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Your Mood Is a Metabolic Signal You’re Not Tracking

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dr. Karunia Valeriani Japar

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When Mood Mirrors Metabolism

Metabolic dysfunction and emotional instability are emerging as parallel epidemics in contemporary societies, driven by converging shifts in diet, sleep, physical activity, and psychosocial stress. Individuals increasingly present with overlapping constellations of symptoms such as fatigue, impaired concentration, irritability, and mood lability alongside central adiposity, impaired glucose tolerance, and dyslipidemia, yet these are often compartmentalized into separate “mental” and “physical” diagnoses. This reductionist separation obscures a central reality: emotional states are tightly coupled to metabolic signalling, and disturbances in energy homeostasis frequently manifest first as changes in mood, motivation, and stress tolerance rather than overt organ failure. Framing unstable emotion as a potential clinical expression of unhealthy metabolism may therefore enable earlier detection of cardiometabolic risk and more integrated preventative strategies.

Blood glucose dynamics, systemic inflammation, and hormone balance constitute three major biological interfaces between metabolism and emotion. Rapid postprandial glucose excursions and subsequent reactive declines can acutely influence arousal, irritability and cognitive clarity through shifts in cerebral energy availability and counter-regulatory hormone responses. Chronic hyperglycemia and insulin resistance further alter central neurotransmission and neuroplasticity, contributing to increased vulnerability to depression and anxiety. In parallel, low-grade systemic inflammation associated with visceral adiposity and metabolic syndrome can cross the blood-brain barrier, modulate monoaminergic pathways, and promote “sickness behaviour”  phenotypes characterized by anhedonia, withdrawal, and emotional reactivity. Dysregulation of key hormones, including cortisol, insulin, leptin, ghrelin, and thyroid hormones integrates these signals and exerts widespread effects on reward processing, stress responsivity, appetite, and sleep, all of which shape emotional experience.

These converging mechanisms argue strongly against treating mental and metabolic health as independent domains. Instead, they support a systems-biology perspective in which mood, cognition, and behaviour are emergent properties of an integrated neuroendocrine–immune–metabolic network. In this model, emotional instability is not merely a psychological or social construct but a clinically meaningful indicator of underlying physiological dysregulation. For clinicians, researchers, and health tech innovators, recognizing this bidirectional relationship has several implications: mental health assessments should routinely incorporate metabolic risk evaluation; metabolic interventions should be evaluated not only for cardiometabolic endpoints but also for effects on emotional stability and quality of life; and digital health tools that track both affective and metabolic signals may be uniquely positioned to detect early deviations from homeostasis. Although specific empirical references cannot be provided in this context due to current access limitations, the conceptual synthesis presented here aligns with a growing body of literature linking glycemic control, inflammatory status, and hormonal milieu to mood and stress-related disorder.

The Brain-Body Axis of Emotion and Metabolism

The regulation of emotion and metabolism emerges from a highly integrated brain–body network in which neuroendocrine, autonomic, and immune pathways continuously exchange information. The hypothalamic–pituitary–adrenal (HPA) axis and autonomic nervous system form core components of this stress and energy-regulation interface. In response to real or anticipated threat, corticotropin-releasing hormone released from the hypothalamus stimulates pituitary adrenocorticotropic hormone secretion, driving adrenal glucocorticoid output, particularly cortisol in humans. Under acute conditions, this response is adaptive, mobilizing glucose, modulating cardiovascular output, and transiently adjusting immune activity. However, chronic or repeated activation leads to HPA axis dysregulation, impaired negative feedback, and sustained elevations or maladaptive rhythms of cortisol that are consistently observed in subgroups of patients with depression and metabolic disease. Parallel shifts in autonomic balance characterized by sympathetic overactivity and reduced parasympathetic (vagal) tone further couple stress exposure to metabolic outcomes, promoting central adiposity, insulin resistance, and low-grade inflammation that feed back into brain circuits regulating mood [1,2,3,4,5].

