Body Composition, Emotional Dysregulation, and Suicide Risk in College Students

Abstract

Introduction: University students often describe their academic years as a period of continuous personal change, which may increase vulnerability to unhealthy lifestyle habits. These habits can influence body composition and are associated with both physical conditions (e.g., overweight, sedentary behavior) and psychological well-being, including suicide risk. Method: A quantitative, non-experimental, cross-sectional, descriptive–comparative–correlational design was employed, using a non-probabilistic intentional sample of 174 university students. Data were collected using the OMRON 514C body composition monitor, the Difficulties in Emotional Regulation Scale (DERS-E), and Plutchik’s Suicide Risk Scale. Statistical analyses included descriptive statistics, independent samples t-tests for gender comparisons, Pearson’s correlation analyses, and multiple linear regression analyses to examine whether the observed bivariate associations remained significant after controlling for gender. Results: Descriptive analyses showed variability in body composition, emotional dysregulation, and suicide risk. Gender comparisons indicated that men presented higher weight, height, skeletal muscle mass, visceral fat level, and basal metabolic rate, whereas women reported higher body fat percentage, greater emotional dysregulation, and higher suicide risk. Correlation analyses revealed that suicide risk was negatively associated with skeletal muscle mass (r = −0.24, p = 0.002), basal metabolic rate (r = −0.21, p = 0.006), height (r = −0.27, p < 0.001), emotional rejection (r = −0.24, p = 0.001), and emotional confusion (r = −0.22, p = 0.004). Multiple regression analyses, controlling for gender, indicated that the associations between body composition indicators (skeletal muscle and basal metabolism) and suicide risk did not remain statistically significant (p > 0.05). In contrast, emotional dysregulation dimensions, particularly emotional rejection, maintained significant associations with suicide risk after adjustment for gender. Additionally, negative associations were found between BMI and emotional dysregulation, and between height and emotional clarity, even after controlling for gender. Discussion: The findings highlight emotional dysregulation as a central and robust factor associated with suicide risk in university students, whereas body composition indicators appear to play a more limited and gender-dependent role. The fact that associations between physical markers (skeletal muscle, basal metabolism) and suicide risk were mediated by gender underscores the importance of considering sociodemographic factors when interpreting body–mental health relationships. These results support the need for integrated biopsychosocial prevention strategies that address emotional regulation within the university context, while considering the differential impact of gender on both physical and psychological risk factors.

1. Introduction

University life is described by students as a time of constant personal change, coinciding with separation from family, entry into the labor market, adaptation to teachers and classmates, new learning, curricular reorganization, and greater academic evaluation demands [1]. This reality affects the healthy lifestyle habits of university students, resulting in a population at greater risk of developing unhealthy lifestyle habits [2], such as stress, smoking, alcoholism, sedentary lifestyles, and poor eating habits [3,4]. Among these bad habits, body composition is related to diseases such as obesity, overweight, and sedentary lifestyles, with Chile recording a 71% increase in overweight, 3.2% increase in morbid obesity, and 40.1% increase in metabolic syndrome [5].

Body composition (BC) refers to the size and shape of the body, typically described using anthropometric measurements [6]. In this regard, BC is influenced by habits, especially during stages of biopsychosocial change or high academic demand, such as university. At university, dynamics can affect eating patterns (skipping breakfast or excessive caloric intake and low nutritional intake), compounded by little or no physical activity, alcohol consumption, smoking, and other habits that are harmful to human well-being [7]. In this context, aspects associated with BC are directly related to healthy lifestyle habits, with physical activity being one of the main non-pharmacological aspects that contribute to changes in body composition [8] so that it not only has effects on the biological dimension of human beings, but also on the psychological well-being and academic performance of university students [9,10]. Critically, emotional dysregulation can disrupt these lifestyle habits. For example, difficulties in emotional regulation are linked to academic procrastination, which is associated with suicidal risk and can undermine engagement in health-promoting behaviors. Furthermore, unhealthy lifestyles characterized by poor eating habits and inactivity are directly related to negative mental health outcomes and poorer body composition (4, 7). Emerging theoretical frameworks suggest that specific BC metrics, such as skeletal muscle mass and basal metabolic rate, may influence mental health through neurobiological pathways (e.g., neuroplasticity, inflammation modulation, HPA axis regulation) and psychological mechanisms (e.g., self-efficacy, body image). This is supported by research showing that physical activity and a positive body image are associated with greater psychological well-being in university students (9), and that food habits are linked to mental health and executive function. The above is linked to Sustainable Development Goals (SDGs) 3 and 4, since the fields of education (SDG 4) and health (SDG 3) are primarily responsible for promoting programs that encourage physical activity as one of the most relevant aspects in improving body composition and mental and emotional well-being [11].

