Depressive symptoms and quality of life

O R I G I N A L R E S E A R C H

Correlation Between Depressive Symptoms And

Quality Of Life, And Associated Factors For

Depressive Symptoms Among Rural Elderly In

Anhui, China This article was published in the following Dove Press journal:

Clinical Interventions in Aging

Jian Rong 1, *

Guimei Chen 1, *

Xueqin Wang 2

Yanhong Ge 1

Nana Meng 1

Tingting Xie 1

Hong Ding 1

1Department of Health Services

Management, School of Health

Management, Anhui Medical University,

Hefei 230032, People’s Republic of China; 2Department of Medical Engineering, The

Second Hospital of Anhui Medical

University, Hefei 230601, People’s Republic of China

*These authors contributed equally to

this work

Purpose: We aimed to assess the current status of depressive symptoms and quality of life

(QoL) among rural elderly in central China (Anhui Province) and explore their correlation

and associated factors for depressive symptoms.

Methods: A multi-stage random sampling method was used to obtain 3349 participants

(aged ≥60): 1206 poor and 2143 non-poor. The 30-item Geriatric Depression Scale (GDS-30)

and five-dimensional European quality of health scale (EQ-5D) were employed to evaluate

depressive symptoms and QoL, respectively.

Results: The prevalence of depressive symptoms was 52.9%, and that in the poor group

(62.3%) was significantly higher than the non-poor group (47.6%). The GDS-30 score was

12.40 ± 7.089, and the poor group scored significantly higher (14.045 ± 6.929) than the non-

poor group (11.472 ± 7.011). The EQ-5D score was 0.713 ± 0.186, and the poor group (0.668

± 0.192) scored significantly lower than the non-poor group (0.738 ± 0.178). There was a

significant negative correlation between depressive symptoms and QoL (r = −0.400, P-value

<0.05). The following factors were associated with depressive symptoms: poverty, low

EQ-5D score, female gender, older age, illiteracy, unemployed, chronic diseases, and hospi-

talization in previous year.

Conclusion: Rural elderly in central China have a high prevalence of depressive symptoms

and low QoL. Poverty was associated with a higher prevalence of depressive symptoms and

lower QoL.

Keywords: depressive symptoms, quality of life, rural elderly, central China

Introduction Aging is an inevitable social problem around the globe, and China has the world’s

largest elderly population. According to the National Bureau of Statistics, in 2018,

the population aged 60 years and over in China was 249.49 million (17.9% of the

total population), with more than two-thirds living in rural areas.1 It was predicted

that the proportion of elderly persons aged 60 and over in China will exceed 30% of

the total population by 2050.2 With this rapid growth, increasingly more elderly

persons are suffering from age-related mental diseases. Depression is the most

common mental disorder found in the elderly population around the world, putting

tremendous pressure on the social health service system.3 In addition, with the

medical and social developments for the aging population, elderly persons seek to

Correspondence: Hong Ding School of Health Management, Anhui Medical University, No. 81 Meishan Road, Hefei 230032, People’s Republic of China Tel +86 551 516 1220 Fax +86 551 512 8754 Email [email protected]

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have not only a long life but also high quality of life

(QoL). Thus, researchers are increasingly interested in

assessing depressive symptoms and QoL in older adults.

Depression is an important public health problem in the

elderly population, as late-life depression might have ser-

ious consequences, such as an increased risk of suicide.4 In

addition, it is anticipated that depression will become the

second most common cause of disability in the world by

2020.5 The worldwide prevalence of depressive disorders

varies between 4.5% and 37.4%.6 However, in recent

years, especially in rural China, the prevalence of geriatric

depression far exceeds this rate. A study on geriatric

depression in rural China showed a prevalence rate of

30.8%.7 Previous research found that being female, older,

illiterate, solitary, and cognitively impaired were risk fac-

tors for geriatric depression.8–11

The QoL of elderly persons has become another impor-

tant public health problem because of demographic changes

as a result of aging. Studies found that the QoL scores of

elderly persons were lower than those of non-elderly

individuals.12 Although QoL has been widely investigated

for many years, there are scarce relevant research data on the

QoL of the rural elderly population in central China. Most

previous studies were mainly based on Chinese urban resi-

dents or special disease groups. Assessment scales mainly

included the 12-Item Short-Form Health Survey (SF-12), the

36-Item Short-Form Health Survey (SF-36), and the World

Health Organization Quality of Life (WHOQOL)-BREF and

mainly aimed to identify factors influencing QoL.13–15

Previous studies revealed that QoL is an important

factor affecting depression in the elderly.16 However, the

impact of QoL on the psychology of the elderly is difficult

to assess. There is currently a feasible method to assess the

correlation between depression and QoL.17 However, there

is limited research on this correlation among the rural

elderly population of central China.

Anhui Province is located in the central part of China.

The terrain consists of plains, hills, and mountains, with a

geographical area of 140,100 km2. The per capita gross

domestic product was 47,712 CNY (about 7210 dollars) in

2018,18 and the level of economic development was at a

medium level in China. At the end of 2018, the resident

population of the province was 63.236 million, of which

the proportion aged 60 and over was 18.34%, and the propor-

tion aged 65 and over was 12.97%.19 As in other provinces in

China, aging has become a serious social problem. Anhui

Province is the first province in China to implement a com-

prehensive reform of the primary health care system.

