Is it chicken or the egg: Obesity,anxiety and depression in hospital workers

Abstract

BACKGROUND:

Healthcare workers are susceptible to obesity, anxiety and depression.

OBJECTIVE:

To determine the prevalence and association of obesity, anxiety and depression symptoms in individuals working in a hospital.

METHODS:

In this cross-sectional study all of the employees of a hospital were invited to participate (n = 150). Anxiety (via Beck Anxiety Scale) and depression symptoms (via Beck Depression Scale) and obesity were dependent and independent variables. Obesity was determined both with body mass index (BMI) and abdominal obesity (Waist circumference-WC). Data were collected with face-to-face interviews and anthropometric measurements were done. Data were analyzed using SPSS version 25.0 with student t-test, chi-square and correlation tests. Significance was set at a p-value < 0.05.

RESULTS:

Among the participants who agreed to participate (n = 131, 64.1% females), 35.1% were obese and 50.4% were abdominally obese. The 35.9% had moderate-severe anxiety symptoms, 19.1% had moderate-severe depression symptoms. Both BMI and WC had positive, moderate and significant correlation with anxiety and depression scores. After adjusting for socio-demographic variables obesity (both with BMI and WC) was an independent factor for anxiety and depression symptom presence, whereas after adjusted for these variables anxiety and depression symptom presence was an independent factor for obesity and abdominal obesity (p = 0.001 for all).

CONCLUSIONS:

There is a correlation between anxiety, depression and obesity. In addition to nutrition interventions in combating obesity, services that will improve mental health should be provided together as teamwork.

Keywords

Obesity abdominal obesity anxiety depression hospital workers

1 Introduction

Obesity is ever increasing all over the world, as well as in Turkey [1]. According to National Nutrition and Health Survey (2010) [2] obesity prevalence was found to be 41.0% among women and 20.5% in men, thus, 30.3% in total. According to TURDEP II (2010) [3], the prevalence of obesity was shown to be 36%. Obesity may cause many chronic diseases such as diabetes mellitus, cardiovascular diseases and cancer, which cause complications, require hospitalization, have a high disease burden, decrease quality of life and shorten lifespan [4, 5].

Physical health and mental health goes along together. According to different studies conducted, anxiety and depression symptoms were more prevalent in obese people [6, 7]. In their study on morbid obese patients, Megias et al. [8], stated that obesity causes limitations in movement, stigmatization and social isolation, decrease in self-esteem, thus, anxiety and depression. On the other hand, in study conducted on overweight and obese people, the ones with anxiety and depression had significantly higher means of BMI [9]. In a tertiary university hospital (n = 131, 55% females), a significant positive correlation was found between BMI and depression scale points via Beck Depression Inventory and, as BMI increased the severity of depression symptoms were also significantly increased [10]. Pan et al. [11] evaluated approximately 66 thousands of people in Nurse’s Health Study and concluded that the ones who are obese can be more depressed as well as the ones who are more depressed can tend to be more obese, thus, this relationship can be bidirectional. Similarly Mannan et al. [12], in a meta-analysis of 19 studies, stated that obesity increased depression and depression increased obesity.

Healthcare services have a special place in occupational environment. Recently, increase in burnout, work stress and anxiety in healthcare employees was shown due to necessity of continuous and non-stop service, not tolerating any mistakes, increased workload with long working hours and shift work and increased violence against healthcare workers [13 –16]. Anxiety and depression can be higher than the general population and studies have found that the prevalence of obesity is high in healthcare workers due to these vulnerable working conditions [17, 18]. In a study conducted in Taiwan showed that high stress and low social support may lead to overweight/obesity among nurses [19]. Shift work itself may contribute to obesity by exposure to continuous light during the night, destruction of circadian rhythm, frequent snacks and nocturnal eating habits, nocturnal physical activity, and sleep disorders in healthcare workers [20].

Thus, the objective of this study was to determine the prevalence of obesity, anxiety and depression symptoms in a private hospital and to evaluate the bidirectional association between obesity and anxiety and depression symptoms.

