Article Text

Impact of a pandemic shock on unmet medical needs of middle-aged and older adults in 10 countries
  1. Chao Guo1,2,
  2. Dianqi Yuan1,
  3. Huameng Tang1,
  4. Xiyuan Hu3 and
  5. Yiyang Lei1
  1. 1Institute of Population Research, Peking University, Beijing, China
  2. 2APEC Health Science Academy, Peking University, Beijing, China
  3. 3Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
  1. Correspondence to Dr Chao Guo; chaoguo{at}pku.edu.cn

Abstract

Objective The objective is to explore the impact of the pandemic shock on the unmet medical needs of middle-aged and older adults worldwide.

Methods The COVID-19 pandemic starting in 2020 was used as a quasiexperiment. Exposure to the pandemic was defined based on an individual’s context within the global pandemic. Data were obtained from the Integrated Values Surveys. A total of 11 932 middle-aged and older adults aged 45 years and above from 10 countries where the surveys conducted two times during 2011 and 2022 were analysed. We used logistic regression models with the difference-in-difference method to estimate the impact of pandemic exposure on unmet medical needs by comparing differences before and after the pandemic across areas with varying degrees of severity.

Results Among the 11 932 middle-aged and older adults, 3647 reported unmet medical needs, with a pooled unmet rate of 30.56% (95% CI: 29.74% to 31.40%). The pandemic significantly increased the risk of unmet medical needs among middle-aged and older adults (OR: 2.33, 95% CI: 1.94 to 2.79). The deleterious effect of the pandemic on unmet medical needs was prevalent among middle-aged adults (2.53, 2.00 to 3.20) and older adults (2.00, 1.48 to 2.69), as well as among men (2.24, 1.74 to 2.90) and women (2.34, 1.82 to 3.03). The results remained robust in a series of sensitivity analyses.

Conclusion These findings suggest that efforts should be made by policymakers and healthcare professionals to balance healthcare resources to adequately address the comprehensive healthcare demands of individuals regarding multiple health issues, taking into account the challenges posed by pandemics.

  • COVID-19
  • Health Services Accessibility
  • Outcome Assessment, Health Care
  • Global Health

Data availability statement

Data are available in a public, open access repository. This study is based on publicly available datasets, and the data were released to the researchers without access to any personal information from the website: https://www.worldvaluessurvey.org/WVSEVStrend.jsp.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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WHAT IS ALREADY KNOWN ON THIS TOPIC

  • Some previous studies have reported a decline in medical services utilisation among older patients without coronavirus after COVID-19, but most studies only observe changes in outcomes before and after the pandemic, without differentiating whether these changes are specifically attributed to the effects of the pandemic or reflect general temporal trends over the same period due to other factors.

WHAT THIS STUDY ADDS

  • This study contributes to the literature pool by providing trustworthy evidence about the impact of COVID-19 on medical services utilisation among middle-aged and older adults at the global level based on reliable data and methods

  • This study demonstrates that pandemic shocks have a negative impact on the fulfilment of medical needs among middle-aged and older adults of different age groups and sexes.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

  • These findings suggest that policymakers and healthcare professionals, while prioritising pandemic-related measures and response, should not overlook the healthcare needs of individuals, particularly middle-aged and older adults, for other medical services during such outbreaks.

  • In addition to the investment of resources for prevention and control directly related to pandemic prevention and control, other medical services for people, especially middle-aged and older adults with high needs and vulnerabilities for disease treatment and rehabilitation, should be further strengthened in strategies to address the emerging infectious diseases transmission for a better health promotion and high-quality development in an ageing world.

