The CUPID (Cultural and Psychosocial Influences on Disability) Study: Methods of Data Collection and Characteristics of Study Sample

Abstract

Background

The CUPID (Cultural and Psychosocial Influences on Disability) study was established to explore the hypothesis that common musculoskeletal disorders (MSDs) and associated disability are importantly influenced by culturally determined health beliefs and expectations. This paper describes the methods of data collection and various characteristics of the study sample.

Methods/Principal Findings

A standardised questionnaire covering musculoskeletal symptoms, disability and potential risk factors, was used to collect information from 47 samples of nurses, office workers, and other (mostly manual) workers in 18 countries from six continents. In addition, local investigators provided data on economic aspects of employment for each occupational group. Participation exceeded 80% in 33 of the 47 occupational groups, and after pre-specified exclusions, analysis was based on 12,426 subjects (92 to 1018 per occupational group). As expected, there was high usage of computer keyboards by office workers, while nurses had the highest prevalence of heavy manual lifting in all but one country. There was substantial heterogeneity between occupational groups in economic and psychosocial aspects of work; three- to five-fold variation in awareness of someone outside work with musculoskeletal pain; and more than ten-fold variation in the prevalence of adverse health beliefs about back and arm pain, and in awareness of terms such as “repetitive strain injury” (RSI).

Conclusions/Significance

The large differences in psychosocial risk factors (including knowledge and beliefs about MSDs) between occupational groups should allow the study hypothesis to be addressed effectively.

About the Authors:

David Coggon

* E-mail: [email protected]

Affiliation: Medical Research Council Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK

Georgia Ntani

Affiliation: Medical Research Council Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK

Keith T. Palmer

Affiliation: Medical Research Council Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK

Vanda E. Felli

Affiliation: School of Nursing, University of São Paulo, São Paulo, Brazil

Raul Harari

Affiliation: Corporación para el Desarrollo de la Producción y el Medio Ambiente Laboral – IFA (Institute for the Development of Production and the Work Environment), Quito, Ecuador

Lope H. Barrero

Affiliation: School of Engineering, Pontificia Universidad Javeriana, Bogotá, Colombia

Sarah A. Felknor

Affiliations Southwest Center for Occupational and Environmental Health, The University of Texas Health Science Center at Houston School of Public Health, Houston, Texas, United States of America, Center for Disease Control and Prevention/National Institute for Occupational Safety and Health, Atlanta, Georgia, United States of America

David Gimeno

Affiliation: Southwest Center for Occupational and Environmental Health, The University of Texas Health Science Center at Houston School of Public Health, Houston, Texas, United States of America

Anna Cattrell

Affiliation: Medical Research Council Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Kings College, London, UK

Consol Serra

Affiliations Center for Research in Occupational Health (CiSAL), Pompeu Fabra University, Barcelona, Spain, Carlos III Health Institute: Biomedical Research Networking Center of Epidemiology and Public Health, Granada, Spain, Occupational Health Department, Parc de Salut MAR, Barcelona, Spain

Matteo Bonzini

Affiliation: Epidemiology and Preventive Medicine Research Center, University of Insubria, Varese, Italy

Eleni Solidaki

Affiliation: Department of Social Medicine, Medical School, University of Crete, Heraklion, Greece

Eda Merisalu

Affiliation: Department of Public health, University of Tartu, Tartu, Estonia

Rima R. Habib

Affiliation: Department of Environmental Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon

Farideh Sadeghian

Affiliation: Department of Occupational Health, Faculty of Health, Shahroud University of Medical Sciences, Shahroud, Iran

Masood Kadir

Affiliation: Department of Community Health Sciences, Aga Khan University, Karachi, Pakistan

Sudath S. P. Warnakulasuriya

Affiliation: Department of Medical Education and Health Sciences, Faculty of Medical Sciences, University of Sri Jayewardenepura, Gangodawila, Nugegoda, Sri Lanka

Ko Matsudaira

Affiliation: Clinical Research Centre for Occupational Musculoskeletal Disorders, Kanto Rosai Hospital, Kawasaki, Japan

Busisiwe Nyantumbu

Affiliations National Institute for Occupational Health, National Health Laboratory Service, Johannesburg, South Africa, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa

Malcolm R. Sim

Affiliation: Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia

Helen Harcombe

Affiliation: Department of Preventive and Social Medicine, University of Otago, Dunedin, New Zealand

Ken Cox

Affiliation: Medical Research Council Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK

Maria H. Marziale

Affiliation: School of Nursing of Ribeirão Preto, University of São Paulo, São Paulo, Brazil

Leila M. Sarquis

Affiliation: Federal University of Paraná, Curitiba-PR, Brazil

Florencia Harari

Affiliation: Corporación para el Desarrollo de la Producción y el Medio Ambiente Laboral – IFA (Institute for the Development of Production and the Work Environment), Quito, Ecuador

Rocio Freire

Affiliation: Corporación para el Desarrollo de la Producción y el Medio Ambiente Laboral – IFA (Institute for the Development of Production and the Work Environment), Quito, Ecuador

Natalia Harari

Affiliation: Corporación para el Desarrollo de la Producción y el Medio Ambiente Laboral – IFA (Institute for the Development of Production and the Work Environment), Quito, Ecuador

Magda V. Monroy

Affiliation: School of Engineering, Pontificia Universidad Javeriana, Bogotá, Colombia

Leonardo A. Quintana

Affiliation: School of Engineering, Pontificia Universidad Javeriana, Bogotá, Colombia

Marianela Rojas

Affiliation: Institute for Studies on Toxic Substances (IRET), National University of Costa Rica, Heredia, Costa Rica

