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. 2022 Dec 7;8(12):e12148. doi: 10.1016/j.heliyon.2022.e12148

Gender-based depression factors of older adults living alone during the COVID-19 pandemic: A cross-sectional and secondary data approach

SuJung Jung 1,∗
PMCID: PMC9726648  PMID: 36510561

Abstract

The coronavirus disease 2019 (COVID-19) pandemic negatively affected the mental health of older adults living alone. This study aimed to examine the differences in factors that influence depression among older adults based on gender. This study was a cross-sectional study employing the secondary data of 3581 older adults living alone at the early stage of COVID-19, collected from the 2020 Korea Community Health Survey, and used multiple linear regression analyses to identify factors associated with depression. We found that women had a higher level of depressive status than men. Low subjective health status was most significantly related to depression in both older men and older women. For women, body mass index and more changes in daily life due to COVID-19 were predictors of depression. Conversely, for men, a lower level of monthly income and smoking were significant predictors of depression. Depressive status caused by COVID-19 was likely to be frailer for older women who were living alone. There were differences in the factors related to depression due to COVID-19 by gender.

Keywords: Depression, COVID-19, Living alone, Gender

Highlights

  • •

    Older Korean women living alone were more vulnerable than men to depression during the pandemic.

  • •

    Determinants of depression among older adults living alone differ by gender.

  • •

    These gender-based differences suggest the pertinence of gender-specific preventive interventions.

Depression; COVID-19; Living alone; Gender.

1. Introduction

In March 2020, the World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19) a pandemic (WHO, 2021). The pandemic led to increased physical and mental health issues (Morrow-Howell et al., 2020). In particular, mental health was aggravated by social distancing. Depression is one of the most common mental disorders. Based on the epidemiological findings, older adults from Koreahave higher prevalence rates of major depressive disorder than those from Western countries and other Eastern countries (Park and Kim, 2011). Even before the pandemic, researchers had found that depression had higher rates among older adults living alone due to a lack of family relationships and social support than among those who were not living alone (Bruce and McNamara, 1992; Kim et al., 2018). Many studies on depression have been conducted among older adults living alone, especially women with long life expectancy and relatively high depressive tendencies (Lee and Kim, 2016; Won and Lee, 2016; Kim, 2015; Hong et al., 2021).

Living alone in late life has been a long-standing concern as life expectancy increases worldwide (Esteve et al., 2020; Reher and Requena, 2018). Among the related factors with the prevalence of older adults living alone, national economic status is also one of the associated predictos (Reher and Requena, 2018). Moreover, mostly women older adults living alone are considered as an matter in later life due to live long than men (Esteve et al., 2020). In Korea, the proportion of older adults living alone among the total older adult population gradually increased from 16% in 2000 to 19.5% in 2022 (Statistics Korea, 2022a, 2022b). With the number of older adults increasing, 35.1% of households now comprise older adults living alone (Statistics Korea, 2021).

Among older single-person households, the proportion of older men living alone is expected to rise from 28.3% in 2021 to 35.9% in 2047, while the proportion of older women living alone is expected to decrease from 71.7% in 2021 to 64.1% in 2047 (Statistics Korea, 2021). The degree of depression among older men living alone is significantly higher than that among older women living alone (Girgus et al., 2017; Ko et al., 2019). The COVID-19 pandemic has been prolonged, and 65.8% of older Koreans living alone responded that they were depressed (Namkung, 2021). COVID-19 induced restrictions affected the interactions and inclusion of older adults living alone in society. Although the ratio of the older adults living alone in Korea continues to change and has been exposed to a long-term pandemic situation, the latest evidence for gender-based depression in the older adults living alone is still a lacking.

Older Koreans living alone had different risk factors for depression compared to those living with others (Kim et al., 2018). Previous studies report conflicting results with factors related to depression among older adults living alone. Specifically, these include psychosocial factors such as social network satisfaction and subjective health status in older men living alone (Choi and Lee, 2022). Similarly, in a study of older adults living alone, Kim (2015) found that subjective health status was significantly correlated with depression. Conversely, Hong et al. (2021) reported that subjective health status was only related to depression in older women living alone, and there were differences in factors depending on gender. Many studies have only focused on what variables predict depression in a particular gender (Girgus et al., 2017). Although gender is a factor related to depression in older adults living alone (Kim et al., 2018), it is difficult to draw a concrete conclusion about what other factors are related to depression in older adults based on gender.

