ArticlePDF Available

Prevalence of arthritis according to age, sex and socioeconomic status in six low and middle income countries: Analysis of data from the World Health Organization study on global AGEing and adult health (SAGE) Wave 1

Authors:
  • Deakin University Melbourne Australia

Abstract and Figures

Background In higher income countries, social disadvantage is associated with higher arthritis prevalence; however, less is known about arthritis prevalence or determinants in low to middle income countries (LMICs). We assessed arthritis prevalence by age and sex, and marital status and occupation, as two key parameters of socioeconomic position (SEP), using data from the World Health Organization Study on global AGEing and adult health (SAGE). MethodsSAGE Wave 1 (2007–10) includes nationally-representative samples of older adults (≥50 yrs), plus smaller samples of adults aged 18-49 yrs., from China, Ghana, India, Mexico, Russia and South Africa (n = 44,747). Arthritis was defined by self-reported healthcare professional diagnosis, and a symptom-based algorithm. Marital status and education were self-reported. Arthritis prevalence data were extracted for each country by 10-year age strata, sex and SEP. Country-specific survey weightings were applied and weighted prevalences calculated. ResultsSelf-reported (lifetime) diagnosed arthritis was reported by 5003 women and 2664 men (19.9% and 14.1%, respectively), whilst 1220 women and 594 men had current symptom-based arthritis (4.8% and 3.1%, respectively). For men, standardised arthritis rates were approximately two- to three-fold greater than for women. The highest rates were observed in Russia: 38% (95% CI 36%–39%) for men, and 17% (95% CI 14%–20%) for women. For both sexes and in all LMICs, arthritis was more prevalent among those with least education, and in separated/divorced/widowed women. Conclusions High arthritis prevalence in LMICs is concerning and may worsen poverty by impacting the ability to work and fulfil community roles. These findings have implications for national efforts to prioritise arthritis prevention and management, and improve healthcare access in LMICs.
Content may be subject to copyright.
R E S E A R C H A R T I C L E Open Access
Prevalence of arthritis according to age, sex
and socioeconomic status in six low and
middle income countries: analysis of data
from the World Health Organization study
on global AGEing and adult health (SAGE)
Wave 1
Sharon L. Brennan-Olsen
1,2,3,4*
, S. Cook
1
, M. T. Leech
5
, S. J. Bowe
1
, P. Kowal
6,7
, N. Naidoo
6
, I. N. Ackerman
8
,
R. S. Page
1,9
, S. M. Hosking
1
, J. A. Pasco
1,3
and M. Mohebbi
1
Abstract
Background: In higher income countries, social disadvantage is associated with higher arthritis prevalence; however,
less is known about arthritis prevalence or determinants in low to middle income countries (LMICs). We assessed
arthritis prevalence by age and sex, and marital status and occupation, as two key parameters of socioeconomic
position (SEP), using data from the World Health Organization Study on global AGEing and adult health (SAGE).
Methods: SAGE Wave 1 (200710) includes nationally-representative samples of older adults (50 yrs), plus smaller
samples of adults aged 18-49 yrs., from China, Ghana, India, Mexico, Russia and South Africa (n= 44,747). Arthritis was
defined by self-reported healthcare professional diagnosis, and a symptom-based algorithm. Marital status and
education were self-reported. Arthritis prevalence data were extracted for each country by 10-year age strata, sex and
SEP. Country-specific survey weightings were applied and weighted prevalences calculated.
Results: Self-reported (lifetime) diagnosed arthritis was reported by 5003 women and 2664 men (19.9% and 14.1%,
respectively), whilst 1220 women and 594 men had current symptom-based arthritis (4.8% and 3.1%, respectively). For
men, standardised arthritis rates were approximately two- to three-fold greater than for women. The highest rates were
observed in Russia: 38% (95% CI 36%39%) for men, and 17% (95% CI 14%20%) for women. For both sexes and in all
LMICs, arthritis was more prevalent among those with least education, and in separated/divorced/widowed women.
Conclusions: High arthritis prevalence in LMICs is concerning and may worsen poverty by impacting the ability to
work and fulfil community roles. These findings have implications for national efforts to prioritise arthritis prevention
and management, and improve healthcare access in LMICs.
Keywords: Arthritis, Epidemiology, Prevalence, Socio-demographic characteristics, Low and middle income countries
* Correspondence: sbrennan@unimelb.edu.au
1
Deakin University, Geelong, Australia
2
Australian Institute for Musculoskeletal Science (AIMSS), The University of
Melbourne-Western Precinct, Level 3, Western Centre for Health Research
and Education (WCHRE) Building, C/- Sunshine Hospital, Furlong Road, St
Albans, Melbourne, VIC 3021, Australia
Full list of author information is available at the end of the article
© The Author(s). 2017 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.
Brennan-Olsen et al. BMC Musculoskeletal Disorders (2017) 18:271
DOI 10.1186/s12891-017-1624-z
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Background
Worldwide, musculoskeletal disorders represent a global
threat to healthy ageing [1], and are ranked as the sec-
ond most common cause of disability, measured by years
lived with disability (YLDs) [2]. Lower and middle in-
come countries (LMICs) are not immune to the burden
of musculoskeletal diseases, indeed the prevalence of this
non-communicable disease (NCD) group is dramatically
increasing in LMICs [3]. The 2010 Global Burden of
Disease (GBD) study reported that musculoskeletal dis-
eases accounted for 19.2% of all YLDs in LMICs [3].
Despite this, the majority of the global NCD initiatives
do not include musculoskeletal diseases [3]. Significantly
contributing to the global disability burden associated
with the musculoskeletal system are arthritis diseases.
Arthritisisanumbrellatermthatencompassesinex-
cess of 100 different arthritic conditions which are a
chronic, painful, and debilitating group of diseases.
Arthritis, specifically osteoarthritis, is a significant
contributor to global disability burden, and the YLDs
attributable to osteoarthritis have increased by 75%
from 1990 to 2013 [2], indicating this disease as a
growing problem internationally. In combination with
an increasing trajectory of arthritis prevalence [2, 4],
growth in YLDs attributable to arthritis is due pri-
marily to increased life expectancy worldwide, and
prolonged exposure to arthritis risk factors [5].
Compared to higher income countries, many LMICs
[6], where two-thirds of the worlds population resides,
have a much lower capacity to pay for adequate health-
care. Indeed, LMICs have 90% of the global burden of
disease but only 12% of global health spending [7]. In
higher income countries, arthritis is associated with re-
duced workplace productivity [8, 9]; however, for resi-
dents of LMICs, arthritis imposes a potential additional
burden by creating a vicious cycle that subsequently
worsens poverty [10]. For example, compared to higher
income countries, and in context of scarce medical
and social support systems, residents of LMICs with
arthritis also experience reduced ability to access,
afford or utilize treatments including analgesic and
anti-inflammatory pharmacotherapies [11, 12], or
arthroplasty for advanced disease [13, 14]. They also
have, in context of workforce capacity limitations, less
flexibility regarding working conditions or hours [15],
and few if any options for early retirement, or social
security safety netspertaining to minimum income,
including financial and/or material goods.
Whilst the majority of research regarding arthritis
prevalence has been undertaken in higher income coun-
tries, recent data from the 2010 GBD Study provides
some evidence that LMICs may have greater arthritis
prevalence than higher income countries [16]. Yet, while
valuable population level estimates, extrapolation from
these GBD estimates is difficult given that they are based
on published prevalence and incidence data from a small
number of heterogeneous studies spanning different
time periods in a limited number of LMIC [17]. Further-
more, data from multi-country studies of LMICs that
have examined prevalence of arthritis across sociodemo-
graphic factors are typically not readily available [18, 19],
with the exception of a recent publication, which
showed that more years of schooling and greater levels
of wealth decreased the odds of having an undiagnosed
NCD, including arthritis [20]. Understanding the preva-
lence of arthritis across different parameters of socioeco-
nomic position (SEP) data would augment our global
understanding of global arthritis prevalence, social deter-
minants and burden.
To date, country-specific arthritis prevalence across
parameters of SEP has not been systematically evalu-
ated in large, nationally representative samples of
populations from LMICs. This information is crucial
for planning future healthcare delivery for high bur-
den chronic conditions and to ensure sufficient
health workforce capacity both significant concerns
in an ageing world [21]. Comprehensive data have
been collected in the World Health Organization
(WHO) Study on global AGEing and adult health
(SAGE) [20, 22, 23], thus providing an important re-
source to investigate disease prevalence in large
population samples from six LMICs. Using SAGE
Wave 1, these analyses were undertaken to determine
the prevalence of arthritis in LMICs according to
age, sex, and socioeconomic position (SEP).
Methods
Study population and design
SAGE Wave 1 (200710) is a longitudinal study with na-
tionally representative samples of persons aged 50+ years
and a smaller sample of adults aged 1849 years that in-
cludes 44,747 adults aged 18 years from China, Ghana,
India, Mexico, Russian Federation and South Africa [23].
Multistage cluster sampling strategies were used with
households as sampling units. Households were classi-
fied into one of two mutually exclusive categories: i) all
persons aged 50 years and older were selected from
olderhouseholds, and ii) one person aged 1849 years
was selected from each youngerhousehold. An older
or younger household was defined by the age of the re-
spondent targeted for individual interview. Household-
level and person-level analysis weights were calculated
for each country. This research was performed in ac-
cordance with the Declaration of Helsinki. The WHO
and the respective implementing agency in each country
provided ethics approvals. Written, informed consent
was obtained from all participants.
Brennan-Olsen et al. BMC Musculoskeletal Disorders (2017) 18:271 Page 2 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Data collection in WHO SAGE
Using a standardized survey instrument to ensure
consistency, and based on standardized methods, inter-
viewer training and translation protocols, face-to-face in-
terviews were conducted in China (200810; response
93%), Ghana (200809; response 81%), India (200708;
response 68%), Mexico (200910; response rate 53%),
the Russian Federation (200710; response 83%) and
South Africa (200708; response 75%), as previously
published [23]. Full details regarding the probability
sampling design, cluster sampling strategies and
country-specific areas included in SAGE have been pub-
lished elsewhere [23]. Briefly, the SAGE questionnaire
consisted of household, individual and proxy question-
naires, a verbal autopsy, and appendices: the domains of
which are summarised in Table 1 [23].
Arthritis status: self-reported and symptom-based
For the current analyses, self-reported diagnosis of arth-
ritis (lifetime) was based on participant responses to the
question; Have you ever been diagnosed with/told by a
health care professional you have arthritis (a disease of the
joints; or by other names rheumatism or osteoarthritis)?
As a secondary endpoint, a symptom-based determination
of arthritis (yes/no for current within the previous
12 months) was also employed, by applying an algorithm
developed by the WHO SAGE study team [23]; questions
and the algorithm are presented in Table 2.
