Are Working Conditions of Nurses Associated With Nutrition, Physical Activity, and Stress Levels?

ABSTRACT

Aim

This study aimed to examine the associations between working conditions and nurses’ stress levels, nutritional status, and physical activity in Türkiye.

Background

Nurses often face challenging working conditions that may lead to both psychological and physiological issues.

Methods

Data were collected from 825 female nurses aged 19–60 working in private hospitals across Türkiye. Working conditions were assessed by weekly working hours and total years of service. Nutritional status was assessed using a 24‐hour food recall, physical activity with the International Physical Activity Questionnaire‐Short Form, and stress with the Turkish version of the Nurse Stress Scale. The study followed the STROBE checklist for cross‐sectional studies.

Results

Overall, 39% of nurses had 0–5 years of total service, and 61% worked 40–45 hours/week. Nurses working 40–45 hours/week had significantly higher dietary fat and cholesterol intakes, while overall nutrient intake did not differ significantly by years of service. 49.1% were physically inactive, with those working longer hours and having more years of service tending to exhibit minimal levels of physical activity. Stress levels increased with longer working hours; however, nurses with 0–5 years of service reported significantly higher total stress scores compared to their more experienced counterparts.

Discussion

The results indicate that nurses’ demanding working conditions and unhealthy lifestyle behaviors are critical issues requiring attention in organizational and policy‐level discussions.

Conclusion

Longer working hours are associated with higher stress, lower physical activity, and unbalanced nutrition, while greater work experience appears to mitigate stress levels.

Implications for nursing and health policy

Policymakers and hospital administrations should implement structured programs to improve nurses’ working conditions, reduce occupational stress, and promote healthy nutrition and physical activity.

1. Introduction

Nursing, one of the oldest professions, constitutes the largest group of health professionals worldwide today (Yılmaz Kuşaklı et al. 2019). Nurses, who work to protect and improve health, are frequently exposed to adverse working conditions, including long and irregular working hours, heavy workloads, poor workplace environments, high stress levels, and work‐related pressure. However, these conditions may lead to psychological, physiological, and behavioral problems among nurses (Silva et al. 2010; Hacialioglu 2023).

Nutrition is defined as the intake of nutrients essential for growth, development, and survival. The energy and nutrient requirements for each individual vary according to gender, age, physical activity level, environmental factors, metabolic conditions, and health status. Both inadequate and excessive nutrient intake can pose risks to physical and mental health (Baysal 2010). Nurses are exposed to heavy workloads and long working hours in their workplace, which often leads to the skipping of meals and irregular eating habits. They also tend to consume fast food or packaged snacks, which typically have low nutritional value and are high in energy and fat content, during meals. These inadequate and unbalanced eating habits among nurses may increase the risk of obesity and related chronic diseases, ultimately impacting work quality and productivity (Beebe et al. 2017). A study conducted on nurses found that more than half of the nurses (57.3%) skipped meals. The most common responses given to the reasons for skipping meals were sleeping after work/shift, lack of hunger, and insufficient time for meals due to work pressure (Das and Adams 2021). Another study reported that most nurses consumed 3–4 meals per day, with breakfast being the most frequently skipped meal, and cookies and biscuits being common snack choices (Gupta 2017).

Physical activity, one of the main protective factors against obesity related noncommunicable diseases, is defined by the World Health Organization (WHO) as any bodily movement produced by skeletal muscles that requires energy expenditure (WHO 2024). Urbanization, increased use of transportation, demanding work schedules, and stress are the main causes of inadequate physical activity in daily life (Benzo et al. 2021). Nurses with demanding work schedules typically engage in low‐intensity physical activities during their shifts. Moreover, many are unable to allocate time for physical activities outside of work due to long working hours and fatigue. However, regular physical activity has been shown to have protective and therapeutic effects against chronic diseases, aid in weight management, reduce fatigue and stress, and improve nurses’ overall physical, mental, and occupational health (Owusu‐Sekyere 2020; Das and Adams 2021).

Psychological stress is a state of mental tension or anxiety that arises in response to adverse situations and is often a natural reaction to negative environmental stimuli. Occupational stress arises when employees are unable to meet job‐related demands or when they are exposed to unfavorable working environments and conditions. The intensity of stress responses can vary depending on the employee's personality traits and experiences (Dighe 2020). Work‐related stress in the nursing profession is considered one of the major global problems today. Factors such as heavy workloads, providing emotional support to patients, interactions with other healthcare professionals, and shift work negatively affect stress levels among nurses. High levels of stress experienced by nurses can disrupt body homeostasis, lead to various chronic and mental health problems, and negatively impact the quality of healthcare services (Abo Elmagd et al. 2024).

Nurses have important roles in acquiring healthy lifestyle behaviors of patients. However, it has been noted that, due to several factors, nurses often struggle to adopt these healthy behaviors in their own lives. Recent studies have highlighted how rotating shifts and irregular work schedules affect nurses’ health behaviors and stress levels. For example, Chiang et al. (2022) found that fixed shifts positively influenced lifestyle behaviors (including physical activity, dietary habits, and sleep) and were associated with reduced perceived stress among nurses. Similarly, during the COVID‐19 pandemic, higher physical activity and better sleep quality were associated with lower stress levels, particularly among nurses working rotating shifts (Chiang et al. 2025). While these studies provide valuable insights into the effects of shift work, few have focused specifically on more quantifiable indicators of working conditions, such as weekly working hours and total years of service. In light of this information, the present study aims to address a gap in the literature by examining how measurable aspects of female nurses’ working conditions—specifically, weekly working hours and total years of service—relate to their nutritional status, physical activity levels, and stress levels in Türkiye. Additionally, according to a joint report by the WHO and the International Labour Organization (ILO) in 2022, women constitute approximately 67% of the global health and social care workforce (WHO and ILO 2022). In Türkiye, although gender‐specific data for the nursing profession are limited, national reports indicate that the nursing workforce is predominantly female (Republic of Türkiye Ministry of Health 2025; Anadolu Ajansi 2024; Aca et al. 2025). Based on this demographic distribution, this study focused exclusively on female nurses to enhance sample homogeneity and minimize gender‐related variability in health‐related outcomes such as stress, physical activity, and dietary behaviors.

