Archives of Physical Medicine and Rehabilitation 2020 (Feb 5) [Epub] ~ FULL TEXT
Tiago S. Jesus (Ph.D), Michel D. Landry (Ph.D), Dina Brooks (Ph.D), Helen Hoenig (MD, MPH)
Global Health and Tropical Medicine &
WHO Collaborating Center on Health Workforce Policy and Planning,
Institute of Hygiene and Tropical Medicine-NOVA University of Lisbon.
OBJECTIVE: To determine how total physical rehabilitation needs have been distributed per relevant condition groups (musculoskeletal & pain, neurological cardiothoracic, neoplasms, pediatric, and HIV-related), globally and across countries of varying income level.
DESIGN: Sub-group, secondary analyses of data from the Global Burden of Disease 2017. Data for the year 2017 are used for determining current needs, and data from every year between 1990 and 2017 for determining changing trends.
SETTINGS: Globally and High, Upper Middle, Lower Middle, and Low-Income countries.
PARTICIPANTS: Not applicable INTERVENTIONS: Not applicable.
MAIN OUTCOME MEASURE: Years Lived with Disability per 100,000 people (YLD Rates) for the 6 condition groups.
RESULTS: In 2017, musculoskeletal & pain conditions accounted for 52.6% of the total physical rehabilitation needs worldwide; HIV-related for 5.7% of the physical rehabilitation needs in low-income nations, but about 1% in all other locations. Worldwide, significant increases in YLD Rates were observed since 1990 for the 6 condition groups (p<0.01). However, across country types, we observed significant decreases in YLD Rates for specific conditions: pediatric in high-income countries, and neurological and neoplasm conditions in low-income (p<0.01). In upper middle-income countries, YLD Rates from neurological and neoplasm conditions grew exponentially since 1990, with overall increases of 67% and 130%, respectively.
CONCLUSION: At a global scale, physical rehabilitation needs per-capita are growing for all major condition groups, with musculoskeletal & pain conditions currently accounting for over half of those needs. Countries of varying income level have different typologies and evolutionary trends in their rehabilitation needs.
KEYWORDS: disability; global burden of disease; global health; health services needs and demand; rehabilitation
List of Abbreviations:
99% CI ( 99% confidence interval),
GBD ( Global Burden of Disease),
HIC ( high-income country),
HIV ( human immunodeficiency virus),
LIC ( low-income country),
LMIC ( lower-middle-income country),
UMIC ( upper-middle-income country),
YLD ( years lived with disability)
From the FULL TEXT Article:
Worldwide, gains in health have dramatically increased life expectancy and reduced
mortality. [1, 2] However, advances in health care have been far less dramatic in averting nonfatal
health losses; indeed, many life-saving interventions result in life-long disabilities.  As a
result, there is a growing focus on health policies and interventions that result in both
longer and healthier lives.4 One way to do so is by strengthening the health systems’
capacity to provide rehabilitation services. [4-11]
Physical rehabilitation has the potential to improve health outcomes worldwide. [10, 12, 13]
Rehabilitation has been shown to be a cost-effective health care intervention that enables
people with physical impairments (e.g., in mobility) or symptoms (e.g., low back pain) to
(re)gain or maintain personal independence and participate in broader aspects of daily life
such as education, work, and social roles (e.g., parent). [4, 14-16] Physical rehabilitation can also
result in reduction of secondary consequences of disability (e.g., deconditioning, pressure
sores). Finally, rehabilitation can reduce overall costs of care through reduced hospital
lengths-of-stay, preventing rehospitalizations, and enabling patients to be cared for at
Despite its health and economic benefits, unmet physical rehabilitation needs are
widespread. [11, 18, 19] Especially in many low- and middle-income countries, availability of
physical rehabilitation resources is often a small fraction of what is needed (e.g.
professionals estimated to be one-tenth of those required ), unevenly distributed within
and across nations or service types,  and of suboptimal quality. [20-22]
Moreover, needs for physical rehabilitation have been growing worldwide. A recent study,
using data from the Global Burden of Disease 2017, found a 66% increase since 1990 in the
world’s Years Lived with Disability (YLD Counts), and 17% increase when adjusting for the
growth of the population (YLD Rates).10 The same study also found that YLD Counts
appropriate for physical rehabilitation more than doubled since 1990 in countries of low
income (112% increase), while YLD Rates increased the most (by 30%) in upper-middle
In response to the widespread and growing unmet needs for physical rehabilitation, the
World Health Organization launched the “Rehabilitation 2030” initiative. This initiative
brings together key stakeholders to develop strategies and action plans to scale-up and
improve the quality of rehabilitation services worldwide,  with a goal of reducing unmet
needs for physical rehabilitation services. [13, 14] Hence, there is an acute need for data on the
physical rehabilitation needs worldwide, to inform the planning of physical rehabilitation
services and resources. However, it is not known yet which conditions are driving the
physical rehabilitation needs, and how those may differ, in actual values or proportion, by
country type, i.e. by the economic level of the country.
