Quantifying the Impoverishing Effects of Purchasing Medicines: A Cross-Country Comparison of the Affordability of Medicines in the Developing World
et al. (2010) Quantifying the Impoverishing Effects of Purchasing Medicines: A Cross-
Country Comparison of the Affordability of Medicines in the Developing World. PLoS Med 7(8): e1000333. doi:10.1371/journal.pmed.1000333
Quantifying the Impoverishing Effects of Purchasing Medicines: A Cross-Country Comparison of the Affordability of Medicines in the Developing World
Laurens M. Nie ns 0
Alexandra Cameron 0
Ellen Van de Poel 0
Margaret Ewen 0
Werner B. F. Brouwer 0
Richard Laing 0
Joshua A. Salomon, Harvard School of Public Health, United States of America
0 1 Institute for Medical Technology Assessment and Institute for Health Policy & Management, Erasmus University Rotterdam, The Netherlands, 2 Essential Medicines and Pharmaceutical Policies, World Health Organization , Geneva, Switzerland, 3 Health Action International Global, Amsterdam , The Netherlands
Background: Increasing attention is being paid to the affordability of medicines in low- and middle-income countries (LICs and MICs) where medicines are often highly priced in relation to income levels. The impoverishing effect of medicine purchases can be estimated by determining pre- and postpayment incomes, which are then compared to a poverty line. Here we estimate the impoverishing effects of four medicines in 16 LICs and MICs using the impoverishment method as a metric of affordability. Methods and Findings: Affordability was assessed in terms of the proportion of the population being pushed below US$1.25 or US$2 per day poverty levels because of the purchase of medicines. The prices of salbutamol 100 mcg/dose inhaler, glibenclamide 5 mg cap/tab, atenolol 50 mg cap/tab, and amoxicillin 250 mg cap/tab were obtained from facilitybased surveys undertaken using a standard measurement methodology. The World Bank's World Development Indicators provided household expenditure data and information on income distributions. In the countries studied, purchasing these medicines would impoverish large portions of the population (up to 86%). Originator brand products were less affordable than the lowest-priced generic equivalents. In the Philippines, for example, originator brand atenolol would push an additional 22% of the population below US$1.25 per day, whereas for the lowest priced generic equivalent this demographic shift is 7%. Given related prevalence figures, substantial numbers of people are affected by the unaffordability of medicines. Conclusions: Comparing medicine prices to available income in LICs and MICs shows that medicine purchases by individuals in those countries could lead to the impoverishment of large numbers of people. Action is needed to improve medicine affordability, such as promoting the use of quality assured, low-priced generics, and establishing health insurance systems. Please see later in the article for the Editors' Summary.
In developing countries the cost of medicines accounts for a
relatively large portion of total healthcare costs . As the
majority of people in developing countries do not have health
insurance  and medicines provided free through the public
sector are often unavailable , medicines are often paid for out of
pocket at the time of illness. Consequently, where medicine prices
are high, people may be unable to procure them and therefore
forego treatment or they may go into debt. For this reason, the
World Health Organization (WHO) has designated affordable
prices as a determinant of access to medicines (together with
rational selection and use, sustainable financing, and reliable
health and supply systems) . In several international treaties,
access to healthcare has been established as a right [7,8]. States
have a legal obligation to make essential medicines available to
those who need them at an affordable cost. Determining the
degree of affordability of medicines, especially in low- and
middleincome countries (LICs and MICs), is an important, yet complex
undertaking as affordability is a vague concept.
Medicine affordability has been investigated in terms of the
days wages that a countrys lowest paid unskilled government
worker (LPGW) needs to spend on a standard course of treatment
[4,9]. However, this metric is limited because it does not provide
insight into the affordability of medicines for the often large
sections of the population that earn less than the LPGW [4,10].
Recently, Niens et al. have proposed two alternative methods to
gain insight into the affordability of medicines in the developing
world . A first method focuses on the catastrophic impact of
expenditures on medicines, while the second approach consists of
studying the impoverishing effect of these expenditures. Here we
discuss the application of the latter approach and present the
results of a cross-country analysis of the affordability of four
medicines in 16 developing countries.