Eduardo J. Salazar Vega

Affiliation: Southwest Center for Occupational and Environmental Health, The University of Texas Health Science Center at Houston School of Public Health, Houston, Texas, United States of America

E. Clare Harris

Affiliation: Medical Research Council Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK

Sergio Vargas-Prada

Affiliation: Center for Research in Occupational Health (CiSAL), Pompeu Fabra University, Barcelona, Spain

J. Miguel Martinez

Affiliations Center for Research in Occupational Health (CiSAL), Pompeu Fabra University, Barcelona, Spain, Carlos III Health Institute: Biomedical Research Networking Center of Epidemiology and Public Health, Granada, Spain

George Delclos

Affiliations Southwest Center for Occupational and Environmental Health, The University of Texas Health Science Center at Houston School of Public Health, Houston, Texas, United States of America, Center for Research in Occupational Health (CiSAL), Pompeu Fabra University, Barcelona, Spain, Carlos III Health Institute: Biomedical Research Networking Center of Epidemiology and Public Health, Granada, Spain

Fernando G. Benavides

Affiliations Center for Research in Occupational Health (CiSAL), Pompeu Fabra University, Barcelona, Spain, Carlos III Health Institute: Biomedical Research Networking Center of Epidemiology and Public Health, Granada, Spain

Michele Carugno

Affiliation: Department of Occupational and Environmental Health, Università degli Studi di Milano, Milan, Italy

Marco M. Ferrario

Affiliation: Epidemiology and Preventive Medicine Research Center, University of Insubria, Varese, Italy

Angela C. Pesatori

Affiliations Department of Occupational and Environmental Health, Università degli Studi di Milano, Milan, Italy, Fondazione Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy

Leda Chatzi

Affiliation: Department of Social Medicine, Medical School, University of Crete, Heraklion, Greece

Panos Bitsios

Affiliation: Department of Psychiatry, Medical School, University of Crete, Heraklion, Greece

Manolis Kogevinas

Affiliations Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain, IMIM (Hospital del Mar Research Institute), Barcelona, Spain, Consorcio de Investigación Biomédica de Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain, National School of Public Health, Athens, Greece

Kristel Oha

Affiliation: North Estonia Medical Centre, Tallinn, Estonia

Tuuli Sirk

Affiliation: Põlva Hospital, Põlva, Estonia

Ali Sadeghian

Affiliation: Klinikum Leverkusen, Leverkusen, Germany

Roshini J. Peiris-John

Affiliations Department of Physiology, Faculty of Medical Sciences, University of Sri Jayewardenepura, Gangodawila, Nugegoda, Sri Lanka, Section of Epidemiology and Biostatistics, School of Population Health, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand

Nalini Sathiakumar

Affiliation: Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America

A. Rajitha Wickremasinghe

Affiliation: Faculty of Medicine, University of Kalaniya, Kelaniya, Sri Lanka

Noriko Yoshimura

Affiliation: Department of Joint Disease Research, University of Tokyo, Tokyo, Japan

Danuta Kielkowski

Affiliations National Institute for Occupational Health, National Health Laboratory Service, Johannesburg, South Africa, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa

Helen L. Kelsall

Affiliation: Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia

Victor C. W. Hoe

Affiliations Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia, Centre for Occupational and Environmental Health, Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia

Donna M. Urquhart

Affiliation: Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia

Sarah Derett

Affiliation: Injury Prevention Research Unit, Department of Preventive and Social Medicine, University of Otago, Dunedin, New Zealand

David McBride

Affiliation: Department of Preventive and Social Medicine, University of Otago, Dunedin, New Zealand

Andrew Gray

Affiliation: Department of Preventive and Social Medicine, University of Otago, Dunedin, New Zealand

Introduction

Musculoskeletal disorders of the back, neck and upper limb are a major cause of morbidity and disability with substantial economic impact, especially in western countries. In some cases symptoms arise from identifiable pathology in the spine or arm (e.g. a herniated inter-vertebral disc or peripheral nerve compression in the carpal tunnel). Most often, however, the underlying pathology is unclear, and the symptoms are classed as “non-specific”.

Epidemiological research has linked the occurrence of back, neck and upper limb disorders with various physical activities in the workplace [1]–[4], and also with psycho-social risk factors such as low mood and job dissatisfaction [5]–[8]. More recently, evidence has accumulated for a causal role also of “somatising tendency” (i.e. a general tendency to report and worry about common somatic symptoms) [6], [9]. Together, however, these established risk factors do not adequately explain striking temporal changes that have been observed in disability attributed to common musculoskeletal complaints. For example, in Britain rates of incapacity for work because of back problems increased more than sevenfold between 1953 and 1992 at a time when the physical demands of work were generally reducing [10]; and in Australia there was a major epidemic of disability from arm pain during the early 1980s which was not paralleled in other countries where similar technologies and working methods were employed [11].

This gap in understanding has prompted the hypothesis that the development and persistence of non-specific musculoskeletal complaints and resultant disability are importantly influenced by culturally-determined health beliefs as well as by physical activities and mental health [12]. Several observations provide support for a role of health beliefs. For example, among 178 workers carrying out repetitive tasks on an assembly line in Mumbai, India, only one of whom had ever heard of “RSI” (repetitive strain injury), the 12 month prevalence of disabling arm pain (5%) was less than one fifth of that found using the same questions among manual workers in the UK (including those who were of Indian sub-continental origin) [13]. In longitudinal studies of individuals with back and arm pain, negative beliefs about prognosis have proved predictive of their persistence [7], [14]. And in Victoria, Australia, a community-based intervention aimed at modifying people’s beliefs and expectations about back pain was followed by a reduction in morbidity that was not paralleled in a control state [15].