Socioeconomic position
SEP was measured using two key parameters of marital
status and educational attainment: the latter used due to
the inextricable link between education and skilled vs. un-
skilled labour, and thus financial remuneration for work.
Self-reported marital status was categorised for analyses
into three groups of: (i) never married, (ii) currently mar-
ried or cohabitating, and (iii) separated/divorced or
widowed. Participants were asked if they had ever been to
school; for those that indicated yes, they were also asked
to identify the highest level of education completed. Educa-
tion was categorised as (i) no formal schooling,(ii)less
than primary school, or primary school completed, (iii) sec-
ondary school completed, or high school (or equivalent)
completed, or (iv) college, pre-university or university com-
pleted, or post-graduate degree completed. Education
levels were mapped to an international standard [24].
Statistical analyses
Arthritis (self-reported and symptom-based) prevalence
and 95% confidence intervals (95%CI) were calculated
by implementing household level analysis weights separ-
ately for each of the six countries across 10-year age
strata (the 2029 year age group was expanded to also
include those aged 1819 years), sex, marital status and
education. Country-specific survey weightings were
applied, and weighted prevalence calculated for each
country. Adjustment of prevalence estimates for differ-
ences in the age structure across countries was accom-
plished by age-standardisation, using the direct method
of standardisation [25] and the WHO World Standard
Population distribution (%) as standard population [26].
Ten-year intervals were used for age categorisation.
Results
Country-specific numbers and proportions of the total
44,747 participants (total 57.1% women), were; China
n= 15,050 (33.6%), Ghana n=5573(12.5%),India
n=12,198(27.3%),Mexicon= 2752 (6.1%), the Russian
Federation n= 4947 (11.1%), and South Africa n=4227
(9.5%). Across the entire study population, 5003 women
and 2664 men had (lifetime) self-reported arthritis (19.9%
and 14.1%, respectively), whilst 1220 women and 594 men
Table 1 Questionnaire sections included in the SAGE Wave 1
standardized survey instrument [23]
Questionnaire
section
Household roster Questions regarding the dwelling, income, transfers
[of family members] in and out of the household,
assets and expenditures
Individual
questionnaire
Questions regarding health and its determinants,
disability, work history, risk factors, chronic
conditions, caregiving, subjective well-being, health
care utilization and health systems responsiveness
Proxy
questionnaire
Questions regarding health, functioning, chronic
conditions, and health care utilization
Verbal autopsy Performed to ascertain the probable cause of death
for deaths in the household in the 24 months prior
to interview or between interview waves
Appendices Includes show-cards to assist with the interviews
Table 2 Symptom-based questions and the related algorithm
to ascertain prevalent arthritis, developed as part of the World
Health Organization SAGE Wave 1 [23]
Question number Question text and algorithm
1 During the last 12 months, have you experienced
pain, aching, stiffness or swelling in or around the
joints (like arms, hands, legs or feet) which were
not related to an injury and lasted for more than
a month?
2 During the last 12 months, have your experienced
stiffness in the joint in the morning after getting up
from bed, or after a long rest of the joint without
movement?
3 Did this stiffness last for more than 30 min?
4 Did this stiffness go away after exercise or
movement in the joint?
Algorithm If a participant responded with yesto questions
1 and/or 2, and responded with yesto question
3 and noto question 4, then the participant was
categorised as having arthritis
Brennan-Olsen et al. BMC Musculoskeletal Disorders (2017) 18:271 Page 3 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
were identified as having (within previous 12 months)
symptom-based arthritis (4.8% and 3.1%, respectively).
Table 3 presents the country-specific proportional
responses (non-weighted) to the four symptom-based
questions (see Table 2), that were included in the
algorithm to determine symptom-based arthritis. For
women, proportions that reported any pain during the
last 12 monthsor any stiffness during the last 12
monthswere lowest for Mexico (28.4% [95% CI 26.3%
30.9%] and 23.3% [95% CI 20.9%26.0%], respectively)
and highest for the Russian Federation (48.4% [95% CI
46.4%50.4%] and 50.5% [95% CI 48.8%52.1%], respect-
ively). For men, the proportions that reported any pain
during the last 12 monthsor any stiffness during the
last 12 monthswere lowest for Mexico (20.1% [95% CI
17.5%23.0%] and 16.1% [95% CI%CI 14.1%18.3%], re-
spectively) and highest for the Russian Federation (32.9%
[95% CI 30.5%35.5%] and 34.6% [95% CI 32.4%
36.9%], respectively).
Table 4 presents the country-specific and sex-stratified
prevalence of self-reported arthritis (weighted), across
age strata, educational attainment and marital status.
For both sexes in each country, arthritis prevalence
increased proportionally with advancing age; with the
exception of women from China and men and women
from South Africa who had the greatest prevalence in
the age group of 6069 years, all other groups showed a
peak in arthritis prevalence in the oldest age group
70 years. For women, the prevalence by country ranged
from 22.9% (95% CI 11.2%41.1%) in Mexico to 45.7%
(95% CI 39.1%52.3%) in the Russian Federation. For
men, prevalence ranged from 9.7% (95% CI 6.3%14.5%)
in Mexico to 37.8% (95% CI 30.3%46.0%) in the
Russian Federation. In each country, women who had
never been formally schooled or had completed less than
primary school had the highest prevalence of arthritis
compared to those with a greater level of educational at-
tainment. Higher arthritis prevalence was consistently
observed for women that were separated, divorced or
widowed (range: Russian Federation 36.4% [95% CI
29.1%44.4%] to Ghana 11.7% [95% CI 8.9%15.1%])
compared to those that were never married or currently
married (range: China 0.9% [95% CI 0.3%3.0%] to
South Africa 12.1% [95% CI 5.5%24.7%]). Similar to
women, men that had never been formally schooled had
the highest arthritis prevalence, with the exception of
men from the Russian Federation, for whom the greatest
prevalence was observed in those that had completed all
or some primary school level education (39.6% [95% CI
21.3%61.4%]), however these numbers were small.
Compared to other categories, men that were never
married had the lowest arthritis prevalence (range:
Mexico 0.1% [95% CI 0.0%0.5%] to India 3.9% [95% CI
1.5%9.5%]). In China and India, men that were
currently married had the highest prevalence (11.9%
[95% CI 9.4%14.8%], and 8.8% [95% CI 7.2%10.7%],
respectively), whilst for all other countries, men that
were separated, divorced or widowed were observed to
have the highest arthritis prevalence (highest: Russian
Federation 33.5% [95% CI 13.3%62.3%]).
Table 5 presents the country-specific and sex-stratified
prevalence of symptom-based arthritis prevalence
(weighted), across age strata, educational attainment and
marital status, for each LMIC. Patterns of symptom-
based arthritis prevalence were similar to self-reported
arthritis for both sexes; however, prevalence was lower
than observed for self-reported arthritis.
Figure 1 presents a box plot of the age-standardised
rates of self-reported arthritis, stratified by sex, across each
country (crude and age-standardised rates are presented
in Additional file 1: Online Table S1). For five of the six
LMICs, the standardised rates of arthritis for men were
approximately twice that observed for women; the excep-
tion was Ghana, where men had rates three times greater
than those observed for women (12% [95% CI 11%13%]
vs.4%[95%CI3%5%]). The highest rates of arthritis
were observed in the Russian Federation: for men the rate
was 38% (95% CI 36%39%) and for women it was 17%
(95% CI 14%20%).
Discussion
We present the prevalence of arthritis across age, sex
and different parameters of SEP in a large population-
based study spanning six LMICs. Across the countries
and for both sexes, higher arthritis prevalence was con-
sistently associated with older age and lower educational
attainment, whilst higher prevalence was also observed
in women, but not men, that were separated, divorced,
or widowed.
