Risk of mental disorders and malnutrition in elderly COVID-19 survivors: An observational study

Ria Maria Theresa; Marlina Dewiastuti; Sri Rahayu Ningsih; Lisa Safira

doi:10.12688/f1000research.121696.2

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Research Article

Revised

Risk of mental disorders and malnutrition in elderly COVID-19 survivors: An observational study

[version 2; peer review: 1 approved, 1 approved with reservations, 1 not approved]

Ria Maria Theresa¹, Marlina Dewiastuti², Sri Rahayu Ningsih³, Lisa Safira⁴

PUBLISHED 02 Oct 2023

Author details Author details

¹ Psychiatry, Universitas Pembangunan Nasional Veteran Jakarta, Jakarta, DKI, 12310, Indonesia
² Internal Medicine, Universitas Pembangunan Nasional Veteran Jakarta, Jakarta, DKI, 12310, Indonesia
³ Biostatistik, Universitas Gunadarma, Depok, West Java, Indonesia
⁴ Medical study program, Universitas Pembangunan Nasional Veteran Jakarta, Jakarta, DKI, 12310, Indonesia

Ria Maria Theresa
Roles: Conceptualization, Supervision, Writing – Original Draft Preparation

Marlina Dewiastuti
Roles: Investigation, Project Administration, Validation, Writing – Review & Editing

Sri Rahayu Ningsih
Roles: Data Curation, Formal Analysis, Methodology, Project Administration, Software

Lisa Safira
Roles: Funding Acquisition, Resources, Validation, Visualization, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Research Synergy Foundation gateway.

This article is included in the Coronavirus (COVID-19) collection.

Abstract

Background: The incidence rate of COVID-19 is around 11-15% in the elderly. The case fatality rate (CFR) of COVID-19 in the elderly is around 8.9% and increases with age. The risk of mental disorders and malnutrition is increased in COVID-19 survivors. Continuous inflammatory conditions result in a state of hypercatabolism that can disrupt brain neuroendocrine and protein consumption for the formation of acute-phase reactant proteins. Mental disorders and malnutrition can lead to fragility. The aim of this study was to assess the risk of mental disorders and malnutrition in elderly survivors of COVID-19.
Methods: This research was a cross-sectional study. The results of the research on age, disease symptoms, and comorbidities have proven that they are risk factors for mental disorders and malnutrition in elderly COVID-19 survivors. This study used total sampling and included 100 study subjects. The research was conducted in Depok for two months; data was collected directly through shared questionnaires and direct anthropometric measurements. The questionnaires used were the SRQ-20 tool for mental disorder screening and MNA for malnutrition screening.
Results: The risk factors for mental disorders were age over 70 years old OR 3 (CI 1.0-8.8), severe COVID-19 symptoms OR 4.5 (CI 1.2-16.17), and multi-comorbidity OR 2.3 (CI 0.6-8.8). The risk factors for malnutrition were age higher than 70 years old OR 2.5 (CI 0.8-7.9), moderate COVID-19 symptoms OR 6.3 (CI 2.0-19.81), and multi-comorbidity OR 6.6 (CI 1.5-28.5).
Conclusions: Those infected with COVID-19 have a risk of mental disorders and malnutrition, especially in geriatrics, and this risk increases with age.

Keywords

COVID-19, elderly, survivors, mental disorders, malnutrition

Corresponding author: Marlina Dewiastuti

Competing interests: No competing interests were disclosed.

Grant information: This study was supported by a research grant from the Research and Community Service Institute UPN Veteran Jakarta.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2023 Theresa RM 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: Theresa RM, Dewiastuti M, Ningsih SR and Safira L. Risk of mental disorders and malnutrition in elderly COVID-19 survivors: An observational study [version 2; peer review: 1 approved, 1 approved with reservations, 1 not approved]. F1000Research 2023, 12:42 (https://doi.org/10.12688/f1000research.121696.2) First published: 11 Jan 2023, 12:42 (https://doi.org/10.12688/f1000research.121696.1) Latest published: 02 Oct 2023, 12:42 (https://doi.org/10.12688/f1000research.121696.2)

Revised Amendments from Version 1

I have corrected this article according to the input from reviewers. Malnutrition in the elderly will worsen health status in any situation. No studies have assessed malnutrition in elderly covid patients. Subjects were diagnosed covid-19 by hospital data from a Hospital located in Depok Jawa Barat Indonesia, using a total sampling of hospital data. Based on hospital data (BMI and mini nutritional assessment), the subjects were not malnourished. In this study, inclusion criteria were people over 60 years old and diagnosed for the first time exposure by covid-19.

See the authors' detailed response to the review by Mirasari Putri

Introduction

The Coronavirus disease 2019 (COVID-19) is currently a worldwide pandemic. The morbidity and mortality rates are still increasing, especially in developing countries such as Indonesia. More than one million Indonesians suffer from COVID-19. Data from several studies indicate high morbidity and mortality rates in the elderly population. The incidence rate of COVID-19 in the population is around 11-17%, while the case fatality rate (CFR) is around 8.9% and increases with age.¹^–⁵

The elderly population has an immunosenescence state, which causes disturbances in innate and adaptive immune systems. COVID-19 in the elderly results in a continuous inflammatory response, causing the clinical symptoms of COVID-19 in the elderly to often be more severe and the mortality rate to be high.⁶

Survivors of COVID-19 have an increased risk of psychiatric disorders. About 20% of COVID-19 survivors will experience mental disorders. The most common clinical manifestations are depression, anxiety, and sleep disturbances.⁶^–¹⁰

Mental disorders increase along with the increasing age of COVID-19 survivors. The pathogenesis of psychiatric disorders in COVID-19 survivors is a continuous inflammatory state that can result in disturbances in neuroendocrine, neuroimmune, and nervous structures.¹¹^–¹⁵

A total of 52.7% of the elderly population who were infected by COVID-19 suffers from malnutrition. This is due to the fact that most elderly people who suffer from COVID-19 have multiple comorbidities. In addition, the inflammatory reaction causes high catabolism, causing high protein consumption for the formation of acute phase reactants. The expression of angiotensin-2 receptor (ACE-2) in the gastrointestinal tract is high which causes symptoms of nausea, vomiting, diarrhea, and reduced appetite to increase in the elderly. The ongoing inflammatory reaction that occurs in the elderly results in a higher risk of malnutrition even when they have survived COVID-19.¹⁶^–²⁰

Factors that influence mental disorders and malnutrition in COVID-19 survivors will be investigated in this study. Including gender, employment status, inpatient or outpatient care during illness, degree of illness, presence of caregiver, and vaccination status. There is no research was conducted on the factors that influence mental disorders and malnutrition in elderly COVID-19 survivors.

The risk of mental disorders and malnutrition in elderly COVID-19 survivors can lead to fragility. The fragility of elderly COVID-19 survivors increases hospitalization rates and mortality (Figure 1).¹⁷^,²¹^–²⁵

Figure 1. Risk of mental disorders and malnutrition in elderly COVID-19 survivors.

The aim of this study was to investigate the risk of mental disorders and malnutrition in elderly COVID-19 survivors.