Compared with western China, the health service level in

Anhui Province is good, but it is lower relative to eastern

China.20

We conducted this study to assess the current status of

depressive symptoms and QoL among rural elderly (aged

≥60) in central China (Anhui Province) and explore their

correlation and associated factors for depressive symp-

toms. We believe our findings will provide a scientific

theoretical reference for further improving the physical

and mental health of rural elderly, and promoting grass-

roots public health services in central China.

Methods Study Design And Sample A multi-stage sampling survey method was used to ran-

domly select one county in the northern, central, and

southern regions of Anhui Province in central China,

respectively, from January to July 2018 for the current

study. In each county, two towns were randomly selected,

in each of which three villages were randomly chosen.

This made a total of 18 villages as survey sites. In each

of the selected villages, 50 households were randomly

selected according to the list of poor households (the per

capita net income of rural households in China was less

than 2736 CNY in 2013). Simultaneously, non-poor survey

households were selected among the neighbors of poor

households in a ratio of 1:1.5. Participants were elderly

persons (aged ≥60) from the poor and non-poor house-

holds. Among the households surveyed, all of the elderly

aged 60 years and over were the participants. The inves-

tigation was conducted with the assistance of local health

care committees, village committees, and village doctors.

Questionnaires were completed through a face to face

interview conducted by specially trained investigators vis-

iting the participants’ homes.

We surveyed 3491 elderly persons (900 poor house-

holds and 1350 non-poor households) and obtained 3349

valid questionnaires (1206 poor and 2143 non-poor elderly

respondents). The effective response rate was thus 95.93%

(3349/3491).

Persons aged 60 years and over and living at their

residence for at least 1 year participated in the survey.

Exclusion criteria included having cognitive impairments

and language communication barriers as well as being

unavailable for the investigation.

The study was conducted in accordance with the

Declaration of Helsinki and was approved by the Ethics

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Committee of Anhui Medical University. All respondents

provided written informed consent and volunteered to

participate in the survey.

Assessment Instruments 30-Item Geriatric Depression Scale (GDS-30)

The GDS-30 is a tool for measuring depressive symptoms

in elderly adults and has been widely used in different

countries around the world.21,22 Each item in the scale is a

question that respondents need to answer using “Yes” or

“No”. Scale items 1, 5, 7, 9, 15, 19, 21, 27, 29, and 30 are

scored with 1 point for “No” and 0 points for “Yes”; the

remaining 20 items are scored with 1 point for “Yes” and 0

points for “No”; thus, the total score ranges from 0 to 30

points. Previous research confirmed that the GDS-30 scale

has high sensitivity (70.6%) and specificity (70.1%) in a

Chinese sample aged 60 years and over, and internal con-

sistency was confirmed by a Cronbach’s α value of 0.890.23 Elderly individuals with a GDS-30 score higher

than or equal to 11 are considered to have depressive

symptoms.24

Five-Dimensional European Quality Of Health Scale

(EQ-5D)

The Chinese version of the EQ-5D scale was employed to

assess the QoL of respondents. Previous research con-

firmed that the scale had good reliability and validity in

a Chinese elderly sample.25 Internal consistency was con-

firmed by a Cronbach’s α value of 0.7026.26 The scale consists of the EQ-5D health state description system and

the EQ-visual analogue scale (EQ-VAS) scores. The EQ-

5D health state description system consists of five dimen-

sions: mobility (M), self-care ability (SC), usual activities

(UA), pain/discomfort (PD), and anxiety/depression (AD).

The respondents self-rate the level of problem severity in

each dimension using three levels: no problems, moderate

problems, and extreme problems, coded as 1, 2, and 3,

respectively. The EQ-VAS is a 20-cm visual scale, from 0

(representing the worst health condition in mind) to 100

(representing the best health condition in mind); respon-

dents rate their health status on that day using the most

appropriate point on the visual scale.

Considering geographic and ethnic factors, we used the

Japanese scale utility scoring system, by which the utility

score was calculated according to the following formula-

tion: U(utility scoring) = 1-(0.152 + 0.075 * M2 + 0.418 *

M3 + 0.054 * SC2 + 0.102 * SC3 + 0.044 * UA2 + 0.133

* UA3 + 0.080 * PD2 + 0.194 * PD3 + 0.063 * AD2 +

0.112 * AD3), where 0.152 is a constant term; M2, SC2,

UA2, PD2, and AD2 represent the M, SC, UA, PD, and

AD, respectively, in the second level (code 1); otherwise

the code is 0. M3, SC3, UA3, PD3, and AD3 represent the

M, SC, UA, PD, and AD in the third level (code 1);

otherwise the code is 0.27 For example, “21223” stands

for a state of having moderate problems in M, UA, and

PD, and extreme AD; U = 1-(0.152+0.075+0+0.044+0.080

+0.112) = 0.537. The higher the EQ-5D utility score, the

better the QoL; while the higher the dimension score, the

worse the dimension. The total utility score U ranges from

−0.111 to 1.

