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# Occupational Health among People with Obesity

Francesca Ingegnere, Selene Macrì, Francesca Bruno, Martina Barbera, Maria

Letizia Caracciolo, Rossella Alfa, Daniele Di Pauli, Amelia Rizzo

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## To cite this version:

Francesca Ingegnere, Selene Macrì, Francesca Bruno, Martina Barbera, Maria Letizia Caracciolo, et al. Occupational Health among People with Obesity. Advances in Medicine, Psychology, and Public Health, 2025, 3 (1), pp.99-112. 10.5281/zenodo.16756026. hal-05281527

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https://hal.science/hal-05281527v1

Submitted on 24 Sep 2025

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# Occupational Health among People with Obesity

Francesca INGEGNERE<fnref n="1" />, Selene MACRI<fnref n="2" />, Francesca BRUNO<fnref n="3" />*, Martina BARBERA<fnref n="4" />, Maria Letizia CARACCIOLO<fnref n="5" />, Rossella ALFA<fnref n="6" />, Daniele DI PAULI<fnref n="7" />, Amelia RIZZO<fnref n="8" />

## Abstract

**Introduction:** Obesity is a medical condition that has reached epidemic proportions globally, significantly impacting individuals' quality of life, social engagement, and occupational health. This study aims to explore the relationship between employment status and perceived quality of life among individuals with obesity, focusing on both physical and mental health aspects.

**Methods:** The study recruited 121 Italian adults with obesity through an online survey conducted between January and June 2024. Participants were selected based on specific criteria: aged 18-65 years, with a BMI of ≥ 30, and willing to complete the questionnaire. The sample was predominantly female (68.6%), with an average age of 40.91 years. Measures included the anagraphic sheet, the SF-36 Health Survey to assess perceived health status across eight domains, and the Beck Depression Inventory (BDI) to evaluate depressive symptoms.

**Results:** Data analysis involved comparing SF-36 scores between employed (N=53) and unemployed (N=58) individuals with obesity. Chi-square tests were used to assess the significance of differences across the eight SF-36 dimensions. Correlations between BDI scores and SF-36 dimensions were also analyzed to understand the relationship between depressive symptoms and

<footnote n="1">¹Department of Philosophy, Social, Human and Educational Sciences, University of Perugia, Italy. E-mail: francescaingegnere00@gmail.com.</footnote>

<footnote n="2">²Department of Cognitive Sciences, Pedagogical Psychological and Cultural Studies, University of Messina, Messina, Italy. E-mail: selene.macri@studenti.unime.it.</footnote>

<footnote n="3">³Department of Cognitive Sciences, Pedagogical Psychological and Cultural Studies, University of Messina, Messina, Italy. E-mail: francesca.bruno3@studenti.unime.it. ORCID: 0009-0007-1842-2470.</footnote>

<footnote n="4">⁴Department of Cognitive Sciences, Pedagogical Psychological and Cultural Studies, University of Messina, Messina, Italy. E-mail: martinabarbera17@gmail.com. ORCID: 0009-0008-6872-7931.</footnote>

<footnote n="5">⁵MD, Specialist in Psychiatry, Provincial Health Authority of Messina, Messina, Italy. ORCID: 0000-0002-2808-7035.</footnote>

<footnote n="6">⁶CRPG Center for Group Psychoanalytic Research, IIPG Italian Institute of Group Psychoanalysis, Messina. E-mail: rossellaalfa2@gmail.com ORCID: 0000-0003-3958-726X.</footnote>

<footnote n="7">⁷Psychologist, CBT Psychotherapist. Trainer at the Specialistic School of Cognitive Psychotherapy, Verona, Italy. E-mail: danieledipauli@hotmail.com ORCID: 0009-0004-5703-0830.</footnote>

<footnote n="8">⁸National Institute of Social Welfare, Messina, Italy. Department of Clinical and Experimental Medicine University of Messina, Messina, Italy. E-mail: amrizzo@unime.it. ORCID: 0000-0002-6229-6463.</footnote>

<footnote>* Corresponding Author</footnote>
perceived quality of life. The results indicated significant differences in physical functioning, bodily pain, vitality, social functioning, and role emotional dimensions, with employed individuals reporting better outcomes. Higher levels of depressive symptoms were associated with lower perceived quality of life across all SF-36 dimensions, with stronger correlations observed in the unemployed group.

