

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

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Lucie Ecker-Ledesma, Instituto de Investigación Nutricional, Lima, Peru, Lima, Peru
Bruna Brondani, Universidade de Sao Paulo, São Paulo, Brazil
Patricia Pavón León, Universidad Veracruzana, Xalapa, Mexico

Abel Domínguez Morán, Veracruzana University, Xalapa, Mexico

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01 Sep 2023 | for Version 2

Patricia Pavón León, Department of Health Systems Research, Universidad Veracruzana, Xalapa, Veracruz, Mexico

Abel Domínguez Morán, Instituto de Ciencias deSalud, Veracruzana University, Xalapa, Veracruz, Mexico

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Not Approved

General: The document presents notable areas for improvement, such as the development of their abstract, more specifically in their results and conclusions part of it. The correct use of punctuation as well as the language used should also be checked through the whole document. The translation into English can also be improved. As a copy of the original document in Spanish was not provided, it is not possible to assess the quality of the translation made, except in specific cases where the misuse of certain words is obvious. It is suggested to submit the document to a certified translator in order to avoid errors.

Introduction:

Page 3 – paragraph 1 – line 4: This pandemic has changed the lives of millions of people and has 6.3 million deaths around the world. Proposal to change the wording and specify the cause of death.

Page 3 – paragraph 2 – line 1: Governments applied various public policies to reduce its spread, one of them being social isolation. Proposal to define what "social isolation" entails, and more specifically in the country of the study.

Page 3 – paragraph 3– line 3/4: Currently, 72% of the population is of Metropolitan Lima immunized with two doses of the vaccine 73.92% have received the third dose and 25% have received the fourth dose. Proposal to check the punctuation and wording of the sentences.

Page 3 – paragraph 5– line 1: On the other hand, the emergence of pandemic-related psychological reactions; cases in people without a pre-existing. Proposal to change the wording/translation of “on the other hand”.

Page 3 – paragraph 6: The human response to a pandemic is not uniform and may vary between countries and regions. Likewise, given that lethality differs by gender and age, it is possible that coping may also differ. Subjects with co-morbidities, males and older people have had higher case fatality rates. Peru is one of the countries with the highest case fatality and currently has COVID-19 mortality of 202, 424 people. Proposal to check the wording of the whole paragraph. Go over again the translation for “coping”.

Page 3 – paragraph 7– line 2/3: Academic factors had a greater impact on mental health, which may lead to a decrease in their performance. Core idea is not clear: are the academic factors taken in consideration WITH the confinement factors for their decrease in performance?

Page 3 - last two paragraphs: The information about the SF-20 is suggested to be moved to the methodology section.

Include at the end of the introduction the objective of the article.
There are many published studies about the impact on HRQoL due to social isolation and that are not mentioned in the introduction. These should be analyzed to clarify the contribution of this study to the knowledge on the subject.

Methods: The study takes participants 18 years of age or older, but a solid argument is not established as to why the evaluation is carried out from that age and minors are not taken. An argument regarding the relationship between the confinement situation and the impact on the university population in terms of their performance in classes is attached previously, but seeing that the average age is centered on 37 years, there are no mentions of school or work performance, and it was not carried out exclusively in an academic environment, the argument lacks significance beyond a certain part of its population.

Page 4 – paragraph 1: This was a cross-sectional analytical study. Participants were recruited by a convenience sample of males and females over 18 years of age and residents of Metropolitan Lima, capital of Peru for more than 1 year before the time of participation in the survey. Access to an electronic device was required. Participants completed the survey after the established date and those who did not agree to participate in the informed consent were excluded. Proposal to check the wording of the whole paragraph. Proposal to define what types of “electronic devices” were required. Check the wording on the last sentence “Participants WHO completed the survey…”

Page 4 – paragraph 2– line 1/2: This is a cross-sectional analytical study conducted during the months of October and December 2021. For data collection we worked with Google Forms, which contained the survey and informed consent form. This line repeats the type of study, which is not needed. There is also the mention of doing the study during the months of October and December, which may be a mistranslation regarding the duration (of October THROUGH December). On the contrary, if it was done during those 2 months separately, a reason for that choice should be established. Proposal to change first person to third person (“we worked”).