2 Materials and methods

This cross-sectional study was conducted on workers of a private hospital situated in eastern parts of Turkey. All of the employees (health and non-health) (n = 150) were invited to participate in the study and no sample was selected. Physicians, nurses and other health-related personnel was considered as health personnel, whereas the secretaries, janitors etc. were named as non-health personnel Obesity, presence of anxiety symptoms and depression symptoms were both dependent and independent variables for each other. Age, sex, educational and marital status, perceived work stress, income were interrogated as confounding factors. Presence of anxiety symptoms was determined via Beck Anxiety Inventory (BAI) whereas presence of depression symptoms was evaluated with Beck Depression Inventory (BDI). BAI was a 21-item scale with a scoring system of 0–3 points for each item developed by Beck and his colleagues in 1988. Increased score show a more severe situation with cut-off points as “0–7 points Minimal”, “8–15 point Mild”, “16–25 points Moderate” and “26 and above points Severe”. Turkish validity and reliability study was conducted in 1993 by Ulusoy et al. [21].

BDI was first developed in 1961 originally but second version was published by Beck and his colleagues in 1978. This self-administered questionnaire consisted of 21 items, each one defined by a 0–3 points Likert scale, investigating how a person felt within last week. Increased scores show a more severe situation with cut-off points as “0–13 points Minimal”, “14–19 point Mild”, “20–28 points Moderate” and “29 and above points Severe”. Turkish validity and reliability study was conducted in 1988 by Hisli et al. [22, 23]. For both of the scales in the analyses, minimal and mild scores were combined as one group whereas moderate and severe scored were evaluated as one group.

Obesity was evaluated via both body mass index (BMI) and waist circumference (WC) as abdominal obesity. BMI was calculated by dividing weight by height in square meters (kg/m²). According to the World Health Organization (WHO), subjects with a BMI ≥30 kg/m² were classified as obese. Abdominal obesity was defined by WC ≥94 cm in males, and ≥80 cm in females [24]. For perceived work stress, visual analog scale of 0 to 10 points were given and the participants were asked to evaluate their work stress as “0” being at least and “10” being at most. Data were collected by the researchers via face-to-face interview and all anthropometric measurements were conducted by the researchers. Weight was measured by calibrated Tanita BC 730 with light clothes on without shoes. Height was measured by a stadiometer in accordance with Frankfort plane while looking forward and standing still without shoes. WC was measured via non elastic tape in between the inferior margin of the ribs and superior border of the iliac crest bone.

Data were analyzed via SPSS (IBM, Vers 25.0). The association of socio-demographic variables with obesity, anxiety and depression was determined by chi-square tests and Spearman correlation was used in order to evaluate the correlation between BMI, WC, BDI points, and BAI points. After adjusting age, sex and other socio-demographic variables, association between obesity and anxiety and depression was established by logistic regression models. Significance was set at a p-value < 0.05.

Study was approved by an independent ethics committee (Protocol: 274-2017.08/01, date: 12.10.2017). Study was conducted according to Helsinki Declaration and oral and written informed consent was obtained from the participants.

3 Results

Among invited participants, 131 of them agreed to participate in the study. Among them 64.1% (n = 84) were female. Mean age was 30.1 years ±7.0 (min:19-max: 65). About two thirds (60.3%) were married, 66.4% had at least a bachelor’s degree and 46.6% was a health care professional. Nearly half (48.9%) stated that his/her wage is inferior to their expenses. None of the participants were diagnosed with depression or on anti-depressants.

Using BMI, obesity prevalence was 35.1% whereas for abdominal obesity it was 50.4%. Among the participants, 35.9% of them showed moderate and severe anxiety symptoms whereas, for depression it was 19.1%. Association of socio-demographic variables and obesity, anxiety and depression symptoms were shown in Table 1.

