Does food insecurity affect musculoskeletal symptoms,fatigue,and productivity of municipality cleaners? A cross-sectional study

Abstract

BACKGROUND:

Municipality cleaners are exposed to food insecurity, Musculoskeletal Symptoms (MSs), and fatigue.

OBJECTIVE:

This study aimed to investigate the effect of food insecurity on MSs, fatigue, and productivity among municipality cleaners.

METHODS:

This study was conducted on 399 Iranian male municipality cleaners with at least one year of working experience. The data were gathered via a demographic/occupational questionnaire, the Persian version of the Household Food Insecurity Access Scale (P-HFIAS), the Persian version of Nordic Musculoskeletal Questionnaire (P-NMQ), the Persian version of the Multidimensional Assessment of Fatigue scale (P-MAF), and the Persian version of Health and Work Questionnaire (P-HWQ). Data were analyzed using descriptive statistics, multiple logistic regression (Forward Wald), and multiple linear regression (Stepwise).

RESULTS:

The findings revealed that 42.6%of the municipality cleaners were in the ‘severely food insecure’ category. The highest prevalence of MSs in the past week were related to knees (35.8%), lower back (35.1%), and ankles/feet (28.8%). Based on the results, the chance of MSs in the shoulders (OR = 1.66) and ankles/feet (1.60) regions, and MSs at least in one body region (OR = 1.47) was higher in the individuals with severe food insecurity than the others. Considering the P-MAF, food insecurity was associated with the ‘degree and severity’, ‘distress that it causes’, and ‘timing of fatigue’ subscales and ‘total fatigue’. Considering the P-HWQ, food insecurity was associated with ‘productivity’, ‘other’s assessment’, ‘concentration/focus’, ‘supervisor relations’, ‘non-work satisfaction’, and ‘impatience/irritability’ subscales.

CONCLUSION:

The study revealed an association between food insecurity and MSs in some body regions and fatigue and productivity subscales among the municipality cleaners. Nutritional and ergonomic programs are recommended to reduce municipality cleaners’ food insecurity, MSs, and fatigue and enhance their productivity.

Keywords

Fatigue food insecurity musculoskeletal symptom productivity

1 Introduction

Municipality cleaners are a working group that has a significant role in public environments [1]. They frequently work outside regular working hours [2]. They use a broom and a shovel to clean off litter and waste from the streets [1]. This working group is encountered with various risk factors, such as high workload (both physical and mental), time pressure, monotony, and lack of control on the work-rest cycle [3]. Literature has shown that 50–70%of municipality cleaners reported that they were encountered with excessive work rates [4]. Despite the large amount of work done by these workers, evidence has revealed that municipality cleaners usually get lower wages than most other occupations [2]. This issue (low wage) could restrict access to life necessities, such as sufficient food [5]. Food insecurity, which the United States Department of Agriculture (USDA) has defined as a household-level social and economic condition of limited/uncertain access to adequate food, is a significant national health problem and an under-recognized social determinant of health [6]. One potential consequence of food insecurity is its direct/indirect adverse effects on individuals’ health and quality of life [7].

Municipality cleaners are potentially exposed to a variety of occupational diseases (e.g., gastrointestinal, respiratory, and other infectious diseases as well as Musculoskeletal Symptoms (MSs)) [8, 9]. MSs are one of the most important occupational health topics, resulting in sickness absence from work [10], compensation claims [11], presenteeism [12], and reduced productivity and performance at work [10]. Based on the National Institute for Occupational Safety and Health (NIOSH), MSs are multifactorial, as several factors may contribute to developing these problems in occupational groups [13]. In this context, individual and organizational factors, such as socioeconomic status, have been disclosed to be critical predictive variables [14].