This is not to say that common musculoskeletal symptoms never arise from traumatic injury to tissues. For the most part, however, such injuries would be expected to heal spontaneously over a period of days or weeks, as in other parts of the body. The influence of health beliefs, low mood and somatising tendency is likely to be more on the persistence of symptoms and levels of associated disability than on the occurrence of acute and transient symptoms.

If the hypothesised role of health beliefs were correct, it would have important practical implications. There might be scope for interventions aimed at modifying beliefs and expectations, along the lines of the successful campaign on back pain in Victoria, Australia [15]. More importantly, however, there would be a need for wider review of strategies aimed at preventing work-related musculoskeletal disorders. Currently, preventive efforts focus largely on reduction of physical stresses to the back and arm so as to minimise the risk of injury and maximise opportunities for continued employment in those who have developed symptoms. However, this approach may reinforce beliefs that even quite minor physical stresses (e.g. from use of a computer keyboard) can be seriously hazardous, and might thereby increase workers’ vulnerability to long-term symptoms and disability.

The CUPID (Cultural and Psychosocial Influences on Disability) study was designed to explore further the impact of cultural and psychosocial influences on musculoskeletal symptoms and associated disability. It aims to compare the prevalence of symptoms and disability in workers who are carrying out jobs with similar physical demands, but in a range of cultural environments, and to explore risk factors for the incidence and persistence of symptoms and disability in these varying cultural environments. We here describe the methods by which participants have been recruited and data collected, summarise various characteristics of the study sample, and discuss strengths and limitations of the study method.

Methods

Ethical Approval

Ethical approval for the study was provided by the relevant research ethics committee or institutional review board in each participating country (Appendix S1). Written informed consent was obtained from all participants with the following exceptions. For self-administered questionnaires in the UK and Iran, information about the study was provided, and consent to the baseline survey was deemed to be implicit in the return of a completed questionnaire. In Lebanon, according to local practice, oral informed consent was obtained from all participants before interview, and this was recorded on a form signed and dated by the interviewer. In all cases, the method of obtaining consent was approved by the relevant research ethics committee.

Overview

The study focuses on 47 occupational groups from 18 countries (1–4 groups per country), from which information has been collected by means of an initial baseline questionnaire, followed by a further, shorter questionnaire after an interval of 12 months. Data collection in each country was led by a local investigator, who forwarded anonymised computerised data files to a team at the University of Southampton for collation and analysis (several earlier papers have described analyses based, all or in part, on components of the study in individual countries [16]–[22]). Local investigators also provided background information on the socio-economic circumstances of their study cohorts – for example, on levels of unemployment in the local community and eligibility for sick pay and compensation for occupational injuries.

Identification and Recruitment of Participants

Local investigators were asked to recruit samples of nurses, office workers who regularly used a computer keyboard and/or mouse, and workers who carried out repetitive manual tasks with their arms or hands. Postal workers sorting mail were identified in advance as a group of manual workers who might be suitable for study, but other sources of manual workers were allowed at the discretion of the local investigator. In one country (Japan), a group of sales and marketing workers was also recruited, and in the presentation and discussion of results, three main categories of occupation are distinguished – nurses, office workers, and “other workers”, the last including the sales and marketing group as well as various manual occupations.

The aim was to restrict the international analysis to workers aged 20–59 years, who had been in their current job for at least 12 months. However, local investigators were free to recruit and carry out local analyses without these restrictions. Initial power calculations indicated that a sample size of 200 workers per occupational group would be more than adequate to detect differences between countries in the prevalence of symptoms and disability of the magnitude that was anticipated, and also for analysis of important risk factors for the incidence and persistence of pain at different anatomical sites in the longitudinal follow-up.

Table 1 describes the occupational groups that were selected for study, and the methods by which participants were identified and the baseline questionnaire administered. In most cases, potentially eligible subjects were identified from employers’ records, sometimes with random sampling to achieve the desired sample size. Some occupational groups provided information at interview, and others by self-completion of questionnaires. In one country (UK), most questionnaires were self-completed, but random sub-samples of each occupational group were instead interviewed.

[Figure omitted. See PDF.]

Table 1. Specification and recruitment of study sample.

https://doi.org/10.1371/journal.pone.0039820.t001

At the time of answering the baseline questionnaire, participants were asked whether they were willing to be re-contacted in the future, and those who agreed were asked (or will be asked) to complete a follow-up questionnaire after an interval of 12 months. In most cases, subjects have been followed up through their place of work, but where this was not possible (e.g. because they had left their original employer), they have been contacted at their home address. In each occupational group, follow-up questionnaires have been completed by the same method (interview or self-administration) as the baseline questionnaire.

Questionnaires

The baseline questionnaire (Appendix S2) asked about demographic characteristics; education; height; smoking habits; current occupation; pain in different anatomical regions and associated disability for tasks of daily living; awareness of others with musculoskeletal pain; fear-avoidance beliefs concerning upper limb and low back pain; awareness of repetitive strain injury (RSI) or similar terms; distress from common somatic symptoms; mental health; and sickness absence in the past 12 months because of musculoskeletal problems and other types of illness.

