Startseite Impact of omicron wave and associated control measures in Shanghai on health management and psychosocial well-being of patients with chronic conditions
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Impact of omicron wave and associated control measures in Shanghai on health management and psychosocial well-being of patients with chronic conditions

  • Zhimin Xu , Gabriela Lima de Melo Ghisi , Xia Liu , Lixian Cui und Sherry L. Grace EMAIL logo
Veröffentlicht/Copyright: 28. März 2023

Abstract

The objective of this cross-sectional study was to investigate health management, well-being, and pandemic-related perspectives of chronic disease patients in the context of stringent measures, and associated correlates. A self-report survey was administered during the Omicron wave lockdown in Shanghai, China. Items from the Somatic Symptom Scale (SSS) and Symptom Checklist-90 were administered, as well as pandemic-related items. Overall, 1,775 patients (mostly married females with hypertension) were recruited through a community family physician group. Mean SSS scores were 36.1 ± 10.5/80, with 41.5% scoring in the elevated range (i.e., >36). In an adjusted model, being female, diagnosis of coronary artery disease and arrhythmia, perceived impact of pandemic on life, health condition, change to exercise routine, tolerance of control measures, as well as perception of future and control measures were significantly associated with greater distress. One-quarter perceived the pandemic had a permanent impact on their life, and 44.1% perceived at least a minor impact. One-third discontinued exercise due to the pandemic. While 47.6% stocked up on their medications before the lockdown, their supply was only enough for two weeks; 17.5% of participants discontinued use. Chief among their fears were inability to access healthcare (83.2%), and what they stated they most needed to manage their condition was medication access (65.6%). Since 2020 when we assessed a similar cohort, distress and perceived impact of the pandemic have worsened. Greater access to cardiac rehabilitation in China could address these issues.

1 Introduction

The coronavirus disease (COVID-19) pandemic, with its many unpredictable waves, has resulted in major negative impacts on economies, health systems, and citizens worldwide [1,2]. While the impact of COVID-19 on the health of all people has been of major concern, it has been a particular concern for those at higher risk of severe outcomes. This includes notably patients with chronic conditions, such as cardiovascular diseases (CVD). For instance, hospitalization rates and mortality rates are much higher in this population; in the United States alone, chronic diseases account for 75% of aggregate healthcare spending and are responsible for 7 out of 10 deaths [3]; in China, the deaths caused by chronic diseases account for 87% of total deaths [4].

Measures to control infection spread, such as physical distancing often necessitating closure of essential businesses [5], as well as diversion of healthcare resources for COVID-19 [6], have also had a negative impact. In the general population, this has resulted in reduced access to care [7] as well as increases in mental health conditions [8]. Despite their greater risk, there is only limited study of the impacts of the pandemic and associated control measures on the psychosocial well-being and self-management of patients with chronic conditions; we identified some abstracts only to date [9,10].

Government policy varies worldwide in terms of implementation of infection prevention and control measures. Based on the COVID-19 stringency index, such strategies are among the most stringent in China [11]. For example, in one of the world’s most populous cities of Shanghai, a strict “closed-loop” control system has been enforced. This involves home isolation except for medical reasons, with extra-household interpersonal contact and outdoor time forbidden, and transactions quickly moving online. This caused residents to become anxious and unsettled [12].

Given these unprecedented circumstances, assessment of the impacts of these strict control measures on chronic disease patients is needed, particularly in the context of some of the most stringent control measures globally, in one of the most densely populated cities in the world where risk of transmission is hence greater [13,14], and 2 years into the pandemic when these patients have thus been coping with isolation, economic impacts, as well as changed and inconvenient access to care and treatments for a prolonged period – specifically during the Omicron wave in Shanghai. Therefore, the objective of this study was to assess these impacts in terms of (1) psychosocial well-being, (2) health management, and (3) perceptions related to the pandemic and associated control measures. The associations of their health/well-being with the perceived impact of the pandemic on their health were also tested, as were the association of pandemic-related attitudes with psychological well-being.

2 Methods

2.1 Design and procedure

Study approval was secured from the Ethics Committee of Xinhua Hospital, affiliated with Shanghai Jiaotong University School of Medicine (XHEC-C-2022-042). The anonymous online survey in Simplified Chinese was created by the Cardiac Rehabilitation (CR) group, Health Risk Assessment and Control of the Chinese Preventive Medical Association. Data collection for this cross-sectional study was undertaken between March and June 2022. It was distributed via Wenjuanxing by family doctors who belonged to the Community Physician group of the Psychosomatic Medicine Special Committee of the Shanghai Association of Integrated Chinese and Western Medicine; this group cooperates closely with the Chinese Preventive Medical Association.