This study aims were to explore the typology, and the changing typology, of physical
rehabilitation needs. Specifically, we describe how physical rehabilitation needs are
distributed (in 2017), and have been distributed (since 1990), per relevant groups of
conditions (i.e. musculoskeletal & pain, neurological cardiothoracic, neoplasms, pediatric,
and HIV-related). That includes quantifying the yearly changes in physical rehabilitation
needs (and in the portion of physical rehabilitation needs) arising for each condition group,
globally and across countries of varying income level.
For this study, we used data from the Global Burden of Disease (GBD) 2017,  90 the largest
global epidemiological study to date, carrying out sub-group analyses of a previous study
using that database.  In the previous analsyis,  we determined the changing trends, from
1990 to 2017, of the total physical rehabilitation needs (i.e. for all conditions combined),
worldwide and across the groups of high-income countries (HICs), upper middle-income
countries (U-MICs), lower middle-income countries (L-MICs), and low-income countries
(LICs). In this analysis, we stratify that data by relevant conditions groupings, both
worldwide and according to country type (i.e., HICs, U-MICs, L-MICs and LICs).
Underlying health conditions and their grouping:
The underlying conditions deemed to benefit from physical rehabilitation were determined
in the original paper  through a structured process. Briefly, the process started with search
of systematic reviews on the effect of physical rehabilitation interventions for target health
conditions. For conditions in which the evidence of physical rehabilitation benefit was not
the sequalae, an explicit trade-off reasoning was applied to the selection decisions to include conditions and
not others, with a goal to avoid either an under- or over-estimation of the total physical
rehabilitation needs. The final set of health conditions deemed relevant to physical
rehabilitation is presented in table 1, left column. Then, for this analysis, these conditions
were aggregated into condition groupings, according to typical areas of physical
rehabilitation practice: [23-25] musculoskeletal & pain; neurological, cardiothoracic, neoplasms,
pediatric, and HIV-related (see table 1, right coluumn).
We also carried out a separate, further stratified analysis for 3 large groups of conditions
(i.e. musculoskeletal & pain; neurological; and cardiothoracic conditions) to examine specific
conditions. For example, in that analysis, data on cardiothoracic conditions are further
broken down into that for cardiac and pulmonary ones. The condition grouping used for
that stratified analysis is depicted in the table 1, middle column. Importantly, any these
condition groupings and subsequent units of analysis were defined a priori of the data
Physical rehabilitation needs were estimated through YLDs, which is the measure in the GBD
study that focuses exclusively on non-fatal health losses. [3, 10] YLDs consist of the years lived
with any short-term or long-term health loss weighted for severity by disability 126 weights. For
stroke, for example, disability weights vary from 0.019 for mild consequences to 0.588 for
severe consequences plus cognition problems. Details on how YLDs and disability weights
are determined, and all the disability weight values, are available elsewhere. [3, 26] Here,
envisioning the feasibility of the analysis, we used a single YLD metric, notably YLDs per
100,000 people (i.e. YLDs Rates), which adjusts YLD values to population size. This metric
most directly informs the planning of physical rehabilitation resources, in terms of the
population-adjusted amount of physical rehabilitation services and workforce required.
We used the World’s Bank classification for HICs, U-MICs, L-MICs, and LICs.
Data for the year 2017 were used to determine current physical rehabilitation needs per
condition groupings, while data from every year from 1990 to 2017 were used for
determining the change in rehabilitation needs. The use of multiple data points as a time
series allowed us to more accurately detect the changing trend in rehabilitation needs.