The questions about current occupation covered working hours, whether the job involved each of a specified list of physical tasks, and psychosocial aspects of employment such as time pressures and targets, control over work organisation, support, satisfaction and job security. The questions about pain and disability focused on six anatomical regions (low back, neck, shoulder, elbow, wrist/hand and knee) delineated in diagrams, and were similar in wording to questions that had been used successfully in earlier studies, both by self-administration [9], [23], [24] and at interview [13]. The questions on fear-avoidance beliefs were adapted from the Fear Avoidance Beliefs Questionnaire [25]. Questions about distress from somatic symptoms were taken from the Brief Symptom Inventory (BSI) [26], and were chosen to provide a measure of the subject’s tendency to somatise. Questions on mental health were taken from the Short Form-36 (SF-36) questionnaire [27].

The follow-up questionnaire (Appendix S3) asked about: any change of job since baseline and the reasons; recent pain in different anatomical regions and associated disability for tasks of daily living; distress from common somatic symptoms; mental health; and sickness absence in the past 12 months for musculoskeletal and other reasons. Where possible, the wording of questions was identical to that used in the baseline questionnaire.

Both the baseline and follow-up questionnaires were compiled first in English. If necessary, they were then translated into local languages, and the accuracy of the translation was checked by independent back-translation to English. Where this revealed errors, appropriate corrections were made. In addition, in some countries, translated questionnaires were piloted in samples of workers who were not included in the main study, and where this revealed difficulties in understanding, further amendments were made.

Local investigators were at liberty to add to the “core” questions of the international study, and a few (e.g. in Italy, Greece, Iran, Japan, South Africa, Australia and New Zealand) took up this option. However, in doing so, they were asked where possible to place the supplementary questions after the core questions, so as to minimise the chance that they would alter the ways in which participants answered the core questions.

Group-level Socio-economic Information

As well as individual data on study participants, local investigators also provided standardised information about the socio-economic circumstances of the occupational groups which they had recruited. This included the local unemployment rate at the time of the survey, availability of social security support for the unemployed, entitlement to sick pay in the first three months of absence, entitlement to compensation for work-related musculoskeletal disorders, special financial support for ill-health retirement, fees paid for healthcare, and access to an occupational health service.

Results

Response to Baseline Questionnaire

The response to the baseline questionnaire is summarised in Table 2. Participation rates among those invited to take part in the study were greater than 80% in 33 of the 47 occupational groups, ranging from 28% in UK other workers and 39% in Australian nurses to 100% in six occupational groups from Ecuador, Nicaragua, Pakistan and Sri Lanka. However, 2,279 participants were excluded from the international analysis because they fell outside the specified age range (310), had missing data (317), had not worked in their current job for as long as 12 months (783), or (in the case of Australian nurses) were excluded by random sampling (869). After these exclusions, a total of 12,426 workers were available for analysis, with between 92 and 1018 in each occupational group.

[Figure omitted. See PDF.]

Table 2. Response to baseline questionnaire.

https://doi.org/10.1371/journal.pone.0039820.t002

Circumstances of Occupational Groups

Table 3 summarises various economic aspects of employment for the occupational groups studied. The local rate of unemployment ranged from <5% in 16 occupational groups to ≥15% in seven. Members of 28 groups would be eligible for social security provision if they became unemployed, although in the three groups from Costa Rica this would be limited to the first three months without a job. Almost all participants could receive some form of sick pay during the first three months of absence from work, but in 22 groups this would not compensate fully for all loss of earnings over that period. Some form of financial compensation for work-related musculoskeletal disorders was available to 40 occupational groups, but 19 groups were ineligible for any special financial support in the event of ill-health retirement.

[Figure omitted. See PDF.]

Table 3. Economic aspects of employment.

https://doi.org/10.1371/journal.pone.0039820.t003

Table 4 describes the access of participants to different sources of healthcare. Most participants had free access to doctors in primary care and hospitals, but fees were more often required for consultation of other health practitioners. All but nine occupational groups were covered by an occupational health service.

[Figure omitted. See PDF.]

Table 4. Access to healthcare for musculoskeletal disorders.

https://doi.org/10.1371/journal.pone.0039820.t004

Characteristics of Participants

Table 5 gives information about the demographic characteristics of participants and their hours of work. In all countries, nurses were predominantly female, and in 18 occupational groups more than 90% of subjects were from one sex. Most groups had a broad distribution of ages, but in a few groups, younger (<30 years) or older (≥50 years) workers were less well represented. Levels of education were generally high in nurses and office workers, but lower in many groups of “other workers”. Most subjects had been in their current job for longer than five years, and most worked between 30 and 49 hours per week. However, in Pakistan, Sri Lanka and Japan, the prevalence of longer working hours (>50 hours per week) was high relative to other countries.

[Figure omitted. See PDF.]

Table 5. Characteristics of study sample – prevalence (%) by occupational group.

https://doi.org/10.1371/journal.pone.0039820.t005

Table 6 shows the prevalence of different physical tasks by occupational group. As would be expected, a high proportion of office workers (>80% in all but one group) reported using a computer keyboard for longer than four hours per day, while manual lifting of weights ≥25 kg in an average working day was most common in nurses. Patterns of physical activity among the “other workers” were more variable, but several such groups reported a relatively high prevalence of work with the hands above shoulder height.

[Figure omitted. See PDF.]

Table 6. Physical activities in an average working day – prevalence (%) by occupational group.

https://doi.org/10.1371/journal.pone.0039820.t006

Table 7 summarises reported psychosocial aspects of work. Time pressure was common in most occupational groups, but the prevalence of financial incentives to productivity was much more variable. Personal autonomy at work was lowest among “other workers”. Most subjects were satisfied with their jobs, but job dissatisfaction was notably high in Italy, Japan and South Africa. The prevalence of perceived job insecurity ranged from 1.6% in Sri Lankan postal workers to 90.3% in Brazilian sugar cane cutters.

[Figure omitted. See PDF.]