This study is grounded in the Job Demands–Resources (JD‐R) Theory, which provides a comprehensive framework for understanding how job characteristics influence employees’ health and well‐being. The theory posits that excessive job demands combined with limited job resources may lead to psychological strain and unhealthy lifestyle behaviors (Demerouti et al. 2001). Within this framework, working conditions such as long working hours and heavy workloads represent job demands that heighten nurses’ stress levels. In contrast, behaviors like maintaining regular physical activity and healthy eating can be viewed as personal resources that help buffer the negative effects of occupational stress. Consequently, nurses exposed to excessive job demands may experience elevated stress levels and reduced engagement in health‐promoting behaviors. Therefore, the JD‐R framework provides a robust theoretical basis for examining how nurses’ working conditions, such as weekly working hours and total years of service, are likely to be associated with their stress levels, nutritional habits, and physical activity.

2. Methods

2.1. Research Design

This descriptive, multicenter, cross‐sectional research was conducted between February and June 2024 on a total of 825 female nurses working in 7 private hospitals across Türkiye, including regional hospitals, using a simple random sampling method.

2.2. Sample and Setting

The inclusion criteria for participants were being a healthy female nurse aged 19–60 and employed at private hospitals. Exclusion criteria for the study were as follows: participants under the age of 19 or over 60, male nurses, those with any diagnosed mental diseases, those with physical disabilities, those on a special diet program, and pregnant or breastfeeding women. The recruitment of participants is demonstrated in Figure 1.

FIGURE 1.

A flow diagram showing the study design.

Sample size was calculated using G‐Power based on a point‐biserial correlation model, with 99% power, α = 0.003, and effect size = 0.2, yielding a minimum requirement of 622 participants (Kang 2021).

2.3. Ethical Considerations

Ethical approval was received from the Istanbul Medipol University Noninterventional Clinical Research Ethics Committee (dated January 18, 2024, approval number 45). The study was conducted in accordance with the Declaration of Helsinki. Signed informed consent forms were obtained from participants.

2.4. Assessment of Personal Information and Working Conditions

All data were collected by trained researchers through face‐to‐face interviews conducted during nurses’ working hours in hospital rest areas or designated meeting rooms. Prior to data collection, all researchers were trained on standardized measurement protocols to ensure consistency.

Demographic information (age, sex, education, marital status, etc.) and general health status (presence of any diseases, medication use, sleep patterns, etc.) of the participants were recorded using a questionnaire form. Participants’ anthropometric measurements, including body weight, height, body mass index (BMI), waist circumference (WC), and waist‐to‐hip ratio (WHR), were collected. WC and HC were measured by trained researchers using a nonelastic tape measure (precision: 0.5 cm), while body weight and height were self‐reported by the participants. WC was measured at the midpoint between the lower margin of the last rib and the top of the iliac crest, with the participant standing and arms parallel to the floor at the end of a normal expiration. HC was measured at the level of the widest portion of the buttocks, with the measuring tape held horizontally and parallel to the floor. BMI was calculated using the formula: body weight (kg) divided by height (m²). BMI (<18.5: kg/m² underweight; 18.5–24.9 kg/m²: normal; 25–29.9 kg/m²: overweight; ≥30 kg/m²: obese), WC (>94 cm for men, >80 cm for women), and WHR (>0.90 for men, >0.85 for women) were assessed according to WHO standards (WHO 2008).

Participants provided information on their total years of service, number of working days per week, weekly working hours, shift type, and perceived satisfaction with the work environment. In this study, working conditions were operationalized through two key variables: weekly working hours and total years of service. These variables were selected based on their conceptual relevance to cumulative occupational exposure, as well as prior evidence supporting their association with occupational stress and health‐related outcomes (Hoedl et al. 2021; Şanlıtürk 2021). Weekly working hours were categorized into three groups: 40–45, 46–60, and 61–80 hours/week, based on national labor regulations (Resmi Gazete 2003). Years of service were categorized as 0–5, 6–10, 11–15, and >15 years, following previously used classifications (Şanlıtürk 2021). Other workplace‐related characteristics, such as shift type, number of working days, and job satisfaction, were reported descriptively to provide a broader context on the participants’ working conditions but were not included in the analytical models.

2.5. Assessment of Nutritional Status

A 24‐hour food consumption record was used to examine nurses’ daily nutrient intakes in detail and to collect comprehensive information about the foods and beverages consumed during a working day. The types and quantities of food and beverages consumed during main meals and snacks throughout the day were recorded. The booklet Food and Nutrition Photograph Catalogue: Measurements and Quantities was used to determine the portion sizes consumed by individuals (Rakicioglu et al. 2012). The energy, macronutrients, and micronutrients in the nurses’ daily diets were analyzed using the Nutrition Information Systems Package Program, version 9 (BeBIS). The percentages of individuals meeting their energy and nutrient requirements were calculated according to age and gender based on the Türkiye Nutrition Guide (TUBER)‐2022 (Republic of Türkiye Ministry of Health 2022). The percentages were evaluated according to the daily dietary recommendations: intake was considered inadequate if it was ≤67%, adequate if it ranged between 67% and 133%, and excessive if it was ≥133%.