Data Management & Analysis:
The YLD Rates for each health condition, extracted for the previous study,  were grouped
according to the structure in table 1. Those YLD Rates can also be extracted from the
original source, the GBD 2017, through the freely - available platform
The Microsoft’s Excel software, [a] with the XLMiner Analytical ToolPak, was used for data
storage, management, and analysis. Within each location, yearly YLD Rates were summed
up for each condition group. Also, we computed relative percentages for each of those
values and we used the YLD Rates for the total physical rehabilitation need (i.e. all
conditions germane to physical rehabilitation combined)  as common denominator. That
percent value allowed us to determine which, for any given year, was the portion of the
total physical rehabilitation needs that came specifically from each condition group.
Then, yearly values were plotted and analyzed for each location using regression models.
That included determining whether the data fitted better into a linear, exponential or
logarithmic regression model, as determined by both visualization and r2 values of the
alternative models. Whenever differences between r2 values were minimal (i.e. <0.02), the
linear option was retained. The Web-Appendix 1 provides all the graphs and visually depicts
the respective regression models that best fit the data.
Linear regression analyses, with the use of ANOVA, were used to determine any significant
yearly changes in YLDs Rates and their relative percentage per condition group from 1990 to
2017. In each of those regressions (i.e. one per country type, within each condition group),
we used respective YLD Rates as the dependent variable and the years as the independent
variable. The same analytical approach was employed also for the data that best fit into an
exponential or logarithmic regression model. In those cases, we used both the actual YLD
Rates or a log-transformed version of these.
In no case for any of the six major groups of
conditions did it make a difference in the significance level of the findings. Hence, although
and confidence intervals for the actual YLD Rates (not the log-transformed ones), so to report the
magnitude of the yearly change estimates in actual YLD Rates. Nonetheless, we still signal
that such data had a best fit into a logarithmic or exponential model type (e.g. growth rate
higher in the earlier or later years, respectively), which informs on the temporal trend.
Finally, within the ancillary analyses (i.e. sub-stratifying data on type of cardiothoracic
conditions, etc, whose results are provided into appendixes), only in two cases did the
analyses with log-transformed values provide a different significant level.
In those cases, we
explictly report the statistical significance for the two approaches. Altogether, we consider
two subsequent levels of statistical significance: P values <0.05 and p values <0.01. The
latter reflects a Bonferroni correction that accounts for the five tests (i.e. one per location;
0.05/5 = 0.01) that were conducted per condition group / unit of analysis.
1- YLD Rates per condition groups
Table 2 shows that worldwide YLD Rates (i.e. YLDs per 100,000 people) relevant to physical
rehabilitation have increased significantly from 1990 to 2017 for each of the six condition
groups (p <0.01).
By stratifying the data per countries of varying income level, the following patterns were
Table 2 shows that HICs and U-MICs had high increases in the YLD Rates for musculoskeletal
& pain, neurological, and neoplasm conditions. For example, in HICs musculoskeletal & pain
conditions accounted for 16.8 additional YLDs per 10,000 inhabitants a year (99%
Confidence Interval (CI): 15.9 – 17.7) and U-MICs 20.5 (99% CI: 19.0 – 21.9).
Besides, in U-MICs YLD Rates from neurological and neoplasm conditions grew exponentially
(both r2 = 0.95; p<0.01), i.e. at a higher rate in the more recent years, with overall increases
of 67% and 130%, respectively (see Table 2), even though significant decreases in YLD Rates
from the infectious type of neurological conditions were observed across country types (all
p <0.01; see Web-Appendix 2).
Still in countries of higher income (i.e. HIC and H-UMICs), YLD Rates from cardiothoracic
conditions grew substantially in HICs (b= 7.0: 99% CI: 6.3 – 7.7), and to a lesser degree in UMICs (b= 4.3: 99% CI: 2.2 – 6.4) (Table 2), while the Web-Appendix 2 shows that increases occurred predominantly in the YLD Rates for cardiac conditions in U-MICs (b= 3.3: 99% CI:
3.1 – 3.5) and for pulmonary conditions in HICs (b= 5.5: 99% CI: 4.8 – 6.2).
In turn, in countries of lower income (i.e. L-MICs and LICs), the growth of YLD Rates from
pediatric conditions stood out. Indeed, we observed a significant increase of 4.6 YLDs a year
per 100,000 inhabitants in L-MICs (99% CI: 4.4 – 4.8), and of6.4 in LICs ((99% CI: 5.8 – 6.9).