Table 7. Psychosocial aspects of work – prevalence (%) by occupational group.

https://doi.org/10.1371/journal.pone.0039820.t007

Table 8 shows the proportions of participants who were aware of a term such as “repetitive strain injury” (“RSI”), “work-related upper limb disorder” (“WRULD”) or “cumulative trauma syndrome” (“CTS”), and also the proportions who knew someone else outside work, who had experienced musculoskeletal pain in the past 12 months. Awareness of RSI and similar terms varied widely – from 0.0% in Brazilian sugar cane cutters and 7.0% in South African office workers to 94.6% in Brazilian nurses and 95.9% in New Zealand office workers. There were also marked differences in knowledge of others with musculoskeletal complaints. For example, among food production workers in Lebanon, only 16.1% knew someone outside work with upper limb pain, whereas in telephone call centre workers in Costa Rica, the proportion was 65.9%.

[Figure omitted. See PDF.]

Table 8. Awareness of repetitive strain injury (RSI) work related upper limb disorder (WRULD) or cumulative trauma syndrome (CTS) – prevalence (%) by occupational group.

https://doi.org/10.1371/journal.pone.0039820.t008

Table 9 presents the prevalence of potentially adverse health beliefs about back and arm pain by occupational group. These again varied substantially (more than tenfold) between occupational groups. For example, 78.6% of Greek postal workers and 77.7% of Lebanese nurses believed that low back pain is commonly caused by people’s work, as compared with only 4.0% of Sri Lankan postal workers and no Brazilian sugar cane cutters; and 31.4% of Brazilian nurses and 31.0% of Brazilian office workers had pessimistic views about the prognosis of arm pain, as compared with 1.6% of nurses and office workers in Iran and 0.0% of Brazilian sugar cane cutters.

[Figure omitted. See PDF.]

Table 9. Adverse health beliefs regarding low back and arm pain – prevalence (%) by occupational group.

https://doi.org/10.1371/journal.pone.0039820.t009

Table 10 compares the characteristics of participants in the UK who answered the questionnaire at interview and by self-administration. Among the nurses and especially the “other workers”, participation rates were higher among those invited to interview, whereas in the office workers they were slightly lower. However, there were no consistent differences in the prevalence of reported occupational activities and musculoskeletal pain according to the method of data collection.

[Figure omitted. See PDF.]

Table 10. Comparison of UK participants who provided information by interview and by self-administered questionnaire.

https://doi.org/10.1371/journal.pone.0039820.t010

Discussion

The CUPID study has generated substantial information which will be the subject of multiple reports. A particular strength is its use of standardised questions to collect information from participants in many different countries and cultural settings. This should provide valuable insights into the determinants of common musculoskeletal illness and associated disability, and particularly the extent of differences between countries.

The occupational groups were chosen for study with the aim that the prevalence of relevant physical tasks should differ between the three broad categories (nurses, office workers and “other workers”), but that within each of these categories, it should be broadly similar across countries. For nurses and office workers this objective was fairly well achieved, although inevitably there was some heterogeneity. For example, in some countries, nurses routinely lift and move patients, whereas in others such tasks may normally be undertaken by care assistants or patients’ family members. For “other workers”, there was more variation in occupational activities, reflecting the greater diversity of groups selected for study. Nevertheless, the mix of activities tended to differ from that of nurses and office workers, with a relatively high prevalence of work with the arms elevated; and apart from sales personnel in Japan, all groups of “other workers” had a high prevalence of work involving prolonged repetitive movement of the wrists or hands.

The international analysis of data is restricted to subjects aged 20–59 years at baseline, who had held their current job for at least 12 months. These restrictions were set when the CUPID study was first planned, the latter because some outcomes of interest from the baseline survey, such as sickness absence in the past 12 months, would otherwise be difficult to interpret.

The questions used in the baseline and follow-up surveys were for the most part well-established, having been used successfully in previous studies. In particular, the items on mental health and somatising tendency were taken from validated instruments, and have previously demonstrated predictive validity for the incidence and persistence of musculoskeletal symptoms [7]. Similarly, the questions on fear avoidance beliefs were based on a validated questionnaire [25], and have shown predictive validity in a longitudinal study [7]. The questions on occupational physical activities have been successfully used in earlier studies [7], [13], [23], [24], and the consistency of answers with expectation (e.g. the high prevalence of prolonged keyboard use in office workers) supports their validity. There is no reliable standard against which to assess the accuracy with which subjective symptoms such as pain are reported, but the questions about pain and disability had again been used successfully in earlier studies. Moreover, the style of our questions about symptoms was similar to that of the Nordic questionnaire, which has been shown to have acceptable reliability [28].

Ensuring the accuracy with which the questionnaire was translated into local languages was a challenge. Care was taken to check the accuracy of translation by independent back-translation to English, and this revealed a number of problems. One was the distinction between “stairs” and “flights of stairs”, and despite attempts to resolve this problem, it is not certain that the term “30 flights of stairs” was always interpreted correctly. Therefore, this question will be ignored in future analyses based on the full dataset. Another difficulty arose with questions of the form “Do you expect that your back pain will be a problem in 12 months time”. In some languages this became “Do you expect your back pain will be a problem over the next 12 months”. Attempts were made to correct this misunderstanding, but it is possible that they were not fully successful.

In addition, terms such as “pain” may be understood differently in different languages even though translated as closely as possible. For this reason, when comparing countries, differences in the relative frequency of pain at different anatomical sites may be particularly revealing – there should have been little ambiguity in the understanding of anatomical sites since they were depicted clearly in diagrams. Interpretation should also be assisted by the questions that were asked about associated difficulty with tasks of daily living, since these were probably understood more uniformly.

