Heterogeneity of COVID-19 symptoms and associated factors: Longitudinal analysis of laboratory-confirmed COVID-19 cases in San Antonio

Author:

Choi Byeong YeobORCID,Grace Abigail R.,Tsai JackORCID

Abstract

Few studies have examined heterogeneous associations of risk factors with Coronavirus Disease-2019 (COVID-19) symptoms by type. The objectives of this study were to estimate the prevalence of and risk factors associated with COVID-19 symptoms and to investigate whether the associations differ by the type of symptoms. This study obtained longitudinal data over 6 months from laboratory-confirmed COVID-19 cases in a citywide sample in San Antonio. Sixteen symptoms of COVID-19 infection, measured at baseline and three follow-up times (1, 3, and 6 months), were analyzed using generalized estimating equations (GEE) to investigate potential risk factors while accounting for the repeated measurements. The risk factors included time in months, sociodemographic characteristics, and past or current medical and psychiatric conditions. To obtain interpretable results, we categorized these sixteen symptoms into five categories (cardiopulmonary, neuro-psychological, naso-oropharyngeal, musculoskeletal, and miscellaneous). We fitted GEE models with a logit link using each category as the outcome variable. Our study demonstrated that the associations were heterogeneous by the categories of symptoms. The time effects were the strongest for naso-oropharyngeal symptoms but the weakest for neuro-psychological symptoms. Female gender was associated with increased odds of most of the symptoms. Hispanic ethnicity was also associated with higher odds of neuro-psychological, musculoskeletal, and miscellaneous symptoms. Depression was the most robust psychiatric condition contributing to most of the symptoms. Different medical conditions seemed to contribute to different symptom expressions of COVID-19 infection.

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference35 articles.

1. WHO. WHO Coronavirus Disease (COVID-19) Dashboard. [cited 12 Jun 2023]. https://covid19.who.int/

2. Incidence, co-occurrence, and evolution of long-COVID features: A 6-month retrospective cohort study of 273,618 survivors of COVID-19;M Taquet;PLoS Med,2021

3. Post-COVID Syndrome: Incidence, Clinical Spectrum, and Challenges for Primary Healthcare Professionals;A Pavli;Archives of Medical Research,2021

4. Symptoms, complications and management of long COVID: a review;OL Aiyegbusi;J R Soc Med,2021

5. Long COVID: An overview;AV Raveendran;Diabetes & Metabolic Syndrome: Clinical Research & Reviews,2021

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