Introduction

Although the current leading cause of human disease and death has shifted from infectious and parasitic diseases to chronic non-communicable and degenerative diseases according to the theory of epidemiological transition,1 as some scholars have pointed out, this shift should not obscure the ongoing threat posed by infectious diseases.2 In recent decades, outbreaks of new infectious diseases have occurred in some regions of the world. New infectious diseases are daunting due to their unexpected appearance and rapid spread.3 Severe outbreaks of new infectious diseases often become public health emergencies, even international ones, such as the outbreak of severe acute respiratory syndrome (SARS) in 2003,4 the influenza (H1N1) pandemic in 2009,5 the Ebola virus in 2014–2016,6 the Zika virus in 20167 and COVID-19 recognised by the WHO as a public health emergency of international concern (PHEIC) in March 2020.8

This COVID-19 pandemic is a global public health and safety challenge, and the crisis has brought disruptive effects on health, social, economic, political and even cultural macroscopic areas. A UN framework for the immediate socioeconomic response to COVID-19 states that the COVID-19 pandemic is not just only a health crisis, but is also affecting the social and economic core and that while the extent of the pandemic varies from country to country, it is likely to increase poverty and inequality globally and affect the achievement of the Sustainable Development Goals.9 Studies have shown that middle-aged and older adults are undoubtedly vulnerable to this pandemic event due to their higher susceptibility to COVID-19 and the risk of death and secondary disease following infection,10–13 people aged 50 and above in some countries were more likely to have medical services postponed14 and were more likely than younger adults to experience impairment in general,15 as well as their relatively lower resilience to other life and behavioural effects beyond infection in the pandemic.16 17 Are middle-aged and older adults experiencing a shortage of health services due to the global COVID-19 pandemic in the context of the large number of health resources that have to be devoted to prevention and treatment in response to the event of an outbreak? This is an important issue for policymakers and medical services professionals in the demographic context of increasing global ageing, which is crucial for targeting medical services to the middle-aged and older population, promoting the rehabilitation of geriatric diseases and preventing middle-aged and older adults from falling into a vicious cycle of increased disease susceptibility due to unmet medical needs.

Some previous studies have reported a decline in medical services utilisation among middle-aged and older patients without coronavirus after COVID-19. In Europe, a study showed substantial increases in the number of avoidable cancer deaths in England as a result of diagnostic delays due to the COVID-19 pandemic in the UK.18 In Asia, middle-aged and older Singaporeans’ healthcare utilisation and the diagnosis of chronic conditions substantially decreased among non-COVID-19 patients during the first peak period of the COVID-19 outbreak.19 A study in Japan showed that the total number of hospitalisations and outpatient visits decreased by 27% and 22%,20 respectively, after the first wave of COVID-19. Studies assessing the effect of the COVID-19 pandemic on health services utilisation in China showed that health facility visits were observed significant reduction and the impact still existed 2 years later.21 22 A study in Hong Kong, China, showed that the number of missed medical appointments among older adults during COVID-19 increased from 16.5% a year ago to 22.0% after the outbreak.23 Studies in Latin America showed a similar pattern that a majority (83%) of patient advocacy organisations reported their patients experienced delays in receiving their treatment and care services.24 And the same is true with many multicountry analyses. A study including six low-income and middle-income countries, such as Zimbabwe, showed that people with disabilities experienced additional difficulties accessing healthcare during the pandemic.25 And a review summarising literature from Africa, Australia and New Zealand, China, Europe, Latin America and the USA showed that individuals with rheumatic diseases during the pandemic faced disruptions in healthcare and medication supply shortages.26 However, many of these studies rely on small local samples or people with certain diseases and do not explore whether the decline in service utilisation is a result of reduced or unmet demand. Additionally, most studies only observe changes in outcomes before and after the pandemic, without differentiating whether these changes are specifically attributed to the effects of the pandemic or reflect general temporal trends over the same period due to other factors.

Given this, this study employed the global pandemic of COVID-19 as a quasiexperiment, combined with international large-scale survey data, to estimate the impact of the pandemic on the medical services utilisation of middle-aged and older adults worldwide. By constructing difference-in-difference (DID) models that considered both exposure time and severity, the study aims to provide robust evidence regarding the imbalances in medical services during public health emergencies. The findings would offer valuable insights for policymakers and healthcare practitioners, enabling them to avoid neglecting and proactively address the utilisation of routine medical resources for middle-aged and older individuals in future pandemics. This facilitates the development of comprehensive and targeted contingency plans to effectively tackle population health challenges arising from global public health emergencies, including infectious disease outbreaks.

