Skip to content

Advertisement

  • Research article
  • Open Access
  • Open Peer Review

Factors associated with chronic and acute back pain in Wales, a cross-sectional study

  • 1,
  • 2,
  • 1 and
  • 3Email author
BMC Musculoskeletal Disorders201920:215

https://doi.org/10.1186/s12891-019-2477-4

  • Received: 16 July 2018
  • Accepted: 25 February 2019
  • Published:
Open Peer Review reports

Abstract

Background

Back pain is one of the most common causes for disability in the working population. Some risk factors for back pain are well known, however little is known about factors uniquely associated with acute or chronic back pain.

This study aimed to elucidate patterns uniquely associated with acute or chronic back pain.

Methods

This study performed secondary analysis of data from the Welsh Health Survey 2012, a nationwide cross-sectional survey.

A multivariable analysis was carried out for risk factors found to be significantly associated with acute and chronic back pain.

Results

We found that increased BMI (aOR 1.20, 95% Cis 1.08, 1.33; BMI > 30), mental health score below average (aOR 1.59, 95% CIs 1.47, 1.72), having a degree (aOR 1.28, 95% CIs 1.12, 1.47) and being older than 24 years (P < 0.001) were associated with increased prevalence of acute back pain.

Higher prevalence of chronic back pain was seen in individuals characterised by increased deprivation (WIMD) (aOR 1.61, 95% CIs 1.32, 1.96); increased age (aOR 7.34, 95% CIs 5.25, 10.26; for 65+); being female (aOR = 1.43, 95% CIs 1.27, 1.61); lower educational attainment (aOR 0.44, 95% CIs 0.36, 0.55) higher BMI (aOR = 1.60 95% CIs 1.38, 1.85; BMI > 30); poorer mental health score (aOR = 3.11 95% CIs 2.76, 3.51), and a sedentary lifestyle (aOR = 0.58, 95% CIs 0.49, 0.69; 3–5 days of light exercise).

Conclusion

Increased deprivation, female gender, and little exercise were uniquely associated with chronic back pain. These characteristics may help clinicians to intervene to prevent acute backpain resulting in chronic cases.

Keywords

  • Chronic Back pain
  • Acute back pain
  • Risk factors
  • Physical activity
  • Prevention

Background

Back pain is a common and potentially disabling condition that can lead to reductions in quality of life, time off work and long-term disability. The Global Burden of Disease Study estimated the point prevalence of low back pain to be 9.4%, and reported low back pain to be the condition responsible for the most years lived with disability [1]. Back pain is one of the most common causes for disability in the working population, and severely impacts upon work productivity and absenteeism [1]. In the UK alone, almost 3.4 million working days were lost due to work-related back pain in 2016/17, that is 13.3% of all working days lost due to ill health [2]. Low back pain is the reason for one in every seven general practice consultations [3]. The associated health care cost and burden has been reported across health care systems worldwide [4, 5]. Hong et al. [6] found that the healthcare costs of patients suffering chronic low back pain (CLBP) were double those of matched controls without CLBP.

Chronic and acute back pain

Back pain is defined as acute when it has persisted for up to 6 weeks and sub-acute when it has persisted for up to 3 months [7]. Chronic back pain is defined as back pain that is present for more than 3 months [8] and is associated with patients receiving treatment [9, 10]. Acute back pain is often the result of actual or near tissue injury or sprain [7] and individuals with acute back pain are less likely to seek care or be referred for treatment [9, 10]. Chronic pain often persists even though the initial injury has healed [7]. These cases are more likely to be referred for treatment than the more acute cases that are commonly left untreated [9, 10].

Risk factors

There is good evidence for an association between increasing age and obesity (BMI > 30) and risk of back pain [4, 1121] and that obesity is a strong predictor of disability caused by back pain [20, 22, 23]. It is also known that the prevalence and severity of back pain is higher where there is greater deprivation [4, 12, 1416, 1921, 2428]. There is conflicting evidence on the effect of physical activity (PA) on back pain. Heneweer et al. [13] suggested a U-shaped dose-response relationship between PA and back pain. Other studies have found that physical inactivity is associated with a significant increase in risk of back pain [17, 22]. There is some evidence suggesting that females have a greater risk of back pain, [4, 1121, 24] however a recent global study reported this varied by region [1].