Another difficulty that had not been expected was in the use of dates. It emerged that some participants in Iran and Japan used different numbering for calendar years, and where this occurred, corrections had to be made.

Some local investigators opted to include extra questions in addition to the core questions prescribed by CUPID. However, these additions were relatively minor and generally followed after the core questions. Thus, it seems unlikely that they will have influenced answers to the core questions importantly.

Ideally, all questionnaires would have been completed in the same way (interview or self-administration) by all participants. However, this proved impractical. Some occupational groups (especially manual workers in developing countries) would have had great difficulty in answering a written questionnaire, while some employers were unwilling to release their staff for interviews. Moreover, in New Zealand, where nurses and office workers were recruited from across the country, interviews would have been prohibitively expensive.

To explore whether the two methods of answering the questionnaire might lead to systematic differences in answers, we therefore elected to interview a random subset of UK participants while collecting data from the remainder by self-administration. Comparison of responses using the two approaches (Table 10) suggests that no major bias will have occurred as a consequence using both interviews and self-administration. However, if appropriate, method of data collection can be taken into account in statistical analyses.

Participation rates among subjects eligible for study were mostly high, but were less than 50% in five occupational groups (Table 2). We have no reason to expect that those who elected to take part were importantly unrepresentative in the prevalence of pain and its associations with risk factors. However, in future work it may be appropriate to carry out sensitivity analyses, excluding the occupational groups with the lowest response rates. The incomplete response to the baseline questionnaire will be less of a concern in longitudinal analyses based on the follow-up questionnaire.

The numbers of participants by occupational group that were suitable for analysis ranged from 92 to 1018 with a mean of 264. At the outset, our aim was to recruit at least 200 subjects in each group, and this was for the most part achieved (only 7 groups provided fewer than 150 subjects). Furthermore, the occupational groups studied varied substantially in their employment conditions (Table 3), access to healthcare (Table 4), and prevalence of psychosocial risk factors (Tables 7, 8, and 9). When exploring possible reasons for differences in the prevalence of pain and disability between occupational groups, it will be important to investigate these group-level characteristics as well as individual-level risk factors such as mental health and somatising tendency. The heterogeneity in their distribution should enhance statistical power to address their impact.

As might be expected, the demographic constitution of occupational groups also varied. In particular, many of the samples of nurses were largely or completely female, whereas some groups of “other workers” were all men. This reflects the nature of the occupations of interest. However, it should not be a major problem in interpretation of comparisons since there were an adequate number of occupational groups with a fairly even distribution of sex and age. Moreover, the occurrence of common musculoskeletal complaints appears not to vary greatly between men and women or between older and younger adults of working age [13], [23], [24].

In summary, the CUPID study is a major resource for the investigation of cultural and psychological determinants of common musculoskeletal disorders and associated disability. Although the data collected have inevitable limitations, the large differences in psychosocial risk factors (including knowledge and beliefs about MSDs) between occupational groups carrying out similar physical tasks in different countries should allow the study hypothesis to be addressed effectively. It will also allow exploration of differences in patterns of musculoskeletal complaint between the three categories of occupation examined, and the consistency of these differences across countries.

Supporting Information

[Figure omitted. See PDF.]

Appendix S1.

Committees which provided ethical approval for the cupid study.

https://doi.org/10.1371/journal.pone.0039820.s001

(DOCX)

Appendix S2.

Baseline questionnaire.

https://doi.org/10.1371/journal.pone.0039820.s002

(DOCX)

Appendix S3.

Follow-up questionnaire.

https://doi.org/10.1371/journal.pone.0039820.s003

(DOCX)

Acknowledgments

We thank: Pietro Muñoz, Patricio Oyos, Gonzalo Albuja, María Belduma and Francisco Lara for their assistance with data collection in Ecuador; Patrica Monge, Melania Chaverrri and Freddy Brenes, who helped with data collection in Costa Rica; Aurora Aragón, Alberto Berríos, Samaria Balladares and Martha Martínez who helped with data collection in Nicaragua; Alfredo José Jirón who assisted with data entry in Nicaragua; Catalina Torres for translation and piloting of the questionnaire in Spain; Ben and Marie Carmen Coggon for back translation of the Spanish questionnaire; Cynthia Alcantara, Xavier Orpella, Josep Anton Gonzalez, Joan Bas, Pilar Peña, Elena Brunat, Vicente San José, Anna Sala March, Anna Marquez, Josefina Lorente, Cristina Oliva, Montse Vergara and Eduard Gaynés for their assistance with data collection in Spain; Natale Battevi, Lorenzo Bordini, Marco Conti and Luciano Riboldi who carried out data collection in Italy; Paul Maurice Conway for back translation of the Italian questionnaire; Tiina Freimann, who helped with data collection in Estonia; Asad Ali Khan for supervision of data collection and checking in Pakistan; Khalil Qureshi for training of field workers and supervision of data collection and checking in Pakistan; Masami Hirai, Tatsuya Isomura, Norimasa Kikuchi, Akiko Ishizuka and Takayuki Sawada for their help with data collection and management in Japan; and Peter Herbison for assistance with data collection in New Zealand.

We are particularly grateful to all of the organisations that allowed us to approach their employees; and all of the workers who kindly participated in the study.

