Review Article
This review summarizes protocols used to assess behavioral risk factors and metabolic profiles in clinical cohorts. It highlights biomarkers, mechanistic pathways, and translational applications for early detection, risk stratification, and targeted lifestyle interventions for metabolic dysfunction.
Metabolic abnormalities have been identified in relation to behavioral risk factors in clinical cohorts. Individual risk factors, such as smoking, alcohol intake, sedentary lifestyle, and poor dietary quality, remain predominant contributors to disease, yet their combined effects on metabolic physiology require a clear characterization. This review summarizes current evidence linking behavioral risk factors with altered metabolic profiles in clinical cohorts, with a focus on mechanistic pathways, biomarker changes, and interaction effects. Across multiple cohorts, poor health behaviors were associated with impaired insulin sensitivity, dyslipidemia, increased visceral adiposity, hypertension, and chronic low-grade inflammation. Behaviors have been shown to exert additive and, in some cases, synergistic metabolic effects. Psychological stress, sleep disruption, and genetic predisposition acted as modifiers, further influencing metabolic patterns. Behavioral risk factors significantly affect metabolic health, with cumulative effects exceeding the impact of individual behaviors. Integrating structured behavioral assessment into routine care may improve early detection and guide targeted intervention.
Behavioral risk factors such as poor sleep, physical inactivity, unhealthy diet, smoking, and psychosocial stress are associated with adverse metabolic profiles. These profiles are characterized by elevated glucose, increased triglycerides, raised LDL cholesterol with reduced HDL cholesterol, hypertension, and central adiposity. These behavioral risk factors, associated metabolic alterations, clinical outcomes, and key supporting references are summarized in Table 1. Collectively, these abnormalities contribute to an increased risk of cardiovascular disease, type 2 diabetes, mood disorders, and other chronic conditions1,2,3,4.
Metabolic syndrome represents a major and expanding global health challenge. Recent estimates suggest that it affects approximately one quarter to one third of adults worldwide, with a global burden exceeding one billion individuals and continuing to rise across most regions4. The International Diabetes Federation reports that more than 530 million adults are currently living with diabetes, with projections approaching 780 million by 2045–2050, reflecting the accelerating global severity of cardiometabolic disease5. In parallel, World Health Organization data highlight diabetes and related metabolic disorders as increasing non-communicable diseases with substantial impacts on mortality, disability, and healthcare systems6. Large-scale meta-analytic evidence further confirms substantial geographic and demographic variability in metabolic syndrome prevalence. Higher rates were observed in older populations, urban settings, and in individuals exposed to adverse lifestyle environments3,4.
Regarding metabolic health and behavior, there is growing evidence that one influences the other in a bidirectional manner. For instance, individuals with depression or bipolar disorder have a higher prevalence of insulin resistance, dyslipidemia, and central obesity, and often present with more severe symptoms and poorer treatment outcomes1. Conversely, metabolic syndrome components are also associated with increased risk and poorer prognosis of psychiatric disorders2,7.
Lifestyle patterns appear to play a central role in this relationship. Individuals with healthier combined behavioral profiles have a lower risk of developing metabolic syndrome compared with those with multiple adverse behaviors, and this association appears consistent across both cross-sectional and longitudinal studies8. The risk increases progressively with the accumulation of unhealthy behaviors, supporting a dose-dependent relationship between lifestyle and metabolic outcomes3,9,10.
Taken together, these findings highlight the importance of understanding how behavioral factors contribute to metabolic dysfunction and how metabolic changes, in turn, influence behavior and disease progression. This review examines current evidence from clinical cohorts, focusing on shared mechanisms, metabolomic signatures, biological modifiers, and implications for early detection and targeted intervention.
Conceptual framework
To address the multidimensional nature of metabolic dysfunction in clinical populations, this review adopts an integrative conceptual framework that connects behavioral risk factors, metabolic alterations, psychiatric comorbidity, and biological modifiers within a unified systems-based model. Rather than treating these domains as independent contributors, the framework conceptualizes them as interdependent components of a dynamic biopsychosocial network that collectively shapes metabolic health outcomes1,2,3,8.
At the core of this model are behavioral risk factors, including physical inactivity, poor dietary quality, sleep disruption, smoking, alcohol consumption, and psychosocial stress. These changes converge into clinical phenotypes such as insulin resistance, dyslipidemia, hypertension, and central obesity, which define metabolic syndrome and related cardiometabolic disorders2.
