Autonomic function characteristics and stratification analysis of adolescent patients with depressive disorders based on the low-frequency:high-frequency ratio

Abstract

BACKGROUND

Autonomic nervous system imbalance can mediate an individual’s physiological response to psychological stress and play a role in the progression of depression; conversely, social factors such as academic stress and family environment may serve as key external risk factors for adolescent depression. To investigate the symptoms and autonomic nervous function characteristics of adolescents with depressive disorders and the correlation with sociologic data.

AIM

To explore the associations of autonomic function and psychosocial factors with adolescent depressive severity and determine the independent predictors.

METHODS

Adolescents with DDs who were treated at Wutaishan Hospital from November 2025 to March 2026 were enrolled and classified into four groups based on depressive symptoms: Normal group (59 cases); mild depression group (87 cases); moderate depression group (78 cases); and severe depression group (45 cases). Autonomic nervous function characteristics were assessed using a heart rate variability monitor, while psychological status was evaluated with the Zung Self-rating Anxiety Scale (SAS) and the Zung Self-rating Depression Scale.

RESULTS

Among the 269 adolescents with DDs, significant statistical differences existed in gender, treatment status, place of residence, payment method, per capita monthly household income, caregivers, family relationships, adverse experiences, body mass index, SAS scores, autonomic nervous function [low-frequency (LF):high-frequency (HF) ratio], and disease duration (all P values < 0.05). The independent risk factors included place of residence [odds ratio (OR) = 2.18], payment method (OR = 4.42), per capita monthly household income (OR = 0.32), presence of caregivers (OR = 3.81), family relationships (OR = 2.12), adverse experiences (OR = 2.81), SAS scores (OR = 4.17), and LF:HF ratio (OR = 1.94) with per capita monthly household income having a protective effect.

CONCLUSION

These findings suggest that clinical practice should integrate the LF:HF ratio with psychosocial factors to achieve early identification, disease stratification, and targeted intervention for adolescent DDs.

Key Words: Adolescents; Depressive disorder; Autonomic nervous function; Stratified analysis

Core Tip: Adolescent depressive disorder (DDs) severity is independently correlated with the low-frequency (LF):high-frequency (HF) ratio (reflecting autonomic nervous imbalance), anxiety symptoms, and various socio-familial factors. Per capita monthly household income is a protective factor. Integrating the LF:HF ratio with psychosocial factors can facilitate early identification, severity stratification, and precise intervention for adolescent DDs.

INTRODUCTION

Adolescence is a critical developmental stage that is characterized by an imbalance between physiological and psychological growth. The asynchronous progression of physical maturation and psychological development, coupled with the sudden emergence of adult role identity conflicts during this period, makes adolescents a high-risk group for mental health issues[1]. Depressive disorders (DDs) among adolescents have increasingly become a prevalent mental health problem globally, exerting a profound negative impact on individual psychological development, physical health, and social functioning[2]. In recent years the annual incidence of DDs among adolescents has shown a continuous upward trend with a notable trend toward onset at an earlier age[3]. The core clinical manifestations of DDs include persistent low mood and a significant diminished interest in learning and daily activities that is often accompanied by various somatic and psychological symptoms[4]. These symptoms not only cause severe physical and psychological distress to patients but also impair social functioning and reduce the quality of life, while imposing substantial caregiving and financial burdens on families. Adolescent DDs are clinically characterized by prolonged duration, early onset, high recurrence rates, and elevated suicide risks, which severely compromise academic performance, family relationships, and social interactions[5].

Existing studies have confirmed that autonomic nervous dysfunction is one of the key pathologic mechanisms underlying the onset and progression of DDs[6]. The dynamic balance between the sympathetic and parasympathetic nervous systems serves as the foundation for maintaining normal physiologic homeostasis. Disruption of this balance can trigger psychiatric conditions, such as depression. Heart rate variability (HRV)[7] reflects minute fluctuations in instantaneous heart rate or cardiac cycle duration. The HRV frequency-domain parameters, including high-frequency (HF) power, which primarily reflects parasympathetic activity, and low-frequency (LF) power, which is regulated jointly by sympathetic and parasympathetic nerves, have led to the widespread use of the LF:HF ratio to assess autonomic nervous balance. In this study adolescents with DDs were grouped according to the severity of depression and a systematic analysis was performed to determine the correlations between depressive severity, autonomic function, general demographic characteristics, and psychosocial factors, by incorporating the LF:HF ratio, anxiety levels, and baseline patient data.

