Biopsychosocial factors associated with depression in the elderly: A systematic literature review

Yanti Harjono Hadiwiardjo; Rita Damayanti

doi:10.12688/f1000research.121710.1

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Systematic Review

Biopsychosocial factors associated with depression in the elderly: A systematic literature review

[version 1; peer review: 2 approved with reservations]

Yanti Harjono Hadiwiardjo ^1,2, Rita Damayanti²

PUBLISHED 20 Sep 2022

Author details Author details

¹ Faculty of Public Health, University of Indonesia, Depok, 10430, Indonesia
² Medical Faculty, University Pembangunan Nasional Veteran Jakarta, Jakarta, 12450, Indonesia

Yanti Harjono Hadiwiardjo
Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Writing – Original Draft Preparation

Rita Damayanti
Roles: Validation, Writing – Original Draft Preparation, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Research Synergy Foundation gateway.

This article is included in the Sociology of Health gateway.

Abstract

Background: One of the most common mental illnesses worldwide and that has significant negative effects on well-being and physical health, is depression. Many factors that affect the occurrence of depression are biopsychosocial. Elderly people have high risk factors for depression. This study aims to review and find a gap in current evidence of biopsychosocial factors affecting depression in the elderly.
Methods: We conducted an advanced search on PubMed database between October and November 2021. We screened the bibliographies of the articles from the database search using a set of inclusion criteria: studies with quantitative design; elderly population sample; exploration of at least one biopsychosocial factor; depression as the outcome or dependent variable; written in English; and published between 2011 and 2021.
Results: We found 54 studies that met the inclusion criteria. Of these, five papers discussed biopsychosocial factors, 18 discussed biological and psychological/social factors, five discussed psychosocial factors, and the rest of the studies discussed one component of biopsychosocial factors. Biological factors influencing elderly depression include being female, having health problems or low health status, older age, genetics, brain structure, and biomarkers, taking certain drugs, and lack of or inability to carry out daily activities. Psychosocial factors include lack of social support, low education level, financial problems, single/unmarried, lack of contact with family/friends, living alone, low self-perceived health, stressful life events, loneliness, and losing hobbies. From the literature search, it was also found that there are biopsychosocial factors that have not been studied and are expected to be able to make references for future research. From this literature review, we found gaps in the availability of evidence about biopsychosocial factors that require further research.
Conclusions: Knowing the biopsychosocial factors that affect them can help to prevent depression in the elderly.

Keywords

elderly, depression, biopsychosocial, systematic review

Corresponding author: Yanti Harjono Hadiwiardjo

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2022 Harjono Hadiwiardjo Y and Damayanti R. 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: Harjono Hadiwiardjo Y and Damayanti R. Biopsychosocial factors associated with depression in the elderly: A systematic literature review [version 1; peer review: 2 approved with reservations]. F1000Research 2022, 11:1068 (https://doi.org/10.12688/f1000research.121710.1) First published: 20 Sep 2022, 11:1068 (https://doi.org/10.12688/f1000research.121710.1) Latest published: 14 Feb 2024, 11:1068 (https://doi.org/10.12688/f1000research.121710.2)

Introduction

Many developing countries are experiencing rapid growth in their older populations (Isdijoso et al., 2020). The elderly are predicted to become 25% of the global population, or 74 million people by 2050 (Isdijoso et al., 2020). In Indonesia, citizens 60 years old or older have reached about 25.7 million people (Isdijoso et al., 2020). The older population in the UK is projected to grow, with people aged 65 and over making up 24% of the population by 2043 (17.4 million people) (Lewis, 2021). The proportion of the population aged 75 and over is projected to rise from 8% in 2018 to 13% in 2043, while the proportion aged 85 and over is projected to rise from 2% to 4% (Lewis, 2021). The elderly can have specific physical and mental health issues, including decreased mobility and increased frailty, with some of them losing their independence due to such issues. In the USA, 20% of adults aged 55 and over suffered from a mental health disorder at the beginning of the millennium (World Federation for Mental Health, 2013).

In older people, mental health problems can affect their ability to carry out the basic activities of daily living, reducing their independence, autonomy, and quality of life. A common mental health problem that occurs in older people is depression (Carayanni, Stylianopoulou, Koulierakis, Babatsikou, & Koutis, 2012). Depression is related to distress and suffering and can cause impairment in mental, physical, and social functioning (World Federation for Mental Health, 2013).

Depression is one of the most common mental illnesses worldwide, with serious consequences for one’s well-being and physical health (Thipprakmas, 2021). The elderly may be particularly impacted by depression due to high levels of risk factors including illnesses, social isolation, and lack of emotional support. Depression is considered as a clinical syndrome. Low mood, anhedonia, and decreased energy levels are the three basic symptoms of depression, according to the International Classification of Diseases (ICD) diagnostic classification systems (Pocklington, 2017; Thipprakmas, 2021).

Other clinical findings which were listed include loss of confidence, impaired concentration, disturbances in sleep, suicidal ideation, and changes in appetite. If the above symptoms are present for at least in two weeks, then a diagnosis of depression can be established (Pocklington, 2017).

Major depression presents with all three core symptoms according to ICD criteria, and at least five other symptoms also present (Pocklington, 2017).

Depression consists of two types: early-onset and late-onset depression. In individuals over the age of 65, there is a new diagnosis for depression, namely late-onset depression in which more than half of cases of depression in older adults are newly emerged i.e., the person has never experienced depression. Late-type depression is related to structural changes in the brain, cognitive deficits, and vascular risk factors (Pocklington, 2017).

There are two principal points of view commonly used to explain depression, the bio-medical perspective, and the psychosocial perspective. These perspectives oftentimes conflict with each other. The biomedical perspective asserts that disturbances in the functioning of the brain manifest as psychopathological symptoms, whereas the psychosocial perspective maintains that mental issues are caused by disruptive life experiences (Garcia-Toro & Aguirre, 2007).

Frequently, this twofold viewpoint influences certainly the different affirmations that are made about mental problems, albeit expressly it is progressively perceived that organic and psychosocial angles are generally involved, interfacing in a complex way. Indeed, this is the explanation for why the term “biopsychosocial model” has flourished (Garcia-Toro & Aguirre, 2007).

Depression in older adults is related to cognitive, physical, and social functional impairment (Pocklington, 2017). It is also related to a variety of psychological, biological, and social factors causing it (Alexopoulos & Kelly, 2009; Blazer, 2003). It has a variety of biopsychosocial risk variables that interact to predict the onset of depressive symptoms in a single person. However, it is unclear how much each risk factor contributes to the onset of depressive symptoms. A greater understanding of the individual contributions of biological, psychological, and social risk factors can have a big impact on the adoption of preventive actions to lower the population's risk of depression (Diniz, 2020). Several studies have investigated several biological, psychological, and social factors associated with depression in the elderly, so this systematic review aims to review and synthesize current evidence of biopsychosocial factors affecting depression in the elderly and can also contribute to future research on factors that affect depression which can eventually contribute to the decrease in the incidence of depression in the elderly.

Objectives

This systematic review aims to examine and find gaps or current evidence regarding biopsychosocial factors that influence depression in the elderly. The review is reported in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. See Reporting guidelines (Hadiwiardjo and Damayanti, 2022c) for the completed checklist.

Methods

We conducted an advanced search on PubMed database using a set of keywords which consisted of population sample keywords (elderly OR geriatric OR late life OR older) combined with independent variable keywords (psychological factors OR social factors OR biological factors OR biopsychosocial), and the outcome (depression). After obtaining these search results, we downloaded the records into our reference manager software Mendeley and removed any duplication. From those search results, we gathered 728 records of studies. The data search on PubMed was conducted in October - November 2021. The last data search was carried out on November 18, 2021.

We applied a two-step screening process that involved two reviewers. Both reviewers worked independently, and any disagreements were resolved through discussion. First, we screened the title and abstract of the bibliography using a set of eligibility criteria. The inclusion criteria were original studies with a quantitative design, that were peer-reviewed, with elderly people (over 60 years) as the population sample, and that explored at least one biopsychosocial factor, with depression as the outcome or dependent variable. Articles also needed to be written in English and published between 2011 and 2021 to be included. Studies published as review articles, qualitative studies, brief reports, letters to the editor or editorial comments, and working papers published in a language other than English were all excluded. In the first stage of screening, we removed studies before 2011 and collected 470 records to be screened. After further screening, 99 studies are eligible for the next screening process.