Older adults living alone experience a disconnection from social networks, suffer from economic poverty, and are at high risk of being isolated from the public security system (Kwon, 2019). Such isolation increases depression, which can lead to further isolation from society by homeboundness (Kim and Jung, 2022). The lack of resources and limited support also leaves health care vulnerable (Haslbeck et al., 2012). The main purpose of this study was to examine the differences in factors associated with depression in older Koreans living alone during the COVID-19 era. The specific objectives of study were to assess (a) the differences in depression depending on gender and other participant characteristics and (b) determinants of depression among older adults living alone by gender. This study’s findings contribute to future improvement of gender-based interventions for the mental health of older adults living alone.

2. Methods

2.1. Design

This cross-sectional study used secondary data from the 2020 Korea Community Health Survey to identify the factors related to depression, based on gender, through the COVID-19 experiences of older adults living alone. The Korea Community Health Survey is organized by the Korea Disease Control and Prevention Agency. It is conducted annually to calculate the health statistics necessary for establishing local health and medical plans (KDCA, 2021). This survey typically targets about 900 local residents of the community (aged 19 and over) per public health center, of which there are 225 total. In the 2020 survey, 142 items across 18 categories including temporary questions related to COVID-19 experiences were investigated. Thorough quarantine regulations were followed due to the COVID-19 pandemic (Appendix 1). The Korea Community Health Survey was conducted from August 16 to October 31, 2020, in which a trained surveyor directly visited the sample household and conducted one-on-one interviews using computer-assisted (laptop) personal interviewing. The interviews took an average of 20–30 min per participant.

2.2. Study participants

In this study, data from 842 men to 2739 women aged 65 years or older and who were living alone were extracted from the 229,269 subjects who participated in the 2020 Korea Community Health Survey.

2.3. Measurements

2.3.1. Background characteristics

Demographic, social and economic conditions (age, education, and monthly income), and physical characteristics (hypertension, diabetes, and subjective health status) were evaluated to determine the background characteristics of the participants. Age, education, and monthly income were measured on a continuous scale. Additionally, the chronic diseases that can be investigated through the 2020 Korea Community Health Survey are hypertension and diabetes, which are categorized as either diagnosed by a doctor and not diagnosed. We used a single item to measure subjective health status: “How would you rate your current health status, in general?” WHO recommended five options: very good, good, fair, bad, and very bad (de Bruin et al., 1996) The higher the score, the better the subjective health status.

2.3.2. Depression

To measure depression, the Korean version of the Patient Health Questionnaire-9 (PHQ-9; Choi et al., 2007) tool was used in the 2020 Korea Community Health Survey. The PHQ-9 evaluates nine items on a scale of 0–3, with a total score of 27 points; higher scores indicate higher levels of depression. The Cronbach’s alpha in this study was 0.828.

2.3.3. Health-related behaviors

“Never smoking,” “no heavy drinking,” and “not obese” were measured to assess health-related behaviors (KDCA, 2021). Current nonsmoking was defined as respondents’ self-reporting of smoking 100 cigarettes or less during their lifetime or having smoked at the time of the survey. Heavy drinking was defined as more than 7 drinks for men and 5 drinks for women per drinking session at least twice a week during the previous year. Body mass index (BMI) was used to evaluate normal body weight based on self-reported height and weight. BMI was classified as less than 25.0 kg/m2 and 25kg/m2 and more (KDCA, 2021; Statistics Korea, 2022a, 2022b).

2.3.4. COVID-19 experiences

Self-quarantine or admission due to COVID-19 and daily life changes were measured. Daily life changes were investigated using the question “What is your current state of life, with 100 points being the state of daily life before COVID-19 and 0 points being the complete suspension of daily life?” This was a question to verify how much the average change in recent daily life compared to before the COVID-19 pandemic’s outbreak in January 2020 (KDCA, 2021). A lower score indicated more negative changes in daily life due to COVID-19.

2.4. Ethical considerations

The 2020 Korea Community Health Survey was obtained without personal identifying information after approval from the Korea Institute for Health and Social Affairs. In addition, this study was approved by the Institutional Review Board (IRB No.: SMU-EX-2022-07-003) of Semyung University.