2.2 Setting and participants

During the Omicron wave lockdown in Shanghai, residents including patients with chronic conditions were to remain indoors and could not go outside to exercise or purchase groceries at the supermarket. They could receive care via telehealth or consultation in internet hospitals. Medication was available through online pharmacies with in-home delivery. This could be challenging for seniors who may have low digital literacy or who do not have access to a smartphone.

To receive in-person care, health codes had to be scanned. Daily nucleic acid tests were mandatory for in-patients and the one allowed family member who could accompany a patient.

Participant inclusion criteria were the following: outpatients with cardiovascular and cerebrovascular diseases, diabetes, kidney, or another chronic condition (e.g., cancer). Participant exclusion criteria were: (1) outpatients with severe cognitive impairments or any conditions that prevent them from being able to understand and agree to participate in the research; (2) outpatients unwilling to cooperate with the research protocol; and (3) outpatients with any missing data within questionnaire items.

2.3 Measures

All items were self-reported. Two relevant and validated psychosocial scales available for use in China were selected by the CR group, assessing depressive and anxiety symptoms, somatic symptoms, as well as sleep and cognitive issues. First, five items from the validated Symptom Checklist-90 were administered to assess depressive symptoms [15,16]. There is a 5-point Likert-type response option for each, with a maximal score of 25; higher scores indicate more severe symptoms.

The Chinese version of the Somatic Symptom Scale (SSS) was also administered [17]. It comprises 20 items, each assessed on a 4-point Likert-type scale. Items assess physical (e.g., half the items query each body system), depressive, and anxiety symptoms, and the final 2 items assess sleep and cognitive issues. Thus, the SSS assesses psychosocial well-being broadly. Total scores range from 20 to 80; scores ≥36 were considered elevated.

In addition, non-psychometrically validated items related to pandemic perceptions and health management were generated by the CR group, based on their knowledge and expertise. Response options were forced choice, with some where respondents could select all that apply. Participants were asked to respond these items based on their experience in the prior 2 weeks.

2.4 Statistical analysis

IBM SPSS statistics version 25.0 was used for all statistical analyses, with p < 0.05 considered statistically significant. Descriptive analysis was first performed. Perceptions of impact of the pandemic (at least minor vs none) on their chronic condition and psychosocial well-being were tested using chi-square and t-tests as applicable. The association of pandemic-related perceptions with SSS scores was assessed using the t-test and chi-square, as applicable. Finally, associations between participant sociodemographic and clinical characteristics with SSS scores were tested using logistic regression analysis as applicable. Then, an adjusted model was computed for the association of the SSS with those sociodemographic, clinical, and pandemic-related perceptions that were significant at p < 0.05.

3 Results

Of 1,775 responding patients, most were educated, working, married females living with family, and who had healthcare insurance (Table 1). As shown in Table 2, most participants had hypertension, over one-fifth had diabetes, and just under that coronary artery disease. Other conditions included cancer, as well as endocrine and immune diseases, and psychiatric conditions.

Table 1

Participant sociodemographic characteristics (N = 1775)

Characteristic n (%)/mean ± SD
Sex (female) 1,061 (59.8)
Age 57.69 ± 13.80
Marital status
 Married 1,489 (83.9)
 Widowed 111 (6.3)
 Never married 107 (6.0)
 Separated/divorced 68 (3.8)
Living situation
 With children and/or other extended family members 786 (44.3)
 With partner only 768 (43.3)
 Alone 221 (12.5)
Highest educational attainment
 Junior college or senior high school 818 (46.1)
 Bachelor and above 723 (40.7)
 Junior high school and below 234 (13.2)
Income status
 Has work income 1,501 (84.6)
 No fixed income (e.g., rely on children, state subsidies) 138 (7.8)
 Has additional source of income on top of salary (e.g., online) 136 (7.7)
Current or previous occupation
 City worker 557 (31.4)
 Civil servants 440 (24.8)
 Management (private or public) 289 (16.3)
 Health care provider 181 (10.2)
 Teacher 129 (7.3)
 Government 59 (3.3)
 Own business 44 (2.5)
 Farmer 34 (1.9)
 Research 34 (1.9)
 Other (e.g., Arts) 8 (0.5)
Healthcare insurance
 Employee 960 (54.1)
 Town residents 664 (37.4)
 Off-site 77 (4.3)
 Self-pay 74 (4.2)

SD, standard deviation.

