This paper details the methods and results for estimating the global burden of LBP for GBD 2010. It is one of a series of articles. The overall capstone GBD 2010 papers were published in the Lancet, 9 , 13–16 and the papers that report the methods and results for the MSK conditions are published in Annals of Rheumatic Diseases. 17–25 One of these papers describes in detail the methods used for estimating the global burden of the MSK conditions 22 and should be read in conjunction with the current paper.

Low back pain (LBP) is well documented as an extremely common health problem 1–4 ; it is the leading cause of activity limitation and work absence throughout much of the world, 5 and it causes an enormous economic burden on individuals, families, communities, industry and governments. 6–8 As part of the Global Burden of Disease 2010 Study (GBD 2010), 9 the global burden of musculoskeletal conditions was estimated using updated methods that address methodological limitations of previous GBD studies. 10–12 Burden was expressed in disability-adjusted life years (DALYs).

Methods

Figure 1 outlines the steps taken in estimating the burden of LBP. The GBD LBP expert group performed steps 1 to 3, and the GBD core team performed the remaining steps.

Figure 1 Steps taken in estimating the global burden of low back pain, GBD 2010.

Established case definition The initial case definition for LBP was ‘activity-limiting LBP (± pain referred into one or both lower limbs) that lasts for at least one day’.12 The ‘low back’ was defined as the area on the posterior aspect of the body from the lower margin of the twelfth ribs to the lower glutaeal folds. For the final analysis, ‘activity-limiting’ was removed from the case definition because: (1) this provided a more robust analytical model given that relatively few data points from the systematic review conformed to the case definition of LBP that was activity-limiting and (2) this definition aligned better with the LBP definition used in national health surveys that were included in the final analysis.

Established health states A series of sequelae were developed to characterise the different levels of severity and take into account the variation in functional loss associated with acute and chronic LBP with or without leg pain (table 1).12 Each sequela was defined in lay terms. Table 1 Sequelae for low back pain in GBD 2010

Performed systematic reviews The systematic reviews have been described elsewhere26–28—see online supplementary file 1 for further details. For incidence, a small number of studies were found, but all counted the number of people as the numerator rather than the number of incident episodes. This number could not be converted to episode incidence as no data were found on the average number of episodes a person with LBP experiences over time. Thus, incidence could not be used as a parameter in the burden estimates.26 For duration and remission, no population-based studies were found, and for mortality, there was no consistent and conclusive evidence that LBP is associated with an increased risk of mortality.26 For prevalence, 170 published studies were identified. These reported 1139 age and/or sex-specific estimates. All included studies were assessed for risk of bias using a tool specifically developed for GBD 2010.28 High risk of bias estimates (n=242) and estimates with a prevalence recall period greater than 1 year (n=105) were excluded, leaving a total of 792 estimates from 118 studies (101 papers). One German study29 was excluded, as it contained outlier data (point prevalence ranging from 77% to 92% in elderly Germans), and estimates more consistent with most other studies (point prevalence ranging from 20% to 50%) were available in two other German studies of equal or lower risk of bias.30 ,31 This left a total of 117 studies and 780 estimates, with data available from 47 countries and 16 of the 21 GBD world regions. There was substantial heterogeneity between studies with respect to prevalence period and case definition (ie, the minimum episode duration), anatomical location, and whether or not cases had to experience activity limitation. To make data points more comparable, adjustments were made in DisMod-MR, a Bayesian meta-regression tool developed for GBD 2010 by predicting the value of a data point as if the study had used the reference definition. To do so, DisMod-MR estimates coefficients for study-level covariates by comparing the values of prevalence measured by various methods in the global dataset. For the purpose of these analyses, it was necessary to reduce the number of categories of case definition and prevalence period. This was done by merging some of the categories on the basis of overlapping CIs or expert opinion (on the basis of proximity to overlapping CIs) for prevalence and/or regression coefficients. To determine how best to reduce the number of categories, a multivariate regression was done with prevalence (log transformed plus 0.2 to achieve normality) as the dependent variable and the following independent variables: age, sex, prevalence period, minimum episode duration, anatomical location, activity limitation, coverage, urbanicity and risk of bias (see online supplementary file 2). Three groups were formed for prevalence recall period: (1) point (including one day); (2) short-term (one week to two months); and (3) longer-term (three months to one year). Three groups were formed for anatomical case definition: (1) back, low back, ‘posterior aspect of the body from the lower margin of the twelfth ribs to the lower glutaeal folds’, and ‘thoraco-lumbo-sacral’; (2) lumbar, ‘lumbar or sacro-iliac joint(s)’, and ‘neck or back’; and (3) ‘posterior aspect of the body from the seventh cervical vertebra to the lower glutaeal folds’, and ‘thoracic or lumbar’. For the minimum episode duration definition variations, two groups were formed: (1) ‘not specified’, ‘>1 day’, ‘>3 days’, ‘>1 week’, and ‘>7 weeks’; and (2) ‘>3 months’, ‘>6 months’, ‘chronic’, and ‘frequent’. Note, the first category in each of the above groups is considered the reference category.

