COVID-19 anxiety and related factors amid adjusted epidemic prevention policies: a cross-sectional study on patients with late-life depression in China

Abstract

Objectives

To explore the prevalence and associated factors of COVID-19 anxiety in patients with late-life depression (LLD) during the adjustment of epidemic prevention policies in China.

Design

Cross-sectional study.

Setting

The data analysed in this study were collected from seven regions in China between November 2022 and January 2023.

Participants

A total of 1205 patients with LLD (aged 60–78 years) participated in the survey. They completed a social demographic assessment and the Chinese version of the five-point Coronavirus Anxiety Scale (CAS).

Primary outcome measures

The primary outcome was the anxiety level of the participants. Patients were categorised into two groups based on their anxiety levels, one with anxiety and one without, according to CAS scores.

Results

The prevalence of COVID-19 anxiety in depressed older adults was 47.3%. Regression analysis revealed that the average COVID-19 anxiety score was significantly higher among females (AOR: 2.177, 95% CI 1.201 to 3.947), widowed individuals (AOR: 3.015, 95% CI 1.379 to 6.591), patients residing at a distance from healthcare facilities (AOR: 3.765, 95% CI 1.906 to 7.438), and those who frequently experienced worry (AOR: 1.984, 95% CI 1.111 to 3.543). Conversely, the anxiety score was significantly lower among divorced individuals (AOR: 0.491, 95% CI 0.245 to 0.988), those aged 70 years and above (AOR: 0.117, 95% CI 0.064 to 0.213), patients without difficulty obtaining medication (AOR: 0.027, 95% CI 0.007 to 0.097), those living with family members (AOR: 0.080, 95% CI 0.022 to 0.282) or in nursing homes compared with those living alone (AOR: 0.019, 95% CI 0.004 to 0.087).

Conclusion

Women with LLD who are widowed, live far from healthcare facilities, and are prone to excessive worry are more likely to experience anxiety. It is advisable to implement appropriate preventive measures and provide psychosocial support programmes for this vulnerable group during the COVID-19 pandemic.

Correspondence to Dr Qin Zhou; [email protected]

STRENGTHS AND LIMITATIONS OF THIS STUDY

• This cross-sectional study assessed COVID-19 anxiety levels in patients with late-life depression using the Coronavirus Anxiety Scale.

• Various models and logistic regressions were employed to fit and analyse anxiety levels.

• This study was conducted immediately after the adjustment of epidemic policies.

• The cross-sectional nature of the study does not establish causal relationships between the outcomes and independent factors.

Introduction

The COVID-19 pandemic stands as one of the most significant public health emergencies of this century.¹ Beginning with the declaration of the pandemic by the WHO on 11 March 2020, the global count of confirmed cases reported to WHO exceeded 756 million by February 2023, with more than 6.8 million recorded deaths.² To prevent epidemics and safeguard lives and property, the Chinese government implemented a precise sealing strategy to reduce infection rates, famously known as the ‘Dynamic clearing’ policy—a measure aimed at controlling the number of patients with COVID-19. Over the past 3 years, a delicate balance between epidemic prevention and daily life was achieved by quarantining infected areas within buildings while maintaining the free movement of other regions. Consequently, by the close of 2022, the number of infections and case fatality rates in China were notably lower than those reported by the WHO. However, owing to the mutations of the SARS-CoV-2, shifts in the global epidemiological landscape, and the challenges to the national economy, the Chinese government was compelled to transition from the ‘Dynamic clearing’ policy to the ‘Class B management’ policy—a categorisation that signifies a shift from stringent epidemic prevention measures to managing COVID-19 as a category B infectious disease. This shift implies reduced epidemic control measures and forewarns an unprecedented epidemic burden in the future.

The COVID-19 pandemic has not only led to extensive impacts on physical health but also cast a long shadow on mental well-being, resulting in elevated stress, fear, anxiety and depression. Globally, in 2020, the pandemic led to a 27.6% increase in major depression cases and a 25.6% surge in anxiety disorders.³ Previous studies highlighted the increased prevalence of anxiety among older individuals during the COVID-19 pandemic, which poses a great threat to them.^4–6 Furthermore, research indicates that there was a sharp rise in mental health-related symptoms at the onset of the epidemic.⁷

Late-life depression (LLD) refers to depressive disorders in individuals aged 60 years and above.⁸ It represents a common mental health challenge among older adults, which not only diminishes the quality of life and social functioning but also places an added burden on caregivers.⁹ Patients with LLD frequently present with various underlying diseases,¹⁰ with anxiety and restlessness being the most prevalent and prominent manifestations.¹¹ Research has revealed COVID-19 anxiety and panic, particularly in older adults, can be exacerbated by public health measures aimed at curtailing the spread of SARS-CoV-2, including traffic restrictions and home isolation.¹² Moreover, older adults often have weaker immune systems and limited access to medications, rendering them more susceptible to fear and anxiety, particularly if they have pre-existing health conditions.¹³ In essence, patients with LLD at a heightened risk of experiencing anxiety during the pandemic.

While previous research has demonstrated the prevalence of anxiety in older adults resulting from COVID-19 in various countries,¹⁴ limited studies have focused on COVID-19 anxiety among patients with LLD in China. Much of the existing work has primarily focused on anxiety and depression among young people using online and telephone surveys.^15–17 For instance, Stephanie L. Clendennen and colleagues discovered that young individuals in Texas mitigated their mental health symptoms during the COVID-19 pandemic by resorting to increased consumption of cigarettes, e-cigarettes and marijuana.¹⁸ To the best of our knowledge, there is no study using the Coronavirus Anxiety Scale (CAS) to comprehensively investigate COVID-19 anxiety among patients with LLD in China. Thus, our research aims to fill this gap by examining the prevalence of COVID-19 anxiety and its associated factors among depressed older adults within the context of evolving epidemic prevention policies.

