Prevalence and risk factors for foot and ankle musculoskeletal disorders experienced by nurses

The study took place in a large paediatric hospital in Brisbane, Australia. Ethical approval was granted by Queensland University of Technology Human Research Ethics Committee and subsequent approval was given by the relevant hospital ethics committee. Letters of support and approval were provided by the occupational health and safety manager and nurse unit managers of the participating hospital. Questionnaires were distributed to all temporary and permanent nursing staff rostered to work at the time of the study (n = 416) in consultation with Nurse Unit Managers. All nurses from participating wards/work areas were provided with the questionnaire via the internal mail system. Consent to participate was implied by the return of a completed questionnaire. Two waves of survey distributions, followed by a non-responder survey, were used over a nine week period to promote participation, consistent with a modified Dillman technique [10].

A 13-page questionnaire was developed for the study, using a seven-step process [11] that included obtaining input from nurses, podiatrists, occupational health practitioners and epidemiologists. The survey was piloted with researchers, nurses and health care workers (n = 25), and revised to improve clarity and speed of completion. The final questionnaire comprised four parts containing questions about: 1) personal demographic and work characteristics; 2) MSDs (incorporating the standardised Nordic Musculoskeletal Questionnaire (NMQ) [12]); 3) foot health and foot conditions; and 4) general health status (SF36 Acute Version) [13]. An open-ended question “Is there anything else you would like to tell us about your foot problems or musculoskeletal problems to help us to better understand these issues?” was included as the final question in the survey. An a priori calculation of sample size assuming the prevalence of foot problems was 50%, determined that 385 responses would be required to ensure a 5% precision for the prevalence estimate. Lower prevalences would require fewer responses for the same precision. Previous staff surveys at the hospital suggested that more than 200 responses would be received. A final sample size target of all eligible permanent and temporary staff nurses rostered to work in the hospital during the recruitment period was used (n = 416).

Proposed risk factors for foot/ankle MSDs were determined based on the literature and discussions with nurses and podiatrists during the questionnaire development phase, focusing on individual characteristics and workplace characteristics. The individual characteristics included age, BMI, smoking history, general physical health (SF36 Acute- Physical Component Scores (PCS) [13]), number of self-reported foot conditions associated with foot discomfort (bunions, curled toes, flat feet, high arches, corns or callous, heel spur), and footwear features (shoe style, heel heights). The number of foot conditions was summed and categorised (none, one, two or more) to give a crude index of foot conditions. The workplace characteristics included: level of nursing position, hospital location, (mean) hours worked per week, hours worked in the last week and length of time since last break from work.

The three ankle/foot questions from the NMQ [12] component of the questionnaire were: ‘trouble (such as ache, pain, discomfort, numbness)’ in the last 12 months, ‘trouble during the last seven days’ and ‘prevented from carrying out normal activities (e.g. job, housework, hobbies) because of this trouble’ in the last 12 months. The outcome variables based on these questions were foot/ankle MSDs in the last 12 months, in the last seven days and activity-limiting foot/ankle MSDs. Reporting prevalence estimates for all three variables was deemed appropriate, given the small number of studies in this area have generally reported the annual prevalence in isolation.

The data were double-entered into a data set and imported into the Statistical Package for Social Sciences version 12.0 (SPSS Inc. – Chicago IL) which was used for all subsequent statistical analyses. SF36 PCS scores were calculated using the recommended formulae [13] and substituting Australian population norms [14]. Ambiguous responses and missing data for the SF36 were dealt with using techniques described by Ware and colleagues [13].

Continuous explanatory variables were coded into categorical variables using objective definitions (e.g. quartiles for SF 36 PCS scores) and with reference to categories accepted in the literature (e.g., World Health Organisation BMI groups [15]). This allowed for group comparisons and easier descriptions of differences between subjects based on these characteristics. A priori criteria were adopted to define meaningful relationships between adverse risk factors and outcome variables (statistically significant p < 0.05 or odds ratio > 2.0) so that neither statistical significance nor effect size dominated interpretation of potential importance, in this situation where sample size was calculated to ensure precision of MSD prevalence, rather than to power particular testing of hypotheses around risk factors.

Reliability testing of the NMQ responses from cashier workers (n = 44) has shown non-identical responses varying from 7-26% for annual prevalence and 6-19% for weekly prevalence questions after a one week test-re-test period. Non-identical responses for annual disability were lower, ranging from 0-8% [16]. Reliability of an extended version of the NMQ completed by 59 nursing students, after a 24 hour test-retest period, was better, with non identical responses of 10% for annual prevalence and 3% for annual disability on the foot problem questions [17].