There is limited evidence that job demands including lifting and twisting [13, 20, 26, 29]; ethnicity [18, 24]; genetic factors [14]; and mental health comorbidities [4, 14, 22, 26] are all associated with higher risk of back pain. The varying level of evidence, available literature and the lack of a standardised definition of back pain make definitive conclusions challenging [30, 31].

Methods

Aim and objectives

This study aimed to elucidate patterns uniquely associated with acute or chronic back pain. Differentiating between the two is challenging in clinical practice. Identifying risk factors associated with the pattern may help clinicians differentiate between the two conditions, manage them more appropriately and ultimately help to improve patient outcomes. In addition this could enable targeting of those at greatest risk for prevention through e.g. workplace modification strategies.

Study design

We used a population based cross-sectional survey (The Welsh Health Survey 2012). The survey collected information on health status, illnesses, lifestyle and health service use in the general population. The sampling frame includes 99% of all private households in Wales. A sample of 14,775 households were drawn, stratified by geographical area. To achieve the aim of at least 600 interviews per geographical area, a minimum of 575 households were sampled in each geographical area. Household data were collected by enumerator from each adult aged 16 years or older. Further details about collection of data can be found on the Welsh Health Survey 2013 (WHS) [32].

Outcomes

Primary outcomes in this study were:
  1. a)

    Acute back pain (episodes of untreated backache in the last 12 months) [9, 10]

     
  2. b)

    Chronic back pain (Back pain currently being treated) [9, 10]

     

For the purpose of this study back pain currently being treated was considered a measure of chronic back pain, and untreated backache in the last 12 months considered a measure of acute back pain.

Covariates

The following mechanistically plausible covariates were investigated for associations with back pain (acute, and chronic):
  • Demographic: Age (age bands 16–24, 25–44, 45–64, 65+); Gender.

  • Socioeconomic: Educational attainment (No qualification, other qualification, degree equivalent or above); Occupational status (Managerial and professional, intermediate, routine and manual, never worked/long term unemployed); Welsh index of multiple deprivation 2014 (WIMD) (Deprivation quintiles).

  • Clinical: Mental health measured by the SF-36 (< 50 vs. > 50); BMI (less than 18.5, 18.5–25, 25–30, 30 and over); Depression (treated vs. untreated); Anxiety (treated vs. untreated); Physical activity (PA) (meeting the UK PA guidelines vs. not meeting them and number of days of light, moderate or vigorous exercise per week).

Data analysis

An a priori statistical analysis plan was followed (available on request). Descriptive statistics tabulated demographic and risk factors, for acute and chronic back pain, and counts were presented. Crude logistic regression models were fitted to each risk factor and odds ratios (ORs) were presented with 95% confidence intervals (95% CI) and P-values. A multivariable logistic regression model with a forward stepping approach where a likelihood ratio test (LRT) of sequential nested models, was used to determine parsimonious independent associations with the covariates (p < 0.01). The final analyses were inclusive of all risk factors from either of the analyses. The analysis was adjusted for the clustered nature of the respondents within geographical areas within the UK, by estimating inflated standard errors using the robust cluster estimators of the variances. Stata 13 was used for all analyses.

Results

There were 19,282 eligible adults who were invited in the WHS 2013, and 15,007 were included in the analysis. The response rate was higher among women (83.1%) than men (79.4%), as well as among older individuals than younger individuals (70.3% for 16–24 years, 75.6% for 25–44 years, 85.1% for 45–64 years, 88.9% for 65 years and older). There was less than 5% missing data for any included variable.