Established disability weights Surveys were conducted in five countries for GBD 2010 and complemented by an open access internet survey; pair-wise comparison questions were used, in which respondents were asked to indicate which of two health states presented as brief lay descriptions they considered ‘the healthier’. Results were used to derive DWs.15

Added information from National Health Surveys Additional information on prevalence of LBP was derived from the World Health Surveys (50 countries; 1495 data points)32; Australian National Health Surveys (1995, 2001, 2003/2004 and 2007/2008; 43 data points)33; Australian Surveys of Disability, Ageing and Carers (2003 and 2009; 41 data points)34; and the US National Health Information surveys (2001–2008; 168 data points)35 and NHANES (2009; 20 data points).36 Data from these surveys were not included in the systematic review as they did not fulfil our inclusion criteria at that time.

Bayesian metaregression DisMod-MR is a Bayesian metaregression tool that has a number of functions, including: (1) pooling heterogeneous data and adjusting data for methodological differences; (2) checking data on incidence, prevalence, duration, remission and mortality risk for internal consistency and (3) predicting values for countries and regions with little or no data using disease-relevant country characteristics and random effects for country, region and super-region. In the absence of usable incidence and remission data, a ‘prevalence-only’ model was run (see online supplementary file 3).

Severity distribution To estimate the distribution of LBP cases across the GBD 2010 health states, the US Medical Expenditure Panel Survey (MEPS) from 2000 to 2009 was used. This had information on the prevalence of 156 disorders included in the GBD as well as health status information provided by all individuals using the Short Form-12 (SF-12) questionnaire.37 In order to provide a translation of SF-12 values into a scale comparable with that used by the GBD 2010 DWs, the GBD core team conducted a small study on a convenience sample of respondents who were asked to fill in SF-12 to reflect 62 lay descriptions covering a wide range of severity that were used in the GBD DW surveys. With regression methods, the proportion of an individual's SF-12 score, translated into a GBD DW, that could be attributed to LBP was calculated, while controlling for any comorbid other condition. Cases were then grouped in categories of disability based on the midpoints between DWs reflecting successive levels of severity. It was assumed that those with no disability in MEPS were cases that had remitted since their diagnosis of LBP was reported. As the case definition was for ‘point prevalence’, this proportion of cases was excluded from the calculation of the average DW for all LBP and the remaining proportions were scaled to add up to 100%. MEPS respondents with LBP were partitioned into levels of severity for LBP with leg and another four for LBP without leg pain. The mild acute and chronic neck pain DWs were used as proxy DWs for the lowest LBP disability classes given that no mild LBP health states were available from the household and on-line surveys used to derive DWs (tables 2 and 3). An age distribution of the proportions of LBP with and without leg pain was derived from the prevalence figures in MEPS. The proportions for males and females combined were calculated after finding little difference by sex. From these proportions, the average DWs were calculated by age. Table 2 The eight sequela categories used for calculating the severity distribution of low back pain (with disability weights, and proportional distributions), GBD 2010 Table 3 Age-standardised prevalence and DALYs (with 95% CIs) for low back pain in the age range 0–100 years, by region and sex, 2010, GBD 2010