Further screening of 99 eligible studies was conducted with Population, Intervention, Comparison Outcome and Study (PICOS) criteria where if not appropriate it would be excluded. We retrieved the full text of the potentially relevant studies and conducted a second screening process. The selection process can be seen in the flowchart presented in Figure 1, also available in Extended data (Hadiwiardjo and Damayanti, 2022b). The eligible studies were extracted for the design of the study, country of origin, number of samples, the instrument used to measure depression, and factors associated with depression. That information was extracted from each included study into a standardized spreadsheet and checked by two reviewers. The two reviewers worked independently and if there were any disagreements, these were resolved by discussion between the two reviewers. Any ambiguous material from an included paper was clarified after contacting the respective authors, or else only the available data was analyzed. Microsoft Excel was used to organize the identified papers. The results were described narratively and helped to identify the gaps in the literature that can be filled by future studies.

These studies included quantitative synthesis. After the two-step screening process was conducted, 54 papers were reviewed and extracted. We first described the number of articles based on the country of origin of the article, the type of research design, and the year. Next, we extracted the data based on the research design, the number of samples, the measuring instruments used to measure depression and factors related to depression. After that, the purpose of the content analysis was to identify and assess the primary research streams, reporting in an objective manner on the various domains while also addressing future research prospects and problems.

The 54 papers were then reassessed using the Joanna Briggs Institute (JBI) checklist which is a tool for critical appraisal of a paper. The risk of bias can occur if the quality of the data from the reviewed papers is mostly of low quality. To determine the quality of the data, the JBI critical appraisal tool was used (we accessed this JBI checklist here). This critical appraisal was carried out by two reviewers and if there was a disagreement, it was discussed. From the critical appraisal results it was determined that 53 papers were high quality, and one paper was low quality. The last articles obtained are all used in this systematic review.

Results and discussion

A total of 54 studies met the inclusion criteria after the full-text screening. Previously there were papers that were eventually excluded because there were discrepancies in terms of population and outcome (Pollock & Berge, 2018). The full list of the 54 studies are available in Underlying data (Hadiwiardjo and Damayanti, 2022a). The process using the PRISMA flowchart is shown in Figure 1. The majority of the 54 studies came from the United States, followed by China, as seen in Figure 2.

Figure 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram.

Figure 2. Origin of included studies.

Twenty-two papers used a cohort study design, two studies used a combination of cohort and a cross-sectional design, and 24 studies used cross-sectional design. We also included experimental and case-control studies. An illustration of the number of types of study designs used in all studies can be seen in Figure 3. Figure 3 shows that most studies use cross-sectional research designs which are then followed by cohort research designs.

Figure 3. Design of included studies.

The graph of publication shows the number of studies during the last eleven years from 2011 to 2021 as shown in Figure 4. The total number of publications collected from PubMed database are shown in Figure 4. In 2012 there were nine studies related to biopsychosocial factors related to depression in the elderly but from 2013 to 2020 there were less. In 2021 there was an increase in the number of studies related to depression in the elderly. This can be attributed to an increase in the elderly population globally which was also followed by an increase in the incidence of depression, so it was necessary to conduct more research.

Figure 4. Year of publication for included studies.

An overview of critical appraisal using JBI Checklist shows that there are 53 papers with high quality paper and one paper with low quality as illustrated in Figure 5.

Figure 5. Critical appraisal based on Joanna Briggs Institute (JBI) checklist.

The data extraction of each study can be seen in Table 1. Five papers discussed biopsychosocial factors, 18 papers discussed biological and psychological/social factors, five papers discussed psychosocial factors, and the rest of the studies discussed one component of biopsychosocial factors associated with depression. Now we outline the results for the biological, psychological, and social factors of depression (examples of determinants and consequences are shown below).

Table 1. Data extracted from eligible studies.