Methods

Data source and participants

The study used the global pandemic COVID-19 starting in 2020 as a quasiexperiment. Data on the global pandemic COVID-19 were obtained from the WHO COVID-19 Detailed Surveillance Data.27 Daily COVID-19 case numbers of each country, area or territory were collected for further analysis. Individual information on medical needs and other demographic statuses was obtained from the Integrated Values Surveys (IVS), which were constructed based on repeated questions from the European Value Study (EVS) from 1981 to 2021 and the World Value Survey (WVS) from 1981 to 2022.28 29 EVS and WVS are both renowned, international, large-scale, repeated cross-sectional surveys that are dedicated to gathering extensive information on the social, political, economic, religious and cultural values of individuals across the globe.

While the IVS covered a wide range of surveyed countries, our evaluation of the pandemic’s impact is based on comparing differences in unmet medical needs before and after the pandemic across regions with varying COVID-19 severity levels. Therefore, our analysis only included participants residing in countries surveyed both before and after 2020, when the pandemic outbreak occurred. We combined COVID-19 data for countries surveyed during both periods and included participants with available information on medical needs. We focused on participants aged 45 years and above, excluding those with missing data on the outcome measure or any covariate. In the final analysis, a total of 11 932 middle-aged and older adults from 10 countries were included. Each country was surveyed two times between 2011 and 2022. Among the participants, 5764 were interviewed between 2011 and 2014, while 6168 were interviewed between 2020 and 2022 (online supplemental table S1). Figure 1 illustrates the process we followed to derive our analytical sample.

Supplemental material

Figure 1

Flowchart of samples.

Exposure

Exposure to the pandemic was defined based on an individual’s context within the global pandemic, rather than their infection status. It was measured by both exposure time relative to the outbreak and exposure severity. All samples surveyed after 2020 were considered part of the after-pandemic group (exposure group), indicating that they had experienced the pandemic. Samples surveyed before 2020 were classified as the before-pandemic group (reference group). Regarding severity, we tentatively assumed that amidst the global outbreak, residents living in a specific country have a consistent perception of the severity of the outbreak within their country relative to other countries, given the reduced international travel. Consequently, we used country-level average data as an estimation of the pandemic’s severity within each country.

The incidence of confirmed cases from 2020 to the survey year in a country or region was used in this study to measure the severity of the pandemic in a country and was standardised to mitigate dimensional influences. Let Embedded Image represent the cumulative number of COVID-19 cases in the ith country from 2020 to the survey year of this country, and Embedded Image denotes the total population of the ith country in the survey year j. The incidence of COVID-19 by the survey year can be calculated as a ratio of Embedded Image and Embedded Image . Next, let μ and σ denote the mean and SD of the afore-mentioned ratio, respectively. Then, the standardised incidence (SI) of the ith country by the survey year can be obtained using the following formula:

Embedded Image

where a larger value indicates a more severe pandemic. In the analysis, the SI was initially treated as a continuous variable. It was then divided into high and low groups using bisection to create a dichotomous variable, which replaced the continuous SI for sensitivity analysis. Additionally, a sensitivity analysis was conducted using the SI in the survey year as a proxy for the SI by the survey year, substituting the cumulative COVID-19 cases in the survey year for the cumulative cases from 2020 to the survey year.

Outcome

The main outcome of this study was whether participants reported any unmet medical needs during the survey year. The original survey question was, ‘What is the frequency you or your family gone without needed medicine or treatment during the last 12 months?’. Respondents could choose one of four options: ‘often’, ‘sometimes’, ‘rarely’ or ‘never’.

In this study, to assess the overall situation of unmet medical needs, the outcome event of ‘unmet’ was defined by combining the three categories of ‘often’, ‘sometimes’ and ‘rarely’. The category of ‘never’ indicated the absence of unmet needs, resulting in the creation of a dichotomous variable indicating whether there were any unmet medical needs (yes or no). Additionally, we retained the original four-category approach to measure the severity of unmet medical needs based on the frequency of their occurrence (never, rarely, sometimes or often).