2.5. Data analysis

IBM’s SPSS Statistics (version 23.0) was used for the statistical analyses in this study. To explain the characteristics of the participants, descriptive statistics included means with standard deviations (SDs) for numeric variables and proportions with percentages for categorical variables. To examine the differences in depression according to participant characteristics by gender, an independent t-test and analysis of variance (ANOVA) were used for numeric data and Pearson’s χ2 test for categorical data, respectively. For ANOVA, the Bonferroni post-hoc test was used. Multiple linear regression was used to identify the factors related to depression by sex. Before running the multiple linear regression, we conducted a correlation analysis. In multiple linear regression, covariates (age, educational level, monthly income, diagnosed hypertension or diabetes, subjective health status, smoking, drinking, BMI, daily life change due to COVID-19) were adjusted. Data analyses were conducted in accordance with the guidelines provided by the Korea Disease Control and Prevention Agency (KDCA, 2021). By applying listwise deletion, less than 10% of missing cases were excluded from the analysis (Hair et al., 2006; KDCA, 2021). p values <.05 were considered statistically significant.

3. Results

3.1. Participants' characteristics based on gender

The participants' characteristics according to gender are presented in Table 1. Among the older adults living alone, women were more depressed than men. Furthermore, women were older, had a lower education level, and were poorer than men. Regarding physical characteristics, women had more higher rates of hypertension and lower subjective health status than men. On the other hand, in health-related behaviors, men included more current smokers and heavy drinkers than women. Moreover, regarding BMI, there were more women than men weighing at 25.0 kg/m2 and more. Women’s daily life changes were higher than men’s due to COVID-19.

Table 1.

Participants' characteristics according to gender.

Classification Variables Categories Total (n = 3581) n (%) Men (n = 842) Women (n = 2739) χ2/t(p)∗
Background characteristics Age 65–74 1749 (48.8) 506 (60.1) 1243 (45.4) 55.799 (.000) ∗
≥75 1832 (51.2) 336 (39.9) 1496 (54.6)
Mean (SD) 75.13 (6.690) 73.41 (6.510) 75.65 (6.656) -8.618 (.000) ∗
Education None (a) 516 (14.4) 36 (4.3) 480 (17.5) 397.760 (.000) ∗
Elementary ≥ (b) 1418 (39.6) 183 (21.8) 1235 (45.1)
Middle (c) 677 (18.9) 199 (23.7) 478 (17.5)
≥High (d) 968 (27.0) 422 (50.2) 546 (19.9)
Monthly income (KRW10,000) Mean (SD) 94.93 (84.771) 106.41 (95.800) 91.47 (80.854) 4.023 (.000) ∗
Hypertension Yes 2005 (56.0) 401 (47.6) 1604 (58.6) 31.698 (.000) ∗
No 1575 (44.0) 441 (52.4) 1134 (41.4)
Diabetes Yes 872 (24.4) 217 (25.8) 655 (23.9) 1.503 (.472)
No 2708 (75.6) 625 (74.2) 2083 (76.0)
Subjective health status Excellent (a) 120 (3.4) 58 (6.9) 62 (2.3) 58.534 (.000) ∗
Very good (b) 937 (26.2) 252 (29.9) 685 (25.0)
Good (c) 1478 (41.3) 330 (39.2) 1148 (41.9)
Fair (d) 799 (22.3) 153 (18.2) 646 (23.6)
Poor (e) 247 (6.9) 49 (5.8) 198 (7.2)
Health-related behaviors Smoking Yes 299 (8.3) 236 (28.0) 63 (2.3) 557.088 (.000) ∗
No 3282 (91.7) 606 (72.0) 2676 (97.7)
Drinking Yes 87 (2.4) 65 (7.7) 22 (0.8) 129.969 (.000) ∗
No 3494 (97.6) 777 (92.3) 2717 (99.2)
BMIa <25 2435 (68.0) 605 (71.9) 1830 (66.8) 18.247 (.000) ∗
≥25 1042 (29.1) 229 (27.2) 813 (29.7)
Mean (SD) 23.54 (3.144) 23.44 (2.878) 23.57 (3.224) -1.133 (.257)
COVID-19 experiences Self-quarantine or admission due to COVID-19 Yes 8 (0.2) 0 8 (0.3) 2.465 (.116)
No 3573 (99.8) 842 (100.0) 2731 (99.7)
Daily life changeb 0 82 (2.3) 27 (3.2) 55 (2.0) 20.410 (.026) ∗
10 108 (3.0) 21 (2.5) 87 (3.2)
20 182 (5.1) 42 (5.0) 140 (5.1)
30 322 (9.0) 61 (7.2) 261 (9.5)
40 247 (6.9) 52 (6.2) 195 (7.1)
50 973 (27.2) 219 (26.0) 754 (27.5)
60 324 (9.0) 74 (8.8) 250 (9.1)
70 432 (12.1) 97 (11.5) 335 (12.2)
80 385 (10.8) 101 (12.0) 284 (10.4)
90 219 (6.1) 58 (6.9) 161 (5.9)
100 247 (6.9) 76 (9.0) 171 (6.2)
Mean (SD) 56.18 (24.311) 58.02 (25.438) 55.61 (23.930) 2.416 (.016) ∗
Depression Mean (SD) 3.00 (3.913) 2.72 (3.781) 3.09 (3.949) -2.428 (.015) ∗
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Note.a1.0% (8 cases) missing data in men, 3.5% (96 cases) missing data in women, b1.7% (60 cases) missing data in total, 1.7% (14 cases) missing data in men, 1.7% (46 cases) missing data in women, ∗p < .05.