No.	Author	Method	Country	Sample size	Instrument	Biological	Psychological	Social
1	(Nicolosi et al., 2011)	Cross-sectional	Brazil	303	Geriatric Depression Scale (GDS)	Health problems	Poor self-perceived health	Lower education level
2	(Gureje et al., 2011)	Cohort	Nigeria	1408	Major Depressive Disorder based on DSM-IV Axis I Disorders	Female	-	Rural residence and poor social network
3	(Piboon et al., 2012)	Cross-Sectional	Thailand	317	Thai Geriatric Depression Scale	Female, functional ability	Stressful life events, loneliness, problem-focused and emotional focused coping strategy	Lack of social support, income
4	(Arve et al., 2012)	Cohort	Finland	276	Zung depression scale	Negative health status	Feeling sick, Loneliness	-
5	(Leggett et al., 2012)	Cross-Sectional	Vietnam	600	Center for Epidemiologic Studies- Depression Scale	Female, Pain, ADL assistance need	-	Low education level, low economic status. and lack of emotional support
6	(Petkus, Gum, & Wetherell, 2012)	Cross-Sectional	US	142	Brief Symptom Inventory-18 (BSI-18), Structured Clinical Interview for DSM-IV Diagnosis (SCID)	-	Thought suppression	-
7	(Popescu et al., 2012)	Cross-Sectional	Canada	315	Geriatric Depression Scale Short Form (GDS-15)	Age-related macular degeneration (AMD), glaucoma, or Fuchs corneal dystrophy	-	-
8	(Carayanni et al., 2012)	Cross-Sectional	Greece	360	15-item geriatric depression scale (GDS)	Female, multimorbidity	-	Unmarried, not meeting friends, childless, economic problems, not caring for a grandchild, lack of social participation
9	(Davison et al., 2012)	Case- Control	Australia	100	Major Depressive Disorder based on DSM-IV Axis I Disorders, 15-item version of the Geriatric Depression Scale	Lower physical health and higher disability levels	Purpose in life, and autonomy	Time spent in the facility, environmental mastery
10	(Chan et al., 2012)	Cohort	China	2630	15-item version of the Geriatric Depression Scale	-	Losing hobby, stressful events	Losing pets, economic problems
11	(Pusswald et al., 2012)	Case- Control	Vienna	110	Geriatric Depression Scale	Parkinson disease	-	-
12	(Glei et al., 2013)	Cohort	Taiwan	4049	Center for Epidemiologic Studies Depression scale (CES-D)	Female	-	Live far from family, widow, losing a child
13	(Sjöberg et al., 2013)	Cohort	Sweden	891	DSM-IV-TR	-	Loneliness, losing hobby	Lack of contact with family, unmarried/widowed, low education level
14	(Sadler et al., 2013)	Cross-sectional	Australia	171	Centre for Epidemiologic Studies Depression Scale (CESD)	Insomnia	Dysfunctional beliefs about sleep and hopelessness	-
15	(Horita et al., 2013)	Cross-sectional	Japan	84	Geriatric Depression Scale Short Form (GDS-15)	Low BMI, dyspnea, exercise capacity, Oxygen level	-	-
16	(Lewin, Jöbges, & Werheid, 2013)	Cross-sectional	Germany	105	Geriatric Depression Scale Short Form (GDS-15)	-	Self-efficacy, history of pre-stroke depression	Lack of social support
17	(Meesters et al., 2014)	Cross-sectional	Dutch	99	Centre for Epidemiologic Studies Depression Scale (CESD)	Higher functional limitation, more chronic physical disorder	-	Lack of social support
18	(Choi et al., 2014)	Cross-sectional and Cohort	United States	5414	Patient Health Questionnaire-2 (PHQ-2)	Cardiovascular disease	-	-
19	(Wild et al., 2014)	Cohort	Germany	3124	Patient Health Questionnaire (PHQ-8) depression scale	-	-	Health care needs
20	(Nadimpalli, James, Yu, Cothran, & Barnes, 2015)	Cross-sectional and Cohort	United States	487	Centre for Epidemiologic Studies Depression Scale (CESD)	-	-	Discrimination
21	(Rzewuska et al., 2015)	Cohort	UK	501	Hospital Anxiety and Depression Scale (HADS)	Female, older age, pain, low activity level	-	Lack of support, routine work
22	(Park & Yu, 2015)	Experimental	South Korea	24	Beck Depression Inventory (BDI)	Nordic walking (negative)	-	-
23	(Sanders et al., 2015)	Cohort	Netherland	1528	Centre for Epidemiologic Studies Depression Scale (CESD)	Pain	-	-
24	(Klinedinst et al., 2015)	Cross-sectional	US	114	Useful Depression Screening Tool (UDST)	Single nucleotide polymorphisms (SNPs) in the NTRK3 gene, pain, physical activity	Fear of falling	-
25	(Ylli et al., 2016)	Cross-sectional	Canada, Albania, Colombia, Brazil	1995	Centre for Epidemiologic Studies Depression Scale (CESD)	Multiple chronic conditions, and poor physical performance	-	Low education and insufficient income
26	(Jovanova et al., 2016)	Cohort	Netherland	1823	Centre for Epidemiologic Studies Depression Scale (CESD)	Recognized myocardial infarction (RMI)	-	-
27	(Wang et al., 2016)	Cohort	China	608	Post stroke depression based on ICD-10 criteria	Insomnia, neurological deficit, low Barthel Index	-	-
28	(Manaf et al., 2016)	Cross Sectional	Malaysia	230	Depression, Anxiety, and Stress Scale (DASS-21)	Poor health status	-	Single, living with family
29	(Kato, Zweig, Schechter, Barzilai, & Atzmon, 2016)	Cross Sectional	US	357	Geriatric Depression Scale Short Form (GDS-15)	-	Attitudes toward life, self-rated health	High level of care
30	(Brinda et al., 2016)	cross-sectional	China, Ghana, India, Mexico, South Africa, Russia	34159	International Classification of Diseases-10th revision Diagnostic Criteria for Research (ICD-10 DCR)	Female, angina, stroke	Bereavement	Illiteracy, poverty, indebtedness, past informal-sector occupation, pension support and health insurance
31	(Kuroda et al., 2017)	Cohort	Japan	438	Basic Checklist	Female, gender, age, diabetes, cognitive disorder	-	-
32	(Matthieu, Lawrence, & Robertson-Blackmore, 2017)	Cohort	US	346	Patient Health Questionnaire-2 (PHQ-2)	-	-	Social activities
33	(Ferrand et al., 2018)	Cross Sectional	French	402	30-items Geriatric Depression Scale	High fish-fruit- vegetable compared to ready meals	-	-
34	(Rippon & Steptoe, 2018)	Cohort	England	9886	Centre for Epidemiologic Studies Depression Scale (CESD)	Older age	-	-
35	(Olsen et al., 2018)	Cohort	Norway	7068	Hospital Anxiety and Depression Scale (HADS)	Age, cardiovascular morbidity	-	Low education level
36	(Odlum et al., 2018)	Cross Sectional	US	3377	Centre for Epidemiologic Studies Depression Scale (CESD)	Female, incontinence	-	Demanding spouse, lack of time with spouse
37	(Wang et al., 2018)	Cross Sectional	China	47	Depression based on ICD-10 criteria	White matter hyperintensity	-	Religious beliefs, family harmony
38	(Kobylańska et al., 2018)	Quasi-experimental	Poland	120	30-items Geriatric Depression Scale	Mobility and independence	-	Education level
39	(Akila et al., 2019)	Cross Sectional	India	510	Geriatric Depression Scale Short Form (GDS-15)	-	Perceived mental health	Rural area, illiteracy, social support, financial problems
40	(Sakurai et al., 2019)	Cohort	Japan	400	Zung Self-Rating Depression Scale	-	-	Living alone, social support
41	(Laird et al., 2019)	Cross Sectional	US	113	Montgomery-Åsberg Depression Rating Scale (MADRS)	Lower Grey Matter Volume (GMV) bilaterally in the insula, lower Total Intracranial Volume (TIV)	-	-
42	(Misawa & Kondo, 2019)	Cohort	Japan	3464	Geriatric Depression Scale Short Form (GDS-15)	Female	Life events, sense of coherence, hobby, self-rated health	Meeting with friends
43	(Bui, 2020)	Cohort	US	2200	Centre for Epidemiologic Studies Depression Scale (CESD)	-	-	Social support, density
44	(Stringa et al., 2020)	Cohort	Netherland	2276	Centre for Epidemiologic Studies Depression Scale (CESD)	Higher PRS-D (genetic)	-	Single, network
45	(Bond et al., 2020)	Cohort	Ireland	291	Glasgow Depression Scale for people with a Learning Disability (GDS-LD)	Mood stabilisers, anxiolytic medications, hypnotic/sedative medications	Had trouble sleeping, difficulties in carrying out ADLs. difficulties in keeping up enthusiasm to get things done, feeling lonely, aggression	-
46	(Hong et al., 2021)	Cohort	US	12998	Health and Retirement Study (HRS) Psychosocial and Lifestyle Questionnaire	-	Sense of control	-
47	(Woods et al., 2021)	Experimental	US	189	Hamilton Depression Rating Scale (HAM-D)	-	-	Unmarried, lack of social support, interpersonal problems
48	(Rhee et al., 2021)	Cross Sectional	South Korea	8522	Geriatric Depression Scale Short Form (GDS-15)	Incident of fall	-	Unmarried, living alone, lack of network
49	(Cordes, Zwingmann, Rudisch, Voelcker-Rehage, & Wollesen, 2021)	Experimental	Germany	52	Centre for Epidemiologic Studies Depression Scale (CESD)	Exercise	-	-
50	(Chen et al., 2021)	Cross Sectional Cohort	China	1764	Geriatric Depression Scale Short Form (GDS-15)	-	-	Social frailty
51	(Koo et al., 2021)	Cohort	South Korea	3011	Centre for Epidemiologic Studies Depression Scale (CESD)	-	-	Live alone and the periods of living alone
52	(Derry et al., 2021)	Cross Sectional	US	161	Centre for Epidemiologic Studies Depression Scale (CESD)	Higher composite cytokine levels	-	-
53	(Paralikas et al., 2021)	Cross Sectional	Greece	230	General Health Questionnaire 28 (GHQ-28)	-	-	Unmarried, single, divorced, widowed
54	(Karczewska & Młynarska, 2021)	Cohort	Poland	158	Hospital Anxiety and Depression Scale (HADS)	ICD discharged	-	-

Biological factors

Biological factors were frequently found to influence geriatric depression. Such factors mentioned included gender (Brinda et al., 2016; Carayanni et al., 2012; Glei, Goldman, Liu, & Weinstein, 2013; Gureje, Oladeji, & Abiona, 2011; Kuroda et al., 2017; Leggett, Zarit, Nguyen, Hoang, & Nguyen, 2012; Misawa & Kondo, 2019; Odlum et al., 2018; Piboon, Subgranon, Hengudomsub, Wongnam, & Louise Callen, 2012; Rzewuska, Mallen, Strauss, Belcher, & Peat, 2015), health problems (Arve et al., 2012; Carayanni et al., 2012; Choi, Kim, Marti, & Chen, 2014; Horita et al., 2013; Jovanova et al., 2016; Karczewska & Młynarska, 2021; Leggett et al., 2012; Meesters et al., 2014; Nicolosi et al., 2011; Olsen, Schirmer, Wilsgaard, Bønaa, & Hanssen, 2018; Popescu et al., 2012; Pusswald et al., 2012; Rhee, Jang, Kim, & Chang, 2021; Rzewuska et al., 2015; Sadler, McLaren, & Jenkins, 2013; Sanders, Comijs, Bremmer, Deeg, & Beekman, 2015; Wang et al., 2016; Ylli et al., 2016), older age (Olsen et al., 2018; Rippon & Steptoe, 2018; Rzewuska et al., 2015), genetics (Klinedinst, Resnick, Yerges-Armstrong, & Dorsey, 2015; Stringa et al., 2020), brain anatomical (Laird et al., 2019; Wang et al., 2018), cytokine level (Derry et al., 2021), taking drugs (Bond et al., 2020), low activity (Davison, McCabe, Knight, & Mellor, 2012; Kobylańska et al., 2019; Leggett et al., 2012; Meesters et al., 2014; Piboon et al., 2012; Rzewuska et al., 2015), diet (Ferrand et al., 2018) and BMI (body mass index) status (Horita et al., 2013). One study has found that women showed a significant positive association with geriatric depression (Brinda et al., 2016). Other literature found that the prevalence of depression is higher in women than in men (Piboon et al., 2012; Ylli et al., 2016). In total, ten different kinds of studies have shown that women were more likely to have depression or higher depressive symptoms than men, indicating a relationship between gender and older age depression.