Covariates

According to previous studies, the medical services utilisation of middle-aged and older adults is influenced by various factors, such as age, gender, education, marriage, income and health insurance status.30 31 Thus, the following covariates were included in the analysis: age (continuous), sex (male or female), marital status (single or having a partner), religious denomination (do not belong to a denomination, Roman Catholic, Protestant, Orthodox, other Christian, Jew, Muslim, Hindu, Buddhist or other), educational level (lower, medium, upper), employment status (unemployed, full-time employed, part-time employed, self-employed, retired, housewife, students or other) and income level (comprising a total of ten steps). Self-rated health (very good, good, fair, poor) was also included as a potential confounder since individual health status is a key determinant of the demand for care. Additionally, a control variable indicating international immigrant status (yes or no) was included to account for potential confounding, as inclusive healthcare coverage often relates to national status. Furthermore, the analysis also took into account the nation and year in which participants were surveyed as control variables. More detailed information on these variables is available in online supplemental table S2.

Statistical analysis

The descriptive analysis used frequencies and percentages to describe the demographic and socioeconomic characteristics of the sample, along with the unmet medical need status. The χ2 test was used to compare the characteristics before and after the pandemic, as well as the prevalence of unmet medical needs among samples with different characteristics.

The inferential analysis used logistic regression models with the DID method. This approach aimed to estimate the impact of pandemic exposure on unmet medical needs by comparing differences before and after the pandemic across areas with varying degrees of severity.

The logistic regression model based on DID estimation was developed as follows:

Embedded Image

where p=P(Embedded Image =1|x) denotes the probability of experiencing unmet medical needs (1=yes, 0=no) for the ith participant interviewed in period j and with severity k. Embedded Image denotes the survey time (before or after the pandemic) and Embedded Image represents the severity of the pandemic measured by SI. Embedded Image denotes covariates if any. Embedded Image represents the random error, and Embedded Image denotes the constant term. Then, Embedded Image as the interaction coefficient between exposure time and exposure severity is the DID estimate of the pandemic’s effect on unmet medical needs for middle-aged and older adults.

Furthermore, we conducted multinomial logistic regressions using the severity of unmet medical needs as the dependent variable. This allowed us to assess the impact of the pandemic across all the range of potential unmet needs.

In addition, subgroup analyses were conducted to examine the heterogeneity across age groups and sexes. The same models were applied for analysis among two age groups: middle-aged adults (aged 45–64 years) and older adults (aged 65 years and above), as well as for both men and women, separately.

To test the robustness of the results, the following sensitivity analyses were conducted in this study. First, models were repeated substituting the SI in the survey year for the SI by the survey year as a measure of the pandemic severity. Next, models were reanalysed by replacing the continuous variable SI with a binary classification. Then, models were reanalysed through multilevel logistic regression, incorporating additional adjustments at the national level including economic indicators and relevant information on health systems.

Crude ORs and 95% CIs were initially calculated for models without control variables and then the estimates were adjusted by including control variables. In this study, two-sided p values less than 0.05 were considered statistically significant. STATA V.17 (STATA Corp, College Station, Texas, USA) software was used for the statistical analysis of all data.

Results

Sample characteristics

A total of 11 932 middle-aged and older adults aged 45 years and above from 10 countries were included in this study. Among them, 5764 (48.31%) were interviewed before the pandemic, while 6168 (51.69%) were interviewed after the pandemic. In terms of pandemic severity, 4499 (37.71%) participants resided in areas with lower severity, while 7 433 (62.29%) were in areas with upper severity. Regarding demographic characteristics, 55.78% of the participants were women and 31.50% were older adults. The majority of participants (68.78%) had a partner and 24.51% reported not belonging to a religious denomination. 72.66% had a medium or upper-range education level, 31.61% were retired and 9.95% were international migrants. Only a few of the participants reported poor health (10.82%). Table 1 presents more detailed information on sample characteristics by period.