Our measurement of the affordability of medicines is based on
the approach taken by Van Doorslaer et al. , who reassessed
poverty estimates in 11 Asian countries after taking into account
household expenditures on health care. The impoverishment
approach has also been used in other fields of study such as
housing affordability [12,13] and health insurance .
The impoverishing effect of a medicine is defined in terms of the
percentage of the population that would be pushed below an
income level of US$1.25 or US$2 per day when having to
purchase the medicine. Although different income levels have
been used/proposed [3,15], the US$1.25 and US$2 poverty lines
were chosen because they are the most recent widely recognized
poverty indicators as used by the World Bank . Thus, the
approach essentially compares households daily per capita income
before and after (the hypothetical) procurement of a medicine. If
the prepayment income is above the US$1.25 (or US$2) poverty
line and the postpayment income falls below these lines,
purchasing the medicine impoverishes people. We used this
method to generate impoverishment rates, which denote the
percentage of the population that would become impoverished.
The unaffordability of a medicine then refers to the percentage of
the population that either already is or would fall below the
poverty line when having to procure the medicine. First we
consider the affordability of medicines in the total population at
risk of becoming ill. We also indicate, using prevalence rates for
the three chronic diseases, the expected number of patients
To conduct the first analysis, three types of data were required
per country: medicine prices, aggregated income data, and
information on the income distribution. In calculating expected
numbers of patients affected, prevalence data are also required.
Medicine prices were taken from standardized surveys using the
WHO/Health Action International (HAI) price measurement
methodology, which report median patient prices for a selection of
commonly used medicines in the private sector, for both originator
brand (OB) and lowest priced generic (LPG) products . We
focused on the private sector because the availability of essential
medicines in the public sector is much lower . In the countries
studied here, therefore, many people will depend on the private
sector for their medicines.
The World Banks World Development Indicators (WDIs)
provided Household Final Consumption Expenditure (HHFCE)
data and information on income distribution . Although WDIs
have shortcomings (highlighted in the Discussion section), they
have the advantage of being available for a wide range of
countries. Moreover, in this context commonly used household
surveys are often not available on a yearly basis and are not
conducted in a standardized way, limiting the comparability of
results across countries and over time [3,19]. Here we use an
affordability measure that can be quite easily applied in LICs and
MICs where the use of more detailed household survey data may
HHFCE was selected as an aggregate income measure rather
than gross domestic product (GDP) per capita as it better reflects
households resources , while GDP also includes consumption,
gross investment, and net trade. Because the WDI did not provide
any information on HHFCE for Nigeria and Yemen, the
Economist Intelligence Unit (EIU) nominal private consumption
figure was used for these countries . For simplicity, we refer to
income as measured by HHFCE or nominal private
consumption. Apart from average income, the WDIs also provide some
information on a countrys income distribution by listing the
proportion of total income earned in seven income groups; five
income quintiles, with the poorest and richest quintiles split into
At the time of analysis, medicine price surveys were available for
53 countries. In large countries such as India and China, price
surveys were carried out on a state or provincial level . Because
the WDIs do not provide state-level income distributions,
HHFCE, and population figures, these countries were excluded
from the current study. To ensure cross-country comparability, the
analysis was limited to countries where income distributions (WDI
data) were available from the year 2000 onwards. We used WDI
income data from the same year as the WHO/HAI price data.
Data on income distributions for the same year were used when
possible, if not, the most recent income distribution data prior to
the year of the price and income data were used.
Table 1 provides an overview of all countries and data used in
this study. When discussing results, countries were grouped into
LICs and MICs according to the 2008 World Banks classification
. Sixteen countries were selected on the basis of the availability
of WHO/HAI data. They are not representative of the developing
world as a whole. However, as these countries vary substantially in
terms of economic development, health care infrastructure, and
medicine prices, they provide an interesting sample to study
affordability of medicines.