Methods

Ethical considerations

This study was approved by the UPN Veteran Jakarta Ethical Clearance Committee (Protocol number: 455/X/2021/KEPK) after due consultation, consent letters had been provided by the researchers to all respondents.

Research methods

This research was a cross-sectional study conducted in Depok, Indonesia. Depok is an urban city that supporting the capital city. The elderly population is 3.77% of the total Depok population. The research sampled 100 people, patients diagnosed with COVID-19 by hospital data from Depok Hospital and willing to take part in the research (male = 52, female = 48) using total sampling. Data were collected by interview and direct data collection within three months of respondents being infected with COVID-19. The data was taken from the elderly population of Depok who had been infected with COVID-19 between May to July 2021. Inclusion criteria were the population of people over 60 years old and first time diagnosed with COVID-19 who were undergoing treatment in a hospital or quarantine at home, while exclusion criteria were the population who had been diagnosed with mental disorders and malnourished. Medical conditions such as dementia or other cognitive disorders were not previously evaluated in the study.

The outcome variables of this study were the risk of mental disorders and malnutrition. Both variables were categorized as having risks and having no risks. The independent variable in the study was age, measured since the respondent's birth. Another variable was the degree of severity of COVID-19; the severity of the disease was characterized as mild, moderate, and severe, and whether there were concomitant diseases or not.¹ The three variables were observed and tested using a logistic regression test. Insignificant variable expenditure causes a change in odds ratio (OR); if the OR change is more than 10% then the variable is a confounder variable and must be included in the model. Other potential confounders not observed in the study were economic status and a history of previous mental disorders.

Data were collected from questionnaires and anthropometric measurements. Questionnaire interviews were conducted by trained interviewers (RM). Interviews and data collection took 20-30 minutes per participant. Responses to questionnaires were inputted into electronic data. Before the data was collected, interrater reliability was carried out.

Sociodemographic information and health conditions obtained in this study included age, occupation, availability of caregivers, already received vaccinations, symptoms of COVID-19, and comorbidities. Data on comorbidities was obtained from self-reports.

Anthropometric measurements included measurements of height, weight, and body mass index. Measurement of body mass index was calculated based on the weight in kilograms divided by height in meters squared.

The data was cleaned after collection. Incomplete questionnaire data at the time of collection was re-confirmed with the study respondents.

The mental disorder questionnaire was based on the SRQ-20 questionnaire. There were 20 questions that were asked by direct interview. Obtaining a value of more than or equal to 8 meant the respondent had a risk of mental disorders. This questionnaire is a screening questionnaire that has been tested for validity and reliability and a diagnostic test with 88% sensitivity for mental disorder screening.²⁶^–²⁸

The malnutrition questionnaire used a mini nutritional assessment (MNA) questionnaire, conducted directly with interviews and direct body index measurements. Obtaining a value less than 11 was considered possible malnutrition. The MNA questionnaire is a questionnaire commonly used for malnutrition screening in the elderly. This questionnaire has been conducted with validity and reliability tests and diagnostic tests with a sensitivity of 96%.²⁹^,³⁰

Statistical analysis was performed with the Statistical Package for Social Sciences (SPSS). Significance was determined with an alpha value of <0.05. Descriptive analysis was conducted to look at demographic data such as gender, occupation, care during COVID-19, availability of caregivers, and vaccination status. Variables such as age, the severity of disease, and comorbidities were assessed using a Chi-square test. A logistic regression test was conducted to determine the factors that influence mental disorders and malnutrition with a multivariate model.

Results

This study invited 158 participants; 56 participants refused and did not respond the questionnaire. Two had missing data on the dependent variable and could not be contacted for confirmation of research data. A total of 100 participants were studied (Figure 2).

Figure 2. Participant inclusion chart.

A total of 100 respondents were tested based on baseline characteristics; p-values were over 0.05, so it can be concluded that there was no significant differences in the characteristics of respondents. The variable of availability of caregivers or nurses while being infected with COVID-19 for those who have a disorder did not show any significant differences; this is because the number of respondents who were outpatients is small.

As seen in Table 1, there was no difference in the occurrence of mental disorders between sexes; men and women had almost the same percentages. There was no difference in the occurrence of mental disorders between the different professions, nor was there a difference in the occurrence of mental disorders between those with caregivers and those without. Regarding treatment, a difference was observed because most of the elderly population infected with COVID-19 are likely to receive treatment in hospitals.

Table 1. Demographic description of respondents by mental disorder status.

Variable	Mental disorders		Total (%)	P-value
Variable	Yes (%)	No (%)	Total (%)	P-value
Gender
Male	24 (46.20)	28 (53.80)	52 (100.00)	0.423
Female	26 (54.20)	22 (45.80)	48 (100.00)
Profession
Housewife	22 (55.00)	18 (45.00)	40 (100.00)	0.706
Retired	25 (46.30)	29 (53.70)	54 (100.00)
Employee	3 (50.00)	3 (50.00)	6 (100.00)
Inpatient/outpatient
Outpatient	7 (26.90)	19 (73.10)	26 (100.00)	0.016
Inpatient	43 (58.10)	31 (41.90)	74 (100.00)
Caregiver
Yes	47 (49.00)	49 (51.00)	96 (100.00)	0.307
No	3 (75.00)	1 (25.00)	4 (100.00)
Income
<Rp. 5.000.000	35 (50.00)	35 (50.00)	70 (100.00)	0.999
≥Rp. 5.000.000	15 (50.00)	15 (50.00)	30 (100.00)
Vaccinated status
Done	10 (38.50)	16 (61.50)	26 (100.00)	0.171
None	40 (54.10)	34 (45.90)	74 (100.00)

The characteristics of the malnourished group also showed there was no difference in baseline characteristics (gender, profession, caregiver, income, vaccinated status), where the characteristics of the respondents in patients who had malnutrition and those who did not suffer from malnutrition were homogeneous.

In Table 2 there are no differences between gender, profession, and availability of caregivers’ effect on the risk of malnutrition. However, there was a difference between treatment during COVID-19 infection and the risk of malnutrition; this may be because most elderly people infected with COVID-19 get treatment in hospitals.

Table 2. Demographic description of respondents based on malnutrition disorder status.

Variable	Malnutrition		Total (%)	P-value
Variable	Yes (%)	No (%)	Total (%)	P-value
Gender
Male	25 (48.10)	27 (51.90)	52 (100.00)	0.543
Female	26 (54.20)	22 (45.80)	48 (100.00)
Profession
Housewife	21 (52.50)	19 (47.50)	40 (100.00)	0.970
Retired	27 (50.00)	27 (50.00)	54 (100.00)
Employee	3 (50.00)	3 (50.00)	6 (100.00)
Inpatient/outpatient
Outpatient	6 (23.10)	20 (76.90)	26 (100.00)	0.001
Inpatient	45 (60.80)	29 (39.20)	74 (100.00)
Caregiver
Yes	47 (49.00)	49 (51.00)	96 (100.00)	0.136
No	4 (100.00)	0 (00.00)	4 (100.00)
Income
<Rp. 5.000.000	35 (50.00)	35 (50.00)	70 (100.00)	0.760
≥Rp. 5.000.000	16 (53.30)	14 (46.70)	30 (100.00)
Vaccinated status
Done	11 (42.30)	15 (57.70)	26 (100.00)	0.171
None	40 (54.10)	34 (45.90)	74 (100.00)

Based on the results in Tables 3 and 4, the variables of age, symptoms, and comorbidities were included in the multivariate analysis, both for mental disorders and malnutrition disorders.