Figure 1. Vagal Afferents Transmit Signals From Gut Microbiota to The Central Nervous System [3]

Metabolic disturbances such as glycemic variability and insulin resistance exert direct and indirect effects on central neurotransmitter systems, including serotonin, dopamine, glutamate, and GABA. Postprandial hyperglycemia and subsequent rapid glucose declines influence cerebral energy availability and trigger counter-regulatory hormone responses that can acutely alter arousal, irritability, and cognitive performance. Over time, chronic hyperglycemia and insulin resistance modify monoaminergic transmission and receptor sensitivity, contributing to increased vulnerability to depression and anxiety in individuals with type 2 diabetes and metabolic syndrome. Experimental and clinical data indicate that disrupted glucose and energy metabolism alter glutamate–GABA homeostasis, with changes in excitatory–inhibitory balance linked to depressive symptomatology and stress-related disorders. Inflammatory mediators induced by metabolic dysregulation, including interleukin-6 and tumor necrosis factor-α, further impact tryptophan–kynurenine metabolism and monoamine synthesis, thereby shaping serotonergic and dopaminergic tone and influencing mood and stress responsivity [2,5,6,7,8,9,10].

Figure 2. From Peripheral Immune Activation to Central Neuroinflammation in Mood Disorders [9]

Bidirectional communication between the brain and peripheral metabolism is additionally mediated by vagal signalling and cytokine pathways, forming a key component of the brain–gut–immune axis. The vagus nerve provides a major afferent route by which visceral, metabolic, and inflammatory signals reach brainstem and limbic structures, while efferent vagal fibers exert anti-inflammatory effects through the so-called “cholinergic anti-inflammatory reflex.” Reduced vagal tone, often indexed by low heart rate variability, has been observed in individuals with depression and inflammatory bowel and metabolic conditions, suggesting a shared autonomic phenotype linking emotional and metabolic vulnerability. Experimental vagus nerve stimulation can attenuate gut and systemic inflammation and improve depressive symptoms, underscoring the causal relevance of this pathway. In parallel, pro-inflammatory cytokines produced in adipose tissue, gut, and other peripheral sites can cross or signal across the blood–brain barrier, modulating HPA axis activity and neurotransmitter systems and contributing to persistent depressive symptoms in the context of metabolic disease. Together, these data support a model in which the brain–body axis of emotion and metabolism operates through tightly interwoven neuroendocrine, autonomic, and immune mechanisms, making emotional instability a plausible clinical marker of underlying metabolic dysregulation [2,3,5,9,11,13].

How Metabolic Dysregulation Triggers Emotional Instability

Fluctuating glucose represents one of the most immediate and tangible metabolic drivers of emotional variability in daily life. Glycemic excursions particularly rapid postprandial glucose increases followed by steep compensatory declines can produce a characteristic pattern of transient mood disturbance that patients frequently describe but clinicians often overlook. Acute hyperglycemia has been shown experimentally to induce decreased hedonic tone (reduced happiness), decreased energetic arousal (increased tiredness and lethargy), and increased tense arousal (heightened agitation and anxiety), with these mood changes occurring independently of cognitive impairment. Observational studies using continuous glucose monitoring have demonstrated that higher rates of postprandial glucose increase are associated with more negative mood symptoms, and that greater multiday glycemic variability correlates with higher depressive symptom scores and lower positive well-being in individuals with type 1 diabetes. Reactive hypoglycemia, whether absolute or relative to an individual’s habitual glucose range, further amplifies this pattern by triggering counter-regulatory hormone release (epinephrine, cortisol, glucagon) that acutely provoke irritability, anxiety, difficulty concentrating, shakiness, and fatigue. For individuals with prediabetes, metabolic syndrome, or poorly controlled diabetes, this cycle of “metabolic mood swings” can occur multiple times daily, eroding emotional stability and contributing to chronic fatigue, yet the emotional component is frequently attributed to psychological rather than metabolic origins [14,15,16,17,18,19,20].

Mitochondrial dysfunction and oxidative stress constitute deeper, systemic drivers of emotional dysregulation that operate at the cellular and molecular level. Mitochondria are the primary source of neuronal energy and simultaneously generate reactive oxygen species as metabolic byproducts; when mitochondrial respiratory chain efficiency declines or antioxidant defenses are overwhelmed, the resulting oxidative stress can damage lipids, proteins, and nucleic acids within neurons. Preclinical and clinical studies consistently demonstrate that major depressive disorder is associated with impaired mitochondrial respiration, reduced adenosine triphosphate production, altered expression of electron transport chain subunits, and elevated markers of oxidative damage in brain tissue and peripheral blood. Specific genetic variants in mitochondrial DNA have been shown to interact with inflammatory markers such as C-reactive protein to increase risk for anxiety and depression, suggesting an intricate interplay between mitochondrial function and immune activation. Insulin resistance further compounds this problem: experimental models demonstrate that brain-specific insulin receptor deficiency leads to mitochondrial dysfunction, increased monoamine oxidase expression, accelerated dopamine turnover, and the development of anxiety and depressive-like behaviours that can be reversed with monoamine oxidase inhibitors. This mechanistic evidence indicates that mitochondrial and oxidative stress pathways are not merely downstream consequences of mood disorders but active contributors to emotional instability, particularly in the context of metabolic disease [21,22,23,24,25].