We selected four medicines for which price data were available
for the majority of countries and for which treatment regimens are
relatively standard across countries. While these may not lead to
results that are in a strict sense generalisable, they provide valuable
Medicine Price Survey and WDI Income Data
WDI Data on Income Distribution
Our method of estimating the impoverishing effect of procuring
medicines was based on the method used by Van Doorslaer et al.
. However, using aggregate data requires some simplifying
assumptions about the income distribution across population
groups. For a detailed discussion of the method used to calculate
the impoverishing effect of medicines, we refer to Niens et al. .
The basic idea is to compare poverty estimates before and after a
(potential) purchase of the medicines listed in Table 1. Average per
capita income within each income group is estimated by
combining information on the proportion of total income earned
across income groups with data on the HHFCE (as provided by
the WDIs). As only data on average income in the different
quintiles and deciles were available, we assumed linearity of the
income distribution within these relevant groups in which the
US$1.25 and US$2 poverty lines were located in calculating
poverty and impoverishment. The proportion of the population
that would earn less than US$1.25 or US$2 per day after buying a
medicine but not before would therefore be impoverished because
of purchasing medicines. The medicine is deemed affordable for
the proportion of the population that would remain above the
30 (1 inhaler)
Total n of Doses per
aNominal private consumption from EIU was used.
insight into the affordability of common medicines in the selected
countries. Table 2 lists the medicine, the ill health conditions for
which these medicines are used, the total number of units per
treatment course, and the treatment duration in days . Three
of the four study medicines are used to treat chronic conditions
(asthma, diabetes, and hypertension). For each of these, we also
calculated the expected numbers of patients becoming
impoverished, using the prevalence data shown in Table S1. We could not
do this for adult respiratory infection because of unavailability of
comparable prevalence data.
The emphasis on medicines for chronic disease is justified by the
fact that these conditions require ongoing, usually lifelong
expenditures, making it more difficult for households to use
financing strategies like borrowing and selling assets . Table 2
shows that the treatment duration for these medicines was set at
30 d to represent the monthly treatment costs. The affordability of
one acute condition (adult respiratory infection) treated with a 7-d
treatment course of amoxicillin was also studied. Recently, the
WHO increased the guidelines for treatment of adult respiratory
infection with amoxicillin to a daily regimen of three times 500 mg
amoxicillin. This change implies that the affordability of this
medicine is likely to be lower than reported here .
Ill Health Condition
Adult Respiratory Infection
P 6 4 1 0 2 4 8 8 0 3 4 2
L 2 a 8 2 5 8 7 5 2 a 9 1 1 1 3 a
P 5 1 2 4 0 4 1 5 7 2 9 0 8
L 1 a 8 1 3 8 7 4 2 1 1 4 1 1 2 3
o 5 P 3 2 7 3 9 2 2
l 2 L 1 a 6 0 1 5 5 1 9 1 0 0 4 4 1 0
7 2 0 5 5 3 7
a A U O a a 6 1 a a 7 a 2 1 1 1 a 1 2 a
P 5 9 2 3 1 4 3 6 6 9 1 9
L 2 6 7 1 3 8 7 4 2 1 6 3 1 1 2 2
poverty line after having purchased it. We also estimated the
actual number of patients with one of the three chronic illnesses for
which the medicine is unaffordable. To make this estimation, we
used prevalence rates from various data sources and again assume
that the respective disease is evenly spread over the income
Because HHFCE is measured in current US$, we recalculated
the US$1.25 and US$2 poverty lines to US$ values for the HAI/
WHO survey year. HAI/WHO medicine prices were expressed in
US$ for the same year.
Table 3 presents the percentages of the population that are
pushed below the poverty line owing to the purchasing of each of
the four study medicines, both LPG and OB products.
