Prevalence and influencing factors of long COVID brain fog among college students: a cross-sectional study in Taizhou, China

Abstract

Background

Long COVID following SARS-CoV-2 infection is a public health concern. Brain fog, a symptom of long COVID, has an impact on patients’ daily lives and health. However, studies on the effects of COVID on college students are limited.

Methods

This cross-sectional study included students from two tertiary institutions in Taizhou, China. Data were collected using WeChat-based electronic questionnaires on the Wen-Juan-Xing survey platform from July 20, 2023 to August 7, 2023. Chi-square analyses and binary logistic regression were used to evaluate the factors contributing to brain fog.

Results

A total of 1,071 students participated in the survey. Of these 1,071 students, 13.7% (147/1,071) reported experiencing long COVID, of whom 27.2% (40/147) reported symptoms of brain fog. Significant associations with brain fog were observed for the following factors: age (> 20 vs. ≤ 20 years, odds ratio (OR) = 4.360, 95% confidence interval (CI) [1.620–11.740]), clinical classification of COVID-19 (OR = 2.940, 95% CI [1.230–7.010]), and a decreased sense of smell and taste (OR = 5.110, 95% CI [1.240–21.110]).

Conclusions

This study highlights the significant prevalence of long COVID brain fog among college students and identifies key associated factors, underscoring the need for specific, focused interventions and support for affected individuals.

Introduction

The novel coronavirus disease, also known as 2019 coronavirus disease (COVID-19) and caused by severe acute respiratory syndrome (SARS)-CoV-2 infection, is an ongoing global health threat (Fisher & Heymann, 2020; Wang et al., 2023). The average incubation period for COVID-19 is 6.4 days, with hallmark symptoms including fever, coughing, dyspnea, myalgia, and fatigue (Ochani et al., 2021). Most people infected with COVID-19 recover from COVID-19-related symptoms within one-to-two months, with some patients remaining asymptomatic until two-to-three months post SARS-CoV-2 infection (Sivaselvi et al., 2023). Following the acute phase of the pandemic, estimates indicate that 10–20% of individuals infected with SARS-CoV-2 experience persistent symptoms after their initial illness has resolved (Bull-Otterson et al., 2022; Davis et al., 2023; World Health Organization, 2024; eBioMedicine, 2024). Lingering symptoms following COVID-19 can persist for weeks to months, severely reducing the patient’s quality of life. These lingering symptoms are commonly reported in the general literature as ‘long COVID’ (Davis et al., 2023). According to the World Health Organization (WHO), individuals who persistently experience or develop novel symptoms within a three-month timeframe following the initial SARS-CoV-2 infection, with these symptoms enduring for a minimum of two months and lacking an alternative explanation, are classified as having “post-COVID-19 condition (PCC)” or “long COVID” (Soriano et al., 2022; Global Burden of Disease Long COVID Collaborators et al., 2022).

The most common symptoms of long COVID include brain fog, gastrointestinal symptoms, palpitations, loss of smell or taste, chronic cough, dizziness, changes in sexual desire or capacity, thirst, chest pain, and abnormal movements (Thaweethai et al., 2023). Among the diverse symptoms of long COVID, brain fog is recognized as the most prevalent and persistent neurological manifestation, drawing substantial attention (Aghajani Mir, 2024). Brain fog is a colloquial term for a common complaint in patients with post-COVID-19 conditions (Krishnan et al., 2022); however, currently, there are no standardized diagnostic criteria for brain fog (Ross et al., 2013; Thaweethai et al., 2023; Denno et al., 2025). The characteristics of long COVID brain fog manifest as impaired attention, concentration, memory, information processing speed, and executive function, and are dependent on self-reporting (Monje & Iwasaki, 2022; Ceban et al., 2022).

Postmortem studies have detected SARS-CoV-2 in cerebral tissues, indicating an association between SARS-CoV-2 and neurological manifestations, although the pathological mechanisms remain unclear (Crunfli et al., 2022; Stein et al., 2022; Meinhardt et al., 2024). Many studies have explored the mechanisms underlying SARS-CoV-2-related brain fog, including the direct viral infection of neurons, immune activation, inflammatory responses, neuronal fusion, changes in synaptic activity, blood–brain barrier disruption, and astrocyte infections (Boldrini, Canoll & Klein, 2021; Aschman et al., 2022; Crunfli et al., 2022; Fernández-Castañeda et al., 2022; Greene et al., 2024; Yang et al., 2024). Impaired glutamate- and gamma-aminobutyric acid (GABA)-regulated pathways have also been reported in patients with long COVID brain fog (Manganotti et al., 2023).