**Discussions and Conclusions:** The findings suggest that employment status significantly influences the perceived quality of life among individuals with obesity. Employed individuals tend to report better physical and mental health outcomes compared to their unemployed counterparts. These results highlight the need for integrated interventions that address both obesity management and support for labor market inclusion to improve overall well-being in this population.

**Keywords:** Depression; Employment Status; Obesity; Quality of Life; SF-36 Health Survey.

**Cite this paper as:** Ingegnere F, Macri S, Bruno F, Barbera M. Caracciolo ML, Alfa R, Di Pauli D, Rizzo A. Occupational Health among People with Obesity. Adv Med Psychol Public Health. 2026;3(1):99-112. Doi:10.5281/zenodo.16756026

Received: 10 September 2024; Revised: 15 December 2024; Accepted: 30 March 2025; Published Online: 06 August 2025

## INTRODUCTION

Obesity is a medical condition that has gained massive, epidemic proportions across the world due to serious and adverse impacts on quality of life, social engagement, and healing in the workplace [1]. The WHO defines obesity as a body mass index higher than 30, which brings with it an augmented risk of various diseases: cardiovascular illnesses, type 2 diabetes, and several types of cancer [2].

The quality of life of obese people is in general impaired by physical and psychological conditions. On a physical level, being overweight may limit movement, reduce physical endurance, and even increase pain, which negatively influences the ability to perform everyday and work-related activities [3].

From a psychological point of view, obesity is often associated with depression, anxiety, and lowered self-esteem, combined with social condemnation and discrimination [4]. All these elements create a vicious circle that can lead to further degradation of mental and physical health [5].

Obesity can be a significant hindrance to social and professional life [6,7]. It creates problems not only of a physical nature, when modern cities and offices are not designed for an individual with obesity, but also social and psychological ones [8,9]. The negative attitudes associated with obesity may lead to social exclusion, marginalization, and reduced opportunities for employment. Bases for discrimination in employability and further limiting opportunities are common in work environments where obese people are involved. The stigma of obesity underpins and authorizes social attitudes to an individual with this condition and directly affects many aspects of their life, including not only access to appropriate jobs and general working conditions but also the quality of that environment [10].

The stigma against obesity, as underlined by Puhl and Heuer [11], goes far beyond surface judgment; it is deeply ingrained in the culturally propagated biases that frame obesity as a deficiency in individual self-control or willpower and not as something multifaceted, shaped by genetic and environmental impacts, and affecting psychological conditions. Brownell and colleagues [12] discuss different contexts of demonstrating stigma against patients with obesity, particularly the workplace where these individuals can be discriminated against in a hiring and promotion process, in addition to the
everyday treatment by coworkers and managers. Such discrimination decreases one's career outlook and heightens the psychological pressure that living with obesity implies, thus leading into a vicious cycle of stress and weight gain. In the domain of job work, the research conducted by Rebecca Puhl and Chelsea Heuer [13] illustrates how individuals who are obese are often perceived as less capable to perform specific jobs, particularly high-visibility ones or jobs involving bodily exertion.

However, studies such as "Discrimination and Obesity" from Sutin et al. [14] show that it is not really obesity that leads to lowered productivity in the work environment, so such negative perception may be influenced by bias as opposed to actual research results.

Redressing of the apparent stigma of obesity necessitates changes in the individual and societal attitudes. These will form the main strategies in realization of public change, as identified in the analysis by Tomiyama and colleagues [15]. Community education on the true causes of obesity and creating an inclusive and supportive working environment are key interventions to reduce the weight of stigmatization and improve health outcomes among the obese. A related study by Trogdon, Finkelstein, Hylands, and Dellea [16] also highlighted that high rates of absenteeism caused by obesity require employers to spend vast resources in the event productivity goes down. Surveys indicate that obesity-related absenteeism is reduced through targeted healthy lifestyles programs, hence ultimately improving productivity among employees. Gates et al. [17] discovered that obesity puts people at risk of workplace injuries, more so of movement and physical expenditure, attributed to the physical constraints posed by obesity.

