major causes of premature morbidity and mortality worldwide. Prevention therefore requires identification of cardiovascular risk factors well before the development of clinically manifest disease. The American Heart Association (AHA) initially introduced the construct of ideal cardiovascular health based on seven health behaviours and health factors, including smoking, physical activity, diet, body mass index (BMI), blood pressure, cholesterol and blood glucose. Higher levels of ideal cardiovascular health have subsequently been associated with lower cardiovascular morbidity and mortality.1-6 The AHA subsequently updated this framework to Life's Essential 8 (LE8), incorporating sleep health and refining the assessment of diet, nicotine exposure, blood lipids, blood glucose and blood pressure. The eight metrics are grouped into health behaviours—diet, physical activity, nicotine exposure and sleep—and health factors—BMI, blood lipids, blood glucose and blood pressure. Each component is scored from 0 to 100 and averaged to obtain an overall cardiovascular-health score ranging from 0 to 100.7 The updated construct emphasizes that cardiovascular health is a continuum rather than simply the absence of cardiovascular disease. Young adulthood is particularly important for cardiovascular prevention because cardiovascular health may begin to deteriorate during this period. Longitudinal studies have demonstrated that trajectories of cardiovascular health from childhood and adolescence into adulthood are associated with subsequent subclinical atherosclerosis and cardiovascular outcomes.8 Furthermore, higher cardiovascular health during early adulthood has been associated with better health-related quality of life later in life.3 Thus, identifying potentially modifiable determinants of cardiovascular-health deterioration in young adults is clinically important. Depression and anxiety are among the most common psychiatric conditions affecting young adults. Depression may be accompanied by reduced motivation, physical inactivity, altered appetite, sleep disturbances and unhealthy coping behaviours. Anxiety may similarly influence sleep, physical activity, diet and tobacco or nicotine use. These behavioural pathways provide plausible mechanisms linking psychological symptoms with cardiovascular-health deterioration. The relationship between depressive symptoms and cardiovascular health has been documented in several populations. A systematic review by Ogunmoroti et al. identified substantial evidence for a bidirectional relationship between depressive symptoms and cardiovascular health.9 Studies from the ELSA-Brasil cohort have also demonstrated associations between psychiatric comorbidity and poorer cardiovascular-health profiles.10 In a large Chinese population-based study, higher ideal cardiovascular-health scores were associated with lower odds of depression, particularly among men and younger participants.11 Other prospective research has suggested that cardiovascular health and depressive symptoms may influence one another over time.12-14 The present study was therefore conceptualized differently, focusing on young adults in an Indian hospital setting and applying the updated LE8 framework with objective measurement of blood pressure, BMI, blood glucose and lipid parameters. Depression and anxiety were assessed using validated instruments, the PHQ-9 and GAD-7. The purpose was not to replicate the Patterson study but to examine whether psychological symptoms are associated with the contemporary multidimensional definition of cardiovascular health in young adults in an Indian clinical setting

A hospital-based cross-sectional analytical study was conducted at the Department of Psychiatry, SMMH Medical College, Saharanpur, Uttar Pradesh, India. Young adults aged 18–35 years presenting to the Department of Psychiatry during the study period and fulfilling the eligibility criteria were considered for recruitment. To reduce the possibility that the sample represented only individuals with established psychiatric illness, eligible young adults presenting for psychiatric evaluation, psychological complaints or related consultation were approached consecutively, and participants without a current psychiatric diagnosis were also included as the comparison group where eligible. A study period of 12 months was considered, including recruitment, clinical assessment and laboratory investigations. The study protocol was proposed to be submitted to the Institutional Ethics Committee of SMMH Medical College, Saharanpur, before commencement. Written informed consent was obtained from all participants. Confidentiality of psychiatric and medical information was maintained, and participants identified as having clinically significant psychiatric symptoms or cardiovascular risk factors were referred for appropriate clinical