Table 3. Relationship variables age, symptoms, and comorbidities with mental disorders.

Variable	Mental disorders		Total (%)	P-Value
Variable	Yes (%)	No (%)	Total (%)	P-Value
Age
60-70 yo	30 (41.10)	43 (58.90)	73 (100.00)	0.003
>70 yo	20 (74.10)	7 (25.90)	27 (100.00)
Symptoms
Mild	12 (30.80)	27 (69.20)	39 (100.00)	0.005
Moderate	25 (58.10)	18 (41.90)	43 (100.00)
Severe	13 (72.20)	5 (27.80)	18 (100.00)
Comorbidities
None	15 (36.60)	26 (63.40)	41 (100.00)	0.042
1 Comorbidity	24 (58.50)	17 (41.50)	41 (100.00)
>1 Comorbidity	11 (61.10)	7 (38.90)	18 (100.00)

Table 4. Relationships between variables of age, symptoms, and comorbidities with malnutrition disorder.

Variable	Malnutrition		Total (%)	P-value
Variable	Yes (%)	No (%)	Total (%)	P-value
Age
60-70 yo	31 (42.50)	42 (57.50)	73 (100.00)	0.005
>70 yo	20 (74.10)	7 (25.90)	27 (100.00)
Symptoms
Mild	11 (28.20)	28 (71.80)	39 (100.00)	0.001
Moderate	27 (62.80)	16 (37.20)	43 (100.00)
Severe	13 (72.20)	5 (27.80)	18 (100.00)
Comorbidities
None	12 (29.30)	29 (70.70)	41 (100.00)	0.001
1 Comorbidity	27 (65.90)	14 (34.10)	41 (100.00)
>1 Comorbidity	12 (66.70)	6 (33.30)	18 (100.00)

Table 3 shows there was a relationship between increased age and the risk of mental disorders. There was also a relationship between the severity of COVID-19 symptoms and the number of comorbidities with the risk of mental disorders.

Table 4 shows a relationship between increasing age and the risk of malnutrition. There was also a relationship between the severity of COVID-19 symptoms and the number of comorbidities with the risk. Comorbidities that affect degree of disease were hypertension, diabetes mellitus, and cardiovascular disease (coronary arterial disease or cerebrovascular disease.

Based on the results of the multiple logistic regression analysis in Table 5, the factors that influenced mental disorders were age and symptoms. People older than 70 years had a three-time greater risk of experiencing mental disorders than the elderly aged between 60-70 years old, after controlling for symptoms and comorbidities variables at a 95% confidence interval (CI) between 1,071 to 8,83. The elderly with severe COVID-19 symptoms were at a 4.5-time greater risk of experiencing mental disorders compared to the elderly with mild symptoms, after controlling for age and comorbidities variables at a 95% confidence level between 1.23 to 16.71.

Table 5. Mental disorder multiple logistic regression model.

Variable	P-value	OR	95% Confidence interval
Variable	P-value	OR	Lower	Upper
Age
60-70 yo*
>70 yo	0.037	3.085	1.071	8.883
Symptoms
Mild*	0.022
Moderate	0.021	3.219	1.195	8.671
Severe	0.023	4.540	1.23	16.71
Comorbidities
None*	0.335
1 Comorbidity	0.223	1.872	0.684	5.124
>1 Comorbidity	0.202	2.359	0.631	8.812

Based on the results of multivariate analysis in Table 5, malnutrition disorders were influenced by symptom variables and comorbidities. Elderly people with more than one comorbidity had a 6.6-time greater risk of experiencing malnutrition after controlling for symptoms and age variables at a 95% confidence level, between 1.56 to 28.57.

Discussion

One-third of the post-COVID-19 population experience mental disorders; 40% of patients will experience depression, and the rest will experience symptoms such as anxiety, and delirium.¹⁰^,¹¹^,²³^,³¹^-³³ Between 43-70% of COVID-19 survivors experience psychological disorders. Several studies say this is related to the degree of disease, age, and comorbidities. However, several studies have stated that mental disorders are not related to this, especially in the elderly.⁵^,⁶^,¹⁴^,¹⁵

The older the age, the higher the risk for mental disorders will be. Based on the results of our study, it was found that as age increased, the risk of mental disorders in the elderly after COVID-19 infection increased by 2.5 times according to the results of the study in Tables 3 and 5.¹⁶

COVID-19 infection predisposes to mental disorders, which are induced by cytokine bodies and hyperinflammatory states.¹⁰^,¹¹ Therefore, it can cause disruption of the blood-brain barrier and ultimately inflammation of the nervous system. In the elderly, there is a susceptibility to inflammation.¹⁷ Hyper-inflammatory conditions affect the severity of COVID-19 disease; the severity of COVID-19 disease will increase the risk of post-infection mental disorders. In addition, comorbidity in the elderly is often multi-comorbid.¹⁷ The number of comorbidities increases the risk of mental disorders.²³^,³²^,³⁴ Table 3 shows that there is a relationship between age, the degree of disease severity, and comorbidities that increase the risk of mental disorders in the elderly after COVID-19 infection. The degree of severe illness leads to a 4.5 times higher risk of mental disorders and multi comorbidities lead to a 2.3 times higher risk of experiencing mental disorders.³⁴ Interferon-gamma related to hyperinflammatory condition increase during covid-19 infection can affect brain function. it is well-known that chronic accumulation of cytokines causes neuronal damage.²^,³

Malnutrition is a nutritional disorder that has an unfavorable impact, especially on the elderly. The incidence of malnutrition in the elderly infected with COVID-19 is higher than in the general population. The pathomechanism of malnutrition is an acute inflammatory state causing high body protein consumption, and less lean body mass in the elderly, which continues to decrease with increasing age so that elderly people often lose weight due to acute inflammation. The infection of SARS-CoV-2 in the gastrointestinal system of the elderly is greater, so elderly people who are infected with COVID-19 often experience severe gastrointestinal disorders. Other factors can also influence malnutrition: the severity of COVID-19 infection increases the risk of malnutrition as 32.3% of the elderly infected with COVID-19 will continue to be malnourished 30 days after infection. Comorbidity in the elderly is also related to the incidence of malnutrition, which is related to chronic inflammation that leads to acute exacerbations causing a hyperinflammatory state so that catabolism increases and muscle mass is used.¹⁰^,¹²^,¹⁸^,¹⁹^,³⁵^,³⁶

Based on the results of the study, it was found that older age, degree of disease severity, and comorbidities were associated with the risk of malnutrition in the elderly after COVID-19. Increasing age increased the risk of malnutrition by 2.5 times. The severity of the disease also increased the risk of malnutrition, although in this study it was shown that people with the moderate disease had the highest risk of malnutrition, which was 6.3 times higher, while people with severe degree disease had 4.4 times risk of malnutrition based on data number of participants with moderate symptoms is more than severe symptoms and patients with severe symptoms had died during hospitalization. In some studies, 32.3% of patients suffering from malnutrition during treatment still experienced malnutrition on day 30, meaning about 70% experienced an improvement in their condition. In this study, multi-comorbidities led to 6.6 times higher risk of malnutrition, more comorbidities, and increased susceptibility in the elderly as seen in Table 6.¹⁰^,¹⁹^–²²

Table 6. Malnutrition disorder multiple logistic regression model.