Within this framework, psychiatric disorders represent both a consequence and a driver of metabolic dysfunction. Mood disorders, including major depressive disorder and bipolar disorder, are associated with adverse metabolic profiles, including insulin resistance and dyslipidemia7,9. Conversely, metabolic abnormalities exacerbate psychiatric symptom severity through shared mechanisms such as inflammation, hypothalamic–pituitary–adrenal (HPA) axis dysregulation, endothelial dysfunction, and neurotransmitter alterations2,7,11. This bidirectional interaction supports a unified “metabolic–psychiatric axis” rather than isolated disease entities.
Finally, demographic and biological modifiers, including age, sex, genetic susceptibility, epigenetic regulation, and body composition, influence the strength and expression of these relationships12,13,14. These modifiers explain inter-individual variability and contribute to differential vulnerability to metabolic and psychiatric comorbidity. Collectively, this integrative framework positions metabolic dysfunction as the outcome of interacting behavioral, psychological, molecular, and biological systems rather than isolated risk domains1,2,3,7,8. This structure underpins the organization of the present review.
Unlike prior reviews that primarily focused on isolated behavioral factors or single metabolic outcomes, the present review integrates behavioral risk factors, metabolomic alterations, psychiatric comorbidities, and biological modifiers within a unified clinical framework. In addition, this review emphasizes the reciprocal and multidirectional interactions between behavioral exposures and metabolic dysfunction, incorporating emerging evidence from metabolomics, neuroendocrine pathways, and precision medicine approaches. We also highlight translational implications for early detection, risk stratification, and integrated behavioral-metabolic interventions in clinical populations, which distinguishes this review from earlier narrative or disease-specific reviews.
Methods
This study is a narrative review of the literature examining associations between behavioral risk factors and altered metabolic profiles in clinical cohorts. The aim was to synthesize current evidence on behavioral determinants of metabolic dysfunction, including biomarkers, mechanistic pathways, and translational implications for early detection and targeted intervention. A structured literature search was conducted in the Scopus database to identify relevant peer-reviewed studies. The search strategy used combinations of keywords including “behavioral risk factors,” “metabolic profiles,” “metabolic syndrome,” “diet,” “physical inactivity,” “sleep,” “stress,” “alcohol consumption,” and “cardiometabolic risk.” Boolean operators were applied to refine and combine search terms where appropriate.
Studies were included if they: (1) investigated associations between behavioral risk factors and metabolic outcomes, (2) were conducted in human clinical or population-based cohorts, and (3) reported metabolic, biochemical, or clinical endpoints relevant to cardiometabolic health. Exclusion criteria included non-peer-reviewed articles, case reports, animal or in vitro studies, and studies not directly addressing behavioral–metabolic relationships. The search was limited to English-language publications. Articles published between 2010 and 2024 were considered eligible for inclusion. Study selection involved screening of titles and abstracts followed by full-text review to assess relevance to the review objectives. Data from eligible studies were synthesized qualitatively, focusing on metabolic biomarkers, mechanistic pathways, and clinical and translational implications.
Combined lifestyle behaviors, metabolic risk, and metabolomic signatures
Research suggests that lifestyle behaviors influence metabolic risk, supporting approaches that consider multiple behavioral patterns together. Across the review, individuals with the healthiest combined profiles exhibited lower likelihood to develop metabolic syndrome compared with those with the least healthy lifestyles, with an approximately 43% risk reduction. Notably, the inverse association was consistent across both cross-sectional and prospective cohort studies, highlighting the importance of combined lifestyle behaviors in metabolic risk development8.
Emerging metabolomic evidence has provided greater mechanistic insight into how behavioral risk factors influence metabolic dysfunction. Unhealthy behavioral patterns, including physical inactivity, poor dietary quality, sleep disruption, smoking, and chronic psychosocial stress, have been associated with alterations in several metabolite classes and metabolic pathways15. Specifically, elevated circulating acylcarnitines and branched-chain amino acid metabolites have been linked with impaired mitochondrial fatty acid oxidation, insulin resistance, and disrupted energy metabolism15. Increased trimethylamine N-oxide concentrations have also been associated with endothelial dysfunction, systemic inflammation, and increased cardiovascular risk15. In parallel, adverse behavioral profiles have demonstrated associations with elevated triglyceride-rich lipoproteins and pro-inflammatory lipid mediators, alongside reductions in protective lipid metabolites, phosphocreatine, and metabolites involved in cellular energy homeostasis15. These findings suggest that behavioral exposures produce quantifiable molecular signatures that may contribute to the development and progression of cardiometabolic disease.
