2.1 Sampling

Each year in January the GPPS is issued by post to a random sample of GP-registered patients in England. It can be completed on paper, online or using a dedicated telephone helpline. Invitations and reminders are also issued by text message and the online survey is available in 14 languages and British Sign Language. Paper copies can be requested in Braille and large print. Data is grouped by geographical and health system factors including general practice (GP), Primary Care Network (PCN), Integrated Care System, Local Authority and NHS Region. Indices of deprivation are also available according to patient postcode. Further technical detail is available online [19].

The survey is issued to approximately 2.5 million registered patients and aims to ensure a minimum number of responses per practice and PCN and a set confidence interval for each practice. A proportionately stratified (by age, gender and postcode) unclustered sample is drawn for each practice [19]. Patient identifiable data is not collected. It is a standalone self-reported survey that is not linked to GP patient records. The questionnaire was last significantly revised in 2021 (available online) [20]. More detail about the survey is available at https://gp-patient.co.uk/FAQ.

2.2 Design

This is an analysis of cross-sectional survey data using the GPPS data set for 2023. Permission to access and use the individual patient level survey data from 2023 was requested and granted by agreement between NHS England and the University of Southampton. Ethical approval was granted by the University of Southampton Faculty of Medicine Ethics Committee (No.82369).

2.3 Variables

The outcome was the response to the question “Would you describe yourself as having ‘Long Covid’, that is, you are still experiencing symptoms more than 12 weeks after you first had COVID-19, that are not explained by something else?”. Respondents could select ‘yes’, ‘no’, ‘not sure’ or ‘prefer not to say’.

All exposure variables used in the analysis (listed in Supporting Information S1: Tables 1 and 2) were categorical and used as collected with the exception of smoking status. Smoking status was recorded as never, former, occasional and regular smoker and was condensed to never, former and current smoker (regular and occasional) for analysis. A new variable was created to identify respondents with at least one defined long-term condition (LTC) (other than LC). The question that asked if respondents had any LTCs could not be included as respondents with LC could have counted their LC as a LTC (the LTC variable could include the LC outcome).

2.4 Analysis

Data was analysed using Stata v17 [21]. Descriptive statistics, frequencies and proportions were calculated followed by univariable and multivariable logistic regression. The primary analysis compared those answering ‘yes’ and ‘no’ to the LC question, excluding those answering unsure or ‘prefer not to say’. The same analysis comparing those answering ‘not sure’ and ‘no’ was also undertaken, as well as comparing ‘not sure’ and ‘yes’. We conducted the latter analysis to understand the factors associated with uncertainty about having the health condition which may act as a barrier to seeking care and support.

We conducted multivariable analysis to assess the independent effects of variables given they can potentially confound each other. The multivariable analysis included age, sex, sexual orientation, parental/guardian status, carer status, ethnicity, patient's area of residence index of multiple deprivation (IMD) quintile (a combined index of relative deprivation based on data in seven domains) [22], religion, smoking status and having at least one defined LTC (other than LC). Work status was included as an adjustment in the analysis comparing ‘yes’ and ‘not sure’ but not included when comparing ‘yes’ and ‘no’ (since work status could have been impacted by having LC).

4.1 Summary

Analysis of this national GP survey data found that 4.8% of respondents had LC while 9.1% were unsure whether they had it or not. This is a high burden of disease with potential for significant impact on individuals, their families, the economy and wider society. LC is unequally distributed in England, with the condition being more prevalent in minoritised and disadvantaged groups. This study adds new evidence that there are more people who are unsure whether they have LC than those who are confident they have it, again some from more vulnerable groups.

4.2 Comparison With Existing Literature

The 4.8% prevalence estimate is similar to that found in other surveys in the UK [1], and latest data from the GP Patient Survey (2024) indicates 5.0% prevalence with 9.0% unsure [18]. Many of this study's findings support existing research on risk factors for LC, for example lower odds of having LC in males compared to females [2-9], higher odds in those of working age [2-4, 6, 7], the strong trend of increasing odds of LC with increasing deprivation [1, 3-5, 9] and higher odds for people who are unemployed [1], and who have existing health conditions [2, 5, 7]. UK studies have also found higher prevalence of LC in particular ethnic minority groups [1, 3, 5, 8] but findings have not been consistent. Lower odds were also found for people of Black ethnicity, something that has been found in other UK studies [1, 7]. Higher prevalence in people from sexual orientation minorities has also been identified in one US study [23].