It has been reported that fatigue could affect workers in the street cleaning process [15]. Fatigue is widespread in the working population [16] and varies in duration and intensity [17]. In this context, some studies have reported that fatigue was related to socioeconomic status [18, 19]. Indeed, Pelders and Nelson concluded that low nutritional status was a noted contributor to mineworkers’ fatigue [19]. Furthermore, workers’ socioeconomic factors, including income [20] and nutritional status [21], might impact productivity loss improvements. Kim and Garman stated that the people who had higher levels of financial stress [22], which could lead to food insecurity [23], had lower workplace performance and productivity in comparison to their colleagues [22].

Municipality cleaners comprise a big workforce group employed in the municipal waste management organization. This working group work in bad ergonomic working conditions (e.g., awkward postures, manual material handling, and extra force exertion) for a long time. Besides, they do not usually have access to sufficient amounts of safe and nutritious food because of low wages. This situation can collectively lead to the development of MSs, fatigue, and loss of productivity. The present study hypothesized that food insecurity among municipality cleaners could effectively develop MSs, fatigue, and productivity loss.

2 Materials and methods

In this cross-sectional study conducted from June to August 2019, 399 Iranian male municipality cleaners with at least one year of working experience participated (response rate: 94.77%). Workers with underlying diseases or accidents affecting the musculoskeletal system were excluded from the study. The participants were selected from Shiraz municipality waste management organization through simple random sampling using the table of random numbers. Subjects voluntarily participated after receiving information about the study objectives. The study was approved by the ethic committee of Shahid Beheshti University of Medical Sciences (Approval ID: IR.SBMU.RETECH.REC.1398.269). Additionally, the study was performed in accordance with the Declaration of Helsinki of 2013 [24]. Each participant received the below-mentioned questionnaires in his workplace.

Data gathering tools:

Demographic/occupational questionnaire: This questionnaire included questions about age, weight, height, job tenure, working h/day, marital status, number of children, and education level.

Persian version of the Household Food Insecurity Access Scale (P-HFIAS): This tool is a user-friendly scale for measuring the access component of household food security. P-HFIAS consisted of nine occurrence questions that represented a generally increasing level of food insecurity severity (access) and nine ‘frequency-of-occurrence’ questions asked as a follow-up to each occurrence question to determine how often the condition occurred. The respondents were asked to reflect their experiences of food insecurity in the past month [25]. The psychometric properties of the P-HFIAS have been surveyed by Salarkia et al. (α= 0.95) [26].

Persian version of the Nordic Musculoskeletal Questionnaire (P-NMQ): P-NMQ examined the reported prevalence of MSs in different body regions among the study population [27]. In the present study, the reported MSs were limited to the past week. The psychometric properties of the P-NMQ have been examined by Choobineh et al. [28].

Persian version of the Multidimensional Assessment of Fatigue (P-MAF) scale: MAF scale was developed by Belza et al. (1993) among older adults with rheumatoid arthritis [29]. Also, it has been used in other populations and working groups [30]. A total of 16 items are included in the MAF scale to assess various aspects of fatigue. This scale is a self-administered tool to assess four dimensions of fatigue, including degree and severity, amount of distress it causes, it’s timing, and the degree to which fatigue interferes with daily living activities. The participants were asked to reflect their experiences of fatigue in the past week [29]. The psychometric properties of the P-MAF have been surveyed by Daneshmandi et al. (α≥0.854 for all subscales) [31].

Persian version of Health and Work Questionnaire (P-HWQ): HWQ was developed by Shikiar et al. (2004) to assess various aspects of workplace productivity. HWQ consists of 30 questions responded through a 10-point Likert scale. The items are grouped into six subscales, including productivity (own assessment and other’s assessment), concentration/focus, supervisor relations, work and non-work satisfaction, and impatience/irritability in this questionnaire [32]. It is worth mentioning that concentration/focus and impatience/irritability subscales are in reverse mode. This means that higher scores represent lower concentration/focus and impatience/irritability. The psychometric properties of the P-HWQ have been examined by Daneshmandi et al. (α≥0.65 for all subscales) [33].