Variable	P-Value	OR	95% Confidence interval
Variable	P-Value	OR	Lower	Upper
Age
60-70 yo*
>70 yo	0.114	2.515	0.800	7.906
Symptoms
Mild*	0.003
Moderate	0.001	6.368	2.047	19.812
Severe	0.029	4.420	1.163	16.802
Comorbidities
None*	0.007
1 Comorbidity	0.005	5.045	1.645	15.472
>1 Comorbidity	0.010	6.685	1.56	28.57

Conclusions

Age, COVID-19 symptoms and the presence of disease comorbidities are risk factors for mental disorders and malnutrition in COVID-19 elderly survivors. The older the age, the more severe the symptoms of COVID-19; the number of comorbidities also increased the risk of mental disorders and malnutrition.

Evaluation of mental health and nutritional status in elderly COVID-19 survivors needs to be carried out regularly to avoid vulnerabilities which will negatively impact the quality of life of elderly people.

The limitations of this study are the total sampling approach. In addition, in this study some variable confounders couldn’t be strictly controlled. Variable confounders that can affect the results include mental disorders that have previously been experienced or have had previous symptoms.

Data availability

Underlying data

Figshare: Risk of mental disorders and malnutrition in elderly COVID-19 survivors, https://doi.org/10.6084/m9.figshare.19588519.v2.³⁷

This project contains the following underlying data:

- response from 100 respondents in Covid-19 Survivor.csv

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

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30. Guigoz Y, Vellas B: Nutritional Assessment in Older Adults: MNA® 25 years of a Screening Tool & a Reference Standard for Care and Research; What Next?. J. Nutr. Heal. Aging. 2021; 25(4): 528–583. PubMed Abstract | Publisher Full Text
31. Menges D, Ballouz T, Anagnostopoulos A, et al.: Burden of post-COVID-19 syndrome and implications for healthcare service planning: A population-based cohort study. PLoS One. 2021; 16(7 July): e0254523. PubMed Abstract | Publisher Full Text
32. Taquet M, Geddes JR, Husain M, et al.: 6-month neurological and psychiatric outcomes in 236 379 survivors of COVID-19: a retrospective cohort study using electronic health records. Lancet Psychiatry. 2021; 8(5): 416–427. PubMed Abstract | Publisher Full Text
33. Damayanthi HDWT, Prabani KIP: Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID- 19. The COVID-19 resource centre is hosted on Elsevier Connect, the company’ s public news and information.2020; (January).
34. Grolli RE, Eduarda M, Mingoti D, et al.: Impact of COVID-19 in the Mental Health in Elderly: Psychological and Biological Updates. Published online 2021.
35. Liu K, Chen Y, Lin R, et al.: Clinical features of COVID-19 in elderly patients: A comparison with young and middle-aged patients. J. Infect. 2020; 80(6): e14–e18. PubMed Abstract | Publisher Full Text
36. Quilliot D, Gérard M, Bonsack O, et al.: Impact of severe SARS-CoV-2 infection on nutritional status and subjective functional loss in a prospective cohort of COVID-19.
37. Theresa RM, Dewiastuti M, Ningsih SR, et al.: RISK OF MENTAL DISORDERS AND MALNUTRITION IN ELDERLY COVID-19 SURVIVOR. figshare. Dataset.2022. Publisher Full Text

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Version 2

VERSION 2 PUBLISHED 11 Jan 2023

Author details Author details

Ria Maria Theresa
Roles: Conceptualization, Supervision, Writing – Original Draft Preparation

Marlina Dewiastuti
Roles: Investigation, Project Administration, Validation, Writing – Review & Editing

Sri Rahayu Ningsih
Roles: Data Curation, Formal Analysis, Methodology, Project Administration, Software

Lisa Safira
Roles: Funding Acquisition, Resources, Validation, Visualization, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

This study was supported by a research grant from the Research and Community Service Institute UPN Veteran Jakarta.
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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https://doi.org/10.12688/f1000research.121696.2

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https://doi.org/10.12688/f1000research.121696.1

© 2023 Theresa RM 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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Theresa RM, Dewiastuti M, Ningsih SR and Safira L. Risk of mental disorders and malnutrition in elderly COVID-19 survivors: An observational study [version 2; peer review: 1 approved, 1 approved with reservations, 1 not approved]. F1000Research 2023, 12:42 (https://doi.org/10.12688/f1000research.121696.2)

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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

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Reviewer Report 10 Jun 2024

Yan-Jiang Wang, Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, China

Yu-Hui Liu, Department of Neurology and Clinical Center for Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, Chongqing, China

Not Approved

https://doi.org/10.5256/f1000research.155800.r279772

This study aimed to examine the risk of mental disorders and malnutrition among older individuals who survived COVID-19. The findings revealed that older age, severe COVID-19 infection, and the presence of multiple comorbidities were linked to adverse mental health outcomes and malnutrition following the infection. The study was conducted in a meticulous manner; however, a few concerns need to be addressed.
-Introduction

The authors should provide a clear explanation for why they chose to investigate both mental health disorders and malnutrition in a single study, as these two outcomes may not appear to be directly related.
The authors claimed that “There is no research was conducted on the factors that influence mental disorders and malnutrition in elderly COVID-19 survivors”. This should be approached with caution because there is a significant amount of research on this topic.

Tosato M, et.al., 2023 (Ref 1)
Griffiths J et.al., 2023 (Ref 2)
Boaz M. et.al., 2023 (Ref 3)
Feng X et.al., 2022 (Ref 4)

- Methods

It is important to acknowledge the potential bias in participant recruitment. Individuals who have experienced mental health complaints and malnutrition may be more inclined to participate, whereas those in good health may have less interest in participation.
Age was considered as a dichotomous variable in the regression models. However, it is important for the authors to provide an explanation for their selection of 70 years as the threshold to differentiate between the older and younger age groups.
Using the SRQ-20 questionnaire for assessment was too simplistic and did not provide a clear indication of the specific type of mental health disorders among older COVID-19 survivors. This limitation should be acknowledged.

- Results
The authors observed that multicomorbidities were linked with both mental health disorders and malnutrition. However, it's crucial to identify the primary contributing comorbidity to these health outcomes. I would recommend the authors to analyze the association between each comorbidity and the outcomes separately
- Discussion

In a cross-sectional investigation, establishing causative associations between age, disease severity, comorbidities, and the health consequences of COVID-19 is challenging. This limitation should be acknowledged, and further longitudinal investigations are necessary to address this gap.
The small sample size should be acknowledged as a limitation of the 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?