Behavioral risk factors exert cumulative and, in some cases, synergistic effects on metabolic health. Individuals with the healthiest combined lifestyle behaviors demonstrated an approximately 43% lower risk of metabolic syndrome compared with those with the least healthy behavioral profiles8. Across multiple large-scale cohort studies, adverse behavioral patterns, including physical inactivity, poor dietary quality, smoking, sleep disruption, and psychosocial stress, were associated with increased incidence of insulin resistance, dyslipidemia, hypertension, central adiposity, and chronic systemic inflammation3,9,10. The magnitude of these metabolic disturbances appeared to increase in a dose-dependent manner, particularly among individuals with multiple concurrent behavioral risk factors3,9,10.
Metabolomic investigations further support these observations, demonstrating that unhealthy behavioral patterns are associated with elevated triglycerides, acylcarnitines, and trimethylamine N-oxide, as well as reductions in protective lipid metabolites and phosphocreatine, indicating measurable molecular signatures of lifestyle-related metabolic dysfunction6. These findings emphasize the clinical importance of early behavioral risk identification and targeted preventive interventions in at-risk populations3,8,9,10,15.
Diet and physical activity are two of the most influential behavioral determinants of metabolic health. Dietary patterns characterized by high intake of ultra-processed foods, refined carbohydrates, and saturated fats, and low intake of fiber-rich foods, fruits, and vegetables are consistently associated with insulin resistance, dyslipidemia, central adiposity, and systemic inflammation1,3,8. In contrast, dietary patterns such as Mediterranean-style or plant-forward diets are linked with improved lipid profiles, better glycemic control, and reduced cardiometabolic risk3,8.
Physical activity also shows a clear dose–response relationship with metabolic outcomes. Sedentary behavior is associated with increased risk of obesity, insulin resistance, and cardiovascular disease, whereas regular moderate-to-vigorous physical activity improves insulin sensitivity, reduces visceral fat, lowers blood pressure, and improves lipid profiles1,2,15. Increasing activity levels are associated with progressively greater reductions in cardiometabolic risk, supporting a graded protective effect rather than a threshold response1,2.
Metabolic syndrome, disease risk, and preventive strategies
Metabolic syndrome is defined by the co-occurrence of central obesity, hypertension, insulin resistance, and dyslipidemia, which involve elevated total cholesterol, low-density lipoprotein (LDL) cholesterol, and/or triglycerides, and/or reduced high-density lipoprotein (HDL) cholesterol. Each of these components increases disease risk, but when these factors are present together there is an amplified effect to develop cardiovascular disease, type 2 diabetes mellitus, non-alcoholic fatty liver disease, and other chronic conditions2,3,4,16,17.
Cardiovascular disease
Metabolic syndrome is linked to a higher risk of cardiovascular disease, and research shows that this risk tends to rise as more components of the syndrome are present. Some factors, particularly hypertension and insulin resistance, appear to be stronger predictors of cardiovascular complications than others. Certain populations, including individuals living with HIV, may be more vulnerable to the combined effects of metabolic abnormalities, highlighting the importance of early detection and intervention18.
Cancer risk: Colorectal adenoma and colorectal cancer
Conditions associated with metabolic dysfunction, including obesity, type 2 diabetes mellitus, non-alcoholic fatty liver disease, and hypertension, have been linked to an increased risk of colorectal adenoma and colorectal cancer9,19. Higher levels of HDL cholesterol may provide a protective effect, although findings for other lipid markers remain inconsistent19. Evidence also suggests that the risk of colorectal adenoma and cancer increases with the accumulation of metabolic syndrome components, particularly among older men and in right-sided colon lesions, highlighting the importance of targeted screening and early prevention strategies in high-risk populations9.
Sleep, stress, and metabolic dysregulation
Both sleep disturbances and psychosocial stress contribute to the development and progression of metabolic syndrome and are associated with an increased risk of cardiovascular disease2,3,10. Inadequate or fragmented sleep has been linked to inflammation, insulin resistance, dyslipidemia, and hypertension, with these effects appearing particularly pronounced in psychiatric populations2,10. Psychosocial stress may further impair endothelial function through activation of the hypothalamic–pituitary–adrenal axis, thereby increasing metabolic risk and potentially accelerating disease progression3.