The multi-domain psychosocial factors examined alongside autonomic function markers in this research include residential location, medical expense payment method, household per capita monthly income, primary caregiver type, quality of family relationships, adolescent adverse life experiences, and anxiety severity indexed by the Zung Self-rating Anxiety Scale (SAS). These variables were selected based on consistent epidemiological and developmental psychiatric evidence[8]: Socioeconomic status shapes material security and mental health resource accessibility; caregiver configuration and family relational closeness determine core emotional attachment support; adolescent adverse life events act as acute stress triggers; and comorbid anxiety constitutes a well-documented psychological amplifier of depressive symptoms. Three complementary theoretical frameworks jointly underpin the variable interrelationships tested herein. Bronfenbrenner’s family ecological systems theory[9] explains how layered socioeconomic and familial environments modify adolescents’ stress vulnerability. Thayer’s neurovisceral integration model[10] establishes the biological pathway linking psychological stressors to disrupted sympathetic-parasympathetic balance quantified by the LF:HF ratio. The bidirectional anxiety-depression cycle theory[11] further illustrates how co-occurring anxiety exacerbates depressive manifestations via sustained limbic-autonomic hyperarousal. Despite accumulating separate research on either HRV-based autonomic biomarkers or isolated psychosocial risk factors for youth depression, few clinical studies have integrated physiological and multi-dimensional psychosocial indicators to stratify depressive severity in hospitalized adolescent patients. Against this research gap, the present study sets two core research objectives: (1) To clarify univariate differences in autonomic function and psychosocial characteristics across adolescent patients stratified by depressive severity; and (2) To identify independent physiological and psychosocial predictors of depressive severity.

Three primary hypotheses were proposed: (1) Hypothesis 1: Rural residence, out-of-pocket medical payment, low household income, non-parental single caregiving, distant family relationships, adverse adolescent experiences, and elevated SAS anxiety scores will independently predict more severe depressive symptoms; (2) Hypothesis 2: Abnormally elevated LF:HF ratios (sympathetic predominance) will serve as an independent neurophysiological risk factor for greater depressive severity after adjusting for all psychosocial covariates; and (3) Hypothesis 3: Detrimental psychosocial exposures correlate with autonomic imbalance, jointly exacerbating depressive severity in adolescents with DDs.

MATERIALS AND METHODS

Study subjects

The study cohort consisted of adolescents with DDs who received treatment at Yangzhou Wutai Mountain Hospital in Jiangsu Province from November 2025 to March 2026. The inclusion criteria were as follows: (1) Compliance with the diagnostic criteria of the 10^th revision of the International Classification of Diseases (ICD); (2) Diagnosis of a depressive episode or recurrent DDs; (3) 13–17 years of age; (4) Participation in HRV monitoring; and (5) Informed consent obtained from the patients and their guardians. The exclusion criteria were as follows: (1) Intellectual disability, dementia, substance abuse, or organic mental disorders; (2) Comorbid severe somatic diseases or other complications; (3) Language or cognitive impairment causing an inability to complete questionnaires; (4) Use of pacemakers, implantable cardioverter-defibrillators (ICDs), or radiofrequency ablation for arrhythmia treatment[12]; and (5) Withdrawal of informed consent.

Detailed informed consent procedures for minor participants: All eligible adolescent patients and their legal guardians received printed standardized written information sheets prior to study enrollment. Research clinicians verbally explained the study purpose, testing procedures, potential non-invasive risks, data anonymization rules, and the right to withdraw at any time without penalty. Written informed consent signatures were separately collected from each adolescent participant (assent form for minors aged 13-17) and their primary legal guardian (formal consent form). All consent documents were archived securely in the hospital’s clinical research file repository.

This study was a cross-sectional study. The sample size for multivariate analysis should be at least 5-10 times the number of variables according to the Kendall sample size estimation method[13]. The study included 15 independent variables with a sample size ranging from 75-150 cases. To further validate sample adequacy, formal a priori power analysis was performed using G*Power 3.1 software for multiple linear regression. Parameters were set as: Fixed effect size f² = 0.15 (medium), significance level α = 0.05, statistical power (1-β) = 0.80, and 15 predictor variables. The analysis generated a minimum required sample size of 139 participants. The final sample size was 269 cases.