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

References

1. Tosato M, Calvani R, Ciciarello F, Galluzzo V, et al.: Malnutrition in COVID-19 survivors: prevalence and risk factors.Aging Clin Exp Res. 2023; 35 (10): 2257-2265 PubMed Abstract | Publisher Full Text
2. Griffiths J, Seesen M, Sirikul W, Siviroj P: Malnutrition, Depression, Poor Sleep Quality, and Difficulty Falling Asleep at Night Are Associated with a Higher Risk of Cognitive Frailty in Older Adults during the COVID-19 Restrictions.Nutrients. 2023; 15 (13). PubMed Abstract | Publisher Full Text
3. Boaz M, Kaufman-Shriqui V: Systematic Review and Meta-Analysis: Malnutrition and In-Hospital Death in Adults Hospitalized with COVID-19.Nutrients. 2023; 15 (5). PubMed Abstract | Publisher Full Text
4. Feng X, Liu Z, He X, Wang X, et al.: Risk of Malnutrition in Hospitalized COVID-19 Patients: A Systematic Review and Meta-Analysis.Nutrients. 2022; 14 (24). PubMed Abstract | Publisher Full Text

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Neurology; Dementia; Covid-19

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 17 Oct 2023

Mirasari Putri, Department of Biochemistry, Nutrition, and Biomolecular, Faculty of Medicine, Universitas Islam Bandung, Bandung, Indonesia

Approved

https://doi.org/10.5256/f1000research.155800.r211293

I think ... Continue reading

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Reviewer Report 31 Jul 2023

Tusawar Iftikhar Ahmad, The Islamia University of Bahawalpur Pakistan, Bahawalpur, Punjab, Pakistan

Amina Alamgir, Department of Economics, The Islamia University of Bahawalpur Pakistan, Bahawalpur, Punjab, Pakistan

Approved with Reservations

https://doi.org/10.5256/f1000research.133591.r186579

Feedback for improving the quality of the manuscript:

In the abstract, include statistics on the incidence and case fatality rate (CFR) of COVID-19 in the elderly within the context of Indonesia.

Feedback for improving the quality of the manuscript:

In the abstract, include statistics on the incidence and case fatality rate (CFR) of COVID-19 in the elderly within the context of Indonesia.
In the abstract, present the findings related to Odds Ratios in the following format: for example, provide the numeric value of the OR (p-value = 0.00; CI = 1.0-8.8).
In Figure 1, the visualization of the sequence depicting the risk of mental disorders and malnutrition in elderly COVID-19 survivors is unclear. Please clarify the directions of the arrows and sequence of the text boxes to provide a more coherent understanding.
Please provide a statistical justification for the adequacy of the sample size (n = 100) and its implications for the generalizability of the findings.
The current study lacks a clear presentation of its theoretical underpinnings. Please include a section to address this aspect.
The research gap is not specifically identified. Consider highlighting the specific gap that this study aims to address.
Provide a brief description of the study area (Depok, Indonesia), including cartographic presentation, demography, socioeconomic dynamics, etc.
The paper mentions the use of the SRQ-20 and the MNA questionnaires to assess mental disorder and malnutrition, respectively. Please add a brief description of the structures of both questionnaires in the paper.
Please specify the sampling technique employed to collect the data.
Include a description, along with a mathematical expression, explaining the relevance of using multiple logistic regression as the estimation technique for this research.

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

Yes
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?

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

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

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Health Economics

We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however we have significant reservations, as outlined above.

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Reviewer Report 02 May 2023

Mirasari Putri, Department of Biochemistry, Nutrition, and Biomolecular, Faculty of Medicine, Universitas Islam Bandung, Bandung, Indonesia

Approved with Reservations

https://doi.org/10.5256/f1000research.133591.r164467

Abstract

Method: Write the time of this research conducted
Write down the significant comorbidities that play a role in mental disorders and malnutrition based on the findings in this study.

Abstract

Method: Write the time of this research conducted
Write down the significant comorbidities that play a role in mental disorders and malnutrition based on the findings in this study.

Introduction:

It should provide evidence gaps to highlight unanswered questions in this study and how this study will contribute to filling the gap.
Highlight the originality and novelty of this study.

Method:

Was it true that there were 100 elderly people affected by Covid in May-July 2021 throughout Depok? Explain further what is meant by the total sample in this study.
Why was malnutrition in the elderly before being diagnosed with Covid not excluded in this study? Malnutrition is one risk factor in the elderly with or without Covid. How can authors ensure that the patients' malnutrition is because of Covid, not because they have had it before?
Paragraph 2, line 2 adds a reference for mental disorder categorization.
Paragraph 2, line 4 adds the reference for Covid severity.
Write the number of ethical approval.
Paragraph 1, line 2 add the reference for mental disorder categorized and explain the method briefly
Explain whether the patients who are used as subjects were patients who experienced Covid for the first time, have been exposed to it more than once, or were all taken as subjects.

Result:

Explain further about the comorbidities presented in tables 3 and 4. In more than 1 comorbidity, which comorbidities are the high risk factors for mental disorder and malnutrition in your research?
Paragraph 10: which table represents multivariate analysis? Please write it.
In the table note, write the statistical method used and the total number of respondents.

Discussion:

Paragraph 3: Explain in more detail the mechanism of hyperinflammation and cytokines in infections associated with the nervous system, which are at risk of causing mental disorders
Paragraph 3: Explain in more detail about the multiple comorbidities that can increase the risk of mental disorders concerning the comorbidities found in your research and also the mechanism
Paragraph 4: the authors explained that gastrointestinal factors are one of the causes of malnutrition in the elderly with Covid. Did the authors investigate these gastrointestinal factors? If yes, the results can be written in the results section. Because this is something that can confirm the mechanism of malnutrition in the elderly with Covid
Paragraph 5: Discuss why the risk of malnutrition in Covid patients with moderate symptoms was higher than those with severe ones.

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

Yes
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?

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

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

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Nutrition-Immunology-Biomolecular

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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Author Response 02 Oct 2023

Ria Maria Theresa, Psychiatry, Universitas Pembangunan Nasional Veteran Jakarta, Jakarta, 12310, Indonesia

02 Oct 2023

Author Response

Abstract : There is no cachexia and no cancer

Introduction:
1. Malnutrition in elderly will worsen health status in any situation.
2. No studies have assesed malnutrition in elderly covid ... Continue reading Abstract : There is no cachexia and no cancer

Introduction:
1. Malnutrition in elderly will worsen health status in any situation.
2. No studies have assesed malnutrition in elderly covid patients.

Method:
1. Pasien was diagnosed covid-19 by hospital data from Depok hospital, using total sampling of hospital data.
2. The malnourished patient was excluded in this study.
We are sure that from this study, the sample was not diagnosed malnourished based on hospital data (BMI and by mini nutritional assessment from hospital data when patients were hospitalized).

3.Paragraph 2, line 2 adds a reference for mental disorder categorization:
Stein AMB: Coronavirus disease 2019 (COVID-19): Psychiatric illness. Wolters Kluwer. 2020; 2019: 1–31.

4.Paragraph 2, line 4 adds the reference for Covid severity:
Azwar MK, Setiati S, Rizka A, et al.: Clinical Profile of Elderly Patients with COVID-19 hospitalised in Indonesia’s National General Hospital. Acta Med. Indones. 2020; 52(3): 199–205

5.Write the number of ethical approval: 455/X/2021/KEPK

6. The sudden changes situation during the covid 19 had an impact on difficulty adapting and this situation had impact on mental health of elderly.
Reference for mental health disorder categorized are DSM V and ICD XI

7. in this study, inclusion criteria were the population og people over 60 years old and diagnosed for the first time exposure by covid 19.