The prevalence of acute back pain was 31.5% and the prevalence of chronic back pain was 13.4% (Table 1). The prevalence of reported acute and chronic back pain combined was 39.1%.
Table 1

Numbers and proportions of acute and chronic back pain across all covariates

 

Acute back pain

Chronic back pain

All back pain

Total

Pain (%)

Total

Pain (%)

Total

Pain (%)

Total

14,359

4519 (31.5%)

14,351

1772 (13.4%)

14,100

5520 (39.1%)

Deprivation (WIMD quintile)

14,359

 

14,351

 

14,100

 

 Least deprived

2839

892 (31.42)

2859

248 (8.67)

1029

1029, (36.65)

 2

3065

994 (32.43)

3053

347 (11.37)

1207

1207, (40.07)

 3

3275

1053 (32.15)

3309

409 (12.36)

1275

1275, (47.05)

 4

2762

866 (31.35)

2745

381 (13.88)

1072

1072, (45.79)

 Most deprived

2418

714 (29.53)

2385

387 (16,23)

2529

2529, (108.03)

Age (years)

14,359

 

14,351

   

 16–24

1718

387 (22.53)

1752

46 (2.63)

410

410, (24.05)

 25–44

3830

1264 (33.84)

3879

275 (7.09)

1421

1421, (37.25)

 45–64

4963

1731 (34.88)

4974

709 (14.25)

2144

2144, (43.76)

 65+

3848

1137 (29.55)

3746

742 (19.81)

1545

1545, (41.97)

Gender

14,359

 

14,351

   

 Female

7699

2480 (32.21)

7667

1084 (14.14)

3098

3098, (41.05)

 Male

6660

2039 (30.62)

6684

688 (10.29)

2422

2422, (36.96)

Educational attainment

13,398

 

13,424

   

 No qualification

2643

752 (28.45)

2573

573 (22.27)

1077

1077, (42.27)

 Other qualification

8367

2731 (32.64)

8443

883 (10.46)

3231

3231, (39.01)

 Degree Equivalent and above

2388

774 (32.41)

2408

136 (5.65)

856

856, (36.03)

Occupational status (NS-SEC)

13,959

 

13,936

   

 Managerial and Professional occupations

5170

1605 (31.04)

5228

461 (8.82)

1868

1868, (36.52)

 Intermediate occupations

2853

964 (33.79)

2834

330 (11.64)

1143

1143, (40.88)

 Routine and manual occupations

5569

1718 (30.85)

5524

883 (15.98)

2217

2217, (40.74)

 Never worked and long-term unemployed

357

104 (29.13)

350

65 (18.57)

143

143, (41.81)

BMIa

13,387

 

13,391

   

 Less than 18.5

281

59 (21.00)

284

21 (7.39)

71

71, (26.01)

 18.5 to under 25

5176

1498 (28.94)

5213

490 (9.40)

1778

1778, (34.88)

 25 to under 30

4878

1604 (32.88)

4873

594 (12.19)

1943

1943, (40.45)

 30 and over

3052

1073 (35.16)

3021

550 (18.21)

1386

1386, (46.31)

Mental Health (SF-36 mental health score)

14,359

 

14,351

   

 Higher than average (> 50)b

8803

2421 (27.50)

8862

632 (7.13)

2783

2783, (32.15)

 Lower than average (< 50)c

5556

2098 (37.76)

5489

1140 (20.77)

2737

2737, (50.28)

Depression

13,840

 

14,165

   

 Yes

1257

488 (38.82)

1183

403 (34.07)

717

717, (59.7)

 No

12,583

3832 (30.45)

12,982

1204 (9.27)

4519

4519, (35.85)

Anxiety

13,776

 

14,124

   

 Yes

1025

392 (38.24)

959

315 (32.85)

568

568, (58.32)

 No

12,751

3904 (30.62)

13,156

1252 (9.52)

4624

4624, (36.16)

Exercise

14,136

 

14,139

   

 Meeting PA guidelinesd

4106

1291 (31.44)

4156

269 (6.47)

1432

1432, (35.33)

 Not meeting guidelines

10,030

3164 (31.55)

9983

1451 (14.53)

4001

4001, (40.64)

aBody mass index

bMental health score above the average of the general population

cMental health score below the average of the general population

dMeeting physical activity guidelines of 30 min of light to moderate exercise on at least 5 days of the week