Eighteen studies in this review have found that the presence of depression is associated with health problems including pain, degenerative diseases, multimorbidity, poor respiratory indicators, cardiovascular morbidity, insomnia, and a falling incident. One of the literature obtained a p<0.001, showing the significant relationship between health problems and depression (Nicolosi et al., 2011).

There were three studies in this review that have found that older age is associated with depression (Olsen et al., 2018; Rippon & Steptoe, 2018; Rzewuska et al., 2015). One of the literature showed that age of ≥70 year associated with depression disorder (Rzewuska et al., 2015). Another study showed with increase in the subject age, greater depressive symptoms were present (Rippon & Steptoe, 2018). Other factors mentioned concerning older age depression were genetic, brain anatomical, and cytokine levels (Derry et al., 2021; Klinedinst et al., 2015; Laird et al., 2019; Stringa et al., 2020; Wang et al., 2018).

One study, namely research conducted by Bond, revealed that taking drugs such as mood stabilizers, anxiolytics, and hypnotic or sedatives were associated with depression (Bond et al., 2020). They obtained a p=0.001 for mood stabilizers, p<0.001 for anxiolytic, and p=0.009 for hypnotic or sedatives, suggesting a significant relationship for this drug-taking factor.

Low activity or low activity tolerance and disability were also found to have a positive relationship with older age depression (Davison et al., 2012; Kobylańska et al., 2018; Leggett et al., 2012; Meesters et al., 2014; Piboon et al., 2012; Rzewuska et al., 2015). Lastly, diet and BMI status were explored as possible biological factors (Ferrand et al., 2018; Horita et al., 2013).

From one study, it was found that female gender was significantly associated with depression where p<0.001 was found (Piboon et al., 2012). Gender differences in depression can potentially be explained genetically, where genetic studies have found that female twins with a history of depression in the family were more likely to develop depression, and according to the psychological perspective, men and women have different personality features, which could explain the gender variations in depression. A study showed that females are more nurturing, non-aggressive, modest, and reliant than males, and they are more likely to have a relationship-oriented disposition (Piboon et al., 2012).

Individuals who had a chronic disease or health problems, particularly related to the musculoskeletal system such as arthritis and osteoporosis, are likely to had a weakened sense of self-efficacy, which can cause functional impairment and their presence has been associated with depression (Nicolosi et al., 2011). Health problems like pain were a predictive of depressive symptoms (Leggett et al., 2012). Some other studies showed that once pain and depression occurred, they will remain associated (Sanders et al., 2015). People with comorbidities are more likely to suffer from depression, indicating that it is another risk factor (Carayanni et al., 2012).

Psychological factors

The results of this research showed that seventeen studies discussed psychological factors that influence the occurrence of depression in the elderly. These factors were low self-perceived health, stressful life events, loneliness, and losing hobby/interest/purpose in life.

According to research conducted by Nicolosi et al. (2011), poorer self-perceived health leads to more depressive symptoms (Nicolosi et al., 2011).

One of three studies on stress in life, namely the study conducted by Chan (2012), found that there is a relationship between the number of stressful events in life and the incidence of depression (p=0.0020), with the number of stressful events associated with an increased risk of having depression (Chan et al., 2012). In both men and women, life events predicted the odds of depression among older people (Misawa & Kondo, 2019).

According to research conducted by Bond et al. (2020), there is a significant relationship between loneliness and the occurrence of depression, where p<0.05 (Bond et al., 2020). Piboon (2012) found that loneliness had a significantly positive impact on depression, with an obtained p<0.001. Chan et al. also found that loss of hobbies is related to an increased incidence of depression (Chan et al., 2012).

Loneliness had a significantly positive relationship and was a predictor of depression among older adults because they are more likely to experience losses and changes in later life, so those that may feel lonely are more likely to suffer from depression than younger adults who do not feel lonely (Piboon et al., 2012).

Social factors

In this literature study, there were 20 studies that discussed social factors that affect the occurrence of depression in the elderly. The social factors were social/emotional support, education level, financial problem, marital status, lack of contact with family/friends, living alone, dependency, environmental and religious beliefs. According to three from 12 that examined social support, social support was associated with depression. Research conducted by Bui (2020) found that there was a reciprocal relationship between social support and depressive symptoms, with p<0.001 (Bui, 2020). Meanwhile, research by Piboon (2012) found that there was a positive relationship between social support and depression (Piboon et al., 2012). Chen et al. found in their research that social frailty may be a predictor of depression among community-dwelling older adults (Chen et al., 2021).

This study found seven papers that discussed the relationship between education levels and the incidence of depression. In research conducted by Brinda (2016), it was found that low education correlated with geriatric depression (Brinda et al., 2016). Other studies have also found that less educated people have higher depressive symptoms (Akila, Arvind, & Isaac, 2019; Kobylańska et al., 2018; Leggett et al., 2012; Nicolosi et al., 2011; Olsen et al., 2018; Sjöberg et al., 2013).

Education was the key indicator of social risk for depression. Individuals with lower education tend to feel more uncertain about the future and on a higher poverty level which makes greater prevalence of depression (Nicolosi et al., 2011). Individuals with lower education and income may have less access to health services, putting them at higher risk of getting depressive symptoms (Nicolosi et al., 2011).

Financial problems or poverty were also found to be factors that influence the incidence of depression. In this study we found seven papers that discusses financial problems or poverty as factors that influence the occurrence of depression. Brinda (2016) showed that poverty had a positive association with depression in the elderly (Brinda et al., 2016). Other literature studies have suggested that a significant lack of income is associated with the prevalence of depression (Ylli et al., 2016), furthermore showing that income has a negative effect on depression (Piboon et al., 2012). Income also had an indirect effect on depression in older adults. Some studies reported that elderly people living alone are single, divorced or lost a partner where they then unknowingly suffer from financial burdens and look at their health status negatively (Koo, Son, & Yoo, 2021). It is also reported that elderly people who are reluctant to live alone are prone to depression (Koo et al., 2021).

Eight literature studies discussed the relationship between marital status and (Koo et al., 2021) depression. According to Manaf (2016), marital status was a factor that was significantly associated with depression where they obtained a p=0.00l. Single elderly people experienced depression three times more often compared to elderly who are married (Manaf, Mustafa, Rahman, Yusof, & Aziz, 2016). Other literature showed that single/divorced/widowed people had more depressive symptoms than those who are married (Paralikas et al., 2021; Sjöberg et al., 2013).

In this study, we found that people with poor social networks, especially those lacking contact with friends, had an elevated risk of an incident of depression (Gureje et al., 2011). The frequency of meetings with friends predicted reduced odds of depression in older men (Misawa & Kondo, 2019).

It was also found that living alone is a risk factor associated with depression, where p<0.001 was obtained (Carayanni et al., 2012). Additionally, Living with an unmarried son was linked to a higher risk of depression than living with a married son and daughter-in-law (Glei et al., 2013). A study conducted by Koo (2021) also stated that those living alone are at higher risk of suffering from depression compared to those living with others (Koo et al., 2021). Lastly we found one study that stated that religious beliefs were associated with depression (Wang et al., 2018).

The risk of bias in this systematic review is that depression is assessed as all depression that occurs in the elderly, whether they have a chronic disease and not. In this literature review, based on the JBI checklist, high-quality papers were obtained.

Limitations

The limitation of the results of this systematic literature review is that most papers do not clearly identify the confounding factor. Papers included in this review are varied, so they do not allow for quantitative synthesis. Therefore, we discuss the results narratively in order to provide the big picture of the topic.

Conclusions

The results confirmed that biopsychosocial factors were correlated with depression within a population of older individuals. Depression is a clinical condition that requires a holistic approach with biopsychosocial factors. From the results of this literature search, it was also found that there are biopsychosocial factors that have not been studied and are expected to be able to make references for future research. As for the variables that have not been discussed before such as in biological factors are the weakening that occurs in the elderly and psychological factors are a history of previous mental status and coping style. Understanding the biopsychosocial factors influencing them is paramount in developing the management programs to tackle depression in the elderly.

Data availability

Underlying data

Figshare: Data Extraction_Depression in Elderly from 54 research papers.csv. https://doi.org/10.6084/m9.figshare.19661373.v1 (Hadiwiardjo and Damayanti, 2022a).

This project contains the following underlying data:

- Data Extraction_Depression in Elderly from 54 research papers.csv.