Demographic Characteristics

The survey collected key demographic information of par-

ticipants, including poverty, age, gender, education level,

profession status, number of chronic diseases, living

arrangement (others refer to living with a spouse and

unmarried children, living with a spouse and married chil-

dren, single elderly living with children, and living with

their relatives), and hospitalization within previous year.

Statistical Analysis A double data entry procedure was followed by two trained

data-entry workers using EpiData 3.1 software (EpiData

Association, Odense, Denmark). Data were analyzed using

SPSS 16.0 (SPSS, Inc., Chicago, IL, USA). A descriptive

analysis was used to describe the demographic characteris-

tics of the sample. The chi-square test was used to compare

the demographic characteristics of the two groups (i.e., poor

and non-poor). Multiple linear regression was used to adjust

for demographic characteristics. Partial correlation analysis

was used to analyze the correlation between depressive

symptoms and QoL. Binary logistic regression analysis

was used to assess the associated factors for depressive

symptoms, and the forced introduction method was used

to include the independent variables. Covariates with a P-

value < 0.2 on univariate analysis were included in multi-

variable model. A two-tailed P-value < 0.05 was considered

to be statistically significant.

Results Sample Characteristics In total, 3349 respondents comprised the effective sample,

including 1206 poor and 2143 non-poor elderly persons.

Table 1 shows the demographic characteristics of the two

groups. Age ranged from 60 to 97 years (mean age 71.17 ±

7.087 years), with the average age of the poor group

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(71.74 ± 7.121 years) being significantly higher than that

of the non-poor group (70.84 ± 7.04 years). The proportion

of males in the poor group (53.5%) was significantly

higher than that in the non-poor group (46.8%). A total

of 66.1% of the participants were illiterate, 64.1% were

unemployed, and the proportion of illiterate (69.0%) and

unemployed participants (71.0%) in the poor group was

significantly higher than that in the non-poor group (64.5%

and 60.2%, respectively).

A total of 74.0% of the participants had chronic dis-

eases, and the proportion of individuals with two chronic

diseases and three or more chronic diseases in the poor

group was significantly higher than in the non-poor group.

Moreover, 19.7% of the participants lived alone and 43.0%

lived with a spouse, and there were no significant

differences in living arrangements between the poor and

non-poor groups. Finally, 31.7% of the participants had

been hospitalized the year before the survey, and the

percentage in the poor group (39.5%) was significantly

higher than in the non-poor group (27.4%) (Table 1).

Depressive Symptoms And QoL Table 1 also shows the evaluation of the prevalence of

depressive symptoms in the survey sample, which was

52.9%. The prevalence of depressive symptoms in the

poor group (62.3%) was higher than in the non-poor

group (47.6%), and the difference between the two groups

was statistically significant (P-value <0.001).

Table 2 shows the evaluation of depressive symp-

toms and QoL in the sample. The average GDS-30

Table 1 Demographic Characteristics And Depressive Symptoms Of Respondents, N (%)

Variables Total

(n = 3349)

Poor

(n = 1206)

Non-Poor

(n = 2143)

P-Value

Age

60–69 1535 (45.8) 504 (41.8) 1031 (48.1) 0.002

70–79 1332 (39.8) 509 (42.2) 823 (38.4)

≥80 482 (14.4) 193 (16.0) 289 (13.5)

Gender

Male 1648 (49.2) 645 (53.5) 1003 (46.8) <0.001

Female 1701 (50.8) 561 (46.5) 1140 (53.2)

Education

Illiterate 2215 (66.1) 832 (69.0) 1383 (64.5) 0.009

Elementary and above 1134 (33.9) 374 (31.0) 760 (35.5)

Profession

Unemployed 2146 (64.1) 856 (71.0) 1290 (60.2) <0.001

Employed 1203 (35.9) 350 (29.0) 853 (39.8)

Chronic diseases

0 870 (26.0) 258 (21.4) 612 (28.6) <0.001

1 1231 (36.7) 445 (36.9) 786 (36.7)

2 757 (22.6) 307 (25.5) 450 (21.0)

≥3 491 (14.7) 196 (16.3) 295 (13.8)

Living arrangement

Alone 660 (19.7) 257 (21.3) 403 (18.8) 0.165

With a spouse 1440 (43.0) 499 (41.4) 941 (43.9)

Others 1249 (37.3) 450 (37.3) 799 (37.3)

Hospitalization

Yes 1063 (31.7) 476 (39.5) 587 (27.4) <0.001

No 2286 (68.3) 730 (60.5) 1556 (72.6)

Depressive symptoms

Presence 1772(52.9) 751(62.3) 1021(47.6) <0.001

Absence 1577(47.1) 455(37.7) 1122(52.4)

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score of the survey sample was 12.40 ± 7.089, and the

poor group’s score (14.045 ± 6.929) was higher than

that of the non-poor group (11.472 ± 7.011). After

adjusting for demographic characteristics, the differ-

ence between the two groups was statistically signifi-

cant (P-value <0.001).