Author Contributions

Conceived and designed the experiments: DC KTP. Performed the experiments: DC GN KTP KC VEF MHM LMS RH FH RF NH LHB MVM LAQ MR SAF DG EJSV ECH AC SVP CS JMM GD FGB MB MC MMF ACP ES LC PB MK EM KO TS RRH FS AS MMK SSPW RJPJ NS ARW KM NY BN DK MRS HLK VCWH DMU HH SD DM AG. Analyzed the data: GN DC. Wrote the paper: DC. Principal investigator Brazil: VEF. Principal investigator Ecuador: RH. Principal investigator Colombia: LHB. Principal Investigators Costa Rica and Nicaragua: SAF DG. Principal investigator UK: DC. Principal investigator Spain: SV-P. Principal investigator Italy: MB. Principal investigator Greece: ES. Principal investigator Estonia: EM. Principal investigator Lebanon: RRH. Principal investigator Iran: FS. Principal investigator Pakistan: MMK. Principal investigator Sri Lanka: SSPW. Principal investigator Japan: KM. Principal investigator South Africa: BN. Principal investigator Australia: MRS. Principal investigator New Zealand: HH. All authors reviewed the draft manuscript and contributed to its finalization.

Citation: Coggon D, Ntani G, Palmer KT, Felli VE, Harari R, Barrero LH, et al. (2012) The CUPID (Cultural and Psychosocial Influences on Disability) Study: Methods of Data Collection and Characteristics of Study Sample. PLoS ONE 7(7): e39820. https://doi.org/10.1371/journal.pone.0039820

References

1. Lötters F, Burdorf A, Kuiper J, Miedema H (2003) Model for the work-relatedness of low-back pain. Scand J Work Environ Health 29: 431–40.F. LöttersA. BurdorfJ. KuiperH. Miedema2003Model for the work-relatedness of low-back pain.Scand J Work Environ Health2943140

2. Palmer KT, Smedley J (2007) Work relatedness of chronic neck pain with physical findings – a systematic review. Scand J Work Environ Health 33: 165–91.KT PalmerJ. Smedley2007Work relatedness of chronic neck pain with physical findings – a systematic review.Scand J Work Environ Health3316591

3. Palmer KT (2011) Carpal tunnel syndrome: the role of occupational factors. Best Pract Res Clin Rheumatol 25: 15–29.KT Palmer2011Carpal tunnel syndrome: the role of occupational factors.Best Pract Res Clin Rheumatol251529

4. Palmer KT, Harris EC, Coggon D (2007) Compensating occupationally related tenosynovitis and epicondylitis: a literature review. Occup Med 57: 67–74.KT PalmerEC HarrisD. Coggon2007Compensating occupationally related tenosynovitis and epicondylitis: a literature review.Occup Med576774

5. Linton SJ (2000) A review of psychological risk factors in back and neck pain. Spine 25: 1148–56.SJ Linton2000A review of psychological risk factors in back and neck pain.Spine25114856

6. Macfarlane GJ, Hunt IM, Silman AJ (2000) Role of mechanical and psychosocial factors in the onset of forearm pain: prospective population based study. Br Med J 321: 676–9.GJ MacfarlaneIM HuntAJ Silman2000Role of mechanical and psychosocial factors in the onset of forearm pain: prospective population based study.Br Med J3216769

7. Palmer KT, Reading I, Linaker C, Calnan M, Coggon D (2008) Population-based cohort study of incident and persistent arm pain: role of mental health, self-rated health and health beliefs. Pain 136: 30–37.KT PalmerI. ReadingC. LinakerM. CalnanD. Coggon2008Population-based cohort study of incident and persistent arm pain: role of mental health, self-rated health and health beliefs.Pain1363037

8. Macfarlane GJ, Pallewatte N, Paudyal P, Biyth FM, Coggon D, et al. (2009) Evaluation of work-related psychosocial factors and regional musculoskeletal pain: result from a EULAR Task Force. Ann Rheum Dis 68: 885–91.GJ MacfarlaneN. PallewatteP. PaudyalFM BiythD. Coggon2009Evaluation of work-related psychosocial factors and regional musculoskeletal pain: result from a EULAR Task Force.Ann Rheum Dis6888591

9. Palmer K, Calnan M, Wainwright D, Poole J, O’Neill C, et al. (2005) Disabling musculoskeletal pain and its relation to somatization: A community-based postal survey. Occup Med 55: 612–617.K. PalmerM. CalnanD. WainwrightJ. PooleC. O’Neill2005Disabling musculoskeletal pain and its relation to somatization: A community-based postal survey.Occup Med55612617

10. Clinical Standards Advisory Group (1994) Epidemiology review: the epidemiology and cost of back pain. London: HMSO. Clinical Standards Advisory Group1994Epidemiology review: the epidemiology and cost of back pain.London: HMSO

11. Gun RT (1990) The incidence and distribution of RSI in South Australia 1980–81 and 1986–87. Med J Aust 153: 376–80.RT Gun1990The incidence and distribution of RSI in South Australia 1980–81 and 1986–87.Med J Aust15337680

12. Coggon D (2005) Occupational Medicine at a turning point. Occup Environ Med 62: 281–3.D. Coggon2005Occupational Medicine at a turning point.Occup Environ Med622813

13. Madan I, Reading I, Palmer KT, Coggon D (2008) Cultural differences in musculoskeletal symptoms and disability. Int J Epid 37: 1181–1189.I. MadanI. ReadingKT PalmerD. Coggon2008Cultural differences in musculoskeletal symptoms and disability.Int J Epid3711811189

14. Ramond A, Bouton C, Richard I, Roquelaire Y, Baufreton C, et al. (2011) Psychosocial risk factors for chronic low back pain in primary care – a systematic review. Fam Prac 28: 12–21.A. RamondC. BoutonI. RichardY. RoquelaireC. Baufreton2011Psychosocial risk factors for chronic low back pain in primary care – a systematic review.Fam Prac281221