The properly adapted workplaces to the needs of people with obesity may not only be a matter of justice but a good investment. The International Labour Organization highlights inclusion as the domain that underscores the importance of fostering workplace settings capable of supporting physical diversity to maximize productivity and minimize disability-and health-related costs [18].

The creation of an inclusive and nondiscriminatory workplace not only improves the well-being of individual employees but also helps raise productivity at a broader level. It has been supported by the fact that a respectful and supportive work environment increases both employee satisfaction and engagement and thus contributes positively toward organizational performance [19].

In conclusion, obesity is a comprehensive condition that adversely affects the quality of life, social interaction, work participation, and general health of the affected. Destigmatizing and promoting societal and professional environments with supports inclusive to human beings suffering from obesity will add value not only to their health but also to social cohesion and the well-being of society.

An individuals' employment status can be a likelihood of overall health quality, exposure to if working versus not working has had out great effect on health.

For example, the routines and networks of socialization of working individuals likely make for a more routine life with purpose or can help mental health and well-being [20]. Alternatively, the physical qualities and stress of employment may impact in ways that heighten physical health vulnerabilities from obesity. In this way, the type and depth of employment may either enhance or diminish health, encapsulated as a 'phenomenon' [21].

In contrast, social isolation and economic deprivation caused by unemployment due to obesity-related stigma or discrimination could result in the erosion of time minimizing activities, a lack of order in daily life compared to working individuals (environmental factors that severely weigh on physical, mental); this may worsen physical and mental health leading additional health issues and quality of life [22].

It indicates that health quality is an important consideration for the extension of interventions focused on employment status due to, at least in part, the complexity in relation to the working environment and its ability to facilitate or impede health outcomes for people with obesity. For this reason, understanding the role of occupational status in predicting health
quality is crucial for addressing the holistic needs of individuals affected by obesity, ensuring that both work and non-work environments contribute to improving their overall health outcomes.

Though literature has an abundance of content on the influence of obesity on health and work-related issues, there are still some significant gaps that need to be filled.

For example, even though it is known that the stigma of obesity negatively impacts social and professional relations [23], little research exists that investigates whether this stigma leads to discrimination during different phases of a person's career, such as hiring, promotion, or just being treated as an employee. Stigma appears to have practical implications in a work setting that are not well studied, and further focused research is required in order to comprehend these issues more comprehensively.

Additionally, even though some studies like Kolotkin & Andersen [24] associate obesity with low quality of life, the effects of comorbid physical and psychiatric disorders of obesity like depression, anxiety, diabetes, cardiovascular disease, and their effects on occupational performance seem to be understudied. This range of studies is important in understanding the context of obesity in occupational settings and should be conducted more.

The literature has also identified the increased risk of absenteeism and workplace injuries associated with obesity [17] yet there is still a lack of comprehensive research on the long-term effects of obesity on workplace productivity, job satisfaction, and career advancement. Most of the studies focus on short-term outcomes like absenteeism, but there is a need for longitudinal studies that assess the full scope of obesity's impact on professional life over time.

Lastly, while some research has examined the physical barriers in work environments [25], very few studies address the broader issue of workplace adaptations for employees with obesity.

The hypothesis underlying this study is that employment status is a significant determinant of perceived quality of life in individuals with obesity, differentially affecting both physical and mental health. Specifically, it is hypothesized that unemployed individuals with obesity will score lower on the SF-36 subscales compared to those who are employed, reflecting greater psychophysical vulnerability. However, it is also assumed that even among those who are employed, individuals with obesity may experience specific challenges related to their condition, which negatively impact their overall well-being. The aim is therefore to explore whether, and to what extent, employment can act as a protective factor, while also recognizing the need for targeted interventions to adequately support this population in the workplace.

# METHODS

## Procedure

The study belongs to the project "Breaking the Weight Stigma: A Psychosocial Education Program for Psychology Students" registered in OSF on 2023-05-13 at the following link: OSF | Breaking the Weight Stigma: A Psychosocial Education Program for Psychology Students.