3.2. Differences in depression depend on gender by participants' characteristics

Table 2 displays the differences in depression depending on gender by participants' characteristics. Both women and men were more depressed with lower levels of education, poor subjective health status, and current smoking. However, only women with older age, hypertension and diabetes were more likely to be depressed.

Table 2.

Differences in depression depending on gender and participants' characteristics.

Classification Variables Categories Depression Mean (SD)
Men (n = 842) t/F(p)∗ Women (n = 2739) t/F(p)∗
Background characteristics Age 65–74 2.71 (3.812) -.100 (.920) 2.76 (3.686) -3.948 (.000) ∗
≥75 2.73 (3.739) 3.36 (4.136)
Education None (a) 3.69 (4.458) 4.500 (.004) b > d 3.87 (4.618) 9.683 (.000) ∗ a>b > c > d
Elementary ≥ (b) 3.26 (4.158) 3.09 (3.793)
Middle (c) 2.99 (4.100) 2.86 (3.759)
≥High (d) 2.26 (3.325) 2.60 (3.720)
Hypertension Yes 2.86 (3.777) 1.074 (.283) 3.24 (4.047) 2.330 (.020) ∗
No 2.58 (3.784) 2.88 (3.799)
Diabetes Yes 2.85 (3.520) .596 (.552) 3.28 (4.220) 2.784 (.005) ∗
No 2.67 (3.869) 2.97 (3.850)
Subjective health status Excellent (a) 0.98 (1.395) 58.783 (.000) a<b < c < d < e 1.34 (3.219) 143.117 (.000) ∗ a<b < c < d < e
Very good (b) 1.40 (2.016) 1.80 (2.642)
Good (c) 2.32 (2.910) 2.32 (2.857)
Fair (d) 4.72 (4.986) 4.65 (4.631)
Poor (e) 7.98 (5.932) 7.48 (5.834)
Health-related behaviors Smoking Yes 3.36 (4.364) 2.798 (.005) 4.22 (4.467) 2.304 (.021) ∗
No 2.47 (3.500) 3.06 (3.933)
Drinking Yes 2.46 (3.496) -.565 (.572) 3.41 (2.754) .380 (.704)
No 2.74 (3.805) 3.09 (3.957)
BMIφ <25 2.67 (3.611) .435 (.663) 2.86 (3.782) -1.574 (.116)
≥25 2.80 (4.071) 3.12 (3.967)
COVID-19 experiences Self-quarantine or admission due to COVID-19 Yes 0 - 1.88 (2.416) -.872 (.383)
No 2.72 (3.781) 3.09 (3.952)
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Note.φ2.9% (104 cases) missing data, ∗p < .05.

3.3. Factors related to depression in men and women living alone

The models of older adults living alone were statistically significant and explained 20.7% and 15.4% of the variance in depression in men and women, respectively (Table 3). The results of the regression analysis showed that low subjective health status was a significant predictor of depression in men and women living alone; moreover, subjective health status was the strongest impact factor among the predictors in both men and women with depression. Conversely, a lower level of monthly income and current smoking were significant predictors of depression in men living alone. For women living alone, less than 25.0 kg/m2 and more changes in daily life due to COVID-19 were significant predictors of depression.