Table 2

Participant physical and mental health and association with pandemic health impact (n = 1,775)

n (%)/mean ± SD Perceived impact of pandemic on health condition
No effect (n = 993) Minor or greater (n = 782) X 2/t p
Chronic condition
 Coronary artery disease 333 (18.8) 132 (13.3) 201 (25.7) 44.209 <0.001
 Heart failure 49 (2.8) 12 (1.2) 37 (4.7) 20.228 <0.001
 Arrhythmia 189 (10.6) 75 (7.6) 114 (14.6) 22.693 <0.001
 Hypertension 938 (52.8) 481 (48.4) 457 (58.4) 17.559 <0.001
 Cerebrovascular disease 98 (5.5) 37 (3.7) 61 (7.8) 13.923 <0.001
 Diabetes 405 (22.8) 210 (21.1) 195 (24.9) 3.565 0.059
 Renal disease 62 (3.5) 23 (2.3) 39 (5.0) 9.259 0.002
 Other 780 (43.9) 420 (43.7) 360 (44.2) 0.049 0.825
Years living with chronic condition
 <5 years 692 (39.0) 415 (41.8) 277 (35.4) 10.488 0.015
 5–10 years 510 (28.7) 273 (27.5) 237 (30.3)
 10–20 years 344 (19.4) 173 (17.4) 171 (21.9)
 >20 years 229 (12.9) 132 (13.3) 97 (12.4)
History psychiatric disorder
 Yes, being treated with meds 148 (8.3) 49 (4.9) 99 (12.7) 97.857 <0.001
 Yes, but untreated 116 (6.5) 29 (2.9) 87 (11.1)
 Yes, but remitted 97 (5.5) 45 (4.5) 52 (6.6)
 No 1,414 (79.7) 870 (87.6) 544 (69.6)
Major life event (n, % yes) 232 (13.1) 103 (10.4) 129 (16.5) 14.438 <0.001
 Somatic self-rating scale (/80) 36.07 ± 10.50 31.38 ± 7.68 42.03 ± 10.58 −23.666 <0.001
 Somatic symptoms (/36) 15.54 ± 4.65 13.52 ± 3.47 18.10 ± 4.69 −22.864 <0.001
 Anxiety symptoms (/20) 8.84 ± 2.95 7.68 ± 2.18 10.30 ± 3.14 −19.925 <0.001
 Depressive symptoms (/16) 7.59 ± 2.61 6.56 ± 2.12 8.90 ± 2.59 −20.437 <0.001
 Sleep and cognitive symptoms (/8) 4.10 ± 1.36 3.62 ± 1.17 4.72 ± 1.35 −18.017 <0.001
SCL-90 depressive items (/25) 9.94 ± 4.29 8.35 ± 3.28 11.95 ± 4.57 −18.563 <0.001
 Sadness (/5) 2.39 ± 1.02 2.07 ± 0.88 2.80 ± 1.03 −15.703 <0.001
 Suicidal ideation (/5) 1.45 ± 0.80 1.21 ± 0.54 1.75 ± 0.96 −13.882 <0.001
 Hopelessness (/5) 1.83 ± 1.02 1.50 ± 0.79 2.25 ± 1.12 −15.865 <0.001
 Feel empty inside (/5) 2.04 ± 1.03 1.70 ± 0.85 2.47 ± 1.07 −16.400 <0.001
 Anhedonia (/5) 2.23 ± 1.09 1.87 ± 0.93 2.69 ± 1.10 −16.622 <0.001

SD, standard deviation; SCL, symptom checklist 90.

Note: some items allowed single responses and others multiple.

The mean psychosocial well-being scores are shown in Table 2. Approximately 80% had no known psychiatric history. 41.5% of participants with elevated SSS scores indicating psychological distress (Table 3) was significantly more likely to be women, older, unmarried, living alone, with no fixed income, and had lower educational attainment than those with subclinical scores (all p ≤ 0.016). All chronic conditions except hypertension and diabetes were associated with significantly more distress on the SSS (all p ≤ 0.013), and they were living longer with their condition (p < 0.001). They were significantly more likely to have suffered a major life event (16.7% vs 10.5%; p < 0.001).

Table 3

Participant pandemic attitudes and impact on chronic disease management (N = 1,775)

