Abstract
The latest Global Burden of Disease Study, published at the end of 2012, has highlighted the enormous global burden of low back pain. In contrast to the previous study, when it was ranked 105 out of 136 conditions, low back pain is now the leading cause of disability globally, ahead of 290 other conditions. It was estimated to be responsible for 58.2 million years lived with disability in 1990, increasing to 83 million in 2010. This chapter illustrates the ways that the Global Burden of Disease data can be displayed using the data visualisation tools specifically designed for this purpose. It also considers how best to increase the precision of future global burden of low back pain estimates by identifying limitations in the available data and priorities for further research. Finally, it discusses what should be done at a policy level to militate against the rising burden of this condition.
Introduction
The Global Burden of Disease Injuries, and Risk Factors (GBD) 2010 Study has been the most comprehensive effort to date to estimate summary measures of population health for the world, a venture that has involved hundreds of researchers from nearly 50 countries over a number of years . The overall summary measure of population health that the GBD uses, disability-adjusted life years (DALYs), combines data on mortality, measured as years of life lost due to premature mortality (YLLs), and years of life lived in less than ideal health, measured as years lived with disability (YLDs). YLDs are the number of incident cases, multiplied by the average duration of the condition (average number of years that the condition lasts until remission or death), multiplied by the disability weight (DW). In some instances, it is calculated by multiplying the number of prevalent cases by the DW.
For the GBD 2010 study, the 1990, 2005 and 2010 burden for 291 diseases and injuries in 187 countries and 21 regions of the world were estimated. This included five musculoskeletal conditions – low back pain, neck pain, osteoarthritis of the hip and/or knee, rheumatoid arthritis and gout and an ‘other musculoskeletal conditions’ category.
As well as allowing comparisons of overall population health across different settings over time, repeated measures of population health identify which conditions are contributing most to health loss in a given population (e.g., a region or country) and capture any changes that occur over time. These data are important in informing health policy and ensuring that the most burdensome health conditions receive appropriate attention. Despite strong evidence that low back pain is a highly prevalent, disabling and costly condition , and the most common problem among the working population in high-income countries , the enormous global burden of low back pain has remained largely unrecognised and therefore underprioritised by many governments to date.
No burden estimates were made for low back pain in the original GBD 1990 study, while, for the GBD 2000–2004 updates, low back pain was ranked 105 out of 136 conditions, and estimated to contribute just 2.5 million YLDS to the global burden of disease . The low ranking in comparison to other conditions may, in part, be explained by the fact that low back pain does not cause premature mortality. However, there are several other possible contributors to the significant underestimation of the problem . Two of the three health states used to define burden from low back pain referred to an intervertebral disc disorder (episode of intervertebral disc displacement or herniation and chronic intervertebral disc disorder). As well as requiring imaging to detect these, the presence of disc pathology has been demonstrated to have poor correlation with symptoms . In addition, mild nonspecific low back pain (a common state with a substantial global impact) was excluded, duration of low back pain was assumed to be 4 days, incidence was extrapolated from period prevalence, the DWs were lower and there was a paucity of suitable data for many countries.
New, more advanced methods have been used in the most recent GBD study to estimate disease burden. As well, unlike previous GBD studies that relied solely upon a core team of scientists and methodologists to produce the GBD estimates, approximately 37 expert groups were formed to provide content expertise to the process. The expert groups assumed primary responsibility for defining the case definition and conducting systematic reviews of the incidence, prevalence and disabling sequelae of the conditions in their content areas. DWs and mortality working groups were also established to derive study-wide DW and mortality estimates, respectively.
In a previous issue of this journal devoted to low back pain, we described the process that the Low Back Pain Expert Group for the GBD 2010 study undertook to derive a case definition of low back pain and a set of discrete health states to describe the severity levels and disabling consequences of low back pain . In a subsequent issue devoted to the epidemiology of rheumatic disease, we described the methods and brief results of a series of systematic reviews undertaken to determine the incidence, remission and prevalence of low back pain throughout the world Other papers present findings of the systematic review of the global prevalence of low back pain and the development and testing of a risk of a bias tool developed specifically to assess potential bias in prevalence studies . Following on from the publication of the overall GBD study results in The Lancet at the end of 2012 , the Musculoskeletal Expert Group has reported the specific methods that were used for estimating burden of the GBD musculoskeletal conditions as well as more detailed results outlining the global burden of each of these conditions including low back pain .
To aid in the rapid dissemination of results, the GBD study data are now publicly available as a series of data visualisations, which can be accessed at http://www.healthmetricsandevaluation.org . As new information becomes available, these visualisations are being continuously updated. The tools to access the data were developed by the Institute for Health Metrics and Evaluation (IHME), an independent global health research centre based at the University of Washington and supported by the Bill & Melinda Gates Foundation and the State of Washington. As well as its utility for decision makers, it is hoped that making the data accessible in this way will allow wider scrutiny of the results .
There are many ways to examine the GBD results using these data visualisations . For example, users can produce a world map of low back pain showing YLDs or DALYs by region or country, or show the ranking of low back pain compared with other causes within a country, providing an easy-to-understand appreciation of the relative importance of low back pain within each country. The data can also be broken down by gender and age and can show changes that occur over time (1990–2010), such as how low back pain burden has changed over time in comparison with other conditions globally and within regions or individual countries.
This chapter places the findings from the GBD study relating to low back pain in context and illustrates the ways that the data can be displayed using the data visualisation tools developed by the IHME. Of note, as the data visualisations are being continuously updated, there are minor differences between the published GBD study results and the data visualisation screenshots we present (taken 31 August 2013). We will also consider and make recommendations for how further research could improve the precision of global burden of low back pain estimates in the future. Finally, the chapter will discuss what should be done at a policy level to militate against the rising burden of this condition.