Figure 3. Damaging Effects of Oxidative Stress on Cell Structures and Its Relation to Disease Initiation/ Progression, Aging, and Senescence [25]

Chronic low-grade inflammation, increasingly recognized under the term “inflammaging” in the context of aging populations, serves as a critical molecular bridge linking metabolic dysregulation to depression and emotional lability. Individuals with major depressive disorder consistently exhibit elevated circulating levels of pro-inflammatory cytokines, including interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α), alongside C-reactive protein, mirroring the inflammatory profile observed in metabolic syndrome and type 2 diabetes. Meta-analyses confirm that IL-6 is particularly elevated in elderly individuals with depression and that inflammatory marker levels correlate with depressive symptom severity. These cytokines exert direct effects on mood circuitry through multiple pathways: they activate indoleamine 2,3-dioxygenase, which shunts tryptophan metabolism away from serotonin synthesis toward the kynurenine pathway, producing neuroactive metabolites such as quinolinic acid that possess excitotoxic properties and further activate monoamine oxidase. IL-1β and TNF-α acutely increase serotonin transporter activity, reducing synaptic serotonin availability, while IL-6 directly modulates hypothalamic-pituitary-adrenal axis activity and promotes insulin resistance through effects on hepatic and adipose tissue. Aging amplifies this process by rendering microglia hypervigilant and prone to excessive cytokine release when challenged, creating a self-perpetuating loop in which metabolic dysfunction drives inflammation, inflammation impairs neurotransmitter metabolism and insulin signalling, and the resulting emotional instability further disrupts health behaviours and metabolic control [26,27,28,29,30,31,32,33,34,35].

Figure 4. Schematic Overview for The Pathogenesis of Immune-related Diseases Such As Major Depressive Disorder, Bipolar disorder, Cardiovascular Diseases, Acute Kidney Injury, Chronic Kidney Disease, Inflammatory Bowel Disease, Osteoporosis, and Polycystic Ovary Syndrome [32]

The Emotional Consequences of Modern Lifestyles

Modern lifestyles create a convergence of behavioural stressors that simultaneously disturb metabolic regulation and emotional stability. Sleep deprivation is now endemic and strongly associated with insulin resistance, impaired glucose tolerance, elevated evening cortisol, increased sympathetic tone, and higher levels of proinflammatory cytokines, all of which are known drivers of mood disturbance and fatigue. Experimental sleep restriction in healthy adults decreases insulin sensitivity and worsens fasting and postprandial glucose, while also increasing subjective sleepiness and negative mood. In people with type 2 diabetes, insomnia severity correlates with poorer carbohydrate control and higher anxiety and depression scores, illustrating how impaired sleep quality simultaneously worsens metabolic and psychological outcomes. Diets dominated by ultra-processed foods (UPFs) further amplify this vulnerability: systematic reviews show that high UPF intake is consistently associated with a 20–50% higher risk of developing depressive symptoms, alongside increased risk of obesity, metabolic syndrome, and type 2 diabetes. Mechanistically, UPFs promote glycemic volatility, excess fructose and saturated fat intake, nutrient displacement, gut dysbiosis, and neuroinflammation, which together degrade both metabolic control and emotional resilience. Digital overstimulation through late-night screen use, social media, and constant notifications adds a chronic cognitive and emotional load that fragments attention, increases perceived stress, and delays sleep onset, thereby worsening both circadian alignment and recovery processes [36,37,38,39,40,41,42,43].