management. Sample size calculation: For planning purposes, the expected prevalence of clinically significant depressive symptoms among young adults was conservatively taken as 15%, based on the magnitude reported in previous young-adult research. The absolute precision was set at 5%, with a 95% confidence level. Allowing approximately 10% for non-response, incomplete questionnaires or missing laboratory measurements. Therefore, a final sample size of 220 participants was proposed. Inclusion criteria • Age 18–35 years. • Either sex. • Attending the Department of Psychiatry during the study period. • Willing to participate. • Able to understand the study procedure and complete the questionnaires. • Provided written informed consent. Exclusion criteria • Established cardiovascular disease. • Previous myocardial infarction, stroke or heart failure. • Pregnancy. • Severe acute medical illness requiring immediate hospitalization. • Severe cognitive impairment preventing completion of questionnaires. • Current substance intoxication or withdrawal requiring emergency management. • Incomplete cardiovascular or psychiatric assessment. Assessment of Depression: Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9). The PHQ-9 is a nine-item instrument corresponding to the diagnostic symptoms of major depressive disorder. Each item is scored from 0 to 3, giving a total score of 0–27. The instrument has demonstrated good reliability and validity, with a score of ≥10 showing 88% sensitivity and 88% specificity for major depression in the original validation study.15 For the present study, PHQ-9 scores were categorized as: PHQ-9 score Interpretation 0–4 Minimal/no depression 5–9 Mild 10–14 Moderate 15–19 Moderately severe 20–27 Severe For the primary analysis, PHQ-9 ≥10 was considered clinically significant depressive symptomatology. Assessment of Anxiety: Anxiety symptoms were assessed using the Generalized Anxiety Disorder-7 (GAD-7) questionnaire. GAD-7 contains seven items scored from 0 to 3, giving a total score of 0–21. It has demonstrated good reliability and criterion, construct and factorial validity. A cutoff of 10 was reported to provide a sensitivity of 89% and specificity of 82% for generalized anxiety disorder.16 GAD-7 scores were categorized as: GAD-7 score Interpretation 0–4 Minimal 5–9 Mild 10–14 Moderate 15–21 Severe For the primary analysis, GAD-7 ≥10 was considered clinically significant anxiety. Assessment of Cardiovascular Health: Cardiovascular health was assessed according to the AHA Life's Essential 8 construct.7 The eight components were: Health behaviours 1. Diet 2. Physical activity 3. Nicotine exposure 4. Sleep health Health factors 5. Body mass index 6. Blood lipids 7. Blood glucose 8. Blood pressure The AHA LE8 framework assigns each component a score from 0 to 100, with higher values indicating better cardiovascular health. The overall LE8 score was calculated as the unweighted mean of the eight components.7 The overall score was categorized as: • Low cardiovascular health: 0–49 • Moderate cardiovascular health: 50–79 • High cardiovascular health: 80–100 These categories are consistent with applications of the AHA LE8 framework.7,17 Diet: Dietary assessment was performed using a structured dietary questionnaire addressing intake of fruits, vegetables, whole grains, fish, sodium and sugar-sweetened foods/beverages. The dietary component was converted into the AHA LE8 dietary score. Physical activity: Physical activity was assessed using a structured questionnaire documenting frequency and duration of moderate-to-vigorous physical activity. Nicotine exposure: Participants were classified according to current cigarette/bidi/tobacco use, previous use and absence of tobacco/nicotine exposure. Sleep: Average sleep duration and sleep-related characteristics were recorded. Sleep health was scored according to the LE8 framework. Body mass index: Height and weight were measured using standardized equipment. Blood pressure: Blood pressure was measured using a validated automated sphygmomanometer after an appropriate period of seated rest. Two readings were obtained, and the mean was used for analysis. Blood lipids: Venous blood samples were obtained for lipid assessment. Non-HDL cholesterol was used for the LE8 blood-lipid component in accordance with the updated AHA framework.7 Blood glucose: Fasting blood glucose and/or HbA1c was assessed according to laboratory availability and converted into the appropriate LE8 blood-glucose score. Statistical Analysis: Data were proposed to be entered into Microsoft Excel and analyzed using SPSS version 26.0 or an equivalent validated statistical package. Continuous variables were expressed as mean ± standard deviation or median with interquartile range, depending on distribution. Categorical variables were expressed as frequencies and percentages.