The study aimed to recruit Italian adult individuals affected by obesity through an online survey, opened in January 2024 and closed in June 2024. A questionnaire was designed using Google Forms, including an informed consent section. Specifically, an anagrapic sheet, self-assessment scales and questionnaires were administered, allowing for a multidimensional clinical evaluation of the psychological characteristics relevant to health quality.

Participants had to read and accept the research purpose and ethical information before accessing the survey. The survey was distributed via social media, particularly in groups and pages dedicated to people with obesity or those awaiting surgical treatment. Selection was based on a demographic form, ensuring only individuals meeting the criteria were recruited: aged 18-65 years, with a BMI of ≥ 30, willing to complete the questionnaire, and who accepted the informed consent. A non-probability convenience sampling method was used, as participants were recruited through dedicated social media groups, representing an easily accessible sample interested in the study topic. The final sample was automatically selected based on the demographic form.
## Measures

The demographic form was structured to collect essential background information from participants. The first section concerned the Education Level, where participants indicated their highest level of completed education, with options ranging from elementary school certificate (code 1) to postgraduate qualification (code 9). The second section recorded the Gender of the participants, coded as 1 for male and 2 for female. The third section addressed the Occupational Status, offering choices among employed (1), unemployed (2), retired (3), or student (4). The fourth section captured the Marital Status, with options for married (1), single (2), widowed (3), or divorced (4). The fifth section collected information on Previous Dieting Experiences, where participants indicated "No" (0) or "Yes" (1) to whether they had engaged in dieting in the past. Finally, the form classified participants based on their Body Mass Index (BMI), distinguishing between overweight (1) for a BMI between 25 and 30, and first-degree obesity (2) for a BMI between 30.1 and 34.9.

**SF-36 Health Survey.** The Short Form-36 Health Survey (SF-36; Ware & Sherbourne, [26]) was used to assess participants' perceived health status. The instrument evaluates eight domains: Physical Functioning, Role Physical, Bodily Pain, General Health, Vitality, Social Functioning, Role Emotional, and Mental Health. Two summary measures can also be derived: the Physical Component Summary (PCS) and the Mental Component Summary (MCS). The Italian validation by Apolone and Mosconi [27] demonstrated good psychometric properties, with Cronbach's alpha coefficients for the subscales ranging from 0.73 to 0.93, indicating satisfactory to excellent internal consistency.

**Beck Depression Inventory (BDI).** Depressive symptoms were measured using the Beck Depression Inventory (BDI; Beck et al., [28]), a 21-item self-report questionnaire designed to evaluate cognitive, affective, and somatic symptoms of depression. The original version of the BDI demonstrated high internal consistency, with Cronbach's alpha values between 0.86 and 0.93. The Italian adaptation by Sica and Ghisi [29] confirmed the reliability of the instrument, reporting internal consistency indices comparable to those of the original version.

## Participants

The study sample consists of 121 participants. The gender distribution is skewed towards females, who make up 68.6% of the sample, while males represent 31.4%. The average age of participants is approximately 40.91 years with a standard deviation of 11.08, indicating a moderately varied age range, spanning from 18 to 62 years.

In terms of educational background, the majority of participants hold a high school diploma (39.67%), followed by those with a lower secondary school diploma (32.23%). A small portion has attained higher education, with 5.79% holding a master's degree, and 1.65% a bachelor's degree. Notably, 9.92% of responses regarding education were missing.

Regarding employment status, 43.8% of participants are employed, while 47.93% are unemployed. A small number are students (1.65%), and no participants reported being retired. 6.61% did not provide employment information.

In terms of marital status, over half of the participants are married (52.07%), while 19.01% are single. Smaller proportions are divorced (8.26%) or widowed (1.65%), with 19.01% of responses missing.

When asked about previous dieting experience, 56.2% reported having dieted before, while only 9.92% said they had not. However, a significant 33.88% did not respond to this question.