Our research holds pivotal importance in the understanding and development of interventions for mental health during and after the pandemic. Although mental health is increasingly gaining recognition in China, it is an aspect that older adults have rarely been given the opportunity to experience.¹⁹ China’s ageing population is becoming increasing serious, and paying attention to the mental health of older adults is a very important issue. In addition, the most important considerations for the adjustment of China’s epidemic prevention strategies are older adults, patients with basic diseases and children.²⁰ In the post-epidemic era, the infection status and mental health level of these groups significantly affect the operation of the policy. Other risk factors emerged following policy adjustments, such as low vaccination rates among older adults, inadequacies in medical facilities and shortages of medical supplies, increasing the anxiety of patients with LLD. The COVID-19 pandemic has disrupted already insufficient mental health services,²¹ especially affecting older adults,²² thereby increasing their risk of anxiety and depression. Furthermore, patients with LLD may experience worsening mental health during the pandemic in China due to socioeconomic challenges such as collective panic spurred by policy shifts, the risk of family members contracting COVID-19, declining income following infection and health-related concerns.²³ Severe psychological issues, including suicides have already been reported,²⁴ even among older adults.²⁵ Therefore, gaining a deeper understanding of COVID-19 anxiety and its associated factors in patients with LLD is imperative for the enhancement of mental health interventions in this vulnerable population.

Methods

Patient and public involvement

Patients or the public were not involved in the design, or conduct, or reporting, or dissemination plans of our research.

Study design and data sources

This cross-sectional study was conducted between November 2022 and January 2023 in China using questionnaires administered to patients with LLD. Participants were selected from seven regions. To ensure representative sampling, we employed a probability proportional to the region’s characteristics in the geographical distribution of older adults in China. Sample sizes for each partition were calculated, and participants were selected accordingly. Taking into account a prevalence of 23.2%²⁶ and a margin of error of 5%, a sample size of 1133 was calculated at a 95% CI, 90% test power and 95% response rate. Considering the loss rate of 20%, the required sample was 1417. Finally, 1205 samples were recovered, and the overall response rate was about 85%. The inclusion criteria were patients with LLD, and the exclusion criteria were as follows: (1) patients who had been diagnosed with anxiety before the epidemic; (2) patients who had hearing impairment or inability in communication. Whether participants were infected with COVID-19 was not considered as an exclusion criterion. All participants signed informed consent before the investigation.

Variables and measurements

Dependent variable

CAS²⁷ was used to measure the COVID-19 anxiety level. CAS has higher sensitivity and specificity than Generalized Anxiexy Disorder-7 (GAD-7).²⁸ The scale was translated into Chinese and 5-point Likert scale was used to assess participants' agreement or disagreement with these items. Each statement had five answers: ‘Not at all’, ‘Rare, less than a day or two’, ‘Several days’, ‘More than 7 days’, ‘Almost every day over the last 2 weeks’. It is recorded as 0, 1, 2, 3 and 4 points, respectively. The total score of each respondents’ attitude is the sum of the scores obtained from his answers to each question. This total score can indicate his attitude or different states on this scale. The cumulative score ranged from 0 to 20 points. The higher the score, the greater the anxiety of COVID-19. Participants were further divided into COVID-19 anxiety (if they reported anxiety in any CAS project) or no COVID-19 anxiety (if they reported no anxiety in each CAS project). The reliability of the participants’ scale was acceptable (Cronbach’s α=0.825).

Independent variables

In this study, several independent variables were considered to identify factors related to COVID-19 anxiety. The research team conducted an extensive review of COVID-19 anxiety-related literature,^29–31 and subsequently, identified four major influencing factors, comprising a total of 34 items. These factors included sociodemographic characteristics, economic status, physical condition and COVID-19-related information. These influencing factors were used as independent variables to prepare the ‘COVID-19 Anxiety and its Associated Factors Questionnaire’ for data collection. The results were categorised based on the questionnaire responses. As the total variable was not normally distributed, the median value was employed as a cut-off point for classification (tables S2 in the online supplemental appendix).

Bias control

This study adopts strict data management methods, such as double entry, cross-examination and controversial data are discussed and backtracked by multiple professionals.

Statistical analysis

Descriptive statistics were employed to evaluate the distribution of variables. Sample size calculations were conducted using PASS V.15.0, and data analysis was conducted using SPSS V.26.0. Logistic regression was used to analyse anxiety levels and their associated factors. Independent variables included two categories: (1) variables displaying statistically significant differences in univariate analysis (p<0.05), and (2) variables believed to be clinically associated with anxiety levels despite lacking statistical significance. As there were no continuous independent variables in this study, the Box-Tidwell transformation was not applied to the model. Multicollinearity was assessed by examining the variance inflation factor and tolerance in a multiple regression model. The overall significance of the model was assessed using the −2 log-likelihood ratio test.

Sociodemographic characteristics, economic status, physical condition and COVID-19-related information of the participants were considered to be associated with anxiety levels. Therefore, three models were constructed: model I incorporated social factors such as demographics, family characteristics and economic status; model II included individual factors such as physical condition and medical condition; and model III included both social and individual factors. Model fit was further evaluated using the Hosmer-Lemeshow goodness-of-fit χ² test and omnibus tests of model coefficients. Receiver-operating characteristic curves were used to assess specificity and sensitivity. Ultimately, model III, which initially included all factors with significant differences, was determined to be the best-fitting model based on multifactorial evaluation (table S1 in the online supplemental appendix). Adjusted ORs (AORs) with 95% CIs and p values<0.05 were used to identify factors associated with COVID-19 anxiety.

Results

Characteristics of the participants

The distribution of sex and age of patients

A total of 1205 participants from seven regions in China were enrolled in this study, consisting of 602 males (49.96%) and 603 females (50.04%). Among them, a greater proportion was within the age range of 60–69 years (70.62%) as compared with 70 years or older (29.38%). The marital status of the respondents included unmarried (6.64%), married (47.05%), divorced (10.46%) and widowed (35.85%), whereas their educational backgrounds ranged from illiteracy (3.82%) to primary school (52.03%) and junior high school and above (44.15%). Prior to retirement, there were 26.64% of individuals held professional positions such as doctors and teachers, military personnel (18.09%), administrative management (18.76%), service personnel (6.8%), workers (18.51%) and farmers (3.07%) (table 1).