The EQ-5D utility score for the whole sample was

0.713 ± 0.186, and the EQ-5D VAS score was 69.30 ±

16.820; the poor group’s EQ-5D utility score (0.668 ±

0.192) and EQ-5D VAS score (65.80 ± 13.159) were

lower than those of the non-poor group (0.738 ± 0.178

and 71.27 ± 18.277, respectively). For each QoL dimen-

sion, the scores of the poor group were higher than those

of the non-poor group, and the difference between the two

groups was statistically significant after adjusting for

demographic characteristics (P-value <0.001).

Correlation Of Depressive Symptoms

And QoL Table 3 shows the partial correlation analysis between

depressive symptoms and QoL. After controlling for demo-

graphic characteristics, the partial correlation analysis

showed a significant negative correlation between depres-

sive symptoms and QoL (r = −0.400, P-value <0.001), and there was also a significant negative correlation between

depressive symptoms and QoL in the poor and non-poor

groups (P-value < 0.001).

Associated Factors For Depressive

Symptoms Binary logistic regression analysis was conducted with the

presence of depressive symptoms as the dependent vari-

able, and poverty, EQ-5D score, gender, age, education,

profession, living arrangement, hospitalization in previous

year, and number of chronic diseases as independent vari-

ables. The results showed that poverty (OR =1.402), low

EQ-5D score (OR =0.010), female gender (OR =0.605),

older age (OR =1.017), illiteracy (OR =1.340), unem-

ployed (OR =1.234), suffering from chronic diseases

(OR =1.101), and hospitalization in previous year (OR

=1.445) were associated factors for depressive symptoms

among rural elderly persons. Living arrangement had no

effect on depressive symptoms (Table 4).

Discussion Depression and QoL in rural elderly persons are important

public health issues that may have a major impact on

primary health care systems. However, there are few stu-

dies examining depression and QoL among rural elderly

individuals in central China, and the correlation between

Table 2 Depressive Symptoms And QoL Scores (Mean ± SD) And Differences Between Poor And Non-Poor Groups By Multivariate Linear Regression

Variables Poor Non-Poor Total t-Valuea P-Valuea

M 0.051 ± 0.077 0.034 ± 0.057 0.041 ± 0.066 4.323 <0.001

SC 0.016 ± 0.028 0.009 ± 0.022 0.012 ± 0.025 4.455 <0.001

UA 0.034 ± 0.037 0.024 ± 0.034 0.028 ± 0.036 5.457 <0.001

PD 0.063 ± 0.040 0.052 ± 0.042 0.056 ± 0.042 5.479 <0.001

AD 0.034 ± 0.036 0.022 ± 0.032 0.026 ± 0.034 6.714 <0.001

EQ-5D 0.668 ± 0.192 0.738 ± 0.178 0.713 ± 0.187 −7.302 <0.001

EQ-5D VAS 65.803 ± 13.159 71.266 ± 18.277 69.299 ± 16.820 −8.142 <0.001

GDS-30 14.045 ± 6.929 11.472 ± 7.011 12.398 ± 7.089 6.314 <0.001

Notes: aAdjust for following demographic variables: age, gender, education, profession status, number of chronic diseases, living arrangement, and hospitalization within previous year.

Table 3 Partial Correlation Between Depressive Symptoms And QoL

Variable GDS Score

Totala Poorb Non-Poorb

r P-Value r P-Value r P-Value

EQ-5D score −0.400 <0.001 −0.365 <0.001 −0.419 <0.001

Notes: aControl variables: poverty, age, gender, education, profession, living arrangement, hospitalization within previous year, and number of chronic diseases; bControl variables: age, gender, education, profession, living arrangement, hospitalization within previous year, and number of chronic diseases.

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depressive symptoms and QoL in this population has not

been previously reported. The results of this study provide

a scientific theoretical basis and reference values for the

prevention and control of depressive symptoms in rural

elderly persons in central China.

Prevalence Of Depressive Symptoms The results of the current study showed that the prevalence

of depressive symptoms among rural elderly persons in

central China was 52.9%, which is higher than previously

reported rates of depression in rural Chinese elderly also

using the GDS-30. For example, He G et al28 reported a

prevalence of depression of 36.94% among elderly persons

in rural China, and another survey in rural China reported

18.1%.29 The high prevalence of elderly depressive symp-

toms may be due to the rapid development of urbanization

in China in recent years. The rural youth labor force has

flocked to urban areas, resulting in a rapid increase in the

proportion of rural elderly persons and weakening the

family’s economic and spiritual support for elderly persons.

Using the same measurement tool, Park J et al30

reported a prevalence of depression in the elderly popula-

tion in Korea was 30.3%; Arslantas D et al31 found that

the prevalence of depression among elderly persons in

Turkey was 45.8%; moreover, the prevalence of

depression in Mexico elderly adults reported by Ortiz

GG et al32 was 29.1%. The prevalence of depressive

symptoms in rural elderly individuals in central China

was higher than the above findings. The reasons may be

as follows: First, the social security system for the elderly

in rural areas in China is imperfect. Financial support from

their children is the main form of support available to the

elderly in rural areas, which is often unstable and unreli-

able. To a certain extent, this support system has increased

the psychological burden on the elderly. Second, the con-

cept of filial piety in Chinese traditional culture is crucial

to the social support of rural elderly: children are the main

source of social support for parents and families. However,

with the rapid development of urbanization in China, rural

young and middle-aged laborers have been flocking to

cities, and the lack of family members to care for the

rural elderly in daily life may be another reason for the

high prevalence of depressive symptoms.