Definition of adverse experiences: The “Adverse Experiences” recorded in this research refer to stressful negative life events encountered by participants during adolescence, including school bullying, long-term family discord and family trauma.

Full study implementation procedures

After successful enrollment and consent signing, all participants completed standardized demographic and psychosocial questionnaires under the guidance of trained research nurses in a quiet independent consultation room. Completion of the SAS and Zung Self-rating Depression Scale (SDS) was finished first. Following a 10-minute resting adaptation period, standardized HRV autonomic function testing was conducted in accordance with uniform laboratory specifications. All questionnaire data and HRV physiological indicators were double-entered into a dedicated encrypted electronic database, with personal identifiers removed to ensure participant anonymity.

Autonomic nervous function testing

All HRV recordings were performed under standardized quiet resting conditions. Each subject was seated in a soundproofed examination room with dim lighting and constant ambient temperature. A mandatory 10-minute pre-recording adaptation period was required prior to signal acquisition; all adolescents were instructed to fast for at least 2 hours to avoid metabolic interference. The total duration of continuous HRV signal recording was 5 minutes, during which autonomic respiratory rate was monitored in real time without manual adjustment. The HRV power spectrum can be used to assess sympathetic and parasympathetic nerve activity. LF (0.04-0.15 Hz) reflects the dual influence of sympathetic and parasympathetic nerve tension in HRV frequency domain analysis with sympathetic nerve tension predominating. HF (0.15-0.40 Hz) only reflects parasympathetic nerve tension (primarily vagal nerve tension). The LF:HF ratio indicates the balance between sympathetic and parasympathetic nerve tension[7]. Patients were divided into three groups based on HRV detection results (LF:HF ratio as the primary index of autonomic nerve tension balance)[14]: Normal autonomic nerve tension group with the balance point interval of autonomic nerve tension ranging from -1.5σ to 1.5σ (representing physiological sympathovagal equilibrium); severe sympathetic nerve tension group with the balance point interval of autonomic nerve tension ≥ 1.5σ (indicating significant sympathetic overactivity); and severe parasympathetic nerve tension group with the balance point interval of autonomic nerve tension ≤ -1.5σ (indicating significant parasympathetic overactivity). Autonomic nerve function was measured using an HRV detector (ZSY-1; Shenyang Weijin Gene Technology Co., Ltd., Shenyang, China). The σ value represents the statistical comparison between the measured values of the device and an internal healthy population database.

Psychological status assessment

The SAS and SDS were used to assess patient anxiety and depressive states over the past week. Both scales consist of 20 items with an SAS standard score ≥ 50 and an SDS standard score ≥ 53, indicating significant anxiety or depressive symptoms. Higher scores reflect more severe anxiety or depression[15].

Statistical analysis

Statistical analysis was performed using IBM SPSS 26.0 software. Categorical data are expressed as n (%) and analyzed using the χ² test. Normality was assessed with the Kolmogorov-Smirnov test. Normally distributed continuous variables are presented as a mean ± SD and analyzed using a t-test, while non-normally distributed continuous variables are expressed as a median and interquartile range and analyzed using the Kruskal-Wallis H-test. Variables with statistically significant results from univariate analysis were selected as independent variables and multiple stepwise regression analysis was used to determine the factors influencing SDS in adolescents with DDs. All unordered multi-category categorical variables were converted into dummy variables prior to regression analysis, binary variables and continuous indicators were directly incorporated without dummy transformation. Two-tailed testing was used with a P value < 0.05 considered statistically significant.

RESULTS

General information of study subjects

This study enrolled a total of 269 adolescents with DDs and the following characteristics (Table 1): 15.18 ± 1.35 years; disease duration, 0-0.5 years; females (64.68%) outnumbered males (35.32%); initial onset (63.20%) was more common than recurrent episodes (36.80%); the relatively high early recurrence rate within half a year is a genuine clinical feature of this adolescent sample, largely attributable to underdeveloped emotion regulation capacity, inadequate family emotional support and premature treatment dropout in young depressive patients; and autonomic dysfunction existed in 152 patients (56.51%), while normal autonomic function was noted in 117 patients (43.49%).

Table 1 General characteristics of adolescents with depressive disorders (n = 269), n (%)/mean ± SD/median (interquartile range).

