Risk of symptomatic osteoarthritis associated with exposure to ergonomic factors at work in a nationwide Italian survey

Data collectionStudy population

Data from the 2013 National Health Survey (NHS), conducted by the Italian National Institute of Statistics (hereafter: ISTAT) on a representative sample of the Italian population, were used to get information on sociodemographic factors, lifestyles, biological CVD risk factors, job title, symptomatic OA and comorbidities. In Italy, this survey is carried out periodically, generally every 5 years (Odone et al. 2018). The survey collects detailed information on individual and household socioeconomic characteristics and on health conditions, including perceived health, long-term chronic diseases, and functional limitations, as well as on lifestyles and use of health services. The survey is based on a two-stage sampling, with municipalities as primary sampling units and households as secondary sampling units. For each household, information is gathered for all the members belonging to the family unit, partly through face-to-face interviews and partly through a self-administered questionnaire, the latter mainly used to collect information on health conditions and lifestyles. For the 2013 survey, ISTAT collected information on 119,073 subjects from 1,456 municipalities, with a participation rate of 82.5% (Fabiani et al. 2016).

The study was restricted to employed men and women, because information on job codes with the maximum level of detail (ISTAT’s Classification of Professions, CP 2011 5-digit), which was needed to link exposure scores in the JEM to survey data, was available only for subjects still in employment. The study population was further restricted to subjects 40–69 years, given the very low prevalence of symptomatic OA among younger people, as well as to workers who reported to have worked in the same job for at least five years, to guarantee a minimum exposure duration (Fig. 1). The final sample included 14,812 men and 9,792 women.

Fig. 1figure 1

Selection of the study population

Exposure assessment

Exposure to ergonomic factors was assigned to the study population through a JEM constructed from the Italian O*NET database. O*NET contains information on hundreds of physical and mental descriptors, in terms of skills, knowledge, activities, work context, etc., aggregated at the job level (www.onetcenter.org). The Italian O*NET database includes scores of all these dimensions, constructed from workers’ self-reports, based on interviews of approximately 20 workers for each of the 796 jobs of the Italian classification (CP2011, 5-digit level). For each job, the O*NET database contains scores for each descriptor, rated by importance, frequency, or level of a certain workplace characteristic. Answers to these questions are collected on 5-point or 7-point level, depending on the item, which represent the score assigned by each worker to a certain work characteristic, averaged for each of the 796 occupations.

From the hundred variables available in O*NET, a JEM was constructed on 21 physical factors, which were further reduced through Principal Component Analysis to 17 factors potentially associated with musculoskeletal disorders. For all 17 factors, good reliability against the same items of a corresponding US O*NET JEM has been shown (d’Errico et al. 2019) (Table 1). Of the 17 items, 3 focussed on force exertion (static strength, dynamic strength, trunk strength), 6 on activity level and repetitive movements of the upper limb (manual dexterity, fingers dexterity, wrist-finger speed, handling and moving objects, time spent making repetitive motions, time spent using hands to handle, control, or feel objects, tools or controls), 4 on postures (awkward positions; standing; kneeling, crouching, stooping, or crawling; bending and twisting the body), 2 items on activities involving the whole body (performing generalized physical activity; walking and running), 2 items on exposure to vibration (whole-body vibration, driving vehicles or other types of moving machinery).

Table 1 Description of the items in the Italian O*NET databases used to construct the composite ergonomic index

Scores of each item were standardized on a 0–100 scale and averaged, to compute a composite ergonomic exposure index (Cronbach alpha = 0.90). Among the factors selected, those belonging to the “ability” and the “activity” domains are scored for both importance of a certain characteristic in a job and for the level of the characteristic, such as the level of an ability needed to perform a job or the level of an activity typical of that job. For these factors (manual and finger dexterity, trunk strength, handling and moving objects), importance is scored from 1 to 5, whereas level ranges from 1 to 7 (Table 1). In contrast, the other 7 factors, which belong to the “context” domain and focus on aspects of both job content and on workplace characteristics, are collected on a frequency scale from 1 to 5 (from never to all the time, or every day). ‘Level’ scores of items in the ‘work ability’ and ‘work activities’ domains were reclassified to a level equal to zero, if their importance score was below or equal to 1.

