Short-term and long-term impacts of COVID-19 on economic vulnerability: a population-based longitudinal study (COVIDENCE UK)

Abstract

To determine whether COVID-19 has a significant impact on adequacy of household income to meet basic needs (primary outcome) and work absence due to sickness (secondary outcome), both at the onset of illness (short term) and subsequently (long term).

Design

Multilevel mixed regression analysis of self-reported data from monthly online questionnaires, completed 1 May 2020 to 28 October 2021, adjusting for baseline characteristics including age, sex, socioeconomic status and self-rated health.

Setting and participants

Participants (n=16 910) were UK residents aged 16 years or over participating in a national longitudinal study of COVID-19 (COVIDENCE UK).

Results

Incident COVID-19 was independently associated with increased odds of participants reporting household income as being inadequate to meet their basic needs in the short term (adjusted OR (aOR) 1.39, 95% CI 1.12 to 1.73) though this did not persist in the long term (aOR 1.00, 95% CI 0.86 to 1.16). Exploratory analysis revealed a stronger short-term association among those who reported long COVID, defined as the presence of symptoms lasting more than 4 weeks after disease onset, than those reporting COVID-19 without long COVID (p for trend 0.002). Incident COVID-19 associated with increased odds of reporting sickness absence from work in the long term (aOR 4.73, 95% CI 2.47 to 9.06) but not in the short term (aOR 1.34, 95% CI 0.52 to 3.49).

Conclusions

We demonstrate an independent association between COVID-19 and increased risk of economic vulnerability among COVIDENCE participants, measured by both household income sufficiency and sickness absence from work. Taking these findings together with pre-existing research showing that socioeconomic disadvantage increases the risk of developing COVID-19, this may suggest a ‘vicious cycle’ of impaired health and poor economic outcomes.

Trial registration number

NCT04330599 .

SciScore for 10.1101/2022.03.03.22271835: (What is this?)

Please note, not all rigor criteria are appropriate for all manuscripts.

Table 1: Rigor

Ethics	not detected.
Sex as a biological variable	The following covariates were selected prior to analysis based on their potential to act as confounders of the relationship between incident COVID-19 and study outcomes:11 age (classified as ‘working age’ [16-65 years] or ‘not working age’ [>65 years]), sex (male vs female, defined by sex assigned at birth), ethnicity (classified as white or minority ethnic origin), country of residence (England, Scotland, Wales, or Northern Ireland), Index of Multiple Deprivation (IMD) quartile of residential area,12 baseline occupational status (employed, self-employed, retired, furloughed, unemployed, student, never employed, not working due to sickness/disability/illness, or ‘other’), housing status (owns home outright, mortgage holder, private rental, renting from council, or other) and self-reported general health (poor, fair, good, very good, or excellent).
Randomization	not detected.
Blinding	not detected.
Power Analysis	not detected.

Table 2: Resources

No key resources detected.

Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

This work also has limitations. First, the variables of interest are all self-reported, including both SARS-CoV-2 test results and indicators of economic vulnerability. Participants were unaware of the hypotheses tested in this work, however, reducing potential for reporter bias to operate. Second, the study population was not perfectly representative of the adult UK population as a whole: males, younger people, people of minority ethnic origin and those with lower educational attainment were all under-represented. Further, internet access was a prerequisite to take part, which could limit generalisability of results particularly amongst the most economically deprived. While this may have limited our power to detect associations within sub-groups, we highlight that representativeness is not necessarily a barrier to identification of causal associations in observational epidemiology.19 Third, as with any observational study, residual or unmeasured confounding cannot be ruled out as an explanation for the associations we observe. Finally, we handled missing data under the assumption that survey data were missing at random. It is possible that data were more likely to be missing if someone had COVID-19 or became economically vulnerable. In the most extreme case, fatal or very severe COVID-19 would prevent questionnaire completion; alternatively, someone may have become ill or lost their job then no longer have the cognitive or physical capacity to complete the questionnaires. Co...

Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

Identifier	Status	Title
NCT04330599	Active, not recruiting	Longitudinal Population-based Observational Study of COVID-1…

Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

Results from JetFighter: We did not find any issues relating to colormaps.

Results from rtransparent:

Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
No protocol registration statement was detected.

Results from scite Reference Check: We found no unreliable references.

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