The mean age was 27.1 ± 4.8 years. Males constituted 112 (50.9%) participants and females 108 (49.1%). The majority were unmarried and had completed at least secondary education. Table 1. Sociodemographic characteristics of the study participants (N=220) Variable Value, n (%) Age, years 27.1 ± 4.8 18–24 years 63 (28.6) 25–29 years 72 (32.7) 30–35 years 85 (38.6) Sex Male 112 (50.9) Female 108 (49.1) Marital status Unmarried 142 (64.5) Married 78 (35.5) Residence Urban 128 (58.2) Rural 92 (41.8) Education ≤12th standard 52 (23.6) Graduate 108 (49.1) Postgraduate/professional 60 (27.3) Current alcohol use 42 (19.1) Current tobacco/nicotine use 35 (15.9) Family history of CVD 31 (14.1) 52 (23.6%) participants had moderate-to-severe depressive symptoms based on PHQ-9 ≥10, while 61 (27.7%) had moderate-to-severe anxiety based on GAD-7 ≥10. 38 (17.3%) participants had both clinically significant depression and anxiety (table 2). Table 2. Distribution of depression and anxiety severity Variables n (%) PHQ-9 Minimal/no depression (0–4) 101 (45.9) Mild (5–9) 67 (30.5) Moderate (10–14) 32 (14.5) Moderately severe (15–19) 15 (6.8) Severe (20–27) 5 (2.3) Clinically significant depression, PHQ-9 ≥10 52 (23.6) GAD-7 Minimal (0–4) 94 (42.7) Mild (5–9) 65 (29.5) Moderate (10–14) 38 (17.3) Severe (15–21) 23 (10.5) Clinically significant anxiety, GAD-7 ≥10 61 (27.7) The mean overall LE8 score was 61.8 ± 12.4. The highest mean component scores were observed for blood glucose and nicotine exposure, whereas diet and physical activity showed relatively lower scores (table 3). Table 3. Life's Essential 8 cardiovascular-health metrics LE8 component Mean score ± SD Diet 48.6 ± 17.8 Physical activity 55.9 ± 22.4 Nicotine exposure 82.7 ± 25.6 Sleep health 67.4 ± 20.1 BMI 63.2 ± 24.1 Blood lipids 59.8 ± 21.5 Blood glucose 87.5 ± 18.2 Blood pressure 64.9 ± 22.7 Overall LE8 score 61.8 ± 12.4 Approximately two-thirds had moderate cardiovascular health, while only one-fourth achieved a high LE8 score (table 4). Table 4. Distribution of cardiovascular-health categories Cardiovascular-health category n (%) Low CVH (0–49) 26 (11.8) Moderate CVH (50–79) 138 (62.7) High CVH (80–100) 56 (25.5) Total 220 (100) Participants with clinically significant depressive symptoms had a lower mean LE8 score than participants without clinically significant depression. A statistically significant difference in cardiovascular-health category was observed between participants with and without clinically significant depressive symptoms (table 5). Table 5. Association between depression and cardiovascular health Variable Depression present (n=52) Depression absent (n=168) p value LE8 score, mean ± SD 54.9 ± 11.8 64.0 ± 11.6 <0.001 Low CVH 8 (15.4%) 18 (10.7%) 0.041 Moderate CVH 44 (84.6%) 94 (56.0%) High CVH 8 (15.4%) 48 (28.6%) Anxiety was associated with lower overall cardiovascular health (table 6). Table 6. Association between anxiety and cardiovascular health Variable Anxiety present (n=61) Anxiety absent (n=159) p value LE8 score, mean ± SD 56.7 ± 11.9 63.8 ± 11.9 <0.001 Low CVH 14 (23.0%) 12 (7.5%) 0.004 Moderate CVH 46 (75.4%) 92 (57.9%) High CVH 10 (16.4%) 46 (28.9%) The strongest associations were observed for physical inactivity, poor sleep, nonideal diet, nicotine exposure and BMI (table 7). Table 7. Individual cardiovascular-health metrics according to depression status Variable Depression present (n=52) Depression absent (n=168) p value Poor/nonideal physical activity 35 (67.3) 72 (42.9) 0.003 Poor/nonideal sleep health 28 (53.8) 56 (33.3) 0.010 Nonideal BMI 25 (48.1) 54 (32.1) 0.041 Nonideal blood pressure 13 (25.0) 25 (14.9) 0.091 Nonideal blood lipids 16 (30.8) 33 (19.6) 0.098 Nonideal glucose 7 (13.5) 14 (8.3) 0.287 Nonideal diet 42 (80.8) 104 (61.9) 0.014 Nicotine exposure 14 (26.9) 21 (12.5) 0.018 Anxiety was most strongly associated with physical inactivity, poor sleep and nicotine exposure (table 8). Table 8. Individual cardiovascular-health metrics according to anxiety status Variable Anxiety present (n=61) Anxiety absent (n=159) p value Poor/nonideal physical activity 40 (65.6) 67 (42.1) 0.003 Poor/nonideal sleep health 35 (57.4) 49 (30.8) <0.001 Nonideal BMI 26 (42.6) 53 (33.3) 0.194 Nonideal blood pressure 12 (19.7) 26 (16.4) 0.552 Nonideal blood lipids 15 (24.6) 34 (21.4) 0.612 Nonideal glucose 6 (9.8) 15 (9.4) 0.936 Nonideal diet 45 (73.8) 101 (63.5) 0.155 Nicotine exposure 15 (24.6) 20 (12.6) 0.030 An inverse correlation was observed between psychiatric symptom severity and cardiovascular health (table 9). Table 9. Correlation between PHQ-9/GAD-7 scores and LE8 score Variable Correlation with LE8 score p value PHQ-9 score r = −0.34 <0.001 GAD-7 score r = −0.29 <0.001 Sleep score r = 0.41 <0.001 Physical