Table 1
Association of socio-demographic factors and obesity, abdominal obesity, anxiety symptoms and depression symptoms

All participants Presence of Obesity (BMI) Presence of Abdominal Obesity (WC) Presence of Moderate & Severe Anxiety Symptoms Presence of Moderate & Severe Depression Symptoms

n (%) n % p n % p n % P N % p

Sex 0.056 0.247 0.605 0.252

Female 84 (64.1) 35 41.7 46 54.8 32 38.1 19 22.6

Male 47 (35.9) 11 23.4 20 42.6 15 31.9 6 12.8

Marital status 0.928 0.642 0.290 0.793

Single 52 (39.7) 19 36.5 28 53.8 22 42.3 11 21.2

Married 79 (60.3) 27 34.2 38 48.1 25 31.6 14 17.7

Educational Status 0.117 0.049 0.028 0.604

> 12 years (at least high-school degree) 87 (66.4) 26 29.9 38 43.7 25 28.7 15 17.2

≤12 years 44 (33.6) 20 45.5 28 63.6 22 50.0 10 22.7

Occupation 0.071 0.029 0.020 0.340

Healthcare worker 61 (46.6) 16 26.2 24 39.3 15 24.6 9 14.8

Other 70 (53.4) 30 42.9 42 60.0 32 45.7 16 22.9

Income 1.000 0.430 0.575 0.899

Income≥expenditure 67 (51.1) 24 35.8 31 46.3 22 32.8 12 17.9

Income < expenditure 64 (48.9) 22 34.4 35 54.7 25 39.1 13 20.3

Total 131 (100.0) 46 35.1 66 50.4 47 35.9 25 19.1

	All participants	Presence of Obesity (BMI)	Presence of Abdominal Obesity (WC)	Presence of Moderate & Severe Anxiety Symptoms	Presence of Moderate & Severe Depression Symptoms
Sex				0.056			0.247			0.605			0.252
Female	84 (64.1)	35	41.7		46	54.8		32	38.1		19	22.6
Male	47 (35.9)	11	23.4		20	42.6		15	31.9		6	12.8
Marital status				0.928			0.642			0.290			0.793
Single	52 (39.7)	19	36.5		28	53.8		22	42.3		11	21.2
Married	79 (60.3)	27	34.2		38	48.1		25	31.6		14	17.7
Educational Status				0.117			0.049			0.028			0.604
> 12 years (at least high-school degree)	87 (66.4)	26	29.9		38	43.7		25	28.7		15	17.2
≤12 years	44 (33.6)	20	45.5		28	63.6		22	50.0		10	22.7
Occupation				0.071			0.029			0.020			0.340
Healthcare worker	61 (46.6)	16	26.2		24	39.3		15	24.6		9	14.8
Other	70 (53.4)	30	42.9		42	60.0		32	45.7		16	22.9
Income				1.000			0.430			0.575			0.899
Income≥expenditure	67 (51.1)	24	35.8		31	46.3		22	32.8		12	17.9
Income < expenditure	64 (48.9)	22	34.4		35	54.7		25	39.1		13	20.3
Total	131 (100.0)	46	35.1		66	50.4		47	35.9		25	19.1

BMI: Body mass index, WC: Waist circumference, Bold indicates significant difference, $χ_{Yates,}^{2}$

Low educated personnel and non-health workers were significantly more abdominally obese and showed more moderate and severe anxiety symptoms. Other socio-demographic factors were not found to be significant.

BMI and anxiety and depression scores were significantly and positively correlated (for anxiety rho: 0.559 (p < 0.001); for depression rho: 0.515 (p < 0.001)). Even though correlation coefficients were lower, WC, anxiety and depression scores were also significantly and positively correlated (for anxiety rho: 0.454 (p < 0.001); for depression rho: 0.457 (p < 0.001)) (Table 2.)

Table 2

Correlation between anthropometric indices, anxiety, and depression

	Anxiety	Depression
BMI	0.559 (< 0.001)	0.515 (< 0.001)
WC	0.454 (< 0.001)	0.457 (< 0.001)
Depression	0.725 (< 0.001)	–

BMI: Body mass index, WC: Waist circumference, Spearman’s rho (p).