Extended data

Figshare: Prisma flowchart depression in Elderly. https://doi.org/10.6084/m9.figshare.19991789.v1 (Hadiwiardjo and Damayanti, 2022b).

This project contains the following extended data:

- Prisma search figure_Depression in Elderly.jpg (PRISMA flowchart).

Reporting guidelines

Figshare: PRISMA checklist for ‘Biopsychosocial factors associated with depression in the elderly: A systematic literature review’. https://doi.org/10.6084/m9.figshare.20152346.v1 (Hadiwiardjo and Damayanti, 2022c).

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

Acknowledgements

The author would like to thank the faculty members at the University of Indonesia and University of Pembangunan Veteran Jakarta for their support and providing a good research environment. Furthermore, ‘thank you’ to the Research Synergy Foundation for the recommendations and support in making this research more successful.

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¹ Faculty of Public Health, University of Indonesia, Depok, 10430, Indonesia
² Medical Faculty, University Pembangunan Nasional Veteran Jakarta, Jakarta, 12450, Indonesia

Yanti Harjono Hadiwiardjo
Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Writing – Original Draft Preparation

Rita Damayanti
Roles: Validation, Writing – Original Draft Preparation, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

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The author(s) declared that no grants were involved in supporting this work.

Article Versions (2)

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Published: 14 Feb 2024, 11:1068

https://doi.org/10.12688/f1000research.121710.2

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Harjono Hadiwiardjo Y and Damayanti R. Biopsychosocial factors associated with depression in the elderly: A systematic literature review [version 1; peer review: 2 approved with reservations]. F1000Research 2022, 11:1068 (https://doi.org/10.12688/f1000research.121710.1)

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Reviewer Report 17 Feb 2023

Rahul Shidhaye, Department of Psychiatry, Pravara Institute of Medical Sciences, Loni, Maharashtra, India

Approved with Reservations

https://doi.org/10.5256/f1000research.133605.r155783

In the paper titled, ‘Biopsychosocial factors associated with depression in the elderly: A systematic literature review’, the aim of the authors is to review the evidence related to the contribution of biopsychosocial factors to depression in the elderly.

... Continue reading

Large number of studies have investigated the role of biological, psychological, and social factors associated with depression in the general population and in the elderly. In this backdrop, the rationale for undertaking the current systematic review is not clear. Authors mention, "a greater understanding of the individual contributions of biological, psychological, and social risk factors can have a big impact on the adoption of preventive actions to lower the population's risk of depression", but this review doesn’t seem to assess the individual contribution of each of these factors.
Methods section can be re-structured based on the points included in the PRISMA guidelines.
Why was the search limited to the last ten years only?
The meaning of the sentence, "these studies included quantitative synthesis", is not clear. The following sentence is included in the limitations section, "papers included in this review are varied, so they do not allow for quantitative synthesis." Kindly clarify.
Who completed the critical appraisal of all the included papers? The score for each included paper based on the JBI checklist could be presented in a table as part of the supplementary material.
One of the biological factors mentioned is "brain anatomical". Kindly explain.
Limitations of the review and limitations of the included studies need to be described much more elaborately. There are multiple limitations of this study/review which are not discussed at all.
It will be good to compare the findings of this review with other similar studies.
Results from individual papers are presented without a clear high-level synthesis of these findings.
The aim of this review is to identify the research gaps, but this doesn’t seem to be covered anywhere in the paper.

Are the rationale for, and objectives of, the Systematic Review clearly stated?

No
Are sufficient details of the methods and analysis provided to allow replication by others?

Partly
Is the statistical analysis and its interpretation appropriate?

Partly
Are the conclusions drawn adequately supported by the results presented in the review?

No

Competing Interests: Rahul Shidhaye is supported by India Alliance (DBT-WELLCOME Trust) intermediate career fellowship in clinical and public health research.

Reviewer Expertise: Depression, Anxiety Disorders, Elderly, Pregnant women, Yoga, Implementation Science

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 14 Feb 2024

Yanti Harjono Hadiwiardjo , Faculty of Public Health, University of Indonesia, Depok, 10430, Indonesia

14 Feb 2024

Author Response

One of the key areas of focus in this revision has been the enhancement of the synthesis level in our article. We have made concerted efforts to this revision. By ... Continue reading One of the key areas of focus in this revision has been the enhancement of the synthesis level in our article. We have made concerted efforts to this revision. By meticulously reorganizing and rephrasing sections of the manuscript, we have aimed to present a more cohesive and integrated narrative. Additionally, we have addressed your recommendation regarding the introduction of a JBI score. We have now included this score as a vital component of our methodology, providing a transparent and standardized measure of the quality and reliability of our research.
One of the key areas of focus in this revision has been the enhancement of the synthesis level in our article. We have made concerted efforts to this revision. By meticulously reorganizing and rephrasing sections of the manuscript, we have aimed to present a more cohesive and integrated narrative. Additionally, we have addressed your recommendation regarding the introduction of a JBI score. We have now included this score as a vital component of our methodology, providing a transparent and standardized measure of the quality and reliability of our research.
Competing Interests: No competing interests were disclosed. Close
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Author Response 14 Feb 2024

Yanti Harjono Hadiwiardjo , Faculty of Public Health, University of Indonesia, Depok, 10430, Indonesia

14 Feb 2024

Author Response
1. After the author reviews it further, what the author means by individual contribution is if a person already knows these risk factors so they can be prevented, and
... Continue reading
After the author reviews it further, what the author means by individual contribution is if a person already knows these risk factors so they can be prevented, and the incidence of depression can decrease. The author changed the paragraph to “A greater understanding of the individual factors of biological, psychological, and social risk factors can have a big impact on the adoption of preventive actions to lower the population's risk of depression.”

Done for submission, the article re-structured based on the PRISMA guidelines.

The selection of the last 10 years for research is driven by the need to focus on recent and relevant information. This time frame allows us to capture the most up-to-date developments, trends, and insights in the field. The requirement for articles to be written in English and published between 2011 and 2021 further ensures that the sources are contemporary and provide valuable insights within a reasonable time span. This approach enhances the accuracy and relevance of the information gathered for the study.

After reviewing it again, the author revised the limitations sections in the article to be “The limitation of the results of this systematic review is that most papers do not clearly identify the confounding factor so it cannot be determined whether there is bias in the study. Therefore, we discuss the results narratively in order to provide a big picture of the topic.”

Completed for submission, the article includes a paper based on JBI checklist scores as an attachment.

The means of brain anatomical is like a history of trauma, infectious diseases and other abnormalities in the brain.

The limitation of the results of this systematic review is that most papers do not clearly identify the confounding factor so it cannot be determined whether there is bias in the study. Therefore, we discuss the results narratively in order to provide a big picture of the topic.

Thank you for the suggestion, the author will add the section comparing the findings of this review with other similar studies.

The author had limited time, so he did not have time to carry out a meta-analysis.

This article aims to identify research gaps, which means the authors want to analyze current risk factors. The reason is the author feels that the risk factors for depression are different between now and then.
After the author reviews it further, what the author means by individual contribution is if a person already knows these risk factors so they can be prevented, and the incidence of depression can decrease. The author changed the paragraph to “A greater understanding of the individual factors of biological, psychological, and social risk factors can have a big impact on the adoption of preventive actions to lower the population's risk of depression.”

Done for submission, the article re-structured based on the PRISMA guidelines.

The selection of the last 10 years for research is driven by the need to focus on recent and relevant information. This time frame allows us to capture the most up-to-date developments, trends, and insights in the field. The requirement for articles to be written in English and published between 2011 and 2021 further ensures that the sources are contemporary and provide valuable insights within a reasonable time span. This approach enhances the accuracy and relevance of the information gathered for the study.

After reviewing it again, the author revised the limitations sections in the article to be “The limitation of the results of this systematic review is that most papers do not clearly identify the confounding factor so it cannot be determined whether there is bias in the study. Therefore, we discuss the results narratively in order to provide a big picture of the topic.”

Completed for submission, the article includes a paper based on JBI checklist scores as an attachment.

The means of brain anatomical is like a history of trauma, infectious diseases and other abnormalities in the brain.

The limitation of the results of this systematic review is that most papers do not clearly identify the confounding factor so it cannot be determined whether there is bias in the study. Therefore, we discuss the results narratively in order to provide a big picture of the topic.