15. Buchbinder R, Jolley D, Wyatt M (2001) Population based intervention to change back pain beliefs and disability: three part evaluation. Br Med J 322: 1516–1520.R. BuchbinderD. JolleyM. Wyatt2001Population based intervention to change back pain beliefs and disability: three part evaluation.Br Med J32215161520

16. Ferrari AL, Baptista PCP, Felli VEA, Coggon D (2010) Translation, adaptation and validation of the “Cultural and Psychosocial Influences on Disability (CUPID) Questionnaire” for use in Brazil. Rev Latino-Am Enfermagem 18: 1092–8.AL FerrariPCP BaptistaVEA FelliD. Coggon2010Translation, adaptation and validation of the “Cultural and Psychosocial Influences on Disability (CUPID) Questionnaire” for use in Brazil.Rev Latino-Am Enfermagem1810928

17. Harcombe H, McBride D, Derrett S, Gray A (2009) Prevalence and impact of musculoskeletal disorders in New Zealand nurses, postal workers and office workers. Aust N Z J Public Health 33: 437–41.H. HarcombeD. McBrideS. DerrettA. Gray2009Prevalence and impact of musculoskeletal disorders in New Zealand nurses, postal workers and office workers.Aust N Z J Public Health3343741

18. Harcombe H, McBride D, Derrett S, Gray A (2010) Physical and psychosocial risk factors for musculoskeletal disorders in New Zealand nurses, postal workers and office workers. Injury Prevention 16: 96–100.H. HarcombeD. McBrideS. DerrettA. Gray2010Physical and psychosocial risk factors for musculoskeletal disorders in New Zealand nurses, postal workers and office workers.Injury Prevention1696100

19. Hoe VCW, Kelsall HL, Urquhart DM, Sim MR (2011) Risk factors for musculoskeletal symptoms of the neck or shoulder alone or neck and shoulder among hospital nurses. Occup Environ Med 69: 198–204.VCW HoeHL KelsallDM UrquhartMR Sim2011Risk factors for musculoskeletal symptoms of the neck or shoulder alone or neck and shoulder among hospital nurses.Occup Environ Med69198204

20. Matsudaira K, Palmer KT, Reading I, Hirai M, Yoshimura N, et al. (2011) Prevalence and correlates of regional pain and associated disability in Japanese workers. Occup Environ Med. 68: 191–196.K. MatsudairaKT PalmerI. ReadingM. HiraiN. Yoshimura2011Prevalence and correlates of regional pain and associated disability in Japanese workers. Occup Environ Med.68191196

21. Solidaki E, Chatzi L, Bitsios P, Markatzi I, Plana E, et al. (2010) Work related and psychological determinants of multi-site musculoskeletal pain. Scand J Work Environ Health 2010 36: 54–61.E. SolidakiL. ChatziP. BitsiosI. MarkatziE. Plana2010Work related and psychological determinants of multi-site musculoskeletal pain.Scand J Work Environ Health 2010365461

22. Warnakulusariya S, Peiris-John R, Ntani G, Coggon D, Sathiakumar N, et al. (In press) Musculoskeletal pain in four occupational populations in Sri Lanka. Occupational Medicine. Warnakulusariya S, Peiris-John R, Ntani G, Coggon D, Sathiakumar N, et al. (In press) Musculoskeletal pain in four occupational populations in Sri Lanka.Occupational Medicine

23. Palmer KT, Walsh K, Bendall H, Cooper C, Coggon D (2000) Back pain in Britain: Comparison of two prevalence surveys at an interval of ten years. Br Med J 320;1577–8. KT PalmerK. WalshH. BendallC. CooperD. Coggon2000Back pain in Britain: Comparison of two prevalence surveys at an interval of ten years.Br Med J 320;1577–8

24. Palmer KT, Walker-Bone K, Griffin MJ, Syddall H, Pannett B (2001) The prevalence and occupational associations of neck pain in the British population. Scand J Work Environ Health 27: 49–56.KT PalmerK. Walker-BoneMJ GriffinH. SyddallB. Pannett2001The prevalence and occupational associations of neck pain in the British population.Scand J Work Environ Health274956

25. Waddell G, Newton M, Henderson I, Somerville D, Main CJ (1993) A Fear-Avoidance Beliefs Questionnaire (FABQ) and the role of fear-avoidance beliefs in chronic low back pain and disability. Pain 52: 157–68.G. WaddellM. NewtonI. HendersonD. SomervilleCJ Main1993A Fear-Avoidance Beliefs Questionnaire (FABQ) and the role of fear-avoidance beliefs in chronic low back pain and disability.Pain5215768

26. Derogatis LR, Melisoratos N (1983) The Brief Symptom Inventory: an introductory report. Psychol Med 13: 595–605.LR DerogatisN. Melisoratos1983The Brief Symptom Inventory: an introductory report.Psychol Med13595605

27. Ware JE, Sherbourne CD (1992) The MOS 36-item short-form health survey (SF-36). Med Care 30: 473–83.JE WareCD Sherbourne1992The MOS 36-item short-form health survey (SF-36).Med Care3047383

28. Kuorinka I, Jonsson B, Kilbom A, Vinterberg H, Biering-Sørensen F, et al. (1987) Standardised Nordic questionnaires for the analysis of musculoskeletal symptoms. Appl Ergon 18: 233–7.I. KuorinkaB. JonssonA. KilbomH. VinterbergF. Biering-Sørensen1987Standardised Nordic questionnaires for the analysis of musculoskeletal symptoms.Appl Ergon182337