Emotions are also a fundamental component of human development [12]. Several studies have shown that emotional regulation is associated with people’s health [13,14,15] and that not having the skills to regulate emotions can negatively affect biological, psychological, cognitive, and social aspects, directly interfering with overall well-being and functioning [16]. This reality is no stranger to university life, considering that emotional regulation plays a role in academic adaptation, directly influencing performance [17,18]. However, academic overload exacerbates emotional disorders in the university population [17]. For this reason, the study of factors that influence emotional regulation processes in university students is becoming increasingly relevant in the scientific community [19]. In this regard, emotional dysregulation, considered a failure in emotional regulation processes, can directly affect the well-being and functioning of university students. In other words, when the biological and learning components of emotional regulation are configured in a non-adaptive way, they result in patterns of dysregulated behavior that can lead to psychological disorders such as anxiety, depression, borderline personality disorder, substance use, and eating disorders [20]. These dysregulated patterns, combined with physiological vulnerabilities potentially reflected in adverse body composition, may create a synergistic risk for severe outcomes, including suicidality. In this regard, difficulties in regulating emotions manifest themselves negatively in different ways [21]:

(a)

Physical and biological: Substance use, self-harm, high blood pressure, increased heart rate, cancer, and eating disorders, among others.

(b)

Psychological and cognitive: Anxiety disorders, panic attacks, stress, depression, and low self-esteem, among others.

(c)

Social: Attention deficit, aggression, lack of empathy, ineffective communication, problems with coexistence, among others.

In the context that emotional dysregulation problems have been considered a risk factor for suicide from an early age, such as adolescence [4], suicide is regarded as the second leading cause of death worldwide among 15- to 29-year-olds, with a common trend among university students, where it not only threatens the lives of students but is also associated with physical and mental health and academic performance [22]. Therefore, this stage of life is considered critical and is also associated with various mental health problems, with students experiencing a high risk of suicide in response to new academic environments, leaving home, new relationships, and academic pressure [23]. In other words, the high levels of distress associated with this period of transition between adolescence and adulthood can contribute to mental health problems, which in turn increase the likelihood of developing suicidal ideation and behavior [24,25]. A biopsychosocial perspective posits that physiological factors, including BC, may interact with emotional dysregulation to modulate this risk. For instance, lower skeletal muscle mass and basal metabolism could reflect or contribute to a physiological substrate of low energy, anhedonia, and reduced stress resilience, thereby potentially exacerbating suicidal vulnerability. However, research on suicide risk among university students is still emerging, as few studies have investigated suicidal ideation, and the findings remain inconclusive [26].

In reference to the background mentioned above, the research questions were: What differences exist in body composition, emotional dysregulation, and suicide risk between men and women? What is the relationship between body composition, emotional dysregulation, and suicide risk in university students? Which variables of body composition and emotional dysregulation predict suicide risk?

To answer these questions, the hypothesis is that body composition has significant relationships with the average and components of emotional dysregulation and suicide risk. Specifically, it is hypothesized that indicators of better metabolic and muscular health (e.g., higher skeletal muscle mass, higher basal metabolic rate) will be associated with lower emotional dysregulation and lower suicide risk, potentially reflecting shared underlying mechanisms related to physiological regulation and psychological resilience. To confirm this, the objectives of the research were: (a) to identify the levels of emotional dysregulation among university students; (b) to measure the body composition (weight, height, Body Mass Index [BMI], body fat, visceral fat, skeletal muscle, basal metabolism, and body age) of university students; (c) to compare body composition, suicide risk, and emotional regulation and dysregulation according to the gender of university students; and (d) to identify associations between body composition, emotional dysregulation, and suicide risk among university students.

2. Materials and Methods

This research has a quantitative, non-experimental, cross-sectional, descriptive–comparative–correlational design.

2.1. Sample

The sample was non-probabilistic and intentional and consisted of n = 174 university students from a private university located in Temuco, Chile (

Table 1. Sociodemographic background of the sample.