2.6. Assessment of Physical Activity

The International Physical Activity Questionnaire‐Short Form (IPAQ‐SF) was used to assess the physical activity levels of the participants. Developed with WHO support across 12 countries, it is considered an effective tool for measuring physical activity in large populations. The international validity and reliability studies for this questionnaire were conducted by Craig et al. (2003). Cronbach's alpha for the IPAQ‐SF was reported as α = 0.79. In the current study, it was α = 0.74. The scale included seven questions across four activity categories: sitting, walking, moderate‐intensity, and severe‐intensity activities. Metabolic Equivalent of Task (MET) values (sitting: 1.5, walking: 3.3, moderate: 4.0, vigorous: 8.0) were used to calculate the total weekly physical activity score. A total score was calculated by multiplying the MET value by the duration of each activity in minutes (min). This total score constituted the individual's weekly physical activity score. According to the IPAQ scoring guidelines, participants’ physical activity levels were categorized based on their total MET‐minutes per week: physically inactive (<600 MET‐min/week), minimally active (600–3000 MET‐min/week), and very active (>3000 MET‐min/week).

2.7. Assessment of Job Stress Status

The Nurse Stress Scale (NSS), developed by Gray‐Toft and Anderson (1981), and a Turkish validity‐reliability study conducted by Mert et al. (2021) were used to assess the job stress levels of nurses. In the Turkish validation study, the Cronbach's alpha for the total NSS was α = 0.92 and α = 0.86 in the present study. The NSS consisted of 34 items divided into seven subfactors: “Uncertainty Concerning Treatment” (8–32 points), “Workload” (6–24 points), “The Death of the Patient” (5–20 points), “Conflict with a Physician” (5–20 points), “Conflict with Peers” (5–20 points), “Insufficient Support” (3–12 points), and “Suffering Patient” (2–4 points). The total score, obtained by summing all item responses, reflected the individual's overall stress level. Scores ranged from 34 (minimum) to 136 (maximum), with higher scores indicating more frequent stress in physical and psychological environments.

2.8. Statistical Analysis

Statistical analysis of the collected data was performed using the SPSS (Statistical Package for Social Sciences) software, version 25.0. Quantitative variables were expressed as mean (X) ± standard deviation (SD), while categorical variables were presented as number (n) and percentage (%). Categorical variables were compared using the Χ ² test. The normality of data distribution was assessed using the one‐sample Kolmogorov–Smirnov test. For nonnormally distributed data, the Mann–Whitney U test was used for comparisons between two groups, the Kruskal–Wallis test for comparisons involving three or more groups. Spearman's correlation analysis was employed to evaluate the relationships between continuous variables, and a visual correlation plot (Figure 2) was generated using R software based on Spearman correlation coefficients. Multinomial logistic regression analysis was conducted to evaluate the associations of weekly working hours and years of service on nurses’ stress, nutrition, and physical activity, adjusting for age as a potential confounder. This method was chosen because the dependent variables were not continuous but ordinal/categorical in nature, and assumptions of normality were not met. The use of multinomial regression allowed comparison across multiple outcome categories simultaneously while controlling for potential confounders. Age was included as the sole covariate in the regression model due to its strong association with years of service and its previously observed confounding effect on anthropometric outcomes. Other potential confounders, such as gender or BMI, were not included due to the homogeneity of the sample (i.e., all participants were female) and because BMI was neither a primary predictor nor a key outcome in the present analysis. A p value of <0.05 was considered statistically significant.

FIGURE 2.

Paired correlations between nurses’ working conditions and their nutrition, physical activity, and stress levels.

Working condition variables (weekly working hours and years of service) were included as predictors in both Mann–Whitney U and multinomial logistic regression models. Other workplace‐related characteristics (e.g., shift type, number of working days, job satisfaction) were excluded from multivariate models due to limited variability and multicollinearity concerns, and were instead reported descriptively to provide contextual information about the work environment.

3. Results

Data on the general characteristics of the participants are shown in Table 1. A total of 825 nurses were included in the study. The mean age of the nurses was 32.2 ± 7.5 years, and 74.3% held a bachelor's degree. Most of the nurses (72.1%) did not have any chronic diseases. It was determined that 51.4% of the nurses had a regular sleep pattern, and 75.4% slept between 4 and 8 hours per day. Additionally, 63.3% had a normal body weight (mean BMI: 23.9 ± 3.7 kg/m²), and their WC and WHR measurements were not classified as being at risk according to WHO standards.

TABLE 1.

General characteristics of nurses.

Variables	Total (n = 825)
Age, years (mean ± SD)	32.2 ± 7.5
Educational status, n (%)
Health vocational high school	64 (7.8)
Associate in nursing	74 (9.0)
Bachelor's degree	613 (74.3)
Postgraduate degree	74 (9.0)
Marital status, n (%)
Single/divorced	361 (43.8)
Married	464 (56.2)
Smoking, n (%)
Yes	242 (29.3)
No	583 (70.7)
Smoking duration (months), (mean ± SD)	92.3 ± 79.7
Number of smoking/day, (mean ± SD)	11.3 ± 6.5
Alcohol use, n (%)
Yes	101 (12.2)
No	724 (87.8)
Alcohol consumption (ml/day), (mean ± SD)	231.5 ± 215.4
Chronic diseases, n (%)
None	595 (72.1)
Cardiovascular diseases	49 (5.9)
Diabetes	28 (3.4)
Hormonal diseases	38 (4.6)
Liver—bile diseases	26 (3.1)
Gastrointestinal system diseases	46 (5.5)
Other	43 (5.4)
Sleep regularity status, n (%)
Yes	424 (51.4)
No	401 (48.6)
Daily sleep duration (hours), n (%)
<4	47 (5.7)
4–8	622 (75.4)
9–12	156 (18.9)
Nutritional supplement use, n (%)
Yes	154 (18.7)
No	671 (81.3)
Anthropometric measurements
Weight (kg) (mean ± SD)	64.7 ± 11.1
BMI (kg/m2) (mean ± SD)	23.9 ± 3.7
BMI classification, n (%)
Underweight (<18.5 kg/m2)	22 (2.7)
Normal (18.5–24.9 kg/m2)	522 (63.3)
Overweight (25.0–29.9 kg/m2)	217 (26.3)
Obese (≥30 kg/m2)	64 (7.7)
Waist circumference (cm) (mean ± SD)	79.0 ± 11.6
Waist–hip ratio (mean ± SD)	0.79 ± 0.09

Abbreviation: BMI, Body mass index.