Bivariate associations between the proposed risk factors and the specific outcome variable of activity-limiting foot or ankle MSDs were considered using logistic regression modelling. A multivariable model was used to assess the relationships between risk factors and the presence of activity-limiting foot or ankle MSDs, as these were considered to be the MSDs that had the greatest impact on the nurses, as well as being the most reliable based on the literature. For this model, the variable ‘average hours per week’ was collapsed to full-time and less than full-time workload (36 or more hours per week, <36 hours per week) because of the relative homogeneity in odds ratios across the categories used in the bivariate analyses. Odds ratios were reported in comparison to the designated referent (lowest risk group).

Of the 416 eligible nurses, 304 (73% response rate) returned a completed survey used for analysis. Twenty-three participants were males (7.6%), 276 were female (92.4%), 5 did not indicate gender. The ratio of male to female nurses followed the state nursing workforce average (9%: 91%) [18], as did the distribution of nurses across job levels and the proportion of nurses working full-time (53.9%) and part-time (46.1%) [19] and closely reflected the nursing workforce in Queensland in 2011 (9.8% males, 49.5% part-time) [20]. However, the mean age was 37 years, which was younger than the state average of 43 years [18] and lower than the 2011 national mean age of 44.2 yrs [20]. Twenty-six nurses (24% of the non-responders) returned a one-page non-respondents’ survey. Table 1 presents summary statistics for key characteristics of the responders and non-responders, with minimal differences between the groups. Compared to responders, the prevalence of foot MSDs in the last 12 months was 9% greater for non-responders (64%) but was essentially the same for foot MSDs in the last 7 days (40%) and for activity-limiting foot MSDs (16%).

The prevalence of MSDs across the different body regions are presented in Figure 1. Foot/ankle MSDs were the most prevalent conditions experienced by nurses during the preceding seven days (43.8%, 95% CI 38.2-49.4%), the second most prevalent MSD to impair nurses’ physical activity (16.7%, 95% CI 13.0-21.3%) and the third most prevalent MSD, after lower-back and neck problems, to be experienced by nurses during the preceding 12 months (55.3%, 95% CI 49.6-60.7%).

The bivariate relationships between the nurse characteristics and activity-limiting foot/ankle MSDs can be seen in Table 2. The nurse characteristics of older age (50+), obesity, general physical health (PCS) below the median and having 2 or more existing foot conditions more than doubled the odds of experiencing activity-limiting foot/ankle MSDs and each of these associations was statistically significant. There was a threefold increase in the odds of activity limiting foot/ankle MSDs for the work characteristic of working more than 32 hours per week, although this was not statistically significant and the odds more than doubled for nurses working in ICU (Table 3). Nurses who reported using insoles/orthoses in their footwear were also more likely to report disabling foot conditions (Bivariate analyses).

Multivariable modelling examined the independent contributions of the risk factors that met criteria for meaningful association with activity-limiting MSDs in the bivariate analyses, see Table 4. After adjustment, reporting activity-limiting foot/ankle MSDs was almost five times more likely for nurses who were obese (OR 4.74 CI 1.70-13.23) or those with 2 or more foot conditions (OR 5.59 CI 1.75,17.81) and six times more likely for nurses with physical health scores in the lowest quartile (OR 6.05 CI 1.64, 22.38). Working in the ICU increased the odds almost fourfold (OR 3.87 CI 1.23, 12.12). All of these results were statistically significant.

Although cross-sectional in nature, this study has provided important information regarding the high prevalence of foot/ankle MSDs among nurses and the fact that both individual characteristics of nurses and the nature and location of their work are linked to the occurrence of foot/ankle MSDs that are disabling. The sample reflected the broader nursing workforce in terms of distribution across gender, nursing positions and full-time vs part-time positions. However, it should be noted that the study targeted hospital nurses engaged in work tasks caring for paediatric patients, which may differ somewhat from the broader nursing workforce. A number of issues may have conservatively biased the prevalence estimates, namely, the younger (mean) age of the nurses in this study, the hospital admissions and nursing workload were at their lowest for the year (based on bed days and admissions) and nurses may have under-reported their MSDs, as observed in other studies [36, 37]. There were some additional limitations to the study. Psychosocial factors, such as job stress were not considered as risk factors in our study. Grouping of nurses across work locations also may have affected results, although this was done in consultation with nursing staff in an attempt to ensure that workload characteristics in pooled categories were as similar as possible. The study did not determine if nurses electing to use insoles/orthoses initiated this as self-treatment or if they had been prescribed by health professionals. Further research is required to determine not only the effectiveness of orthoses, but also the extent to which other interventions e.g. medication are being utilised by nurses to relieve foot problems. Measurement of actual time periods nurses spent on their feet would have been a more accurate measure than hours worked per week (study measure), however it would have involved a more resource intensive observational design or relied on self-report.