Gender	Number	Percentage
Male	97	55.7%
Female	77	44.3%
Age	Number	Percentage
<20	55	31.6%
20–25	105	60.3%
>25	14	8%
University year	Number	Percentage
First year	78	44.8%
Second year	28	16.1%
Third year	27	15.5%
Fourth year	38	21.8%
Fifth year	3	1.7%

). No a priori power calculation was conducted, as this was an exploratory pilot study. This sampling strategy limits the representativeness of the sample and the generalizability of the findings to the broader university population. The inclusion criteria included being a regular student at the time of data collection and having previously signed the informed consent form. The exclusion criterion included those who did not complete the questionnaire established in the instruments section.

2.2. Instruments

The instruments used for data collection in this study were:

(a)

OMRON 514C scale used to measure body composition (BMI, basal metabolism, body weight, fat percentage, visceral fat level, muscle percentage, and body age) using bioimpedance.

(b)

Difficulties in Emotion Regulation Scale (DERS-E) in its Spanish-adapted version [27], validated in the Chilean population in a study in which an internal consistency of 0.92 was obtained using Cronbach’s alpha [28]. The scale consists of 25 items and allows for a total score to be obtained by adding up all the items in the instrument, as well as a subscale score by calculating the sum of the items that comprise it (emotional rejection, everyday interference, emotional inattention, emotional dyscontrol, and emotional confusion).

(c)

Plutchik’s Suicide Risk Scale consists of a scale that includes 15 items, where each affirmative answer adds one point and each negative answer adds 0 points. The total score ranges from 0 to 15 points, with a cut-off score of 6. The higher the score, the greater the suicide risk [29].

2.3. Analysis Procedure

Data analysis was conducted using the Statistical Package for the Social Sciences (SPSS), version 29 (IBM Corp., Armonk, NY, USA). Body composition variables and scores from the DERS-E and Plutchik Suicide Risk Scale were entered into the database. Descriptive statistics were calculated for all study variables. Independent samples t-tests were performed to examine gender differences in body composition, emotional dysregulation, and suicide risk. Pearson’s correlation coefficients (r) were computed to explore bivariate associations between suicide risk, body composition indicators, and emotional dysregulation dimensions. To further investigate these relationships while controlling for potential confounding variables, multiple linear regression analyses were conducted. These analyses examined the extent to which body composition variables (BMI, skeletal muscle mass, visceral fat, body fat, basal metabolism, height, weight and body age) and emotional dysregulation dimensions predicted suicide risk scores, with gender included as a covariate in all models. Variance Inflation Factor (VIF) statistics were examined to assess multicollinearity among predictors. The total score of the Plutchik Suicide Risk Scale was treated as a continuous dependent variable.

2.4. Ethical Considerations

This research was conducted under the guidelines provided in the Singapore Declaration, taking into account the principles of honesty, responsibility, professional courtesy, and good management during the study. It was also based on the four principles of bioethics associated with autonomy, justice, beneficence, and non-maleficence, considering that the sample had complete freedom of choice regarding their participation in the research and that in no case would any physical, psychological, or moral harm be caused to the participants.

3. Results

In relation to body composition variables, the sample consisted of 174 subjects, with an average weight of 71.5 kg (SD = 13.4; range = 47.6–114.6) and an average height of 168.3 cm (SD = 10.1; range = 147–195). The BMI averaged 25.1 (SD = 3.7086), with extreme values observed that widened the dispersion. The percentage of body fat indicated an average of 27.1% (SD = 10.2395), and muscle mass reached 33.5% (SD = 7.7). Visceral fat had an average of 5.9% (SD = 2.68; range = 1–17), with some participants having values above the metabolic risk threshold. Finally, the average basal metabolic rate was 1575 kcal/day (SD = 256.45), while the average body age was 35 years (SD = 13; range = 18–80), with great diversity observed in relation to the body composition of the sample (

Table 2. Descriptive statistics regarding body composition.

	N	Min	Max	Mean	SD
Weight	174	47.6	114.6	71.538	13.4114
Height	174	147.0	195.0	168.310	10.1547
BMI	174	17.0	37.2	25.124	3.7086
Body fat	174	8.2	54.7	27.959	10.2395
Skeletal muscle	174	11.9	47.2	33.534	7.7031
Visceral fat	174	1	17	5.87	2.688
Basal metabolism	174	1133	2216	1574.97	256.450
Body age	174	18	80	35.21	13.013
Valid N (by list)	174

).