Thank you for the suggestion, the author will add the section comparing the findings of this review with other similar studies.

The author had limited time, so he did not have time to carry out a meta-analysis.

This article aims to identify research gaps, which means the authors want to analyze current risk factors. The reason is the author feels that the risk factors for depression are different between now and then.
Competing Interests: No competing interests were disclosed. Close
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Author Response 14 Feb 2024

Yanti Harjono Hadiwiardjo , Faculty of Public Health, University of Indonesia, Depok, 10430, Indonesia

14 Feb 2024

Author Response

One of the key areas of focus in this revision has been the enhancement of the synthesis level in our article. We have made concerted efforts to this revision. By ... Continue reading One of the key areas of focus in this revision has been the enhancement of the synthesis level in our article. We have made concerted efforts to this revision. By meticulously reorganizing and rephrasing sections of the manuscript, we have aimed to present a more cohesive and integrated narrative. Additionally, we have addressed your recommendation regarding the introduction of a JBI score. We have now included this score as a vital component of our methodology, providing a transparent and standardized measure of the quality and reliability of our research.
One of the key areas of focus in this revision has been the enhancement of the synthesis level in our article. We have made concerted efforts to this revision. By meticulously reorganizing and rephrasing sections of the manuscript, we have aimed to present a more cohesive and integrated narrative. Additionally, we have addressed your recommendation regarding the introduction of a JBI score. We have now included this score as a vital component of our methodology, providing a transparent and standardized measure of the quality and reliability of our research.
Competing Interests: No competing interests were disclosed. Close
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Author Response 14 Feb 2024

Yanti Harjono Hadiwiardjo , Faculty of Public Health, University of Indonesia, Depok, 10430, Indonesia

14 Feb 2024

Author Response
1. After the author reviews it further, what the author means by individual contribution is if a person already knows these risk factors so they can be prevented, and
... Continue reading
After the author reviews it further, what the author means by individual contribution is if a person already knows these risk factors so they can be prevented, and the incidence of depression can decrease. The author changed the paragraph to “A greater understanding of the individual factors of biological, psychological, and social risk factors can have a big impact on the adoption of preventive actions to lower the population's risk of depression.”

Done for submission, the article re-structured based on the PRISMA guidelines.

The selection of the last 10 years for research is driven by the need to focus on recent and relevant information. This time frame allows us to capture the most up-to-date developments, trends, and insights in the field. The requirement for articles to be written in English and published between 2011 and 2021 further ensures that the sources are contemporary and provide valuable insights within a reasonable time span. This approach enhances the accuracy and relevance of the information gathered for the study.

After reviewing it again, the author revised the limitations sections in the article to be “The limitation of the results of this systematic review is that most papers do not clearly identify the confounding factor so it cannot be determined whether there is bias in the study. Therefore, we discuss the results narratively in order to provide a big picture of the topic.”

Completed for submission, the article includes a paper based on JBI checklist scores as an attachment.

The means of brain anatomical is like a history of trauma, infectious diseases and other abnormalities in the brain.

The limitation of the results of this systematic review is that most papers do not clearly identify the confounding factor so it cannot be determined whether there is bias in the study. Therefore, we discuss the results narratively in order to provide a big picture of the topic.

Thank you for the suggestion, the author will add the section comparing the findings of this review with other similar studies.

The author had limited time, so he did not have time to carry out a meta-analysis.

This article aims to identify research gaps, which means the authors want to analyze current risk factors. The reason is the author feels that the risk factors for depression are different between now and then.
After the author reviews it further, what the author means by individual contribution is if a person already knows these risk factors so they can be prevented, and the incidence of depression can decrease. The author changed the paragraph to “A greater understanding of the individual factors of biological, psychological, and social risk factors can have a big impact on the adoption of preventive actions to lower the population's risk of depression.”

Done for submission, the article re-structured based on the PRISMA guidelines.

The selection of the last 10 years for research is driven by the need to focus on recent and relevant information. This time frame allows us to capture the most up-to-date developments, trends, and insights in the field. The requirement for articles to be written in English and published between 2011 and 2021 further ensures that the sources are contemporary and provide valuable insights within a reasonable time span. This approach enhances the accuracy and relevance of the information gathered for the study.

After reviewing it again, the author revised the limitations sections in the article to be “The limitation of the results of this systematic review is that most papers do not clearly identify the confounding factor so it cannot be determined whether there is bias in the study. Therefore, we discuss the results narratively in order to provide a big picture of the topic.”

Completed for submission, the article includes a paper based on JBI checklist scores as an attachment.

The means of brain anatomical is like a history of trauma, infectious diseases and other abnormalities in the brain.

The limitation of the results of this systematic review is that most papers do not clearly identify the confounding factor so it cannot be determined whether there is bias in the study. Therefore, we discuss the results narratively in order to provide a big picture of the topic.

Thank you for the suggestion, the author will add the section comparing the findings of this review with other similar studies.

The author had limited time, so he did not have time to carry out a meta-analysis.

This article aims to identify research gaps, which means the authors want to analyze current risk factors. The reason is the author feels that the risk factors for depression are different between now and then.
Competing Interests: No competing interests were disclosed. Close
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Reviewer Report 16 Dec 2022

Acharaporn Seeherunwong, Department of Mental Health and Psychiatric Nursing, Mahidol University, Nakhon Pathom, Thailand

Approved with Reservations

https://doi.org/10.5256/f1000research.133605.r155782

The study's objective should be "...biopsychosocial factors associated with or predictors of depression in the elderly."

Comment from reviewer:

The study of “Biopsychosocial factors associated with depression in the elderly: A systematic literature review” ... Continue reading

The title: I suggest using “A systematic review” instead of “A systematic literature review”.
Introduction section: In the 1st paragraph, "In Indonesia, citizens 60 years old or older have reached about 25.7 million people" should be revised to calculate to be a percentage of the total population. As a result, the amount of elderly in Indonesia is comparable to the proportion of elderly in the UK and other countries worldwide.
Result: The outcome has varied the severity of depressive symptoms. I suggest categorizing the paper into two groups, as the outcomes differ in severity. The first group is the elderly diagnosed with MDD or depressive disorder (article nos. 2, 6, 9,13, 30). The second one is elderly with depressive symptoms who were not diagnosed with depressive disorders. The associated factors may be different as well.
Please separate the result section from the discussion section. In addition, the authors should find previous studies to explain the results.

Are the rationale for, and objectives of, the Systematic Review clearly stated?

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

Yes
Is the statistical analysis and its interpretation appropriate?

Not applicable
Are the conclusions drawn adequately supported by the results presented in the review?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Depression, mental health, nursing

CITE

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Author Response 14 Feb 2024

Yanti Harjono Hadiwiardjo , Faculty of Public Health, University of Indonesia, Depok, 10430, Indonesia

14 Feb 2024

Author Response

One of the key areas of focus in this revision has been the enhancement of the synthesis level in our article. We have made concerted efforts to this revision. By ... Continue reading One of the key areas of focus in this revision has been the enhancement of the synthesis level in our article. We have made concerted efforts to this revision. By meticulously reorganizing and rephrasing sections of the manuscript, we have aimed to present a more cohesive and integrated narrative. Additionally, we have addressed your recommendation regarding the introduction of a JBI score. We have now included this score as a vital component of our methodology, providing a transparent and standardized measure of the quality and reliability of our research.
One of the key areas of focus in this revision has been the enhancement of the synthesis level in our article. We have made concerted efforts to this revision. By meticulously reorganizing and rephrasing sections of the manuscript, we have aimed to present a more cohesive and integrated narrative. Additionally, we have addressed your recommendation regarding the introduction of a JBI score. We have now included this score as a vital component of our methodology, providing a transparent and standardized measure of the quality and reliability of our research.
Competing Interests: No competing interests were disclosed. Close
Report a concern
Author Response 14 Feb 2024

Yanti Harjono Hadiwiardjo , Faculty of Public Health, University of Indonesia, Depok, 10430, Indonesia

14 Feb 2024

Author Response
1. The title the title has been changed to "Biopsychosocial factors associated with depression in the elderly: A systematic review"
2. Introduction section: In the 1st paragraph changed
... Continue reading
The title the title has been changed to "Biopsychosocial factors associated with depression in the elderly: A systematic review"

Introduction section: In the 1st paragraph changed to "Demographic Profiles and Implications of the Top 10 Countries with the Highest Number of People Aged 65+ in 2020" delves into a significant global demographic shift observed in the year 2020 with calculations conducted by ESCAP based on the United Nations' Department of Economic and Social Affairs, Population Division (2019). The data reveals the following key insights China emerged as the country with the largest elderly population, with a staggering 172,262 individuals aged 65 and above, representing 46.05% of its total population, India follows closely, with 90,720 seniors, constituting 24.25% of the population, Japan recorded 35,916 elderly citizens, making up 9.60% of its populace, The Russian Federation reported 22,633 seniors, accounting for 6.05% of its total population, Indonesia had 17,219 elderly individuals, representing 4.57% of the population, Pakistan's elderly population reached 9,606, making up 2.56% of its total, Thailand reported 9,044 seniors, equivalent to 2.41% of its population, Bangladesh recorded 8,608 elderly citizens, constituting 2.30% of its populace and Korea reported 8,096 elderly individuals, representing 2.16% of the total population.