The pattern between advancing age and increasing
arthritis prevalence in LMICs appears similar to the pat-
tern observed in higher income countries [27]. However,
after age-standardisation, we observed in our current
study that the rates of arthritis in LMICs were greater
than those reported in higher income countries, specific-
ally for men from China, India, the Russian Federation
and South Africa. Compared to higher income countries,
higher age-standardised rates of arthritis were also ob-
served for women from the Russian Federation; however,
for the remaining five LMICs, rates appeared to be simi-
lar to those observed from higher income countries. Our
results indicate the importance of age-standardisation
when reporting prevalence data, in order that fair com-
parisons can be applied when discussing whether any
disparities in diseases exist between countries. In
addition to the peak of arthritis prevalence observed in
older age groups, we observed a sizeable proportion of
arthritis in younger age groups; prevalence that would
Brennan-Olsen et al. BMC Musculoskeletal Disorders (2017) 18:271 Page 4 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Table 3 Responses to the four questions
a
included in the algorithm for symptom-based arthritis, stratified by country and sex
b
(non-weighted)
Women (n= 25,180)
China (n= 8016) Ghana (n= 2749) India (n= 7489) Mexico
b
(n= 1692) Russian Federation (n= 2806) South Africa (n= 2428)
c
Any pain during last 12 months? (Yes) 29.1% (28.0%30.2%) 38.2% (36.4%40.0%) 29.2% (28.0%30.4%) 28.4% (26.3%30.9%) 48.4% (46.4%50.4%) 36.5% (34.6%38.4%)
c
Any stiffness during last 12 months? (Yes) 24.2% (23.2%25.2%) 43.5% (41.5%45.6%) 29.7% (28.5%30.8%) 23.3% (20.9%26.0%) 50.5% (48.8%52.1%) 33.2% (31.2%35.3%)
d
Did stiffness last for >30 min? (Yes) 24.7% (22.4%27.1%) 38.1% (35.6%40.7%) 33.3% (30.9%35.2%) 26.1% (21.8%31.0%) 45.3% (42.8%47.9%) 36.3% (33.3%39.4%)
d
Did stiffness go away after movement? (No) 19.2% (17.4%21.0%) 31.5% (28.9%34.2%) 25.4% (23.7%27.3%) 15.3% (12.3%18.9%) 33.1% (30.5%35.9%) 19.8% (17.2%22.7%)
Men (n= 18,914)
China (n= 6993) Ghana (n= 2816) India (n= 4709) Mexico (n= 1050) Russian Federation
b
(n= 1549) South Africa (n= 1797)
c
Any pain during last 12 months? (Yes) 20.4% (19.6%21.3%) 25.2% (23.5%26.9%) 23.4% (22.0%24.7%) 20.1% (17.5%23.0%) 32.9% (30.5%35.5%) 25.3% (23.3%27.5%)
c
Any stiffness during last 12 months? (Yes) 17.2% (16.4%17.9%) 29.8% (28.2%31.5%) 25.4% (24.1%26.7%) 16.1% (14.1%18.3%) 34.6% (32.4%36.9%) 23.7% (21.9%25.5%)
d
Did stiffness last for >30 min? (Yes) 26.5% (24.4%28.8%) 29.2% (25.6%33.1%) 29.0% (26.5%31.6%) 25.9% (19.7%33.3%) 40.0% (35.0%45.1%) 30.1% (25.6%35.0%)
d
Did stiffness go away after movement? (No) 20.4% (18.1%22.9%) 25.2% (22.3%28.3%) 22.5% (19.8%25.4%) 17.9% (12.6%24.8%) 29.4% (25.5%33.7%) 16.4% (13.0%20.6%)
Data presented as proportions with 95% confidence intervals (95% CI)
a
Complete wording of the symptom-based questions are presented in Table 2
b
Approximately 12% of the sample from the Russian Federation had no information regarding sex of respondents
c
Proportions (95% confidence intervals) are based on the total study population from each LMIC
d
Proportions (95% confidence intervals) are based on those that responded yesto either one or both of the first two symptom-based questions
Brennan-Olsen et al. BMC Musculoskeletal Disorders (2017) 18:271 Page 5 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Table 4 Country-specific self-reported arthritis prevalence (weighted), across age strata, educational attainment and marital status, stratified by sex
Women with self-reported arthritis (n= 5003)
China
n= 1851
Ghana
n= 350
India
n= 946
Mexico
n= 206
Russian Federation
n=1049
South Africa
n= 601
Age (years)
1829 3.7% (0.9%14.5%) 4.4% (1.3%13.8%) 2.9% (1.9%4.2%) 0.4% (0.1%2.8%) 4.0% (0.6%22.1%) 8.9% (1.8%34.2%)
3039 6.0% (3.8%9.5%) 3.0% (0.9%9.2%) 8.5% (6.7%10.7%) 1.8% (0.5%6.0%) 14.7% (7.0%28.3%) 0.2% (0.0%1.6%)
4049 15.1% (11.2%20.0%) 3.6% (1.6%8.1%) 12.2% (9.6%15.3%) 7.9% (2.2%24.5%) 21.4% (10.5%38.6%) 11.3% (5.6%21.4%)
5059 22.1% (20.0%24.4%) 11.5% (9.1%14.5%) 19.8% (16.7%23.2%) 6.6% (2.3%17.5%) 21.1% (15.6%27.9%) 29.2% (24.6%34.2%)
6069 29.7% (27.1%32.6%) 15.4% (12.1%19.5%) 21.4% (16.7%26.9%) 13.0% (8.8%18.7%) 36.4% (29.6%43.8%) 31.5% (25.7%38.0%)
70+ 29.2% (26.7%31.9%) 22.8% (18.6%27.6%) 23.5% (18.8%29.0%) 22.9% (11.2%41.1%) 45.7% (39.1%52.3%) 26.5% (20.7%33.2%)
Formal education
a
Never schooled 24.1% (19.9%28.8%) 9.5% (7.0%12.7%) 12.6% (10.9%14.6%) 11.0% (4.7%23.5%) 51.8% (31.0%72.1%) 17.5% (12.8%23.5%)
Primary school 18.1% (13.7%23.6%) 5.2% (2.9%9.3%) 12.7% (10.5%15.3%) 7.4% (3.7%14.4%) 42.4% (33.0%52.4%) 31.1% (21.0%43.5%)
Secondary school 13.0% (10.1%16.5%) 4.6% (2.4%8.9%) 5.5% (4.0%7.5%) 3.1% (1.3%7.4%) 25.0% (20.0%30.8%) 8.4% (4.8%14.3%)
College 4.7% (1.6%13.1%) 1.6% (0.7%4.0%) 6.7% (2.7%15.6%) 1.6% (0.7%3.6%) 15.1% (10.0%22.2%) 1.5% (0.6%3.6%)
Marital status
b
Never married 0.9% (0.3%3.0%) 7.8% (2.3%23.2%) 1.1% (0.4%3.0%) 1.3% (0.7%2.4%) 7.8% (4.4%13.4%) 12.1% (5.5%24.7%)
Married 14.7% (12.6%17.2%) 3.5% (2.1%6.0%) 10.3% (9.1%11.7%) 4.3% (2.5%7.3%) 17.4% (12.4%24.0%) 9.2% (5.5%14.9%)
Divorced/widowed 25.2% (19.9%31.5%) 11.7% (8.9%15.1%) 19.1% (15.9%22.7%) 19.0% (8.1%38.4%) 36.4% (29.1%44.4%) 19.3% (12.8%28.1%)
Men with self-reported arthritis (n= 2664)
China
n= 1145
Ghana
n= 230
India
n= 578
Mexico
n=77
Russian Federation
n=363
South Africa
n= 271
Age strata (years)
1829 1.3% (0.2%8.8%) 2.1% (1.0%4.7%) −−0.7% (0.1%3.4%)
3039 5.5% (2.4%12.1%) 0.2% (0.0%1.4%) 6.1% (3.8%9.8%) 14.6% (5.4%34.1%) 1.3% (0.3%5.8%)
4049 12.0% (7.9%18.0%) 3.7% (1.5%8.7%) 7.9% (5.1%12.1%) 2.9% (0.6%13.2%) 4.7% (1.3%15.9%) 0.9% (0.3%3.0%)
5059 13.7% (11.8%15.8%) 7.4% (5.4%10.1%) 13.7% (11.3%16.5%) 0.9% (0.3%2.6%) 21.6% (9.5%42.2%) 12.6% (9.3%16.8%)
6069 20.0% (17.7%22.5%) 11.6% (8.6%15.4%) 16.9% (13.8%20.6%) 8.0% (4.7%13.3%) 21.3% (15.2%29.0%) 28.2% (22.1%35.2%)
70+ 22.9% (20.7%25.2%) 16.7% (12.6%21.7%) 17.8% (14.5%21.7%) 9.7% (6.3%14.5%) 37.85 (30.3%46.0%) 20.9% (13.5%30.9%)
Formal education
a
Never schooled 22.3% (13.2%35.2%) 6.3% (4.5%8.7%) 9.0% (6.7%12.1%) 7.7% (3.2%17.3%) 4.4% (0.6%26.8%) 10.4% (6.0%17.6%)
Primary school 14.8% (10.3%20.7%) 2.9% (1.6%4.9%) 9.0% (6.6%12.1%) 3.7% (1.8%7.7%) 39.6% (21.3%61.4%) 7.1% (4.4%11.2%)
Secondary school 9.2% (7.3%11.5%) 4.6% (2.3%8.9%) 8.5% (6.4%11.3%) 0.3% (0.1%0.7%) 11.9% (7.2%19.0%) 2.2% (1.1%4.6%)
College 7.4% (3.8%-13.95) 2.3% (1.1%4.9%) 4.1% (2.0%8.0%) 0.2% (0.0%1.1%) 9.4% (3.1%25.1%) 2.3% (0.9%6.1%)
Brennan-Olsen et al. BMC Musculoskeletal Disorders (2017) 18:271 Page 6 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Table 4 Country-specific self-reported arthritis prevalence (weighted), across age strata, educational attainment and marital status, stratified by sex (Continued)
Marital status
b
Never married 3.0% (1.5%5.9%) 0.3% (0.1%1.0%) 3.9% (1.5%9.5%) 0.1% (0.0%0.5%) 0.9% (0.3%3.1%) 2.0% (0.8%4.7%)
Married 11.9% (9.4%14.8%) 4.5% (3.1%6.5%) 8.8% (7.2%10.7%) 2.2% (1.1%4.4%) 11.3% (7.5%16.7%) 5.6% (4.1%7.6%)
Divorced/widowed 11.8% (8.7%15.7%) 8.5% (5.4%13.2%) 6.5% (3.8%10.7%) 6.6% (3.3%12.6%) 33.5% (13.3%62.3%) 13.2% (5.6%27.9%)
Data presented as proportions with 95% confidence intervals (95% CI)
Abbreviations:LMIC low and middle income countries, WHO World Health Organization
a
Categories of formal education are; primary school (less than primary school, or primary school completed); secondary school (secondary school completed, or high school or its equivalent completed); college
(college or pre-university completed, or post-graduate degree completed)
b
Categories of marital status are; married (currently married or cohabiting); divorced/widowed (separated or divorced, or widowed)
Brennan-Olsen et al. BMC Musculoskeletal Disorders (2017) 18:271 Page 7 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
have significant impacts on work capacity and social
roles. Indeed, whilst contextually different and focused
upon osteoarthritis, similar findings have been reported
in higher income countries [28, 29].