Page 6 – paragraph 2– line 3: The scores obtained from the questions are summed… The optimal wording, or translation, would be “added” instead of “summed”.

Page 7 – paragraph 1– line 2: therefore, we tried to disseminate the survey to population groups of different ages and within the same socio-economic level. Proposal to change first person to third person (“we tried”).
Move Table 1 to the results section.

Results:
Page 7 – paragraph 6– line 2: Overall, 19.5% of male respondents studied had COVID-19 while 20.4% of women had COVID-19 (p>0.05). The idea is not clear. The use of “studied” appears as a translation error.

Page 8 – paragraph 2– line 3/4: if they aggravate the disease, shortness of breath manifests. Correct translation would be “if the disease aggravates”.

Page 8 – paragraph 6– line 2/3: Health-related quality of life (HRQoL) is an indicator that helps us to measure people’s self-perception of their health. Proposal to change first person to third person (“helps us”).

Table 1. The results for the General Health Component and the sociodemographic characteristic of education are not included.
Explain how the variables included in the Spearman correlation analysis were selected; sex and education were missing.
Time of CSC: time of compulsory social confinement, TVA: time after vaccination, this information should be included in the methods section and in Table 2.

Discussion: The authors maintain that the strength of the study was the methodology, but as a previous reviewer mentioned, the development of the evaluation by purely digital means and based on the own perception of the participants limits the veracity of the study if there is no way to corroborate these results, especially on the side of physical measurements.

In the same way, the authors repeatedly mention aspects related to mental health, but this is only measured with the SF-20 and not corroborated with other types of evaluations, so their statements are based purely on the results of other investigations, which they themselves mention.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Aging, drug consumption, health systems.

We confirm that we have read this submission and believe that we have an appropriate level of expertise to state that we do not consider it to be of an acceptable scientific standard, for reasons outlined above.

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Reviewer Report

6 Views

26 Apr 2023 | for Version 2

Bruna Brondani, Department of Pediatric Dentistry and Orthodontics, School of Dentistry, Universidade de Sao Paulo, São Paulo, State of São Paulo, Brazil

6 Views Cite this report Responses(0)

Not Approved

Even though the authors have made some of the suggested changes, there are still questions not understood about the methodology used, sample calculation, and statistical analysis. The justification for carrying out this work remains little explored in the introduction. Therefore, many of my previous considerations are still valid.

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Epidemiology. Public Health. Pediatric Dentistry. Quality of Life. Social Determinants of Health. Iniquities.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

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23 Views

19 Oct 2022 | for Version 1

Bruna Brondani, Department of Pediatric Dentistry and Orthodontics, School of Dentistry, Universidade de Sao Paulo, São Paulo, State of São Paulo, Brazil

23 Views Cite this report Responses(0)

Not Approved

Comments to the Author
This cross-sectional study evaluated the association between social isolation due COVID-19 and HRQoL in 638 adults in Lima, Peru. Sociodemographic characteristics and anthropometric measures were also collected. As the main result, obesity, female sex, the longest time of mandatory social confinement, and the existence of chronic disease were associated with a low total score of the HRQoL questionnaire.

While the study addressed an interesting topic, there are issues that need to be clarified and improved. In my opinion, the authors fail to present a more sophisticated rationale for the study, since similar articles have been recently published. In this sense, the authors should state what the new information provided and the innovation for international dentistry. I suggest detailing some methodological points that were not addressed or were not clear. Also, it is necessary to rethink the conduct of statistical analysis. Further insights into the text should be provided as follow:

Comments

Abstract

In the methods section of the abstract, I find it interesting to mention the age group of the evaluated participants and the statistical analysis conducted.
I suggest including the names of the effect measures obtained by the statistical analysis in the methodology section of the abstract [i.e. "Beta coefficient (β) and 95% confidence intervals (CI) were calculated"].

Introduction

In the sentence “This pandemic has changed the lives of millions of people and has resulted in, as of 28 February 2022, 5,950,433 deaths around the world.³”, I suggest that the author update this data.
In my opinion, the description of SF-20 in the introduction of the manuscript is not necessary. This information could be more useful in the methods section.
The introduction would benefit from a contextualization of what is already known about social isolation due to COVID-19 and HRQoL. In this sense, the authors could state more clearly what this study adds to the existing literature. Previous studies have already evaluated the impact of COVID-19 on psychosocial outcomes. Therefore, it is questioned why this study become special compared to others already published. The authors should justify more clearly what is the differential of this article.
At the end of the introduction section, I suggest the insertion of the aim of the study and the conceptual hypothesis, as it guides the investigation itself and is recommended by STROBE guidelines.