2.1 Statistical methods

Data were analyzed by the IBM SPSS version 21, using descriptive statistics, multiple logistic regression (Forward Wald), and multiple linear regression (Stepwise).

For multiple logistic regression (Forward Wald), in the first step, the association between variables, such as age, Body Mass Index (BMI), job tenure, working h/day, marital status, number of children, education level with MSs in different body regions were examined via a χ2 test with a significance level of p≤0.25 [34]. For this aim, the quantitative variables were divided into two categories (age≤35 years and age > 35 years, BMI≤24.9 and BMI > 25, number of children = 0 and number of children ≥1, job tenure≤10 years and job tenure > 10 years, and working h/day≤8 hours and working h/day > 8 hours). Subsequently, all the independent variables that had significant associations were included in the multivariate logistic regression model.

For multiple linear regression (Stepwise), variables (including age, BMI, job tenure, working h/day, and food insecurity) with p≤0.25 [34] in the univariate test were entered into the model. A p-value < 0.05 was considered to be statistically significant.

3 Results

Some demographic/occupational details of the studied municipality cleaners have been presented in Table 1. The participants reported that their average wage was 20,000,000 Rials (about 167 USD) per month.

Table 1
Some demographic/occupational details of the studied municipality cleaners (n = 399)

Quantitative variables Mean±standard deviation

Age (years) 40.21±7.58

Weight (kg) 69.40±12.91

Stature (cm) 170.97±8.54

BMI (kg.m–^2 ) 23.83±5.23

Job experience (years) 10.49±5.74

Working h/day 8.20±0.80

Qualitative variables* No. (%)

Marital status

Single 25 (6.3%)

Married 374 (93.7%)

Number of children

0 25 (6.3%)

1–3 319 (79.9%)

4–7 55 (13.8%)

Educational level

Diploma 391 (98.0%)

Associate degree 8 (2.0%)

Quantitative variables	Mean±standard deviation
Age (years)	40.21±7.58
Weight (kg)	69.40±12.91
Stature (cm)	170.97±8.54
BMI (kg.m–^2 *)	23.83±5.23
Job experience (years)	10.49±5.74
Working h/day	8.20±0.80
Qualitative variables	No. (%)
Marital status
Single	25 (6.3%)
Married	374 (93.7%)
Number of children
0	25 (6.3%)
1–3	319 (79.9%)
4–7	55 (13.8%)
Educational level
Diploma	391 (98.0%)
Associate degree	8 (2.0%)

^*Body Mass Index.

The frequency of food insecurity among the studied individuals has been presented in Table 2. Accordingly, 42.6%of the participants were in the ‘severely food insecure’ category. Besides, the mean±standard deviation of the participants’ food insecurity was 13.22±4.78.

Table 2

The frequency of food insecurity among the study participants (n = 399)

Food insecurity	No. (%)
Food secure	51 (12.8)
Mildly food insecure	65 (16.3)
Moderately food insecure	113 (28.3)
Severely food insecure	170 (42.6)

Table 3 presents the prevalence of MSs in different municipality cleaners’ body regions during the past week. As the table depicts, the highest prevalence rates were related to knees (35.8%), lower back (35.1%), and ankles/feet (28.8%).

Table 3

The frequency of reported MSs in different body regions among the municipality cleaners during the past week (n = 399)

Body region	MSs
	No.	%
Neck	85	21.3
Shoulders	96	24.1
Elbows	56	14.0
Wrists/hands	99	24.8
Upper back	93	23.3
Lower back	140	35.1
Thighs	73	18.3
Knees	143	35.8
Ankles/feet	115	28.8

Table 4 shows the association between potential risk factors and MSs in different body regions of participants, using multiple logistic regression. As shown, independent variables, including BMI, job tenure, working h/day, number of children, and food insecurity, were significantly associated with MSs in participants’ different body regions.

