Pre-infection stress may increase the risk of long COVID and specific long COVID symptoms

In a recent study posted to the medRxiv* pre-print server, researchers predicted the development of long coronavirus disease (COVID) and its three specific symptoms, namely, difficulty with mobility, cognition, and self-care, based on the adversity experiences and worries about adversity experiences within the month before coronavirus disease 2019 (COVID-19) infection.

Background

The multifaceted etiology of long COVID makes it a serious public health issue. Although previous research has identified demographic and infection-related characteristics as risk factors for long COVID, research demonstrating stress foregoing the first severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection as a predictor of long COVID is lacking.

About the study

In the present longitudinal study, researchers used multiple imputations to analyze the data of 1,966 United Kingdom (UK) adults who met the study inclusion criteria but had missing data on other study variables.

The 1,966 study participants took part in the COVID-19 Social Study conducted in the UK during the COVID-19 pandemic to collect the psychological and social experiences of over 75,000 adults.

The study data was well-stratified, and all the participants met the following selection criteria: they were infected with SARS-CoV-2 before November 2021, had COVID-19 only once, and provided a date for their COVID-19 infection which was at least five weeks before survey distribution or before April 7, 2020. The majority, i.e., 91.71% of the study sample had data from four weeks before the infection.

The team examined the interaction between a three-level index of socioeconomic position (SEP) and the exposure variables concerning long COVID status, including annual household income, highest educational qualification, employment status, if they were living on rent/rent-free/a house owner, and household overcrowding.

There were 10 and 11 items in the categories – adversity and worries, respectively. They summed binary responses to adversity and worry-related questions to create the total number of adversity experiences and worries about adversity.

The researchers also assessed self-reported COVID-19 infection variables, including asymptomatic, mild, moderate, and severe. The two binary variables indicated the presence or absence of pre-existing physical and mental health conditions.

The team carried out three sets of analyses. First, they used binary logistic regression models to evaluate the association between adversity experiences and related worries and the development of long COVID. Next, they fitted an interaction term between adversity experiences and worries and the low SEP index. The SEP index collapsed into 0, 1, and 2+ indications of low SEP to attain adequate sample sizes for each category.

Lastly, they examined the associations between three specific long COVID symptoms, including difficulty with mobility, cognition, and self-care, and adversity experiences and worries about adversity. All the study analyses controlled socio-demographics, health-related factors, and COVID-19 characteristics.

The researchers presented coefficients from the binary logistic regressions as odds ratios (OR), with corresponding 95% confidence intervals (CI).

Study findings

Over 12% of the weighted study population were unsure whether they had long COVID or not; however, 3.76% had been diagnosed with long COVID, and 16.34% believed they had long COVID.

One month before developing COVID-19, the odds of self-reported long COVID augmented by 1.25 with every added worry about adversity experience, such as job loss. Consequently, worries about adversity experiences emerged as a persistent predictor of long COVID (OR: 1.43; 95% CI). Additionally, the number of worries about adversity experiences also correlated with greater odds of developing cognition difficulties by 1.46.

Although there was no indication of any interaction between SEP and an exposure variable, compared to the highest SEP group, the lowest SEP group participants were two times more prone to develop long COVID (OR: 1.95; 95% CI).

There were vast differences in the socio-demographic characteristics of people who were most likely to develop long COVID, such as these people were in the age group of 45 to 49 years, less educated, had lower household incomes, lived in crowded places or rural areas, and belonged to ethnic minorities.

For individuals who had developed long COVID, there was evidence that experiencing more worries about adversity experienced in the month before the infection increased the likelihood of difficulty with cognition but not with mobility or self-care.

Accordingly, close to 62% of participants in the long COVID group had difficulty with cognition, i.e., remembering or concentrating, which was much higher than reported by previous systematic reviews (15% to 26%) and the coronavirus infection survey (25%). Individuals with cognition difficulties were more likely to be older, female, from an ethnic minority group, and employed; additionally, 57.87% of the participants had difficulty with mobility.

Conclusions

According to the authors, this is the first study highlighting the factors present before the index SARS-CoV-2 infection which contributed to the development of long COVID. In particular, the study highlighted the role of stress, both chronic stress, such as low SEP, and pandemic-related adversities and worries.

In the UK, the authorities discontinued free COVID-19 testing and financial support for the general population from April 2022. However, the study identified stress preceding COVID-19 as a risk factor, and therefore, policies that reassure people in times of social and financial uncertainty are urgently warranted.

*Important notice

medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.