Despite overall global increases in YLDs Rates for conditions benefitting from rehabilitation,
there were some scenarios where decreases in YLD Rates were observed. HICs had a
0.3 – (-0.1)), and
LICs a decrease for YLD Rates coming from both neoplasms (b= -0.1: 99% CI: -0.2 – (-0.1))
and neurological conditions (b= -0.5: 99% CI: -0.7 – (-0.3)). The decrease in YLD Rates from
neurological conditions in LICs was mostly driven by a reduction in the infectious type of
neurological conditions (b= -0.6: 99% CI: -0.7 – (-0.5)) - see Web-Appendix 2 where table 2’s
data are further stratified.
2- Percentage of physical rehabilitation needs
Table 3 shows that, in 2017, musculoskeletal & pain conditions account for over half of the
world’s physical rehabilitation needs (52.6%); most of these came from pain conditions in
particular (55.8%; 29.4% of the total). Moreover, we observe that musculoskeletal & pain
conditions account for 57.7% of the physical rehabilitation needs in HICs but only 47.5% in
Cardiothoracic, pediatric, and neurological conditions also account for important portions of
the world’s physical rehabilitation needs: 18.0%, 13.1%, and 12.9, respectively. Neoplasms,
in turn, represent for 2.2% of the world’s physical rehabilitation needs, but nearly twice as
much in HICs (4.1%). Finally, HIV-related conditions account for 1.2% of the physical
rehabilitation needs worldwide, albeit accounting for 5.7% of the physical rehabilitation
needs in LICs.
With respect to change between 1990 and 2017, table 3 shows that the portion of physical
rehabilitation needs arising from musculoskeletal & pain conditions significantly decreased
across countries of all income levels (all p<0.01). In turn, the portion of physical
rehabilitation needs arising from neurological conditions and neoplasms significantly
increased across country types, except for LICs in which a significant decreased was
observed (all p<0.01). Table 3 also shows that in LICs the portion of physical rehabilitation
needs coming from pediatric conditions was the only with a significant increase (p<0.01),
and by an aggregate 30.6% from 1990 to 2017.
Finally, among neurological conditions, HICs and U-MICs saw a 21.3% and 41.6% increase
respectively in the portion of physical rehabilitation needs coming from the non
communicable type of neurological disorders, relative to the 0.9% and 8.0% increase
respectively in LICs and L-MICs (see Web-appendix 3).
This paper provides an exploratory analysis of the trends in distribution of physical
rehabilitation needs per condition type, globally and across countries of varying income
level. Several findings are particularly noteworthy.
First, substantial growth of YLDs per capita occurred worldwide in all condition groups
benefitting from physical rehabilitation. Likely this is a reflection of the growing prevalence
worldwide of chronic, non-communicable and disabling health conditions, [3, 7, 27] due to
factors such as:
1) increased life expectancy and population ageing; [7, 28, 29]
medical advances and survival rates for those with heretofore fatal conditions but which
often leave sequalae benefitting from physical rehabilitation (e.g. neoplasms, HIV,
stroke); [30, 31] and
3) increased rates of obesity and sedentary lifestyles [32, 33] that lead to higher
risks for musculoskeletal, cardiovascular and other conditions with sequalae responsive to
The reduction of physical rehabilitation needs from infectious
related neurological conditions, partly due to increased vaccination rates and improved
health care, did not offset the overall increase in physical rehabilitation needs coming from
non-infectious neurological conditions.
Second, we observed important differences in the typology and growth of physical
rehabilitation need according to the countries’ income level. For instance, L-MICs and LICs
had both a higher portion and growth of physical rehabilitation needs coming from pediatric
conditions. Likely, this finding is due their population’s age structure, from higher fertility
rates and lower life expectancy, [1, 2, 34] in combination with reduction in neonatal and
children’s mortality [1, 35] and increasing survival rates and life expectancy for those with
developmental disabilities. [36, 37]
We also found that LICs had 6% of their physical
rehabilitation needs attributable to HIV-related conditions, while for the other countries this
estimate was equal to, or less than, 1%. While this difference in HIV-related conditions may
reflect a higher prevalence of HIV in LICs,  it may also reflect increasing access to anti-retroviral therapy in LICs, which increasingly transforms this life-threatening condition into a chronic, disabling condition.  Thus, based on our results, improving survival of children and services to enable optimal health outcomes.