Table 1

Characteristics of samples

Prevalence of unmet medical needs among middle-aged and older adults

Among all the participants, a total of 3647 reported any unmet medical needs, with a pooled unmet rate of 30.56% (95% CI: 29.74 to 31.40). Overall, the prevalence of unmet medical needs among middle-aged and older adults in the 10 countries after the pandemic (27.25, 26.15 to 28.38) was significantly lower than that before the pandemic (34.11, 32.88 to 35.35) (p<0.0001). However, a significantly higher prevalence was found in areas with an upper pandemic severity (32.45, 31.39 to 33.53) compared with areas with a lower severity (27.45, 26.15 to 28.78) (p<0.0001). Table 2 and figure 2 present the prevalence of unmet medical needs by period and severity of the pandemic. For more detailed information on the prevalence by other demographic and socioeconomic characteristics, please refer to online supplemental table S3.

Figure 2

Prevalence of unmet medical needs by country, pandemic severity and period. The black numbers are the proportion of participants with a certain characteristic to the total participants. The pink numbers represent the prevalence of unmet needs among participants with certain characteristics. The abbreviations in the figure adhere to the ISO 3166-1 alpha-3 code standard, which assigns three-letter alphabetic codes to countries, including ARM for Armenia, KGZ for Kyrgyzstan, LBY for Libya, MAR for Morocco, NLD for the Netherlands, NZL for New Zealand, SGP for Singapore, UKR for Ukraine, URY for Uruguay, and ZWE for Zimbabwe.

Table 2

Prevalence of unmet medical needs, by period and severity of the pandemic

The impact of the pandemic on unmet medical needs among middle-aged and older adults

After estimating the change in unmet medical needs related to the pandemic beyond the background trends by doing a DID analysis (figure 3A), we found that the pandemic significantly increased the risk of any unmet medical needs among middle-aged and older adults (OR: 1.17, 95% CI: 1.07 to 1.27). This effect was partially increased and remained significant after controlling for multiple covariates (2.33, 1.94 to 2.79).

Figure 3

The impact of the pandemic on unmet medical needs among middle-aged and older adults. (A) Total sample, (B) subsamples by age group and (C) subsamples by sex. In models with controlling covariates, exact age, sex, marital status, religious denomination, educational level, employment status, income level, international migration, self-rated health, nation and survey year were controlled in the total sample; control variables in the age-specific models were the same as above; control variables in the sex-specific models were the same as the above model except for sex. DID, difference-in-difference.

In the analysis of heterogeneity based on age (figure 3B) and sex (figure 3C), we found that the deleterious effect of the pandemic on unmet medical needs was prevalent among middle-aged adults (2.53, 2.00 to 3.20) and older adults (2.00, 1.48 to 2.69), as well as among men (2.24, 1.74 to 2.90) and women (2.34, 1.82 to 3.03), without heterogeneity in age groups (P for interaction=0.913) and sexes (P for interaction=0.615).

The results from the multinomial models indicated that the impact of the pandemic on the increased risk of unmet medical needs among middle-aged and older adults intensified with higher frequencies of occurrences of unmet medical needs. Relative to never reporting any unmet medical needs, the OR and 95% CI for reporting unmet medical needs rarely, sometimes and often were 1.65 (1.34 to 2.02), 3.75 (2.69 to 5.23) and 4.88 (2.67 to 8.91), respectively. This trend was observed across the samples of middle-aged adults, older adults, men and women (table 3).

Table 3

The impact of the pandemic on various severity of unmet medical needs among middle-aged and older adults

Sensitivity analysis

The series of sensitivity analyses we conducted indicated a certain level of robustness in the study findings. First, the effects of the pandemic were still observed in the overall participants (2.13, 1.77 to 2.57) as well as the subpopulations by age groups and sexes in models that repeated substituting the SI in the survey year for the SI by the survey year as a measure of the pandemic severity (online supplemental table S4). Second, models by replacing the continuous variable SI with a binary classification also yielded similar results. The pandemic also exhibited a significant increase in the risk of unmet medical needs across all participants (2.85, 2.25 to 3.62), and this effect remained significant when analysing middle-aged adults, older adults, men and women separately (online supplemental table S5). Third, the effect observed among the participants remained statistically significant (2.77, 1.66 to 4.61) in the multilevel models. Similar trends were also identified when examining subpopulations based on age groups and sexes (online supplemental table S6).