For each country, Table 3 first highlights the proportion of the
population already below the US$1.25 and US$2 poverty lines
without purchasing these medicines. These poverty estimates
correlate highly with the commonly used (household-survey based)
estimates from the United Nations Development Program with
Pearson correlation coefficients  equal to 0.90 for the
proportion of the population below the US$1.25 poverty line,
and 0.86 for the proportion below the US$2 poverty line. Table 3
also shows the proportion of the population earning less than the
LPGW, which varies widely across countries; from only 1% in
Tajikistan to 96% in Tanzania. This cross-country variability
represents one of the limitations of the LPGW metric as used by
the WHO/HAI methodology .
Comparing the proportion of the population below the US$1.25
and US$2 poverty lines before and after procurement of medicines
gives insight into the impoverishing effect of medicine
procurement. By adding the proportion of the population already living
below the US$1.25 and US$2 poverty lines to the group that
would fall below these poverty lines when procuring the medicines,
we get the proportion of the population for which the four
medicines are unaffordable.
The results in Table 3 illustrate that the impoverishing effect of
medicines varies substantially between OB and LPG products. For
example in Yemen, a LIC where 7% of the population lives on a
prepayment income of less than US$1.25 a day, OB glibenclamide
purchased in the private sector would impoverish an additional
22% of the population versus 3% for the LPG equivalent. In
Nigeria, a LIC where 56% of the population lives below US$1.25
per day, purchasing amoxicillin from the private sector would
impoverish an additional 23% if the OB is bought and 12% if
buying the LPG.
Rather than showing proportions of the population, Table 4
presents both the absolute number of individuals that would be
pushed into poverty owing to the cost of buying medicines from
the private sector (Impoverished column) and the number of
people for which medicines are unaffordable (Unaffordable
column). Besides absolute figures, in Table 5 we present the
relative change of the poverty estimates for the total population
studied as well as for the patient population. So, if 40% of the
population is initially above the poverty line, while only 30%
would remain above after purchasing medicines, this proportion is
25% (10% out of 40% are impoverished). These numbers are
listed for all four medicines, both OB and LPG. The total
population of the 16 countries analyzed amounts to over 775
million people, of which approximately 126 million live on less
than US$1.25 and 209 million on less than US$2 per day,
respectively. Table 4 illustrates that across this set of 16 developing
countries, for respectively almost one-fourth and two-fifths of the
Chronic Patient Population
total population, essential medicines are unaffordable using the
US$1.25 and US$2 poverty line.
The upper half of Table 4 shows the proportions of the total
population for which medicines would be unaffordable when
having to procure them. The actual number of people affected by
this unaffordability (in terms of experiencing the disease) depends
on the prevalence of diseases as well. Therefore, the lower half of
Table 4 also shows the expected absolute number of patients
affected by the unaffordability of medicines using the prevalence
rates listed in Table S1. As the prevalence rates of hypertension
are substantially higher than those of asthma and diabetes, the
impoverishing effect, and therefore also the unaffordability, of
atenolol is substantially higher than that for the other medicines.
In this approach, given the height and distribution of income,
impoverishment is determined by both medicine prices and
prevalence rates for the relevant diseases.
The results illustrate that substantial proportions of the
population would be pushed into poverty as a result of medicine
procurement, implying that in many countries affordability of
these treatments is low. In the private sector, LPGs were generally
substantially more affordable than OB products. Thus, increasing
the use of quality-assured generics could reduce the impoverishing
effect of medicines. This use of generics, in turn, could bring about
improvements in the health status of these populations by avoiding
low compliance to recommended dosages or duration of
treatment, resulting in problems such as sustained hypertension,
elevated blood glucose levels, or the promotion of bacterial
resistance due to too short courses of antibiotics.