n (%)/mean ± SD Association with somatic symptoms
Elevated (n = 736) Subclinical (n = 1,039) X 2/t p
Source of Pandemic-related Information
 Traditional and new media (e.g., WeChat) 1,624 (91.5) 651 (88.5) 973 (93.6) 16.124 <0.001
 Television and newspaper only (traditional media) 110 (6.2) 59 (8.0) 51 (4.9)
 No media, only family or neighbors 41 (2.3) 36 (3.5) 15 (1.4)
Impact of pandemic on life
 None 210 (11.8) 42 (5.7) 168 (16.2) 200.903 <0.001
 Only physical distancing 184 (10.4) 108 (14.7) 76 (7.3)
 Temporary 947 (53.4) 302 (41.0) 645 (62.1)
 Permanent changes 434 (24.5) 284 (38.6) 150 (14.4)
View of pandemic status in future and control measures
 Situation is serious, and worry about future 652 (36.7) 378 (51.4) 274 (26.4) 144.777 <0.001
 Think the strict measures will turn things around 403 (22.7) 144 (19.6) 259 (24.9)
 Always optimistic 397 (22.4) 85 (11.5) 312 (30.0)
 I am not worried about getting Omicron 323 (18.2) 129 (17.5) 194 (18.7)
How long strict control measures can be tolerated
 I cannot even endure 1–2 weeks 166 (9.4) 111 (15.1) 55 (5.3) 65.327 <0.001
 A month at maximum 847 (47.7) 367 (49.9) 480 (46.2)
 3 months maximum 258 (14.5) 79 (10.7) 179 (17.2)
 6 months maximum 23 (1.3) 9 (1.2) 14 (1.3)
 As long as I can get necessities, I can endure it for a long time 481 (27.1) 170 (23.1) 311 (29.9)
Impact of pandemic on health condition
 No effect 993(55.9) 214 (29.1) 779 (75.0) 407.066 <0.001
 Minor 564 (31.8) 338 (45.9) 226 (21.8)
 Serious 218 (12.3) 184 (25.0) 34 (3.3)
Adherence to control measures
 Stayed home 772 (43.5) 315 (42.8) 457 (44.0) 10.330 0.016
 Only went out to get food and medicine 518 (29.2) 193 (26.2) 325 (31.3)
 Community sealed, so could not go out 460 (25.9) 215 (29.2) 245 (23.6)
 No change 25 (1.4) 13 (1.8) 12 (1.2)
Exercise maintenance when strict control measures
 Changed to exercise in home 761 (42.9) 240 (32.6) 521 (50.1) 58.656 <0.001
 Stopped exercise because of pandemic 595 (33.5) 306 (41.6) 289 (27.8)
 Do not exercise as usual 366 (20.6) 169 (23.0) 197 (19.0)
 Exercise in residential area as before 53 (3.0) 21 (2.9) 32 (3.1)
Access to medication when strict control measures
 I was sure to stock up before 845 (47.6) 306 (41.6) 539 (51.9) 50.597 <0.001
 Someone else got my medication 360 (20.3) 165 (22.4) 195 (18.8)
 Discontinued use 310 (17.5) 170 (23.1) 140 (13.5)
 Internet dispensing 228 (12.8) 74 (10.1) 154 (14.8)
 Borrowed medicine from another 32 (1.8) 21 (2.9) 11 (1.1)
Available supply of chronic disease medication
 I discontinued 236 (13.3) 116 (15.8) 120 (11.5) 66.290 <0.001
 Not enough even for a week 309 (17.4) 168 (22.8) 141 (13.6)
 Enough for 1–2 weeks 469 (26.4) 213 (28.9) 256 (24.6)
 Enough for 2–4 weeks 393 (22.1) 138 (18.8) 255 (24.5)
 More than a month on hand 368 (20.7) 101 (13.7) 267 (25.7)
Greatest worries about chronic condition related to Omicron
 Being unable to access care due to control measures 1,477 (83.2) 640 (87.0) 837 (80.6) 12.625 <0.001
 Getting infected and deteriorating 747 (42.1) 372 (50.5) 375 (36.1) 36.913 <0.001
 The economic impact of the pandemic affects health resourcing 438 (24.7) 190 (25.8) 248 (23.9) 0.878 0.349
 Other 112 (6.3) 40 (5.4) 72 (6.9) 1.629 0.202
What needed during waves to manage chronic condition
 Easier access to medications 1,165 (65.6) 478 (64.9) 687 (66.1) 0.264 0.607
 Ensuring access to care regardless of control measures 1,147 (64.6) 512 (69.6) 635 (61.1) 13.451 <0.001
 Guarantee of emergency hospital and outpatient care access 992 (55.9) 450 (61.1) 542 (52.2) 14.079 <0.001
 Facilitating access to care even if I cannot use or do not have a mobile phone 760 (42.8) 335 (45.5) 425 (40.9) 3.742 0.053
 Greater availability of telehealth (year) 659 (37.1) 265 (36.0) 394 (37.9) 0.677 0.411

Note: some items allowed single responses and others multiple.

SD, standard deviation.

Variables used for association tests in previous table.

3.1 Impact of pandemic

As shown in Table 3, most participants perceived the pandemic had a temporary impact on their lives, but almost one-quarter perceived changes would be permanent. In terms of the future, over one-third were very worried about it, and one-quarter each was optimistic or perceived the control measures would be successful in mitigating COVID-19 impact. Most commonly, participants reported that they could withstand the lockdown for a month.

Half perceived the pandemic had at least a minor impact on their health or more (Table 3). As shown in Table 2, those perceiving health impact were significantly more likely to be older, unmarried, and with lower educational attainment and income. Participants with cardiovascular, renal, and psychiatric diseases, who had their diseases for more years, reported major life events, and higher somatic and depressive symptoms (including all subscales) were also significantly more likely to perceive the impact of the pandemic on their health than their counterparts (Table 3).