Regarding the DERS-E scale, participants had a total average of 66.2 (SD = 14.57; range = 41–110), reflecting variability in levels of emotional dysregulation; in emotional rejection, they had a mean of 17.4 (SD = 7.2; range 7–35); in emotional dyscontrol, they had an average of 11.6 (SD = 4.94; range = 6–29); emotional interference showed a mean of 11.3 (SD = 3.44; range = 4–20); emotional inattention had a mean of 18.85 (SD = 3.9; range = 8–25); and emotional confusion had a mean of 16.42 (SD = 4.213; range = 8–25) (

Table 3. Descriptive statistics regarding difficulties in emotion regulation.

	N	Min	Max	Mean	SD
Emotional rejection	174	7	35	17.40	7.224
Emotional dyscontrol	174	6	29	11.64	4.941
Emotional interference	174	4	20	11.31	3.448
Emotional inattention	174	8	25	18.85	3.901
Emotional confusion	174	8	25	16.42	4.213
DERS-E average	174	41	110	66.17	14.573
Valid N (by list)	174

).

The descriptive statistics for Plutchik’s Suicide Risk Scale showed an average score of 3.7 (SD = 2.68; range = 0–11), with variability observed in the levels self-reported by university students. Although low to moderate values were reported, high scores were also identified, revealing students with a higher level of suicide risk (

Table 4. Descriptive statistics for suicide risk.

	N	Min	Max	Mean	SD
Suicide risk	174	0	11	3.74	2.685
Valid N (by list)	174

).

The comparison of body composition according to gender showed statistically significant differences in most variables (

Table 5. Comparison of body composition by gender.

	F	Sig.	t	gl	p
Weight	0.036	0.849	6.843	172	0.000 *
			6.845	163.321	0.000 *
Height	2.465	0.118	15.112	172	0.000 *
			14.986	157.461	0.000 *
BMI	7.214	0.008	−0.673	172	0.502
			−0.656	142.827	0.513
Body fat	6.738	0.010	−13.826	172	0.000 *
			−13.366	136.056	0.000 *
Skeletal muscle	0.231	0.631	19.556	172	0.000 *
			19.447	159.452	0.000 *
Visceral fat	5.687	0.018	5.663	172	0.000 *
			5.865	170.898	0.000 *
Basal metabolism	0.001	0.976	15.314	172	0.000 *
			15.232	159.599	0.000 *
Body age	4.111	0.044	1.179	172	0.240
			1.207	171.933	0.229

Note: * = indicates statistical significance (p < 0.05).

). In this regard, men had higher weight (t(172) = 6.84, p ≤ 0.001) and height (t(172) = 15.11, p ≤ 0.001) compared to women. In addition, higher values were observed in men, with significant differences in basal metabolism (t(172) = 15.31, p < 0.001), skeletal muscle (t(172) = 19.56, p < 0.001), and visceral fat (t(172) = 5.66, p < 0.001). In comparison, women had significantly higher values in body fat (t(172) = −13.826, p < 0.000). No significant differences were found in BMI and body age.

The comparison of emotional dysregulation according to gender showed statistically significant differences in several dimensions (

Table 6. Comparison of emotional dysregulation by gender.

	F	Sig.	t	gl	p
Emotional rejection	0.393	0.531	−4.751	172	0.000 *
			−4.714	157.854	0.000 *
Emotional dyscontrol	4.189	0.042	−3.217	172	0.002 *
			−3.124	140.006	0.002 *
Emotional interference	0.789	0.376	−2.428	172	0.016 *
			−2.389	151.087	0.018 *
Emotional inattention	0.415	0.520	1.125	172	0.262
			1.118	161.330	0.265
Emotional confusion	0.562	0.455	0.842	172	0.401
			0.836	158.774	0.404
DERS-E average	1.191	0.277	−4.136	172	0.000 *
			−4.074	152.243	0.000 *

Note: * = indicates statistical significance (p < 0.05).

). The total average of the DERS-E scale revealed significant differences, with women reporting higher levels of emotional dysregulation (t(172) = −4.14, p < 0.001). Concerning the dimensions, the findings indicated that women had higher scores on emotional rejection (t(172) = −4.75, p < 0.001), emotional dyscontrol (t(172) = −3.22, p = 0.002), and emotional interference (t(172) = −2.43, p = 0.016), compared to men. No statistically significant differences were found in the dimensions of emotional inattention (t(172) = 1.125, p = 0.262) or emotional confusion (t(172) = 0.842, p = 0.401).

The comparison of suicide risk by gender showed statistically significant differences (

Table 7. Comparison of suicide risk by gender.

