Cardiometabolic Risk and Symptom Burden Converge in Adults With Overlapping Immune and Cardiovascular Complaints
A cross-sectional analysis of 524 adults links cardiometabolic risk factor burden with a broader cluster of immune-related and cardiovascular symptoms, while also placing psychological symptoms at the center of that pattern. The study examined how fatigue, cardiovascular complaints, and immune-related symptoms move together in the same adults rather than treating them as separate clinical silos. In practice, the findings point toward a symptom constellation that tracks with adiposity, insomnia, and depressive symptoms, not just isolated organ dysfunction.
The cohort was middle-aged on average, with a mean age of 51.16 years, and carried a mean body mass index of 28.33 kg/m². Women made up 57.8% of the sample, men 42.2%. Across 12 symptom items, mean immune symptom burden was 4.09, mean cardiovascular symptom burden was 4.42, and total symptom burden reached 8.52. Those scores are not just statistical abstractions; they represent a population in which symptom load was high enough to justify thinking about cardiovascular and immune complaints as intertwined bedside signals.
Bifactor Modeling Pointed to One Shared Symptom Construct With Domain-Specific Layers
The psychometric analysis was one of the most important pieces of the study. The bifactor model fit best, with a comparative fit index of 0.995 and a root mean square error of approximation of 0.016. In plain clinical terms, the symptom items behaved as though they belonged to a general burden construct while still preserving immune-specific and cardiovascular-specific structure.
This kind of architecture fits the reality of many symptomatic adults. Fatigue, shortness of breath, chest discomfort, sleep disruption, and low mood rarely arrive in tidy compartments. They often travel together, and shared biological drivers such as low-grade inflammation, autonomic dysregulation, disrupted sleep, and excess adiposity may help explain why one symptom cluster bleeds into another. The model does not prove mechanism, but it does support a framework in which symptom surveillance should be broader than a single complaint or a single risk factor.
Adiposity, Sleep Disturbance, and Depressive Symptoms Carried the Strongest Associations
In adjusted analyses, immune symptom burden was independently associated with age, body mass index, and depressive symptoms. Cardiovascular symptom burden was independently associated with body mass index, insomnia severity, and depressive symptoms. Total symptom burden showed the broadest set of associations: age, body mass index, insomnia severity, and depressive symptoms all remained significant.
The pattern is clinically coherent. Excess adiposity is a plausible upstream driver of chronic inflammatory signaling, endothelial stress, and metabolic strain, any of which could intensify both immune-type and cardiovascular-type symptom reporting. Insomnia can magnify autonomic activation, blunt recovery, and worsen pain and fatigue perception, making cardiovascular sensations more noticeable and harder to ignore. Depressive symptoms can amplify symptom salience, lower physiologic resilience, and overlap with fatigue and somatic distress. One sentence from the data stands out clearly: psychological symptoms were not peripheral; they were woven into both symptom domains.
Risk-Factor Count Rose With Symptom Load, But Lost Independence After Adjustment
Symptom burden increased descriptively across categories of cardiometabolic risk factors, suggesting a dose-like relationship between accumulated risk and symptom intensity. Yet the count of risk factors did not remain independently associated after adjustment. This means the surface gradient was real, but its explanatory power was absorbed by other variables in the model, especially body mass index, insomnia, and depressive symptoms.
The finding matters because it shifts attention away from a simple tally of risk factors and toward the symptom ecology around them. A patient with multiple cardiometabolic risks may appear clinically more complex, but the burden may be expressed through sleep disruption, low mood, and widespread fatigue rather than through a neat linear effect of risk-factor count alone. Clinicians who stop at the number of risk factors may miss the symptom channels through which risk becomes clinically visible.
Two Latent Symptom Classes and a Network Centered on Fatigue
Latent class analysis supported a two-class solution, indicating that the adult population could be separated into distinct symptom phenotypes rather than a single undifferentiated group. The article did not supply the class labels in the abstract, but the structure itself suggests heterogeneity in how immune and cardiovascular symptoms cluster across adults.
The network analysis brought another layer into focus. Fatigue-related symptoms emerged as central bridge symptoms across domains. In network terms, bridge symptoms are the items most likely to connect one cluster to another, and fatigue fits that role well. It is a biologically plausible connector because fatigue can arise from inflammation, sleep loss, depression, autonomic imbalance, and metabolic dysfunction all at once. When fatigue sits at the center of the network, it can pull immune complaints and cardiovascular complaints into the same lived experience of poor health.
What This Means for Symptom Surveillance in Public Health and Primary Care
These findings support integrated assessment rather than fragmented screening. Adults with elevated body mass index, poor sleep, and depressive symptoms may warrant closer attention not only for metabolic endpoints but also for immune-related and cardiovascular symptom burden. The study strengthens the case for asking about fatigue, insomnia, and mood in any patient evaluation that touches cardiometabolic risk, because those symptoms may be the earliest visible markers of a broader burden pattern.
The work is also a reminder that symptom burden can be clinically meaningful even when it is not tied to a single diagnosed disease state. Public-health surveillance usually prioritizes blood pressure, lipids, glucose, or body mass index. Those remain essential, but they do not capture the full picture of how risk is experienced by patients. A patient with rising symptom burden may be signaling biological stress before a formal cardiometabolic diagnosis becomes obvious.
Cross-Sectional Design Limits Causal Claims
The study’s design keeps the conclusions appropriately bounded. Cross-sectional data can identify association and clustering, but it cannot determine whether adiposity, insomnia, and depressive symptoms drive symptom burden, or whether symptom burden worsens sleep and mood, or whether all of these processes evolve together over time. The sample also came from a questionnaire-based observational setting, and the symptom constructs were measured at one point in time.
Even with those limitations, the pattern is difficult to dismiss. Immune-related and cardiovascular symptoms did not appear randomly distributed. They clustered with adiposity and psychological distress, and the strongest bridge across domains was fatigue. For clinicians, that combination argues for a broader interview, not a narrower one: the next question should not stop at chest discomfort or palpitations, but should extend to sleep quality, mood symptoms, and the fatigue that often knits them together.