Forty percent exercised at their home, but over one-third stopped exercising and one-fifth changed their exercise (Table 3). Participants who had their condition for fewer years (p = 0.009) and who had lower somatic (p < 0.001) were more likely to change their exercise due to the pandemic and associated control measures (no association with chronic condition).

With regard to medication, while almost half tried to stock up before the lockdown, almost one-fifth of participants discontinued use (Table 3). Only just over 10% of this older cohort used an internet-based pharmacy. Of those who still had medication, just under half had enough supply to last at least 2 weeks.

Participant’s greatest worries related to Omicron and their chronic condition are also shown in Table 3. Chief among them were fears around inability to access healthcare and medicines, as well as contracting COVID-19 and their health deteriorating. To best manage their chronic condition during the wave, participants most wanted guaranteed access to care and medication, particularly even if they do not have – or are not able to use – a mobile phone.

Pandemic perceptions were highly associated with SSS (Table 3). Participants who were significantly less likely to use new media to get pandemic-related information and more often relied on family or neighbours for information only and who were more likely to view pandemic impacts on their lives as permanent were less optimistic about the future, reported being able to tolerate control measures for a significantly shorter amount of time, perceived a significantly greater impact of the pandemic on their health, were less likely to go out even to get food or medicine, were more likely to stop exercise, and were more likely to discontinue medicine use or had less supply on hand, and had elevated SSS scores, indicating not only somatic but also anxious, depressive, and sleep-related symptoms. These participants with elevated distress were also more concerned about all but two of the worries related to the pandemic and were more likely to want assurances around access to in- and outpatient care regardless of COVID-19 wave status and associated control measures. An adjusted model is shown in Table 4.

Table 4

Model assessing correlates of SSS

Independent variable OR 95% CI p
Age 0.997 0.985–1.008 0.572
Sex
 Male 1
 Female 1.577 1.220–2.039 0.001
Marital status
 Married 1
 Widowed 0.898 0.502–1.606 0.716
 Never married 0.808 0.446–1.463 0.481
 Divorced 1.196 0.633–2.259 0.581
Living arrangement
 Alone 1
 With partner only 0.678 0.424–1.086 0.106
 With children and/or other extended family members 0.677 0.438–1.045 0.078
Educational attainment
 Junior high school and below 1
 Junior college or senior high school 1.021 0.693–1.503 0.918
 Bachelor and above 0.842 0.552–1.284 0.425
Income status
 No fixed income (e.g., rely on children, state subsidies) 1
 Has work income 0.696 0.433–1.118 0.134
 Has additional source of income on top of salary (e.g., online) 0.630 0.330–1.203 0.161
Diagnosis
 Coronary artery disease 2.006 1.439–2.797 <0.001
 Arrhythmia 2.588 1.731–3.870 <0.001
Pandemic media source type
 Traditional and new media (e.g., WeChat) 1
 Television and newspaper only (traditional media) 0.932 0.558–1.555 0.787
 No media, only family or neighbors 1.139 0.432–3.002 0.793
Perceived impact of pandemic on life
 None 1
 Only physical distancing 2.566 1.491–4.418 0.001
 Temporary 1.433 0.929–2.209 0.103
 Permanent changes 3.298 2.051–5.305 <0.001
Perception of future and control measures
 Situation is serious, and worry about future 1
 Think the strict measures will turn things around 0.632 0.456–0.876 0.006
 Always optimistic 0.418 0.291–0.600 <0.001
 I am not worried about getting Omicron 0.636 0.453–0.894 0.009
Duration can tolerate control measures
 I cannot even endure 1−2 weeks 1
 A month at maximum 0.534 0.341–0.835 0.006
 3 months maximum 0.415 0.245–0.706 0.001
 6 months maximum 0.623 0.199–1.951 0.416
 As long as I can get necessities, I can endure it for a long time 0.496 0.305–0.806 0.005
Adherence to control measures
 No change 1
 Only went out to get food and medicine 0.854 0.301–2.423 0.767
 Stayed home 0.972 0.343–2.756 0.957
 Community sealed, so could not go out 1.017 0.355–2.913 0.975
Perceived impact of pandemic on health condition
 No effect 1
 Minor 3.900 3.024–5.030 <0.001
 Serious 12.905 8.340–19.968 <0.001
Change to exercise routine due to pandemic
 Do not exercise as usual 1
 Stopped exercise because of pandemic 0.850 0.609–1.187 0.340
 Changed to exercise in home 0.596 0.432–0.822 0.002
 Exercise in residential area as before 0.938 0.445–1.981 0.868

SSS: somatic self-rating scale, including physical disorders, depressive, anxious, sleep and cognitive symptoms as well.