Regarding categorizing the paper into two groups, the author feels objections and does not want to categorize it into two groups. Just following the initial research with the expected results as of now.

In the latest and revised article, the author has categorized the results and discussion into different sections according to the reviewer's input.
The title the title has been changed to "Biopsychosocial factors associated with depression in the elderly: A systematic review"

Introduction section: In the 1st paragraph changed to "Demographic Profiles and Implications of the Top 10 Countries with the Highest Number of People Aged 65+ in 2020" delves into a significant global demographic shift observed in the year 2020 with calculations conducted by ESCAP based on the United Nations' Department of Economic and Social Affairs, Population Division (2019). The data reveals the following key insights China emerged as the country with the largest elderly population, with a staggering 172,262 individuals aged 65 and above, representing 46.05% of its total population, India follows closely, with 90,720 seniors, constituting 24.25% of the population, Japan recorded 35,916 elderly citizens, making up 9.60% of its populace, The Russian Federation reported 22,633 seniors, accounting for 6.05% of its total population, Indonesia had 17,219 elderly individuals, representing 4.57% of the population, Pakistan's elderly population reached 9,606, making up 2.56% of its total, Thailand reported 9,044 seniors, equivalent to 2.41% of its population, Bangladesh recorded 8,608 elderly citizens, constituting 2.30% of its populace and Korea reported 8,096 elderly individuals, representing 2.16% of the total population.

Regarding categorizing the paper into two groups, the author feels objections and does not want to categorize it into two groups. Just following the initial research with the expected results as of now.

In the latest and revised article, the author has categorized the results and discussion into different sections according to the reviewer's input.
Competing Interests: No competing interests were disclosed. Close
Report a concern
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COMMENTS ON THIS REPORT

Author Response 14 Feb 2024

Yanti Harjono Hadiwiardjo , Faculty of Public Health, University of Indonesia, Depok, 10430, Indonesia

14 Feb 2024

Author Response

One of the key areas of focus in this revision has been the enhancement of the synthesis level in our article. We have made concerted efforts to this revision. By ... Continue reading One of the key areas of focus in this revision has been the enhancement of the synthesis level in our article. We have made concerted efforts to this revision. By meticulously reorganizing and rephrasing sections of the manuscript, we have aimed to present a more cohesive and integrated narrative. Additionally, we have addressed your recommendation regarding the introduction of a JBI score. We have now included this score as a vital component of our methodology, providing a transparent and standardized measure of the quality and reliability of our research.
One of the key areas of focus in this revision has been the enhancement of the synthesis level in our article. We have made concerted efforts to this revision. By meticulously reorganizing and rephrasing sections of the manuscript, we have aimed to present a more cohesive and integrated narrative. Additionally, we have addressed your recommendation regarding the introduction of a JBI score. We have now included this score as a vital component of our methodology, providing a transparent and standardized measure of the quality and reliability of our research.
Competing Interests: No competing interests were disclosed. Close
Report a concern
Author Response 14 Feb 2024

Yanti Harjono Hadiwiardjo , Faculty of Public Health, University of Indonesia, Depok, 10430, Indonesia

14 Feb 2024

Author Response
1. The title the title has been changed to "Biopsychosocial factors associated with depression in the elderly: A systematic review"
2. Introduction section: In the 1st paragraph changed
... Continue reading
The title the title has been changed to "Biopsychosocial factors associated with depression in the elderly: A systematic review"

Introduction section: In the 1st paragraph changed to "Demographic Profiles and Implications of the Top 10 Countries with the Highest Number of People Aged 65+ in 2020" delves into a significant global demographic shift observed in the year 2020 with calculations conducted by ESCAP based on the United Nations' Department of Economic and Social Affairs, Population Division (2019). The data reveals the following key insights China emerged as the country with the largest elderly population, with a staggering 172,262 individuals aged 65 and above, representing 46.05% of its total population, India follows closely, with 90,720 seniors, constituting 24.25% of the population, Japan recorded 35,916 elderly citizens, making up 9.60% of its populace, The Russian Federation reported 22,633 seniors, accounting for 6.05% of its total population, Indonesia had 17,219 elderly individuals, representing 4.57% of the population, Pakistan's elderly population reached 9,606, making up 2.56% of its total, Thailand reported 9,044 seniors, equivalent to 2.41% of its population, Bangladesh recorded 8,608 elderly citizens, constituting 2.30% of its populace and Korea reported 8,096 elderly individuals, representing 2.16% of the total population.

Regarding categorizing the paper into two groups, the author feels objections and does not want to categorize it into two groups. Just following the initial research with the expected results as of now.

In the latest and revised article, the author has categorized the results and discussion into different sections according to the reviewer's input.
The title the title has been changed to "Biopsychosocial factors associated with depression in the elderly: A systematic review"

Introduction section: In the 1st paragraph changed to "Demographic Profiles and Implications of the Top 10 Countries with the Highest Number of People Aged 65+ in 2020" delves into a significant global demographic shift observed in the year 2020 with calculations conducted by ESCAP based on the United Nations' Department of Economic and Social Affairs, Population Division (2019). The data reveals the following key insights China emerged as the country with the largest elderly population, with a staggering 172,262 individuals aged 65 and above, representing 46.05% of its total population, India follows closely, with 90,720 seniors, constituting 24.25% of the population, Japan recorded 35,916 elderly citizens, making up 9.60% of its populace, The Russian Federation reported 22,633 seniors, accounting for 6.05% of its total population, Indonesia had 17,219 elderly individuals, representing 4.57% of the population, Pakistan's elderly population reached 9,606, making up 2.56% of its total, Thailand reported 9,044 seniors, equivalent to 2.41% of its population, Bangladesh recorded 8,608 elderly citizens, constituting 2.30% of its populace and Korea reported 8,096 elderly individuals, representing 2.16% of the total population.

Regarding categorizing the paper into two groups, the author feels objections and does not want to categorize it into two groups. Just following the initial research with the expected results as of now.

In the latest and revised article, the author has categorized the results and discussion into different sections according to the reviewer's input.
Competing Interests: No competing interests were disclosed. Close
Report a concern

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Version 2

VERSION 2 PUBLISHED 20 Sep 2022

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Version 1 20 Sep 22	read	read

Acharaporn Seeherunwong, Mahidol University, Nakhon Pathom, Thailand
Rahul Shidhaye, Pravara Institute of Medical Sciences, Loni, India

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3 Views

02 Apr 2024 | for Version 2

Rahul Shidhaye, Department of Psychiatry, Pravara Institute of Medical Sciences, Loni, Maharashtra, India

3 Views Cite this report Responses(0)

Approved

Thank you for addressing all the comments.

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Depression, Anxiety Disorders, Elderly, Pregnant women, Yoga, Implementation Science

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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8 Views

23 Mar 2024 | for Version 2

Acharaporn Seeherunwong, Department of Mental Health and Psychiatric Nursing, Mahidol University, Nakhon Pathom, Thailand

8 Views Cite this report Responses(0)

Approved With Reservations

Comment from the reviewer:
I have the following comments for the first revised manuscript.

The title: I suggest using the term “A systematic review” instead of “A systematic literature review.” The authors did not revise the tile. I have suggested revising it to clarify the method and procedure of the review paper to the reader. There are many types of article review including integrated review, scope review, and systematic review.
In the discussion section, I did not find the knowledge gap in the part of the discussion as the goal of this systematic review. For example, it may need to examine the interaction among the biopsychosocial factors, or the multilevel of the factors.
The gender and sex variables have different meanings. Sex is used as a biological factor, while gender is used as a social factor. Please reconsider this issue.