Third, in U-MICs, physical rehabilitation needs arising from neoplasms and neurological
conditions have grown exponentially, despite the significant decrease in the infectious-type
of neurological conditions. Also, the growth of physical rehabilitation needs from cardiac
conditions stood out in U-MICs. Potential contributing factors include economic
development with changes in diet and more sedentary life style increasing the prevalence of
health conditions with adverse cardiovascular and neurological sequelae (e.g., hypertension,
hyperlipidemia), neurological trauma related to higher use of motor vehicles, and increased
life expectancy from the advances in health care. [32, 33, 39] The observed levels and typology of
physical rehabilitation needs of U-MICs were approaching those of wealthier nations.
Fourth, in HICs, we found that musculoskeletal and pain conditions account for a higher
portion of physical rehabilitation needs than in any other country type, while physical
rehabilitation needs coming from neoplasms and pulmonary conditions had the greatest
increase over time in YLD Rates. Potential contributory factors include higher life expectancy
and related population ageing in HICs, advances in cancer care, historical smoking patterns
and environmental pollution. [2, 28, 31, 40]
Finally, using YLD Rates as a metric, we found that musculoskeletal and pain conditions
account for over than 50% of the world’s physical rehabilitation needs, even though a
significant decrease in that percent value was observed across country types. This high
portion might be due the higher prevalence of musculoskeletal and pain conditions, [3, 27] even though many sequelae of neurologic conditions (e.g. stroke with severe consequences plus
cognition problems) have higher disability weights  and may in turn consume more rehabilitation resources. That may be why other studies have found that neurological conditions had the highest volume of physical rehabilitation research. [23, 24] Another possible
explanation is that we found a significant growth of the portion of physical rehabilitation
needs coming from neurological conditions in all country types, except LICs. Prioritization
for rehabilitation resource allocation and research is complex, and our analysis did not take
into account rehabilitation intensity or resource allocation across the different condition
Yet, combined with other types of data (e.g. methodological and knowledge
gaps, perspectives from the minorities and the underserved), [41-44] metrics on physical
rehabilitation needs can and should help inform global physical rehabilitation research
priorities, as increasingly observed in other health fields. [45-51] For instance, these results can
help inform research agendas on comparative effectiveness, health services and
implementation research, to help identify high-value, cost-effective and locally-relevant
rehabilitation solutions for conditions that have shown particularly important portions
and/or increases in physical rehabilitation needs. Examples might include HIV-related and
pediatric rehabilitation needs in LICs, pulmonary conditions in HICs, neurological conditions
in U-MICs, and musculoskeletal and pain conditions worldwide. In other words, our data
help highlight specific areas and conditions which, if targeted specifically, might generate
highest value for improved health outcomes at the population level.
This study has the following limitations.
First, YLD Rates from selected health conditions is only a proxy indicator of physical
rehabilitation need. YLDs for specific conditions account for the prevalence of that
condition, the time during which sequalae are present, and the severity of those sequalae;
however, it does not measure resultant functional limitations - a more proximate indicator of physical rehabilitation need.
Second, YLD Rates extracted from the GBD 2017 are only estimates modelled from the best available data and research, not actual YLD Rates. The quantity and quality of the data to
produce those estimates vary by timing and location (e.g. typically lower in earlier times and
LICs), which leads to varying levels of preciseness. That does affect the capacity to more
precisely detect any significant change in the real YLD Rates based in the YLD Rate estimates
the GBD study provides. It does not imply, however, systematic error toward under or over
estimation of physical rehabilitation needs. At each new cycle, the GBD study apply newly
collected data and more advanced estimation methods to re-calculate YLDs across locations
and the entire time series.
Third, the selection of health conditions germane to physical rehabilitation followed an a
priori methodology informed by existing systematic reviews,  but it cannot be considered
as a fixed standard of conditions germane to physical rehabilitation as the field of
rehabilitation is not static. The conditions appropriate for rehabilitation will continue to
evolve with continued advances in rehabilitation therapies and research.
Fourth, the condition groups were established according to impairment types commonly
treated by rehabilitation and/or benefitting from rehabilitation. However, the groupings do
not depict where those conditions might best be treated (e.g., inpatient, outpatient) nor the
timing of treatment (e.g., acute, episodic, chronic).
Fifth, unlike the preceding analysis of total physical rehabilitation needs which used 4
alternative YLD metrics,  we used only one YLD metric (i.e. YLDs Rates, i.e. YLDs per
100,000 population), and not Age-Standardized YLD Rates, for example.
Sixth, this study was exploratory in nature, looking for patterns in data from a large data set,
rather than testing specific hypothesis generated a priori.