Table 1

Basic characteristics of the participants (N=1205)

Characteristics	N	%	Anxiety (%)		P value
			No	Yes
Area of residence
North China	195	16.18	57.44	42.56	0.083
Northeast	44	3.65	54.55	45.45
East China	552	45.81	50.54	49.46
Central China	204	16.93	55.39	44.61
South China	138	11.45	44.20	55.80
Southwest	15	1.24	60.00	40.00
Northwest	57	4.73	64.91	35.09
Age (year)
60–69	851	70.62	50.76	49.24	0.037*
≥70	343	29.38	57.34	42.66
Sex
Male	602	49.96	55.65	44.35	0.040*
Female	603	50.04	49.75	50.25
Marital status
Unmarried	80	6.64	60.00	40.00	0.015*
Married	567	47.05	55.03	44.97
Divorced	126	10.46	57.94	42.06
Widowed	432	35.85	46.76	53.24
Educational level
Illiteracy	46	3.82	54.35	45.65	0.967
Primary school	627	52.03	52.79	47.21
Junior high school and above	532	44.15	52.44	47.56
Career before retirement
Special skill (doctor/teacher)	321	26.64	52.34	47.66	0.971
Soldiers	218	18.09	55.05	44.95
Administration/general staff	226	18.76	51.33	48.67
Service personnel	82	6.80	56.10	43.90
Workers	223	18.51	51.12	48.88
Farmers	37	3.07	54.05	45.95
Other	98	8.13	52.04	47.96

*A significant statistical difference according the p value<0.05.

Family members and living habits

The majority participants (89.13%) resided in urban areas. Over half (51.37%) of the participants had fewer than four family members. Notably, 28.63% of patients lived alone, 27.3% lived in nursing homes and 44.07% resided with family members. Less than half (42.90%) of the patients had a pension of less than ¥2000. A significant proportion of participants (75.02%) engaged in regular exercise to varying degrees, whereas 40.25% of patients reported smoking habits. Approximately a quarter (24.98%) of the population slept for more than 7 hours, and over half (55.19%) of the patients had a habit of consuming alcohol. A modest 9.13% of respondents rated their health as good. Housework was a daily activity for 60.66% of the individuals, and 58.76% were frequently involved in manual labour (table 2).

Table 2

Family members and living habits of the participants (N=1205)

Characteristics	N	%	Anxiety (%)		P value
			No	Yes
Residence
City	1074	89.13	54	46	0.009*
Rural	131	10.87	41.98	58.02
Family members
≤4	619	51.37	54.93	45.07	0.111
>4	586	48.63	50.34	49.66
Living conditions
Living alone	345	28.63	42.61	57.39	<0.001*
Together with family members	531	44.07	60.26	39.74
Nursing homes	329	27.3	51.06	48.94
Personal pensions
<2000	517	42.9	50.48	49.52	0.182
≥2000	688	57.1	54.36	45.64
Self-assessment of economic conditions
Rich	97	8.05	56.7	43.3	0.706
General	768	63.73	52.21	47.79
Difficulty	340	28.22	52.65	47.35
Do you exercise regularly
Yes	904	75.02	54.54	45.46	0.027*
No	301	24.98	47.18	52.82
Smoking or not
Yes	485	40.25	55.26	44.74	0.144
No	720	59.75	50.97	49.03
Sleeping time
<7 hours	301	24.98	61.79	38.21	<0.001*
≥7 hours	904	75.02	49.67	50.33
Diet taste
Lightness	585	48.55	48.55	51.45	0.061
Salty	134	11.12	55.97	44.03
Sweeter	283	23.49	55.12	44.88
Spicy	157	13.03	57.96	42.04
No special	46	3.82	63.04	36.96
Do you drink
Yes	665	55.19	54.74	45.26	0.116
No	540	44.81	50.19	49.81
Self-evaluation of health status
Good	110	9.13	60	40	0.186
General	406	33.69	54.68	45.32
Not good	613	50.87	50.73	49.27
Can not answer	76	6.31	47.37	52.63
Do you do housework
Yes	731	60.66	52.12	47.88	0.619
No	474	39.34	53.59	46.41
Do you often engage in manual labour
Yes	708	58.76	54.1	45.9	0.246
No	497	41.24	50.7	49.3

*A significant statistical difference according the p value<0.05.

Physical condition and medical condition

Around one-fifth (22.57%) of the respondents reported difficulty in self-care. Vision problems were reported by 30.87% of the participants, and 29.96% reported having experienced falls. Satisfaction with current life was limited among a few participants (4.98%). A majority of respondents (59.83%) had to walk less than 30 min to reach the nearest medical centre. A significant 27.72% of patients experienced difficulties in concentrating. Over one-third (36.35%) of the population encountered challenges in obtaining necessary medications. A total of 86.56% of patients with LLD had one or more chronic diseases. A notable 26.89% of patients believed their communication with relatives remained unchanged. A significant 63.82% of respondents often felt isolated from others, and 36.27% reported a lack of emotional response from family members. Approximately 3.32% of patients were consistently concerned about the COVID-19 pandemic. A substantial 82.41% of respondents required additional medical care. Simultaneously, 85.39% of patients expressed worries regarding the pandemic, with 80.66% feeling overwhelmed by the impact of COVID-19 (table 3).

Table 3

Physical condition and medical condition of the participants (N=1205)