Material and methods

I recommend using the STROBE guideline checklist, as well as mentioning its use in the manuscript¹.
Some information should be given about the context (Lima, Peru). How many inhabitants are in total in Lima? How many citizens over 18 years of age live in the city? We can see a part of this information in the discussion session. However, this should be clarified in the methods.
In addition, some information should be given about the study population. What age group is covered in the study? How were participants selected for the survey? How did the researchers find and select the participants?
The sample calculation provided lacks additional information necessary for its understanding. Were similar parameters used in studies conducted in the literature? Why did the authors want to evaluate 1000 participants?
In data collection and management, the authors must comment on how the variables were collected, categorized, and worked on in the analysis. For example, it is not possible to understand how the level of education was measured and categorized. Authors must provide response options for each variable collected before reporting how they were categorized for analysis.
Since the participants were supposed to take their own anthropometric measurements, were they given any instructions on how the measurement should be taken?
In the sentence “Data were obtained on the presence of illness or symptoms related to COVID-19 and the time from the occurrence until the date the survey was completed”, how to know if it was really COVID-19? Symptoms are common to other infectious diseases, such as influenza, for example.
Regarding the SF-20 questionnaire, some additional information should be provided for readers' better understanding. For example, what are the response options for this questionnaire? What is the score variance? Does a higher score indicate a worse HRQoL?
“The methodology of using virtual surveys limits the information to a group with the availability of electronic equipment; therefore, we tried to disseminate the survey to population groups of different ages and within the same socio-economic level.” I believe that the attempt to include a larger sample number compromised the external validity of the results, since representativeness, already limited by non-probability sampling, was already a factor that compromised the representative sample.
Were the participants selected according to the city areas? If that’s the case, a correction factor for this type of sample should be considered to perform the descriptive analysis (sample weight).
In the statistical analysis, the authors used a multiple linear regression analysis to assess the predictors in the outcome. Again, I recommend that statistical analyses should consider the sample weight or the multilevel structure: participants (level 1) nested into a neighborhood or city area (level 2). Multilevel models take into account the spatial clustering of individuals within areas [Snijders; Boske, 2003]. In this sense, the social isolation due to COVID-19 in HRQoL can be influenced by the environment. The analysis should consider this factor².
The data analysis description lacks a clear theoretical framework and referenced to explain the relationship between exposures and outcomes, which are mediated and confounded. Did the authors build this statistical model based on any previous theoretical model? This explanation should be strengthened and need a broad and consistent theoretical framework.

Results

“Based on the inclusion criteria, data from 638 study participants (256 men, and 382 women) were analyzed.⁴⁰” What were the inclusion criteria adopted This information must be clarified in the methods section.
In all tables, add captions for the terms used in the abbreviated form [i.e. “BMI, SD, 95% CI”]. Enter information about the missing data [i.e. "Unmatched values due to missing data"].
Some variables are not seen in the tables. For example - socioeconomic level is a factor that can influence the outcome. Also, why didn't the authors collect income? It is also something that can influence. The authors say that individuals belonging to higher socioeconomic levels responded more to the questionnaires. But where is this information?
Table 2 is not clear. For each variable, it must have the category - yes or no - and the values expressed in their respective lines. Thus, the reader cannot interpret the table without having to look for help in the text of the article.
“In the crude model, obesity, female sex, time in compulsory social confinement, and the presence of chronic disease are associated with lower total scores on the HRQoL questionnaire. These same variables remain significantly associated in the adjusted model.” According to table 3, age was also significantly associated with the outcome, right?
Why did the authors decide to individually assess only the physical dimension of the FS-20 questionnaire?

