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Mental health comorbidity in low-income and middle-income countries: a call for improved measurement and treatment

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 ميثم محسن مهدي الياسري
17/10/2018 19:06:58
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Comment Published online August 30, 2018 1
Mental health comorbidity in low-income and middle-income
countries: a call for improved measurement and treatment
Considerable progress has been made over the past
decade in epidemiological and intervention research,
service delivery, and increasing awareness of and
appreciation for the importance of mental health in lowincome
and middle-income countries (LMICs). A key
example of this progress is the WHO’s Comprehensive
Mental Health Action Plan 2013–2020.1 As global mental
health moves forward into areas of implementation
science, health systems strengthening, and policy
making, we believe it is necessary to highlight what,
in our opinion, is a major gap in the field: the lack of
information on the prevalence and treatment of cooccurring
mental health, substance use, and other
psychosocial problems.
In high-income countries (HICs), published literature
shows that comorbidity of common mental health
problems is the rule, not the exception. Depression,
anxiety, and post-traumatic stress disorder frequently
occur together,2 and mental health problems are common
among people with alcohol and other substance use
disorders, and those individuals who have or perpetrate
interpersonal violence.3 On the basis of data from our
studies, including an ongoing one in Zambia (Kane JC,
Murray, LK, unpublished), we suspect co-occurrence
of mental health, substance use, and psychosocial
problems is similarly prevalent in LMICs, albeit not well
documented. Not surprisingly, our data also suggest that,
similar to HICs,4 comorbidity of mental health problems is
common among people with physical health issues, such
as HIV and disabilities (Kane JC, Murray, LK, unpublished).
The lack of information and attention on comorbidity
in LMICs results from multiple issues. First, many studies
focus on a single disorder of interest (eg, depression
alone) and are not designed to assess co-occurring
symptoms or conditions. This narrow focus impedes
our understanding of comorbidity and undermines
our ability to improve the understanding of the cause.
Second, treatment for mental health in LMICs has
also been primarily focused on a single problem. As
suggested elsewhere,5 such siloed treatment models are
not only inefficient, given the need for extensive and
complex referrals, but also greatly inhibit scale-up and
sustainability. Third, studies or programmes that have
an interest in assessing comorbidity often lack both
validated assessment tools that cut across disorder types
and the time needed to collect the data. Finally, studies
that do measure multiple outcomes tend not to report
how often these conditions co-occur and interact, or
how interventions affect multiple conditions among
people with comorbidities.6
We propose three approaches to improve our
understanding of comorbidity in LMICs. First, more
explicit attention in this area is warranted. This approach
includes publication of existing data on comorbidity,
building the measurement of comorbidity into
study designs a priori (including accounting for this
measurement in sample size calculations), and crucially,
increasing financial support from key stakeholders and
funders to assess and treat comorbidity. Second, brief,
pragmatic tools are needed to measure symptoms and
problems across a range of conditions to help us improve
the understanding of who has these problems, how they
change and influence each other, and how treatment
might affect their course. An example of this second
approach in HICs is the measurement of patient-reported
outcomes (PROs) within Center for AIDS Research
Network of Integrated Clinical Systems, a collaboration
of eight clinics that have already treated more than
30 000 patients with HIV in the USA. Every 4–6 months,
while queuing for clinical care, patients complete PRO
assessments that include validated measurement tools
for depression, anxiety, and substance use. Data are
used for clinical care and research.7 In LMIC settings, our
team and our partners are using item response theory
to help refine and improve practical tools that improve
the assessment of comorbidity. For example, in Ukraine,
we used item response theory to reduce successfully an
83-item questionnaire covering depression, anxiety, and
post-traumatic stress, to 20 items.8
Finally, a fundamental shift in treatment approach
is needed. LMIC health systems are increasingly being
modelled after those in HICs, in which treatment of
specific disorders is done by a specialist in a single
problem area (eg, specific provider or clinic for anxiety
distinct from a provider or clinic for substance use).
Mimicking this approach in LMICs seems both misguided,
Lancet Psychiatry 2018
Published Online
August 30, 2018
For more on the Centre for AIDS
Research Network Clinical
Systems see https://www.uab.
Flor N. Melendez Rojas

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  • Co-morbidity