Characteristics	N	%	Anxiety (%)		P value
			No	Yes
Can you take care of yourself
Yes	933	77.43	54.98	45.02	0.003*
No	272	22.57	44.85	55.15
Vision problems
Yes	833	69.13	53.78	46.22	0.259
No	372	30.87	50.27	49.73
Fall occurred
Yes	361	29.96	47.09	52.91	0.011*
No	844	70.04	55.09	44.91
Self-evaluation of life satisfaction
Satisfactory	60	4.98	65.00	35.00	0.257
General	521	43.24	52.78	47.22
Not satisfied	458	38.01	51.53	48.47
Can not answer	166	13.78	51.20	48.80
Lack of memory or concentration
Yes	334	27.72	49.70	50.30	0.197
No	871	72.28	53.85	46.15
Time to walk to the nearest medical centre
<30 min	721	59.83	57.00	43.00	<0.001*
≥30 min	484	40.17	46.28	53.72
Difficult to obtain drugs
Yes	438	36.35	44.98	55.02	<0.001*
No	767	63.65	57.11	42.89
With other non-communicable chronic diseases
Yes	1043	86.56	49.66	50.34	<0.001*
No	162	13.44	72.22	27.78
Chronic diseases
1	329	27.30	51.06	48.94	0.726
2	196	16.27	48.98	51.02
≥3	518	42.99	48.26	51.74
Current communication with family
Same as before	324	26.89	62.04	37.96	<0.001*
Less than before	881	73.11	49.26	50.74
Feeling isolated from others
Almost not	436	36.18	57.57	42.43	0.011*
Sometimes	769	63.82	49.93	50.07
Feeling family members unresponsive
Yes	437	36.27	48.05	51.95	0.015*
No	768	63.73	55.34	44.66
Frequency of epidemic concern
No	31	2.57	54.84	45.16	0.851
Occasionally	101	8.38	56.44	43.56
General	422	35.02	53.55	46.45
Often	611	50.71	51.23	48.77
Always	40	3.32	55.00	45.00
Do you need additional care during the pandemic
Yes	993	82.41	51.86	48.14	0.209
No	212	17.59	56.60	43.40
Do you worry about the pandemic
Almost not	176	14.61	61.93	38.07	0.008*
Sometimes	1029	85.39	51.12	48.88
Do you feel overwhelmed by COVID-19
Almost not	233	19.34	58.80	41.20	0.038*
Sometimes	972	80.66	51.23	48.77

*A significant statistical difference according the p value<0.05.

Anxiety rate in patients with LLD

The prevalence of anxiety among patients with LLD was 47.3%. Notably, there was a significantly higher prevalence of anxiety among patients aged 60–69 years than among those aged 70 years and older. The prevalence was also notably higher among women when compared with men. Furthermore, the prevalence was significantly different among unmarried, married, divorced and widowed families. Widowed individuals experienced the highest prevalence among them. Patients residing in rural areas had a significantly higher anxiety prevalence than those in urban settings. Similarly, individuals living alone exhibited a significantly higher prevalence than those in nursing homes or living with family members. Additionally, patients who did not engage in regular exercise, slept less than 7 hours, were unable to care for themselves, had a history of falling, lived at a distance from healthcare facilities, faced difficulties in obtaining medications and had concurrent chronic infectious diseases exhibited significantly higher rates of anxiety. Patients who reported reduced family communication, frequently felt isolated and perceived a lack of responsiveness among family members during the COVID-19 pandemic also showed significantly higher anxiety prevalence. Moreover, individuals who expressed worries regarding COVID-19 and felt overwhelmed by the pandemic exhibited higher prevalence rates.

Multiple logistic regression

Logistic regression analysis was conducted to assess the factors related to anxiety in patients with LLD during the COVID-19 pandemic. Statistically significant indicators from univariate analysis were considered as independent variables, whereas anxiety served as the dependent variable (figure 1). The corrected regression model demonstrated that females exhibited significantly higher COVID-19 anxiety levels than males (AOR: 2.177, 95% CI 1.201 to 3.947). Similarly, anxiety levels were significantly higher among the widowed (AOR: 3.015, 95% CI 1.379 to 6.591), those residing at a distance from healthcare facilities (AOR: 3.765, 95% CI 1.906 to 7.438), and patients who often experienced worry (AOR: 1.984, 95% CI 1.111 to 3.543). Conversely, divorced individuals were 0.491 times less likely to experience anxiety than the unmarried (AOR: 0.491, 95% CI 0.245 to 0.988). Patients aged 70 years and older had significantly lower anxiety levels than those aged 60–69 years (AOR: 0.117, 95% CI 0.064 to 0.213). Furthermore, patients without difficulty in obtaining medications reported lower anxiety levels than others (AOR: 0.027, 95% CI 0.007 to 0.097). Those living with family members or in nursing homes exhibited substantially lower anxiety levels than individuals living alone (AOR: 0.080, 95% CI 0.022 to 0.282) (AOR: 0.019, 95% CI 0.004 to 0.087) (table 4).

Figure 1. Forest plot of anxiety related factors of COVID-19 in patients with late-life depression (LLD) (model 3).

Table 4

Factors associated with anxiety among the participants (N=1205)

Characteristics	Model 1	Model 2	Model 3
			AOR (95% CI)	P value (model 3)
Age (year)
60–69	Ref		Ref
≥70	0.201 (0.118 to 0.344)		0.117 (0.064 to 0.213)	<0.001*
Sex
Male	Ref		Ref
Female	3.204 (1.823 to 5.631)		2.177 (1.201 to 3.947)	0.010*
Marital status
Unmarried	Ref		Ref
Married	1.079 (0.632 to 1.841)		1.579 (0.890 to 2.801)	0.118
Divorced	0.558 (0.295 to 1.055)		0.491 (0.245 to 0.988)	0.046*
Widowed	3.422 (1.851 to 6.323)		3.015 (1.379 to 6.591)	0.006*
Living conditions
Living alone	Ref		Ref
Together with family members	0.029 (0.009 to 0.100)		0.080 (0.022 to 0.282)	<0.001*
Nursing homes	0.009 (0.002 to 0.038)		0.019 (0.004 to 0.087)	<0.001*
Time to walk to the nearest medical centre
<30 min		Ref	Ref
≥30		3.280 (1.768 to 6.085)	3.765 (1.906 to 7.438)	<0.001*
Difficult to obtain drugs
Yes		Ref	Ref
No		0.105 (0.047 to 0.235)	0.027 (0.007 to 0.097)	<0.001*
Do you worry about the pandemic
Almost not		Ref	Ref
Sometimes		4.769 (2.879 to 7.900)	1.984 (1.111 to 3.543)	0.021*

*A significant statistical difference according the p value<0.05.

Sensitivity analysis

A sensitivity analysis was performed excluding the participants with a history of self-discontinuation of drugs: the analysis was done for 1170 patients (after the exclusion of the 35 individuals with a history of self-discontinuation of drugs). Also, we performed an additional sensitivity analysis excluding the participants with coronary heart disease: the analysis was done for 1127 patients (after the exclusion of the 78 individuals with coronary heart disease). The primary outcome did not change materially (tables S3-S8 in the online supplemental appendix).