Result:
1. Comorbidity in this study was hypertension, diabetes mellitus, and cardiovascular disease (coronary arterial disease or cerebrovascular disease). We dont study comordities that lead to mental disorders.
2. Table 5 and 6

Discussion:
1. COVID-19 infection predisposes to mental disorders induced by cytokine bodies and hyperinflammatory states. Therefore, it can cause disruption of the blood-brain barrier and ultimately inflammation of the nervous system. In the elderly, there is a susceptibility to inflammation. Hyper-inflammatory conditions affect the severity of COVID-19; the severity of COVID-19 will increase the risk of post-infection mental disorders. In addition, comorbidity in the elderly is often multi-comorbid. The number of comorbidities increases the risk of mental disorders. Table 3 shows that there is a relationship between age, the degree of disease severity, and comorbidities that increase the risk of mental disorders in the elderly after COVID-19 infection. The degree of severe illness leads to a 4.5 times higher risk of mental disorders and multi-comorbidities lead to a 2.3 times higher risk of experiencing mental disorders.

Interferon-gamma related to hyperinflammatory condition increase during covid-19 infection can affect brain function. it is well-known that chronic accumulation of cytokines causes neuronal damage

2. Other factors like glucose level, hypertension, and other comorbidities increase the severity of the disease. Immune signatures correlated with diseases trajectory to sequalae

3. In this study, there is no evaluation on gastrointestinal symptoms during hospitalization

4. Decrease appetite, digestive disturbances, increased metabolism, longer duration of illness in moderate patients.
Abstract : There is no cachexia and no cancer

Introduction:
1. Malnutrition in elderly will worsen health status in any situation.
2. No studies have assesed malnutrition in elderly covid patients.

Method:
1. Pasien was diagnosed covid-19 by hospital data from Depok hospital, using total sampling of hospital data.
2. The malnourished patient was excluded in this study.
We are sure that from this study, the sample was not diagnosed malnourished based on hospital data (BMI and by mini nutritional assessment from hospital data when patients were hospitalized).

3.Paragraph 2, line 2 adds a reference for mental disorder categorization:
Stein AMB: Coronavirus disease 2019 (COVID-19): Psychiatric illness. Wolters Kluwer. 2020; 2019: 1–31.

4.Paragraph 2, line 4 adds the reference for Covid severity:
Azwar MK, Setiati S, Rizka A, et al.: Clinical Profile of Elderly Patients with COVID-19 hospitalised in Indonesia’s National General Hospital. Acta Med. Indones. 2020; 52(3): 199–205

5.Write the number of ethical approval: 455/X/2021/KEPK

6. The sudden changes situation during the covid 19 had an impact on difficulty adapting and this situation had impact on mental health of elderly.
Reference for mental health disorder categorized are DSM V and ICD XI

7. in this study, inclusion criteria were the population og people over 60 years old and diagnosed for the first time exposure by covid 19.

Result:
1. Comorbidity in this study was hypertension, diabetes mellitus, and cardiovascular disease (coronary arterial disease or cerebrovascular disease). We dont study comordities that lead to mental disorders.
2. Table 5 and 6

Discussion:
1. COVID-19 infection predisposes to mental disorders induced by cytokine bodies and hyperinflammatory states. Therefore, it can cause disruption of the blood-brain barrier and ultimately inflammation of the nervous system. In the elderly, there is a susceptibility to inflammation. Hyper-inflammatory conditions affect the severity of COVID-19; the severity of COVID-19 will increase the risk of post-infection mental disorders. In addition, comorbidity in the elderly is often multi-comorbid. The number of comorbidities increases the risk of mental disorders. Table 3 shows that there is a relationship between age, the degree of disease severity, and comorbidities that increase the risk of mental disorders in the elderly after COVID-19 infection. The degree of severe illness leads to a 4.5 times higher risk of mental disorders and multi-comorbidities lead to a 2.3 times higher risk of experiencing mental disorders.

Interferon-gamma related to hyperinflammatory condition increase during covid-19 infection can affect brain function. it is well-known that chronic accumulation of cytokines causes neuronal damage

2. Other factors like glucose level, hypertension, and other comorbidities increase the severity of the disease. Immune signatures correlated with diseases trajectory to sequalae

3. In this study, there is no evaluation on gastrointestinal symptoms during hospitalization

4. Decrease appetite, digestive disturbances, increased metabolism, longer duration of illness in moderate patients.
Competing Interests: No competing interests were disclosed. Close
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COMMENTS ON THIS REPORT

Author Response 02 Oct 2023

Ria Maria Theresa, Psychiatry, Universitas Pembangunan Nasional Veteran Jakarta, Jakarta, 12310, Indonesia

02 Oct 2023

Author Response

Abstract : There is no cachexia and no cancer

Introduction:
1. Malnutrition in elderly will worsen health status in any situation.
2. No studies have assesed malnutrition in elderly covid ... Continue reading Abstract : There is no cachexia and no cancer

Introduction:
1. Malnutrition in elderly will worsen health status in any situation.
2. No studies have assesed malnutrition in elderly covid patients.

Method:
1. Pasien was diagnosed covid-19 by hospital data from Depok hospital, using total sampling of hospital data.
2. The malnourished patient was excluded in this study.
We are sure that from this study, the sample was not diagnosed malnourished based on hospital data (BMI and by mini nutritional assessment from hospital data when patients were hospitalized).

3.Paragraph 2, line 2 adds a reference for mental disorder categorization:
Stein AMB: Coronavirus disease 2019 (COVID-19): Psychiatric illness. Wolters Kluwer. 2020; 2019: 1–31.

4.Paragraph 2, line 4 adds the reference for Covid severity:
Azwar MK, Setiati S, Rizka A, et al.: Clinical Profile of Elderly Patients with COVID-19 hospitalised in Indonesia’s National General Hospital. Acta Med. Indones. 2020; 52(3): 199–205

5.Write the number of ethical approval: 455/X/2021/KEPK

6. The sudden changes situation during the covid 19 had an impact on difficulty adapting and this situation had impact on mental health of elderly.
Reference for mental health disorder categorized are DSM V and ICD XI

7. in this study, inclusion criteria were the population og people over 60 years old and diagnosed for the first time exposure by covid 19.

Result:
1. Comorbidity in this study was hypertension, diabetes mellitus, and cardiovascular disease (coronary arterial disease or cerebrovascular disease). We dont study comordities that lead to mental disorders.
2. Table 5 and 6

Discussion:
1. COVID-19 infection predisposes to mental disorders induced by cytokine bodies and hyperinflammatory states. Therefore, it can cause disruption of the blood-brain barrier and ultimately inflammation of the nervous system. In the elderly, there is a susceptibility to inflammation. Hyper-inflammatory conditions affect the severity of COVID-19; the severity of COVID-19 will increase the risk of post-infection mental disorders. In addition, comorbidity in the elderly is often multi-comorbid. The number of comorbidities increases the risk of mental disorders. Table 3 shows that there is a relationship between age, the degree of disease severity, and comorbidities that increase the risk of mental disorders in the elderly after COVID-19 infection. The degree of severe illness leads to a 4.5 times higher risk of mental disorders and multi-comorbidities lead to a 2.3 times higher risk of experiencing mental disorders.