Finally, the BMI distribution reveals that the majority of the sample falls into the Class III obesity category (61.16%), followed by Class II obesity (31.4%). Only 0.83% are overweight or in Class I obesity, and 5.79% of BMI data is missing. This indicates a sample heavily skewed toward individuals with severe obesity.
<table><caption>**Table 1.** Sample characteristics.</caption><thead><tr><th>Section</th><th>N</th><th>Percentage (%)</th></tr></thead><tbody><tr><td>Sample Size</td><td>121</td><td>-</td></tr><tr><td>Gender - Female</td><td>83</td><td>68,6</td></tr><tr><td>Gender - Male</td><td>38</td><td>31,4</td></tr><tr><td>Age - Mean</td><td>40,91</td><td>-</td></tr><tr><td>Age - Standard Deviation</td><td>11,08</td><td>-</td></tr><tr><td>Age - Minimum</td><td>18</td><td>-</td></tr><tr><td>Age - Maximum</td><td>62</td><td>-</td></tr><tr><td>Education - Primary School Diploma</td><td>4</td><td>3,31</td></tr><tr><td>Education - Lower Secondary School Diploma</td><td>39</td><td>32,23</td></tr><tr><td>Education - High School Student</td><td>5</td><td>4,13</td></tr><tr><td>Education - High School Diploma</td><td>48</td><td>39,67</td></tr><tr><td>Education - University Student</td><td>3</td><td>2,48</td></tr><tr><td>Education - Bachelor's Degree</td><td>2</td><td>1,65</td></tr><tr><td>Education - Undergraduate Degree (3 years)</td><td>1</td><td>0,83</td></tr><tr><td>Education - Master's Degree</td><td>7</td><td>5,79</td></tr><tr><td>Education - Postgraduate Degree</td><td>0</td><td>0</td></tr><tr><td>Education - Missing Responses</td><td>12</td><td>9,92</td></tr><tr><td>Occupation - Employed</td><td>53</td><td>43,8</td></tr><tr><td>Occupation - Unemployed</td><td>58</td><td>47,93</td></tr><tr><td>Occupation - Retired</td><td>0</td><td>0</td></tr><tr><td>Occupation - Student</td><td>2</td><td>1,65</td></tr><tr><td>Occupation - Missing Responses</td><td>8</td><td>6,61</td></tr><tr><td>Marital Status - Married</td><td>63</td><td>52,07</td></tr><tr><td>Marital Status - Single</td><td>23</td><td>19,01</td></tr><tr><td>Marital Status - Widowed</td><td>2</td><td>1,65</td></tr><tr><td>Marital Status - Divorced</td><td>10</td><td>8,26</td></tr><tr><td>Marital Status - Missing Responses</td><td>23</td><td>19,01</td></tr><tr><td>Previous Dieting - Yes</td><td>68</td><td>56,2</td></tr><tr><td>Previous Dieting - No</td><td>12</td><td>9,92</td></tr><tr><td>Previous Dieting - Missing Responses</td><td>41</td><td>33,88</td></tr><tr><td>BMI - Overweight</td><td>1</td><td>0,83</td></tr><tr><td>BMI - Class I Obesity (30.1 - 34.9)</td><td>1</td><td>0,83</td></tr><tr><td>BMI - Class II Obesity (35 - 39.9)</td><td>38</td><td>31,4</td></tr><tr><td>BMI - Class III Obesity (40+)</td><td>74</td><td>61,16</td></tr><tr><td>BMI - Missing Responses</td><td>7</td><td>5,79</td></tr></tbody></table>
## Ethical considerations

Ethical considerations included data confidentiality, voluntary participation with the option to withdraw without consequences, and ensuring participants were fully aware of the study's purpose and data handling. All information collected in this research have been treated in compliance with Italian regulations on personal data protection (Legislative Decree 196/2003) and Article 9 of the Italian Psychologists' Code of Ethics. Personal data have been handled with the utmost confidentiality and used solely for research purposes. Participants had the right to exercise their rights under Legislative Decree 101/2018, which adapts the Personal Data Protection Code to EU Regulation 2016/679, at any time. Furthermore, being an online survey the study was conducted following the 'Ethical Guidelines 3.0 for Internet Research' published by the Association of Internet Researchers (AoIR).