Additional control variables analysis

The factors with statistical differences (age and sex) in univariate analysis were excluded, and an additional control variables analysis was conducted. After controlling for age and sex, the results were similar to those of multiple logistic regression. It is worth noting that the COVID-19 anxiety level was significantly higher among those who felt isolated from others (AOR: 4.833, 95% CI 1.834 to 12.740) (tables S9 in the online supplemental appendix).

Discussion

The adjustment of epidemic policies by Chinese government in response to the current COVID-19 pandemic represents a significant public health and social issue. Existing studies have confirmed that the overall level of social anxiety has significantly increased during the pandemic.³² In addition, those most affected by these policy changes in China are children, older adults and patients, especially those with multiple underlying conditions, including LLD. Consequently, it is particularly crucial to assess the anxiety levels of patients with LLD.

Our study reveals that nearly half of the patients with LLD (47.3%) experience COVID-19 anxiety, a prevalence slightly lower than the highest reported incidence of 65%.³³ There has been no anxiety-related research specifically focused on patients with LLD during the COVID-19 pandemic in China. However, a study conducted in the USA using the Geriatric Anxiety Scale revealed that 35% of patients with LLD had at least one diagnosis of lifelong anxiety,³⁴ which is lower than our findings. Existing research reports on students,³⁵ medical students,³⁶ young people,³⁷ health workers,³⁸ the general population³⁹ and patients with mild symptoms⁴⁰ in China have indicated a prevalence of anxiety during the COIVD-19 pandemic ranging from 27.22% to 60.4%. Some factors, such as differences in the nature of work, sampling differences, different measurement tools, heterogeneity in age range, various risk factors, prepandemic conditions, and different cultural variations, can help explain the differences in anxiety levels across these studies.

Sex significantly affected the anxiety levels in this study. Female patients exhibited 2.177 times higher COVID-19-related anxiety scores than males, similar to previous studies.⁴¹ Women often exhibit more anxiety symptoms in response to both minor family issues and major societal events after retirement.⁴² For female patients with LLD, anxiety may be exacerbated by their prior experiences with health-related problems. Our study further established that patients with LLD with coexisting non-communicable chronic diseases had significantly higher anxiety scores than those without underlying conditions. This could be attributed to the severe anxiety symptoms experienced by patients with LLD and comorbid non-communicable chronic conditions. Moreover, the presence of underlying diseases, particularly respiratory conditions, increases the risk of severe and critically COVID-19 outcomes, contributing to increased anxiety during the pandemic.

In our study, marital status had a great impact on anxiety levels among participants during the pandemic. Widowhood, representing a major negative life event, was associated with higher anxiety scores due to drastic lifestyle changes, and the loss of close partners for emotional support. At the same time, divorced individuals exhibited significantly lower anxiety scores than unmarried individuals. Unmarried individuals often lack the opportunity to discuss the epidemic with spouses, which can intensify their inner anxiety. Meanwhile, unmarried seniors may experience greater social isolation, reduced social support and lower self-esteem, all of which are considered risk factors for increased anxiety during the COVID-19 pandemic.⁴³ Divorced patients, accustomed to living independently, may find it easier to cope with social events and isolation.

In this study, patients with LLD who had to walk more than 30 min to reach a medical centre were more likely to develop COVID-19 anxiety, which contrasts with a study conducted in Bangladesh.²⁶ A plausible explanation may be that individuals living in close proximity to medical centres find it easier to access medical care and have not experienced challenges in seeking medical assistance during the pandemic. This confidence in prompt medical care as assured by the government may contribute to reduced anxiety among patients with LLD living near medical facilities. However, individuals who frequently experienced worry exhibited significantly higher levels of COVID-19 anxiety. Their increased anxiety symptoms stem from excessive concern regarding the impending COVID-19 pandemic and personal health issues.

Interestingly, our findings revealed that patients aged 70 years and older were 0.117 times less likely to experience anxiety during the pandemic. This could be attributed to participants aged 60–69 years not having fully adjusted to the psychological role changes post retirement. They often undergo significant life changes, including relocation, loss of social networks and financial strain, all of which increase the risk of anxiety.⁴⁴ Furthermore, the current policy adjustments in China regarding postponed retirement and the extension of the retirement age may exacerbate mental health risks.⁴⁵ Research has also indicated that post retirement-related risk factors can exacerbate mental health problems.⁴⁶

Our study also highlighted the significant link between difficulty in accessing medications during the COVID-19 epidemic and anxiety. Previous research has shown that travel restrictions and lockdowns limit older adults’ access to routine healthcare, increasing their anxiety levels.⁴⁷ In addition, the COVID-19 pandemic has increased concerns about future medical supply shortages and the need for essential medicines.⁴⁸ Older adults often require medication for stable treatment, and the challenges associated with obtaining necessary prescriptions can exacerbate their anxiety. Nowadays, the digital divide among older patients has grown due to increased online healthcare visits and medication purchases, making it more challenging for them to benefit from digital solutions.⁴⁹

In our study, participants living with family members and in nursing homes demonstrated significantly lower anxiety scores than those living alone. Strong family relationships and daily communication can significantly alleviate anxiety levels. While the Chinese government has implemented restrictive measures⁵⁰ to curb the spread of SARS-CoV-2, such as social isolation strategies and traffic restrictions,⁵¹ the interdependence of family members can mitigate the risk of anxiety arising from isolation.⁵² This is also observed among those living in nursing homes. Outside the family, older adults often rely on peers of similar ages to establish interpersonal relationships and spend leisure time. The current social isolation policies limit interactions, which can have a significant impact on mental health during the pandemic,⁵³ especially for those living alone. Evidence suggests that anxiety is more likely to occur and increase in the context of social isolation⁵⁴ and a lack of social support or guidance⁵⁵ in dealing with COVID-19 anxiety.