Circadian disruption represents a central pathway through which modern behaviours exert combined metabolic and emotional effects. The suprachiasmatic nucleus and peripheral clocks orchestrate daily rhythms in cortisol, melatonin, insulin sensitivity, and appetite-regulating hormones, aligning energy metabolism with the light–dark cycle and feeding–fasting patterns. Shift work, irregular sleep–wake schedules, jet lag, and nocturnal light exposure alter the timing and amplitude of cortisol rhythms, often increasing evening cortisol, which is associated with adiposity, metabolic syndrome, and mood disturbances. Experimental circadian misalignment in humans impairs glucose tolerance and elevates insulin and blood pressure, while chronic misalignment has been linked to increased obesity and structural changes in temporal lobe regions implicated in emotional regulation. Melatonin suppression by evening light disrupts normal nocturnal signalling to pancreatic islets and other metabolic tissues, modifying insulin and glucagon secretion patterns and uncoupling central and peripheral clocks. These hormonal and autonomic changes not only predispose to insulin resistance and dyslipidemia but also disturb sleep architecture and neurotransmitter dynamics, manifesting clinically as irritability, mood swings, and heightened stress sensitivity [38,41,42,44].

Within this context, emotional stress becomes both a consequence and a driver of metabolic dysregulation, creating a self-reinforcing feedback loop. Acute and chronic psychosocial stress activate the hypothalamic–pituitary–adrenal axis and sympathetic nervous system, increasing cortisol and catecholamines, which in turn promote preferential intake of highly palatable, energy-dense foods rich in sugar and fat, commonly referred to as stress or emotional eating. These foods acutely elevate dopamine and endogenous opioids, providing short-term relief but reinforcing reward pathways that favour repetitive overeating of UPFs and late-night snacking. Repeated stress eating increases visceral adiposity, worsens insulin resistance, and elevates oxidative stress and inflammatory markers, deepening metabolic vulnerability and further impairing mood regulation. Poor metabolic status then feeds back to degrade sleep quality, increase insomnia, and exacerbate anxiety and depressive symptoms, as demonstrated in patients with type 2 diabetes where insomnia is directly associated with both worse glycemic control and higher psychological symptom burden. Inadequate recovery through curtailed sleep, absence of restorative physical activity, and persistent digital engagement prevents normalization of HPA axis and autonomic tone, locking individuals into a cycle in which emotional distress drives behaviours that sabotage metabolic health, while deteriorating metabolism, in turn, amplifies emotional instability [36,39,41,42,43,44,45].

Emotional Stability as a Marker of Metabolic Flexibility

Emotional stability can be viewed as a patient-friendly marker of underlying metabolic flexibility, particularly when assessed alongside continuous glucose monitoring (CGM) data. In a metabolically flexible state, the body switches efficiently between carbohydrate and fat as fuel, so daily stressors, meals, and activity cause only modest shifts in glucose and hormones, which supports more stable mood and stress resilience. When this flexibility is impaired, as in insulin resistance or type 2 diabetes, postprandial spikes and rapid declines in glucose become more frequent, increasing vulnerability to fatigue, irritability, and “metabolic mood swings [46,47,48,49,50].

CGM provides a practical window into this link between mood and metabolism by capturing real-time glucose dynamics across the day. Systematic reviews in adults with diabetes show that greater glucose variability and faster postprandial glucose rise are often associated with more negative mood states, while smoother glycemic profiles tend to coincide with more stable affect. In applied settings, individuals frequently report that reducing large spikes and dips, through meal composition, timing, and activity correlates with fewer crashes, less irritability, and improved emotional predictability, making CGM a powerful tool to operationalize emotional stability as an observable expression of metabolic flexibility [47].

Interventions to Restore the Metabolic-Emotional Balance

Nutritional Strategies

Dietary interventions targeting glycemic control and systemic inflammation represent foundational approaches to stabilizing both metabolism and mood. Diets with lower glycemic index (GI) and glycemic load (GL) have been associated with reduced risk of depression in large observational studies, with high-GI diets experimentally inducing depressive symptoms in healthy volunteers through mechanisms involving glucose volatility and insulin surges. Conversely, higher dietary insulin index and load in some populations correlate with increased risk of sleep disorders, though effects on depression and anxiety remain inconsistent across studies. Chrononutrition, aligning meal timing with circadian rhythms further supports mental health: irregular eating patterns and late-night meals disrupt circadian alignment and contribute to mood dysregulation, while regular meal timing enhances mood stability and reduces anxiety. Time-restricted eating (TRE), which limits daily food intake to a 4- to 10-hour window, improves cardiometabolic parameters without adverse effects on sleep, mood, or quality of life in adults with overweight or obesity, regardless of whether the eating window is early or late in the day. Polyphenols, bioactive compounds abundant in fruits, vegetables, tea, and cocoa possess anti-inflammatory and antioxidant properties that counteract oxidative stress and neuroinflammation implicated in depression and anxiety. Meta-analyses demonstrate that polyphenol supplementation significantly improves depression scores, with effects mediated through increased plasma antioxidant capacity, modulation of monoamine oxidase activity, and promotion of adult hippocampal neurogenesis. Together, these nutritional strategies offer evidence-based pathways to reduce glycemic variability, dampen inflammation, and support neurotransmitter homeostasis, thereby stabilizing both metabolic control and emotional resilience [51,52,53,54,55,56,57,58].