As shown in Table 2, 39.0% of the nurses had been employed for 0–5 years, and 70.9% reported satisfaction with their work environment. The majority (61.0%) worked 40–45 hours per week, and 65.7% were on continuous day shifts. The mean number of working days per week was 5.1 ± 0.7. Nearly half of the nurses (49.1%) were physically inactive. The total mean score on the NSS was 66.4 ± 16.3. The mean scores for the scale's subfactors are presented in Table 2.

TABLE 2.

Working conditions, physical activity, and job stress status of nurses.

	Total (n = 825)
Work environment satisfaction, n (%)
Yes	585 (70.9)
No	240 (29.1)
Total years of service, n (%)
0–5 years	322 (39.0)
6–10 years	199 (24.1)
11–15 years	111 (13.5)
>15 years	193 (23.4)
Working time (days) (mean ± SD)	5.1 ± 0.7
Average weekly working hours, n (%)
40–45	503 (61.0)
46–60	278 (33.7)
61–80	44 (5.3)
Working schedule, n (%)
Continuous daytime	542 (65.7)
Continuous nighttime	80 (9.7)
Day and nighttime	203 (24.6)
Physical activity status, n (%)
Inactive (<600 MET/min/week)	405 (49.1)
Minimal active (600–3000 MET/min/week)	369 (44.7)
Very active (>3000 MET/min/week)	51 (6.2)
Job stress status (mean ± SD)
Total NSS score	66.4 ± 16.3
NSS subgroups
Uncertainty concerning	14.4 ± 4.3
Workload	12.9 ± 4.0
The death of a patient	10.3 ± 3.8
Conflict with a physician	9.4 ± 3.1
Conflict with peers	9.2 ± 3.1
Insufficient support	5.6 ± 1.9
Suffering patient	4.4 ± 1.6

Abbreviation: NSS, Nurse Stress Scale.

Table 3 presents nurses’ energy, macronutrient, and micronutrient intakes. The nutritional status of the nurses was found to be low in carbohydrates (41.4%) and high in fat (40.6%). The daily intakes of vitamin A (143.5%), vitamin B1 (205.0%), sodium (151.7%), and phosphorus (178.4%) exceeded the recommended levels, while potassium intake (57.7%) was insufficient. All other analyzed nutrients met the recommended intake levels.

TABLE 3.

Energy and macro‐/micronutrient intakes of nurses.

	Mean consumption/day (mean ± SD)	Recommended intake/day *	% of Daily dietary recommendation
Energy (kcal)	1454.4 ± 522.1	—
CHO (g)	151.2 ± 72.6	—	—
CHO (%E)	41.4 ± 10.2	45–60	—
Protein (g)	62.4 ± 24.8	—	—
Protein (%E)	17.8 ± 4.6	10‐20	—
Fat (g)	66.0 ± 27.6	—	—
Fat (%E)	40.6 ± 9.3	20‐35	—
MUFA (g)	23.4 ± 10.8	—	—
PUFA (g)	11.7 ± 7.2	—	—
SFA (g)	24.8 ± 12.2	—	—
Fiber (g)	17.2 ± 9.1	25	68.8
Cholesterol (mg)	308.3 ± 226.9	300	102.7
Vitamin A (mcg)	932.9 ± 657.7	650	143.5
Vitamin E (mg)	10.7 ± 7.5	11	97.2
Vitamin B1 (mg)	0.82 ± 0.44	0.4	205.0
Vitamin B2 (mg)	1.23 ± 0.54	1.6	76.8
Vitamin B6 (mg)	1.11 ± 0.53	1.6	69.3
Vitamin B12 (mcg)	4.4 ± 4.6	4	110.0
Folate (mcg)	266.3 ± 126.4	330	80.6
Vitamin C (mg)	89.2 ± 72.3	95	93.8
Sodium (mg)	3034.6 ± 2793.9	2000	151.7
Potassium (mg)	2022.7 ± 852.2	3500	57.7
Calcium (mg)	640.4 ± 322.9	950	67.4
Magnesium (mg)	240.0 ± 102.8	300	80.0
Phosphorus (mg)	981.3 ± 411.6	550	178.4
Iron (mg)	9.2 ± 4.5	11	83.6
Zinc (mg)	9.8 ± 4.5	9.3	105.3

Abbreviations CHO, carbohydrate; MUFA, Monounsaturated fatty acid; PUFA, Polyunsaturated fatty acid; SFA, Saturated fatty acid.

^*Dietary reference values used for the recommended daily intake were obtained from the Republic of Türkiye Ministry of Health (2022).

Table 4 presents the anthropometric measurements, physical activity levels, job stress, and nutritional status of nurses based on their working hours and years of service. No significant differences were found in the anthropometric measurements of nurses based on their weekly working hours. However, nurses with 11–15 years of service had significantly higher body weight and BMI compared to those with 0–5 years of service (p = 0.001 and p = 0.002, respectively). To examine whether these differences remained significant after controlling for age, an ANCOVA was conducted. The analysis showed that years of service were not a significant predictor of either body weight (F(3, 820) = 1.28, p = 0.280) or BMI (F(3, 820) = 1.62, p = 0.183) after adjusting for age.

TABLE 4.

Anthropometric measurements, physical activity, job stress, and nutritional status of nurses according to their working hours and years of service.