Our calculation method has the advantage of allowing for
comparisons of medicine-induced impoverishment across time and
across countries using widely available aggregate data. The
method, therefore, is useful and generalisable for studying the
affordability of a wide range of goods and health care services. The
use of such data also brings some limitations, which are discussed
in further detail in Niens et al. . First, dividing HHFCE by
total population to get an estimate of income per capita assumes
that each household is the same size. However, poor households
are generally larger than their richer counterparts . This
discrepancy causes the average income per capita to be
overestimated in the lower income groups, making our
affordability estimates rather conservative. Second, the assumption of
linearity of the income distribution between income groups is also
likely to lead to an overestimation of average incomes across the
income distribution and therefore to a downward bias in our
results. We also assumed a linear distribution of illness over the
income distribution to calculate expected numbers of affected
people. Although, in general, disease may be more prevalent in
low income groups, which would imply conservative estimates of
unaffordability, this also depends on the exact diseases studied.
Moreover, it is clear that considering only medicine costs, for four
medicines independently, merely demonstrates the larger problem
of medicine and health care affordability. The treatment of
chronic conditions often requires a combination of medicines and
is therefore likely to be even more unaffordable than what is
reported here . For chronic asthma patients, for example,
appropriate management of their disease requires use of both
salbutamol and beclometasone inhalers for treatment and
prevention . Due to the lack of available price information
on beclometasone inhalers (because of poor availability), it was not
possible to include this medicine in the analysis. As such, the true
affordability of asthma treatment is likely to be lower than
reported in Tables 3 and 4. Having said this, the medicines studied
in this paper are commonly used to treat ill health conditions from
which considerable proportions of the population in the
developing world suffer, as is also illustrated in Table S1 .
As such, low affordability of these medicines is likely to signal a
more general problem of low affordability of medicines in LIC and
MIC. Further, it should be noted that comparability of
impoverishment rates for acute and chronic conditions may be
limited. If people suffer from an adult respiratory infection, on
average three times per year, and are able to shift resources over
time, the impoverishment rates for amoxicillin should be
interpreted with caution. Further research is needed on this issue,
for example by calculating affordability for standardized time
periods taking into account the relevant incidence rates of
Notwithstanding these limitations, this study provides useful
insights into the affordability of these four medicines in the
developing world. When medicine prices are known, the methods
used, as they rely on easily obtainable aggregated data, can be
used to compare affordability of medicines across countries and
over time. Clearly, medicines represent only a part of the costs
associated with the management of an illness. Other costs, such as
for diagnostics, physician consultations, transport costs to clinics,
lost work time, etc., place an additional burden on household
finances in developing countries. However, given the relatively
large share of health care costs for medicines in developing
countries , medicine affordability is likely to be an important
determinant to access to treatment.
This study shows high medicine costs can push large groups of
patients into poverty. These results call for action, both by
governments, civil society organizations, and others, to make
access to essential medicines a priority, and not only to ensure
access to necessary medicines, but also as a component in the
context of reducing poverty. Possible lines of action include
developing, implementing, and enforcing sound national and
international price policies. In the short term these policies could
encompass, for example, restrictions on supply chain mark-ups,
tax exemptions, and regulating prices for end-users. Promoting the
use of quality-assured, low-cost generics, for example, through
preferential registration procedures, is also an important strategy
. In the public sector, ensuring availability of essential medicines
at little or no charge to the poor is critical. In the longer term,
establishing health insurance systems with outpatient medicine
benefits seems crucial to avoid poverty due to health shocks (and
poor health due to poverty). Innovative approaches, such as using
private distribution systems to supply subsidized medicines to
chronic disease patients, should also be considered. For medicines
that are still subject to patent restrictions, pharmaceutical
companies should be encouraged to differentially price these
products, as is the case with antiretrovirals . Countries also
have the option of using compulsory licensing to oblige patent
holders to grant its use to the state or others , as was recently
done by Thailand [29,30].
When resources are limited, those in greatest need, such as
people suffering from chronic disease who earn less than US$1.25
per day, should benefit from state and/or donor actions. The price
in terms of health losses due to unaffordable
something we cannot afford.
Alternative Language Abstract S1 Abstract translated into
French by Ellen Van de Poel and Gabriela Flores.