Table 3.

Factors related to depression in men and women living alone.

Predictors β
 SE
 t
 p∗
 β
 SE
 t
 p∗
Men (n = 792) Women (n = 2638)
(Constant) 1.851 5.576 .000 1.905 5.003 .000
Background characteristics Age -.023 .020 -.705 .481 .032 .012 1.661 .097
Education (None = 0) Elementary .030 .646 .440 .660 -.028 .205 -1.092 .275
Middle .022 .642 .306 .760 -.020 .251 -.806 .420
High -.014 .623 -.174 .862 -.014 .254 -.539 .590
Monthly income -.096 .001 -2.901 .004∗ -.031 .001 -1.627 .104
Hypertension (Yes = 0) .005 .248 .142 .887 .001 .141 .049 .961
Diabetes (Yes = 0) .029 .285 .879 .380 -.003 .160 -.165 .869
Subjective health status -.413 .128 -12.399 .000∗ -.369 .080 -19.696 .000∗
Health-related behaviors Smoking (Yes = 0) -.103 .278 -3.142 .002∗ -.034 .475 -1.868 .062
Drinking (Yes = 0) .005 .468 .168 .866 -.012 .786 -.679 .497
BMI (25≥ = 0) .002 .153 .075 .940 .057 .052 3.097 .002∗
COVID-19 experiences Daily life change -.040 .005 -1.243 .214 -.050 .003 -2.769 .006∗
R2 = .207, F = 18.214, p = .000 R2 = .154, F = 41.131, p = .000
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Note. Missing data were excluded listwise; Men) Durbin-Watson: 423, VIF 1.023–6.589, Women) Durbin-Watson: 303, VIF 1.018–2.102, ∗p < .05.

4. Discussion

This study examined the differences in factors that influence depression among older Korean adults living alone based on gender during COVID-19. We showed that depressive status was likely to be frailer for older women living alone than older men living alone. With related factors to depression, there were differences by gender due to COVID-19. Nevertheless, low subjective health status was the most significantly related factor to depression in both older men and older women.

Social distancing is a preventive measure against COVID-19. However, it isolates older adults from the external environment, thus leading to emotional dysfunction such as depression (Tang et al., 2021). Owing to prolonged COVID-19, 65.8% of older adults living alone responded that they felt depressed (Namkung, 2021). Although the number of older adult men living alone is gradually increasing, evidence of depression-related factors that differ by gender has been insufficient. This study’s findings provide some significant factors of depression identified among older adults living alone at the early stage of COVID-19.

In this study, older women living alone experienced more severe depressive status than older men living alone during COVID-19. Our findings are similar to those of Kim et al. (2018). In contrast, some studies have reported higher levels of depressive symptoms in men than in women (Ko et al., 2019; Hong et al., 2021). However, some researchers have proposed that a gender difference in living alone might be a predictor of the gender difference in depression (Girgus et al., 2017). Thus, to interpret the conflicting findings, further investigation is required, considering the cause of living alone (e.g., widowed or divorced) and the duration of living alone. In addition, it is necessary to confirm COVID-19’s effect on depressive status through longitudinal data.

Similar to previous studies, our findings confirmed that women who are living alone were older, had lower education, lower monthly income, and poorer subjective health than men (Hong et al., 2021; Lee and Lee, 2021). Conversely, in men, lower monthly income was associated with depression. Although men living alone are considered economically vulnerable because of retirement or unemployment, social network satisfaction and self-esteem have significant mediating effects of socioeconomic status on depression (Choi and Lee, 2022). Therefore, for older men living alone after retiring, interpersonal reserves (social network satisfaction, self-esteem, and perceived health status) are important for preventing their depression (Choi and Lee, 2022). Furthermore, many older adults had to stop working or change their employment patterns due to the COVID-19 pandemic (Namkung, 2021). Taken together, it is necessary to review job policies for older men living alone to ensure adequate income and social network maintenance for reducing and preventing depression.