Discussion

I suggest introducing in the first paragraph of the discussion the confirmation/rejection of the hypothesis described in the introduction, as well as reinforcing the originality and contribution of the study to the literature.
“The strength of this study was the methodology, which shows within the context of the pandemic the use of technological tools is valuable for an understanding of society and its relationship with health. The instrument used included diverse sections of information, including a validated questionnaire (SF-20) to evaluate de HRQoL, which allowed a wider perspective to analyze causes for the results obtained.” Are there any studies that prove that this method adopted is reliable and as good as face-to-face interviews and assessments? The fact that participants must measure their own anthropometric measurements is a limitation for me. I question the claim that methodology is a strong point of this study.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

No
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Yes

References

1. Cuschieri S: The STROBE guidelines.Saudi J Anaesth. 2019; 13 (Suppl 1): S31-S34 PubMed Abstract | Publisher Full Text
2. Snijders TAB, Bosker RJ: Multilevel analysis: An introduction to basic and advanced multilevel modeling. London:SAGE Publications Ltd. 2003.

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Epidemiology. Public Health. Pediatric Dentistry. Quality of Life. Social Determinants of Health. Iniquities.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

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Reviewer Report

35 Views

16 Aug 2022 | for Version 1

Lucie Ecker-Ledesma, Instituto de Investigación Nutricional, Lima, Peru, Lima, Peru

35 Views Cite this report Responses(0)

Not Approved

This work is important but an improvement of some aspects have to be done in order to present the data in the best way. Additionally, spelling should be checked across the whole document.

The importance of this work needs to be better explained. Why is this important? Conclusion of the abstract mentions that: "Mandatory social confinement may have harmed the perception of health related quality of life". Is the message that the perception is harmed, or the quality of life?

What is the relation of obesity and HRQoL? This has to be described more deeply.

References are missing in some parts of the document:
"Currently, 72% of the target population is immunized with two doses of the vaccine...."Ref.
"For this purpose, there are several HRQoL questionnaires" only one is referenced.

Reference for SF-20 questionnaire mentions Nottingham questionnaire, not SF-20.

Sample size calculation is not clearly defined. Population has to be defined more precisely. It mentions random sampling technique, however participants were selected by convenience.

Anthropometric measures are presented, however it is not mentioned how they were obtained in methods (if this was an online survey, were they taken by the participants?) This has to be mentioned and the limitation of not having a standardized method to obtain those has to be assessed.

The modified SF-20 questionnaire has to be attached as complementary web appendix.

The result section mentions inclusion criteria, these have to be mentioned before.

Tables and figures have to be improved:

Table 1. mentions as description of the values presented mean+/- SD(95% CI), however it seems that ranges are also included? Please clarify. Comparison of the two groups can be made in table 1 in order to see if they are comparable.
In table 2, the p-value should be included. It is unclear if the question answer is yes/no for the the questions that involves "feelings" presented in table 2, or is it a likelihood scale?
p-values should be added in table3. Coefficient of sex in the adjusted model is wrong it should be negative (according to the CI)? Residuals should be discussed.
Table 4: please review, some coefficients and CI are mixed up.

Discussion should mention all the limitations, and this data cannot be generalized for the 10 million inhabitants of Lima, Perú, at the beginning of the discussion, it seems that the study refers to this population. Main results have to be discussed more accurately.

Is the work clearly and accurately presented and does it cite the current literature?

No
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

No
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Epidemiology, Public health, antibiotic resistance, Infectious disease, vaccines

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

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The social isolation enforced by the COVID-19 pandemic reduces the Health-Related Quality of Life score in the adult population of Metropolitan Lima, Peru

Abstract

Keywords

Introduction

Methods

Study design

Socio-demographic characteristics

Anthropometric measures

History of disease

Data related to COVID-19

Measurement of HRQoL

Statistical analysis

Bias

Ethical aspects

Results

Table 1. Description of the sex, age and anthropometric variables in the participating population of Metropolitan Lima.

Figure 1. Spearman correlation analysis between the different variables studied in the study population of Metropolitan Lima.

Table 2. Data related to the coronavirus disease 2019 (COVID-19) pandemic in participants from Metropolitan Lima who previously presented with COVID-19 compared to those who did not present with COVID-19.

Table 3. Linear regression models for the total score of the HRQoL questionnaire (SF-20) in adult subjects in Metropolitan Lima.

Table 4. Linear regression models for the physical and mental component of the HRQoL questionnaire in adult subjects in Metropolitan Lima.

Discussion

Data availability

Underlying data

References

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