This study also found that the prevalence of depressive

symptoms in poor elderly persons was higher than that in

non-poor elderly persons, which is similar to the findings

of Fang M et al.33 The poor economic situation of poor

elderly persons may lead to negative attitude towards life,

affect mental health, and generate a vicious circle, which

may lead to depressive symptoms.

Table 4 Binary Logistic Regression Analysis Of Associated Factors For Depressive Symptoms

Variables B SE Wald P-Value OR 95% CI

Poverty

(Non-poor a )

0.338 0.083 16.699 <0.001 1.402 1.192 – 1.649

EQ-5D score −4.594 0.270 289.358 <0.001 0.010 0.006 – 0.017

Gender

(Female a )

−0.503 0.086 34.297 <0.001 0.605 0.511 – 0.716

Age 0.017 0.006 8.223 0.004 1.017 1.005 – 1.030

Education

(Elementary and above a )

0.292 0.089 10.820 0.001 1.340 1.125 – 1.595

Profession

(Employed a )

0.211 0.085 6.073 0.014 1.234 1.044 – 1.460

Chronic diseases 0.096 0.039 6.105 0.013 1.101 1.020 – 1.188

Living arrangement

(Not alone a )

−0.129 0.101 1.630 0.202 0.879 0.721 – 1.071

Hospitalization (No a ) 0.368 0.086 18.166 <0.001 1.445 1.220 – 1.711

Constant 1.784 0.484 13.612 <0.001 5.954 –

Note: aReference group. Abbreviations: SE, standard error; OR, odds ratio; CI, confidence interval.

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QoL The utility score of EQ-5D in our study was 0.713 ± 0.186,

which is lower than that reported by Zhou Z et al17 using

the same scale with rural Chinese elderly in different

living arrangements (living with a spouse: 0.8652, living

alone: 0.8427, living with a spouse and adult children:

0.8652, single elderly living with adult children: 0.7720).

Parker L et al34 used the EQ-5D with community elderly

persons in the UK and reported a value of 0.78 ± 0.2.

Moreover, Chen Y et al35 found that the education level

was related to the QoL of elderly persons. The low QoL

score in this study may result from the lower education

level of rural elderly persons in this study. In addition, a

low education level may indirectly affect individuals’

employment opportunities and even income.36 Our analy-

sis also found that the QoL of the elderly with low eco-

nomic level was also low. It may be that a low-income

level cannot provide an adequate material life basis or

medical services for the elderly, which affects their QoL.

Correlation Of Depressive Symptoms

And QoL A significant negative correlation between depression and

QoL has been demonstrated in previous cross-sectional

studies.37–39 Sivertsen H et al5 and González-Celis AL

et al40 found a negative correlation between depression and

QoL, consistent with the results of this study. As age

increases, to some extent, elderly persons experience a

decline in the function of the body organs due to biological

and psychological changes, which leads to a gradual decrease

in QoL.5 The psychological burden of elderly persons may be

worsened by the long-term low QoL, leading to the occur-

rence or aggravation of depressive symptoms.

Associated Factors For Depressive

Symptoms This study found that poverty, low QoL, older age, female

gender, illiteracy, unemployed, suffering from chronic dis-

eases, and hospitalization in the previous year were asso-

ciated factors for depressive symptoms among rural

elderly, and studies have reported similar results.41,42

Consistent with the findings of Grant BF et al,43 this

study found that older persons have a higher prevalence of

depressive symptoms. With increased age, elderly persons’

physical function declines, and vulnerability to chronic

diseases and negative emotions increase, leading to

depressive symptoms.44

The prevalence of depressive symptoms among rural

elderly women was higher than among men, which is

consistent with the findings of Bossola M et al.45 In rural

China, elderly women lose the role of traditional house-

wives when they age, especially after their husbands die,

and they are often alone with reduced family support,

which increases the possibility of depressive symptoms.41

The higher prevalence of depressive symptoms in elderly

persons with lower education level and those unemployed is

consistent with studies by Grant BF et al43 and Kong XY

et al.46 Elderly persons with lower education level, who have

fewer social resources than those with higher education, have

lower self-care awareness and less able to adjust their emo-

tions when experiencing negative life events.47 At the same

time, a low education level may also affect the employment

of elderly persons, resulting in poverty.

In addition, this study found that the prevalence of

depressive symptoms in elderly persons who had been

hospitalized in the previous year and those with chronic

diseases was higher, consistent with the findings of Song

AQ et al48 and Lebowitz BD et al.49 This may be because

elderly individuals suffer from chronic diseases, which

have long disease courses and are difficult to cure; thus,

they need to be hospitalized frequently. Long-term medical

expenses not only increase the family’s economic burden

but also the psychological burden of the elderly, which can

lead to the occurrence or aggravation of depressive symp-

toms in the long term.