Discussion

This study conducted a comprehensive and robust analysis to investigate the influence of the pandemic of COVID-19 on the medical services utilisation of middle-aged and older adults in multiple countries. The results indicated that the pandemic shock has significantly increased the risk of unmet medical needs of middle-aged and older adults, regardless of age or sex. These findings not only support the results of previous studies but also provide further clarification regarding the role of the pandemic in this particular context. As suggested by WHO in implications of the COVID-19 pandemic for patient safety, severe disruptions in all major health areas have led to delays in the diagnosis and treatment of diseases, especially in countries experiencing fragility, social and economic instability, conflict and violence.32

The potential mechanisms underlying the negative effect of the pandemic on the medical utilisation of middle-aged and older adults may be wide-ranging. On the one hand, the outbreak and rapid spread of COVID-19 inevitably crowded out the limited resources of medical services, resulting in a diversion of substantial health resources including human and material resources towards COVID-19 prevention, virus detection and patient care. As a consequence, there was a significant reduction in resources available for the management and care of other diseases.33–35 At the same time, general medical resources have been further reduced by the suspension of hospitals to deal with the potential risk of nosocomial infections, the inability of medical services workers to work due to infections and the emergence of strikes by medical services workers in some countries or regions.36–38 These have objectively reduced the supply of geriatric care in some regions where healthcare systems have reached the point of exhaustion,39 especially in the severe early days of COVID-19.

On the other hand, in response to a sudden outbreak of a new infectious disease, countries and regions have been experimenting and changing their coping strategies, such as some emergency measures such as community closure, traffic control and social distancing to prioritise the response to the spread of the pandemic. Some of the countries analysed in our study also adopted such strategies such as the stay-at-home orders in Singapore,40 which may not only lead to active or passive changes in daily life behaviour and social interaction but also undoubtedly reduces the accessibility of medical services resources, especially in cross-regional medical treatment.41 This is particularly evident among middle-aged and older adults, who may put on hold non-acute or urgent medical needs. In contrast, the impact of the pandemic and social distance can have a significant negative impact on the physical and psychological well-being of older adults.42 For example, studies have shown that the pandemic may increase anxiety, depression, poor sleep quality, nutritional deficiencies and physical inactivity among older adults,43–45 which in turn further amplifies the demand for medical services among the older population, leading to a greater gap between demand and utilisation.

After SARS, the last major pandemic with a significant impact on the population,46 COVID-19 is a wake-up call for humanity at the beginning of entering the 20s of the 21st century, when governments, industries and families are once again aware of the challenges of the emerging disease in this new era, in addition to the traditional disease threats. However, just as we should not overlook emerging infectious diseases due to the increasing prevalence of chronic diseases during epidemiological transitions, we should also not neglect the healthcare needs for chronic and other conventional diseases during a pandemic. With the WHO declaring that the COVID-19 pandemic is no longer a PHEIC, governments worldwide are reflecting on lessons learnt and developing preparedness plans for future pandemics. The increased medical utilisation gaps, particularly among middle-aged and older individuals resulting from the COVID-19 pandemic as discovered in this study, should undoubtedly be given full consideration by policymakers and clinical healthcare professionals. Declines in essential health service utilisation could even result in more deaths than the disease outbreak itself.47 Measures should be taken to reduce the neglect of healthcare needs for other diseases during a pandemic and formulate effective strategies to balance the allocation of healthcare resources.