Item	Classification	Statistic
Gender	Male	95 (35.32)
	Female	174 (64.68)
Diagnose	Depressive episode	156 (57.99)
	Recurrent depressive disorder	113 (42.01)
Medical-seeking status	Initial onset	170 (63.20)
	Recurrent episodes	99 (36.80)
Place of residence	City proper	101 (37.55)
	Town	71 (26.39)
	Rural area	97 (36.06)
Payment method	At one’s own expense	126 (46.84)
	Medical insurance	143 (53.16)
Per capita monthly household income	< 3000	89 (33.09)
	3000-8000	109 (40.52)
	> 8000	71 (26.39)
Caregiver status	Parents	103 (38.29)
	Single parent (mother)	102 (37.92)
	Single parent (father)	64 (23.79)
Family relationships	Intimate	88 (32.71)
	Same as	91 (33.83)
	Drift apart	90 (33.46)
Adverse experiences	No	163 (60.59)
	Yes	106 (39.41)
Body mass index	Normal	121 (44.98)
	Too light	74 (27.51)
	Excess weight	38 (14.13)
	Fat	36 (13.38)
SAS scores	Normal	86 (31.97)
	Mild	94 (34.94)
	Moderate	55 (20.45)
	Severe	34 (12.64)
SDS scores	Normal	59 (21.93)
	Mild	87 (32.34)
	Moderate	78 (29.00)
	Severe	45 (16.73)
LF:HF ratio	Normal	117 (43.49)
	Markedly sympathetic bias	82 (30.49)
	Markedly biased toward the parasympathetic system	70 (26.02)
Age		15.18 ± 1.35
Disease duration factors (year)		0 (0-0.50)

SDS: Self-rating Depression Scale; SAS: Self-rating Anxiety Scale; LF:HF: Low-frequency:high-frequency.

Univariate analysis results of SDS for adolescent patients with DDs

A univariate analysis model was constructed with SDS scores as the dependent variable and demographic characteristics as independent variables to assess differences in demographic characteristics among adolescents with DDs. After Shapiro-Wilk normality and Levene’s homogeneity of variance testing, parametric testing methods (independent samples t-test/rank sum test) were used to evaluate intergroup differences. The results demonstrated statistically significant differences in gender, medical-seeking status, place of residence, payment method, per capita monthly household income, caregiver status, family relationships, adverse experiences, body mass index, SAS scores, LF:HF ratio, and disease duration factors (P value < 0.05; Table 2).

Table 2 Univariate analysis of Self-rating Depression Scale in adolescents with depressive disorders (n = 269), n (%)/median (interquartile range).

Item	Classification	SDS scores				P value
		Normal (n = 59)	Mild (n = 87)	Moderate (n = 78)	Severe (n = 45)
Gender	Male	17 (28.81)	42 (48.28)	23 (29.49)	13 (28.89)	0.02a
	Female	42 (71.19)	45 (51.72)	55 (70.51)	32 (71.11)
Medical-seeking status	Initial onset	28 (47.46)	57 (65.52)	54 (69.23)	31 (68.89)	0.04a
	Recurrent episodes	31 (52.54)	30 (34.48)	24 (30.77)	14 (31.11)
Place of residence	City proper	26 (44.07)	38 (43.68)	23 (29.49)	14 (31.11)	0.04a
	Town	20 (33.90)	22 (25.29)	20 (25.64)	9 (20.00)
	Rural area	13 (22.03)	27 (31.03)	35 (44.87)	22 (48.89)
Payment method	At one’s own expense	38 (64.41)	35 (40.23)	36 (46.15)	17 (37.78)	0.02a
	Medical insurance	21 (35.59)	52 (59.77)	42 (53.85)	28 (62.22)
Per capita monthly household income	< 3000	12 (20.34)	24 (27.59)	33 (42.31)	20 (44.44)	0.04a
	3000-8000	25 (42.37)	39 (44.82)	28 (35.90)	17 (37.78)
	> 8000	22 (37.29)	24 (27.59)	17 (21.79)	8 (17.78)
Caregiver status	Parents	39 (66.10)	24 (27.59)	23 (29.49)	17 (37.78)	< 0.01a
	Single parent (mother)	16 (27.12)	38 (43.68)	34 (43.59)	14 (31.11)
	Single parent (father)	4 (6.78)	25 (28.73)	21 (26.92)	14 (31.11)
Family relationships	Intimate	32 (54.24)	27 (31.03)	18(23.08)	11(24.44)	< 0.01a
	Same as	12 (20.34)	30 (34.48)	30(38.46)	19(42.22)
	Drift apart	15 (25.42)	30 (34.48)	30 (38.46)	15 (33.34)
Adverse experiences	No	38 (64.41)	59 (67.82)	49 (62.82)	17 (37.78)	< 0.01a
	Yes	21 (35.59)	28 (32.18)	29 (37.18)	28 (62.22)
Body mass index	Normal	31 (52.54)	38 (43.68)	32 (41.03)	20 (44.44)	0.04a
	Too light	15 (25.42)	28 (32.18)	20 (25.64)	11(24.44)
	Excess weight	10 (16.95)	10 (11.50)	16 (20.51)	2 (4.44)
	Fat	3 (5.09)	11 (12.64)	10 (12.82)	12 (26.63)
SAS scores	Normal	26 (44.07)	33 (37.93)	19 (24.36)	8 (17.78)	< 0.01a
	Mild	26 (44.07)	34 (39.08)	28 (35.90)	6 (13.33)
	Moderate	6 (10.17)	17 (19.54)	19 (24.36)	13 (28.89)
	Severe	1 (1.69)	3 (3.45)	12 (15.38)	18 (40.00)
LF:HF ratio	Normal	35 (59.32)	43 (49.42)	21 (26.92)	18 (40.00)	< 0.01a
	Markedly sympathetic bias	12 (20.34)	21 (24.14)	33 (42.31)	16 (35.56)
	Markedly biased toward the parasympathetic system	12 (20.34)	23 (26.44)	24 (30.77)	11 (24.44)
Disease duration factors (years)		0.2 (0-1.00)	0 (0-0.40)	0 (0-0.20)	0 (0-0.25)	0.02b