However, this study found that rural elderly persons

with different living arrangements did not differ in terms

of prevalence of depressive symptoms. Kaneko Y et al50

showed that the prevalence of depression in elderly per-

sons living alone was higher than those living in other

arrangements. The reason for the different results may be

that the units of rural communities in China are relatively

small. Rural elderly people live in concentrated commu-

nities and have close communication with their neighbors

in daily life, which means that there is little difference in

daily lifestyle between those living alone and those not

living alone. In addition, although family help is the main

form of support for rural elderly people in China, the basic

life of the elderly living alone or not living alone has been

effectively protected since the Chinese government estab-

lished the pension policy for the elderly in 2015.

Strengths And Limitations The effective response rate of this study was 95.93%,

which is very high. It is well known that the results

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obtained from surveys with high response rates and large

samples are very reliable. At the same time, many poten-

tial associated factors were also investigated, including

demographic characteristics, physical condition, and

QoL. However, there were some limitations to this study.

Most importantly, the included study sample was from

Anhui Province in central China, and samples from other

provinces in China and other countries should be included

in further in-depth studies in the future. Secondly, the

cross-sectional nature of this study limits the ability to

infer causality. Further limitations include the use of the

GDS-30 to measure depressive symptoms not combined

with clinical depression diagnosis may cause accuracy of

the results. Finally, this study was based upon self-reports,

which may increase recall bias and exclude potentially

important associated factors for depressive symptoms

such as cognitive impairment or disability.

Conclusion This was a large cross-sectional study investigating the

status of depressive symptoms and QoL among rural

elderly in central China, as well as the correlation between

depressive symptoms and QoL, and the factors influencing

depressive symptoms. Our study provides baseline infor-

mation for future research and useful data on depressive

symptoms and associated factors from China, which helps

to better understand its epidemiology in China and com-

pares China with other countries. We found that rural

elderly persons in central China had a higher prevalence

of depressive symptoms and lower QoL; the prevalence of

depressive symptoms in poor elderly persons was higher

than in non-poor elderly persons, and poor elderly per-

sons’ QoL was lower than that of non-poor elderly parti-

cipants. Poverty, lower QoL, female gender, older age,

illiteracy, unemployed, chronic diseases, and hospitaliza-

tion within the previous year were associated with depres-

sive symptoms. These findings have a certain significance

for health promotion and protection among the elderly

population in rural China. It is important not only to

perfect the mechanism of the aging security but also

to establish elderly leisure and entertainment facilities to

improve QoL in rural China. It is also necessary to intro-

duce elderly clinics in medical care services and provide

psychological counseling services for early detection and

treatment of high-risk depressive symptom groups in order

to improve the mental health of elderly persons in rural

areas and promote healthy aging.

Acknowledgment This research was funded by Research Projects of Humanities

and Social Sciences in Colleges and Universities of Anhui

Province (No. SK2018A0165) and Doctoral Fund Project of

Anhui Medical University (No. XJ201545).

Disclosure The authors report no conflicts of interest in this work.

References 1. National Bureau of Statistics. Statistical bulletin for national economic

and social development. 2019. Available from: http://www.stats.gov.cn/ tjsj/zxfb/201902/t20190228_1651265.html. Accessed July 10, 2019.

2. UNFPA and Help Age International. Ageing in the twenty-first century: a celebration and a challenge. 2012. Available from: https://www.unfpa. org/publications/ageing-twenty-first-century. Accessed July 10, 2019.

3. Huang C, Zhang X, Dong B, Lu Z, Yue J, Liu Q. Health status and risk for depression among the elderly: a meta-analysis of published literature. Age Ageing. 2010;39(1):23–30. doi:10.1093/ageing/afp187

4. Huang R, Wang K, Hu J. Effect of probiotics on depression: A systematic review and meta-analysis of randomized controlled trials. Nutrients. 2016;8(8):483. doi:10.3390/nu8080483

5. Sivertsen H, Bjørkløf GH, Engedal K, Selbæk G, Helvik A. Depression and quality of life in older persons: a review. Dement Geriatr Cogn. 2015;40(5–6):311–339. doi:10.1159/000437299

6. Luppa M, Sikorski C, Luck T, et al. Age- and gender-specific prevalence of depression in latest-life–systematic review and meta-analysis. J Affect Disord. 2012;136(3):212–221. doi:10.1016/j.jad.2010.11.033

7. Gao S, Jin Y, Unverzagt FW, et al. Correlates of depressive symp- toms in rural elderly Chinese. Int J Geriatr Psych. 2009;24 (12):1358–1366. doi:10.1002/gps.2271

8. Correll CU, Detraux J, De Lepeleire J, De Hert M. Effects of anti- psychotics, antidepressants and mood stabilizers on risk for physical diseases in people with schizophrenia, depression and bipolar disor- der. World Psychiatry. 2015;14(2):119–136. doi:10.1002/wps.v14.2

9. Lenze EJ, Mulsant BH, Blumberger DM, et al. Efficacy, safety, and tolerability of augmentation pharmacotherapy with aripiprazole for treatment-resistant depression in late life: a randomised, double- blind, placebo-controlled trial. Lancet. 2015;386(10011):2404–2412. doi:10.1016/S0140-6736(15)00308-6