In this study, there were higher odds of having LC for people who are parents and carers. This could be explained by disproportionate exposure to SARS-CoV-2 through schools and caring roles, or greater awareness of LC in these groups. The latter is supported by the reduced odds found in this study of being unsure about having LC in those groups. The impact of LC symptoms could be more noticeable due to caring roles, or the likelihood of being able to rest during the acute COVID-19 phase may have been limited (a potential factor in some LC cases [10]). There were also higher odds for people of particular faiths, even after adjusting for ethnicity, deprivation, age, gender and other potential confounding factors. However, this still may be explained by residual confounding. Odds of having LC were higher in former smokers but lower for current smokers, which is contrary to studies where smoking has been identified as a risk factor [3, 5]. However, reviews of this area recognise the variation in findings about the role of smoking in LC [24].

This study adds new evidence about the lack of certainty people feel about whether or not they have LC. Groups who were less confident about having LC included males and non-binary people. In men this could be explained by a tendency to consult less [25] or delay health-related help-seeking behaviour [26]. Also less confident were people from ‘Any other white background’, Indian, Bangladeshi, Chinese, ‘Any other Asian background’, Black Caribbean, Black African, Arab and ‘Any other ethnic group’, those who were working part-time, unemployed, retired, or staying at home and smokers. Those who were less likely to be unsure about having LC included those aged 24−74 years, those who were not heterosexual, parents/guardians and carers, White Gypsy/Irish Traveller, people who were sick or disabled and people with at least one defined LTC. People with LTCs in addition to LC may be less unsure because they are clear about the difference between the symptoms arising from their other LTCs and their LC symptoms. It is also possible that people with other LTCs are more used to navigating the health system, or have increased health literacy due to their LTC history. Those under the age of 25 years were less confident about having LC. This could explain why most research about LC includes older people: most uses self-identification with LC as study inclusion strategy. It could also be the case that there is wider associated stigma with having LC in younger people [17].

4.3 Strengths and Limitations

A key strength of this study is its large and national survey sample size. The GP Patient Survey is a very useful source of information on LC in England, particularly in light of the discontinuation of other national surveys. The demographic information about participants is particularly rich, for example it includes information about the travelling community which can often be difficult to source.

Limitations include lack of data about severity (e.g., hospitalisation) or symptoms of LC, SARS-CoV-2 variant, timing of onset and respondents' COVID-19 vaccination status. Having this information would provide more context. Additionally, interpreting survey responses about LTCs with respect to LC is problematic. LC is a LTC but 21.9% of people who described themselves as having LC said they did not have any LTCs. To take account of this the multivariable models in this study included a variable constructed from named LTCs as reported by respondents rather than the answer to the question ‘any other LTC’ to eliminate potentially including the LC outcome. A further limitation is that we cannot role-reverse causality for some of the variables such as work status, hence this variable was not included in the multivariable analysis.

4.4 Implications for Research and/or Practice

Given the high, unequal burden of LC in the global population and its impact on everyday lives of individuals and the functioning of society, it is important to understand the drivers for this inequality and for the uncertainty around LC to enable people to get the right support. Evidence on access to LC treatment and support indicates there is inequity on many levels. Exploring data from NHS England about access to COVID-19 Post-Covid Assessment Services [27] during the period of the GPPS survey 2023 reveals large differences in waiting times between regions, and those differences do not correspond to differences in regional prevalence of LC.

Levels of uncertainty may indicate a lack of awareness of LC symptoms or confusion, or there may be an overlap in symptoms with other conditions. People who are unsure may have less severe LC symptoms, or may have symptoms that are improving or are currently in remission, and so are no longer sure if they still have LC. They may also be waiting for a LC diagnosis, or unsure if they had previously had a COVID-19 infection. A lack of uncertainty in particular groups may be because a diagnosis has already been secured, indicating that some groups may be more likely than others to be successfully diagnosed, or it could be related to levels of health literacy and self-advocacy. It may also be the case that people who are sure they have LC are likely to be most severely impacted. Stigma and self-doubt can shape self-identification with LC [16, 17, 28-30] which could be discouraging people from coming forward for diagnosis and support, and there is emerging evidence that intersectional identity may compound LC stigma leading to worse outcomes for marginalised groups [16]. Added to this, LC is itself an uncertain illness, with symptoms and impact varying between people and changing over time, and coupled with a lack of clear pathology or biomarkers, this can result in difficulty with diagnosis and may result in hermeneutical (interpretative) injustice [16]. This is a type of epistemic injustice in LC, with people's experiences often being questioned or viewed as unreliable. Another type of epistemic injustice is testimonial injustice: the degree by which a person is not believed about their own story depends on their identity [31]. This has led to calls for the lived experience of people with LC to be consistently acknowledged and given validation [29]. Our study has provided a useful estimate to quantify the uncertainty brought about by these numerous factors.

With involvement of PPIE partners, we plan further analysis using this survey, looking at the experience of support in primary care for people with LC. We will also link survey data with place-based data to consider multi-level factors affecting variation in prevalence and uncertainty. Together with PPIE, the current analysis will be crucial in informing our planned qualitative work to understand the mechanisms that drive inequality in LC prevalence, impact, support and wider societal effects.