^aχ² test.

^bRank sum test.

SAS: Self-rating Anxiety Scale; LF:HF: Low-frequency:high-frequency.

Multivariate analysis results of the SDS for adolescent patients with DDs

SDS scores were used as the dependent variable to perform a multivariate analysis of the SDS in adolescents with DDS and included statistically significant predictors from univariate analysis into a multiple linear regression model. Predictive variables included gender, medical consultation status, place of residence, payment method, per capita monthly household income, caregivers, family relationships, adverse experiences, body mass index, SAS score, LF:HF ratio, and disease duration. The analysis was performed using multiple stepwise regression analysis (α_entry = 0.05, α_exit = 0.10).

Performing multicollinearity diagnostics is an essential step before formally fitting the model. Multicollinearity may lead to inaccurate parameter estimation, increase standard errors of regression coefficients, and as a result, compromise model stability and reliability. Typically, the variance inflation factor (VIF) is used to assess potential severe multicollinearity among predictors. In this study all VIF values were < 10, indicating no significant multicollinearity issues among predictors and meeting the basic assumptions of the regression model. The specific assignment methods are detailed in Table 3.

Table 3 Variable assignment methods for multiple linear regression.

Project	Value assignment method
Gender	Male = 1, female = 2
Medical-seeking status	Initial onset = 1, recurrent episodes = 2
Place of residence	Urban area = 1, town = 2, rural area = 3
Payment method	Out-of-pocket expense = 1, medical insurance = 2
Per capita monthly household income (yuan)	< 3000 = 1, 3000-8000 = 2, > 8000 = 3
Caregiver status	Parents = 1, single parent (mother) = 2, single parent (father) = 3
Family relationships	Intimate = 1, neutral = 2, distant = 3
Adverse experiences	No = 1, yes = 2
Body mass index (kg/m2)	18.5-23.9 = 1, < 18.5 = 2, 24.0-27.9 = 3, ≥ 28.0 = 4
SAS scores	< 50 = 1, 50-59 = 2, 60-69 = 3, ≥ 70 = 4
SDS scores	< 53 = 1, 53-62 = 2, 63-72 = 3, ≥ 73 = 4
LF:HF ratio (autonomic bias)	1.0-2.0 (normal autonomic function) = 1, > 2.0 (severely sympathetic autonomic function) = 2, < 1.0 = 3 (severely parasympathetic autonomic function)
Disease duration factors (years)	Original value carryover

SDS: Self-rating Depression Scale; SAS: Self-rating Anxiety Scale; LF:HF: Low-frequency:high-frequency.