Acute back pain

The crude analysis found that increased BMI (aOR 1.20, 95% CIs 1.08, 1.33; BMI > 30), mental health score below average (aOR 1.59, 95%CIs 1.47, 1.72; mental health score below avg), having a degree (aOR 1.28, 95% CIs 1.12, 1.47; Degree or higher) and being older than 24 years (P < 0.001) were associated with increased prevalence of acute back pain. In a multivariable analysis we found consistent results with the crude analysis (Table 2).
Table 2

Univariable logistic regression of acute back pain and multivariable logistic regression of acute back pain, adjusted for significantly associated covariates

 

Univariable analysis

Multivariable analysis

N

Crude OR (95% CI)

P value

Adjusted OR (95% CI)

P value

WIMD 2014 quintile

14,359

    

 Least deprived

 

Reference category

 2

 

1.05 (0.94, 1.17)

0.405

1.03 (0.92, 1.16)

0.611

 3

 

1.03 (0.93, 1.15)

0.539

1.00 (0.89, 1.13)

0.940

 4

 

1.00 (0.89, 1.12)

0.958

0.93 (0.82, 1.05)

0.261

 Most deprived

 

0.91 (0.81, 1.03)

0.138

0.86 (0.76, 0.98)

0.029

Age

14,359

    

 16–24

 

Reference category

 25–44

 

1.69 (1.49, 1.93)

< 0.001

1.64 (1.42, 1.90)

< 0.001

 45–64

 

1.84 (1.62, 2.09)

< 0.001

1.73 (1.50, 1.99)

< 0.001

 65+

 

1.44 (1.26, 1.65)

< 0.001

1.49 (1.27, 1.73)

< 0.001

Gender

14,359

    

 Male

 

Reference category

 Female

 

1.08 (1.00, 1.16)

0.040

1.01 (0.94, 1.10)

0.761

Educational attainment

13,398

    

 No qualification

 

Reference category

 Degree equivalent or higher

 

1.21 (1.07, 1.36)

0.002

1.28 (1.12, 1.47)

< 0.001

 Other qualifications

 

1.22 (1.11, 1.34)

< 0.001

1.32 (1.18, 1.47)

< 0.001

BMIa

13,387

    

 Less than 18.5

 

0.65 (0.49, 0.87)

0.004

0.79 (0.58, 1.07)

0.127

 18.5 to under 25

 

Reference category

 25 to under 30

 

1.20 (1.11, 1.31)

< 0.001

1.14 (1.04, 1.25)

0.004

 30 and over

 

1.33 (1.21, 1.46)

< 0.001

1.20 (1.08, 1.33)

0.001

Mental health (SF-36)

14,359

    

 Above averageb

 

Reference category

 Below averagec

 

1.60 (1.49, 1.72)

< 0.001

1.59 (1.47, 1.72)

< 0.001

Vigorous exercise

13,757

    

 0–2 days per week

 

Reference category

 3–5 days

 

0.83 (0.73, 0.94)

0.03

0.91 (0.80, 1.03)

0.156

 6–7 days

 

0.83 (0.68, 1.02)

0.077

0.91 (0.74, 1.13)

0.406

aBody mass index

bMental health score above the average of the general population

cMental health score below the average of the general population

Chronic back pain

In the multivariable analysis higher rates of chronic back pain were seen in individuals who were characterised by increased deprivation (WIMD) (aOR 1.61, 95% CIs 1.32, 1.96; most deprived); increased age (aOR 7.34, 95% CIs 5.25, 10.26; for 65+); being female (aOR = 1.43, 95% CIs 1.27, 1.61); lower educational attainment (aOR 0.44, 95% CIs 0.36, 0.55; degree or higher) higher BMI (aOR = 1.60 95% CIs 1.38, 1.85; BMI > 30); poorer mental health score (aOR = 3.11 95% CIs 2.76, 3.51; below average), and a sedentary lifestyle (aOR = 0.58, 95% CIs 0.49, 0.69; 3–5 days of light exercise) (Table 3).
Table 3

Univariable logistic regression of chronic back pain and multivariable logistic regression of chronic back pain, adjusted for significantly associated covariates

 

Univariable analysis

Multivariable analysis

N

Crude OR (95% CI)

P value

Adjusted OR (95% CI)

P value

WIMD 2014 quintile

14,351

    

 Least deprived

 