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Depression, mental health, nursing

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17 Views

17 Feb 2023 | for Version 1

Rahul Shidhaye, Department of Psychiatry, Pravara Institute of Medical Sciences, Loni, Maharashtra, India

17 Views Cite this report Responses(2)

Approved With Reservations

Large number of studies have investigated the role of biological, psychological, and social factors associated with depression in the general population and in the elderly. In this backdrop, the rationale for undertaking the current systematic review is not clear. Authors mention, "a greater understanding of the individual contributions of biological, psychological, and social risk factors can have a big impact on the adoption of preventive actions to lower the population's risk of depression", but this review doesn’t seem to assess the individual contribution of each of these factors.
Methods section can be re-structured based on the points included in the PRISMA guidelines.
Why was the search limited to the last ten years only?
The meaning of the sentence, "these studies included quantitative synthesis", is not clear. The following sentence is included in the limitations section, "papers included in this review are varied, so they do not allow for quantitative synthesis." Kindly clarify.
Who completed the critical appraisal of all the included papers? The score for each included paper based on the JBI checklist could be presented in a table as part of the supplementary material.
One of the biological factors mentioned is "brain anatomical". Kindly explain.
Limitations of the review and limitations of the included studies need to be described much more elaborately. There are multiple limitations of this study/review which are not discussed at all.
It will be good to compare the findings of this review with other similar studies.
Results from individual papers are presented without a clear high-level synthesis of these findings.
The aim of this review is to identify the research gaps, but this doesn’t seem to be covered anywhere in the paper.

Are the rationale for, and objectives of, the Systematic Review clearly stated?

No
Are sufficient details of the methods and analysis provided to allow replication by others?

Partly
Is the statistical analysis and its interpretation appropriate?

Partly
Are the conclusions drawn adequately supported by the results presented in the review?

No

Competing Interests

Rahul Shidhaye is supported by India Alliance (DBT-WELLCOME Trust) intermediate career fellowship in clinical and public health research.

Reviewer Expertise

Depression, Anxiety Disorders, Elderly, Pregnant women, Yoga, Implementation Science

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Responses (2)

Author Response

14 Feb 2024

Yanti Harjono Hadiwiardjo , Faculty of Public Health, University of Indonesia, Depok, 10430, Indonesia

One of the key areas of focus in this revision has been the enhancement of the synthesis level in our article. We have made concerted efforts to this revision. By meticulously reorganizing and rephrasing sections of the manuscript, we have aimed to present a more cohesive and integrated narrative. Additionally, we have addressed your recommendation regarding the introduction of a JBI score. We have now included this score as a vital component of our methodology, providing a transparent and standardized measure of the quality and reliability of our research.

View more View less

Competing Interests

No competing interests were disclosed.

Author Response

14 Feb 2024

Yanti Harjono Hadiwiardjo , Faculty of Public Health, University of Indonesia, Depok, 10430, Indonesia

After the author reviews it further, what the author means by individual contribution is if a person already knows these risk factors so they can be prevented, and the incidence of depression can decrease. The author changed the paragraph to “A greater understanding of the individual factors of biological, psychological, and social risk factors can have a big impact on the adoption of preventive actions to lower the population's risk of depression.”
Done for submission, the article re-structured based on the PRISMA guidelines.
The selection of the last 10 years for research is driven by the need to focus on recent and relevant information. This time frame allows us to capture the most up-to-date developments, trends, and insights in the field. The requirement for articles to be written in English and published between 2011 and 2021 further ensures that the sources are contemporary and provide valuable insights within a reasonable time span. This approach enhances the accuracy and relevance of the information gathered for the study.
After reviewing it again, the author revised the limitations sections in the article to be “The limitation of the results of this systematic review is that most papers do not clearly identify the confounding factor so it cannot be determined whether there is bias in the study. Therefore, we discuss the results narratively in order to provide a big picture of the topic.”
Completed for submission, the article includes a paper based on JBI checklist scores as an attachment.
The means of brain anatomical is like a history of trauma, infectious diseases and other abnormalities in the brain.
The limitation of the results of this systematic review is that most papers do not clearly identify the confounding factor so it cannot be determined whether there is bias in the study. Therefore, we discuss the results narratively in order to provide a big picture of the topic.
Thank you for the suggestion, the author will add the section comparing the findings of this review with other similar studies.
The author had limited time, so he did not have time to carry out a meta-analysis.
This article aims to identify research gaps, which means the authors want to analyze current risk factors. The reason is the author feels that the risk factors for depression are different between now and then.

View more View less

Competing Interests

No competing interests were disclosed.

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Reviewer Report

24 Views

16 Dec 2022 | for Version 1

Acharaporn Seeherunwong, Department of Mental Health and Psychiatric Nursing, Mahidol University, Nakhon Pathom, Thailand

24 Views Cite this report Responses(2)

Approved With Reservations

The title: I suggest using “A systematic review” instead of “A systematic literature review”.
Introduction section: In the 1st paragraph, "In Indonesia, citizens 60 years old or older have reached about 25.7 million people" should be revised to calculate to be a percentage of the total population. As a result, the amount of elderly in Indonesia is comparable to the proportion of elderly in the UK and other countries worldwide.
Result: The outcome has varied the severity of depressive symptoms. I suggest categorizing the paper into two groups, as the outcomes differ in severity. The first group is the elderly diagnosed with MDD or depressive disorder (article nos. 2, 6, 9,13, 30). The second one is elderly with depressive symptoms who were not diagnosed with depressive disorders. The associated factors may be different as well.
Please separate the result section from the discussion section. In addition, the authors should find previous studies to explain the results.

Are the rationale for, and objectives of, the Systematic Review clearly stated?

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

Yes
Is the statistical analysis and its interpretation appropriate?

Not applicable
Are the conclusions drawn adequately supported by the results presented in the review?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Depression, mental health, nursing

Respond to this report

Responses (2)

Author Response

14 Feb 2024

Yanti Harjono Hadiwiardjo , Faculty of Public Health, University of Indonesia, Depok, 10430, Indonesia

View more View less

Competing Interests

No competing interests were disclosed.

Author Response

14 Feb 2024

Yanti Harjono Hadiwiardjo , Faculty of Public Health, University of Indonesia, Depok, 10430, Indonesia

The title the title has been changed to "Biopsychosocial factors associated with depression in the elderly: A systematic review"
Introduction section: In the 1st paragraph changed to "Demographic Profiles and Implications of the Top 10 Countries with the Highest Number of People Aged 65+ in 2020" delves into a significant global demographic shift observed in the year 2020 with calculations conducted by ESCAP based on the United Nations' Department of Economic and Social Affairs, Population Division (2019). The data reveals the following key insights China emerged as the country with the largest elderly population, with a staggering 172,262 individuals aged 65 and above, representing 46.05% of its total population, India follows closely, with 90,720 seniors, constituting 24.25% of the population, Japan recorded 35,916 elderly citizens, making up 9.60% of its populace, The Russian Federation reported 22,633 seniors, accounting for 6.05% of its total population, Indonesia had 17,219 elderly individuals, representing 4.57% of the population, Pakistan's elderly population reached 9,606, making up 2.56% of its total, Thailand reported 9,044 seniors, equivalent to 2.41% of its population, Bangladesh recorded 8,608 elderly citizens, constituting 2.30% of its populace and Korea reported 8,096 elderly individuals, representing 2.16% of the total population.
Regarding categorizing the paper into two groups, the author feels objections and does not want to categorize it into two groups. Just following the initial research with the expected results as of now.
In the latest and revised article, the author has categorized the results and discussion into different sections according to the reviewer's input.

View more View less

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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Biopsychosocial factors associated with depression in the elderly: A systematic literature review

Abstract

Keywords

Introduction

Objectives

Methods

Results and discussion

Figure 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram.

Figure 2. Origin of included studies.

Figure 3. Design of included studies.

Figure 4. Year of publication for included studies.

Figure 5. Critical appraisal based on Joanna Briggs Institute (JBI) checklist.

Table 1. Data extracted from eligible studies.

Biological factors

Psychological factors

Social factors

Limitations

Conclusions

Data availability

Underlying data

Extended data

Reporting guidelines

Acknowledgements

References

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