The results of multiple stepwise regression analysis showed that the factors influencing SDS in adolescent patients with DDs included: Place of residence [odds ratio (OR) = 2.18], payment method (OR = 4.42), per capita monthly household income (OR = 0.32), caregivers (OR = 3.81), family relationships (OR = 2.12), adverse experiences (OR = 2.81), SAS scores (OR = 4.17), and LF:HF ratio (OR = 1.94), all with P values < 0.05 (Table 4).

Table 4 Multivariate analysis of the Self-rating Depression Scale for adolescent patients with depressive disorders.

Variable	β	SE	P value	OR	95%CI
Constant	-10.01	2.42
Place of residence	0.78	0.304	0.01	2.18	1.20-3.96
Payment method	1.49	0.51	< 0.01	4.42	1.63-11.99
Per capita monthly household income	-1.16	0.35	< 0.01	0.32	0.16-0.62
Caregiver status	1.34	0.37	< 0.01	3.81	1.84-7.90
Family relationships	0.77	0.32	0.02	2.12	1.16-4.01
Adverse experiences	1.03	0.52	0.04	2.81	1.03-7.72
SAS scores	1.43	0.28	< 0.01	4.17	2.39-7.26
LF:HF ratio	0.66	0.32	0.04	1.94	1.04-3.63

SAS: Self-rating Anxiety Scale; LF:HF: Low-frequency:high-frequency.

DISCUSSION

This study focused on adolescents 13-17 years of age with DDs, evaluating autonomic nervous function based on the LF:HF ratio in conjunction with sociodemographic characteristics, family traits, and anxiety indicators. A systematic analysis was performed to identify the factors influencing the severity of adolescent depression, revealing the independent effects of autonomic nervous function, social and family factors, and psychological factors on depressive symptoms. The findings provide objective evidence for elucidating disease characteristics in adolescent DDs and optimizing clinical prevention and intervention strategies.

Association between the LF:HF ratio and adolescent depression

The LF:HF ratio serves as a core frequency-domain indicator for evaluating autonomic nervous system homeostasis. The current study revealed that among 269 adolescents with DDs, 152 (56.5%) exhibited autonomic dysfunction. Multivariate analysis demonstrated autonomic dysfunction as an independent predictor of depressive severity in adolescents, a finding further corroborated by univariate analysis. As depressive severity escalated, the distribution characteristics of abnormal LF:HF ratios showed the following distinct patterns: 59.3% of patients in the normal depression group maintained normal LF:HF ratios; the proportion of patients with significantly elevated sympathetic nervous system activity increased to 42.3% in the moderate depression group; and the proportion of patients with elevated sympathetic nervous system activity remained at 35.6% in the severe depression group. These results strongly indicated a significant positive correlation between sympathetic-parasympathetic imbalance and the severity of adolescent depressive symptoms, underscoring autonomic dysfunction as a critical neurophysiologic basis for the onset and progression of depression. This finding aligns with the findings reported in previous studies by Fann et al[16] and Kemp et al[17], suggesting that patients with more severe depressive symptoms exhibit greater susceptibility to significant autonomic nervous system dysregulation.

HRV frequency-domain metrics serve as the gold standard for evaluating autonomic nervous function. Among these metrics, LF components are predominantly governed by sympathetic nerves with parasympathetic coordination, while HF components solely reflect vagus-mediated parasympathetic tone. The core value of the LF:HF ratio lies in quantifying the dynamic balance between sympathetic and parasympathetic nerves. Specifically, elevated ratios indicate relative hyperactivity of sympathetic nerves, whereas decreased ratios suggest parasympathetic dominance. This homeostatic imbalance represents one of the key pathologic mechanisms underlying DDs[18].

Adolescence represents a uniquely vulnerable developmental window for autonomic regulation, shaped by three interrelated neurobiological traits that distinguish this age group from adults. First, prefrontal cortical subregions mediating top-down inhibitory control of stress and emotion undergo protracted, incomplete maturation throughout adolescence, limiting the capacity to suppress excessive subcortical stress signaling. Second, limbic structures including the amygdala and hippocampus exhibit intrinsically heightened reactivity to negative stimuli and acute stressors, driving amplified neuroendocrine and autonomic output following adverse life events[19]. Third, extensive structural and functional reorganization of central-autonomic integration networks occurs across adolescence, reshaping bidirectional signaling between corticolimbic emotion circuits and peripheral sympathetic-parasympathetic outflow[20]. Collectively, these developmental characteristics weaken adolescents’ stress buffering capacity, rendering them prone to persistent sympathetic overactivation and disrupted autonomic equilibrium. This developmental susceptibility establishes a critical mechanistic framework linking abnormal LF:HF ratios to depressive pathology: Unregulated limbic hyperarousal paired with insufficient prefrontal suppression sustains chronic sympathetic predominance, which manifests clinically as emotional dysregulation, sleep disturbance, somatic discomfort, and anhedonia-the hallmark symptoms of adolescent DDs[21].