A low level of subjective health status was a common indicator that increased depressive symptoms in both men and women older adults living alone, which is similar to previous reports (Choi and Lee, 2022; Hong et al., 2021; Kim, 2015). The high subjective health status of older adults during the COVID-19 pandemic was related to positive emotions such as gratitude and contentment (Fingerman et al., 2021). Subjective health status is considered an age-related factor necessary for maintaining independent living in late life (Zivin et al., 2013). In addition, social isolation was associated with poorer subjective health status in older adults (Ward et al., 2019). Older adults who live alone were less likely to see others in person during the pandemic (Fingerman et al., 2021) and therefore, were at risk of isolation. Thus, it is necessary to assess subjective health status at an early stage to intervene and prevent depression in older adults living alone beyond the COVID-19 pandemic.

Among the health-related behaviors predicting depression, smoking was associated with depression in older men living alone. Living arrangements moderated the association between depressive symptoms and current smokers (Kim et al., 2018). Moreover, smoking is considered a determinant of psychosocial health, as smokers are more likely to live alone and increase social isolation (Philip et al., 2022). Owing to COVID-19, there are changes in health-related behaviors among older Koreans (decreased physical activity, decreased sleep duration, and decreased number of meals; see Namkung, 2021). The results of maintaining normal weight in older women living alone were correlated with depression in this study, which may be related to the marked decrease in the number of meals among older women without spouses after COVID-19 (Namkung, 2021).

Older women living alone felt more atrophy in their daily life after COVID-19 than before, and this factor was related to depression. This confirms Ryu et al.’s (2022) results finding that social activity frequency was greater in older women than men living alone during the pandemic in Korea. Older adults living alone may be more reactive to social distancing during COVID-19 than older adults living with others since living alone was associated with more positive emotions when able to engage in in-person contact (Fingerman et al., 2021). In particular, older women living alone had a higher level of depression the less they met close people (Hong et al., 2021; Kim, 2015). In the literature reported during the COVID-19 pandemic, decreased social life and interpersonal interactions were associated with increased depression (Lebrasseur et al., 2021). Therefore, in the face of the long-term pandemic, it is necessary to adopt new ways (such as communication technology) to protect older adults' mental health. The findings of this study with a large sample may help improve interventions that prevent depression for older adults living alone according to gender, thereby maintaining and improving psychological function.

This study had some limitations. First, with cross-sectional data, it was not possible to directly compare the degree of change in depression before and after the pandemic. Second, although the PHQ-9 is a useful tool because of the minimal number of items and easy scoring (Kroenke et al., 2001), there is a need for a depression tool that can assess the depression of older adults living alone. Third, our dataset did not include severity of depression, treatment histories, or medication. Finally, we were unable to include any variables that reflected the details of living alone, such as duration of or reasons for living alone. Further research should consider these variables in longitudinal surveys, since the delayed impact of the COVID-19 on depression needs to be verified. This study was conducted on older adults living alone, a vulnerable group due to the lockdown by COVID-19. Researchers can compare the diversity of depression among groups (older adults living alone versus older adults not living alone, or according to generation) to expand our findings. Social support, government care management systems, and economic support may have positive effects on the mental health of older adults living alone during the COVID-19. Therefore, it is important to conduct further research on and prepare specific community-based non-contact care policies (e.g., communication via ICT technologies) for older adults living alone to prevent depression related to COVID-19 in the future.

5. Conclusion

This study aimed to investigate the factors influencing depression among older Korean adults living alone according to gender during COVID-19. We found that low subjective health status was most significantly associated with depression in both older men and older women living alone. However, BMI and more changes in daily life due to COVID-19 were specifically related to depression in older women living alone. For older men living alone, a lower level of monthly income and smoking status were significant factors of depression. Based on these findings, assessing and intervening with the identified influencing factors is essential for maintaining the psychological function of older adults living alone. In particular, tailored interventions that reflect these factors are necessary to address individual needs by gender, thereby supporting the mental health of older adults living alone in a post-COVID-19 era.

Declarations

Author contribution statement

SuJung Jung: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Funding statement

This work was supported by Semyung University [Semyung University Research Grant of 2022].

Data availability statement

The authors do not have permission to share data.

Declaration of interest’s statement

The authors declare no conflict of interest.

Additional information

No additional information is available for this paper.

Acknowledgements

Not applicable.

Appendix A. Supplementary data

The following is the supplementary data related to this article:

Supplemental file_102922
mmc1.docx (51.3KB, docx)

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