Meta-analyses suggest that 50.1% of COVID-19 survivors may experience one or more long COVID symptoms for up to 12 months after infection, with higher prevalence observed in older adults and those with severe disease (Zeng et al., 2023). In contrast, younger people are at a lower risk of prolonged COVID-19 symptoms. Studies have shown that the prevalence of long COVID among college students ranges from 4% to 25% (Izquierdo-Pujol et al., 2022; Lopez-Leon et al., 2022; Morello et al., 2023; Zheng et al., 2023), while the prevalence of long COVID in children and adolescents is 25.24% (Lopez-Leon et al., 2022). Nevertheless, post-COVID-19 manifestations among college students have been shown to have a considerable impact on their physical, cognitive, and psychosocial health (Alkhormani et al., 2024). Previous studies have suggested that the prevalence of brain fog and objective cognitive impairment ranges from 17% to 85% in young adults recovering from COVID-19 (McNeill et al., 2025). Among young long-COVID patients, brain fog is more likely to occur in college students than in children or adolescents (Lopez-Leon et al., 2022; Broussard, Azola & Rowe, 2024). Despite growing awareness, little is currently known about the specific signs, symptoms, and predictors of long COVID in college campus populations. The potential ramifications of long COVID may adversely affect student learning and their overall quality of life (Landry et al., 2023).

Therefore, this population-based study aimed to investigate the prevalence of long COVID-related brain fog and its associated factors among college students on campus. To provide context for the findings of this study and to situate this study within the existing literature, a targeted literature search specifically focusing on long COVID brain fog across diverse populations was conducted. Table 1 summarizes 40 relevant studies examining the prevalence, operational definitions, and quality-of-life impacts of long COVID brain fog in various settings and age groups.

Table 1. Prevalence of long COVID brain fog in different populations and its impact on quality of life.

Variations in study populations, operational definitions of brain fog, methodological approaches, prevalence rates, and impacts on quality of life across different research studies. NA indicates that the information was not mentioned in the respective article.