In the study population, the composite ergonomic exposure index (Ergo-index) had a mean equal to 25.6 (s.d. 14.3) and a range of scores of 2.9–60.8. The Ergo-index was strongly correlated with most items composing it, with all correlations above 0.70, except for whole-body vibration, driving and awkward postures (Table 2). For the analysis, it was categorized in four ordinal groups, with cut-offs in correspondence of the median (27.4) and the interquartile distribution (15.94, 35.68) of the original JEM.

Table 2 Pearson’s correlation coefficients between the Ergo-Index and each exposure item composing itOutcome

The outcome of the study was: “Self-reported doctor-diagnosed OA, for which drugs were taken in the previous 12 months, combined with moderate or severe limitations in daily activities”, defined as “symptomatic OA”. In detail, subjects were asked if they were affected by OA in any body region, if the disease was diagnosed by a physician, and whether they took any drug for the disease during the previous 12 months. The presence of physical limitations was ascertained through a question on limitations in normal daily activities lasting at least six months, with possible answers: severe limitations, non-severe limitations, no limitations.

Covariates

Information on potential confounding factors was collected through questionnaires in the NHS survey, including socio-demographics (age, gender, geographical area of residence), engagement in domestic work, leisure physical activity, smoking habit, overweight/obesity, diabetes, hypertension, cardiovascular diseases (CVD).

Overweight and obesity were derived from the body mass index (BMI), calculated on the self-reported height and weight in the survey, according to a standard procedure. Based on the WHO classification, BMI was categorized in normal weight (18.5 <  = BMI < 25), underweight (BMI < 18.5), overweight (25 <  = BMI <  = 30), and obese (BMI > 30). Information on diabetes, hypertension, and CVD at the time of the interview was collected through yes/no questions. Smoking habit was classified into five categories of lifetime smoking history, according to pack-years (py) smoked: never smoker (0 py), 0.1–10 py, 10.1–20 py, 20.1–30 py, and > 30 py.

Data analysis

The frequency distribution of covariates between workers affected or not by symptomatic OA was compared using chi-square statistics, for categorical variables, and t test, for continuous ones.

The relationship between prevalence of symptomatic OA and exposure to physical factors, represented by the Ergo-index kept continuous or categorized in quartiles, was examined by means of Poisson regression models with the Huber-White sandwich estimator of variance, also known as Poisson robust regression models. These models were used to avoid overestimation of the variance, which is known to affect confidence intervals of relative risks in Poisson models when applied to binomial data (Barros and Hirakata 2003).

A first analysis was adjusted only for age (5-year age classes), gender, and geographical area of residence (4 areas). In a second model, BMI (normal weight, overweight, obese, underweight), pack-years of smoking (5 categories), number of hours of domestic work per week (continuous), leisure physical activity (intense or regular, light, no activity), diabetes (yes/no), hypertension (yes/no) and prevalent CVD (yes/no) (including coronary heart disease and stroke) were also included as adjustment variables. The association between covariates and OA risk was assessed through the analysis based on Ergo-index quartiles. No adjustment was performed for educational level, as it was too strongly correlated with the Ergo-index (Spearman rho = 0.52), so there was concern about multicollinearity in the regression model (Vatcheva et al. 2016). The high correlation between education and exposure to ergonomic factors was partly caused by the use of a JEM, as education is known to strongly influence selection into job type (e.g., heavy manual, light manual, non-manual occupations). Furthermore, because JEMs provide overall mean scores by occupation, with no exposure variability within occupations, this may artificially increase the correlation between educational attainment and exposure to work factors displaying a social gradient.

Analyses were not stratified by gender, as in preliminary analyses adjusted for age and geographical area no significant interaction was found between gender and Ergo-index quartiles (all p values > 0.28).

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