10. Gonda X, Pompili M, Serafini G, Carvalho AF, Rihmer Z, Dome P. The role of cognitive dysfunction in the symptoms and remission from depression. Ann Gen Psychiatr. 2015;14(1). doi:10.1186/ s12991-015-0068-9

11. Mut-Vitcu G, Timar B, Timar R, Oancea C, Citu IC. Depression influences the quality of diabetes-related self-management activities in elderly patients with type 2 diabetes: a cross-sectional study. Clin Interv Aging. 2016;11:471–479. doi:10.2147/CIA.S104083

12. Netuveli G, Blane D. Quality of life in older ages. Brit Med Bull. 2008;85(1):113–126. doi:10.1093/bmb/ldn003

13. Su S, Wang D. Health-related quality of life and related factors among elderly persons under different aged care models in Guangzhou, China: a cross-sectional study. Qual Life Res. 2019;28 (5):1293–1303. doi:10.1007/s11136-019-02107-x

14. Li J, Yu J, Chen X, Quan X, Zhou L. Correlations between health- promoting lifestyle and health-related quality of life among elderly people with hypertension in Hengyang, Hunan, China. Medicine. 2018;97(e1093725).

15. Zhao Y, Hu C, Feng F, et al. Associations of self-neglect with quality of life in older people in rural China: a cross-sectional study. Int Psychogeriatr. 2017;29(6):1015–1026. doi:10.1017/S1041610217000229

Rong et al Dovepress

submit your manuscript | www.dovepress.com

DovePress Clinical Interventions in Aging 2019:141908

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lin ic

a l I

n te

rv e

n tio

n s

in A

g in

g d

o w

n lo

a d

e d

f ro

m h

tt p

s: //

w w

w .d

o ve

p re

ss .c

o m

/ b

y 1

6 5

.2 1

5 .2

0 9

.1 5

o n

1 8

-N o

v- 2

0 1

9 F

o r

p e

rs o

n a

l u se

o n

ly .

Powered by TCPDF (www.tcpdf.org)

1 / 1

16. Xie J, Ding S, Zhong Z, et al. Mental health is the most important factor influencing quality of life in elderly left behind when families migrate out of rural China. Rev Lat Am Enferm. 2014;22(3):364–370. doi:10.1590/0104-1169.3400.2425

17. Zhou Z, Zhou Z, Gao J, Lai S, Chen G. Urban-rural difference in the associations between living arrangements and the health-related qual- ity of life (HRQOL) of the elderly in China—evidence from Shaanxi province. PLoS One. 2018;13(9):e204118.

18. National Bureau of Statistics. Anhui Province GDP per capita. 2019. Available from: http://www.stats.gov.cn/. Accessed July 10, 2019.

19. Anhui Provincial People’s Government. Statistical communique of Anhui national economic and social development. 2019. Available from: http://www.ah.gov.cn/UserData/DocHtml/1/2019/2/28/ 6043378589099.html. Accessed July 10, 2019.

20. Ding H, Sun X, Chang WW, Zhang L, Xu XP. A comparison of job satisfaction of community health workers before and after local comprehensive medical care reform: a typical field investigation in Central China. PLoS One. 2013;8(9):e73438. doi:10.1371/journal. pone.0073438

21. Ganguli M, Hendrie HC. Screening for cognitive impairment and depression in ethnically diverse older populations. Alzheimer Dis Assoc Disord. 2005;19(4):275–278. doi:10.1097/01.wad.00001908 07.90254.24

22. Yunming L, Changsheng C, Haibo T, et al. Prevalence and risk factors for depression in older people in Xi’an China: a commu- nity-based study. Int J Geriatr Psychiatry. 2012;27(1):31–39. doi:10.1002/gps.2685

23. Chan AC. Clinical validation of the Geriatric Depression Scale (GDS): Chinese version. J Aging Health. 1996;8(2):238–253. doi:10. 1177/089826439600800205

24. Dong Q, Liu JJ, Zheng RZ, et al. Obesity and depressive symptoms in the elderly: a survey in the rural area of Chizhou, Anhui province. Int J Geriatr Psychiatry. 2013;28(3):227–232. doi:10.1002/gps.3815

25. Wang H, Kindig DA, Mullahy J. Variation in Chinese population health related quality of life: results from a EuroQol Study in Beijing, China. Qual Life Res. 2005;14(1):119–132. doi:10.1007/s11136-004- 0612-6

26. Liu WY. Study on the Quality of Life and the Influencing Factors of the Elderly [master’s thesis]. Nanchang: Jiaotong University of East China; 2015.

27. Li MH, Luo N. Euro 5-dimension questionnaire scale (EQ-5D) Chinese version application introduction. Chin Pharmacoecon. 2009;1:49–57.