It is clear that, our research is based on countries with varying levels of socioeconomic development and healthcare resources, and overall, consistent with previous studies,48 49 higher levels of socioeconomic status and healthcare resources at the country level were found to be associated with a lower risk of unmet medical needs in the sample included in this study (see online supplemental table S6). However, even after controlling for these country-level covariates, the impact of the pandemic shock on unmet medical needs remains significant. While this is an ‘averaged’ outcome, such estimates provide support and basis for advocating international attention to ensuring basic healthcare service provision from a more macroscopic global perspective during public health emergencies. Indeed, the WHO has released a position paper calling on countries and the international community to build resilient health systems by integrating universal health cover and health security efforts during COVID-19 pandemic and beyond in 2021.50 In the postpandemic era, the WHO also needs to assume greater international responsibilities in this field and rebuild trust among the people to prepare for the next pandemic.51 The results of our study once again highlights the need for countries all over the world to take every opportunity to build resilient health systems and all-hazards emergency risk management based on a strong primary healthcare foundation and rebuild the health systems sustainably, more equitably and closer to communities.52

There are also some shortcomings in this study. First, several potential confounders, such as the objective medical conditions of participants that were not controlled because of data accessibility, may have had some impact on the results. Second, although the cumulative confirmed infected cases were obtained from the WHO, they were based on the integration of official reports from various countries or regions and the different criteria in each region may produce some bias. Third, the results should be interpreted with caution given that the exposure period groupings in our analysis are in years and the results reflect the average long-term effect over that period. Furthermore, as our data were aggregated at the country level, all individuals within a country were grouped together. This might introduce bias stemming from regional variations within each country. The limited number of countries also poses a potential threat to the external validity when making global generalisations of our research findings and presents challenges in deriving policy implications and recommendations for specific nations. In addition, self-rated health might have a bidirectional relationship with our outcome variable. However, we opted to retain it as a covariate due to the lack of a more appropriate exogenous health condition variable. Additionally, it is unfortunate that we lack further relevant variables pertaining to healthcare access for migrant populations in each country. Consequently, we have solely considered migrant status as a regression factor. Moreover, we did not distinguish between the specific types of medical needs of the participants because there was no such information in the database. Nevertheless, to the best of our knowledge, this study contributes to the literature pool by providing trustworthy evidence about the impact of COVID-19 on medical services utilisation among middle-aged and older adults at the global level based on reliable data and methods for the first time.

The findings of this study on the global pandemic on the medical services utilisation of middle-aged and older adults in multiple countries emphasise the importance of balancing medical resources in the response to outbreaks. In addition to the investment of resources for prevention and control directly related to pandemic prevention and control, other medical services for people, especially middle-aged and older adults with high needs and vulnerabilities for disease treatment and rehabilitation, should be further strengthened in strategies to address the emerging infectious diseases transmission for a better health promotion and high-quality population development in an ageing world.

Data availability statement

Data are available in a public, open access repository. This study is based on publicly available datasets, and the data were released to the researchers without access to any personal information from the website: https://www.worldvaluessurvey.org/WVSEVStrend.jsp.

Ethics statements

Patient consent for publication

Ethics approval

This study involves human participants. The Integrated Values Surveys, including European Value Study and World Value Survey, was reviewed and approved by the ethical review board in each country. The detailed approval numbers can be obtained by contacting the principal investigator of each national team through the e-mail address wvsa.secretariat@gmail.com. Participants gave informed consent to participate in the study before taking part.

References

Supplementary materials

  • Supplementary Data

    This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

Footnotes

  • Contributors CG formulated the research questions, designed the study and wrote the first draft of the manuscript. CG, DY and HT analysed the data. CG, DY, HT, XH and YL revised the manuscript together. All the authors had access to the data and were responsible for the decision to submit the manuscript for publication. CG was responsible for the overall content as the guarantor.

  • Funding This study was funded by the National Natural Science Foundation of China (grant number 82103955) and the Clinical Medicine Plus X—Young Scholars Project, Peking University, the Fundamental Research Funds for the Central Universities (grant number 7100604313). The funders had no role in the study design, data collection, data analysis, the decision to publish or the preparation of the manuscript.

  • Competing interests None declared.

  • 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.