	F	Sig.	t	gl	p
Suicide risk	0.011	0.915	−4.027	172	0.000 *
			−4.073	169.044	0.000 *

Note: * = indicates statistical significance (p < 0.05).

). In this regard, women reported higher scores than men (t(172) = −4.03, p < 0.001), demonstrating that the female group is more vulnerable.

The correlation analysis revealed significant associations between body composition variables, dimensions of emotional dysregulation, and suicide risk (

Table 8. Correlation BC, emotional dysregulation and SR.

	SR	ER	ED	EINT	EINA	EC	DERS-E
Weight	r = −0.13	r = −0.15	r = −0.11	r = −0.10	r = 0.00	r = −0.13	r = −0.16
	p = 0.083	p = 0.04	p = 0.16	p = 0.19	p = 0.99	p = 0.10	p = 0.03
Height	r = −0.24	r = −0.33	r = −0.17	r = −0.16	r = −0.09	r = −0.22	r = −0.27
	p = 0.001	p = <0.001	p = 0.02	p = 0.03	p = 0.21	p = 0.004	p = <0.001
BMI	r = 0.06	r = 0.14	r = −0.03	r = −0.03	r = −0.21	r = 0.09	r = 0.02
	p = 0.40	p = 0.05	p = 0.74	p = 0.70	p = 0.005	p = 0.24	p = 0.84
BF	r = 0.04	r = 0.04	r = 0.11	r = 0.04	r = −0.02	r = 0.09	r = 0.08
	p = 0.63	p = 0.61	p = 0.13	p = 0.62	p = 0.82	p = 0.24	p = 0.30
SM	r = −0.24	r = −0.31	r = −0.17	r = −0.21	r = 0.04	r = −0.12	r = −0.27
	p = 0.002	p = <0.001	p = 0.024	p = 0.006	p = 0.57	p = 0.13	p = <0.001
VF	r = −0.10	r = −0.05	r = −0.12	r = −0.07	r = −0.02	r = −0.06	r = −0.10
	p = 0.20	p = 0.52	p = 0.12	p = 0.37	p = 0.75	p = 0.45	p = 0.20
BM	r = −0.21	r = −0.22	r = −0.12	r = −0.15	r = 0.01	r = −0.14	r = −0.21
	p = 0.006	p = 0.004	p = 0.11	p = 0.05	p = 0.87	p = 0.07	p = 0.007
BA	r = 0.00	r = 0.00	r = −0.04	r = 0.02	r = −0.01	r = −0.02	r = −0.02
	p = 0.96	p = 0.10	p = 0.62	p = 0.83	p = 0.93	p = 0.77	p = 0.84

Note: BMI = Body Mass Index; BF = Body Fat; SM = Skeletal Muscle; VF = Visceral Fat; BM = Basal Metabolism; BA = Body Age; SR = Suicide Risk; ER = Emotional Rejection; ED = Emotional Dyscontrol; EINT = Emotional Interference; EINA = Emotional Inattention; EC = Emotional Confusion; DERS-E = Emotional Regulation Difficulties Scale Average.

). Specifically, suicide risk showed significant negative correlations with skeletal muscle (r = −0.24, p = 0.002), basal metabolism (r = −0.21, p = 0.006), weight (r = −0.16, p = 0.03), and height (r = −0.27, p < 0.001).

Regarding associations between body composition and emotional dysregulation, significant negative correlations were found between BMI and emotional dysregulation (r = −0.21, p = 0.005); between skeletal muscle and emotional rejection (r = −0.24, p = 0.002), emotional regulation (r = −0.31, p < 0.001), emotional inattention (r = −0.17, p = 0.024), and emotional interference (r = −0.21, p = 0.006); and between basal metabolism and emotional rejection (r = −0.22, p = 0.004) and the DERS-E average (r = −0.21, p = 0.007). Height also showed significant negative correlations with emotional rejection (r = −0.24, p = 0.001), emotional regulation (r = −0.33, p < 0.001), emotional inattention (r = −0.17, p = 0.02), emotional interference (r = −0.16, p = 0.03), emotional clarity (r = −0.22, p = 0.004), and the DERS-E average (r = −0.27, p < 0.001).

To determine whether the bivariate associations between body composition variables and suicide risk (SR) were independent of gender, multiple linear regression analyses controlling for this variable were conducted (

Table 9. Multiple linear regression analysis controlling for gender: body composition variables predicting suicide risk and emotional dysregulation dimensions.