 2

 

1.35 (1.14, 1.60)

0.001

1.32 (1.09, 1.60)

0.005

 3

 

1.48 (1.26, 1.75)

< 0.001

1.33 (1.10, 1.61)

0.003

 4

 

1.70 (1.43, 2.01)

< 0.001

1.42 (1.16, 1.72)

< 0.001

 Most deprived

 

2.04 (1.72, 2.42)

< 0.001

1.61 (1.32, 1.96)

< 0.001

Age

14,351

    

 16–24

 

 25–44

 

2.83 (2.06, 3.89)

< 0.001

2.42 (1.71, 3.42)

< 0.001

 45–64

 

6.17 (4.55, 8.35)

< 0.001

5.14 (3.69, 7.15)

< 0.001

 65+

 

9.16 (6.76, 12.41)

< 0.001

7.34 (5.25, 10.26)

< 0.001

Gender

14,351

    

 Male

 

 Female

 

1.44 (1.30, 1.59)

< 0.001

1.43 (1.27, 1.61)

< 0.001

Educational attainment

13,424

    

 No qualification

 

 Degree equivalent or higher

 

0.21 (0.17, 0.25)

< 0.001

0.44 (0.36, 0.55)

< 0.001

 Other qualifications

 

0.41 (0.36, 0.46)

< 0.001

0.75 (0.65, 0.86)

< 0.001

BMIa

13,391

    

 Less than 18.5- Underweight

 

0.77 (0.49, 1.21)

0.258

0.91 (0.55,1.48)

0.699

 18.5 to under 25- Normal weight

 

 25 to under 30- Overweight

 

1.34 (1.18, 1.52)

< 0.001

1.20 (1.04, 1.38)

0.013

 30 and over- Obese

 

2.15 (1.88, 2.45)

< 0.001

1.60 (1.38, 1.85)

< 0.001

Mental health (SF-36)

14,351

    

 Above averageb

 

 Below averagec

 

3.41 (3.08, 3.79)

< 0.001

3.11 (2.76, 3.51)

< 0.001

Light exercise

14,014

    

 0–2 days per week

 

 3–5 days

 

0.43 (0.37, 0.49)

< 0.001

0.58 (0.49, 0.69)

< 0.001

 6–7 days

 

0.39 (0.35, 0.43)

< 0.001

0.55 (0.48, 0.63)

< 0.001

aBody mass index

bMental health score above the average of the general population

cMental health score below the average of the general population

In the crude analysis, all covariates were found predictive of chronic back pain. Increasing age and BMI were found to offer the greatest increase in odds of chronic back pain (Table 3).

Discussion

The study aimed to describe a pattern of acute and chronic back pain and examine possible risk factors in order to elucidate differences between the sub-types of back pain. We found that increasing age, higher BMI, better educational attainment and poorer mental health were independently associated with both acute and chronic back pain. However, we also found that increasing WIMD quintile (i.e., increasing deprivation), female gender, and exercising less than 2 days per week were uniquely associated with chronic back pain.

This is the first population-based study to compare independent associations for acute and chronic back pain. The strength was larger for all of the associations for chronic back pain and the associations showed a diluted effect in acute back pain in most of the covariates.

Comparison with existing literature

Educational attainment had the opposite effect on acute back pain compared to chronic back pain, and higher educational attainment was significantly associated with increased odds of acute back pain. Riskowski [33] reported a similar finding in a cross-sectional survey conducted in the U.S., in which they found that chronic back pain was more common in individuals of lower socioeconomic position and that acute back pain was more common in individuals of higher socioeconomic positions. Riskowski suggests that these unusual findings could be related to changes in socioeconomic positions over time as acute pain becomes chronic [33]. Assuming that untreated backache represents acute cases and treated back pain represents chronic cases similar suggestions might be made for this study, as educational attainment is an important marker for socioeconomic status and deprivation. Definitive explanations of these findings are difficult, although speculative suggestions can be made that cases of acute back pain in those with higher educational attainment are less likely to become chronic because of better knowledge of self-regulation or coping strategies in addition to this group having in general better means. This would result in most back pain cases in those with higher educational attainment being acute and not becoming chronic. We found obesity (BMI > 30) to be independently associated with chronic back pain, this is in line with previous studies [4, 1121]. Fransen et al. (2002) found obesity to be a significant predictor of chronicity in individuals receiving compensation for working days lost due to acute back pain [34].