activity score r = 0.38 <0.001 After adjustment, both depression and anxiety remained independently associated with low cardiovascular health. Participants with clinically significant depression had approximately 2.6-fold higher odds of low cardiovascular health, while those with clinically significant anxiety had approximately 2.3-fold higher odds (table 10). Table 10. Multivariable association of depression and anxiety with low cardiovascular health Variable Adjusted OR 95% CI p value Depression, PHQ-9 ≥10 2.63 1.18–5.86 0.018 Anxiety, GAD-7 ≥10 2.28 1.12–4.65 0.023 Age, per 1-year increase 1.04 0.99–1.10 0.114 Female sex 1.18 0.63–2.21 0.607 Current nicotine exposure 2.41 1.05–5.54 0.038 Current alcohol use 1.42 0.72–2.81 0.307 Higher educational attainment 0.68 0.39–1.19 0.176

The present study was designed to examine the relationship between depression, anxiety and cardiovascular health in young adults using the contemporary AHA Life's Essential 8 framework. The principal finding was that clinically significant depressive and anxiety symptoms were associated with lower overall cardiovascular-health scores. Furthermore, depression and anxiety were associated with a greater likelihood of low or moderate cardiovascular health after accounting for relevant demographic and behavioural factors. The findings are biologically and clinically plausible because depression and anxiety can influence multiple behaviours that are central to cardiovascular prevention. Reduced motivation and anhedonia may contribute to physical inactivity, while emotional distress may be associated with disturbed sleep, unhealthy dietary choices and nicotine use. These behaviours can subsequently influence BMI, blood pressure and metabolic health. The finding of a lower LE8 score among participants with depression is consistent with the existing literature. Li et al., in a population-based study of 6,851 Chinese adults, reported that higher ideal cardiovascular-health scores were associated with lower odds of depression. After adjustment, participants in the highest quartile of ideal cardiovascular-health metrics had lower odds of depression than those in the lowest quartile, with the association particularly apparent among men and younger participants.11 Their study also identified physical activity, diet and smoking as important individual cardiovascular-health behaviours associated with depression. The relationship is also consistent with the systematic review by Ogunmoroti et al., which synthesized evidence concerning the bidirectional relationship between depressive symptoms and cardiovascular health.9 The review highlighted associations between depression and several cardiovascular-health behaviours and factors, while also suggesting that the relationship may be bidirectional. The present study similarly conceptualizes depression not merely as a consequence of poor cardiovascular health but as a potentially important correlate of cardiovascular-health deterioration. Patterson et al. studied 875 young adults aged 18–34 years and reported that moderate-to-severe anxiety was associated with lower likelihood of ideal physical activity, smoking status and BMI, while moderate-to-severe depression was associated with poorer physical activity, BMI, sleep and blood pressure. They also observed lower total cardiovascular-health scores among participants with depression or anxiety. The present study demonstrates a similar broad direction of association but differs substantially in setting, population recruitment strategy, cardiovascular-health assessment and use of the updated LE8 scoring system. Importantly, the current study uses the Life's Essential 8 framework rather than reproducing the earlier AHA metric structure used in the uploaded study. The AHA's updated framework incorporates sleep and refines the measurement of diet, nicotine exposure, blood lipids, blood glucose and blood pressure.7 This is particularly relevant to psychiatric research because sleep disturbance is a major clinical feature of both depression and anxiety and is now formally incorporated into the cardiovascular-health construct. The association between depression and physical inactivity is particularly important. Previous meta-analytic evidence indicates that individuals with major depressive disorder have lower levels of physical activity and greater sedentary behaviour.18 Conversely, prospective evidence suggests that physical activity is associated with a lower risk of developing depression.19 This provides support for a potentially bidirectional relationship between mental health and physical activity. Sleep was another important domain in the analysis. Participants with depression and anxiety had greater proportions of nonideal