DV	Predictor	β	SE	t	p	95% CI for β	VIF	ΔR2
SR	Gender (ref: F)	0.42	0.08	5.25	<0.001	[0.26, 0.58]	1.00	—
	SM	−0.08	0.05	−1.60	0.112	[−0.18, 0.02]	1.32	0.007
	BM	−0.05	0.04	−1.25	0.213	[−0.13, 0.03]	1.28	0.005
	Height	−0.12	0.07	−1.71	0.089	[−0.26, 0.02]	1.45	0.011
	Weight	−0.04	0.06	−0.67	0.505	[−0.16, 0.08]	1.67	0.001
	BMI	0.02	0.05	0.40	0.690	[−0.08, 0.12]	1.22	0.001
ED	Gender (ref: F)	0.38	0.09	4.22	<0.001	[0.20, 0.56]	1.00	—
	BMI	−0.21	0.07	−3.00	0.003	[−0.35, −0.07]	1.18	0.037
	SM	−0.11	0.08	−1.38	0.169	[−0.27, 0.05]	1.52	0.007
	BM	−0.05	0.05	−1.10	0.273	[−0.15, 0.05]	1.41	0.004
	Height	0.08	0.06	1.33	0.185	[−0.04, 0.20]	1.23	0.006
EC	Gender (ref: F)	0.15	0.07	2.14	0.034	[0.01, 0.29]	1.00	—
	Height	−0.19	0.09	−2.11	0.036	[−0.37, −0.01]	1.45	0.024
	BMI	0.05	0.06	0.83	0.407	[−0.07, 0.17]	1.22	0.002
	SM	0.03	0.07	0.43	0.668	[−0.11, 0.17]	1.67	0.001
	BM	−0.04	0.04	−1.00	0.319	[−0.12, 0.04]	1.38	0.003
ER	Gender (ref: F)	0.21	0.08	2.63	0.009	[0.05, 0.37]	1.00	—
	Height	−0.22	0.10	−2.20	0.029	[−0.42, −0.02]	1.45	0.022
	SM	−0.10	0.09	−1.11	0.268	[−0.28, 0.08]	1.67	0.005
	BM	−0.03	0.05	−0.60	0.549	[−0.13, 0.07]	1.38	0.001
	BMI	0.07	0.07	1.00	0.319	[−0.07, 0.21]	1.22	0.003
DERS-E	Gender (ref: F)	0.32	0.08	4.00	<0.001	[0.16, 0.48]	1.00	—
	Height	−0.24	0.09	−2.67	0.008	[−0.42, −0.06]	1.45	0.031
	SM	−0.16	0.08	−2.00	0.047	[−0.32, −0.00]	1.67	0.015
	BM	−0.02	0.04	−0.50	0.618	[−0.10, 0.06]	1.38	0.001
	BMI	0.06	0.06	1.00	0.319	[−0.06, 0.18]	1.22	0.003

Note. β = Standardized Coefficient; SE = Standard Error; VIF = Variance Inflation Factor (all < 1.7, indicating no multicollinearity issues); ΔR² = unique variance explained by each predictor after controlling for gender. Significant predictors (p < 0.05) are highlighted in bold. DV = Dependent Variable; SR = Suicide Risk; ED = Emotional Dyscontrol; EC = Emotional Confusion; ER = Emotional Rejection; DERS-E = Emotional Regulation Difficulties Scale Average. All models control for gender (reference category: Female). Only body composition variables that showed significant bivariate correlations (p < 0.05) with at least one dependent variable in preliminary analyses were included as predictors in these regression models.

). The results indicated that, after adjusting for gender, the previously significant associations between SR and skeletal muscle (SM: β = −0.08, p = 0.112) and basal metabolism (BM: β = −0.05, p = 0.213) were no longer statistically significant. Gender emerged as a significant predictor of SR (β = 0.42, p < 0.001), with women reporting higher scores. In contrast, several associations between body composition variables and emotional dysregulation dimensions remained significant after controlling for gender: BMI negatively predicted emotional dyscontrol (ED: β = −0.21, p = 0.003); height negatively predicted emotional confusion (EC: β = −0.19, p = 0.036) and emotional rejection (ER: β = −0.22, p = 0.029); and both height (β = −0.24, p = 0.008) and skeletal muscle (β = −0.16, p = 0.047) negatively predicted the total DERS-E score. An analysis of variance inflation factors (VIFs) confirmed that multicollinearity was not problematic in the models (all VIFs < 1.7).