Interferon-gamma related to hyperinflammatory condition increase during covid-19 infection can affect brain function. it is well-known that chronic accumulation of cytokines causes neuronal damage

2. Other factors like glucose level, hypertension, and other comorbidities increase the severity of the disease. Immune signatures correlated with diseases trajectory to sequalae

3. In this study, there is no evaluation on gastrointestinal symptoms during hospitalization

4. Decrease appetite, digestive disturbances, increased metabolism, longer duration of illness in moderate patients.
Abstract : There is no cachexia and no cancer

Introduction:
1. Malnutrition in elderly will worsen health status in any situation.
2. No studies have assesed malnutrition in elderly covid patients.

Method:
1. Pasien was diagnosed covid-19 by hospital data from Depok hospital, using total sampling of hospital data.
2. The malnourished patient was excluded in this study.
We are sure that from this study, the sample was not diagnosed malnourished based on hospital data (BMI and by mini nutritional assessment from hospital data when patients were hospitalized).

3.Paragraph 2, line 2 adds a reference for mental disorder categorization:
Stein AMB: Coronavirus disease 2019 (COVID-19): Psychiatric illness. Wolters Kluwer. 2020; 2019: 1–31.

4.Paragraph 2, line 4 adds the reference for Covid severity:
Azwar MK, Setiati S, Rizka A, et al.: Clinical Profile of Elderly Patients with COVID-19 hospitalised in Indonesia’s National General Hospital. Acta Med. Indones. 2020; 52(3): 199–205

5.Write the number of ethical approval: 455/X/2021/KEPK

6. The sudden changes situation during the covid 19 had an impact on difficulty adapting and this situation had impact on mental health of elderly.
Reference for mental health disorder categorized are DSM V and ICD XI

7. in this study, inclusion criteria were the population og people over 60 years old and diagnosed for the first time exposure by covid 19.

Result:
1. Comorbidity in this study was hypertension, diabetes mellitus, and cardiovascular disease (coronary arterial disease or cerebrovascular disease). We dont study comordities that lead to mental disorders.
2. Table 5 and 6

Discussion:
1. COVID-19 infection predisposes to mental disorders induced by cytokine bodies and hyperinflammatory states. Therefore, it can cause disruption of the blood-brain barrier and ultimately inflammation of the nervous system. In the elderly, there is a susceptibility to inflammation. Hyper-inflammatory conditions affect the severity of COVID-19; the severity of COVID-19 will increase the risk of post-infection mental disorders. In addition, comorbidity in the elderly is often multi-comorbid. The number of comorbidities increases the risk of mental disorders. Table 3 shows that there is a relationship between age, the degree of disease severity, and comorbidities that increase the risk of mental disorders in the elderly after COVID-19 infection. The degree of severe illness leads to a 4.5 times higher risk of mental disorders and multi-comorbidities lead to a 2.3 times higher risk of experiencing mental disorders.

Interferon-gamma related to hyperinflammatory condition increase during covid-19 infection can affect brain function. it is well-known that chronic accumulation of cytokines causes neuronal damage

2. Other factors like glucose level, hypertension, and other comorbidities increase the severity of the disease. Immune signatures correlated with diseases trajectory to sequalae

3. In this study, there is no evaluation on gastrointestinal symptoms during hospitalization

4. Decrease appetite, digestive disturbances, increased metabolism, longer duration of illness in moderate patients.
Competing Interests: No competing interests were disclosed. Close
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Version 2 (revision) 02 Oct 23	read		read
Version 1 11 Jan 23	read	read

Mirasari Putri, Universitas Islam Bandung, Bandung, Indonesia
Tusawar Iftikhar Ahmad, The Islamia University of Bahawalpur Pakistan, Bahawalpur, Pakistan

Amina Alamgir, The Islamia University of Bahawalpur Pakistan, Bahawalpur, Pakistan
Yan-Jiang Wang, Third Military Medical University, Chongqing, China

Yu-Hui Liu, Daping Hospital, Third Military Medical University, Chongqing, China

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10 Jun 2024 | for Version 2

Yan-Jiang Wang, Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, China

Yu-Hui Liu, Department of Neurology and Clinical Center for Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, Chongqing, China

2 Views Cite this report Responses(0)

Not Approved

The authors should provide a clear explanation for why they chose to investigate both mental health disorders and malnutrition in a single study, as these two outcomes may not appear to be directly related.
The authors claimed that “There is no research was conducted on the factors that influence mental disorders and malnutrition in elderly COVID-19 survivors”. This should be approached with caution because there is a significant amount of research on this topic.

Tosato M, et.al., 2023 (Ref 1)
Griffiths J et.al., 2023 (Ref 2)
Boaz M. et.al., 2023 (Ref 3)
Feng X et.al., 2022 (Ref 4)

- Methods

It is important to acknowledge the potential bias in participant recruitment. Individuals who have experienced mental health complaints and malnutrition may be more inclined to participate, whereas those in good health may have less interest in participation.
Age was considered as a dichotomous variable in the regression models. However, it is important for the authors to provide an explanation for their selection of 70 years as the threshold to differentiate between the older and younger age groups.
Using the SRQ-20 questionnaire for assessment was too simplistic and did not provide a clear indication of the specific type of mental health disorders among older COVID-19 survivors. This limitation should be acknowledged.

In a cross-sectional investigation, establishing causative associations between age, disease severity, comorbidities, and the health consequences of COVID-19 is challenging. This limitation should be acknowledged, and further longitudinal investigations are necessary to address this gap.
The small sample size should be acknowledged as a limitation of the 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?

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

References

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Neurology; Dementia; Covid-19

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17 Oct 2023 | for Version 2

Mirasari Putri, Department of Biochemistry, Nutrition, and Biomolecular, Faculty of Medicine, Universitas Islam Bandung, Bandung, Indonesia

8 Views Cite this report Responses(0)

Approved

I think revisions are appropriate.

Competing Interests

No competing interests were disclosed.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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31 Jul 2023 | for Version 1

Tusawar Iftikhar Ahmad, The Islamia University of Bahawalpur Pakistan, Bahawalpur, Punjab, Pakistan

Amina Alamgir, Department of Economics, The Islamia University of Bahawalpur Pakistan, Bahawalpur, Punjab, Pakistan

14 Views Cite this report Responses(0)

Approved With Reservations

Feedback for improving the quality of the manuscript:

In the abstract, include statistics on the incidence and case fatality rate (CFR) of COVID-19 in the elderly within the context of Indonesia.
In the abstract, present the findings related to Odds Ratios in the following format: for example, provide the numeric value of the OR (p-value = 0.00; CI = 1.0-8.8).
In Figure 1, the visualization of the sequence depicting the risk of mental disorders and malnutrition in elderly COVID-19 survivors is unclear. Please clarify the directions of the arrows and sequence of the text boxes to provide a more coherent understanding.
Please provide a statistical justification for the adequacy of the sample size (n = 100) and its implications for the generalizability of the findings.
The current study lacks a clear presentation of its theoretical underpinnings. Please include a section to address this aspect.
The research gap is not specifically identified. Consider highlighting the specific gap that this study aims to address.
Provide a brief description of the study area (Depok, Indonesia), including cartographic presentation, demography, socioeconomic dynamics, etc.
The paper mentions the use of the SRQ-20 and the MNA questionnaires to assess mental disorder and malnutrition, respectively. Please add a brief description of the structures of both questionnaires in the paper.
Please specify the sampling technique employed to collect the data.
Include a description, along with a mathematical expression, explaining the relevance of using multiple logistic regression as the estimation technique for this research.