Table 4

Modeling on the association between potential risk factors and MSs in different body regions of participants, using multiple logistic regression (n = 399)

Body region	Association between potential risk factors and MSs
	Potential risk factor	OR	95%CI	p-value
Neck	−	−	−	−
Shoulders	Food insecurity
	Non-severe: Reference	1.66	1.04–2.63	0.032
	Severe
Elbows	Number of children
	0: Reference	1.76	1.01–3.16	0.041
	≥1
	Job tenure (years)
	≤10: Reference	2.59	1.39–4.82	0.003
	> 10
Wrists/hands	−	−	−	−
Upper back	−	−	−	−
Lower back	BMI (kg.m^-2)^*
	≤24.9: Reference	1.81	1.06–3.08	0.029
	> 25
Thighs	−	−	−	−
Knees	Number of children
	0: Reference	3.10	1.04–9.23	0.042
	≥1
Ankles/feet	Food insecurity
	Non-severe: Reference	1.60	1.03–2.47	0.033
	Severe
MSs at least in one body region	Working h/day
	≤8: Reference	2.14	1.17–3.90	0.012
	> 8
	Food insecurity
	Non-severe: Reference	1.47	1.11–2.13	0.029
	Severe

^* Body Mass Index.

The means, standard deviations, minimum and maximum P-MAF scores, and P-HWQ subscales among the studied population are shown in Table 5.

Table 5

Descriptive statistics about the P-MAF and P-HWQ subscales (n = 399)

P-MAF subscales	M (SD)	Min	Max
Degree and severity (2 items)	5.69 (1.67)	1	10
Distress that it causes (1 item)	4.83 (1.94)	1	10
Degree of interference in daily living activities (11 items)	4.18 (0.79)	1	9.18
Timing of fatigue (1 item)	5.83 (0.42)	2.5	9.18
Total fatigue (15 items)	26.24 (6.79)	9.18	48.95
P-HWQ subscales
Productivity (11 items)	7.72 (1.53)	1.82	10
–Own assessment (5 items)	7.66 (1.35)	2.8	10
–Other’s assessment (6 items)	7.77 (1.85)	1	10
Concentration/focus (4 items)^*	3.42 (1.14)	1	10
Supervisor relations (2 items)	7.46 (1.99)	1.5	10
Non-work satisfaction (3 items)	7.21 (2.49)	1	10
Work satisfaction (4 items)	6.99 (1.50)	2.25	10
Impatience/irritability (3 items)^*	2.59 (1.94)	1	10

^*Reverse mode: a higher score represents lower ‘concentration/focus’ or ‘impatience/irritability’.

In Table 6, the multiple linear regression model demonstrates the association between potential risk factors and P-MAF and P-HWQ subscales. As shown, independent variables, including age, BMI, and food insecurity, were significantly associated with some P-MAF and P-HWQ subscales.

Table 6

Modeling on the association between potential risk factors and P-MAF and P-HWQ subscales, using multiple linear regression (n = 399)

P-MAF subscales	Association between potential risk factors and P-MAF and P-HWQ subscales
	Potential risk factor	B	Standard Error	p-value
Degree and severity	Food insecurity	0.062	0.015	< 0.001
	Age (years)	0.039	0.017	0.021
Distress that it causes	Food insecurity	0.047	0.018	0.005
Degree of interference in daily living activities	–	–	–	–
Timing of fatigue	Food insecurity	0.087	0.013	< 0.001
	Age (years)	0.032	0.015	0.038
Total fatigue	Food insecurity	0.092	0.044	0.036
P-HWQ subscales
Productivity	Food insecurity	–0.018	0.008	0.032
–Own assessment	–	–	–	–
–Other’s assessment	Food insecurity	–0.021	0.009	0.025
Concentration/focus^†	Food insecurity	0.082	0.012	< 0.001
Supervisor relations	Food insecurity	–0.032	0.011	0.005
Non-work satisfaction	Food insecurity	–0.43	0.11	< 0.001
	BMI (kg.m^-2)^*	–0.048	0.18	0.008
Work satisfaction	–	–	–	–
Impatience/irritability^†	Food insecurity	0.049	0.011	< 0.001

^*Body Mass Index; ^† Reverse mode: a higher score represents lower ‘concentration/focus’ or ‘impatience/irritability’.