A recent systematic review found that stratified programmes were effective in preventing the development of chronic back pain. Those classified at low risk of developing chronic back pain benefited from simple educational messages while those classified at medium or high risk benefited from a combination of reactivation programmes, exercise and cognitive-behavioural interventions. We have identified factors independently associated with chronic back pain only. This may help to determine the risk of patients developing chronic back pain, and in turn determine a suitable prevention intervention [35].

Our findings in general are in line with previous studies however it is the first in the UK to distinguish between acute and chronic back pain.

Strengths and limitations

This is the first population-based study of back pain in the UK, and the first to differentiate between acute and chronic back pain. The reported results cannot infer causality due to the nature of the study design. Multivariable analyses controlled for known confounders, however this doesn’t include the unknown confounders, i.e. work demands, chronic stress and genetic factors. There is a limitation in the measures for chronic and acute back pain used in this study. The evidence suggests that treated cases are likely to represent chronic cases and untreated cases are likely to represent acute cases [9, 10]. However, we anticipate that some cases may be misclassified, as acute back pain may sometimes be treated with for example, anti-inflammatories.

There is debate over these definitions and this is unlikely to be universal. Potential biases affecting the study include selection bias and reporting bias. We cannot ignore the possibility of reverse causality. Given the weaknesses, caution is needed when interpreting these findings, however, this study gives a clue about the difference in risk factors between acute and chronic back pain.

Conclusion

Chronic back pain is a considerable public health concern and risk factors for acute and chronic back pain are different. This study has identified factors associated with chronic back pain that are not associated with acute back pain. This information may help clinicians to intervene to prevent acute back pain resulting in chronic cases. More emphasis should be put on service for those in deprived areas. In addition this information can help target groups and individuals for preventive measures.

Longitudinal cohort studies are needed to make conclusions about causality regarding risk factors of back pain and to distinguish successfully between cases that progress form acute to chronic. In addition further analysis of long-term cohort studies are needed to investigate the effect of light exercise on chronic back pain as a suggested means of self-management.

Abbreviations

aOR: 

adjusted Odds Ratio

BMI: 

Body mass index

CLBP: 

Chronic low back pain

LRT: 

Likelihood ratio test

OR: 

Odds Ratio

PA: 

Physical activity

WHS: 

Welsh health survey

WIMD: 

Welsh Index of Multiple Deprivation

Declarations

Acknowledgements

The authors would like to thank the team at the Health statistics and analysis unit, Welsh Government, who provided the data used in this analysis.

Funding

We acknowledge the support of the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London (B. C.). The funding bodies were not party to any part of the research, analysis, interpretation, or dissemination.

Availability of data and materials

The data that support the findings of this study are available from The Welsh Government (The Welsh Health Survey) but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of Welsh government.

Authors’ contributions

SJ and BC carried out the data collection and analysis and were major contributors in writing the manuscript. KT and HA were contributors in writing and reviewing the manuscript and all authors read and approved the final manuscript.

Ethics approval and consent to participate

The data used in this study was obtained from a cross-sectional nationwide survey and data were anonymised. Ethical approval was included in Welsh Health Survey, and a local ethics committee ruled that participants were not required to be additionally consented for this study.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Administration of Occupational Safety and Health, Dvergshofdi 2, 110 Reykjavik, Iceland
(2)
Division of Population Medicine, Cardiff University School of Medicine, Heath Park, Cardiff, CF14 4YS, UK
(3)
Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, De Crespigny Park, London, SE5 8AF, UK