4 Discussion

This is the first or one of the first full studies to examine the impact of the COVID-19 pandemic and its associated control measures in a large sample of older adults with chronic conditions [18]. It was undertaken during the Omicron wave in Shanghai, where the population is dense, control measures were strict, and the pandemic had been ongoing for 2 years. Despite that few were living alone that could mitigate isolation during the lockdown, consistent with findings in the general population [19,20], overall results show elevated distress but also negative impacts on chronic disease management. We must ensure that those with chronic conditions have the resources they need to cope and manage their condition, such as is offered in cardiac rehabilitation.

The burden of distress was quite high, even when considering that rates of psychological distress are higher in those with chronic disease [21,22] and rates in the Chinese population. Generally, rates of distress decline with age, but the opposite finding was found herein, likely due to the increased risk of severe COVID-19 with age [23,24,25]. Many patients were very concerned about the impact of the pandemic on their health and their access to care if needed. Research has shown that much preventive and non-preventive care was avoided due to the fear of exposure to SARS-CoV-2, and thus periodic health examinations regarding chronic disease risk factors were likely also missed, likely leaving weight [26], blood pressure, lipids, and blood glucose less-optimally managed.

In terms of health management, despite the proven benefits of secondary prevention behaviours, such as exercise and medication adherence [27], many chronic disease patients discontinued them. Despite the availability of online pharmacies and patient’s low supply of medication, these were not widely used, likely due to low digital literacy or technology access in the elderly [28,29]. One-third stopped exercising, and another quarter changed their exercise rather than moving their exercise routine home. How outpatients were able to maintain a healthy diet with dwindling food supplies would be another important area for study [30], as would be impacts of pandemic-related lockdowns on tobacco access and use in chronic disease patients. Moreover, given the importance of relationship quality to health [31], the impact of prolonged lockdown on relationships in chronic disease patients warrants study.

In our earlier examination of the impact of the pandemic and associated control measures on older adults (many of whom similarly had hypertension, CVD, or diabetes) in the spring of 2020 [32], mean scores on the SSS were somewhat lower at 29/80 vs 36 herein (all mean subscale scores were somewhat lower as well). In terms of pandemic impact on life, only 6% perceived this would be permanent in 2020 vs 25% in 2022. Also in 2020, most participants (47%) reported they could endure strict prevention and control measures for a long time (well over 6 months with another third saying they could endure 6 months); in 2022, however, almost 10% said they could not even endure strict prevention and control measures for a week or two and most (48%) reported that they could endure them for a maximum of a month. Also in 2020, 94% reported no effect of the pandemic on their health condition; yet, this was only 56% in 2022. Overall, for the common measures across the two surveys, perceptions worsened with time.

Study implications relate to ensuring that patients have what they need to manage their condition. What they most wanted was easier access to healthcare and medications, regardless of control measures. This is despite quite fast and broad availability of telehealth in China and online pharmacies [33]. This could likely be due to lower digital literacy or device availability in older adults, or preferences for in-person services [34,35]. Efforts to close the age-related “digital divide” must continue. Greater access to virtual cardiac rehabilitation in China could address these issues as well [6,36].

Caution is warranted when interpreting these results. First, this is a cross-sectional study, so the design precludes causal determinations. Second, the results may not be generalizable beyond China with its political and cultural context, and the city of Shanghai more specifically where the stringency of control measures was high. Nevertheless, the population of Shanghai is very large, and findings can inform other governments when considering their control measures. Moreover, similarity of the sample to the larger population is not known given the recruitment strategy, designed to quickly secure data during the lockdown, but where full reach and number of non-respondents were not collated. Third, all data were self-report, and hence, there may have been socially desirable responding or other measurement error. Relatedly, psychiatric conditions and health status were not verified through structured clinical interview or medical records. Fourth, due to the exploratory nature of the study, multiple comparisons were performed, increasing the chance of type 1 error. Finally, whether patients had COVID-19 prior to or during the period of study was not considered; more research is needed.

In conclusion, 2 years into the pandemic in the midst of arguably the most stringent prevention and control measures globally, over 40% of chronic disease patients are experiencing elevated psychosocial distress, and this was associated with female, diagnosis of coronary artery disease and arrhythmia, perceived impact of pandemic on life, and impact of pandemic on health condition (Figure 1). Many patients stopped exercise and discontinued medication, and their greatest fears concerned access to healthcare. They were less able to tolerate prevention and control measures and had more negative perceptions related to the pandemic than at its beginning. Greater access to cardiac rehabilitation in China, including delivery supported by technology where patients are able, could address these issues.