Author, year	Country	Type of study	Definition of brain fog	Study population	Sample size	Prevalence rate	Impact on quality of life
Bell et al. (2021)	USA	A cohort study	Self-reported Confusion or brain fog	A non-hospitalized COVID-19 patients	303	31%	NA
Davis et al. (2021)	UK	A cross-section study	Poor attention, executive functioning, problem solving, and decision making.	COVID-19 patients	3,762	85%	Efficiency of work
Razai et al. (2021)	UK	A cross-section study	NA	COVID-19 patients	70	30%	NA
Asadi-Pooya et al. (2022)	Iran	A cohort study	Concentration difficultyand a worse status in the ability to concentrate and think	Adult patients (18-55 years old)	2,696	7%	NA
Bai et al. (2022)	Italy	A cohort study	Namely difficulties in attention or concentration and memory disorders	Adult females with long COVID	377	20%	NA
Chudzik et al. (2022)	Poland	A cohort study	Brain fog is used as an umbrella term to describe a range of cognitive impairments.	COVID-19 patients	1,235	12%	NA
Cristillo et al. (2022)	Italy	A cross-section study	Cognitive complaints are commonly described as “brain fog,” characterized by low-thinking, difficulties in focusing the attention, subjective confusion, and forgetfulness	Hospitalised COVID-19 patients	137	19%	Depression
El Otmani et al. (2022)	Morocco	A case-control study	Forgetfulness and the lack of focus and mental clarity	COVID-19 Healthcare Patients	118	14%	NA
Hirahata, Nawa & Fujiwara (2022)	Japan	A cross-section study	Difficulty concentrating, slowed thinking, memory decline—and these symptoms persist for ≥ 2 months without another explanatory diagnosis.	Long COVID patients	1,891	76%	NA
Jennings et al. (2022)	Ireland	A cross-section study	A subjective cognitive complaint characterized by difficulties with concentration, memory, and executive function, often accompanied by fatigue and emotional distress.	COVID-19 patients	108	66%	Memory disorders and with adverse psychological and psychomotor
Kalak et al. (2022)	Israel	A cohort study	Difficulty thinking clearly	COVID-19 patients	166	7%	NA
Moy et al. (2022)	Malaysia	A cross-section study	NA	The COVID-19 survivors in the community	732	9%	Health status, work efficiency
Orfei et al. (2022)	Italy	A cross-section study	Functional Brain Fog (FBF) - those who report the sensation of brain fog plus at least one subjective cognitive complaint (difficulty concentrating, sustaining attention, or remembering).	Employees of a single Italian banking group	441	40%	Neuropsychiatric symptoms, sleep disorders, rumination/indecisiveness
Perlis et al. (2022)	USA	A cohort study	Difficulty thinking or concentrating	Adult patients (≥18 years old)	16,091	46%	Working mode
Spinicci et al. (2022)	Italy	A prospective cohort study	NA	Long COVID patients	428	13%	NA
Tarantino et al. (2022)	Italy	A cross-section study	Difficulty, concentrating, Memory decline Slowed thinking	Adolescents with Previous SARS-CoV-2 Infection	31	Approximately 37%	NA
Wose Kinge et al. (2022)	South Africa	A cross-section study	NA	Frontline Health Workers	207	21%	NA
Antar et al. (2023)	USA	A cohort study	problems with concentration or slow thinking	COVID-19 patients	73	47%	NA
Aziz et al. (2023)	USA	A cross-section study	forgetfulness, difficulty concentrating	Long COVID patients presenting to a dedicated academic post-COVID-19 clinic	252	89%	NA
Horikoshi et al. (2023)	Japan	A cohort study	Definedas difficulty in thinking or concentrating	Children with long COVID	24	33%	NA
Hirschtick et al. (2023)	USA	A cross-section study	Difficulty concentrating, memory problems, and slowed thinking	COVID-19 patients	2,533	24%	NA
Lam et al. (2023)	Canada	A cohort study	Neurocognitive impairment.	Patients diagnosed with long COVID	1,642	60%	Aberrancy in immune response
Nordvig et al. (2023)	USA	A cohort study	A confluence of negative cognitive changes including executive, attention and memory decline	COVID-19 patients	530	32%	Sleep disturbance related, shortness of breath, weakness, smell disturbance/taste disturbance, activity limitation, disability/leave of absence, deterioration of health status
Perlis et al. (2023a)	USA	A cross-section study	Memory problems and difficulty concentrating or focusing	18–69 years old COVID-19 patients	2,236	46%	Employment status
Perlis et al. (2023b)	USA	A cohort study	NA	COVID-19 patients	423	44%	NA
Romero-Rodriguez et al. (2023)	Spain	A cross-section study	Mental fog	>14 years old with long COVID	689	79%	NA
Thaweethai et al. (2023)	USA	A cohort study	Problems thinking or concentrating and details.	Adults with COVID	9,764	20%	NA
Bello-Chavolla et al. (2024)	Mexico	A cross-section study	NA	(≥20 years old) Mexican National Health and Nutrition Survey (ENSANUT)	24,434	3%	NA
Chatys-Bogacka et al. (2024)	Poland	A cohort study	A subjective cognitive complaint characterized by difficulties with concentration, memory, and executive function, often accompanied by fatigue and emotional distress, reported by individuals with long COVID	Hospitalised COVID-19 patients	181	49%	Decline in quality of life
Foret-Bruno et al. (2024)	UK	A prospective cohort study	Cognitive impairment:confusion/memory loss	11–17 years old COVID-19 patients	705	7%–8%	Worse mental health, were more mentally fatigued, had poorer well-being and more trouble sleeping
Floridia et al. (2024)	Italy	A cohort study	NA	COVID-19 adult patients	1,297	7%	Work activity
Hurtado et al. (2024)	Colombia	A cohort study	It appears to play a mediation role in the relationship between objective and subjective cognitive outcomes	Long COVID patients	100	60%	NA
Leitner et al. (2024)	Austria	A cross-section study	Cognitive dysfunction	16,-80 years old COVID-19 patients	416	76%	Experienced work-related changes
Oh et al. (2024)	South Korea	A cross-section study	Decreased attention and cognitive decline	>19-year-old hospitalised patient	85	28.3%	Mental health and quality of life
Qin et al. (2024)	China	A cross-section study	NA	COVID-19 patients	74,075	17%	NA
Saloma et al. (2024)	Philippines	A cohort study	Difficulty thinking or concentrating	>15 years old COVID-19 patients	172	More than 50%	NA
Shigematsu et al. (2024)	Japan	A cross-section study	Memory impairment, poor concentration, dissociative phenomena, cognitive “slowness” and excessive effort, and communication difficulties	Hospitalised COVID-19 patients	109	12%	Labour productivity
Zhao et al. (2024)	China	A cross-section study	Cognitive impairments	Recovered patients with COVID-19 in the cardiovascular unit	452	25%	NA
McNeill et al. (2025)	New Zealand	A cross-section study	retrospectively self-reported cognitive impairment attributed to COVID-19, characterized by difficulties with concentration, memory, or executive function	College students COVID-19 patients	94	40%	NA
Zhang et al. (2025)	USA	A cross-section study	NA	Elderly female COVID-19 patients	13,933	11%	Physical function, daily physical activity

Methods

Study design and data collection

This cross-sectional study was conducted from July 20 to August 7, 2023 and included students from two colleges in Taizhou, China. The data were collected using the Wen-Juan-Xing platform and integrated into WeChat. A total of 1,071 individuals were invited to participate in the study. Convenience sampling was employed to recruit participants. Participation was voluntary, and study information and instructions were provided to all students. The respondents accessed and completed the self-administered questionnaire by scanning a QR code that directed them towards the online survey. A questionnaire was used to determine participants’ infection with SARS-COV-2, long COVID, and long COVID brain fog. The inclusion criteria were as follows: (1) college students enrolled at the time of the study (2) who were willing to participate. Long COVID was defined as SARS-CoV-2 infection for more than three months, with sequelae that persisted for more than two months, as per the World Health Organization’s (WHO) long COVID definition. After collecting the questionnaires, the exclusion criteria for the study participants were as follows: (1) not having been infected with SARS-COV-2 and (2) unavailability for long COVID assessment after SARS-COV-2 infection. Sample selection followed a structured multi-step process (Fig. 1). Of the 1,071 initial respondents, 341 were excluded because they had not been infected with SARS-CoV-2 (coded as missing data (−3) in the questionnaire system), leaving 730 participants who had experienced COVID-19 infection. These 730 individuals were then screened for long COVID status using the WHO’s definition of long COVID (Question 28: “Do you meet the WHO definition of long COVID—persistent symptoms ≥2 months occurring within 3 months post-SARS-CoV-2 infection?”). Of these 730 participants, 583 participants were excluded for not meeting long COVID criteria: 550 (75.3%) responded “No” to having long COVID, and 33 (4.5%) responded “Other” (infected <5 months ago, unable to assess whether symptoms met the 2-month persistence threshold). Ultimately, 147 participants (20.1% of those with prior infection) who responded “Yes” to the long COVID screening question were included in the final analysis. All 147 participants provided complete responses for the key variables analyzed in this study, with no additional missing data requiring imputation. The complete sample selection process is illustrated in Fig. 1.