Influence of biological and demographic factors
Reproductive and developmental factors may influence susceptibility to metabolic dysfunction across the lifespan. In females, reproductive factors such as early menarche, menstrual irregularities, gestational weight gain, and menopause have been associated with altered insulin sensitivity, dyslipidemia, and increased cardiometabolic risk12. These reproductive transitions are influenced by hormonal regulation, inflammatory pathways, and behavioral factors, which may contribute to long-term metabolic alterations.
Similarly, body composition and skeletal muscle mass play important roles in metabolic regulation during childhood and adolescence. Reduced muscle mass in pediatric populations has been associated with impaired glucose metabolism, increased adiposity, and a higher risk of developing metabolic syndrome later in life20. However, these associations are influenced by developmental stage, nutritional status, physical activity levels, and methodological differences between studies.
Genetic and epigenetic mechanisms further contribute to the complex interactions between behavioral exposures and metabolic health. Shared genetic loci have been shown to influence susceptibility to both psychiatric disorders and metabolic traits, including obesity, dyslipidemia, and glucose dysregulation13. In addition, epigenetic modifications induced by early life stress, dietary exposures, sleep disruption, and other environmental factors may alter inflammatory, neuroendocrine, and metabolic pathways, thereby modulating long-term disease risk14. Together, these biological and demographic modifiers help explain the heterogeneity observed in metabolic responses across different clinical populations.
Mechanistic insights
The pathophysiology of metabolic syndrome involves not only traditional metabolic risk factors, but also endothelial dysfunction, chronic inflammation, and stress-related biological mechanisms2,4. Many of these pathways overlap with those implicated in psychiatric disorders, suggesting the presence of interconnected pathogenic processes. Recognition of these shared mechanisms supports the development of integrated preventive and therapeutic strategies that address both behavioral and metabolic contributors to disease2,4.
Early identification of behavioral and metabolic risk factors enables the implementation of targeted preventive and therapeutic interventions. Lifestyle modification, including improvements in diet, physical activity, sleep hygiene, and stress management, remains fundamental in reducing both metabolic and psychiatric morbidity2. Screening strategies, such as colorectal cancer surveillance in high-risk populations and routine monitoring of metabolic markers in psychiatric patients, may facilitate earlier detection and timely intervention9. Personalized approaches that integrate behavioral, metabolic, and demographic factors are likely to improve clinical outcomes and reduce the risk of long-term complications2,9.
Chronic low-grade inflammation is increasingly recognized as one of the key mechanisms linking unhealthy behaviors with metabolic dysfunction. Persistent inflammatory activity and oxidative stress can impair insulin signaling, disrupt glucose metabolism, alter lipid regulation, and damage vascular tissues over time. These processes contribute to insulin resistance, dyslipidemia, endothelial dysfunction, and progression of cardiometabolic disease, particularly in individuals exposed to multiple behavioral risk factors2,4,10.
Endothelial dysfunction also plays an important role in the development of metabolic syndrome and cardiovascular complications. Reduced nitric oxide availability and chronic vascular inflammation impair normal vascular reactivity, promoting hypertension, atherosclerotic progression, and reduced tissue perfusion2,10. These alterations may explain why metabolic abnormalities frequently coexist with increased cardiovascular risk.
Psychosocial stress and psychiatric disorders further influence metabolic health through dysregulation of the hypothalamic–pituitary–adrenal axis. Prolonged activation of this stress-response system leads to sustained cortisol elevation, which has been associated with central adiposity, impaired glucose regulation, autonomic imbalance, and abnormal lipid metabolism. Over time, these metabolic changes may also worsen psychiatric symptoms and contribute to a bidirectional cycle between mental health disturbances and metabolic dysfunction2,10,11.
Sleep disturbance represents another important pathway connecting behavioral and metabolic risk. Poor sleep quality, insufficient sleep duration, and circadian disruption have been associated with altered appetite regulation, sympathetic nervous system activation, impaired glucose metabolism, and increased systemic inflammation. Together, these changes contribute to obesity, insulin resistance, hypertension, and increased cardiometabolic risk, particularly among individuals with psychiatric comorbidities3,10,17.
Reciprocal associations and mechanistic pathways linking behavior, metabolism, and mental health
Although this review primarily focuses on behavioral risk factors and metabolic dysfunction, psychiatric disorders were included because of their substantial biological and behavioral overlap with metabolic disease. Mood disorders, including depression and bipolar disorder, are consistently associated with adverse lifestyle behaviors, sleep disruption, psychosocial stress, systemic inflammation, insulin resistance, and dyslipidemia1,2,7. Therefore, psychiatric populations provide an important clinical model through which interactions between behavioral exposures, metabolic alterations, and chronic disease progression can be better understood.