Adolescents are at a critical stage of physiologic and psychological development during which autonomic nervous system development continues[22], making adolescents particularly susceptible to dysregulation and vulnerable to external factors, such as psychological stress, family environment, and negative life events. When adolescents experience adverse events, familial estrangement, or academic pressure, the stress response pathways become overactivated, leading to abnormal sympathetic hyperexcitability. This hyperexcitability disrupts autonomic balance, triggering core depressive symptoms, including emotional regulation disturbances, sleep disorders, and somatic discomfort[16], thereby accelerating progression from mild-to-severe depression. Adolescents exhibit underdeveloped autonomic nervous systems with reduced tolerance to neural imbalances and weaker compensatory capacity compared to adult patients. Consequently, abnormal LF:HF ratios are more prominent in adolescent depression populations and carry greater clinical significance[23]. The findings of this study are highly consistent with previous research on autonomic dysfunction involvement in depression pathogenesis[21,24]. The findings herein also fill the research gap regarding the stratified association between the LF:HF ratio and depression severity in adolescent populations, demonstrating that the LF:HF ratio is not merely a physiologic indicator but an objective biomarker reflecting the severity of DDs[25]. In addition, the LF:HF ratio can objectively quantify neural balance status through HRV detection, featuring simple operation, high reproducibility, and cost-effective repeated measurements[26]. This approach overcomes the limitations of subjective scale assessments and can be considered a valuable biomarker with potential for early screening and disease stratification[27].

Comorbidity association between anxiety and depression

The results of this study indicate that the SAS score is the strongest independent risk factor for the severity of DDs in adolescents (OR = 4.17). Univariate analysis revealed that higher levels of depressive severity are associated with a concurrent increase in the incidence and severity of anxiety symptoms. Among patients with severe depression, the proportion exhibiting moderate-to-severe anxiety was as high as 40.0%, conclusively demonstrating that the comorbidity of anxiety and depression is highly prevalent, synchronous, and additive in adolescent depressive populations, and serving as a core psychological factor that exacerbates depressive symptoms and impacts disease prognosis[28]. Anxiety is characterized by sympathetic hyperactivity and heightened vigilance, whereas depression manifests primarily as low mood and anhedonia; these two mood disorders interact significantly in adolescents[29]. Chronic anxiety continuously depletes psychological energy, leading to depressive symptoms, such as diminished interest and low mood, while the self-denial and sense of helplessness induced by depression further intensify future-related concerns and fears, triggering and worsening anxiety, thereby forming a vicious emotional cycle that is difficult to break[30]. In addition, anxiety and depression comorbidity results in more complex symptoms and more pronounced somatization manifestations, while masking the typical features of either mood disorder alone, thereby increasing clinical identification and diagnostic difficulty. Patients with comorbidity exhibit longer disease duration, higher recurrence rates, poorer treatment responses, and elevated suicide risks with a more pronounced negative impact on academic performance, family relationships, and social adaptation compared to patients with isolated depression[31]. The findings of this study suggested that adolescent depression screening and assessment should concurrently evaluate anxiety symptoms, rather than focusing solely on a single depressive dimension. Clinical interventions should adopt a combined anxiety-depression intervention strategy, integrating cognitive behavioral therapy and relaxation training with antidepressant treatment to break the emotional vicious cycle. This approach can effectively alleviate depressive symptoms and improve long-term prognosis.

Impact of sociodemographic and family factors

Multivariate analysis revealed that place of residence (OR = 2.18), payment method (OR = 4.42), per capita monthly household income (OR = 0.32), caregiver type (OR = 3.81), family relationships (OR = 2.12), and adverse experiences (OR = 2.81) are all independent predictors of the severity of adolescent depression. These findings indicated that sociodemographic characteristics and the family microenvironment jointly influence the onset and progression of adolescent depression through pathways, such as material support, emotional companionship, and stress exposure, which aligns closely with the fact that adolescent psychological development is highly dependent on family and social support.