Figure 1 
               Correlates of psychosocial distress in chronic disease patients during stringent COVID-19 prevention and control measures. CAD: coronary artery disease.
Figure 1

Correlates of psychosocial distress in chronic disease patients during stringent COVID-19 prevention and control measures. CAD: coronary artery disease.


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Acknowledgments

None.

  1. Funding information: None.

  2. Conflict of interest: None.

  3. Data availability statement: Data are available upon request.

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Received: 2022-11-21
Revised: 2023-01-19
Accepted: 2023-02-06
Published Online: 2023-03-28

© 2023 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  183. The diagnostic accuracy of touch imprint cytology for sentinel lymph node metastases of breast cancer: An up-to-date meta-analysis of 4,073 patients
  184. Mortality associated with Sjögren’s syndrome in the United States in the 1999–2020 period: A multiple cause-of-death study
  185. CircMMP11 as a prognostic biomarker mediates miR-361-3p/HMGB1 axis to accelerate malignant progression of hepatocellular carcinoma
  186. Analysis of the clinical characteristics and prognosis of adult de novo acute myeloid leukemia (none APL) with PTPN11 mutations
  187. KMT2A maintains stemness of gastric cancer cells through regulating Wnt/β-catenin signaling-activated transcriptional factor KLF11
  188. Evaluation of placental oxygenation by near-infrared spectroscopy in relation to ultrasound maturation grade in physiological term pregnancies
  189. The role of ultrasonographic findings for PIK3CA-mutated, hormone receptor-positive, human epidermal growth factor receptor-2-negative breast cancer
  190. Construction of immunogenic cell death-related molecular subtypes and prognostic signature in colorectal cancer
  191. Long-term prognostic value of high-sensitivity cardiac troponin-I in patients with idiopathic dilated cardiomyopathy
  192. Establishing a novel Fanconi anemia signaling pathway-associated prognostic model and tumor clustering for pediatric acute myeloid leukemia patients
  193. Integrative bioinformatics analysis reveals STAT2 as a novel biomarker of inflammation-related cardiac dysfunction in atrial fibrillation
  194. Adipose-derived stem cells repair radiation-induced chronic lung injury via inhibiting TGF-β1/Smad 3 signaling pathway
  195. Real-world practice of idiopathic pulmonary fibrosis: Results from a 2000–2016 cohort
  196. lncRNA LENGA sponges miR-378 to promote myocardial fibrosis in atrial fibrillation
  197. Diagnostic value of urinary Tamm-Horsfall protein and 24 h urine osmolality for recurrent calcium oxalate stones of the upper urinary tract: Cross-sectional study
  198. The value of color Doppler ultrasonography combined with serum tumor markers in differential diagnosis of gastric stromal tumor and gastric cancer
  199. The spike protein of SARS-CoV-2 induces inflammation and EMT of lung epithelial cells and fibroblasts through the upregulation of GADD45A
  200. Mycophenolate mofetil versus cyclophosphamide plus in patients with connective tissue disease-associated interstitial lung disease: Efficacy and safety analysis
  201. MiR-1278 targets CALD1 and suppresses the progression of gastric cancer via the MAPK pathway
  202. Metabolomic analysis of serum short-chain fatty acid concentrations in a mouse of MPTP-induced Parkinson’s disease after dietary supplementation with branched-chain amino acids
  203. Cimifugin inhibits adipogenesis and TNF-α-induced insulin resistance in 3T3-L1 cells
  204. Predictors of gastrointestinal complaints in patients on metformin therapy
  205. Prescribing patterns in patients with chronic obstructive pulmonary disease and atrial fibrillation
  206. A retrospective analysis of the effect of latent tuberculosis infection on clinical pregnancy outcomes of in vitro fertilization–fresh embryo transferred in infertile women
  207. Appropriateness and clinical outcomes of short sustained low-efficiency dialysis: A national experience
  208. miR-29 regulates metabolism by inhibiting JNK-1 expression in non-obese patients with type 2 diabetes mellitus and NAFLD
  209. Clinical features and management of lymphoepithelial cyst
  210. Serum VEGF, high-sensitivity CRP, and cystatin-C assist in the diagnosis of type 2 diabetic retinopathy complicated with hyperuricemia
  211. ENPP1 ameliorates vascular calcification via inhibiting the osteogenic transformation of VSMCs and generating PPi
  212. Significance of monitoring the levels of thyroid hormone antibodies and glucose and lipid metabolism antibodies in patients suffer from type 2 diabetes
  213. The causal relationship between immune cells and different kidney diseases: A Mendelian randomization study
  214. Interleukin 33, soluble suppression of tumorigenicity 2, interleukin 27, and galectin 3 as predictors for outcome in patients admitted to intensive care units