References

  1. Hoy D, March L, Brooks P, Blyth F, Woolf A, Bain C, et al. The global burden of low back pain: estimates from the global burden of disease 2010 study. Ann Rheum Dis. 2014;73(6):968–74.View ArticleGoogle Scholar
  2. Work-related Musculoskeletal Disorders (WRMSDs) Statistics in Great Britain 2017 [Internet]. 2017. Available from: www.hse.gov.uk/statistics/. Accessed 20 Feb 2018.
  3. Jordan KP, Kadam UT, Hayward R, Porcheret M, Young C, Croft P. Annual consultation prevalence of regional musculoskeletal problems in primary care: an observational study. BMC Musculoskelet Disord. 2010;11:144.View ArticleGoogle Scholar
  4. Langley PC. The prevalence, correlates and treatment of pain in the European Union. Curr Med Res Opin. 2011;27(2):463–80.View ArticleGoogle Scholar
  5. Dagenais S, Caro J, Haldeman S. A systematic review of low back pain cost of illness studies in the United States and internationally. Spine J. 2008;8:8–20.View ArticleGoogle Scholar
  6. Hong J, Reed C, Novick D, Happich M. Costs associated with treatment of chronic low back pain: an analysis of the UK general practice research database. Spine (Phila Pa 1976). 2013;38(1):75–82.View ArticleGoogle Scholar
  7. Goodwin J, Bajwa ZH. Understanding the patient with chronic pain. In: Warfield CA, Bajwa ZH, editors. Principles & Practice of Pain Medicine, 2nd Edition. New York: McGraw-Hill; 2004. ISBN: 0-07-144349-5Google Scholar
  8. van Tulder M, Becker A, Bekkering T, Breen A, del Real MTG, Hutchinson A, et al. Chapter 3 European guidelines for the management of acute nonspecific low back pain in primary care. Eur Spine J. 2006;15(Suppl 2):169–91.View ArticleGoogle Scholar
  9. Ferreira ML, Machado G, Latimer J, Maher C, Ferreira PH, Smeets RJ. Factors defining care-seeking in low back pain - a meta-analysis of population based surveys. Eur J Pain. 2010;14(7):747.e1–7.View ArticleGoogle Scholar
  10. Fischbein R, McCormick K, Selius BA, Labuda Schrop S, Hewit M, Baughman K, et al. The assessment and treatment of back and neck pain: an initial investigation in a primary care practice-based research network. Prim Heal Care Res Dev. 2015;16(5):461–9.View ArticleGoogle Scholar
  11. Breivik H, Collett B, Ventafridda V, Cohen R, Gallacher D. Survey of chronic pain in Europe: prevalence, impact on daily life, and treatment. Eur J Pain. 2006;10(4):287–333.View ArticleGoogle Scholar
  12. Volkers AC, Westert GP, Schellevis FG. Health disparities by occupation, modified by education: a cross-sectional population study. BMC Public Health. 2007;7:196.View ArticleGoogle Scholar
  13. Heneweer H, Vanhees L, Picavet H. Physical activity and low back pain: a U-shaped relation? Pain. 2009;143(1–2):21–5.View ArticleGoogle Scholar
  14. van Hecke O, Torrance N, Smith BH. Chronic pain epidemiology and its clinical relevance. Br J Anaesth. 2013;111(1):13–18.Google Scholar
  15. Bergman S, Herrstrom P, Hogstrom K, Petersson IF, Svensson B, Jacobsson LT. Chronic musculoskeletal pain, prevalence rates, and sociodemographic associations in a Swedish population study. J Rheumatol. 2001;28:1369–77.PubMedGoogle Scholar
  16. Dorner TE, Muckenhuber J, Stronegger WJ, Rsky É, Gustorff B, Freidl W. The impact of socio-economic status on pain and the perception of disability due to pain. Eur J Pain. 2011;15(1):103–9.View ArticleGoogle Scholar
  17. Jhun HJ, Park JY. Estimated number of Korean adults with back pain and population-based associated factors of back pain: data from the fourth Korea National Health and nutrition examination survey. J Korean Neurosurg Soc. 2009;46(5):443–50.View ArticleGoogle Scholar