	Working hours (hours/week)				Total service (years)
	40–45 (n = 503)	46–60 (n = 278)	61–80 (n = 44)	p	0–5 (n = 322)	6–10 (n = 199)	11–15 (n = 111)	>15 (n = 193)	p
Anthropometric measures (mean ± SD)
Body weight (kg)	64.9  ± 11.2	64.6 ± 11.1	64.5 ± 9.6	0.863	62.8 ± 10.91,2	64.2 ± 11.03	66.1 ± 11.01	67.8 ± 10.92,3	<0.001
BMI (kg/m2)	24.1 ± 3.7	23.7 ± 3.8	23.6 ± 2.9	0.242	23.1 ± 3.34,5	23.7 ± 3.86	24.2 ± 3.44,7	25.4 ± 3.95,6,7	<0.001
Waist circumference (cm)	78.9 ± 11.5	79.3 ± 11.8	78.0 ± 11.0	0.773	76.9 ± 10.98	78.1 ± 11.59	78.8 ± 9.910	83.3 ± 12.48,9,10	<0.001
Waist–hip ratio	0.79 ± 0.08	0.80 ± 0.11	0.79 ± 0.11	0.956	0.78 ± 0.10 11	0.79 ± 0.1012	0.78 ± 0.0713	0.81 ± 0.1011,12,13	<0.001
Physical activity n (%)
Inactive	197 (48.6)	103 (46.4)	5 (19.2)		132 (50.0)	73 (46.2)	44 (51.8)	56 (38.4)
Minimal	192 (47.4)	89 (40.1)	16 (61.5)	<0.001	104 (39.4)	67 (42.4)	39 (45.9)	87 (59.6)	<0.001
Vigorous	16 (4.0)	30 (13.5)	5 (19.2)		28 (10.6)	18 (11.4)	2 (2.4)	3 (2.1)
Job stress state (mean ± SD)
Total NSS score	64.4 ± 17.3 * , †	69.1 ±14.2 *	73.1 ± 11.2 †	<0.001	71.2 ± 14.8 α , β , ɣ	66.8 ± 16.2 β , ¥ , §	61.1 ± 15.7 ɣ , ¥	61.0 ± 16.6 α , §	<0.001
NSS subgroups
Uncertainty concerning treatment	14.2 ± 4.5	14.8 ± 4.1	15.2 ± 4.3	0.071	15.6 ± 4.3	14.4 ± 4.3	13.3 ± 4.0	13.2 ± 4.2	<0.001
Workload	12.5 ± 4.1	13.5 ± 3.7	14.1 ± 3.9	<0.001	13.5 ± 3.7	13.3 ± 4.1	11.8 ± 4.0	12.2 ± 4.0	<0.001
The death of a patient	10.0 ± 4.0	10.6 ± 3.4	10.7 ± 3.2	0.021	11.0 ± 3.6	10.3 ± 3.7	9.7 ± 4.0	9.3 ± 3.9	<0.001
Conflict with a physician	9.1 ± 3.1	9.7 ± 3.1	11.3 ± 3.2	<0.001	10.3 ± 3.1	9.2 ± 3.0	8.5 ± 3.1	8.6 ± 3.1	<0.001
Conflict with peers	8.8 ± 3.1	9.5 ± 3.2	10.8 ± 3.1	<0.001	9.9 ± 3.0	9.2 ± 3.1	8.5 ± 2.9	8.2 ± 3.0	<0.001
Insufficient support	5.3 ± 1.9	5.9 ± 2.0	6.0 ± 1.9	0.001	5.8 ± 2.0	5.6 ± 1.9	5.0 ± 1.8	5.2 ± 1.8	<0.001
Suffering patient	4.2 ± 1.7	4.8 ± 1.5	5.0 ± 1.4	<0.001	4.8 ± 1.5	4.5 ± 1.7	4.1 ± 1.7	4.0 ± 1.7	<0.001
Nutritional status (mean ± SD)
Energy (kcal)	1449.6 ± 493.8	1439.3 ± 561.9	1604.3 ± 563.3	0.154	1495.0 ± 547.2	1483.7 ± 535.8	1431.1 ± 525.1	1369.7 ± 451.4	0.087
CHO (%E)	40.9 ± 10.2	42.1 ± 10.0	42.7 ± 11.2	0.093	41.8 ± 10.1	41.7 ± 9.3	41.3 ± 11.3	40.6 ± 10.7	0.458
Protein (%E)	17.7 ± 4.4	18.0 ± 4.9	17.7 ± 4.8	0.978	17.8 ± 4.8	17.7 ± 4.4	17.8 ± 4.5	18.2 ± 4.5	0.514
Fat (%E)	41.2 ± 9.5 a	39.7 ± 8.9 a	39.5 ± 9.9	0.037	40.4 ± 9.2	40.5 ± 9.0	40.7 ± 10.6	41.1 ± 9.2	0.720
Cholesterol (mg)	326.1 ± 238.6 b	284.2 ± 203.4 b	257.1 ± 212.6	0.002	317.1 ± 278.7	308.1 ± 200.4	268.9 ± 169.5	316.3 ± 179.1	0.192
Fiber (g)	17.6 ± 9.7	16.5 ± 8.2	17.8 ± 8.1	0.279	16.7 ± 8.4	17.7 ± 10.3	17.8 ± 9.3	17.4 ± 8.8	0.649

Abbreviations: BMI, Body mass index; CHO, carbohydrate; NSS, Nurse Stress Scale.

^1–13Different numbers in the same row correspond to significant differences by the Mann–Whitney U test (p < 0.05).

^* p < 0.001.

^† p = 0.001.

^α p < 0.001.

^β p = 0.002.

^ɣ p < 0.001.

^¥ p = 0.004.

^§ p < 0.001.

^a p = 0.019.

^b p = 0.003.

It was observed that nurses working 40–45 h/w (48.6%) and 46–60 h/w (46.4%) were predominantly inactive, while those working 61–80 h/w (61.5%) exhibited minimal levels of physical activity (p < 0.001). When evaluated according to total years of service, the study revealed that nurses with over 15 years of service (59.6%) had a minimal physical activity, whereas those with 0–15 years of service were found to be inactive (0–5 years: 50.0%; 6–10 years: 46.2%; 11–15 years: 51.8%, p < 0.001) (Table 4).