28. He G, Xie J, Zhou J, Zhong Z, Qin C, Ding S. Depression in left- behind elderly in rural China: prevalence and associated factors. Geriatr Gerontol Int. 2016;16(5):638–643. doi:10.1111/ggi.12518

29. Li N, Chen G, Zeng P, et al. Prevalence of depression and its associated factors among Chinese elderly people: A comparison study between community-based population and hospitalized population. Psychiat Res. 2016;243:87–91. doi:10.1016/j.psychres.2016.05.030

30. Park J, Park TW, Yang J, Chung S. Factors associated with depres- sion among elderly Koreans: the role of chronic illness, subjective health status, and cognitive impairment. Psychogeriatrics. 2016;16 (1):62–69. doi:10.1111/psyg.12160

31. Arslantas D, Ünsal A, Ozbabalık D. Prevalence of depression and associated risk factors among the elderly in Middle Anatolia, Turkey. Geriatr Gerontol Int. 2014;14(1):100–108. doi:10.1111/ ggi.12065

32. Ortiz GG, Arias-Merino ED, Flores-Saiffe ME, Velázquez-Brizuela IE, Macías-Islas MA, Pacheco-Moisés FP. Prevalence of cognitive impairment and depression among a population aged over 60 years in the metropolitan area of Guadalajara, Mexico. Curr Gerontol Geriatr Res. 2012;2012:1–6. doi:10.1155/2012/175019

33. Fang M, Mirutse G, Guo L, Ma X. Role of socioeconomic status and housing conditions in geriatric depression in rural China: a cross- sectional study. BMJ Open. 2019;9(5):e24046. doi:10.1136/bmjopen- 2018-024046

34. Parker L, Moran GM, Roberts LM, Calvert M, McCahon D. The burden of common chronic disease on health-related quality of life in an elderly community-dwelling population in the UK. Fam Pract. 2014;31(5):557–563. doi:10.1093/fampra/cmu035

35. Chen Y, Sun G, Guo X, et al. Factors affecting the quality of life among Chinese rural general residents: a cross-sectional study. Public Health. 2017;146:140–147. doi:10.1016/j.puhe.2017.01.023

36. Gong FF. A Cross-Sectional Study on the Detection Rate of Depression and its Influencing Factors in Empty Nesters in a Rural Area of Anhui Province [master ’s thesis]. Hefei: Anhui Medical University; 2016.

37. Helvik A, Engedal K, Selbæk G. The quality of life and factors associated with it in the medically hospitalised elderly. Aging Ment Health. 2010;14(7):861–869. doi:10.1080/13607861003801003

38. Brown PJ, Roose SP. Age and anxiety and depressive symptoms: the effect on domains of quality of life. Int J Geriatr Psych. 2011;26 (12):1260–1266. doi:10.1002/gps.2675

39. Akyol Y, Durmus D, Dogan C, Bek Y, Canturk F. Quality of life and level of depressive symptoms in the geriatric population. Turk J Rheumatol. 2010;25(4):165–173. doi:10.5152/tjr.

40. González-Celis AL, Gómez-Benito J. Spirituality and quality of life and its effect on depression in older adults in Mexico. Psychology. 2013;4(3):178–182.

41. Aly HY, Hamed AF, Mohammed NA. Depression among the elderly population in Sohag governorate. Saudi Med J. 2018;39(2):185–190. doi:10.15537/smj.2018.2.21353

42. Tiong WW, Yap P, Huat Koh GC, Phoon Fong N, Luo N. Prevalence and risk factors of depression in the elderly nursing home residents in Singapore. Aging Ment Health. 2013;17(6):724–731. doi:10.1080/ 13607863.2013.775638

43. Grant BF, Hasin DS, Stinson FS, et al. Prevalence, correlates, co- morbidity, and comparative disability of DSM-IV generalized anxiety disorder in the USA: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Psychol Med. 2005;35 (12):1747–1759. doi:10.1017/S0033291705006069

44. Riebe D, Garber CE, Rossi JS, et al. Physical activity, physical function, and stages of change in older adults. Am J Health Behav. 2005;29(1):70–80. doi:10.5993/AJHB.29.1.6

45. Bossola M, Di Stasio E, Antocicco M, et al. Functional impairment is associated with an increased risk of mortality in patients on chronic hemodialysis. BMC Nephrol. 2016;17(1). doi:10.1186/s12882-016- 0302-y

46. Kong XY, Xiao QL, Li J. Urban-rural comparison of factors related to depressive symptoms in the elderly. Chin J Ment Health. 2018;32 (8):648–655.

47. Bjelland I, Krokstad S, Mykletun A, Dahl AA, Tell GS, Tambs K. Does a higher educational level protect against anxiety and depres- sion? The HUNT study. Soc Sci Med. 2008;66(6):1334–1345. doi:10.1016/j.socscimed.2007.12.019

48. Song AQ, Liang YJ, Wang WJ, Li YL, Guo LY. Correlation between depressive symptoms and chronic diseases and activities of daily living in the elderly. Chin J Health Manage. 2013;7(3):182–185.

49. Lebowitz BD, Pearson JL, Schneider LS, et al. Diagnosis and treat- ment of depression in late life. Consensus statement update. JAMA. 1997;278(14):1186–1190. doi:10.1001/jama.1997.03550140078045

50. Kaneko Y, Motohashi Y, Sasaki H, Yamaji M. Prevalence of depres- sive symptoms and related risk factors for depressive symptoms among elderly persons living in a rural japanese community: a cross-sectional study. Community Ment Hlt J. 2007;43(6):583–590. doi:10.1007/s10597-007-9096-5

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