Global and regional results
As reported elsewhere, low back pain was estimated to contribute 58.2 million (M) DALYs (95% uncertainty intervals (UI): 39.9–78.1M) to the global burden of disease in 1990, ranking it as the 11th leading global contributor to years lost from premature mortality or years lived in ill health . For 2010, low back pain was ranked the sixth leading contributor to overall disease burden, estimated to be 83.0M (95% UI: 56.6–111.9M) DALYs. Fig. 1 displays the rankings for the top 10 conditions globally with respect to DALYs in 2010 in comparison with 1990, in a screenshot obtained from the GBD Arrow Diagram visualisation tool.
In the absence of evidence that low back pain contributes to mortality, the YLD estimates for low back pain were identical to the DALYs. Low back pain was found to be the greatest contributor to global disability, contributing 10.7% of total YLDs ( Fig. 2 ). Fig. 3 displays a screenshot obtained from the GBD Heatmap tool that compares the top 10 causes of disability in 2010 by world region and by developed or developing countries. Low back pain is the leading cause of disability in both developed and developing countries and ranks among the top three causes in all 21 regions of the world.
Fig. 4 displays the global burden of low back pain according to number of YLDs, confirming that the greatest disability burden from low back pain is in middle age, while Fig. 5 indicates that the greatest disability burden at a per capita level occurs in older age groups. However, both graphs also indicate significant disability already arising in adolescence and early adulthood.
Global and regional results
As reported elsewhere, low back pain was estimated to contribute 58.2 million (M) DALYs (95% uncertainty intervals (UI): 39.9–78.1M) to the global burden of disease in 1990, ranking it as the 11th leading global contributor to years lost from premature mortality or years lived in ill health . For 2010, low back pain was ranked the sixth leading contributor to overall disease burden, estimated to be 83.0M (95% UI: 56.6–111.9M) DALYs. Fig. 1 displays the rankings for the top 10 conditions globally with respect to DALYs in 2010 in comparison with 1990, in a screenshot obtained from the GBD Arrow Diagram visualisation tool.
In the absence of evidence that low back pain contributes to mortality, the YLD estimates for low back pain were identical to the DALYs. Low back pain was found to be the greatest contributor to global disability, contributing 10.7% of total YLDs ( Fig. 2 ). Fig. 3 displays a screenshot obtained from the GBD Heatmap tool that compares the top 10 causes of disability in 2010 by world region and by developed or developing countries. Low back pain is the leading cause of disability in both developed and developing countries and ranks among the top three causes in all 21 regions of the world.
Fig. 4 displays the global burden of low back pain according to number of YLDs, confirming that the greatest disability burden from low back pain is in middle age, while Fig. 5 indicates that the greatest disability burden at a per capita level occurs in older age groups. However, both graphs also indicate significant disability already arising in adolescence and early adulthood.
Exploring the GBD results for low back pain at the country level
As outlined by the GBD Country Collaboration , the availability of standardised estimates of disease burden at a country level provides an opportunity to undertake comparative assessments between countries and also provides national policymakers with the necessary data to identify their most pressing health priorities and the ability to benchmark their performance in addressing them. However, it is important to note that while estimates for all causes are available for each country, empirical data for mortality and morbidity of all conditions for all countries of the world are not available, and modelling programmes have been used to extrapolate missing data for some countries and regions .
The IHME GBD Insight visualisation tool can be used to understand which diseases and injuries cause the highest burden of disease in a given country and to explore any changes that have occurred from 1990 to 2010. Similar patterns of disease burden due to low back pain are seen across the 187 countries that formed the underlying unit of analysis for GBD 2010. As an example, Fig. 6 displays the leading causes of DALYs and percent change from 1990 to 2010 for Australia. The leading contributor to overall disease burden is ischaemic heart disease but importantly, DALYs attributable to this condition have declined by approximately 28%. By contrast, DALYs due to low back pain, the second greatest contributor to overall disease burden in Australia, have increased by approximately 45% from 1990 to 2010. Fig. 7 displays the leading causes of YLDs and percent change from 1990 to 2010 for Australia. As YLDs equal DALYs for low back pain, disability attributable to low back pain, the top cause of disability in Australia, has also increased over time by the same amount. These data should be of significant concern for Australian policymakers and justify the urgent need to make low back pain a health priority area in Australia. Similar changes were seen in other developed countries.
Data limitations
One of the significant methodological innovations in GBD 2010 was the quantification of uncertainty (an approximate range of variation) in the updated burden estimates . This provides an indication of the precision of the estimates of burden of a given condition. It takes into account the number of studies that have contributed to the data and uncertainty from all sources entering the estimation of burden, for example, prevalence, incidence, duration, remission, disability weighting, severity distribution, etc. Like other causes of disease burden, the final estimates of burden attributable to low back pain for the GBD 2010 study were derived from a complex series of steps, utilising data from many sources. There are therefore likely to be multiple contributors to the uncertainty surrounding these estimates ( Table 1 ). Each ‘adjustment’ step in calculating burden will broaden the Uncetainty Interval (UI). Having larger sample sizes and fewer ‘adjustment’ steps can reduce this uncertainty.
| Data used in GBD 2010 | Limitations of data | Recommendations for next steps with respect to collection of additional empirical data |
|---|---|---|
| Prevalence of low back pain |
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| Incidence, duration and remission of low back pain |
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| Severity levels and associated disability of different health states of low back pain |
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