Many patients with LLD exhibited varying degrees of panic regarding the pandemic when participating in our questionnaires. The relaxation of epidemic control measures such as the discontinuation of COVID-19 nucleic acid testing and health codes (a form of nucleic acid negative proof) might have contributed to increased anxiety among them. Moreover, the sudden shift from the ‘Dynamic clearing’ policy resulted in a gradual resurgence of the domestic epidemic, potentially amplifying anxiety levels. The National Health Commission is currently enhancing the capacity of COVID-19 wards, improving immunisation rates and providing transparent statistics to mitigate anxiety. The China Food and Drug Administration is urging companies to ensure a stable supply of related drugs.

To alleviate anxiety, certain measures should be actively promoted. Our study reveals that authoritative news sources are effective in reducing anxiety, and the spread of online anxiety should be curtailed. Although patients with LLD may have limited internet access, their families often consume online information, and this anxiety can permeate households. For recently retired older adults, proactive psychological counselling can be conducted. Moreover, the establishment of offline medical service grids can provide convenient services for these patients. Governments should intervene to ensure a stable drug supply and increase awareness of offline options to bridge the digital divide among older adults. Our results suggest that various interventions tailored to the marital statuses of patients can effectively reduce anxiety during the pandemic. Implementing telephone counselling and community psychological services for depressed elders living alone can also help alleviate pandemic-related anxiety.

This study is the first to reveal the COVID-19 anxiety levels and associated factors in patients with LLD. Most prior research has primarily focused on overall social anxiety levels. Amid adjustments to epidemic prevention policies, few have paid specific attention to the anxiety levels of older patients with LLD. Our study addresses this gap and provides policy-makers with a more comprehensive understanding of the issue. Given the increasing ageing population in China, it is of paramount importance to prioritise the mental health of older adults.

Limitations

Our study had some limitations: first, we collected information during the pandemic through a questionnaire interview. The sample was stratified random sampling, and there may be sampling errors. Therefore, the sample may not represent the entire data of older adults in China. Second, anxiety is based on questionnaires, which may lead to reporting bias and under-reporting anxiety in participants. Notwithstanding these limitations, this is the first study exploring anxiety related to COVID-19 among the patients with LLD in China. It can provide a positive data reference for the upcoming COVID-19 epidemic in China.

Conclusion

In summary, multiple factors^56–58 affect the anxiety experienced by patients with LLD during an epidemic. This study has analysed the COVID-19 anxiety-related factors among patients with LLD amid the adjustment of epidemic prevention policies. Key factors include sex, marital status, family situation, self-emotional assessment, self-health assessment, communication and access to medical resources. Our findings reveal that female patients with LLD who are widowed, reside far from medical facilities, are prone to worry, fall within the 60–69 age group, and face difficulties in obtaining medications are more likely to experience anxiety. In contrast, divorced individuals exhibit lower anxiety levels when compared with the unmarried, and those living with family members and in nursing homes report lower anxiety levels than those living alone.

This study carries significant policy implications. Despite domestic readiness for a potential surge in infections following the relaxation of epidemic policies, China has not yet encountered a substantial influx of infected individuals, and associated risks, including psychological problems, should be minimised. To mitigate anxiety among depressed elders, policy-makers and public health practitioners should carefully consider the dissemination of COVID-19-related information. Our findings highlight the importance of raising awareness of mental health issues among communities and families during this pandemic, and of ensuring that elders with depression receive adequate attention and access to appropriate treatment and support. In addition, collaboration between the Chinese government and local and international development partners is crucial in forming a dedicated strategy to provide comprehensive mental health support to vulnerable community groups, including depressed elders, both during the pandemic and in its aftermath. The involvement of community health workers in targeted interventions is pivotal in delivering cost-effective psychosocial support to depressed elders during the pandemic.

Data availability statement

Data are available upon reasonable request.

Ethics statements

Patient consent for publication

Not applicable.

Ethics approval

The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of Jiangsu Provincial Rongjun Hospital (JSRJH-No.2021-L002). Participants gave informed consent to participate in the study before taking part.

Footnote

Contributors JW and QZ conceived the study. Ju Wu, YS and WX carried out the data analysis and interpretation of the results. LQ performed literature searching and summary. JW contributed to writing the first draft of the manuscript, and JL edited and revised the manuscript. JW was responsible for the overall content as guarantor. All authors read and approved the final manuscript.

Funding The work is supported by the HENGRUI Foundation of Jiangsu Pharmaceutical Association (No. H202139).

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

References

¹ Peeling RW, Heymann DL, Teo Y-Y, et al. Diagnostics for COVID-19: moving from pandemic response to control. Lancet 2022; 399: 757–68. doi:10.1016/S0140-6736(21)02346-1

² WHO. Coronavirus disease (COVID-19) dashboard. 2022. Available: https://covid19.who.int/ [Accessed 18 Feb 2023 ].

³ Collaborators C-MD. Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic. Lancet 2021; 398: 1700–12.

⁴ García-Portilla P, de la Fuente Tomás L, Bobes-Bascarán T, et al. Are older adults also at higher psychological risk from COVID-19? Aging Ment Health 2021; 25: 1297–304. doi:10.1080/13607863.2020.1805723

⁵ Müller F, Röhr S, Reininghaus U, et al. Social isolation and loneliness during COVID-19 Lockdown: associations with depressive symptoms in the German old-age population. Int J Environ Res Public Health 2021; 18: 3615. doi:10.3390/ijerph18073615

⁶ Ouanes S, Kumar R, Doleh ESI, et al. Mental health, resilience, and religiosity in the elderly under COVID-19 quarantine in Qatar. Arch Gerontol Geriatr 2021; 96: 104457. doi:10.1016/j.archger.2021.104457

⁷ Daly M, Robinson E. Depression and anxiety during COVID-19. Lancet 2022; 399. doi:10.1016/S0140-6736(22)00187-8

⁸ Alexopoulos GS. Depression in the elderly. Lancet 2005; 365: 1961–70. doi:10.1016/S0140-6736(05)66665-2

⁹ Inoue Y, Stickley A, Yazawa A, et al. Childhood adversities, late-life stressors and the onset of depressive symptoms in community-dwelling older adults. Aging Ment Health 2022; 26: 828–33. doi:10.1080/13607863.2021.1875190