4. Discussion

The results suggest that although body age and BMI do not vary between genders, this is consistent with other studies that support the fact that BMI is not a differentiating factor between males and females [30]. However, different aspects of body composition do differ between males and females, such as body fat. One study indicates that women tend to have about 10% more fat mass than men [31]. This situation may be due to females having lower basal fat oxidation, which favors greater fat accumulation, thus leading to greater risks of obesity [32,33]. Furthermore, in line with the research results, one study revealed that men tend to have higher levels of weight, height, skeletal muscle, visceral fat, and basal metabolism, and a lower percentage of body fat compared to women, who reported higher percentages, which is consistent with previous studies [34,35]. Finally, the findings indicate that men’s basal metabolism is higher than that of women, which is consistent with studies on body composition in various age groups [36,37]. According to the literature, each of these findings is related to and consistent with the biological differences between men and women [6,38,39,40,41,42].

In this research, women reported higher levels of rejection, lack of control, and emotional interference and a higher overall average on the emotional dysregulation scale, which is consistent with studies indicating that there are statistically significant differences between men and women in the factors of emotional rejection, emotional dyscontrol, everyday interference, and overall average dysregulation. These results contrast and agree with research describing gender differences, where women show higher levels of emotional dysregulation compared to men [21]. Another study conducted on physical education pre-service teachers reported discrepancies with this research, as it indicated that there are no significant differences by age and sex [43]. Likewise, in a sample of teachers, statistically significant differences by gender were reported in the factors of rejection, interference, inattention, dyscontrol, and confusion [16], which is consistent with the findings of this study that higher levels of dysregulation are found in females. This situation suggests that women are more negative about their own emotions, feel greater interference in their daily behaviors, and report less clarity about what they are feeling compared to men [20].

Regarding suicide risk analysis, it was found that men tend to regulate their emotions better and women are at greater risk of suicide, which is consistent with studies reporting a higher prevalence of emotional symptoms and suicide risk in women [44]. This problem has increased considerably over the years, with around 800,000 people worldwide reporting suicide each year, making it the second leading cause of death among young people between the ages of 15 and 29 [44]. In this vein, the results of this research showed that suicide risk is positively associated with emotional rejection, emotional dyscontrol, emotional interference, and average emotional dysregulation. In contrast, it is negatively related to emotional inattention and confusion. This finding is striking, as it contradicts the expectation that all dimensions of emotional dysregulation would be positively associated with suicide risk, and could be explained by collinearity phenomena or specific characteristics of the sample. Multiple regression analyses controlling for gender, however, provide critical clarification: while emotional dysregulation dimensions (particularly emotional rejection) maintained significant associations with suicide risk after adjustment, the bivariate associations between body composition indicators (skeletal muscle and basal metabolism) and suicide risk were no longer statistically significant when gender was included as a covariate. This pattern indicates that the observed physical health–suicide risk link is largely mediated by gender differences in both body composition and psychological reporting, rather than representing a direct physiological pathway.

Likewise, significant correlations were found between suicide risk and certain body composition variables, with negative associations observed with skeletal muscle and basal metabolism, and a positive association with body fat. These suggest that poorer physical condition is associated with higher suicide risk, while better physical condition is linked to lower risk in this sample. The observed associations align with a biopsychosocial understanding of health, where physical state and psychological well-being are interconnected. Indicators of better metabolic and muscular health, such as higher skeletal muscle mass and basal metabolic rate, may reflect an underlying physiological resilience and a lifestyle involving regular physical activity. Such a profile is consistently linked in the literature to enhanced psychological well-being, better stress regulation, and a more positive self-concept, all factors that can mitigate suicidal ideation. Conversely, a higher body fat percentage may not only reflect sedentary habits but also correlate with psychosocial stressors and a physiological state that exacerbates emotional vulnerability. This perspective is also linked to emotional well-being, where high suicide risk is associated with lower levels of emotional clarity and regulation [45].

Discrepancies have also been found in the findings of this study, with statistical evidence reported that university students who died by suicide were more likely to be men who had failed and repeated academic programs, changed personal life plans, and/or dropped out of their studies [46,47]. Another study of a sample of university students found that women between the ages of 23 and 29 were prone to suicide risk, highlighting that for every man, there are three women at high risk of suicide [48]. In this regard, it is essential to note that suicidal ideation is a fundamental aspect to be studied in university contexts as a mental pathology that can lead to attempted or completed suicide, since it could be associated with the high levels of stress and adversity that accompany academic life [49].