Figure 1. Sample selection flowchart.

This study was approved by the Ethics Committee of Taizhou Hospital, Zhejiang Province, China (approval no. K20230716). The committee also granted a waiver for written informed consent for two main reasons: (1) the anonymous survey posed minimal risk to participants and (2) participation was voluntary. Informed instructions were provided to all students before they conducted the online survey. Participation was regarded as an indication of informed consent. All procedures were conducted in accordance with institutional ethics guidelines and conformed to the principles of the Declaration of Helsinki. Participants’ data were handled with strict confidentiality and anonymity. This study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Guidelines for Observational Research.

Structured questionnaires and measurement

Beginning June 2021, a series of population-based surveys were conducted. These surveys were designed to explore variations in awareness, perceptions, practices, and key factors related to COVID-19 symptoms and vaccine acceptance across demographic groups (Xu et al., 2023). Building upon this broader research effort, the current study focused on brain fog in college students.

Figure 2 illustrates the comprehensive framework of variables examined in this study. The framework encompassed three main domains: (1) socio-demographic characteristics (sex, age, education level, specialization, exercise habits); (2) COVID-19-related factors (infection status, vaccination status, clinical classification, treatment); and (3) specific symptoms following SARS-CoV-2 infection (decreased sense of smell and taste, respiratory distress, conjunctivitis), with the primary outcome being long COVID brain fog.

Figure 2. Framework for studying the outcome of variables.

Data for this investigation was gathered through a cross-sectional online survey using relevant background information. The questionnaire was designed through meetings with experts to ensure its completeness, validity, and scientific accuracy. The expert panel consisted of four epidemiologists and three clinicians. Epidemiologists evaluated the epidemiological characteristics of the disease and designed the study framework to ensure feasibility and methodological soundness, whereas clinicians assessed the clinical relevance and finalized the questionnaire. After the questionnaire was designed, it was tested on 30 students who met the inclusion criteria, yielding a Cronbach’s alpha scale coefficient of 0.87. Figure 2 illustrates the variable framework used in the study. The questionnaire included the following questions: (1) demographic information: including sex, age, underlying disease, and exercise habits; (2) SARS-CoV-2 infection-related information: infection frequency (i.e., first or second infection); vaccination status with booster COVID-19 vaccine; (3) clinical characteristics of infection: type of clinical diagnosis (asymptomatic or mild, moderate, or severe) and clinical symptoms (conjunctivitis, reduced sense of smell and taste, respiratory distress) after SARS-COV-2 infection (yes, no); presence of brain fog in patients with long COVID after SARS-CoV-2 infection; use of antiviral drugs after SARS-CoV-2 infection; and (4) information regarding whether participants’ symptoms met the definition of long COVID.

Brain fog was operationally defined as a subjective cognitive complaint characterized by difficulties in memory, concentration, information processing, planning, and organization, along with a general sense of mental confusion. The respondents first completed a screening module confirming that they met the WHO case definition for post-COVID-19 condition. Within this subset, brain fog was considered present when the cognitive symptoms (i) first emerged or distinctly worsened after the resolution of the acute COVID-19 phase; (ii) had been present for ≥4 consecutive weeks after the acute phase, regardless of daily fluctuations; (iii) resulted in demonstrable impairment in daily or social functioning; and (iv) were judged by the respondents to be substantially related to COVID-19, even if coexisting conditions were present.

Although validated cognitive assessment tools exist (such as the Montreal Cognitive Assessment or Mini-Mental State Examination), this study relied on self-reported measures for the following reasons: (1) the large-scale, online nature of the survey made objective cognitive testing logistically unfeasible; (2) self-reported brain fog has been shown to be a clinically meaningful indicator of cognitive dysfunction in long COVID research (Ross et al., 2013; Thaweethai et al., 2023); and (3) this approach aligns with the pragmatic, exploratory nature of this study in an underrepresented population. We acknowledge this methodological choice as a limitation that may affect the precision of prevalence estimates and one that precludes objective quantification of cognitive impairment severity.

Statistical analysis

Descriptive statistics were used to summarize the demographic characteristics of the participants and presented as frequencies and percentages (n [%]). Chi-square tests were initially conducted to explore potential risk factors related to long COVID that may contribute to the development of brain fog.

Variables with a significance level of p < 0.05 in the chi-square analysis were subsequently included in a binary logistic regression model to identify independent associations (Jiang et al., 2022). The results of the logistic regression analysis were reported as odds ratios (ORs) with 95% confidence intervals (CIs). All statistical analyses were performed using IBM SPSS Statistics, version 26.0. A two-tailed p-value of < 0.05 was considered statistically significant.