Ours are the first prevalence figures of arthritis to be
presented across different socioeconomic parameters for
residents of LMICs. Whilst the overall arthritis preva-
lence has been reported for some countries included the
Table 5 Country-specific symptom-related arthritis prevalence (weighted) across age strata, educational attainment and marital sta-
tus, stratified by sex
Women With symptom-related arthritis (n= 1220)
China
n= 201
Ghana
n= 290
India
n= 238
Mexico
n=29
Russian Federation
n= 358
South Africa
n= 104
Age (years)
1829 −− 0.9% (0.4%1.8%) −− −
3039 1.6% (0.4%6.6%) 1.5% (0.7%3.2%) 12.5% (4.4%30.7%) 0.2% (0.0%1.7%)
4049 0.3% (0.1%1.3%) 3.3% (1.3%7.9%) 2.8% (1.7%4.4%) 1.2% (0.2%8.0%) 2.3% (0.5%9.5%) 2.4% (0.3%15.7%)
5059 4.1% (3.0%5.7%) 11.5% (8.6%15.2%) 5.9% (43%8.0%) 0.7% (0.1%4.1%) 4.3% (2.6%7.1%) 6.2% (3.7%10.2%)
6069 4.0% (2.8%5.8%) 16.5% (12.3%21.9%) 5.6% (4.0%7.9%) 1.5% (0.7%3.2%) 10.0% (7.0%14.2%) 5.5% (3.0%9.8%)
70+ 5.6% (3.9%7.9%) 18.6% (14.9%23.0%) 6.7% (4.7%9.7%) 2.1% (0.9%4.7%) 20.1% (14.4%27.4%) 5.6% (3.3%9.2%)
Formal education
a
Never schooled 4.1% (3.3%5.1%) 9.4% (6.9%12.7%) 3.7% (2.9%4.7%) 1.5% (0.5%4.1%) 41.8% (16.6%72.2%) 3.5% (1.7%6.9%)
Primary school 2.0% (1.3%3.1%) 2.2% (1.4%3.6%) 2.2% (1.5%3.4%) 1.0% (0.3%3.3%) 22.6% (14.3%33.7%) 5.9% (2.3%14.3%)
Secondary school 0.5% (0.3%0.8%) 3.0% (1.3%6.5%) 1.2% (0.6%2.5%) 0.0% (0.0%0.3%) 8.9% (4.9%15.4%) 1.0% (0.4%2.6%)
College 0.0% (0.0%0.2%) 1.1% (0.2%6.4%) 0.0% (0.0%0.3%) 4.3% (2.4%7.5%) 0.3% (0.1%1.2%)
Marital status
b
Never married 1.9% (0.4%9.0%) 1.1% (0.3%3.7%) 0.3% (0.1%0.9%) 1.7% (0.7%4.2%) 2.6% (0.6%11.2%)
Married 1.1% (0.9%1.4%) 2.6% (1.7%4.1%) 2.5% (1.9%3.2%) 0.7% (0.2%2.4%) 3.1% (1.9%4.9%) 1.3% (0.6%2.9%)
Divorced/widowed 4.2% (2.2%7.9%) 10.8% (7.7%15.0%) 4.8% (3.5%6.7%) 0.6% (0.3%1.4%) 18.0% (9.9%30.5%) 3.4% (2.0%5.6%)
Men With symptom-based arthritis (n= 594)
China
n= 138
Ghana
n= 170
India
n= 113
Mexico
n=15
Russian Federation
n= 117
South Africa
n=41
Age strata (years)
1829 1.0% (0.1%7.2%) 0.8% (0.1%4.5%) 2.3% (0.3%16.2%)
3039 1.7% (0.5%5.4%) 0.8% (0.2%3.8%) 5.2% (1.0%22.2%)
4049 0.8% (0.2%2.8%) 0.6% (0.1%2.5%) 1.9% (0.8%43%) 1.9% (0.2%13.4%) 1.7% (0.4%6.6%)
5059 2.3% (1.6%3.1%) 3.8% (2.7%5.4%) 2.6% (1.1%6.2%) 1.9% (0.9%4.1%) 2.3% (1.0%4.9%)
6069 3.8% (3.3%4.4%) 9.1% (6.7%12.2%) 3.5% (2.0%6.1%) 0.6% (0.2%2.2%) 6.4% (3.3%12.0%) 3.7% (1.8%7.5%)
70+ 4.3% (3.5%5.2%) 9.2% (6.9%12.3%) 4.8% (3.0%7.5%) 3.0% (1.5%5.9%) 10.7% (6.9%16.4%) 6.0% (2.4%14.3%)
Formal education
a
None 4.8% (3.3%6.8%) 5.6% (4.0%7.7%) 2.7% (1.3%5.5%) 1.5% (0.5%3.8%) 3.4% (0.3%27.7%) 4.2% (1.5%10.8%)
Primary school 1.2% (1.0%1.6%) 1.9% (1.1%3.2%) 1.2% (0.7%1.9%) 0.2% (0.1%0.6%) 10.4% (5.0%20.4%) 1.6% (0.8%3.4%)
Secondary school 1.0% (0.4%2.3%) 1.4% (0.6%3.1%) 2.0% (1.0%4.2%) 0.1% (0.0%0.5%) 3.9% (1.7%9.0%) 0.9% (0.2%5.4%)
College 0.1% (0.0%0.4%) 0.7% (0.2%2.2%) 0.4% (0.1%1.6%) 0.2% (0.0%1.4%) 1.4% (0.4%5.3%)
Marital status
b
Never married 0.9% (0.2%5.0%) 1.5% (0.2%8.8%) 1.6% (0.3%8.2%) 0.2% (0.0%0.9%) 0.8% (0.2%2.8%)
Married 1.1% (0.6%1.8%) 2.5% (1.8%3.4%) 1.8% (1.1%2.7%) 0.3% (0.1%0.5%) 3.7% (1.7%8.0%) 1.4% (0.6%3.2%)
Divorced/widowed 2.9% (1.7%4.9%) 6.5% (3.8%10.9%) 1.9% (0.6%5.5%) 0.6% (0.1%2.6%) 7.9% (2.9%19.6%) 2.9% (0.7%11.4%)
Data presented as proportions with 95% confidence intervals (95% CI)
Abbreviations:LMIC low and middle income countries, WHO World Health Organization
a
Categories of formal education are; primary school (less than primary school, or primary school completed); secondary school (secondary school completed, or
high school or its equivalent completed); college (college or pre-university completed, or post-graduate degree completed)
b
Categories of marital status are; married (currently married or cohabiting); divorced/widowed (separated or divorced, or widowed)
Brennan-Olsen et al. BMC Musculoskeletal Disorders (2017) 18:271 Page 8 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
SAGE, specifically India [30] and China [31], we now
present age-standardised prevalence across all six coun-
tries (Additional file 1: Table S1). Higher prevalence of
arthritis among individuals with lower educational at-
tainment in LMICs, may be indicative of the inextricable
link between lower education and lower-skilled, highly
manual labour. Furthermore, these findings also
replicate the association observed in higher income
countries. For instance, lower educational attainment
has been associated with the prevalence of many chronic
diseases, including self-reported arthritis (non-specific)
[32], osteoarthritis [33] and rheumatoid arthritis [34].
Our observation of higher prevalence of arthritis in indi-
viduals that were divorced, widowed or separated, may
be related to those persons also more likely to be older.
However, and whilst speculative, it may plausibly be due
to having a greater workload that cannot shared with a
partner. Should these individuals also have lower educa-
tional attainment, any job-related exposures will likely
be manual and thus with greater biomechanical stress
on the joints due to increased exposure to heavy lifting,
repetitive movements and/or squatting [35, 36].
The prevalence of musculoskeletal diseases per se in
LMICs [3] will potentially have a greater impact than in
high income countries due to the reduced capacity of
LMICs to avoid and/or alleviate the impact at individual
and national levels. This is especially pertinent given that
global NCD initiatives do not list musculoskeletal
diseases within the top four[3]. In LMICs where pain
management is less than optimal [37], the burden of
chronic, and possibly untreated, pain will be com-
pounded by social and environmental stressors that
require individuals work and fulfil community roles re-
gardless of pain. Indeed, data from a WHO collaboration
reported that between 5 and 33% of individuals in
LMICs experience chronic pain on a daily basis [38].
Similarly, we observed a sizeable proportion of
respondents to have stiffness lasting longer than 30 min
and which did not alleviate with movement; these char-
acteristics are indicative of chronic pain, and potentially
suggest inflammatory arthropathy. In addition, diseases
such as fibromyalgia are likely to cause joint pain,
however, we are unable to determine if this, and similar
issues, may have biased responses to symptomatology-
related questions. Any treatment gapis at odds with
the WHO Constitution, which recognises “…the highest
attainable standard of health as a fundamental right of
every human being[39], however, LMICs experience a
disproportionately lower likelihood of achieving that
standard. We speculate that resource-poor populations,
where informal workersare central to community
structure, are most at risk of worsening poverty levels
due to increased YLD attributable to highly prevalent,
and potentially undertreated, arthritis. It is important to
note that whilst the burden of non-communicable
diseases is increasing, there is a concurrent decline in
the burden of infectious diseases [2]. Given this, more
attention must be given to the management of diseases
such as arthritis in LMICs: action on musculoskeletal
diseases per se in LMICs present opportunities for such
action [3]. Models of care (MoC) for musculoskeletal
diseases have been developed and implemented in the
LMICs of The Philippines, Malaysia, Bangladesh and
Myanmar [40]. Despite mixed results, a four-step
process was designed to inform future development of
musculoskeletal-related MoC for implementation in
LMICs; (i) identify the scale of the problem, (ii) identify
the need, (iii) develop the action plan (including com-
munity engagement and addressing workforce capacity),
and (iv) employ a coordinated approach to implement-
ing the intervention program/MoC [40].
Despite advances in diagnosis and treatment of
arthritis during the last few decades in higher income
countries [16], these advances have not impacted on
ab
Fig. 1 Box plot presenting the direct age-standardised prevalence estimates (%) and 95% confidence intervals of self-reported arthritis diagnosis
for each of the lower to middle income countries, for women (a) and men (b)
Brennan-Olsen et al. BMC Musculoskeletal Disorders (2017) 18:271 Page 9 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
LMICs, which are primarily resource-poor. Gross
domestic product and health care expenditures per
capita are strongly correlated [14, 41]. Governments in
LMICs are constrained by competitive social, economic,
health- and poverty-related issues [7]; this frequently re-
sults in chronic diseases such as arthritis achieving lower
priority when urgent health needs are considered in an
environment with poor education, scarce resources, and
rapid population growth [7, 42]. Not only is suboptimal
access to healthcare a concern, but the cost of healthcare
may be many-fold the gross domestic product, and thus
unattainable for the majority of the population of LMICs
[5]. For many individuals and households in LMIC, there
are inadequate financial resources to manage the cost of
chronic disease, with an impoverishing effect of paying
for healthcare services out-of-pocket [43]. In order to
address the problem of out-of-pocket healthcare ex-
penses, the WHO is encouraging countries to provide
universal health coverage [7]. For LMICs the provision
of universal health coverage may be in the form of
community-based health insurance schemes, whereby
the community voluntarily raises, pools, allocates,
purchases and supervises the health financing arrange-
ment [7, 44]. Whilst there are some national efforts to
prioritise healthcare resources and achieve universal
health coverage, these schemes are likely to focus on
supporting healthcare for diseases that cause early
mortality rather than those that result in disability.
Our study has a number of strengths. The SAGE study
consists of a large multi-national cohort, and our
population for this analysis encompassed almost 45,000
participants. The integrity and coordination of these data
is overseen by WHO, in close collaboration with leading
research institutions in each of the countries, and with a
level of involvement from national health authorities
[23]. The use of a standardized survey instrument and
methods for SAGE Wave 1, the recruitment of represen-
tative samples, and the application of country-specific
weightings to calculate our prevalence estimates have
enabled comparison with similar surveys conducted in
higher income countries. In addition, the use of stan-
dardized tools to measure SEP in each of the countries
in SAGE enables us to undertake between-country com-
parisons. Our findings build on the prevalence data re-
ported by the GBD Study, whereby estimates were based
on systematic reviews of published data on incidence,
prevalence, and severity; however, for some LMICs only
limited data were available [45]. Our study also builds
on previous analyses using the SAGE dataset, as no
study to date has presented arthritis prevalence figures
across parameters of SEP.