As obesity prevalence increased moderate & severe anxiety and depression also increased significantly. It was similar for abdominal obesity, the presence of abdominal obesity also increased the presence of moderate & severe anxiety and depression (p < 0.001 for all) (Table 3).

Table 3

Association between obesity, anxiety, and depression

	All participants		Anxiety					Depression
			Minimal & Mild		Moderate & Severe		p	Minimal & Mild		Moderate & Severe		p
	n		n	%	n	%		n	%	n	%
Obesity							< 0.001 ^*					< 0.001 ^*
Thin &Normal	57	43.6	48	84.2	9	15.8		54	94.7	3	5.3
Overweight	28	21.3	19	67.9	9	32.1		24	85.7	4	14.3
Obese	46	35.1	17	37.0	29	63.0		28	60.9	18	39.1
Abdominal obesity							< 0.001					< 0.001
No	65	49.6	53	81.5	12	18.5		62	95.4	3	4.6
Yes	66	50.4	31	47.0	35	53.0		44	66.7	22	33.3

Bold indicates significant difference, $χ_{Yates,}^{2}$ ^* $X_{for trend .}^{2}$

After adjusted for socio-demographic variables significant associations remained (Table 4 5). Obesity (with BMI) increased risk of moderate & severe anxiety by 5.3-fold (95% CI:2.217–12.823) and depression 5.9-fold (95% CI: 2.106–16.417). For abdominal obesity the ratios were 4.1-fold (95% CI: 1.715–9.631) and 9.3-fold (95% CI: 2.483–35.005) respectively. Increment in age was shown to be significantly inversely associated with anxiety but not for depression (Table 4).

Table 4

Factors associated with presence of moderate & severe anxiety and depression symptoms

	Presence of Moderate &Severe Anxiety Symptoms						Presence of Moderate &Severe Depression Symptoms
	Model 1			Model 2			Model 1			Model 2
	OR	95% CI	P	OR	95% CI	P	OR	95% CI	P	OR	95% CI	P
Age (Cont.)	0.892	0.828–0.960	0.002	0.893	0.832–0.959	0.002	0.974	0.899–1.054	0.508	0.968	0.897–1.044	0.399
Sex (Male)	0.917	0.336–2.499	0.865	0.797	0.301–2.112	0.649	0.597	0.185–1.922	0.387	0.546	0.174–1.716	0.300
Educational status (≤High school)	2.425	0.866–6.794	0.092	2.411	0.874–6.648	0.089	0.972	0.305–3.095	0.962	0.949	0.300–2.999	0.929
Occupation (Other)	2.001	0.761–5.260	0.159	1.937	0.752–4.989	0.171	1.219	0.397–3.738	0.730	1.098	0.353–3.414	0.872
Perceived job stress (Cont.)	0.936	0.755–1.160	0.545	0.947	0.764–1.175	0.623	1.225	0.920–1.632	0.165	1.265	0.933–1.717	0.131
Obesity (obese)	5.331	2.217–12.823	< 0.001	–	–	–	5.881	2.106–16.417	0.001	–	–	–
Abdominal obesity (Yes)	–	–	–	4.064	1.715–9.631	0.001	–	–	–	9.324	2.483–35.005	0.001

OR: Odds ratio, CI: Confidence interval, Bold indicates significant difference. Obesity was included in Model 1, whereas abdominal obesity was included in Model 2.