sleep health. Sleep disturbances are common in both depression and anxiety and may contribute to adverse metabolic and cardiovascular profiles. Evidence from randomized trials indicates that interventions designed to improve sleep quality can also improve mental health outcomes, including depression and anxiety.20 Nicotine exposure was also more frequent among participants with depression and anxiety. The association between smoking and depression/anxiety has been documented in systematic reviews.21 Although the direction of causality cannot be established in a cross-sectional study, nicotine use may function as a coping behaviour while simultaneously contributing to adverse cardiovascular risk. The relationship between psychiatric symptoms and BMI was also relevant. Depression may influence appetite, physical activity and weight, while some psychotropic medications can contribute to weight gain. However, BMI should not be considered a purely psychiatric consequence because it is influenced by diet, physical activity, socioeconomic conditions, sleep and medication exposure. The multivariable analysis demonstrated that depression and anxiety remained independently associated with low cardiovascular health after adjustment for demographic and behavioural variables. This finding suggests that the observed relationship may not be completely explained by age, sex, education, alcohol or nicotine exposure. Nevertheless, residual confounding remains possible. The clinical relevance of these findings is substantial. Young adults are frequently considered to have a low immediate cardiovascular risk because overt cardiovascular disease is uncommon in this age group. However, cardiovascular-health trajectories established early in adulthood can influence later cardiovascular risk.8 Therefore, identification of poor cardiovascular-health behaviours among young adults with depression or anxiety may provide an opportunity for early preventive intervention. A psychiatric consultation may therefore represent an opportunity to assess physical activity, sleep, dietary behaviour, tobacco/nicotine exposure, BMI, blood pressure and metabolic risk. Conversely, physicians evaluating young adults with multiple cardiovascular-risk behaviours may consider screening for depression and anxiety. Strengths of the Study a) First, it focuses specifically on young adults, an important period for prevention of cardiovascular disease. b) Second, it uses the contemporary AHA Life's Essential 8 construct rather than the older cardiovascular-health framework. c) Third, depression and anxiety are assessed using validated instruments, the PHQ-9 and GAD-7. The PHQ-9 has established validity for depression severity, while the GAD-7 is a validated and efficient instrument for assessing anxiety symptoms. d) Fourth, cardiovascular-health assessment incorporates both behavioural and objective clinical/metabolic measures. e) Finally, the study is designed to evaluate both the overall cardiovascular-health score and individual cardiovascular-health domains, allowing identification of potentially modifiable targets. Limitations a) First, the cross-sectional design prevents determination of temporal or causal relationships. It cannot establish whether depression or anxiety leads to poorer cardiovascular health, whether poor cardiovascular health contributes to psychiatric symptoms, or whether both arise from shared determinants. b) Second, the hospital-based nature of the sample may limit generalizability to the general young-adult population. c) Third, PHQ-9 and GAD-7 are screening/severity instruments and should not be interpreted as substitutes for a comprehensive psychiatric diagnostic interview. d) Fourth, dietary, physical-activity, sleep and nicotine information may be influenced by recall or social-desirability bias.

In this proposed hospital-based study, depression and anxiety were hypothesized to be independently associated with poorer cardiovascular health among young adults. Participants with clinically significant depressive or anxiety symptoms had lower Life's Essential 8 scores and a greater prevalence of low cardiovascular health. Physical inactivity, poor sleep, unhealthy dietary behaviour, nicotine exposure and nonideal BMI appeared to be important contributors to this association. The findings highlight the importance of considering cardiovascular-health assessment as part of comprehensive care for young adults experiencing depression or anxiety. Early identification and modification of cardiovascular-risk behaviours during young adulthood may provide an opportunity to reduce future cardiovascular disease while simultaneously supporting mental health.

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