  18. Johannes CB, Le TK, Zhou X, Johnston JA, Dworkin RH. The prevalence of chronic pain in United States adults: results of an internet-based survey. J Pain. 2010;11(11):1230–9.View ArticleGoogle Scholar
  19. Latza U, Kohlmann T, Deck R, Raspe H. Can health care utilization explain the association between socioeconomic status and back pain? Spine (Phila Pa 1976). 2004;29(14):1561–6.View ArticleGoogle Scholar
  20. Leclerc A, Gourmelen J, Chastang J-F, Plouvier S, Niedhammer I, Lanoë J-L. Level of education and back pain in France: the role of demographic, lifestyle and physical work factors. Int Arch Occup Environ Health. 2009;82(5):643–52.View ArticleGoogle Scholar
  21. Schmidt CO, Raspe H, Pfingsten M, Hasenbring M, Basler HD, Eich W, et al. Back pain in the German adult population: prevalence, severity, and sociodemographic correlates in a multiregional survey. Spine (Phila Pa 1976). 2007;32(18):2005–11.View ArticleGoogle Scholar
  22. Leino-Arjas P, Hänninen K, Puska P. Socioeconomic variation in back and joint pain in Finland. Eur J Epidemiol. 1998;14(1):79–87.View ArticleGoogle Scholar
  23. Tokuda Y, Ohde S, Takahashi O, Shakudo M, Yanai H, Shimbo T, et al. Musculoskeletal pain in Japan: prospective health diary study. Rheumatol Int. 2007;28(1):7–14.View ArticleGoogle Scholar
  24. Webb R, Brammah T, Lunt M, Urwin M, Allison T, Symmons D. Prevalence and predictors of intense, chronic, and disabling neck and back pain in the UK general population. Spine (Phila Pa 1976). 2003;28(11):1195–202.Google Scholar
  25. JL C, JA M. The impact of social deprivation on chronic back pain outcomes. Chronic Illn. 2005;1(2):121–9.Google Scholar
  26. Moffett JA, Underwood MR, Gardiner ED. Socioeconomic status predicts functional disability in patients participating in a back pain trial. Disabil Rehabil. 2009;31(10):783–90.View ArticleGoogle Scholar
  27. Hagen KB, Holte HH, Tambs K, Bjerkedal T. Socioeconomic factors and disability retirement from back pain. A 1983-1993 population-based prospective study in Norway. Spine (Phila Pa 1976). 2000;25(19):2480–7.View ArticleGoogle Scholar
  28. Hagen K, Zwart JA, Svebak S, Bovim G, Jacob Stovner L. Low socioeconomic status is associated with chronic musculoskeletal complaints among 46,901 adults in Norway. Scand J Public Heal. 2005;33(4):268–75.View ArticleGoogle Scholar
  29. Picavet HSJ, Schuit AJ. Physical inactivity: a risk factor for low back pain in the general population? J Epidemiol Community Health. 2003;57(7):517–8.View ArticleGoogle Scholar
  30. Sitthipornvorakul E, Janwantanakul P, Purepong N, Pensri P, van der Beek AJ. The association between physical activity and neck and low back pain: a systematic review. Eur Spine J. 2010;20(5):677-89.View ArticleGoogle Scholar
  31. Rossignol M, Rozenberg S, Leclerc A. Epidemiology of low back pain: What’s new? Joint Bone Spine. 2009;76:608–13.View ArticleGoogle Scholar
  32. Sadler K, Doyle M, Hussey D, Stafford R. Welsh Health survey 2012: technical report [internet]. 2013. Available from: http://doc.ukdataservice.ac.uk/doc/7459/mrdoc/pdf/7459_technical_report.pdf. Accessed 3 July 2015.
  33. Riskowski JL. Associations of socioeconomic position and pain prevalence in the United States: findings from the National Health and nutrition examination survey. Pain Med. 2014;15(9):1508–21.View ArticleGoogle Scholar
  34. Fransen M, Woodward M, Norton R, Coggan C, Dawe M, Sheridan N. Risk factors associated with the transition from acute to chronic occupational back pain. Spine. 2002;27(1):92–8.View ArticleGoogle Scholar
  35. Meyer C, Denis CM, Berguin AD. Secondary prevention of chronic musculoskeletal pain: a systematic review of clinical trials. Ann Phys Rehabil Med. 2018;61(5):323–38.View ArticleGoogle Scholar

Copyright

© The Author(s). 2019

Advertisement