Results

A total of 147 participants met the WHO criteria for long COVID and were included in the final analysis, representing 13.7% (95% CI [11.6–16.1]%) of all survey respondents with prior COVID-19 infection (147/1,071) and 20.1% of those with confirmed infection history (147/730).

Ultimately, 147 individuals were included in the long COVID analysis. As shown in Table 2, 53.7% (79/147) of the participants were male and 46.3% (68/147) were female. The majority (76.9%, 113/147) of patients were aged ≤20 years. Regarding academic background, 44.2% (65/147) were from medical disciplines, and 55.8% (82/147) were from non-medical disciplines. In addition, 36.0% (45/147) of patients reported a history of secondary SARS-CoV-2 infection. Overall, 13.7% (95% CI [11.6–16.1]%) of the total survey respondents (147/1,071), all of whom had a previous COVID-19 infection, met the criteria for long COVID. Among them, 27.2% (95% CI [20.3–35.2]%; 40/147) reported experiencing brain fog as a symptom of long COVID.

Table 2. Basic characteristics and univariate analysis of brain fog in college students with long COVID (n = 147).

Independent variables	Categories	Total sample, n (%)	Long COVID brain fog		χ 2	P
			Symptomless, n (%)	Symptomatic, n (%)
		147 (100.0)	107 (72.8)	40 (27.2)
Sex	Male	79 (53.7)	59 (74.7)	20 (25.3)	0.309	0.578
	Female	68 (46.3)	48 (70.6)	20 (29.4)
Education level	Below bachelor’s degree	112 (76.2)	84 (75.0)	28 (25.0)	1.161	0.281
	Undergraduate and above	35 (23.8)	23 (65.7)	12 (34.3)
Specializations studied	Medical specialty	65 (44.2)	47 (72.3)	18 (27.7)	0.014	0.907
	Non-medical specialty	82 (55.8)	60 (73.2)	22 (26.8)
Age	≤20	113 (76.9)	88 (77.9)	25 (22.1)	6.383	0.012
	>20	34 (23.1)	19 (55.9)	15 (44.1)
Exercise habit	Yes	56 (38.1)	37 (66.1)	19 (33.9)	2.061	0.151
	No	91 (61.9)	70 (76.9)	21 (23.1)
Vaccination booster with COVID-19 vaccine	Yes	91 (61.9)	63 (69.2)	28 (30.8)	1.527	0.217
	No	56 (38.1)	44 (78.6)	12 (21.4)
SARS-CoV-2 infection status	First infection	102 (69.4)	72 (70.6)	30 (29.4)	0.815	0.367
	Second infection	45 (30.6)	35 (77.8)	10 (22.2)
Treatment of SARS-CoV-2 infections after	Unused medicine	30 (20.4)	24 (80.0)	6 (20.0)	0.990	0.320
	Use of medication or hospitalization	117 (79.6)	83 (70.9)	34 (29.1)
Clinical diagnostic categorization after SARS-CoV-2 infection	Asymptomatic or mild	97 (66.0)	77 (79.4)	20 (20.6)	6.257	0.012
	Moderate or severe symptoms	50 (34.0)	30 (60.0)	20 (40.0)
Use of antiviral drugs after SARS-CoV-2 infection	Yes	46 (31.3)	30 (65.2)	16 (34.8)	1.938	0.164
	No	101 (68.7)	77 (76.2)	24 (23.8)
Decreased sense of smell and taste	Yes	101 (68.7)	64 (63.4)	37 (36.6)	14.469	<0.001
	No	46 (31.1)	43 (93.5)	3 (6.5)
Respiratory distress	Yes	76 (51.7)	46 (60.5)	30 (39.5)	11.947	0.001
	No	71 (48.3)	61 (85.9)	10 (14.1)
Conjunctivitis	Yes	64 (43.5)	37 (57.8)	27 (42.2)	12.836	<0.001
	No	83 (56.5)	70 (84.3)	13 (15.7)

Handling of missing data

The primary missing data occurred at the initial screening stage, where 341 respondents (31.8%) had not been infected with SARS-CoV-2 and were therefore ineligible for long COVID assessment (coded as −3 in the database). Among the 730 participants with prior COVID-19 infection, an additional 33 (4.5%) could not be definitively classified as having long COVID due to insufficient time since infection (<5 months). All 147 participants who met the long COVID criteria provided complete responses for the key variables analyzed in this study. No imputation methods were required. The high response completeness (100% for analyzed variables) may be attributed to the mandatory field settings in the electronic questionnaire and the relatively brief survey duration.

As shown in the univariate analysis (Table 2), several factors were significantly associated with the presence of brain fog in college students with long COVID. Specifically, statistically significant associations were observed for age (χ2 = 6.383, p = 0.012), clinical diagnostic classification after SARS-CoV-2 infection (χ2 = 6.257, p = 0.012), and the presence of specific symptoms, including reduced sense of smell and taste (χ2 = 14.469, p < 0.001), respiratory distress (χ2 = 11.947, p = 0.001), and conjunctivitis (χ2 = 12.836, p < 0.001).