Lifestyle Interventions

Mind–body practices and structured physical activity directly modulate neuroendocrine stress pathways and autonomic balance, providing powerful non-pharmacological tools for emotional and metabolic regulation. Mindfulness meditation has been shown to attenuate HPA axis reactivity: short-term interventions (seven 20-minute sessions) produce lower cortisol responses and higher testosterone levels following acute psychosocial stress compared to relaxation controls, suggesting improved homeostatic regulation via co-modulation of the HPA and hypothalamic-pituitary-testicular axes. Mindfulness-based interventions also reduce chronic stress, perceived stress, and pregnancy-related stress through reduced HPA axis activation, with effects confirmed across multiple randomized controlled trials. Yoga practice offers complementary benefits by normalizing HPA axis function, reducing cortisol levels, and increasing gamma-aminobutyric acid (GABA) concentrations, a neurotransmitter often deficient in mood disorders, thereby improving depression and anxiety symptoms while enhancing stress resilience. Mechanistically, yoga combines breath regulation, physical postures, and meditative focus to modulate both sympathetic and parasympathetic branches of the autonomic nervous system, improving vagal tone and reducing inflammatory cytokine expression. Regular aerobic and resistance exercise similarly acts as an HPA axis modulator, improving insulin sensitivity, mitochondrial function, and brain-derived neurotrophic factor (BDNF) expression, all of which support emotional stability and cognitive function. These lifestyle interventions are accessible, scalable, and capable of addressing both metabolic inflexibility and emotional dysregulation through shared neuroendocrine mechanisms [59,60,61].

Digital Health Tools

Advances in wearable biosensors and artificial intelligence enable continuous, real-time monitoring of metabolic and autonomic signals, creating personalized feedback loops that support behavioural change and emotional self-awareness. Continuous glucose monitoring (CGM) has emerged as a practical tool for revealing the connection between dietary choices, glycemic excursions, and mood fluctuations: systematic reviews show that higher postprandial glucose rise rates and greater multiday glucose variability are associated with more negative mood symptoms and lower positive well-being in individuals with diabetes. By making these invisible metabolic patterns visible, CGM empowers individuals to adjust meal composition, timing, and activity in ways that reduce glycemic volatility and stabilize mood, transforming abstract nutritional advice into concrete, personalized strategies. Heart rate variability (HRV) biofeedback represents another accessible digital intervention: controlled trials demonstrate that HRV-guided breathing exercises reduce mental health symptoms, perceived stress, and chronic stress biomarkers while increasing parasympathetic tone (reflected in higher SDNN, LF, and LF/HF ratio). Reduced HRV is consistently linked with insulin resistance and mood disorders, whereas higher HRV correlates with better emotional regulation and stress resilience, making HRV a valuable real-time marker of autonomic balance. Emerging AI-driven platforms integrate multiple data streams, such as CGM, HRV, sleep architecture, physical activity, and ecological momentary mood assessments to identify individual-specific patterns and deliver just-in-time adaptive interventions, such as prompts for breathwork, movement, or meal adjustments before emotional instability manifests. These digital tools collectively operationalize metabolic literacy, enabling individuals to see and regulate the metabolic foundations of their emotional experience in daily life [20,62,63,64].

Clinical and Workplace Implications

Emotional instability at work undermines attention, judgment, and reliability, and is associated with higher error rates, reduced productivity, and increased absenteeism, making it a major organizational and economic burden. Because mood symptoms often co-occur with metabolic risk, relying only on psychological screening misses an opportunity for earlier, more systemic intervention [65,66,67,68,69,70].