4 Discussion

This study was conducted to examine the effect of food insecurity on MSs, fatigue, and productivity among Iranian male municipality cleaners. The results showed that 42.6%of the participants had severe food insecurity. Based on our search in scientific databases, such as Web of Science, PubMed, Scopus, Embase, ProQuest, Magiran, Irandoc, IranMedex, no data were found about food insecurity among municipality cleaners. However, the frequency of severe food insecurity was reported as 7.5%among other Iranian populations, such as the general populations [26]. As mentioned earlier, the participants’ frequency of severe food insecurity was higher than the other general groups. This issue might be attributed to the fact that the average wage of the municipality cleaners is less than their current living expenses (e.g., home rent, clothing, children’s costs, and nutritional costs). In this context, it has revealed that low-wage jobs result in food insecurity [35].

The current study showed that the highest prevalence of MSs in the past week was linked to knees (35.8%), lower back (35.1%), and ankles/feet (28.8%). The findings also showed that food insecurity was associated with MSs in the shoulders and ankles/feet, and MSs at least in one body region. The prevalence of MSs in different body regions of the study population was similar to or lower than that reported among other Iranian working groups, including workers in orthotic and prosthetic workshops [36], office workers [33 , 38], assembly line workers [39], petrochemical industry workers [40, 41], healthcare providers, and manufacturing industries workers [37], and hospital attendants [42]. Based on the European Agency for Safety and Health at Work (EU-OSHA), cleaners are at risk of developing MSs in the back, neck, shoulders, elbows, hands, and lower limbs [8]. Nielsen indicated that the highest prevalence of MSs was related to the neck (63%), shoulders (63%), low back (36%), and elbows (27%) among Danish cleaners [9]. In a Swedish study also, Kilbom reported that the highest prevalence of MSs was linked to lower back (33%), shoulders (33%), neck (22%), and wrist (11%) among cleaners in the past seven days [43]. The differences observed in the prevalence of MSs might be attributed to the nature of work in different populations in terms of working conditions, working tools, the volume of work, and working hours.

Based on our findings, a positive association was observed between BMI and low back symptoms in the study population (OR = 1.81). Job tenure was a potential risk factor for elbow symptoms with OR = 2.59. Individuals with work experience more than 10 years were more susceptible to develop elbow symptoms than those with fewer years of work experience. Working h/day had a positive association with MSs at least in one body region (OR = 2.14). This means that chance of developing MSs among subjects with a working h/day more than 8 is higher than the other colleagues. A positive association was revealed between the number of children and elbow and knee symptoms with OR ranging from 1.76 to 3.10.

Our analysis showed a significant association between food insecurity and shoulders, ankles/feet symptoms, and MSs at least in one body region (OR ranging from 1.47 to 1.66). In this regard, interviews with the study population revealed that they had to work for a longer time due to job insecurity and provide their living necessities. It has been determined that losing one’s job has critical economic consequences on the person [44]. Consequently, the individuals who face the prospect of job loss may experience much ambiguity and uncertainty about losing their economic privileges and stability [45]. These issues (job insecurity and more effort to provide living necessities) could put individuals at a greater risk for MSs.

The findings of the current study revealed average mean scores of total fatigue and its subscales. Considering the P-MAF, a positive association was observed between age and ‘degree and severity’, and ‘timing of fatigue’ subscales. Our findings showed that food insecurity was associated with the ‘degree and severity’, ‘distress that it causes’, and ‘timing of fatigue’ subscales and ‘total fatigue’. This implies that an increase in food insecurity was associated with an increase in fatigue’s subscales, as mentioned above. In this context, Jeong reported that fatigue affected workers in the street cleaning process [15].

