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Associations between changes in social contact pattern and the mental health status of Chinese adults: cross-sectional findings

Zhang, Jingya Zhou, Shuai Wang, Qiong Hou, Fangfang Han, Xiao Shen, Guodong Chiang, Chifa Yatsuya, Hiroshi Zhang, Yan 名古屋大学

2023.08

概要

Coronavirus disease 2019 (COVID-19) is a severe public health crisis worldwide. By 22 July
2022, nearly 552 million cases and over 6.3 million deaths had been reported globally,1 with
more than 536 million cases of infection and more than 22,990 deaths occurring in China.2 At the
early stage of the pandemic, to curb the fast spread of COVID-19, the Chinese government set
up the strictest anti-epidemic strategy since the outbreak in January 2020, including precautions
such as maintaining social distancing and stay-at-home orders. As the number of cases decreased,
restrictions were eased, but some precautions were still strongly encouraged in most cities, for
example, maintaining social distance and reducing mass gathering events and unnecessary visits
with relatives and friends,3 which greatly shifted people’s social contact patterns.
Accumulated evidence suggests that lifestyles might affect mental health.4-8 During the
­COVID-19 pandemic, when regular face-to-face communication became difficult to achieve, as
an alternative, people had no choice but to adopt online communication to maintain relationships
with family and friends.9,10 The rapid change in social contact patterns might potentially affect
the mental well-being of individuals. For example, recent studies reported that physical and social
network isolation due to the COVID-19 pandemic was associated with negative mental health
trajectories.11,12 An increasing number of studies suggest that the mental health crisis caused by
COVID-19 is extremely urgent13 because the emotional or tangible support available in various
ways is critically important, especially in times of crisis.12
Although many studies have shown the link between social networks and mental health, few
studies have addressed the relationship between social contact pattern changes and mental health,
regardless of the social contact patterns that might play a key role in well-being. Therefore, our
study aims to estimate the associations between social contact pattern changes and mental health
status, including depression, anxiety, and loneliness, among Chinese adults in the context of
COVID-19. The current study might provide evidence for policymaking regarding mental health
preservation and promotion during infectious disease pandemics. ...

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Social contact pattern and mental health

SUPPLEMENTAL MATERIALS

Table s1 Results of the covariates in the Poisson regression analyses examining the associations

between social contact pattern changes and mental health status, 2021, China

Depression

Covariates

Anxiety

n/N

(%)

PR

95%CI

0.99

0.97,

0.99

Male

1103/1453

(75.9)

Ref

Female

1364/2058

(66.3)

0.95

Employed

1643/2349

(69.9)

Ref

Not employed

824/1162

(70.9)

0.97

Primary school or lower

538/663

(81.1)

Ref

High school

557/746

(74.7)

0.97

1372/2102

(65.3)

0.87

≤6000

1134/1781

(63.7)

Ref

>6000

1333/1730

(77.1)

1.19

Married

1101/1532

(71.9)

Ref

Not married

1366/1979

(69.0)

0.97

Urban

1961/2793

(70.2)

Ref

Rural

506/718

(70.5)

0.99

Yes

794/932

(85.2)

Ref

No

1673/2579

(64.9)

0.86

Age (continuous)

Loneliness

n/N

(%)

PR

95%CI

n/N

(%)

PR

95%CI

0.99

0.99,

1.00

0.99

0.98,

0.99

685/1453

(47.1)

Ref

882/1453

(60.7)

Ref

917/2058

(44.6)

1.05

1028/2058

(50.0)

0.94

1172/2349

(49.9)

Ref

1223/2349

(52.1)

Ref

430/1162

(37.0)

0.80

687/1162

(59.1)

1.04

363/663

(54.8)

Ref

455/663

(68.6)

Ref

0.85,

1.10

359/746

(48.1)

0.91

0.78,

1.06

452/746

(60.6)

0.96

0.84,

1.11

0.77,

0.98

880/2102

(41.9)

0.89

0.77,

1.03

1003/2102

(47.7)

0.78

0.69,

0.89

707/1781

(39.7)

Ref

876/1781

(49.2)

Ref

895/1730

(51.7)

1.15

1034/1730

(59.8)

1.22

656/1532

(42.8)

Ref

874/1532

(57.0)

Ref

946/1979

(47.8)

0.99

1036/1979

(52.3)

0.95

1297/2793

(46.4)

Ref

1498/2793

(53.6)

Ref

305/718

(42.5)

1.02

412/718

(57.4)

1.00

629/932

(67.5)

Ref

633/932

(67.9)

Ref

973/2579

(37.7)

0.70

1277/2579

(49.5)

0.84

Sex

0.88,

1.04

0.95,

1.16

0.85,

1.03

Occupation

0.88,

1.07

0.71,

0.91

0.94,

1.16

Education

College

Monthly income (RMB)