This study also has some limitations. We acknow-
ledge that SAGE chronic disease data are self-
reported, and thus may be subject to recall bias and
potential inaccuracy with a subsequent uncertainty of
estimates. However, the self-reported arthritis ques-
tion is similar to that used for other large population
level studies, including those reported by the Centers
for Disease Control Arthritis Program in the United
States [46], and self-reported arthritis has also been
reported as a sensitive measure for public health sur-
veillance [47]. It is possible that limited access to
healthcare professionals in LMICs may lead to an
underestimation of arthritis prevalence, and those
who have arthritis but have not yet sought care may
have been missed. In addition, it may be possible that
in many countries diagnoses of arthritis may be made
by a non-medical healthcareprovider,thusintrodu-
cing some ambiguity in responses to the diagnosis
question. Yet here, the symptom-reported prevalence,
where access to healthcare professionals would be re-
moved from the equation, indicated an even lower
burden of arthritis than by self-reported diagnosis; an
issue that may also be related to diagnosed arthritis
being across the lifetime, whilst symptom-based arth-
ritis was within the previous 12 months. Our study
does not link prevalence data with disability; however
it should be noted that arthritis has highly variable
impacts on the person. A high proportion of SAGE
Wave 1 participants indicated that they had no formal
education (~50%); this may explain the level of miss-
ing data pertaining to the highest level of educational
attainmentvariable. However, missing data may also
be attributable to the WHO data collection Individual
Questionnairetool, which did not include a category
for those that had completed primary school but who
had not completed secondary school. It has been re-
ported that, in several countries, urban dwellers were
more likely to refuse to participate in SAGE [23],
which may present a bias toward rural-based participants;
however, the high proportion of rural residents may
conversely be considered a key strength of the SAGE
dataset as non-metropolitan groups are commonly
under-represented in population-based surveys. We
acknowledge that the six countries differ substantially
in terms of culture, society, and healthcare system,
and thus our pooled estimates should be considered
in this light. Finally, the response rates were relatively
low for Mexico (53%), due to a short time-frame for
data collection, although response rates for all other
countries in SAGE Wave 1 were 75% or greater, with
the exception of India at 68% [23].
Conclusions
In conclusion, we have identified a high prevalence of
arthritis in LMICs. For people living in LMIC, functional
ability and mobility is imperative to survival, and our
findings therefore have implications for prioritising
Brennan-Olsen et al. BMC Musculoskeletal Disorders (2017) 18:271 Page 10 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
healthcare resources toward arthritis prevention and
treatment in relatively resource-poor countries. It is
plausible that, especially for residents of LMICs, the high
prevalence of arthritis may limit their ability to finan-
cially and/or materially support themselves. Similarly,
poverty and lower educational attainment may predis-
pose populations to manual labour, and subsequent pre-
disposition to diseases such as osteoarthritis. Future
work will focus on occupational types and occupational
activities as risk factors for arthritis and related symp-
tomatology. Our current findings have implications for
national efforts to achieve universal health coverage and
to prioritise healthcare resources toward preventing and/
or treating arthritis.
Additional file
Additional file 1: Online Table S1. Crude and direct age-standardised
prevalence estimates (95%CI) of arthritis, stratified by sex. (DOCX 12 kb)
Abbreviations
GBD: Global burden of disease study; LMICs: Lower and middle income
countries; MoC: Models of care; NCD: Non-communicable disease;
SAGE: Study on global AGEing and adult health; SEP: Socioeconomic
position; WHO: World Health Organization; YLD: Years lived with disability
Acknowledgements
We thank the participants in each country for their contribution to the SAGE,
and acknowledge the contributions and expertise of the country-specific
investigators and their respective survey teams.
Funding
SLB-O is supported by a Career Development Fellowship from the National
Health and Medical Research Council (NHMRC) of Australia (1107510). SAGE is
supported by WHO and the Division of Behavioral and Social Research (BSR) at
the US National Institute on Aging (NIA) through Interagency Agreements
(OGHA 04034785; YA132308-CN-0020; Y1-AG-1005-01) with WHO and a
Research Project Grant R01AG034479. In addition, the governments of China
and South Africa provided financial or other support for Wave 1 of their national
studies. USAID provided additional funds in support of SAGE India to increase
the sample of women aged 1549 years as a nested study examining health in
younger women. All collaborating institutions provided substantial resources to
conduct the studies.
Availability of data and materials
The datasets used and analysed during the current study are available from
Professor Nirmala Naidoo (World Health Organization) on reasonable request.
Permission was granted to access and analyse the data in SAGE Wave 1.
Authorscontributions
Data collection and harmonization between countries: NN, PK, MM.
Conceived and designed the project: SLB-O, SC, MTL, SJB, PK, NN, INA, RSP,
SMH, JAP, MM. Analyzed the data: MM, SC, SJB. Interpreted the results: SLB-O,
SC, MTL, SJB, PK, NN, INA, RSP, SMH, JAP, MM. Wrote, edited, and approved
the final version of this manuscript: SLB-O, SC, MTL, SJB, PK, NN, INA, RSP,
SMH, JAP, MM.
Competing interests
None of the authors have any relevant conflicts of interest related to the
work under consideration for publication. SLB-O has received speaker fees
from Amgen. RSP has received institutional support from De Puy-Synthesis
for educational/training purposes.
Consent for publication
Not applicable.
Ethics approval and consent to participate
This research was performed in accordance with the Declaration of Helsinki.
The WHO and the respective implementing agency in each country
provided ethics approvals. Written, informed consent was obtained from all
participants.
PublishersNote
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
Author details
1
Deakin University, Geelong, Australia.
2
Australian Institute for
Musculoskeletal Science (AIMSS), The University of Melbourne-Western
Precinct, Level 3, Western Centre for Health Research and Education
(WCHRE) Building, C/- Sunshine Hospital, Furlong Road, St Albans,
Melbourne, VIC 3021, Australia.
3
Department of Medicine-Western Health,
Melbourne Medical School, The University of Melbourne, Melbourne,
Australia.
4
Institute of Health and Ageing, Australian Catholic University,
Melbourne, Australia.
5
Faculty of Medicine, Nursing and Health Sciences,
Monash University, Melbourne, Australia.
6
Department of Health Statistics
and Information Systems, World Health Organization, Geneva, Switzerland.
7
Research Centre for Generational Health and Ageing, University of
Newcastle, Newcastle, Australia.
8
Department of Epidemiology and
Preventive Medicine, Monash University, Melbourne, Australia.
9
Barwon
Centre for Orthopaedic Research and Education, Barwon Health, Geelong,
Australia.
Received: 31 March 2017 Accepted: 9 June 2017
References
1. Briggs AM, Cross MJ, Hoy DG, et al. 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(S2):S23455.
2. Global Burden of Disease Collaborators. Global, regional, and national
incidence, prevalence, and years lived with disability for 301 acute and
chronic diseases and injuries in 188 countries, 19902013: a systematic
analysis for the Global Burden of Disease Study 2013. Lancet. 2015;
386(9995):743800.
3. Hoy D, Geere JA, Davatchi F, et al. A time for action: opportunities for
preventing the growing burden and disability from musucloskeletal
conditions in low- and middle-income countries. Best Pract Res Clin
Rheumatol. 2014;28(3):37793.
4. Vos T, Flaxman AD, Naghavi M, et al. Years lived with disability (YLDs) for
1160 sequelae of 289 diseases and injuries 1990-2010: a systematic analysis
for the global burden of disease study. Lancet. 2012;380:216396.
5. Woolf AD, Brooks P, Akesson K, et al. Prevention of musculoskeletal
conditions in the developing world. Best Pract Res Clin Rheumatol. 2008;
22(4):75972.
6. Rudan I, Sidhu S, Papana A, et al. Prevalence of rheumatoid arthritis in low-
and middle-income countries: a systematic review and analysis. J Glob
Health. 2015;5(1):010409.
7. Adebayo EF, Uthman OA, Wiysonge CS, et al. A systematic review of factors
that affect uptake of community-based health insurance in low-income and
middle-income countries. BMC Health Serv Res. 2015;15:543.
8. Lenssinck M-LB, Burdorf A, Boonen A, et al. Consequences of inflammatory
arthritis for workplace productivity loss and sick leave: a systematic review.
Ann Rheum Dis. 2013;72:493505.
9. Agoliotis M, Fransen M, Bridgett L, et al. Risk factors associated with
reduced work productivity among people with chronic knee pain.
Osteoarthr Cart. 2013;21(9):11609.
10. United Nations. Prevention and control of non-communicable diseases: report
of the secretary-general. New York, United Nations: United Nations; 2011.
11. Sokka T, Kautiainen H, Pincus R, et al. Disparities in rheumatoid arthritis
disease activity according to gross domestic product in 25 countries in the
QUEST-RA database. Ann Rheum Dis. 2009;68:166672.
12. Jonsson B, Kobelt G, Smolen J. The burden of rheumatoid arthritis and
access to treatment: uptake of new therapies. Eur J Health Econ. 2008;
(Suppl 2):S6186.
Brennan-Olsen et al. BMC Musculoskeletal Disorders (2017) 18:271 Page 11 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
13. Woolf AD, Pfleger B. Burden of major musculoskeletal conditions. Bull World
Health Organ. 2003;81:64656.
14. Pabinger C, Geissler A. Utilization rates of hip arthroplasty in OECD
countries. Osteoarthr Cart. 2014;22(6):73441.
15. Sokka T, Kautiainen H, Pincus R, et al. Work disability remains a major
problem in rheumatoid arthritis in the 2000s: data from 32 countries in the
QUEST-RA study. Arthrit Res Ther. 2010;12:R42.
16. Storheim K, Zwart J-A. Musculoskeletal disorders and the global burden of
disease study. Ann Rheum Dis. 2014;73:94950.
17. Chopra A, Abdel-Nasser A. Epidemiology of rheumatoid musculoskeletal disorders
in the developing world. Best Pract Res Clin Rheumatol. 2008;22:583604.
18. Hosseinpoor AR, Bergen N, Mendis S, et al. Socioeconomic inequality in the
prevalence of noncommunicable diseases in low- and middle-income
countries: results from the world health survey. BMC Public Health. 2012;12:474.
19. Kumar B. Global health inequities in rheumatology. Rheumatol. 2016; Online
First March 24.
20. Arokiasamy P, Uttamacharya, Kowal P, et al. Chronic noncommunicable
diseases in 6 low- and middle-income countries: findings from wave 1 of
the World Health Organization's study on global Ageing and adult health
(SAGE). Am J Epidemiol. 2017; 185(6):414-428.
21. Bloom DE, Chatterji S, Kowal P, et al. Macroeconomic implications of population
ageing and selected policy responses. Lancet. 2015;385(9968):64957.
22. Chatterji S. World Health Organization's (WHO) study global AGEing and
adult health (SAGE). BMC Proc. 2013;7(Suppl 4):S1.
23. Kowal P, Chatterji S, Naidoo N, et al. Data resource profile: the World Health
Organization study on global AGEing and adult health (SAGE). Int J
Epidemiol. 2012;41(6):163949.
24. UNESCO. International Standard Classification of Education: ISCED. 1997:
2006.
25. Esteve J, Benhamou E, Raymond L. Statistical methods in cancer research.
Volume IV. Descriptive epidemiology. IARC Sci Publ. 1994;128:1302.