Seventh, we consider statistical significance with a minimum p values <0.01. Given the
various linear regression analyses conducted, there is the possibility of a type I error.
Finally, the YLDs from one condition were all allocated to one impairment type, which is
reductionist. For example, a few of the HIV-related impairments can be of a cardiothoracic
type; leprosy can provide more than musculoskeletal sequalae, etc.
According to data from the GBD 2017, world’s physical rehabilitation needs per-capita are
growing for all major groups of conditions germane to physical rehabilitation, with
musculoskeletal & pain conditions currently accounting for over half of those needs.
Countries of varying income level have different typologies and evolutionary trends in their
rehabilitation needs. This paper shows that estimates from the GBD study can be used to
identify the current typology of physical rehabilitation need and their changing trends over
time. This type of estimates can be one indicator for an informed planning of the physical
rehabilitation resources, services, and research to meet the expanding country-specific and
global needs for rehabilitation.
GBD 2017 Mortality Collaborators
Global, regional, and national age-sex-specific mortality and life expectancy, 1950-2017:
a systematic analysis for the Global Burden of Disease Study 2017.
Lancet. 2018; 392: 1684-1735
Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death:
reference and alternative scenarios for 2016-40 for 195 countries and territories.
Lancet. 2018; 392: 2052-2090
GBD 2017 Disease and Injury Incidence and Prevalence Collaborators
Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases
and injuries for 195 countries and territories, 1990-2017: a systematic analysis
for the Global Burden of Disease Study 2017.
Lancet. 2018; 392: 1789-1858
Strengthening health systems to provide rehabilitation services.
Bull World Health Organ. 2017; 95: 167
Rehabilitation: essential along the continuum of care.
in: Disease control priorities. 3rd ed. 9. World Bank, Washington (DC)2017
Health, functioning, and disability in older adults--present status and future implications.
Lancet. 2015; 385: 563-575
Evangelista Jr., B.
Aging, non-communicable diseases, and old-age disability in low- and middle-income countries:
a challenge for global health.
Int J Public Health. 2018; 63: 1011-1012
Socio-demographic patterns of disability among older adult populations of low-income and
middle-income countries: results from World Health Survey.
Int J Public Health. 2016; 61: 337-345
Survival, disabilities in activities of daily living, and physical and cognitive functioning
among the oldest-old in China: a cohort study.
Lancet. 2017; 389: 1619-1629
Global need for physical rehabilitation: systematic analysis from the Global Burden of Disease Study 2017.
Int J Environ Res Public Health. 2019; : 16
World Health Organization
Rehabilitation 2030: A call for action. The need to scale up rehabilitation.
World Health Organization, Geneva, Switzerland2017
Towards a conceptual description of physical and rehabilitation medicine.
J Rehabil Med. 2011; 43: 760-764
Rehabilitation the health strategy of the 21st century, really?
Arch Phys Med Rehabil. 2019; 100: 2212-2214
World Health Organization
Rehabilitation 2030: a call for action. Meeting report.
World Health Organization, Geneva, Switzerland2017
Systematic overview of economic evaluations of health-related rehabilitation.
Disabil Health J. 2016; 9: 11-25
Cost-effectiveness of cardiac rehabilitation: a systematic review.
Heart. 2018; 104: 1403-1410
Cost-effectiveness of physical therapy only and of usual care for various health conditions: systematic review.
Phys Ther. 2016; 96: 774-786
Needs and unmet needs for rehabilitation services: a scoping review.
Disabil Rehabil. 2019; 41: 1227-1237
A systematic review of access to rehabilitation for people with disabilities income countries.
Int J Environ Res Public Health. 2018; 15
Human resources for health (and rehabilitation): six rehab-workforce challenges for the century.
Hum Resour Health. 2017; 15: 8
Compliance with standards of practice for health-related rehabilitation in low and middle-income settings:
development and implementation of a novel scoring method.
Disabil Rehabil. 2019; 41: 2264-2271
Crossing the global quality chasm: where does rehabilitation stand?
Arch Phys Med Rehabil. 2019; 100: 2215-2217
Systematic reviews and clinical trials in rehabilitation: comprehensive analyses of publication trends.
Arch Phys Med Rehabil. 2016; 97: 1853-1862.e1852
Evolving trends in physiotherapy research publications between 2005 and 2015.