Psychiatric disorders and metabolic dysfunction have demonstrated a bidirectional relationship mediated through overlapping behavioral, neuroendocrine, inflammatory, and metabolic mechanisms1,2. Chronic low-grade inflammation, hypothalamic–pituitary–adrenal (HPA) axis dysregulation, endothelial dysfunction, insulin resistance, sleep disruption, and psychosocial stress contribute to both psychiatric symptomatology and metabolic abnormalities. Elevated pro-inflammatory cytokines, including interleukin-6 and tumor necrosis factor-α, have been associated with impaired insulin signaling, endothelial injury, altered neurotransmitter regulation, and increased cardiometabolic risk. Of note, persistent activation of the HPA axis may increase cortisol secretion, promoting central adiposity, hyperglycemia, hypertension, and dyslipidemia while simultaneously contributing to depressive symptoms, cognitive dysfunction, fatigue, and emotional dysregulation.
Furthermore, sleep disturbances exacerbate these interactions through impaired glucose metabolism, autonomic dysfunction, altered appetite regulation, and increased systemic inflammation1,2,10. Interestingly, patients with mood disorders exhibit impaired glucose regulation, dyslipidemia, increased visceral adiposity, and elevated inflammatory biomarkers, with reduced treatment responsiveness compared with healthy populations1,2,7. Conversely, metabolic dysfunction may worsen psychiatric symptom severity and negatively affect adherence to lifestyle and pharmacological interventions. Emerging evidence also suggests that shared genetic susceptibility loci and epigenetic modifications influenced by environmental exposures, diet, stress, and lifestyle behaviors may contribute to the convergence of psychiatric and metabolic disorders. These overlapping biological and behavioral pathways suggest that psychiatric and metabolic disorders should be considered interconnected clinical entities requiring integrated preventive, diagnostic, and therapeutic approaches rather than isolated conditions1,2,7,11,13.
Mood disorders and metabolic dysregulation
Mood disorders, including major depressive disorder and bipolar disorder, are associated with metabolic pathologies. Patients with these disorders show greater fasting glucose, elevated LDL cholesterol, reduced HDL, increased triglycerides, and higher prevalence of insulin resistance compared to healthy cohorts1. These disturbances correlate with greater symptom severity, including anhedonia, sleep disruption, fatigue, and suicidal ideation, and might contribute to treatment resistance and chronic disease progression1,2,7,16. Meanwhile, chronic depression is linked to behavioral changes, such as poor diet, sedentary lifestyle, and sleep disruption, that promote metabolic dysregulation2,7.
Inflammation and endothelial dysfunction
Chronic low-grade inflammation represents a common underlying mechanism linked to psychiatric disorders and metabolic syndrome. Elevated cytokines and impaired endothelial function contribute to insulin resistance and vascular pathology, reinforcing the cycle between mental health and metabolic disturbances2,4.
Hypothalamic–pituitary–adrenal (HPA) axis dysregulation and stress
Psychosocial stress and psychiatric symptomatology activate the hypothalamic–pituitary–adrenal axis, increasing cortisol levels and promoting central adiposity, hyperglycemia, and hypertension. These stress-related metabolic changes further exacerbate mood disorder severity, creating a feedback loop2,10.
Sleep disruption
Sleep disturbances act as central mediators, connecting behavioral and metabolic risk factors to psychiatric outcomes. Insufficient or fragmented sleep contributes to insulin resistance, hypertension, dyslipidemia, and elevated inflammatory markers, particularly in patients with mood disorders, where sleep may serve as a link connecting mental and metabolic pathology2,3.
Genetic and epigenetic contributors
Shared genetic predispositions influence both psychiatric disorders and metabolic traits. Certain loci confer risk for psychiatric illness while modulating body mass index, lipid profiles, or glucose metabolism. Epigenetic modifications, influenced by early-life stress, diet, and lifestyle, further modulate these relationships, underscoring the complex gene–environment interplay13,14.
Clinical implications
Recognizing the reciprocal associations between psychiatric disorders and metabolic dysfunction is critical for comprehensive patient care. Screening for metabolic risk in patients with mood disorders and implementing early behavioral interventions, such as structured physical activity, dietary optimization, stress management, and sleep hygiene, can mitigate metabolic deterioration. Conversely, addressing psychiatric symptoms in patients with metabolic syndrome may improve adherence to lifestyle interventions and reduce cardiometabolic risk2,9.