Gender and certain physiological variables are significantly associated with emotional regulation and suicide risk, reinforcing the need for a biopsychosocial approach to assessing psychological well-being. This view is based on the fact that better physical condition and body composition are associated with greater emotional well-being and lower suicide risk, given that an active lifestyle is valued as a tool for optimizing mental functioning, feelings of satisfaction, and mental health [49,50,51], also considering that some variables associated with body composition correlate positively (for example, body fat) and negatively (for example, basal metabolism, skeletal muscle) with emotional dysregulation. Thus, the specific correlations found between body composition metrics and suicide risk are not merely coincidental but can be interpreted as manifestations of the intricate link between physical health and psychological vulnerability. A healthier body composition likely contributes to a more robust foundation for emotional regulation and resilience against suicidal thoughts, operating through intertwined biological, psychological, and behavioral pathways. A study conducted at a university reported that physically active students show higher scores in self-esteem, life satisfaction, clarity, and emotional repair [52]. This fact supports the existence of a link between physical health and emotional and psychological well-being, meaning that emotional health cannot be dissociated from physical health [53,54,55].

The limitations of this research are primarily related to its cross-sectional design, which precludes the establishment of causal relationships. Additionally, as this study was conducted as a pilot investigation, the sample size and contextual scope were limited, thereby restricting the generalizability of the findings to other populations and settings. Specifically, the non-probabilistic sample of 174 participants, while adequate for descriptive, comparative, and correlational analyses, limits the statistical power for more complex multivariate explanatory models. The exploratory regression analyses conducted, while controlling for gender, represent an important methodological strength that addresses a key critique of bivariate correlation findings in this field. However, these analyses were limited to a subset of variables and did not include potential interaction effects or more comprehensive multivariate models. Therefore, the findings should be interpreted with caution, particularly regarding the relationships between body composition indicators and suicide risk, which were shown to be influenced by gender differences within the sample. Important potential confounding variables were not assessed, including pre-existing psychiatric diagnoses, the use of psychotropic medication, or other clinical factors known to influence both emotional regulation and suicide risk. Furthermore, body composition was assessed using a commercial bioelectrical impedance device (OMRON 514C). While practical for field-based research, this method is less precise than clinical-grade techniques such as dual-energy X-ray absorptiometry (DEXA) and may be affected by factors such as hydration status. Future research should incorporate larger and probabilistic samples, include a broader range of sociodemographic and clinical variables (e.g., socioeconomic status, medical history), and apply more comprehensive multivariate models that test for mediation and moderation effects. Specifically, future studies should examine whether gender moderates the relationship between body composition and mental health outcomes, and explore potential physiological mediators (e.g., inflammatory markers, neuroendocrine function) that might explain the residual associations observed between certain body metrics and emotional regulation. Despite these limitations, the present study contributes exploratory evidence to an emerging interdisciplinary field that integrates bodily and emotional dimensions in the understanding of suicide risk among university students while demonstrating the critical importance of statistical control for gender in such investigations.

5. Conclusions

Gender appears to be a key factor in emotional regulation and suicide risk. The differences observed in this study underscore the need for gender-sensitive interventions that promote emotional well-being and mental health self-care. The tendency for women to report greater difficulties in self-regulation may reflect sociocultural patterns of emotional expression or gender-specific psychosocial vulnerabilities. Interventions should adopt an interdisciplinary approach, integrating evidence-based strategies from psychology, nutrition, physical activity, preventive medicine, and other relevant fields.

Considering the associations identified in this study, body composition and emotional regulation are linked, highlighting the importance of examining these factors in clinical, educational, and preventive contexts. Cross-sectional associations suggest that indicators of better physical condition—such as higher skeletal muscle mass and basal metabolic rate, alongside lower body fat—are associated with lower suicide risk. These findings emphasize the importance of incorporating biological aspects into mental and emotional health assessments of young adults and university students to develop effective, context-sensitive prevention programs at both public policy and educational levels.

Moreover, these results point to the need to consider additional variables that may influence both body composition and mental health outcomes, including nutritional status, body image perception, physical activity levels, sedentary behavior, and socioeconomic status. In summary, significant gender differences were observed in body composition, emotional dysregulation, and suicide risk. Associations were found between body composition variables—particularly BMI, body fat, and skeletal muscle—and emotional aspects, indicating that higher muscle mass and basal metabolism are linked to lower suicide risk, whereas higher body fat is associated with higher risk. These findings underscore the urgent need for prevention and self-care strategies grounded in a biopsychosocial and integrative model.