When examining the stress levels of nurses according to their weekly working hours, it was found that nurses with longer working hours had higher levels of stress (p < 0.001). Additionally, nurses with 0–5 years of service were found to have significantly higher total stress scores compared to those with more than 15 years of service (p < 0.001). Similar findings were observed among nurses across other service groups (0–5 years vs. 6–10 years: p = 0.002; 0–5 years vs. 11–15 years: p < 0.001; 6–10 years vs. 11–15 years: p = 0.004; 6–10 years vs. >15 years: p < 0.001) (Table 4).

When the NSS subfactors were examined, workload (p = 0.007), conflict with a physician (p < 0.001), conflict with peers (p < 0.001), insufficient support (p = 0.048), and suffering patient (p = 0.002) scores of nurses working 61–80 h/w had significantly higher scores compared to those working 40–45 h/w. Similarly, nurses working 46–60 h/w had significantly higher in workload (p < 0.001), the death of a patient (p = 0.010), conflict with a physician (p = 0.004), conflict with peers (p = 0.001), insufficient support (p < 0.001), and suffering patient (p < 0.001) than those working 40–45 h/w. In terms of total years of service, nurses with 0–5 years of service had significantly higher scores across all NSS subfactors—including uncertainty concerning (p < 0.001), workload (p < 0.001), the death of a patient (p < 0.001), conflict with a physician (p < 0.001), conflict with peers (p < 0.001), insufficient support (p < 0.001), and suffering patient (p < 0.001)—compared to those with more than 15 years of service (Table 4).

The daily nutrient intake of nurses was examined according to their weekly working hours (Table 4). It was found that dietary fat (p = 0.019) and cholesterol (p = 0.003) intakes were significantly higher among nurses working 40–45 h/w compared to those working 46–60 h/w. In contrast, no significant differences were observed in daily nutrient intake based on total years of service.

As shown in Figure 2, the total stress score was positively correlated with WHR (r = 0.081, p = 0.023) and energy intake (r = 0.072, p = 0.038). However, the total stress score was negatively correlated with total IPAQ‐SF scores (r = −0.223, p < 0.001) and protein intake (r = −0.136, p < 0.001). Regarding the NSS subfactors, uncertainty concerning was negatively correlated with IPAQ‐SF scores (r = −0.272, p < 0.001) and protein intake (r = −0.113, p = 0.001). In addition, a positive relationship was observed between uncertainty concerning and WC (r = 0.086, p = 0.015) as well as energy intake (r = 0.078, p = 0.026). The workload subfactor was positively associated with WC (r = 0.100, p = 0.005) and WHR (r = 0.108, p = 0.002), while it showed a negative association with fat intake (r = −0.116, p = 0.001). A negative correlation was found between the death of a patient and BMI (r = −0.086, p = 0.014), total IPAQ‐SF scores (r = −0.221, p<0.001), and fiber intake (r = −0.081, p = 0.021). Conflict with a physician and conflict with peers were positively associated with WHR (r = 0.075, p = 0.034 and r = 0.099, p = 0.005, respectively), while a negative association was observed between these variables and total IPAQ‐SF scores (r = −0.148, p < 0.001 and r = −0.123, p = 0.002, respectively) and protein intake (r = −0.136, p < 0.001 and r = −0.129, p < 0.001). Insufficient support was found to be positively associated with WC (r = 0.123, p < 0.001), WHR (r = 0.112, p = 0.002), and carbohydrate intake (r = 0.106, p = 0.002), while it was negatively associated with protein intake (r = −0.139, p < 0.001). A negative correlation was observed between the suffering patient subfactor and BMI (r = −0.119, p = 0.001), WHR (r = −0.076, p = 0.032), total IPAQ‐SF scores (r = −0.175, p < 0.001), and fiber intake (r = −0.078, p = 0.025). In the logistic regression analysis, using 40–45 h/w as the reference category, working 46–60 hours was significantly associated with higher stress scores (B = 0.018, p = 0.002, OR = 1.018, 95% CI: 1.007–1.030) and higher physical activity levels (B = 0.000, p < 0.001, OR = 1.000, 95% CI: 1.000–1.000). In the 61–80 h/w, physical activity levels remained significantly associated with working hours (B = 0.000, p < 0.001, OR = 1.000, 95%CI: 1.000–1.001), while the association with stress scores approached but did not reach statistical significance (B = 0.021, p = 0.128). No significant relationship was found between working hours and nutritional status.

4. Discussion

This study investigated the associations between nurses’ working conditions, nutrition, physical activity, and stress in Türkiye. We found that longer working hours and more years of service were significantly associated with higher stress levels, and these groups also tended to have minimal physical activity. Nutritional status did not differ significantly by years of service, and no significant differences were observed across working hour categories, except for a significantly higher intake of fat and cholesterol in nurses working 40–45 hours per week.

Of the nurses participating in this study, 65.7% worked continuous day shifts, and 61% worked 40–45 h/w (Table 2). In a study involving 281 nurses working in surgical units of private hospitals in Türkiye, it was found that 47.7% of the nurses worked between 55 and 69 h/w, and 77.9% worked both day and night shifts (Aykaç and Yeşilyurt 2023). Similarly, in a study conducted across 20 private hospitals in Istanbul, Türkiye, most nurses (39.9%) worked 55–60 h/w (Özkan et al. 2013). In contrast, another study conducted in a public hospital reported that 60.2% of the nurses worked 40 hours or less per week, and 68.0% worked mixed day/night shifts (Erenoğlu et al. 2019). These differences in working hours across studies may be attributed to variations in institutional policies and staffing levels.