## RESULTS

### SF-36 scores by employment status in individuals with obesity

The analysis of SF-36 scores among individuals with obesity, categorized by employment status, provides a nuanced perspective on the potential influence of work on perceived quality of life. The eight subscales of the SF-36 assess key dimensions of physical, psychological, and social well-being. The results reveal significant differences between employed and unemployed individuals, suggesting that employment may serve as a protective factor across multiple domains of health.

Employed individuals with obesity report a higher frequency of elevated scores in the subscale measuring the extent to which health limits physical activities (34.0% vs. 31.5%), and even more notably, in the subscale assessing the extent to which physical health interferes with work activities (50.9% vs. 34.5%). These findings suggest that being employed may be associated with a more favorable perception of physical functioning and the ability to perform daily tasks. A supportive work environment may encourage an active lifestyle and help preserve functional autonomy.

Conversely, unemployed individuals with obesity report a higher proportion of elevated scores in the subscale related to pain intensity and its impact on usual work (27.6% vs. 24.5%), as well as in the general health perception subscale (29.3% vs. 26.4%). This may reflect reduced exposure to physical strain or occupational stress, potentially leading to a more favorable subjective perception of pain and overall health. However, these differences are modest and not necessarily indicative of better overall well-being.

The subscale measuring vitality—feeling energetic, lively, and enthusiastic—shows similar values between the two groups (27.6% for employed vs. 25.9% for unemployed), indicating that fatigue is a common experience among individuals with obesity, regardless of employment status. However, employed individuals report higher scores in the subscale assessing the extent to which physical or emotional health limits daily activities (58.5% vs. 53.4%), suggesting a greater capacity to maintain social relationships and participate in community life.

The most pronounced differences emerge in the psychological dimensions. Employed individuals with obesity show a higher frequency of elevated scores in the subscale measuring the extent to which emotional problems interfere with work (51.9% vs. 47.4%) and in overall mental health status (47.2% vs. 31.0%). These results indicate that employment may offer significant benefits in terms of emotional stability, self-esteem, and psychological resilience. The workplace can provide structure, a sense of belonging, and opportunities for personal fulfillment—key elements for mental well-being.
<table><caption>**Table 2.** Chi-Square Test Statistics.</caption><thead><tr><th></th><th>Chi-Square</th><th>df</th><th>Asymp. Sig.</th></tr></thead><tbody><tr><td>Physical Functioning</td><td>8,610<sup>a</sup></td><td>2</td><td>,013</td></tr><tr><td>Role Physical</td><td>3,390<sup>b</sup></td><td>2</td><td>,066</td></tr><tr><td>Bodily Pain</td><td>20,051<sup>a</sup></td><td>2</td><td>,000</td></tr><tr><td>General Health</td><td>5,203<sup>a</sup></td><td>2</td><td>,074</td></tr><tr><td>Vitality</td><td>8,661<sup>a</sup></td><td>2</td><td>,013</td></tr><tr><td>Social Functioning</td><td>41,559<sup>a</sup></td><td>2</td><td>,000</td></tr><tr><td>Role Emotional</td><td>15,224<sup>c</sup></td><td>2</td><td>,000</td></tr><tr><td>Mental Health</td><td>3,780<sup>a</sup></td><td>2</td><td>,151</td></tr></tbody></table>

*Note:* 0 cells (0,0%) have expected frequencies less than 5. The minimum expected cell frequency is 39,3. b. 0 cells (0,0%) have expected frequencies less than 5. The minimum expected cell frequency is 59,0. c. 0 cells (0,0%) have expected frequencies less than 5. The minimum expected cell frequency is 38,7.

The statistical analysis conducted using the Chi-square test assessed the significance of differences between employed and unemployed individuals with obesity across the eight dimensions of the SF-36. The results indicate that while some differences are statistically significant, others do not reach the conventional threshold for significance (p < 0.05), suggesting a differential impact of employment status on various aspects of perceived health. Specifically, statistically significant differences were observed in the subscales of Physical Functioning (p = 0.013), Bodily Pain (p < 0.001), Vitality (p = 0.013), Social Functioning (p < 0.001), and Role Emotional (p < 0.001). These findings indicate that employment status is significantly associated with perceptions of physical functionality, pain intensity, energy levels, social participation, and the ability to fulfill emotional roles. In other words, unemployed individuals with obesity report significantly poorer outcomes in these areas compared to their employed counterparts. Conversely, differences in the subscales of Role Physical (p = 0.066), General Health (p = 0.074), and Mental Health (p = 0.151) were not statistically significant. Although trends in these dimensions align with the initial hypothesis—namely, that unemployed individuals perceive worse health—the results do not meet the threshold for statistical significance, suggesting that these outcomes may be influenced by uncontrolled variables or that the effect of employment status on these aspects is less pronounced.
<figure><img src="image_5.png" /><figcaption>**Figure 2.** SF-36 low scores comparison.</figcaption></figure>