  215. Identification of diagnostic immune-related gene biomarkers for predicting heart failure after acute myocardial infarction
  216. Long-term administration of probiotics prevents gastrointestinal mucosal barrier dysfunction in septic mice partly by upregulating the 5-HT degradation pathway
  217. miR-192 inhibits the activation of hepatic stellate cells by targeting Rictor
  218. Diagnostic and prognostic value of MR-pro ADM, procalcitonin, and copeptin in sepsis
  219. Review Articles
  220. Prenatal diagnosis of fetal defects and its implications on the delivery mode
  221. Electromagnetic fields exposure on fetal and childhood abnormalities: Systematic review and meta-analysis
  222. Characteristics of antibiotic resistance mechanisms and genes of Klebsiella pneumoniae
  223. Saddle pulmonary embolism in the setting of COVID-19 infection: A systematic review of case reports and case series
  224. Vitamin C and epigenetics: A short physiological overview
  225. Ebselen: A promising therapy protecting cardiomyocytes from excess iron in iron-overloaded thalassemia patients
  226. Aspirin versus LMWH for VTE prophylaxis after orthopedic surgery
  227. Mechanism of rhubarb in the treatment of hyperlipidemia: A recent review
  228. Surgical management and outcomes of traumatic global brachial plexus injury: A concise review and our center approach
  229. The progress of autoimmune hepatitis research and future challenges
  230. METTL16 in human diseases: What should we do next?
  231. New insights into the prevention of ureteral stents encrustation
  232. VISTA as a prospective immune checkpoint in gynecological malignant tumors: A review of the literature
  233. Case Reports
  234. Mycobacterium xenopi infection of the kidney and lymph nodes: A case report
  235. Genetic mutation of SLC6A20 (c.1072T > C) in a family with nephrolithiasis: A case report
  236. Chronic hepatitis B complicated with secondary hemochromatosis was cured clinically: A case report
  237. Liver abscess complicated with multiple organ invasive infection caused by hematogenous disseminated hypervirulent Klebsiella pneumoniae: A case report
  238. Urokinase-based lock solutions for catheter salvage: A case of an upcoming kidney transplant recipient
  239. Two case reports of maturity-onset diabetes of the young type 3 caused by the hepatocyte nuclear factor 1α gene mutation
  240. Immune checkpoint inhibitor-related pancreatitis: What is known and what is not
  241. Does total hip arthroplasty result in intercostal nerve injury? A case report and literature review
  242. Clinicopathological characteristics and diagnosis of hepatic sinusoidal obstruction syndrome caused by Tusanqi – Case report and literature review
  243. Synchronous triple primary gastrointestinal malignant tumors treated with laparoscopic surgery: A case report
  244. CT-guided percutaneous microwave ablation combined with bone cement injection for the treatment of transverse metastases: A case report
  245. Malignant hyperthermia: Report on a successful rescue of a case with the highest temperature of 44.2°C
  246. Anesthetic management of fetal pulmonary valvuloplasty: A case report
  247. Rapid Communication
  248. Impact of COVID-19 lockdown on glycemic levels during pregnancy: A retrospective analysis
  249. Erratum
  250. Erratum to “Inhibition of miR-21 improves pulmonary vascular responses in bronchopulmonary dysplasia by targeting the DDAH1/ADMA/NO pathway”
  251. Erratum to: “Fer exacerbates renal fibrosis and can be targeted by miR-29c-3p”
  252. Retraction
  253. Retraction of “Study to compare the effect of casirivimab and imdevimab, remdesivir, and favipiravir on progression and multi-organ function of hospitalized COVID-19 patients”
  254. Retraction of “circ_0062491 alleviates periodontitis via the miR-142-5p/IGF1 axis”
  255. Retraction of “miR-223-3p alleviates TGF-β-induced epithelial-mesenchymal transition and extracellular matrix deposition by targeting SP3 in endometrial epithelial cells”
  256. Retraction of “SLCO4A1-AS1 mediates pancreatic cancer development via miR-4673/KIF21B axis”
  257. Retraction of “circRNA_0001679/miR-338-3p/DUSP16 axis aggravates acute lung injury”
  258. Retraction of “lncRNA ACTA2-AS1 inhibits malignant phenotypes of gastric cancer cells”
  259. Special issue Linking Pathobiological Mechanisms to Clinical Application for cardiovascular diseases
  260. Effect of cardiac rehabilitation therapy on depressed patients with cardiac insufficiency after cardiac surgery
  261. Special issue The evolving saga of RNAs from bench to bedside - Part I
  262. FBLIM1 mRNA is a novel prognostic biomarker and is associated with immune infiltrates in glioma
  263. Special Issue Computational Intelligence Methodologies Meets Recurrent Cancers - Part III
  264. Development of a machine learning-based signature utilizing inflammatory response genes for predicting prognosis and immune microenvironment in ovarian cancer
Heruntergeladen am 8.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/med-2023-0674/html
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