Nursing is one of the occupational groups where inadequate and unbalanced diets are common, due to many factors including heavy workloads, shift work, and insufficient sleep. In this study, nurses’ average daily energy intake was 1454.4 kcal, with 41.4% from carbohydrates, 17.8% from protein, and 40.6% from fat (Table 3). Compared to TUBER‐2022 recommendations (45%–60% carbohydrates, 20%–35% fats, 10%–20% proteins; fiber 25–30 g/day) (Republic of Türkiye Ministry of Health 2022), participants consumed insufficient carbohydrates (41.4%) and fiber (17.2 g/day) and excessive fat (40.6%). A study conducted in Istanbul, Türkiye, reported that nurses had a daily energy intake of 1270.8 kcal (45.15% carbohydrates, 17.15% proteins, 29.0% fats) (Daş Geçim and Esin 2019). Another study showed that more than half of nurses (64.8%) did not consume five servings of fruits or vegetables per day (Malik et al. 2011). In our study, carbohydrate and fat intake differed from values reported in previous research. The low‐carbohydrate, high‐fat pattern observed in our study may be explained by several factors. The relatively young age of the participants may have influenced their dietary preferences, as younger adults are more likely to consume fast foods, fried meals, and convenience snacks that are high in fat and low in fiber. In addition, demanding work schedules, long shifts, and inconsistent rest breaks may limit opportunities for balanced meals, leading nurses to rely on readily available high‐fat convenience foods in hospital cafeterias or nearby facilities. Cultural and environmental factors, including the surrounding food environment of hospitals, may also have contributed to this dietary pattern. Furthermore, because dietary intake was self‐reported, recall errors or social desirability bias may have affected the accuracy of the data, potentially underestimating carbohydrate intake and overestimating fat intake. Finally, differences between our findings and those of international studies may partly be explained by cross‐country variations in dietary habits and meal composition. Additionally, in our study, nutrient intake did not differ by years of service; however, fat and cholesterol intake were significantly higher in nurses working 40–45 h/w compared to others (Table 4). The total stress scores were positively correlated with energy intake and negatively correlated with protein intake (Figure 2). No studies in the existing literature were identified that directly support or discuss these findings. This finding, although seemingly counterintuitive, may be explained by the complex nature of stress‐related eating behaviors. Previous research suggests that stress can lead to both hyperphagic and hypophagic responses, depending on individual coping styles, work environment, and the type of stress experienced (Yau and Potenza 2013). In the context of nursing, acute job stress and fatigue may trigger increased consumption of easily accessible high‐calorie foods, providing short‐term relief or comfort, while chronic stress may suppress appetite in some individuals. The relatively young age of our participants may also contribute to higher susceptibility to emotional or convenience eating behaviors. Additionally, long and irregular working hours may disrupt normal meal patterns, promoting the intake of calorie‐dense snacks rather than balanced meals. These occupational and behavioral mechanisms may explain the observed positive association between stress and total energy intake, and the negative association with protein intake in our study. However, workplace‐related factors influencing stress and eating behaviors among nurses may offer some explanatory context. Although nurses in Türkiye are generally entitled to two 15‐minute breaks and one lunch break during their working hours, this practice is not consistently implemented in many healthcare institutions due to heavy workloads and staffing constraints. This may contribute to the irregular eating behaviors observed in the study.

Physical activity is an important factor associated with individuals’ health and work performance. In our study, 49.1% of the nurses were classified as inactive and 44.7% as minimally active (Table 2). Our study also found that nurses working 40–45 h/w and those with 0–15 years of service were inactive, whereas those working 61–80 h/w and with over 15 years of service exhibited minimal physical activity levels (Table 4). Literature indicates that nurses’ physical activity is generally highest during working hours, although it varies with workload intensity (Chin et al. 2016; Wesołowska‐Górniak et al. 2022). Similar to our findings, a study of 212 nurses reported that 52.8% were physically inactive and 25% were minimally active (Aydın and Kamuk 2021). Another study found that shift nurses engaged in an average of 566 minutes/week of moderate‐to‐vigorous physical activity at work and 227 minutes/week during their free time, meeting WHO recommendations (Brennan and Green 2023). Reed et al. (2018) reported that nurses working shifts and day shifts accumulated 288 minutes/week of moderate‐to‐vigorous activity both during work and leisure. In a study of 400 nurses in Saudi Arabia, nurses were found to be most physically active during working hours, but those working more than 60 h/w had lower physical activity levels (Almajwal 2015). As can be seen, there are different results in the studies that evaluate the physical activity of nurses. These differences may be attributed to variations in job description, workload, presence of chronic diseases, and socio‐demographic factors.

Compared to many other professions, nurses are at the forefront of healthcare and have highly demanding jobs, making them vulnerable to high levels of psychosocial work stress. Exposure to high levels of stress at work poses a significant health risk for nurses in later life (Aslan et al. 2022). In our study, the mean total NSS score of the nurses was 66.4 ± 16.3, below average stress levels (Table 4). A study conducted in Türkiye determined the mean NSS score of nurses to be 83.84 ± 18.5 (Baran and Işık 2024). In a study of 1300 nurses in the south‐eastern United States, the stress score was similarly 83.84 ± 18.5 (Purcell et al. 2011), while Australian nurses had lower stress scores (NSS score: 40.4 ± 14.5) (Healy and McKay 2000). It can be noted that the nurses in our study had lower stress levels compared to the studies in the literature, which may be attributed to factors such as their younger age, differences in the units they worked in, and the workload they experienced.

Long and exhausting working hours are a major source of stress for healthcare workers (Aydın et al. 2020). In this study, NSS scores increased with average weekly working hours, with the highest stress observed among nurses working 61–80 h/week (Table 4). In a study, nurses who worked more than 40 h/w had higher stress levels than those with shorter working hours (Soylu Döner and Yaban 2023). Another study reported that weekly working hours were one of the main factors influencing nurses’ stress burden, with Chinese nurses who worked more than 35 h/w experiencing higher stress levels than those working fewer hours (Mo et al. 2020). Our research findings are consistent with the literature, supporting the notion that long working hours are significantly associated with higher stress levels among nurses. Interestingly, our study also found that nurses with fewer years of service reported higher stress levels compared to their more experienced counterparts (Table 4). This result may be attributed to the challenges that early‐career nurses face, including limited professional experience, difficulties in clinical decision‐making, and challenges in adapting to institutional routines and shift work. Junior nurses may also have less confidence in managing patient‐related demands and less access to social or organizational support. In contrast, nurses with longer professional experience may have developed effective coping mechanisms and stronger resilience against occupational stressors. Similar results have been observed in other studies, suggesting that professional experience acts as a protective factor against stress among nurses (Türkdoğan Göngör and Erbay 2024; Cybulska et al. 2022). These findings emphasize the importance of structured mentorship and stress management programs tailored to early‐career nurses.