Table 5

Factors associated with obesity

	Obesity						Abdominal Obesity
	Model 1			Model 2			Model 1			Model 2
	OR	95% CI	P	OR	95% CI	P	OR	95% CI	P	OR	95% CI	P
Age (Cont.)	0.997	0.930–1.069	0.932	0.962	0.900–1.029	0.264	1.012	0.952–1.075	0.710	0.990	0.932–1.050	0.732
Sex (Male)	0.277	0.101–0.759	0.013	0.305	0.111–0.837	0.021	0.428	0.177–1.037	0.060	0.486	0.200–1.183	0.112
Educational status (≤High school)	1.498	0.534–4.206	0.442	2.097	0.768–5.728	0.149	1.507	0.553–4.109	0.423	1.913	0.719–5.090	0.194
Occupation (Other)	1.646	0.637–4.251	0.304	1.941	0.758–4.971	0.167	1.677	0.690–4.072	0.254	1.846	0.762–4.468	0.174
Perceived job stress (Cont.)	1.156	0.934–1.430	0.182	1.078	0.8731.331	0.485	1.145	0.937–1.400	0.186	1.082	0.888–1.319	0.433
Presence^* of Anxiety Symptoms	5.394	2.223–13.087	< 0.001	–	–	–	4.211	1.778–9.969	0.001	–	–	–
Presence^* of Depression Symptoms	–	–	–	5.638	2.054–15.476	0.001	–	–	–	8.420	2.308–30.716	0.001

OR: Odds ratio, CI: Confidence interval, Bold indicates significant difference. (^*) Presence of Moderate & Severe symptoms. Presence of Moderate & Severe Anxiety Symptoms was included in Model 1, whereas Presence of Moderate & Severe Depression Symptoms was included in Model 2.

After adjusted for socio-demographic variables, moderate & severe anxiety increased obesity (OR: 5.4; 95% CI: 2.223–13.087) and abdominal obesity (OR:4.2; 95% CI:1,778–9,969) significantly. On the other hand, moderate & severe depression also affected obesity (OR:5.6; 95% CI: 2.054–15.476) and abdominal obesity (OR:8.4; 95% CI: 2.308–30.716) significantly. Being a male decreased risk of obesity significantly but did not affect abdominal obesity (Table 5).

4 Discussion

In this study, obesity, anxiety, and depression among people working in a private hospital was evaluated. After adjusting for socio-demographic factors, it was found that relationship between obesity and anxiety and depression was bi-directional, obesity increased anxiety and depression whereas anxiety and depression increased obesity.

4.1 Obesity

Two nationally representative studies showed that approximately one third of Turkish adults were obese [2, 3]. In a meta-analysis, in which Dilek et al. [25] examined the epidemiological risk factors of cardiovascular diseases, eight studies with low risk of bias (n = 73.906) showed that the frequency of obesity according to BMI was 28.5% (95% CI 24.0–33.2) in the whole group, 33.2% (95% CI 28.8–37.7) in women and 18.2% (95% CI 16.2–20.2) in men. In studies conducted in various countries, it has been stated that the prevalence of obesity in healthcare professionals is higher than in the general population [18 , 27]. Mohanty et al. [14] emphasized in their study that obesity is disproportionately more common in healthcare professionals than the general population, although they are the most informed group about obesity and its possible consequences. In a study conducted on employees in the USA, Luckhaupt et al. [27] stated that working environments and conditions that create work stress such as shift work, overwork, effort reward imbalance can affect obesity. In a study conducted in a university hospital, the frequency of obesity was 36.6% according to BMI [10]. According to the meta-analysis by Dilek et al. [25], in four studies examined (included 18,493 women and 17,339 men) abdominal obesity was higher than obesity determined by BMI, the prevalence of abdominal obesity was 39.6% (95% CI 30.3–49.3) in the whole group, 50.8% (95% CI 46.5–55.0) in females, and 20.8% (95% CI 16.9–24.9) in males. Our study also supports this finding; while the prevalence of obesity according to BMI was 35.1%, abdominal obesity according to waist circumference was higher as 50.4%. Disruption of circadian rhythm due to shift working, exposure to light during nights, nocturnal eating habits, hormonal imbalances [20], inactive life, high work stress and low social support [19] might trigger obesity according to studies conducted in health care workers.