In some cases, the work-related stress and strains were found to be so high that the cleaners could not recover sufficiently after work, which might cause permanent fatigue in the long run [46]. It has been revealed that fatigue was one of the workers’ frequent complaints with excessive work and atypical working hours (e.g., municipality cleaners) due to low socioeconomic status [47]. A Dutch survey for the European Working Conditions Observatory (EWCO) indicated that evening or night work could cause fatigue among employees and disrupt their quality of life [48]. Moreover, Hamelin et al. disclosed that fatigue and feeling of powerlessness were the outcomes of the social implications of chronic food insecurity [49].

The results of the present study demonstrated higher-than-average mean scores of the productivity subscales. P-HWQ findings depicted a negative association between BMI and the ‘non-work satisfaction’ subscale. Besides, food insecurity was associated with the ‘productivity’, ‘other’s assessment’, ‘concentration/focus’, ‘supervisor relations’, ‘non-work satisfaction’, and ‘impatience/irritability’ subscales. This issue could eventually lead to a loss of total productivity.

Among municipality cleaners, job contents are sometimes repetitive, monotonous, and strenuous, and they have little control over the work organization and their job [50]. Evidence has revealed that employees in a service organization, such as municipality cleaners, are subjected to a high degree of work-related stress (both physical and mental), which is the primary reason for their poor performance and loss of productivity [51]. It has also been proved that excessive work and evening or night shifts could affect the workers’ behaviors, productivity, and attention during work [47]. As mentioned above, the present study participants were faced with job insecurity. Evidence has shown that job insecurity could result in a decrease in creativity and problem-solving ability [52], ultimately suggesting job insecurity to be detrimental to performance (or productivity). Besides, literature has revealed that loss of productivity was one of the social implications of food insecurity [49]. Thus, organizations have been recommended to provide employees with all facilities so that they will be able to do their work correctly and be productive [53].

4.1 Limitations

Regarding the cross-sectional nature of the study and the use of the self-report data gathering method, the findings are to be interpreted cautiously. Indeed, longitudinal and comprehensive studies are needed to achieve more robust results. Furthermore, the findings might not be generalizable to female municipality workers and other working groups.

4.2 Suggestions

Based on the findings, improvement of working and organizational conditions and nutritional and ergonomic corrective actions are recommended. Health policymakers must pay particular attention to this vulnerable group and provide special policy packages to empower and support them. Officials should also consider the economic and physical availability of the workers’ food and plan to improve their nutritional status. In this regard, increasing their food security is a priority to addressing health equity, escalating their economic efficiency by increasing their productivity, and promoting the community’s health. The following ergonomic solutions are recommended, as well:

Using ergonomic tools, such as broom and shovel, to prevent awkward postures.

Handling loads and objects by two or more people to prevent extra force exertion, especially in the lower back region.

Employment of enough workforce.

Using an appropriate work-rest schedule.

5 Conclusions

The study findings showed that 42.6%of the participants were in the ‘severely food insecure’ category. The highest prevalence of MSs in the past week was linked to knees, lower back, and ankles/feet. Our findings revealed average mean scores of total fatigue and its subscales. Besides, the subjects reported higher-than-average mean scores for productivity subscales. The results indicated an association between food insecurity and MSs in some body regions and fatigue and productivity subscales among the municipality cleaners. Thus, improvement of working and organizational conditions and the implementation of nutritional and ergonomic corrective actions in the workplace is recommended as necessary measures to decrease food insecurity, musculoskeletal symptoms, and fatigue and to increase productivity among municipality cleaners.

Footnotes

Acknowledgments

This study is related to project no. 1398/19146 from Shahid Beheshti University of Medical Sciences, Tehran, Iran.

The authors would like to thank the municipality cleaners who participated in the study. They would also like to thank Ms. A. Keivanshekouh at the Research Improvement Center of Shiraz University of Medical Sciences for improving the use of English in the manuscript.

Conflict of interest

None declared.

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