Physiother Can. 2019 Aug 19; ([Epub ahead of print])
15 years of tracking physiotherapy evidence on PEDro, where are we now?
Br J Sports Med. 2015; 49: 907-909
Disability weights for the Global Burden of Disease 2013 study.
Lancet Glob Health. 2015; 3: e712-e723
Musculoskeletal health conditions represent a global threat to healthy aging:
a report for the 2015 World Health Organization World Report on Ageing and Health.
Gerontologist. 2016; 56: S243-S255
Measuring population ageing: an analysis of the Global Burden of Disease Study 2017.
Lancet Pub Health. 2019; 4: e159-e167
SCI longitudinal aging study: 40 years of research.
Top Spinal Cord Inj Rehabil. 2015; 21: 189-200
The increasing chronicity of HIV in sub-Saharan Africa:
re-thinking “HIV as a long-wave event” in the era of widespread access to ART.
Global Health. 2011; 7: 41
Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability
for 32 cancer groups, 1990 to 2015: a systematic analysis for the Global Burden of Disease Study.
JAMA Oncol. 2017; 3: 524-548
Health effects of overweight and obesity in 195 countries over 25 years.
N Engl J Med. 2017; 377: 13-27
The global obesity pandemic: shaped by global drivers and local environments.
Lancet. 2011; 378: 804-814
GBD 2017 Population and Fertility Collaborators
Population and fertility by age and sex for 195 countries and territories, 1950-2017:
systematic analysis for the Global Burden of Disease Study 2017.
Lancet. 2018; 392: 1995-2051
GBD 2016 Mortality Collaborators
Global, regional, and national under-5 mortality, adult mortality, age-specific mortality,
and life expectancy, 1970-2016: a systematic analysis for the Global Burden of Disease Study 2016.
Lancet. 2017; 390: 1084-1150
GBD 2017 Causes of Death Collaborators
Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries
and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017.
Lancet. 2018; 392: 1736-1788
Global Research on Developmental Disabilities Collaborators
Developmental disabilities among children younger than 5 years in 195 countries and territories, 1990-2016:
a systematic analysis for the Global Burden of Disease Study 2016.
Lancet Glob Health. 2018; 6: e1100-e1121
GBD 2015 HIV Collaborators
Estimates of global, regional, and national incidence, prevalence, and mortality of HIV, 1980-2015:
the Global Burden of Disease Study 2015.
Lancet HIV. 2016; 3: e361-e387
GBD 2016 Brazil Collaborators
Burden of disease in Brazil, 1990-2016: a systematic subnational analysis for the Global Burden of Disease Study 2016.
Lancet. 2018; 392: 760-775
GBD 2015 Tobacco Collaborators
Smoking prevalence and attributable disease burden in 195 countries and territories, 1990-2015:
a systematic analysis from the Global Burden of Disease Study 2015.
Lancet. 2017; 389: 1885-1906
Members of minority and underserved communities set priorities for health research.
Milbank Q. 2018; 96: 675-705
The convention on the rights of persons with disabilities:
a foundation for ethical disability and health research in developing countries.
Am J Public Health. 2014; 104: 2037-2043
Towards deep inclusion for equity-oriented health research priority-setting: a working model.
Social Sci Med. 2016; 151: 215-224
Exploring the ethics of global health research priority-setting.
BMC Med Ethics. 2018; 19: 94
The 10 largest public and philanthropic funders of health research in the world:
what they fund and how they distribute their funds.
Health Res Policy Syst. 2016; 14: 12
Alignment of systematic reviews published in the Cochrane Database of Systematic Reviews and the
Database of Abstracts and Reviews of Effectiveness with global burden-of-disease data:
a bibliographic analysis.
J Epidemiol Commun Health. 2015; 69: 708-714
Global burden of eye and vision disease as reflected in the Cochrane Database of Systematic Reviews.
JAMA Ophthalmol. 2015; 133: 25-31
Global burden of skin disease as reflected in Cochrane Database of Systematic Reviews.
JAMA Dermatol. 2014; 150: 945-951
Comparing cutaneous research funded by the National Institute of Arthritis and Musculoskeletal
and Skin Diseases with 2010 Global Burden of Disease results.
PLoS One. 2014; 9 (e102122)
NIH disease funding levels and burden of disease.
PLoS One. 2011; 6 (e16837)
NSFC health research funding and burden of disease in China.
PLoS One. 2014; 9: e111458
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