4.2 Anxiety and depression symptoms

Anxiety and depression are referred to as “common mental illnesses” due to their high prevalence in society that cause decreased quality of life, increased risk of death, frequent use of healthcare services and increased health expenses for themselves and their relatives [28]. Studies have shown that individuals working in healthcare institutions are more prone to anxiety and depression for a variety of reasons. Working environment and conditions (working in shifts, increased workload and prolonged working hours, long-term indoor working, the necessity of continuing the service without interruption and error), violence against healthcare workers which has increased in recent years, can increase work stress, burnout, anxiety and depression in healthcare workers [13, 14]. Afonso et al. showed in their study that long working hours might impair sleep quality and increase anxiety and depression in healthcare workers [29]. Job stress is defined as the physical or emotional response that occurs when job requirements do not meet the employee’s skills, demands, or resources, and is often explained by an effort-reward imbalance model or workload-control model [27]. Excessive workload, lack of control, endless and sometimes meaningless tasks, imbalance between work and private life are risk factors that might increase burnout. Health care workers face with these factors throughout their educational and occupational life. In a study, it was stated that 24–54% of health students and employees showed signs of burnout, which reduced the quality of the service, increased medical errors, and caused health problems [30]. In a longitudinal study conducted in four hospitals in the United States in 2015, assuming that occupational accidents and diseases were 80% higher in hospital workers than other workers in the community showed 21.6% of employees experienced anxiety and/or depression. It was found that the risk of accident / medical error increased by 63% in employees with depression [31]. In addition, employees in healthcare institutions have to deal with traumatized patients throughout their work life and this situation itself causes trauma and compassion, fatigue, anxiety and depression in the employee [32]. Although the data of this study were collected before the COVID-19 pandemic that started in December 2019, encountering infectious diseases as the primary/first step increases the risk of anxiety and depression of healthcare workers. In studies conducted during and after the SARS epidemic affecting China, Singapore, Taiwan and Canada-Toronto, it has been shown that the stress and anxiety levels of healthcare workers, especially those who first encountered the patient, increased [33]. In our study, 35.9% of the participants showed moderate & severe anxiety symptoms, while 19.1% showed signs of moderate & severe depression. Prevention of anxiety and depression in healthcare professionals is extremely important in terms of protecting the health of both the employee and those receiving service from them.

4.3 Association between obesity, anxiety, and depression

It has been shown in various studies that obesity affects depression [6, 7]. In the APNA study in Spain, 20,212 women without depression at baseline were followed for 7 years and as a result, low-weight (OR: 9.8, 95% CI:7.3–12.9%) and obese (OR: 10.3 95% CI: 9.5–11.1) women presented an increased risk for developing depression [34]. The results obtained in the conducted studies suggested that this association might be bi-directional. Pan et al. [11] evaluated 65,955 women who were followed up for 10 years at two-year intervals within the scope of the Nurse’s Health Study, and after adjusted for various confounders, obese people developed depression 1.11 times (95% CI: 1.03–1.18) and depressed people developed obesity 1.38 times (95% CI: 1.24–1.53) more.

On the other hand, in an article published in 1975 in which 739 people were evaluated by Crisp and McGuiness [35], the “Jolly Fat” hypothesis was proposed, showing that obesity may have protective effects against depressive symptoms in middle-aged and elderly individuals. In the following years, many studies were conducted supporting [36 –38] or rejecting [39, 40] this hypothesis. In a study conducted among American individuals aged 50–89 years living at home, Palinkas et al. [36] stated that depression was seen less in men who were overweight and obese supporting the jolly fat hypothesis, but the results were insignificant for women, because women may encounter stigmatization more. On the other hand, in a study conducted on Korea in a similar age group, the opposite results were obtained, it was emphasized that depression was significantly less in overweight and obese women, but there was no significant result in men [37]. In another study conducted with middle-aged and elderly individuals in China, it was found that individuals who were overweight and obese in both genders showed fewer depressive symptoms than normal-weight individuals [38]. Using varied scales, diverse social norms, or perceptions about obesity, or using dissimilar cut-off points in determining obesity according to BMI in Asia may have caused these different results.