26. Ahmad OB, Boschi-Pinto C, Lopez AD, et al. Age standardization of rates: a
new WHO standard. Geneva, Switzerland: WHO; 2001.
27. Cross M, Smith E, Hoy D, et al. The global burden of rheumatoid arthritis:
estimates from the Global Burden of Disease 2010 study. Ann Rheum Dis.
2014; Online First(Feb 18).
28. Ackerman IN, Bucknill A, Page RS, et al. The substantial personal burden
experienced by younger people with hip or knee osteoarthritis. Osteoarthr
Cart. 2015;23(8):127684.
29. Ackerman I, Kemp JL, Crossley KM, et al. Hip and knee osteoarthritis affects
younger people too. J Orthop Sports Phys Ther. 2017;47(2):6779.
30. Basu S, King AC. Disability and chronic disease among older adults in India:
detecting vulnerable populations through the WHO SAGE study. Amer J
Epidemiol. 2013;178(11):16208.
31. Wu F, Guo Y, Kowal P, et al. Prevalence of major chronic conditions among
older Chinese adults: the study on global AGEing and adult health (SAGE)
wave 1. PLoS One. 2013;8(9):e74176.
32. Brennan SL, Turrell G. Neighborhood disadvantage, individual-level
socioeconomic position, and self-reported chronic arthritis: a cross-sectional
multilevel study. Arthrit Care Res. 2012;64(5):7218.
33. Hannan MT, Anderson JJ, Pincus T, et al. Educational attainment and
osteoarthritis: differential associations with radiographic changes and
symptom reporting. J Clin Epidemiol. 1992;45(2):13947.
34. Bengtsson C, Nordmark B, Klareskog L, et al. Socioeconomic status and the
risk of developing rheumatoid arthritis: results from the Swedish EIRA study.
Ann Rheum Dis. 2005;64:158894.
35. Kirkhorn S, Greenlee RT, Reeser JC. The epidemiology of agriculture-related
osteoarthritis and its impact on occupational disability. Wisconsin Med J.
2003;102(7):3844.
36. Andersen S, Caspar-Thygesen L, Davidsen M, et al. Cumulative years in
occupation and the risk of hip or knee osteoarthritis in men and women: a
register-based follow-up study. Occup Environ Med. 2012;69:32530.
37. Bond M. Pain education issues in developing countries and responses to
them by the International Association for the Study of Pain. Pain Res
Manage. 2011;16(6):4046.
38. Gureje O, Von Korff M, Simon GE, et al. Persistent pain and well-being: a
World Health Organization study in primary care. JAMA. 1998;280:14751.
39. WHO. Health and human rights. Geneva, Switzerland: WHo; 2015.
40. Lim KK, Chan M, Navarra S, et al. Development and implementation of
models of care for musculoskeletal conditions in middle-income and low-
income Asian countries. Best Pract Res Clin Rheumatol. 2016;30:398419.
41. Putrik P, Ramiro S, Keszei AP, et al. Lower education and living in countries
with lower wealth are associated with higher disease activity in rheumatoid
arthritis: results from the multinational COMORA study. Ann Rheum Dis.
2016; 75(3):54046.
42. Mody GM, Cardiel MH. Challenges in the management of rheumatoid arthritis
in developing countries. Best Pract Res Clin Rheumatol. 2008;22(4):62141.
43. Xu K, Evans DB, Kawabata K, et al. Household catastrophic health
expenditure: a multicountry analysis. Lancet. 2003;362:1117.
44. Hsiao WC. Experience of community health financing in the Asian Region.
In: Preker AS, Currin G, editors. Health financing for poor people: resource
mobilization and risk sharing. Washington: World Bank; 2004. p. 119.
45. WHO. World Report on Disability 2011; Technical Appendix D, Global
Burden of Disease Methodology. Geneva: World Health Organization; 2011.
46. Helmick CG, Felson DT, Lawrence RC, et al. Estimates of the prevalence of
arthritis and other rheumatic conditions in the United States. Arthrit Rheum.
2008;58(1):1525.
47. Sacks JJ, Harrold LR, Hemick CG, et al. Validation of a surveillance case
definition for arthritis. J Rheumatol. 2005;32:3407.
We accept pre-submission inquiries
Our selector tool helps you to find the most relevant journal
We provide round the clock customer support
Convenient online submission
Thorough peer review
Inclusion in PubMed and all major indexing services
Maximum visibility for your research
Submit your manuscript at
www.biomedcentral.com/submit
Submit your next manuscript to BioMed Central
and we will help you at every step:
Brennan-Olsen et al. BMC Musculoskeletal Disorders (2017) 18:271 Page 12 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”), for small-
scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are maintained. By
accessing, sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of use (“Terms”). For these
purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal
subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription
(to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will
apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within
ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not
otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as
detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that Users may
not:
use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access
control;
use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is
otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association unless explicitly agreed to by Springer Nature in
writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal
content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue,
royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal
content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any
other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not obligated to publish any information or
content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature
may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied
with respect to the Springer nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law,
including merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed
from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not
expressly permitted by these Terms, please contact Springer Nature at
onlineservice@springernature.com
... Criteria for the diagnosis of diabetes mellitus were a fasting glucose concentration of ≥ 7.0 mmol/L or a self-reported history of physician diagnosis of diabetes mellitus or a history of drug treatment for diabetes (insulin or oral hypoglycemic agents). Depression was assessed by applying the Center for Epidemiologic Studies Depression Scale (CES-D) Scoresheet 15 . The estimated glomerular filtration rate (eGFR) was calculated using the chronic kidney disease (CKD) Epidemiology Collaboration (CKD-EPI) equation 26 . ...
... UVOS the Chuvashians formed 49/1525 or 3.2% of the study population and had an OA prevalence of 32.7%, with no significant difference in the OA prevalence as compared with the rest of the study populations. The figures of our study populations compare well with the data obtained from the SAGE study with a self-reported OA prevalence of 38% for men and of 17% for women in Russia with an age of ≥ 50 years 15 . Factors associated with a higher OA prevalence were female sex in the UEMS and in the UVOS, a higher BMI and previous bone fractures in the UEMS. ...
Article
Full-text available
To determine the prevalence of osteoarthritis and its associated factors in populations from Russia. The population-based Ural Eye and Medical Study (UEMS) and the population-based Ural Very Old Study (UVOS) were conducted in a rural and urban region in Bashkortostan/Russia and included participants aged 40+ and 85+ years, respectively. As part of a detailed systematic examination, we assessed the osteoarthritis prevalence in an interview including questions on the self-reported presence of osteoarthritis, the joints affected and osteoarthritis-related pain-relieving therapy taken. Out of 5898 participants of the UEMS, 1636 individuals had osteoarthritis [prevalence: 27.7%; 95% confidence interval (CI) 26.7, 28.7], with 816 individuals (13.8%; 95% CI 12.8, 14.8) taking pain-relieving medication. A higher osteoarthritis prevalence was associated (multivariable analysis) with older age [odds ratio (OR 1.04; 95% confidence interval (CI) 1.03, 1.05], urban region of residence (OR 1.25; 95% CI 1.07, 1.45), higher body mass index (BMI) (OR 1.04; 95% CI 1.03, 1.06), lower monthly income (OR 0.78; 95% CI 0.68, 0.90), higher physical activity score (OR 1.02, 95% CI 1.01, 1.03), higher prevalence of a history of cardiovascular disease including stroke (OR 1.55; 95% CI 1.33, 1.81), previous bone fractures (OR 1.20; 95% CI 1.04, 1.40) and previous falls (OR 1.22; 95% CI 1.03, 1.45), higher hearing loss score (OR 1.01; 95% CI 1.01, 1.02), and less alcohol consumption (OR 0.78; 95% CI 0.65, 0.93). Out of 1526 UVOS participants, 567 individuals had osteoarthritis (prevalence: 37.2%; 95% CI 35.0, 40.0), with 195 (12.8%; 95% CI 11.3, 14.3) individuals taking pain-relieving medication. Higher osteoarthritis prevalence was associated with rural region of habitation (OR 1.69; 95% CI 1.20, 2.38), lower monthly income (OR 0.62; 95% CI 0.46, 0.84), higher prevalence of cardiovascular disease (OR 1.75; 95% CI 1.30, 2.36), and higher anxiety score (OR 1.04; 95% CI 1.03, 1.06). Osteoarthritis and use of pain-relieving medication are common in these populations in Russia. Main associated factors were older age and lower monthly income in both study populations, female sex, higher BMI, urban region, and previous falls and bone fractures in the UEMS population, and rural region and a higher anxiety score in the UVOS study population.
... These complaints are a major source of disability and loss of working time in various industries in developing countries. The World Health Organization (WHO) claims that workers' pain complaints contribute to life-long disability and promote various preventive measures [3]. ...
... In an American survey conducted between 2013 and 2015, 18.1% of males and 23.5% of females suffered from arthritis [40]. In a survey of arthritis in low-to middleincome countries, Russia had the highest rate of arthritis in the past year: 32.9% among males and 48.4% among females [41]. Comparison with these previous studies suggests that the high prevalence of arthritis in the Tsarang population may be a major public health problem. ...
Article
Full-text available
Background In Tsarang (at 3560 m), which is located in Mustang, 62.7% of the residents answered that they had a subjective medical history of arthritis, and 41.1% of the residents answered that their families had a subjective medical history of arthritis on a survey conducted in 2017. The expression of hypoxia-inducible factor (HIF) and its effects are deeply involved in hypoxic adaptation in Tibetan highlanders. At the same time, HIF is also related to the onset of rheumatoid arthritis. Therefore, the adaptive mechanism acquired by Tibetan highlanders may promote the development of rheumatoid arthritis. The prevalence of rheumatoid arthritis is estimated to be approximately 0.5–1.0% worldwide. The objective of this study was to estimate the prevalence of rheumatoid arthritis in Tsarang residents using existing diagnostic criteria and to explore its risk factors. Methods An epidemiological survey was conducted in Tsarang in 2019. Data obtained from anthropometry and questionnaires were statistically analyzed. Biochemical measurements using blood samples were also performed, and the results were used to assess arthritis status. Residents’ joint status was scored, and arthritis was assessed based on the clinical disease activity index and ACR/EULAR 2010 criteria. Results Twenty-seven males and 50 females participated in this survey. In Tsarang, ACR/EULAR 2010 classified 4.3% of males and 7.1% of females as having rheumatoid arthritis, indicating a very high estimated prevalence. We also performed a multivariate analysis to explore its risk factors, and two factors, older age (standardized parameter estimate = 4.84E−01, 95% CI = [9.19E−02, 8.76E−01], p = 0.0170) and a history of living in urban areas (standardized parameter estimate = − 5.49E−01, 95% CI = [− 9.21E−01, 1.77E−01], p = 0.0050), significantly contributed to the higher ACR/EULAR 2010 score in females. In addition, three factors, having no spouse (standardized parameter estimate = 3.17E−01, 95% CI = [5.74E−02, 5.77E−01], p = 0.0179), having a smoking habit (standardized parameter estimate = 2.88E−01, 95% CI = [1.71E−02, 5.59E−01], p = 0.0377), and a history of living in urban areas (standardized parameter estimate = − 3.69E−01, 95% CI = [− 6.83E−01, − 5.60E−02], p = 0.0219), resulted in significantly higher clinical disease activity index scores in females. Furthermore, smoking habits were found to significantly increase blood hyaluronic acid in both males (standardized parameter estimate = 6.03E−01, 95% CI = [3.06E−01, 9.01E−01], p = 0.0020) and females (standardized parameter estimate = 4.87E−01, 95% CI = [5.63E−02, 9.18E−01], p = 0.0291). Conclusions In this study, we evaluated the symptoms of arthritis and estimated the prevalence of rheumatoid arthritis using classification criteria for Tibetan highlanders who have adapted to the hypoxic environment and fostered their own culture. The high prevalence of rheumatoid arthritis among Tsarang residents suggests that the hypoxic adaptation mechanism involving HIF in Tibetan highlanders may promote the onset or exacerbation of rheumatoid arthritis. The high prevalence of rheumatoid arthritis among Tibetan highlanders may be related not only to the environmental factors analyzed in this study but also to hypoxic adaptation genes. Further investigation is needed to clarify the genetic factors involved.