Additionally, binary logistic regression analysis was performed to assess the strength of the association between these variables and the occurrence of brain fog in students with long COVID. As illustrated in Fig. 3, brain fog was significantly associated with age >20 years (OR = 4.360, 95% CI [1.620–11.740]), clinical diagnostic classification (moderate or severe symptoms vs. asymptomatic or mild symptoms, OR = 2.940, 95% CI [1.230–7.010]), and a decreased sense of smell and taste (OR = 5.110, 95% CI [1.240–21.110]).

Figure 3. Forest plot of multivariable logistic regression analysis factors associated with brain fog in college students with long COVID.

Figure 3 presents a forest plot visualizing the odds ratios and 95% confidence intervals for these independent predictors, demonstrating the relative strength of each association.

Discussion

Key findings

This study investigated the prevalence of long COVID-associated brain fog and its influencing factors among on-campus college students, a population that has been underrepresented in previous studies. The results indicated that 13.7% (95% CI [11.6–16.1]%) of college students who had a previous COVID infection reported experiencing long COVID. Among these individuals, 27.2% (95% CI [20.3–35.2]%) reported brain fog as one of their symptoms. It is important to clarify the sample selection rationale and the representativeness of these findings. The final analytic sample of 147 participants represents those who met the WHO criteria for long COVID out of 1,071 total respondents. Long COVID itself is not a rare condition-our prevalence of 13.7% is consistent with prior global estimates suggesting 10–20% of COVID-19 survivors experience persistent symptoms (Bull-Otterson et al., 2022; Davis et al., 2023). Among this already symptomatic subgroup with long COVID, more than one in four in this study (27.2%) reported brain fog symptoms. Students without long COVID (n = 583, 54.5% of total respondents) were appropriately excluded from brain fog-specific analyses, as this study specifically aimed to characterize cognitive symptoms within the long COVID population. This approach aligns with standard epidemiological practice of defining a “population at risk” for the outcome of interest.

Furthermore, the study identified significant associations between brain fog and the following factors: age >20 years, moderate or severe symptoms during acute SARS-CoV-2 infection, and a reduced sense of smell and taste.

Previous studies have reported a prevalence of long COVID among college students, ranging from 4% to 25% (Izquierdo-Pujol et al., 2022; Lopez-Leon et al., 2022; Morello et al., 2023; Zheng et al., 2023). Consistent with earlier findings, the present study found that 13.7% of college students with previous COVID infection experienced long COVID. COVID-19 not only affects the respiratory system but can also affect multiple organ systems (Lam et al., 2024). At the physiological level, SARS-CoV-2 infiltrates host cells through angiotensin-converting enzyme 2 (ACE2) receptors, initiating inflammatory responses, immune activation, and tissue damage (Hoffmann et al., 2020). This process leads to multi-organ dysfunction, with the virus shown to affect the respiratory, cardiovascular, neurological, and gastrointestinal systems (Zhang et al., 2020; Hu et al., 2021). Current research has found that the incidence and manifestations of long COVID vary significantly among age groups, including children and young people. A study conducted in the United States revealed that the incidence rate of long COVID in infants and preschool children (0–5 years) was 14–15%, primarily manifesting as sleep disturbances and fatigue (Gross et al., 2025). The prevalence of long COVID in children and adolescents is estimated to be 25.24%, with emotional symptoms being the most common clinical manifestation (observed in 16.50% of cases), followed by fatigue (9.66%), and sleep disturbances (8.42%) (Lopez-Leon et al., 2022). Long COVID can impair physical, social, and emotional functioning, and college students may be particularly susceptible to cognitive impairment (Broussard, Azola & Rowe, 2024). Therefore, it is essential to address the specific impact of long COVID on this population.

In this study, 27.2% (95% CI [20.3–35.2]%) of college students who had a previous COVID infection with long COVID reported experiencing brain fog, which aligns with previous literature (McNeill et al., 2025). As shown in Table 1, the prevalence of long COVID brain fog ranged from 3% to 89% in previous studies. This wide variation may be attributed to differences in study populations and diagnostic criteria. The results of the present study suggest that the prevalence of long COVID brain fog in college students was higher than that in specific demographic groups, such as older women, where the prevalence figures lie between 11% and 20%. Conversely, the prevalence of brain fog in college students was lower than that in some hospitalized COVID-19 patients, whose prevalence ranges from 12% to 49%. According to previous studies, the higher incidence of brain fog in the hospitalized population may be attributable to the more severe conditions of hospitalized patients and the older age of the hospitalized population (Groff et al., 2021; Ch’en et al., 2023). However, existing literature suggests that young people experience a higher incidence of cognitive dysfunction after COVID-19 infection than older adults, with a longer duration, particularly manifested in terms of brain fog, attention deficits, and executive function impairments (Devita et al., 2021; Herrera et al., 2023). Another study reported that the prevalence of brain fog among children was 33%, which was slightly higher than that observed in the present study (Horikoshi et al., 2023). However, the assessment of self-reported symptoms may be subject to bias, as children are often too young to accurately describe their experiences. This wide range of results from different studies may be attributed to differences in research design, study population, and definition of brain fog, as shown in Table 1. Furthermore, as shown in Table 1, the impact of COVID-related long-term brain fog extends to individual productivity, mental health, physical activity, and the overall quality of life.