Workplace metabolic screening, covering fasting glucose, HbA1c, blood pressure, and adiposity embedded within broader wellness programs has been shown to uncover undiagnosed diabetes and prediabetes and to improve glycemic and weight outcomes over time. Integrating this with mental health initiatives allows identification of employees at dual risk and supports preventive interventions that simultaneously target metabolic and emotional drivers of burnout and poor performance [70,71,72,73].

Organizations that redesign work conditions (sleep- and recovery-friendly schedules, healthier food environments, opportunities for movement) and provide structured metabolic and mental health support can foster teams that are both emotionally resilient and metabolically healthier, which translates into better engagement, decision quality, and long-term performance [70,71].

Future Directions and Digital Health Integration

Future directions in this field center on integrating artificial intelligence with multimodal biosensing to map the dynamic relationship between mood and metabolism at the individual level. Machine learning models already use continuous glucose monitoring (CGM), heart rate, activity, and HRV data to recognize glycemic patterns, predict future glucose excursions, and define metabolic subphenotypes, providing a natural foundation for adding mood signals and building mood–metabolism prediction models. At the biomarker level, glucose variability, inflammatory signatures, and HRV are emerging as key indicators of emotional–metabolic resilience, with reduced HRV and higher inflammatory markers linked to both cardiometabolic risk and depressive symptoms. Personalized prevention programs can then combine these physiological markers with digital phenotyping of diet, activity, sleep, and self-reported affect to deliver tailored lifestyle, nutrition, and stress-management interventions that are continuously adapted based on real-time metabolic and emotional data [72,73,74,75,76,77,78,79,80,81].

A Unified Model of Emotional and Metabolic Health

Emotional stability can be conceptualized as an emergent property of a metabolically coherent system rather than a purely psychological attribute. In this integrated view, stable mood, sustained attention, and resilient stress responses arise when glucose dynamics are relatively smooth, mitochondrial function is efficient, oxidative stress is contained, and inflammatory signalling is appropriately regulated. Conversely, recurrent mood swings, irritability, and emotional exhaustion often signal underlying disturbances in glycemic control, insulin signalling, mitochondrial energetics, and low-grade inflammation. Although precise mechanistic and clinical details require direct reference to primary literature, converging evidence from endocrinology, psychiatry, and neuroimmunology supports the proposition that emotional instability frequently reflects metabolic disharmony rather than isolated “mental” pathology. This framing invites clinicians to interpret mood symptoms as potential biomarkers of systemic metabolic stress and to integrate emotional assessment into cardiometabolic risk evaluation.

Adopting a unified model of emotional and metabolic health implies a shift from a narrow, symptom-focused paradigm toward a form of integrated health intelligence that continuously synthesizes biological, psychological, and behavioural data. Rather than managing depression, anxiety, and burnout as discrete entities, healthcare systems can leverage longitudinal information on glycemic variability, inflammatory markers, autonomic balance, sleep patterns, and subjective affect to detect early deviations from homeostasis and to tailor interventions accordingly. In this paradigm, algorithms and clinical decision-support tools do not treat “mental” and “metabolic” outcomes separately but recognize shared upstream drivers and feedback loops. Such an approach aligns with emerging evidence that insulin resistance, mitochondrial dysfunction, and inflammaging simultaneously increase risk for both metabolic and mood disorders, and that interventions targeting these pathways can improve both cardiometabolic and emotional endpoints.

At the individual level, this model emphasizes metabolic literacy as a foundational skill for emotional self-regulation. Helping people understand how meal composition, eating timing, sleep quality, physical activity, light exposure, and stress responses shape glucose excursions, hormonal rhythms, and inflammatory tone allows them to interpret their own emotional fluctuations through a physiological lens. When individuals can see, for example, that a sequence of large postprandial glucose spikes is consistently followed by irritability and fatigue, or that improved sleep and reduced evening light exposure stabilize both nocturnal heart rate variability and next-day mood, behaviour change becomes more concrete and self-reinforcing. Digital tools that integrate subjective mood tracking with metabolic and autonomic signals can further personalize this learning process, transforming abstract health advice into real-time feedback loops. In this way, emotional regulation becomes not only a function of psychological strategies but also a daily practice of maintaining metabolic harmony, with implications for prevention, treatment, and healthy longevity.

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