... Moreover, risk factors of MSD and their changes over time have mainly been studied individually or by family (eg, biomechanical, organizational, psychosocial), but a global view of their simultaneous change over time is still lacking. Disentangling the respective roles of age and temporal evolution in exposure to risk factors on the occurrence of MSD is thus needed to understand current trends and design adapted prevention policies (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14). Furthermore, understanding the evolution of exposures over time while accounting for age would allow for more accurate prediction of future trends in MSD and help to prevent and control their occurrence (15,16). ...
Article
Full-text available
Objectives: Musculoskeletal disorders (MSD) represent a major public health issue, affecting more then 40 million European workers in 2017. The overall aging of the working population is expected to increase the burden of disease, but temporal changes in exposures or diagnosis may also drive the global trends in MSD. We therefore conducted a systematic review to summarize the evidence on the role of demographic and temporal changes in the occurrence of MSD. Methods: We conducted a systematic review of articles reporting temporal trends in MSD in the general working-age population. Only articles controlling for age in the analysis were included. The risk of bias was assessed. The main indicators extracted were age-controlled time trends in MSD incidence or prevalence. Results: Among 966 articles, 16 fulfilled the inclusion criteria, representing 23 results according to the indicators extracted. No study was found with a high risk of bias. Results presenting time trends in prevalence were found in 12 studies and incidence in 11. After controlling for age, the reported temporal trends varied, mostly between non-monotonic changes (N=12/23) and increases (N=10/23). One article also highlighted an increase among women and non-monotonic changes among men (N=1/23). Several factors other than aging were suggested to explain temporal trends in MSD, mainly trends in obesity, changing occupational exposures, and cultural factors regarding pain tolerance. Conclusion: This review shows that different kind of factors in addition to aging may contribute to varying or increasing trends in MSD. This review also highlighted the scarcity of evidence regarding time trends in the burden of MSD and their underlying causes.
... These conditions tend to be more frequent and disabling in socially disadvantaged groups. [6][7][8][9][10] The need to systematically scale up and implement 'high-value' interventions and models of care is a priority 11-13 and is a specific component of the national strategic framework recently published by Public Health England, NHS England and Versus Arthritis. 14 However, within this framework there must be due regard to health inequalities. ...
Article
Full-text available
Background: It is unclear whether seven interventions recommended by Public Health England for preventing and managing common musculoskeletal conditions reduce or widen health inequalities in adults with musculoskeletal conditions. Methods: We used citation searches of Web of Science (date of 'parent publication' for each intervention to April 2021) to identify original research articles reporting subgroup or moderator analyses of intervention effects by social stratifiers defined using the PROGRESS-Plus frameworks. Randomized controlled trials, controlled before-after studies, interrupted time series, systematic reviews presenting subgroup/stratified analyses or meta-regressions, individual participant data meta-analyses and modelling studies were eligible. Two reviewers independently assessed the credibility of effect moderation claims using Instrument to assess the Credibility of Effect Moderation Analyses. A narrative approach to synthesis was used (PROSPERO registration number: CRD42019140018). Results: Of 1480 potentially relevant studies, seven eligible analyses of single trials and five meta-analyses were included. Among these, we found eight claims of potential differential effectiveness according to social characteristics, but none that were judged to have high credibility. Conclusions: In the absence of highly credible evidence of differential effectiveness in different social groups, and given ongoing national implementation, equity concerns may be best served by investing in monitoring and action aimed at ensuring fair access to these interventions.
... Poverty is not only the lack of sustainable income for basic necessities (food, shelter, education, healthcare), it also refers to limited capacity to participate effectively in society, and importantly, it may lead to social discrimination and exclusion from participation in decision-making (2). Osteoarthritis is thought to impose a greater burden for those living in low-and middle-income countries (LMICs) by creating a vicious cycle of pain and disability that subsequently worsens these outcomes (3). The global prevalence of hip and knee osteoarthritis is estimated at 3754.2 per 100,000 population (4). ...
Article
Full-text available
The “Joint Effort Initiative” (JEI) is an international consortium of clinicians, researchers, and consumers under the auspices of the Osteoarthritis Research Society International (OARSI). The JEI was formed with a vision to improve the implementation of coordinated programs of best evidence osteoarthritis care globally. To better understand some of the issues around osteoarthritis care in low- and middle-income countries (LMICs), the JEI invited clinician researcher representatives from South Africa, Brazil, and Nepal to discuss their perspectives on challenges and opportunities to implementing best-evidence osteoarthritis care at the OARSI World Pre-Congress Workshop. We summarize and discuss the main themes of the presentations in this paper. The challenges to implementing evidence-based osteoarthritis care identified in LMICs include health inequities, unaffordability of osteoarthritis management and the failure to recognize osteoarthritis as an important disease. Fragmented healthcare services and a lack of health professional knowledge and skills are also important factors affecting osteoarthritis care in LMICs. We discuss considerations for developing strategies to improve osteoarthritis care in LMICs. Existing opportunities may be leveraged to facilitate the implementation of best-evidence osteoarthritis care. We also discuss strategies to support the implementation, such as the provision of high-quality healthcare professional and consumer education, and systemic healthcare reforms.
Article
Arthritis and prosthetic joint infections (PJIs) overall are associated with reduced quality of life and limited work capacity. Multiple, overlapping factors contribute to these conditions. Some investigations have suggested a dysbiotic association between the oral‐gut microbiome and pathogenesis of arthritis and PJIs. A better understanding of the role of the oral‐gut microbiota in arthritis and PJI pathophysiology can shed light into how its disequilibrium can discharge a pro‐inflammatory response, and impact the health of patients susceptible to arthritis or with established joint disease. A review of published in vivo and clinical data suggested that alterations in oral and gut microbiota can lead to a disturbance of immunoregulatory properties, and may be associated with joint infections and arthritis. This review brings new insights into the current status of the evidence on the potential molecules and inflammatory biomarkers disrupted by an oral‐gut microbial dysbiosis. Normal commensals and pathogenic oral and gut microflora homeostasis are important not only to prevent infections per se but also its potential progression. Further experiments, especially controlled clinical trials, are needed to ascertain how microbiome manipulation and other microbiota‐directed approaches can help control inflammation and effectively prevent and treat arthritic diseases. Additionally, studies on the effects of the long‐term oral diseases, such as chronic periodontitis, on arthritis and PJIs need to be conducted.
Article
Improving the health and well-being of people with osteoarthritis (OA) requires effective action beyond health service delivery. Integration of the different contexts and settings in which people live, work, and socialize, also known as the social determinants of health (SDH), with health care has the potential to provide additional benefits to health and well-being outcomes compared with traditional OA care. This article explores how SDH can impact the lives of people with OA, how SDH intersect at different stages of OA progression, and opportunities for integrating SDH factors to address the onset and management of OA across the life course.
Article
Nanocellulose (NC)-based materials constitute a new class of bio-based building blocks that are inspiring advances for the next generation of high-performance sustainable materials. However, NC exhibits important drawbacks that should...
Thesis
Full-text available
The health workforce is a critical part of developing responsive health systems that address routine population health needs and respond to health emergencies. However, defective planning has resulted in underinvestment and a looming shortage of about 18 million health workers globally. The empirical literature demonstrates substantial lacunae in existing health workforce planning models. Most models focus on one side of either supply or number needed, and even where there is an attempt to integrate them, the need component is often not linked to the population’s need for health services. The need-based framework combines the population’s health status, planned or otherwise necessary services, and professional standards of service delivery to estimate the health workers needed for a given population. Despite its intuitive appeal, several methodological gaps, and lack of open-access tools, have limited its use for planning in most countries, including Ghana. To address this gap and to contribute to knowledge in the field of health professions education, a need-based model for planning health professions education and employment in Ghana’s primary healthcare context was developed and empirically applied. Leaning on the pragmatic research paradigm, this study adopted a sequential multi-method approach. In the first phase, this study conducted a systematic scoping review of empirical applications of the need-based health workforce planning approach to identify the key methodological gaps, from which six critical methodological considerations were synthesised. The second phase involved model development. Building on the synthesised evidence, a conceptual and empirical comprehensive need-based health workforce model was developed with an accompanying open-access Microsoft® Excel-based model. In the third phase, a cross-sectional survey was conducted amongst a nationally representative sample of health professionals to establish professional standards of service delivery (which is a proxy measure of productivity) that would be incorporated into the need-based analysis. In the final phase, data was triangulated from multiple sources to systematically apply the model to forecast the needs and supply of 11 health professionals in Ghana’s primary health care context. The model application showed a significant gap between the needs of the population and that of the supply of health care professionals in Ghana. The need-based shortage was 73,203 health professionals across 11 professions, which could reach 161,502 health professionals by 2035. Regarding education and employment of health professionals for primary health care in Ghana, averting an existing 33% shortage would require, among others, increasing the intake of pharmacy technicians by 7.5-fold, general practitioners by 100%, and general nurses by 55%, whilst scaling down that of midwives by 15%. At least US$480.39 million investments from both the public and private sectors would be required in health professions education while planning for US$1.762 billion per annum (up to US$2.374 billion in 2035) in terms of the wage bill to maintain jobs and employ those to be trained. Linking the population’s health needs to health professions education curricula and testing the economic feasibility of the need-based health workforce estimates are areas that may warrant further research.