As previously documented, a decreased sense of smell and taste is a common symptom in the acute phase of COVID-19 (Berenguera et al., 2021; Premraj et al., 2022; Leng et al., 2023). The present study found a significant correlation between these symptoms and long COVID brain fog. However, this cross-sectional design cannot establish whether olfactory dysfunction causes brain fog or whether both are parallel manifestations of COVID-19 pathology. In addition, a recent study showed that a decreased sense of smell during the hospitalization of patients with COVID-19 was significantly associated with brain fog (Shigematsu et al., 2024), but the relationship between these two symptoms remains unclear. Studies have indicated that SARS-CoV-2 can directly invade cells by binding to the ACE2 receptor, which is expressed on both olfactory epithelial cells and taste receptors, thereby decreasing the sense of smell and taste in the host. This could also be attributed to the unique immune response elicited by COVID-19, which leads to elevated levels of inflammatory cytokines that subsequently affect the central nervous system, including brain regions related to olfactory function (Taquet et al., 2021). In addition, Meinhardt et al. (2021) reported that SARS-CoV-2 might directly infiltrate the neuromucosal interface of the olfactory epithelium and spread along olfactory pathways to the central nervous system, resulting in a decline in both smell and taste. This has been confirmed in animal experiments, which have shown that chronic inflammation within the olfactory bulb affects sensory, emotional, and cognitive functions (Frere et al., 2022). Therefore, olfactory and gustatory deficits may share overlapping pathophysiological mechanisms with brain fog.

Previous studies reported that the incidence of brain fog is related to the severity of COVID-19 (Taquet et al., 2021; Huang et al., 2023; Leone et al., 2024). This association was also observed in the present study, which found that moderate or severe symptoms during the acute phase of COVID-19 were significantly associated with long COVID brain fog among college students. One potential explanation for this correlation is that severe COVID-19 is associated with a more severe immune response and cytokine storm, which are more likely to cause organ damage (Sykes et al., 2021; Batabyal et al., 2021; Guedj et al., 2021), though these remain correlational findings in the present study and do not establish causation. Severe COVID-19 may also be associated with altered brain function (especially in cognitive areas) caused by SARS-CoV-2 infection (Hugon et al., 2022). This finding suggests that individuals who experience more severe symptoms upon contracting the SARS-CoV-2 infection are likely to experience persistent cognitive impairment.

In addition, the present study found that college students over the age of 20 years who had a previous COVID infection were more likely to develop brain fog associated with long COVID than those who were aged 20 or younger. Previous research demonstrated that SARS-CoV-2 infection can impair the cognitive function of college students (McNeill et al., 2025). Other studies have reported increased neuronal activity in the prefrontal cortex of COVID-19 patients, suggesting potential neurobiological alterations. Moreover, older age has been identified as a risk factor for the development of long COVID sequelae (Chen et al., 2022). However, it is worth noting that the age range within the present study population was relatively narrow. One possible explanation for this finding is that students over 20 years of age may face additional stressors related to graduation or job-hunting. Studies have shown that the pressure for future employment and academic delays during the COVID-19 pandemic were positively correlated with anxiety symptoms among college students (Wang et al., 2020; Cao et al., 2020). Psychological symptoms, such as anxiety and depression, have been increasingly recognized as components of long COVID and may contribute to or exacerbate cognitive dysfunction, including brain fog (Krishnan et al., 2022). Although the specific mechanisms underlying the increased risk of long COVID brain fog among college students over 20 years of age remain unclear, these findings highlight the need for increased attention to this vulnerable subgroup.

Clinical implications

There have been limited investigations into long COVID among college students. Young individuals are vulnerable to various biological, psychological, and social factors (Arnett, Zukauskiene & Sugimura, 2014; Browning et al., 2022), which may shape symptom persistence and recovery, potentially increasing their risk of experiencing persistent cognitive deficits after long COVID. Although evidence specific to college students remains limited, several studies have been conducted to improve cognitive function after long COVID, such as digital therapies targeting attention and executive control delivered via a smartphone or tablet. These studies suggest that cognitive function after long COVID can be improved using these therapies, which would be beneficial in addressing the substantial need for access to effective interventions for individuals with long COVID (Vanova et al., 2024; Victoria et al., 2025). Additionally, exercise interventions have been found to be effective in ameliorating fatigue and cognitive impairment after long COVID (Deodato et al., 2024). Notably, a review of exercise interventions for cognitive deficits after long COVID suggests that exercise may be beneficial for patients with long COVID (Gupta et al., 2025). Therefore, when confronted with long COVID brain fog in college students, previously studied interventions may be considered in order to improve the associated symptoms, thereby improving college students’ quality of life.