The study has several strengths. First, although the study addresses well‐established topics in nursing—such as stress, nutrition, and physical activity—it is, to our knowledge, the first to comprehensively and simultaneously examine the interrelationships between occupational factors (such as working hours and years of service) and nurses’ nutrition, physical activity, and stress within the specific context of Türkiye. Second, to ensure the soundness of the methodology and the reliability of the results, validated instruments such as the IPAQ‐SF and the NSS were used, and a representative sample was selected, which enhances the credibility of the findings. However, there are some limitations. First, as this study employed a cross‐sectional design, it is not possible to establish causal relationships between working conditions and nurses’ nutritional status, physical activity, or stress levels. Therefore, all interpretations should be made with caution, and longitudinal or experimental studies are needed to better clarify the direction and potential causal pathways of these associations. Second, some anthropometric measures (body weight and height) and nutritional data in our study were collected by self‐report; therefore, there may be recall or reporting bias in the data. In addition, social desirability bias may have influenced participants’ responses, particularly in the reporting of dietary habits and anthropometric measures. These limitations may have led to underestimation or overestimation of true dietary intake and anthropometric indicators. Future studies are recommended to use objective assessment methods, such as direct observation of dietary intake and the use of validated body composition analysis devices, to enhance data accuracy and reduce subjective bias. Third, several factors may limit the generalizability of the findings. These include the selection of the study sample from the inclusion of only female nurses, and the restriction to private hospitals. Although focusing on female nurses reflects the gender distribution in Türkiye's nursing workforce, it limits the generalizability of the findings to male nurses, who may experience different stress responses and exhibit distinct patterns of physical activity and dietary behaviors. Furthermore, working conditions, organizational structures, and workloads may differ between private and public healthcare institutions, limiting the applicability of the findings to nurses in the public sector. Thus, the findings may not be generalized to male nurses, nurses working in public hospitals, or those in other international settings. Replication in larger and more diverse samples is needed to confirm and extend these findings. Moreover, the relatively long working hours of nurses in this study, when compared to the standard weekly hours in many Western countries, may limit the international generalizability of the findings. These contextual differences should be taken into account when interpreting the results. Fourth, some potential confounding factors (e.g., work department, specific nursing roles, family responsibilities, and individual psychological characteristics such as anxiety, depression, coping style) were not assessed in this study. These factors may influence outcomes related to stress, work–life balance, and health‐related behaviors, including dietary intake, and should be considered in future research to enable a more comprehensive understanding of the associations observed. Fifth, this study focused on weekly working hours and total years of service as primary indicators of working conditions, due to their direct relevance to occupational stress and health‐related behaviors. However, other important dimensions of working conditions, such as shift patterns, workload intensity, and workplace environment, were not included in the analytical models. This may limit the comprehensiveness of the findings. Future research should aim to incorporate these variables to provide a more holistic understanding of how different aspects of working conditions influence nurses’ health outcomes.

4.1. Implications for Nursing and Health Policy

This study highlights the critical need to improve nurses’ working conditions, reduce occupational stress levels, and promote healthier lifestyle behaviors. The observed associations between adverse working conditions (e.g., prolonged working hours) and detrimental health outcomes (e.g., heightened stress, poor nutritional status, and low physical activity) necessitate immediate and coordinated policy action from multiple stakeholders. Public and private hospital administrations should implement structured programs to monitor and manage occupational stress and to promote healthy lifestyle behaviors among nurses. Such programs may include providing accessible healthy food options across all shifts, integrating nutritional counseling into occupational health services, facilitating physical activity through dedicated time or incentives, and incorporating regular stress monitoring alongside resilience and mindfulness training into professional development programs. In addition to hospital administrators, policymakers, government health authorities, and nursing unions should take an active role in shaping policies that safeguard nurses’ rights and well‐being. To mitigate the impact of high job demands on nurses’ health, healthcare policies should enforce maximum shift lengths, guarantee uninterrupted rest breaks, and maintain optimal nurse‐to‐patient ratios, thereby reducing stress and promoting healthier lifestyles. Furthermore, the lower stress levels observed among more experienced nurses in this study highlight the protective role of experience. Policies should establish formal mentorship and peer‐support programs, encouraging experienced nurses to guide junior nurses in stress management, clinical problem‐solving, and professional adaptation. Such systemic changes are crucial for fostering a healthier work environment and preventing long‐term adverse health consequences among nurses. These reforms will not only safeguard nurses’ rights and well‐being but also enhance the quality, safety, and sustainability of patient care across the nation.

5. Conclusion

This study highlights the multifactorial associations between working conditions and nurses’ health and well‐being. Results reveal that demanding working conditions are significantly associated with lower physical activity, unbalanced nutritional status, and higher stress levels. Given nurses’ essential role in healthcare, policy interventions are needed to mitigate the potential negative associations of long working hours, and institutions should promote supportive work environments.

Author Contributions

Study design: EK and IK. Data collection: EK and IK. Data analysis: EK. Study supervision: EK and IK. Manuscript writing: EK. Critical revisions for important intellectual content: EK and IK.

Funding

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Keskin, E. , and Kalkan I.. 2025. “Are Working Conditions of Nurses Associated With Nutrition, Physical Activity, and Stress Levels?.” International Nursing Review 72, no. 4: e70133. 10.1111/inr.70133