Future directions and research perspectives
Longitudinal and mechanistic studies
While cross-sectional studies have established associations between behavioral risk factors, metabolic profiles, and psychiatric outcomes, longitudinal research is needed to clarify causality, temporal relationships, and dose–response effects. Prospective cohort studies tracking behavioral, metabolic, and psychiatric parameters over time will provide insights into which risk factors are primary drivers versus secondary consequences1,7,11. Future mechanistic studies investigating inflammation, endothelial dysfunction, hypothalamic–pituitary–adrenal axis dysregulation, and neuroendocrine pathways will shed light on how behavioral and metabolic risk factors converge to influence both physical and mental health. Integrating genomics, metabolomics, and proteomics may further identify novel biomarkers for early detection and intervention13,14.
Personalized and precision medicine approaches
Advancements in precision medicine offer the potential for individualized interventions that consider genetic, behavioral, metabolic, and demographic factors. Personalized risk profiling can guide lifestyle interventions, pharmacologic therapy, and psychiatric care, enabling optimized prevention and management strategies. For example, stratifying patients by metabolic phenotype and psychiatric risk may enhance the efficacy of behavioral interventions and improve long-term clinical outcomes3,12.
Integration of behavioral and metabolic interventions
Future research should explore combined interventions targeting both behavioral and metabolic pathways simultaneously. Multi-component programs addressing diet, physical activity, sleep, stress management, and psychiatric care may have additive effects, reducing the burden of chronic disease more effectively than single-component strategies2,3.
Population-level strategies and policy implications
At the population level, public health initiatives aimed at reducing behavioral risk factors, such as promoting physical activity, healthy diet, sleep hygiene, and stress reduction, can mitigate the burden of metabolic and psychiatric diseases. Policies targeting socioeconomic factors, access to preventive healthcare, and early screening programs are essential to address disparities in risk factor exposure and disease outcomes16,17.
Technological innovations and digital health
Digital health tools, including wearable devices, mobile applications, and telemedicine platforms, offer opportunities for real-time monitoring, behavioral modification, and remote management of metabolic and psychiatric risk factors. Integration of digital health data with clinical and laboratory metrics can enable dynamic risk assessment and early intervention, supporting precision public health approaches2,9.
Future research must adopt multidimensional, integrative approaches that account for the reciprocal interplay between behavioral, metabolic, and psychiatric factors. Behavioral risk factors—including diet, physical activity, sleep, and substance use—are closely associated with altered metabolic profiles in clinical populations, shaping the risk and progression of multiple chronic diseases. Longitudinal, mechanistic, and intervention-based studies are essential to generate actionable evidence for both clinical practice and public health. By integrating personalized medicine with population-level strategies, it may be possible to reduce the burden of metabolic and psychiatric disorders, improve patient outcomes, and inform health policy initiatives. These interactions are complex, frequently bidirectional, and modulated by demographic, biological, and psychosocial factors. Comprehensive lifestyle interventions that simultaneously target these behaviors may therefore provide substantial benefits in mitigating metabolic dysfunction and its associated disease burden.
| Behavioral Risk Factor | Metabolic Alteration | Clinical Outcome | Key References |
| Unhealthy diet | Elevated fasting glucose, dyslipidemia, systemic inflammation | Cardiovascular disease, increased mortality, metabolic syndrome | 3,12,16 |
| Physical inactivity | Insulin resistance, adverse lipid profiles, increased visceral adiposity | Metabolic syndrome, cardiovascular disease | 4,10 |
| Sleep disturbance | Chronic inflammation, impaired glucose metabolism, metabolic syndrome components | Cardiovascular disease, psychiatric comorbidity | 3,10 |
| Smoking | Increased cardiometabolic risk, endothelial dysfunction, dyslipidemia | Cardiovascular disease | 9 |
| Obesity | Metabolic syndrome components, metabolic dysfunction-associated steatotic liver disease, increased colorectal cancer risk | Cardiovascular disease, type 2 diabetes mellitus, colorectal cancer | 16,19 |
| Insulin resistance | Hyperglycemia, dyslipidemia | Mood disorder severity, metabolic dysfunction-associated steatotic liver disease | 1,7,16 |
| Psychosocial stress | HPA-axis activation, elevated cortisol, systemic inflammation | Hypertension, cardiovascular disease, psychiatric disorders | 2,10 |
Table 1: Behavioral risk factors and associated metabolic outcomes.
The authors have no conflicts of interest to declare.