Advantages and limitations

This study addresses an important gap in the literature by examining long COVID-associated brain fog specifically in college students, a population that has been underrepresented in previous research. The findings provide preliminary data to inform future strategies for managing long COVID in university settings, particularly in non-Western contexts where such data are scarce.

However, several critical limitations must be acknowledged: First, the cross-sectional design precludes any causal inferences. This also means this study was unable to determine whether the identified factors (age >20 years, symptom severity during acute infection, olfactory/gustatory dysfunction) directly cause brain fog or are merely associated with it. The observed associations may reflect reverse causation or confounding by unmeasured variables. Longitudinal studies with repeated cognitive assessments are necessary to establish temporal relationships and track the trajectory of brain fog over time.

Second, the study relied exclusively on self-reported data without objective cognitive assessments. Brain fog was measured using single-item questions rather than validated neurocognitive batteries (e.g., Montreal Cognitive Assessment, computer-based cognitive testing). This approach, while pragmatic for large-scale online surveys, introduces several concerns: (i) potential recall bias; (ii) inability to quantify the degree of cognitive impairment; (iii) difficulty distinguishing between true cognitive dysfunction and subjective cognitive complaints; and (iv) reduced comparability with studies using standardized measures.

Third, and perhaps most critically, this study did not assess psychosocial confounders such as anxiety, depression, sleep quality, or pandemic-related stress using validated instruments (e.g., GAD-7, PHQ-9, PSQI). This represents a major limitation because psychological distress is highly prevalent among college students and is known to contribute to subjective cognitive complaints. It remains unclear whether the reported brain fog symptoms represent true COVID-related neurological dysfunction or are partially or wholly attributable to mental health factors. This uncertainty substantially limits the ability to draw definitive conclusions about the etiology of brain fog in this population. Future studies must incorporate standardized mental health screening tools to disentangle the contributions of psychological versus neurological factors.

Fourth, the convenience sampling from two institutions in one Chinese city, combined with the narrow age range (primarily 18–23 years), limits the generalizability of the study’s findings to broader college populations, other geographic regions, or other age groups.

Fifth, the operational definition of brain fog, while based on established literature, lacked the specificity and validation of multi-item cognitive scales. This may have affected the accuracy of prevalence estimates.

Despite these limitations, this study makes a meaningful contribution to the understanding of long COVID in an underrepresented population. While the reliance on self-reported measures precludes objective quantification of cognitive impairment, self-reported brain fog has demonstrated clinical relevance and is widely used in long COVID research globally. Our prevalence estimate of 27.2% for brain fog among college students with long COVID falls within the range reported in studies using similar methodologies (7%–85%, as shown in Table 1), supporting the validity of our findings within the context of the broader literature. Importantly, this study provides rare empirical data from college students in China, addressing a critical gap given that most existing research has been conducted in Western populations and clinical settings. The identified associations between brain fog and age, disease severity, and olfactory dysfunction are consistent with mechanistic hypotheses proposed in the literature, suggesting biological plausibility despite the cross-sectional design. These findings, while preliminary and requiring confirmation through longitudinal studies with objective assessments, offer actionable insights for university health services in developing targeted screening and support strategies for students at higher risk of post-COVID cognitive symptoms. Generalization of these results should be approached cautiously, particularly to populations outside of Chinese college settings or those with different COVID-19 variant exposures.

Future research priorities should include: (1) prospective cohort studies with baseline and follow-up assessments to examine brain fog persistence and recovery patterns; (2) incorporation of objective neurocognitive testing alongside self-reported measures; (3) comprehensive assessment of mental health and psychosocial factors using validated instruments; (4) investigation of potential biological mechanisms linking olfactory dysfunction to cognitive impairment; (5) evaluation of the academic and functional impacts of brain fog on college performance; and (6) development and testing of targeted interventions (e.g., cognitive rehabilitation, mental health support) tailored to college students experiencing long COVID-related symptoms.

Conclusions

This cross-sectional study provides preliminary evidence on the prevalence and correlates of long COVID-related brain fog among college students in China. The results showed that 13.7% (95% CI [11.6–16.1]%) of students with prior COVID-19 infection met criteria for long COVID, and 27.2% (95% CI [20.3–35.2]%) of this subgroup reported brain fog symptoms. Age > 20 years, moderate-to-severe acute illness, and olfactory/gustatory dysfunction were independently associated with brain fog in the multivariable analysis.

While these findings add to the limited literature on long COVID in college-aged populations, particularly from non-Western settings, several important limitations must be considered. The cross-sectional design prevents causal inference, the reliance on self-reported cognitive symptoms without objective assessment limits precision, and the absence of mental health measures leaves open the possibility that psychological factors contributed to reported brain fog. Therefore, these results should be interpreted as hypothesis-generating rather than definitive.

Future research should employ longitudinal designs with validated cognitive assessments and mental health screening to better characterize the nature, trajectory, and determinants of brain fog in this population. Such evidence will be essential for developing and testing targeted interventions to support college students experiencing persistent cognitive symptoms after COVID-19, ultimately promoting their academic success and quality of life.

Funding Statement

This study was supported by the Key Research and Development Project of Zhejiang Province (No. 2023C03046). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.