Article
Full-text available
In this paper, we examine patterns of self-reported diagnosis of noncommunicable diseases (NCDs) and prevalences of algorithm/measured test-based, undiagnosed, and untreated NCDs in China, Ghana, India, Mexico, Russia, and South Africa. Nationally representative samples of older adults aged ≥50 years were analyzed from wave 1 of the World Health Organization's Study on Global Ageing and Adult Health (2007–2010; n = 34,149). Analyses focused on 6 conditions: angina, arthritis, asthma, chronic lung disease, depression, and hypertension. Outcomes for these NCDs were: 1) self-reported disease, 2) algorithm/measured test-based disease, 3) undiagnosed disease, and 4) untreated disease. Algorithm/measured test-based prevalence of NCDs was much higher than self-reported prevalence in all 6 countries, indicating underestimation of NCD prevalence in low- and middle-income countries. Undiagnosed prevalence of NCDs was highest for hypertension, ranging from 19.7% (95% confidence interval (CI): 18.1, 21.3) in India to 49.6% (95% CI: 46.2, 53.0) in South Africa. The proportion untreated among all diseases was highest for depression, ranging from 69.5% (95% CI: 57.1, 81.9) in South Africa to 93.2% (95% CI: 90.1, 95.7) in India. Higher levels of education and wealth significantly reduced the odds of an undiagnosed condition and untreated morbidity. A high prevalence of undiagnosed NCDs and an even higher proportion of untreated NCDs highlights the inadequacies in diagnosis and management of NCDs in local health-care systems.
Article
Full-text available
Low-income and middle-income countries (LMICs) have difficulties achieving universal financial protection, which is primordial for universal health coverage. A promising avenue to provide universal financial protection for the informal sector and the rural populace is community-based health insurance (CBHI). We systematically assessed and synthesised factors associated with CBHI enrolment in LMICs. We searched PubMed, Scopus, ERIC, PsychInfo, Africa-Wide Information, Academic Search Premier, Business Source Premier, WHOLIS, CINAHL, Cochrane Library, conference proceedings, and reference lists for eligible studies available by 31 October 2013; regardless of publication status. We included both quantitative and qualitative studies in the review. Both quantitative and qualitative studies demonstrated low levels of income and lack of financial resources as major factors affecting enrolment. Also, poor healthcare quality (including stock-outs of drugs and medical supplies, poor healthcare worker attitudes, and long waiting times) was found to be associated with low CBHI coverage. Trust in both the CBHI scheme and healthcare providers were also found to affect enrolment. Educational attainment (less educated are willing to pay less than highly educated), sex (men are willing to pay more than women), age (younger are willing to pay more than older individuals), and household size (larger households are willing to pay more than households with fewer members) also influenced CBHI enrolment. In LMICs, while CBHI schemes may be helpful in the short term to address the issue of improving the rural population and informal workers' access to health services, they still face challenges. Lack of funds, poor quality of care, and lack of trust are major reasons for low CBHI coverage in LMICs. If CBHI schemes are to serve as a means to providing access to health services, at least in the short term, then attention should be paid to the issues that militate against their success.
Article
Full-text available
Background: Up-to-date evidence about levels and trends in disease and injury incidence, prevalence, and years lived with disability (YLDs) is an essential input into global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013), we estimated these quantities for acute and chronic diseases and injuries for 188 countries between 1990 and 2013. Methods: Estimates were calculated for disease and injury incidence, prevalence, and YLDs using GBD 2010 methods with some important refinements. Results for incidence of acute disorders and prevalence of chronic disorders are new additions to the analysis. Key improvements include expansion to the cause and sequelae list, updated systematic reviews, use of detailed injury codes, improvements to the Bayesian meta-regression method (DisMod-MR), and use of severity splits for various causes. An index of data representativeness, showing data availability, was calculated for each cause and impairment during three periods globally and at the country level for 2013. In total, 35 620 distinct sources of data were used and documented to calculated estimates for 301 diseases and injuries and 2337 sequelae. The comorbidity simulation provides estimates for the number of sequelae, concurrently, by individuals by country, year, age, and sex. Disability weights were updated with the addition of new population-based survey data from four countries. Findings: Disease and injury were highly prevalent; only a small fraction of individuals had no sequelae. Comorbidity rose substantially with age and in absolute terms from 1990 to 2013. Incidence of acute sequelae were predominantly infectious diseases and short-term injuries, with over 2 billion cases of upper respiratory infections and diarrhoeal disease episodes in 2013, with the notable exception of tooth pain due to permanent caries with more than 200 million incident cases in 2013. Conversely, leading chronic sequelae were largely attributable to non-communicable diseases, with prevalence estimates for asymptomatic permanent caries and tension-type headache of 2·4 billion and 1·6 billion, respectively. The distribution of the number of sequelae in populations varied widely across regions, with an expected relation between age and disease prevalence. YLDs for both sexes increased from 537·6 million in 1990 to 764·8 million in 2013 due to population growth and ageing, whereas the age-standardised rate decreased little from 114·87 per 1000 people to 110·31 per 1000 people between 1990 and 2013. Leading causes of YLDs included low back pain and major depressive disorder among the top ten causes of YLDs in every country. YLD rates per person, by major cause groups, indicated the main drivers of increases were due to musculoskeletal, mental, and substance use disorders, neurological disorders, and chronic respiratory diseases; however HIV/AIDS was a notable driver of increasing YLDs in sub-Saharan Africa. Also, the proportion of disability-adjusted life years due to YLDs increased globally from 21·1% in 1990 to 31·2% in 2013. Interpretation: Ageing of the world's population is leading to a substantial increase in the numbers of individuals with sequelae of diseases and injuries. Rates of YLDs are declining much more slowly than mortality rates. The non-fatal dimensions of disease and injury will require more and more attention from health systems. The transition to non-fatal outcomes as the dominant source of burden of disease is occurring rapidly outside of sub-Saharan Africa. Our results can guide future health initiatives through examination of epidemiological trends and a better understanding of variation across countries.
Article
Although osteoarthritis (OA) has traditionally been considered a disease of older age, hip and knee OA can and does affect younger adults, with a profound impact on psychosocial well-being and work capacity. Obesity and a history of traumatic knee injury (eg, anterior cruciate ligament rupture and/or meniscal tear) are key risk factors for the accelerated development of knee OA, while structural hip deformities (including those contributing to femoroacetabular impingement syndrome) are strong predictors of early-onset hip OA. In view of these associations, rising rates of obesity and sports injuries are concerning, and may signal a future surge in OA incidence among younger people. Assessment of hip and knee OA in younger people should focus on a patient-centered history, comprehensive physical examination, performance-based measures, and patient-reported outcome measures to enable monitoring of symptoms and function over time. Referral for imaging should be reserved for people presenting with atypical signs or symptoms that may indicate diagnoses other than OA. Nonpharmacological approaches are core strategies for the management of hip and knee OA in younger people, and these include appropriate disease-related education, activity modification (including for work-related tasks), physical therapist- prescribed exercise programs to address identified physical impairments, and weight control or weight loss. High-quality evidence has shown no benefit of arthroscopy for knee OA, and there are no published clinical trials to support the use of hip arthroscopy for OA. Referral for joint-conserving or joint replacement surgery should be considered when nonpharmacological and pharmacological management strategies are no longer effective.
Article
This chapter discusses the challenges faced in the development and implementation of musculoskeletal (MSK) Models of Care (MoCs) in middle-income and low-income countries in Asia and outlines the components of an effective MoC for MSK conditions. Case studies of four such countries (The Philippines, Malaysia, Bangladesh and Myanmar) are presented, and their unique implementation issues are discussed. The success experienced in one high-income country (Singapore) is also described as a comparison. The Community Oriented Program for Control of Rheumatic Diseases (COPCORD) project and the role of Asia Pacific League of Associations for Rheumatology (APLAR), a professional body supporting MoC initiatives in this region, are also discussed. The experience and lessons learned from these case studies can provide useful information to guide the implementation of future MSK MoC initiatives in other middle-income and low-income countries.
Article
Persistent pain, impaired mobility and function, and reduced quality of life and mental well-being are the most common experiences associated with musculoskeletal conditions, of which there are more than 150 types. The prevalence and impact of musculoskeletal conditions increase with aging. A profound burden of musculoskeletal disease exists in developed and developing nations. Notably, this burden far exceeds service capacity. Population growth, aging, and sedentary lifestyles, particularly in developing countries, will create a crisis for population health that requires a multisystem response with musculoskeletal health services as a critical component. Globally, there is an emphasis on maintaining an active lifestyle to reduce the impacts of obesity, cardiovascular conditions, cancer, osteoporosis, and diabetes in older people. Painful musculoskeletal conditions, however, profoundly limit the ability of people to make these lifestyle changes. A strong relationship exists between painful musculoskeletal conditions and a reduced capacity to engage in physical activity resulting in functional decline, frailty, reduced well-being, and loss of independence. Multilevel strategies and approaches to care that adopt a whole person approach are needed to address the impact of impaired musculoskeletal health and its sequelae. Effective strategies are available to address the impact of musculoskeletal conditions; some are of low cost (e.g., primary care-based interventions) but others are expensive and, as such, are usually only feasible for developed nations. In developing nations, it is crucial that any reform or development initiatives, including research, must adhere to the principles of development effectiveness to avoid doing harm to the health systems in these settings.
Article
To compare Health-Related Quality of Life (HRQoL) and psychological distress in younger people with hip or knee osteoarthritis (OA) to age- and sex-matched population norms, and evaluate work limitations in this group. People aged 20-55 years with hip or knee OA were recruited from major hospitals (n=126) and community advertisements (n=21). HRQoL was assessed using the Assessment of Quality of Life (AQoL) instrument (minimal important difference 0.06 AQoL units) and compared to population norms. Psychological distress was assessed using the Kessler Psychological Distress Scale (K10) and the prevalence of high/very high distress (K10 score ≥22) was compared to Australian population data. Work limitations were evaluated using the Workplace Activity Limitations Scale (WALS). Considering most participants had a relatively recent OA diagnosis (<5 years), the extent of HRQoL impairment was unexpected. A very large reduction in HRQoL was evident for the overall sample, compared with population norms (mean difference -0.35 AQoL units, 95%CI -0.40 to -0.31). Females, people aged 40-49 years, and those with hip OA reported average HRQoL impairment of almost 40% (mean reductions -0.38 to -0.39 AQoL units). The overall prevalence of high/very high distress was 4 times higher than for the population (relative risk 4.19, 95%CI 3.53-4.98) and 67% reported moderate to considerable OA-related work disability, according to WALS scores. These results clearly demonstrate the substantial personal burden experienced by younger people with hip or knee OA, and support the provision of targeted services to improve HRQoL and maximise work participation in this group. Copyright © 2015. Published by Elsevier Ltd.