1.09,

1.29

1.04,

1.29

1.11,

1.35

Marital status

0.88,

1.06

0.89,

1.12

0.85,

1.05

Urban-rural

0.89,

1.10

0.89,

1.17

0.89,

1.13

Chronic illness

Nagoya J. Med. Sci. 85. 476–489, 2023

0.78,

0.94

487

0.62,

0.78

0.75,

0.93

doi:10.18999/nagjms.85.3.476

Jingya Zhang et al

Self-rated health

Very good

979/1519

(64.5)

Ref

Good

758/1068

(71.0)

1.05

Not good

730/924

(79.0)

1.14

<2

841/1168

(72.0)

Ref

2–3

781/1049

(74.5)

1.02

>3

845/1294

(65.3)

0.97

427/609

(70.1)

Ref

1–2

1288/1736

(74.2)

1.04

≥3

752/1166

(64.5)

0.92

Very good

929/1440

(64.5)

Ref

Good

805/1114

(72.3)

1.11

Not good

733/957

(76.6)

761/1519

(50.1)

Ref

0.95,

1.17

455/1068

(42.6)

0.92

1.02,

1.27

386/924

(41.8)

0.95

633/1168

(54.2)

Ref

0.92,

1.12

550/1049

(52.4)

1.04

0.87,

1.08

419/1294

(32.4)

0.77

290/609

(47.6)

Ref

0.93,

1.16

869/1736

(50.1)

1.01

0.82,

1.08

443/1166

(38.0)

0.84

762/1440

(52.9)

Ref

1.01,

1.23

451/1114

(40.5)

0.88

1.24

1.11,

1.39

389/957

(40.6)

0.97

0.96,

0.98

743/1519

(48.9)

Ref

0.82,

1.17

560/1068

(52.4)

1.02

0.91,

1.15

0.82,

1.09

607/924

(65.7)

1.21

1.07,

1.36

639/1168

(54.7)

Ref

0.92,

1.17

598/1049

(57.0)

1.02

0.91,

1.15

0.67,

0.88

673/1294

(52.0)

1.05

0.93,

1.18

336/609

(55.2)

Ref

0.88,

1.16

970/1736

(55.9)

1.02

0.90,

1.16

0.72,

0.98

604/1166

(51.8)

0.96

0.83,

1.10

723/1440

(50.2)

Ref

0.78,

1.00

611/1114

(54.8)

1.07

0.95,

1.20

0.97

0.85,

1.12

576/957

(60.2)

1.22

1.08,

1.39

0.97

0.96,

0.98

0.96

0.95,

0.97

Daily screen time(h)

Physical activity (day/week)

Never

Sleep quality

Mental resilience

(continuous)

n: the number of participants having the condition (depression, anxiety, or loneliness)

N: the number of participants with a particular characteristic

PR: prevalence ratio

CI: confidence interval

Ref: reference

Prevalence ratios and the 95% confidence intervals for depression, dark future anxiety, and loneliness were

estimated from Poisson regression model including sex, age (continuous), occupation (employed, not employed),

education (primary school or lower, high school, college), monthly income (≤6000RMB/ >6000 RMB), marital

status (married, not married), urban/rural dwelling (urban, rural), chronic illness (yes, no), self-rated health status

(very good, good, not good), daily screen-time (<2h, 2–3h, >3h), physical activity (never, 1–2 days per week,

3 days or more per week), sleep quality (very good, good, not good), mental resilience (continuous), and social

contact pattern changes (no change, in-person communication increased, online-communication increased). Results

of social contact pattern changes with mental health status are presented in Table 2.

Nagoya J. Med. Sci. 85. 476–489, 2023

488

doi:10.18999/nagjms.85.3.476

Social contact pattern and mental health

Table s2 Poisson regression analysis of changes of social contact patterns and mental health status

among the participants who did not report any chronic disease

Depression

n/N

(%)

PR

1043/1647

(63.3)

Ref

In-person communication

increased

292/364

(80.2)

1.15

Online communication

increased

338/568

(59.5)

0.95

Anxiety

n/N

(%)

PR

621/1647

(37.7)

Ref

0.99,

1.31

179/364

(49.2)

1.21

0.84,

1.08

173/568

(30.5)

0.87

95%CI

Loneliness

n/N

(%)

PR

815/1647

(49.5)

Ref

1.01,

1.43

220/363

(60.4)

1.02

0.87,

1.20

0.73,

1.03

242/568

(42.6)

0.87

0.75,

1.01

95%CI

95%CI

Social contact pattern changes

No change

n: the number of participants having the condition (depression, anxiety, or loneliness)

N: the number of participants with a particular social contact pattern

PR: prevalence ratio

CI: confidence interval

Ref: reference

Prevalence ratios and the 95% confidence intervals for depression, anxiety, and loneliness were estimated from

Poisson regression model adjusted for sex, age (continuous), occupation (employed, not employed), education

(primary school or lower, high school, college), monthly income (≤6000RMB/ >6000 RMB), marital status

(married, not married), urban/rural dwelling (urban, rural), chronic illness (yes, no), self-rated health status (very

good, good, not good), daily screen-time (<2h, 2–3h, >3h), physical activity (never, 1–2 days per week, 3 days

or more per week), sleep quality (very good, good, not good), and mental resilience (continuous).

References End

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