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

Yes
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?

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

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

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Health Economics

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Reviewer Report

27 Views

02 May 2023 | for Version 1

Mirasari Putri, Department of Biochemistry, Nutrition, and Biomolecular, Faculty of Medicine, Universitas Islam Bandung, Bandung, Indonesia

27 Views Cite this report Responses(1)

Approved With Reservations

Abstract

Method: Write the time of this research conducted
Write down the significant comorbidities that play a role in mental disorders and malnutrition based on the findings in this study.

Introduction:

It should provide evidence gaps to highlight unanswered questions in this study and how this study will contribute to filling the gap.
Highlight the originality and novelty of this study.

Method:

Was it true that there were 100 elderly people affected by Covid in May-July 2021 throughout Depok? Explain further what is meant by the total sample in this study.
Why was malnutrition in the elderly before being diagnosed with Covid not excluded in this study? Malnutrition is one risk factor in the elderly with or without Covid. How can authors ensure that the patients' malnutrition is because of Covid, not because they have had it before?
Paragraph 2, line 2 adds a reference for mental disorder categorization.
Paragraph 2, line 4 adds the reference for Covid severity.
Write the number of ethical approval.
Paragraph 1, line 2 add the reference for mental disorder categorized and explain the method briefly
Explain whether the patients who are used as subjects were patients who experienced Covid for the first time, have been exposed to it more than once, or were all taken as subjects.

Result:

Explain further about the comorbidities presented in tables 3 and 4. In more than 1 comorbidity, which comorbidities are the high risk factors for mental disorder and malnutrition in your research?
Paragraph 10: which table represents multivariate analysis? Please write it.
In the table note, write the statistical method used and the total number of respondents.

Discussion:

Paragraph 3: Explain in more detail the mechanism of hyperinflammation and cytokines in infections associated with the nervous system, which are at risk of causing mental disorders
Paragraph 3: Explain in more detail about the multiple comorbidities that can increase the risk of mental disorders concerning the comorbidities found in your research and also the mechanism
Paragraph 4: the authors explained that gastrointestinal factors are one of the causes of malnutrition in the elderly with Covid. Did the authors investigate these gastrointestinal factors? If yes, the results can be written in the results section. Because this is something that can confirm the mechanism of malnutrition in the elderly with Covid
Paragraph 5: Discuss why the risk of malnutrition in Covid patients with moderate symptoms was higher than those with severe ones.

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

Yes
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?

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

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

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Nutrition-Immunology-Biomolecular

Respond to this report

Responses (1)

Author Response

02 Oct 2023

Ria Maria Theresa, Psychiatry, Universitas Pembangunan Nasional Veteran Jakarta, Jakarta, 12310, Indonesia

Abstract : There is no cachexia and no cancer

Introduction:
1. Malnutrition in elderly will worsen health status in any situation.
2. No studies have assesed malnutrition in elderly covid patients.

Method:
1. Pasien was diagnosed covid-19 by hospital data from Depok hospital, using total sampling of hospital data.
2. The malnourished patient was excluded in this study.
We are sure that from this study, the sample was not diagnosed malnourished based on hospital data (BMI and by mini nutritional assessment from hospital data when patients were hospitalized).

3.Paragraph 2, line 2 adds a reference for mental disorder categorization:
Stein AMB: Coronavirus disease 2019 (COVID-19): Psychiatric illness. Wolters Kluwer. 2020; 2019: 1–31.

4.Paragraph 2, line 4 adds the reference for Covid severity:
Azwar MK, Setiati S, Rizka A, et al.: Clinical Profile of Elderly Patients with COVID-19 hospitalised in Indonesia’s National General Hospital. Acta Med. Indones. 2020; 52(3): 199–205

5.Write the number of ethical approval: 455/X/2021/KEPK

6. The sudden changes situation during the covid 19 had an impact on difficulty adapting and this situation had impact on mental health of elderly.
Reference for mental health disorder categorized are DSM V and ICD XI

7. in this study, inclusion criteria were the population og people over 60 years old and diagnosed for the first time exposure by covid 19.

Result:
1. Comorbidity in this study was hypertension, diabetes mellitus, and cardiovascular disease (coronary arterial disease or cerebrovascular disease). We dont study comordities that lead to mental disorders.
2. Table 5 and 6

Discussion:
1. COVID-19 infection predisposes to mental disorders induced by cytokine bodies and hyperinflammatory states. Therefore, it can cause disruption of the blood-brain barrier and ultimately inflammation of the nervous system. In the elderly, there is a susceptibility to inflammation. Hyper-inflammatory conditions affect the severity of COVID-19; the severity of COVID-19 will increase the risk of post-infection mental disorders. In addition, comorbidity in the elderly is often multi-comorbid. The number of comorbidities increases the risk of mental disorders. Table 3 shows that there is a relationship between age, the degree of disease severity, and comorbidities that increase the risk of mental disorders in the elderly after COVID-19 infection. The degree of severe illness leads to a 4.5 times higher risk of mental disorders and multi-comorbidities lead to a 2.3 times higher risk of experiencing mental disorders.

Interferon-gamma related to hyperinflammatory condition increase during covid-19 infection can affect brain function. it is well-known that chronic accumulation of cytokines causes neuronal damage

2. Other factors like glucose level, hypertension, and other comorbidities increase the severity of the disease. Immune signatures correlated with diseases trajectory to sequalae

3. In this study, there is no evaluation on gastrointestinal symptoms during hospitalization

4. Decrease appetite, digestive disturbances, increased metabolism, longer duration of illness in moderate patients.

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Competing Interests

No competing interests were disclosed.

Alongside their report, reviewers assign a status to the article:

Approved - the 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 approved - fundamental flaws in the paper seriously undermine the findings and conclusions

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Risk of mental disorders and malnutrition in elderly COVID-19 survivors: An observational study

Abstract

Keywords

Revised Amendments from Version 1

Introduction

Figure 1. Risk of mental disorders and malnutrition in elderly COVID-19 survivors.

Methods

Ethical considerations

Research methods

Results

Figure 2. Participant inclusion chart.

Table 1. Demographic description of respondents by mental disorder status.

Table 2. Demographic description of respondents based on malnutrition disorder status.

Table 3. Relationship variables age, symptoms, and comorbidities with mental disorders.

Table 4. Relationships between variables of age, symptoms, and comorbidities with malnutrition disorder.

Table 5. Mental disorder multiple logistic regression model.

Discussion

Table 6. Malnutrition disorder multiple logistic regression model.

Conclusions

Data availability

Underlying data

References

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