Two meta-analyses that examined longitudinal studies conducted at different times and had similar results provided us with clearer results. Luppino et al. [21] examined 15 longitudinal studies (n = 58,745) in 2010, and as a result they stated that the risk of developing depression in individuals who were obese at the beginning was 1.55 times (95% CI: 1.22–1.98), and the risk of developing obesity in individuals with depression at the beginning was 1.58 times (% 95 CI: 1.33–1.87) more. Six years after, in the meta-analysis by Mannan et al. [12]conducted on 19 studies, n = 226,063 subjects were followed up for at least 1 year and showed that risk of developing depression in individuals who were obese at the beginning was 1.18 fold (95% CI: 1.04–1.35), and the risk of developing obesity in individuals with depression at the beginning was 1.37 fold (% 95 CI: 1.17–1.48) more. In our study, obesity increased the presence of depression symptoms approximately six times (OR: 5.9, 95% CI: 2.106–16.417), and the presence of depression symptoms increased obesity approximately six times (OR: 5.6 times, 95% CI: 2.054–15.476). Our study was conducted on a narrower group, and the large confidence interval supports this situation. In addition, the cross-sectional nature of the study, the absence of follow-up period and the specific working conditions of our study group might be the reasons for yielding a higher risk.

Upadhyaya et al. (2019) conducted a systematic review to present the effectiveness of worksite intervention programs focusing on preventing obesity among health care workers. They showed that multifaceted interventions to increase awareness, knowledge, positive attitude and behavior delivered by a trained professional, helped improving weight outcomes [17]. Thus, health care institutions are important sites for interventions to tackle obesity.

Although no sample was selected and it was aimed to reach the whole population, the fact that the study was conducted with individuals working in a single private hospital in a single province may have caused the number of participants to be low. However, it is thought that the heterogeneity of the group in terms of gender, education and occupation reduces this limitation. As a cross-sectional study it is not possible to understand the temporal relationship between obesity, anxiety and depression and to determine which one is the exposure and the other one is the outcome. It can be advised to conduct prospective long-term studies in order to clearly reveal the direction of the causal relationship.

5 Conclusions

In this study conducted on individuals working in a private hospital, slightly more than one third of the employees were obese, half of them were abdominally obese, more than one third showed moderate & severe anxiety symptoms, one fifth showed moderate & severe depression symptoms. After adjusted for age, sex and other socio-demographic characteristics, obesity was significantly associated with symptoms of moderate & severe anxiety and depression. In this study it has been found that an increment in age was inversely associated with moderate & severe anxiety symptoms and being male was inversely associated with obesity. High anxiety and depression levels of healthcare professionals can cause irreversible medical errors and accidents. For this reason, decreasing the factors that might contribute to anxiety and depression such as organizing the working hours of healthcare workers, improving their working environment and legal regulations and policies against violence are needed. Individuals with weight problems should be identified and receiving mental health support as well as medical nutrition therapy may be suggested. In addition, multicomponent improvements such as providing healthy meals and snacks in workplaces and encouraging individuals for physical activity, determining high risk individuals, and giving consultancy to these individuals may be beneficial in terms of tackling obesity.

Institutional review board statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and it was approved by an independent ethics committee (Ege University Health Sciences Scientific Research and Publication Ethics Committe, Protocol: 274-2017.08/01, date: 12.10.2017).

Informed consent statement

Oral and written informed consent was obtained from all subjects involved in the study.

Footnotes

Acknowledgments

The authors have no acknowledgments.

Author’s contributions

RM, SAD and RNA contributed to the conception and design of the research, SAM contributed to acquisition of the data, RM and RNA contributed to the analysis. All authors drafted the manuscript, critically revised the manuscript, agree to be fully accountable for ensuring the integrity and accuracy of the work, and read and approved the final manuscript.

Funding

This research received no external funding.

Conflict of interest

The authors have no conflict of interest to report.

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