<figure><img src="image_6.png" /></figure>
Relationship between employment status and depression

The analysis of correlations between Beck Depression Inventory (BDI) scores and SF-36 dimensions in a sample of individuals with obesity, stratified by employment status, reveals a statistically significant inverse relationship in both groups (See Figure 3). In other words, higher levels of depressive symptoms (i.e., higher BDI scores) are associated with lower perceived quality of life across all SF-36 dimensions.

Among employed individuals, all negative correlations are statistically significant (p < 0.001), with moderate to strong effect sizes. The dimensions most strongly associated with depression are Vitality (r = -0.691), Role Emotional (r = -0.671), Social Functioning (r = -0.618), and Mental Health (r = -0.611), suggesting that depressive symptoms substantially affect psychological and relational well-being even among those who are employed.

In the unemployed group, the correlations are even stronger across nearly all dimensions. Notably, high correlation values are observed for Social Functioning (r = -0.735), Vitality (r = -0.666), Role Physical, and Bodily Pain (both r = -0.657), indicating that in unemployed individuals, depression is associated not only with poorer emotional well-being but also with greater impairment in perceived physical health.

<figure><img src="image_7.png" /><figcaption>**Figure 3.** Correlations between BDI Depression Scores and SF-36 for employed and unemployed individuals with obesity.</figcaption></figure>

These findings confirm that depression represents a cross-cutting vulnerability factor in the population with obesity, but they also suggest that unemployment can amplify the negative impact of depressive symptoms across multiple domains of quality of life. Such evidence reinforces the need for integrated interventions that simultaneously address mental health, obesity management, and support for labor market inclusion.

DISCUSSION

Numerous studies suggest a bidirectional relationship between obesity and unemployment, in which each condition may contribute to the onset or persistence of the other. Research by Caliendo et al. [30], Brunello & Labartino [31], and Bruno et al. [32] consistently highlights a close link between employment status and obesity, emphasizing both the barriers posed by discrimination and the negative health effects of unemployment.

Paradoxically, both employment and unemployment can pose risks. However, the aim of the present study was precisely to compare the health status of employed and unemployed individuals with obesity, in order to identify differences in their challenges and explore tailored management strategies.
On one hand, obesity can hinder entry or re-entry into the labor market due to functional limitations, physical and psychological comorbidities, and, importantly, weight-related stigma and discrimination [33]. Individuals with obesity may face greater difficulties accessing certain professions, particularly those requiring high mobility, physical endurance, or a public image aligned with specific standards [34].

On the other hand, unemployment itself can contribute to weight gain through mechanisms related to sedentary behavior, economic instability, chronic stress, and reduced access to healthy lifestyles [35]. This vicious cycle can lead to a progressive deterioration in health and quality of life, making active participation in the workforce even more difficult [36]. In this context, as suggested by Nossum, Johansen & Kjeken [37], it is essential to promote active labor market policies and integrated prevention strategies that simultaneously address employment barriers and the social determinants of obesity.

To our knowledge, this study represents one of the few contributions in the literature that directly compares employed and unemployed individuals with obesity, systematically investigating both physical and mental health aspects. This approach allows for a deeper exploration of the multidimensional implications of obesity in the workplace, highlighting how employment status can significantly influence perceived well-being and quality of life. The comparative analysis conducted using the SF-36 subscales offers an original and relevant contribution to understanding the interactions between health, work, and social vulnerability in a population often overlooked in research.

One particularly noteworthy finding is the statistical significance of the Social Role and Emotional Role dimensions. As is well known, employment plays a key role in shaping identity, social belonging, status, economic power, independence, and societal roles [38].