¹⁰ Manetti A, Hoertel N, Le Strat Y, et al. Comorbidity of late-life depression in the United States: a population-based study. Am J Geriatr Psychiatry 2014; 22: 1292–306. doi:10.1016/j.jagp.2013.05.001

¹¹ Grayson L, Thomas A. A systematic review comparing clinical features in early age at onset and late age at onset late-life depression. J Affect Disord 2013; 150: 161–70. doi:10.1016/j.jad.2013.03.021

¹² Tyler CM, McKee GB, Alzueta E, et al. A study of older adults' mental health across 33 countries during the COVID-19 pandemic. Int J Environ Res Public Health 2021; 18: 5090. doi:10.3390/ijerph18105090

¹³ Koçak O, Koçak ÖE, Younis MZ. The psychological consequences of COVID-19 fear and the moderator effects of individuals' underlying illness and witnessing infected friends and family. Int J Environ Res Public Health 2021; 18: 1836. doi:10.3390/ijerph18041836

¹⁴ Zhang J, Wang Y, Zhou M. Community resilience and psychological distress in Chinese older adults amid COVID-19: the roles of perceived community prevention effectiveness and risk perception. Aging & Mental Health 2022; 26: 1426–35. doi:10.1080/13607863.2021.1935458

¹⁵ Salerno JP, Boekeloo BO. LGBTQ identity-related victimization during COVID-19 is associated with moderate to severe psychological distress among young adults. LGBT Health 2022; 9: 303–12. doi:10.1089/lgbt.2021.0280

¹⁶ Leung HT, Gong W-J, Sit SMM, et al. COVID-19 pandemic fatigue and its Sociodemographic and psycho-behavioral correlates: a population-based cross-sectional study in Hong Kong. Sci Rep 2022; 12: 16114. doi:10.1038/s41598-022-19692-6

¹⁷ Gong WJ, Sit SMM, Lai AYK, et al. Adversity coping capability and its associations with mental health and family wellbeing amid the COVID-19 pandemic in Hong Kong. BMC Psychiatry 2022; 22: 553. doi:10.1186/s12888-022-04198-2

¹⁸ Clendennen SL, Chen B, Sumbe A, et al. Patterns in mental health symptomatology and cigarette, e-cigarette and marijuana use among Texas youth and young adults amid the COVID-19 pandemic. Nicotine Tob Res 2023; 25: 266–73. doi:10.1093/ntr/ntac205

¹⁹ Liu J, Kwan C, Deng J, et al. The mental health impact of the COVID-19 pandemic on older adults in China: a systematic review. Int J Environ Res Public Health 2022; 19: 14362. doi:10.3390/ijerph192114362

²⁰ Choi JH, Choi SH, Yun KW. Risk factors for severe COVID-19 in children: a systematic review and meta-analysis. J Korean Med Sci 2022; 37: e35. doi:10.3346/jkms.2022.37.e35

²¹ Weich S. Mental health after COVID-19. BMJ 2022; 376: 326. doi:10.1136/bmj.o326

²² Wong SYS, Zhang D, Sit RWS, et al. Impact of COVID-19 on loneliness, mental health, and health service utilisation: a prospective cohort study of older adults with multimorbidity in primary care. Br J Gen Pract 2020; 70: e817–24. doi:10.3399/bjgp20X713021

²³ Yang L, Yang Z, Xia Y. Relationship between negative coping style and fear of COVID-19 among Wuhan college students during the post-pandemic period: a moderated chain mediation model. Front Psychiatry 2022; 13: 994685. doi:10.3389/fpsyt.2022.994685

²⁴ Harvey SB, Epstein RM, Glozier N, et al. Mental illness and suicide among physicians. Lancet 2021; 398: 920–30. doi:10.1016/S0140-6736(21)01596-8

²⁵ Tanaka T, Okamoto S. Increase in suicide following an initial decline during the COVID-19 pandemic in Japan. Nat Hum Behav 2021; 5: 229–38. doi:10.1038/s41562-020-01042-z

²⁶ Mistry SK, Ali AM, Yadav UN, et al. COVID-19 related anxiety and its associated factors: a cross-sectional study on older adults in Bangladesh. BMC Psychiatry 2022; 22: 737. doi:10.1186/s12888-022-04403-2

²⁷ Lee SA. Coronavirus anxiety scale: a brief mental health screener for COVID-19 related anxiety. Death Stud 2020; 44: 393–401. doi:10.1080/07481187.2020.1748481

²⁸ Spitzer RL, Kroenke K, Williams JBW, et al. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med 2006; 166: 1092–7. doi:10.1001/archinte.166.10.1092

²⁹ Morrissette M. School closures and social anxiety during the COVID-19 pandemic. J Am Acad Child Adolesc Psychiatry 2021; 60: 6–7. doi:10.1016/j.jaac.2020.08.436

³⁰ Wang S, Quan L, Chavarro JE, et al. Associations of depression, anxiety, worry, perceived stress, and loneliness prior to infection with risk of post-COVID-19 conditions. JAMA Psychiatry 2022; 79: 1081–91. doi:10.1001/jamapsychiatry.2022.2640

³¹ Liu Y, Li P, Lv Y, et al. Public awareness and anxiety during COVID-19 epidemic in China: a cross-sectional study. Compr Psychiatry 2021; 107: 152235. doi:10.1016/j.comppsych.2021.152235

³² Penninx BWJH, Benros ME, Klein RS, et al. How COVID-19 shaped mental health: from infection to pandemic effects. Nat Med 2022; 28: 2027–37. doi:10.1038/s41591-022-02028-2

³³ Saade YM, Nicol G, Lenze EJ, et al. Comorbid anxiety in late-life depression: relationship with remission and suicidal ideation on venlafaxine treatment. Depress Anxiety 2019; 36: 1125–34. doi:10.1002/da.22964

³⁴ Lenze EJ, Mulsant BH, Shear MK, et al. Comorbid anxiety disorders in depressed elderly patients. Am J Psychiatry 2000; 157: 722–8. doi:10.1176/appi.ajp.157.5.722