The risk of aggravated depression among rural adolescents is significantly higher than in urban and township areas. The core reasons for this finding include inadequate mental health resources, insufficient disease awareness, and strong stigma in rural regions, which often lead to delayed medical consultations and non-standardized treatment. In addition, rural adolescents have weaker social support networks and limited communication patterns, making adolescents more prone to emotional regulation failure under negative stressors, thereby exacerbating depressive symptoms[32,33]. Medical insurance can alleviate financial burdens and improve treatment adherence during payment processes, while out-of-pocket expenses impose economic pressures that may restrict treatment options and intensify family conflicts, highlighting the critical role of healthcare security in standardized interventions for adolescent depression. Household per capita monthly income serves as an independent protective factor for DDs in adolescents. High-income families provide stable living environments, quality education, and timely medical support, mitigating psychological impacts from external stressors. Low-income families often experience chronic stress, insufficient parental companionship, and inadequate psychological support, which can impair adolescent psychological resilience and prolong depressive symptoms[34]. Dual-parent caregiving offers balanced emotional support and secure attachment, whereas single-parent families, constrained by limited caregiving capacity and emotional support, are more likely to expose adolescents to emotional distress[35,36]. Family relationship intimacy directly correlates with depression risk. Intimate family environments alleviate stress and enhance self-worth, while estranged or conflict-ridden family settings may induce loneliness, low self-esteem, persistent psychological stress, and disruption of autonomic nervous system balance[37]. Adverse experiences serve as significant predisposing factors. The immature psychological defense mechanisms of adolescents make adolescents susceptible to psychological trauma from negative events, such as school bullying and family trauma, which can directly activate the sympathetic nervous system and become direct triggers for the onset and exacerbation of depression[38,39].

In summary, sociodemographic factors determine the accessibility of mental health resources and the level of material security, while family factors constitute the core microenvironment of psychological support. Together, these two elements shape the developmental trajectory of adolescent depression, suggesting that clinical interventions should integrate social support, family interventions, and medical security to establish a comprehensive prevention and control system.

CONCLUSION

In summary, this study investigated the relationship between the severity of depression and autonomic nervous function, sociodemographic characteristics, and anxiety symptoms in adolescents with DDs. The results demonstrated that patients residing in rural areas, seeking self-paid medical care, receiving care from single parents, experiencing distant family relationships, having endured adverse experiences, exhibiting high SAS scores, or showing abnormal LF:HF ratios exhibited more severe depressive symptoms and had a higher risk of disease progression. A stratified screening and precise assessment of adolescent DDs can be implemented by integrating the LF:HF ratio with psychosocial factors, followed by personalized interventions tailored to different patient subgroups. This approach enhances the efficacy of clinical management and mental health interventions for adolescent depression, thereby reducing the risk of symptom exacerbation.

This study was a cross-sectional study that only analyzed factor correlations and did not determine causal relationships. The sample consisted solely of patients from our hospital and the single-center design limits geographical and population representativeness. Current findings only indicate a correlation between depressive symptoms and the LF:HF ratio in adolescents with DDs without clarifying the dynamic changes or prognostic associations. Variables, such as campus environment and social support, were not included, necessitating expanded research dimensions. Several targeted directions for future research are proposed to address the above limitations and extend the present work: First, large-sample, multicenter longitudinal cohort studies should be conducted to track dynamic changes in LF:HF ratios and depressive symptoms over time, which can further verify the causal directional relationship between autonomic imbalance and depressive severity. Second, more comprehensive psychosocial variables, including school climate, peer relationships, and social support levels, should be incorporated into multivariate models to build a more complete risk prediction system for adolescent depression. Third, clinical intervention trials focusing on autonomic regulation guided by LF:HF ratio indicators should be designed to validate whether targeted autonomic modulation can alleviate depressive and anxiety symptoms in adolescents. Fourth, integrated multi-stakeholder prevention and intervention models combining hospitals, schools, and families need to be explored, with stratified early warning strategies based on autonomic biomarkers and psychosocial risk factors for high-risk adolescent groups. Integrating family, school, and medical resources will facilitate the establishment of a comprehensive, multi-scenario prevention and control system for adolescent depression.