Moreover, psychological factors reveal a notable presence of depressive symptoms in both employed and unemployed individuals with obesity, underscoring the multifactorial nature of the condition, as widely discussed and established in the literature [39-44].

A study conducted by the National Institute for Occupational Safety and Health (NIOSH) is among the most recent and relevant sources exploring the relationship between employment status and health, including obesity as one of the outcomes. Using data from the Behavioral Risk Factor Surveillance System (2018–2019) [45], researchers found that the prevalence of negative health outcomes — including obesity, poor mental health, and chronic diseases — increases with the duration of unemployment, peaking among those who have been unemployed long-term or report being unable to work.

At the same time, obesity is increasingly recognized as a critical factor in occupational health and safety (OHS). Workers with obesity are more exposed to a range of occupational risks, due to greater susceptibility to musculoskeletal and cardiovascular diseases, as well as reduced mobility and flexibility, which increase the likelihood of workplace injuries. Epidemiological studies have shown that the risk of work-related injuries is up to 48% higher among workers with obesity compared to those of normal weight, with even higher incidence in certain professional categories such as truck drivers, nurses, and firefighters.

## Study limitations

One of the main limitations of this study concerns the observational and cross-sectional nature of the analysis, which does not allow for the establishment of causal relationships between employment status and perceived quality of life in individuals with obesity. The data collected provide a snapshot of a specific moment in time, but do not allow us to determine whether unemployment is a cause or a consequence of deteriorating physical and mental health, or vice versa. Furthermore, the lack of detailed information on potentially confounding variables — such as socioeconomic status, type of employment, duration of unemployment, or the presence of comorbidities — may influence the interpretation of the results.
An additional limitation concerns the representativeness of the sample: although the comparison between employed and unemployed individuals with obesity offers valuable insights, the results may not be generalizable to the entire population with obesity, especially in different cultural, economic, or regulatory contexts. Furthermore, the use of the SF-36, while being a validated and widely used instrument, relies on subjective self-assessments that may be influenced by psychological, social, or environmental factors not directly measured. These limitations highlight the need for further longitudinal and multidimensional studies to deepen the understanding of the relationship between obesity, employment, and health.

## CONCLUSIONS

Despite the findings of our study clearly indicating that individuals with obesity who are unemployed tend to have, on average, poorer physical and mental health compared to those who are employed, it is important to emphasize that employed individuals with obesity are not exempt from challenges. The difficulties they face in the workplace — such as functional limitations, increased risk of injury, chronic comorbidities, and potential experiences of discrimination — can significantly compromise their quality of life and their ability to maintain stable and fulfilling employment.

In light of this, there is a pressing need to develop targeted intervention policies that go beyond obesity prevention and include support for managing the condition and its related symptoms, as well as strategies to promote fair and sustainable employment inclusion (As suggested by Cunningham, Vaquera & Long [46]; Flint & Snook [47]). Such policies should integrate multidisciplinary approaches, involving occupational medicine, psychology, nutrition, and vocational training, in order to create inclusive work environments that value the skills of individuals with obesity while reducing health and safety risks.

**Author Contributions:** Conceptualization: AR. and RA. Methodology: AR. Software: FB. Validation: DDP., MLC. and RA. Formal analysis: MB, FB and AR. Investigation: FI, RA, AR. Resources: SM, FI. Data curation: AR. Writing—original draft preparation: FB, MB, AR, SM, FI. Writing—review and editing: DDP, RA, MLC. Visualization: all authors. Supervision: DDP. Project administration: AR. Funding acquisition: AR. All authors have read and agreed to the published version of the manuscript.

**Acknowledgments:** None

**Conflicts of Interest:** The authors declare no conflict of interest.

**Disclaimer/Publisher's Note:** The Publisher remains neutral regarding jurisdictional claims in published maps and institutional affiliations. Additionally, the Publisher is not responsible for the accuracy, completeness, or validity of the content of scientific articles published herein. This statement exempts the Publisher from any responsibility regarding the content of scientific articles, which is solely the responsibility of the authors and peer reviewers.

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