³⁵ Zhang Y, Bao X, Yan J, et al. Anxiety and depression in Chinese students during the COVID-19 pandemic: a meta-analysis. Front Public Health 2021; 9. doi:10.3389/fpubh.2021.697642

³⁶ Mao Y, Zhang N, Liu J, et al. A systematic review of depression and anxiety in medical students in China. BMC Med Educ 2019; 19: 327. doi:10.1186/s12909-019-1744-2

³⁷ Wu Y, Zhang T, Ye Z, et al. Public anxiety through various stages of COVID-19 coping: evidence from China. PLoS ONE 2022; 17: e0270229. doi:10.1371/journal.pone.0270229

³⁸ Luo M, Guo L, Yu M, et al. The psychological and mental impact of coronavirus disease 2019 (COVID-19) on medical staff and general public - a systematic review and meta-analysis. Psychiatry Res 2020; 291: 113190. doi:10.1016/j.psychres.2020.113190

³⁹ Huang Y, Zhao N. Generalized anxiety disorder, depressive symptoms and sleep quality during COVID-19 outbreak in China: a web-based cross-sectional survey. Psychiatry Res 2020; 288: 112954. doi:10.1016/j.psychres.2020.112954

⁴⁰ Zhang J, Yang Z, Wang X, et al. The relationship between resilience, anxiety and depression among patients with mild symptoms of COVID-19 in China: a cross-sectional study. J Clin Nurs 2020; 29: 4020–9. doi:10.1111/jocn.15425

⁴¹ Wang Q, Zhang J, Yao H, et al. Prevalence and associated factors of anxiety among the population in an urban area of China: a cross-sectional study. BMJ Open 2022; 12: e062431. doi:10.1136/bmjopen-2022-062431

⁴² Gao Y-D, Ding M, Dong X, et al. Risk factors for severe and critically ill COVID-19 patients: a review. Allergy 2021; 76: 428–55. doi:10.1111/all.14657

⁴³ Prince MJ, Harwood RH, Blizard RA, et al. Social support deficits, loneliness and life events as risk factors for depression in old age. the gospel oak project VI. Psychol Med 1997; 27: 323–32. doi:10.1017/s0033291796004485

⁴⁴ Dang L, Ananthasubramaniam A, Mezuk B. Spotlight on the challenges of depression following retirement and opportunities for interventions. Clin Interv Aging 2022; 17: 1037–56. doi:10.2147/CIA.S336301

⁴⁵ Li W, Ye X, Zhu D, et al. The longitudinal association between retirement and depression: a systematic review and meta-analysis. Am J Epidemiol 2021; 190: 2220–30. doi:10.1093/aje/kwab125

⁴⁶ Li Y, Zhang F, Feng D. Does type A personality have a positive or negative impact on the delayed retirement intention of older workers Australas J Ageing 2022; 41. doi:10.1111/ajag.13119 Available: https://onlinelibrary.wiley.com/toc/17416612/41/4

⁴⁷ Ghimire S, Shrestha A, Yadav UN, et al. Older adults with pre-existing noncommunicable conditions and their Healthcare access amid COVID-19 pandemic: a cross-sectional study in Eastern Nepal. BMJ Open 2022; 12: e056342. doi:10.1136/bmjopen-2021-056342

⁴⁸ Romano S, Galante H, Figueira D, et al. Time-trend analysis of medicine sales and shortages during COVID-19 outbreak: data from community pharmacies. Res Social Adm Pharm 2021; 17: 1876–81. doi:10.1016/j.sapharm.2020.05.024

⁴⁹ Martins Van Jaarsveld G. The effects of COVID-19 among the elderly population: a case for closing the digital divide. Front Psychiatry 2020; 11: 577427. doi:10.3389/fpsyt.2020.577427

⁵⁰ Hasnain M, Pasha MF, Ghani I. Combined measures to control the COVID-19 pandemic in Wuhan, Hubei, China: a narrative review. J Biosaf Biosecur 2020; 2: 51–7. doi:10.1016/j.jobb.2020.10.001

⁵¹ Jutai JW, Tuazon JR. The role of assistive technology in addressing social isolation, loneliness and health inequities among older adults during the COVID-19 pandemic. Disabil Rehabil Assist Technol 2022; 17: 248–59. doi:10.1080/17483107.2021.2021305

⁵² Dai L, Xiong F, Li W. The impact of social quarantine on the living status and mental health of the elderly in the Wuhan community: one year after Wuhan COVID-19 blockade. BMC Geriatr 2022; 22: 903. doi:10.1186/s12877-022-03560-z

⁵³ Cao B, Wang D, Wang Y, et al. Moderating effect of people-oriented public health services on depression among people under mandatory social isolation during the COVID-19 pandemic: a cross-sectional study in China. BMC Public Health 2021; 21: 1374. doi:10.1186/s12889-021-11457-6

⁵⁴ Sepúlveda-Loyola W, Rodríguez-Sánchez I, Pérez-Rodríguez P, et al. Impact of social isolation due to COVID-19 on health in older people: mental and physical effects and recommendations. J Nutr Health Aging 2020; 24: 938–47. doi:10.1007/s12603-020-1500-7

⁵⁵ Mukhtar S. Psychological health during the coronavirus disease 2019 pandemic outbreak. Int J Soc Psychiatry 2020; 66: 512–6. doi:10.1177/0020764020925835

⁵⁶ Shi L, Lu Z-A, Que J-Y, et al. Prevalence of and risk factors associated with mental health symptoms among the general population in China during the coronavirus disease 2019 pandemic. JAMA Netw Open 2020; 3: e2014053. doi:10.1001/jamanetworkopen.2020.14053

⁵⁷ Zhang J, Lu H, Zeng H, et al. The differential psychological distress of populations affected by the COVID-19 pandemic. Brain Behav Immun 2020; 87: 49–50. doi:10.1016/j.bbi.2020.04.031

⁵⁸ Benke C, Autenrieth LK, Asselmann E, et al. Lockdown, quarantine measures, and social distancing: associations with depression, anxiety and distress at the beginning of the COVID-19 pandemic among adults from Germany. Psychiatry Res 2020; 293: 113462. doi:10.1016/j.psychres.2020.113462