Found at: doi:10.1371/journal.pmed.1000333.s001 (0.02 MB
Alternative Language Abstract S2 Abstract translated into
Spanish by Laurens M. Niens and Isaac Corro Ramos.
Found at: doi:10.1371/journal.pmed.1000333.s002 (0.02 MB
Table S1 The prevalence of three chronic diseases.
Found at: doi:10.1371/journal.pmed.1000333.s003 (0.05
We would like to thank Dele Abegunde for his critical review of the
manuscript and Eddy Van Doorslaer and Frans Rutten for their useful
ideas on this topic.
ICMJE criteria for authorship read and met: LMN AC EvdP ME WBFB
RL. Agree with the manuscripts results and conclusions: LMN AC EvdP
ME WBFB RL. Designed the experiments/the study: LMN AC WBFB
RL. Analyzed the data: LMN AC ME. Collected data/did experiments for
the study: LMN. Wrote the first draft of the paper: LMN. Contributed to
the writing of the paper: LMN AC EvdP ME WBFB RL.
Background In recent years, the international community
has prioritized access to essential medicines, which has
required focusing on the accessibility, availability, quality,
and affordability of life-saving medicines and the
development of appropriate data and research agendas to
measure these components. Determining the degree of
affordability of medicines, especially in low- and
middleincome countries, is a complex process as the term
affordability is vague. However, the cost of medicines is a
major public health issue, especially as the majority of
people in developing countries do not have health insurance
and medicines freely provided through the public sector are
often unavailable. Therefore, although countries have a legal
obligation to make essential medicines available to those
who need them at an affordable cost, poor people often
have to pay for the medicines that they need when they are
ill. Consequently, where medicine prices are high, people
may have to forego treatment or they may go into debt if
they decide to buy the necessary medicines.
Why Was This Study Done? The researchers wanted to
show the impact of the cost of medicines on poorer
populations by undertaking an analysis that quantified the
proportion of people who would be pushed into poverty (an
income level of US$1.25 or US$2 a day) because their only
option is to pay out-of-pocket expenses for the life-saving
medicines they need. The researchers referred to this
consequence as the impoverishing effect of a medicine.
What Did the Researchers Do and Find? The researchers
generated impoverishment rates of four medicines in 16
low- and middle-income countries by comparing
households daily per capita income before and after (the
hypothetical) purchase of one of the following: a salbutamol
100 mcg/dose inhaler, glibenclamide 5 mg cap/tab, atenolol
50 mg cap/tab, and amoxicillin 250 mg cap/tab. This
selection of drugs covers the treatment/management of
three chronic diseases and one acute illness. The cost of each
medicine was taken from standardized surveys, which report
median patient prices for a selection of commonly used
medicines in the private sector (the availability of essential
medicines in the public sector is much lower so many people
will depend on the private sector for their medicines) for
both originator brand and lowest priced generic products. If
the prepayment income was above the US$1.25 (or US$2)
poverty line and the postpayment income fell below these
lines, purchasing these medicines at current prices
According to the results of this analysis, a substantial
proportion (up to 86%) of the population in the countries
studied would be pushed into poverty as a result of
purchasing one of the four selected medicines. Furthermore,
the lowest priced generic versions of each medicine were
generally substantially more affordable than originator brand
products. For example, in the Philippines, purchasing
originator brand atenolol would push an additional 22% of
the population below US$1.25 per day compared to 7% if the
lowest priced generic equivalent was bought instead. In
effect, purchasing essential medicines for both chronic and
acute conditions could impoverish large numbers of people,
especially if originator brand products are bought.
What Do These Findings Mean? Although the
purchasing of medicines represents only part of the costs
associated with the management of an illness, it is clear that
the high cost of medicines have catastrophic effects on poor
people. In addition, as the treatment of chronic conditions
often requires a combination of medicines, the cost of
treating and managing a chronic condition such as asthma,
diabetes, and cardiovascular disease is likely to be even more
unaffordable than what is reported in this study. Therefore
concerted action is urgently required to improve medicine
affordability and prevent poor populations from being
pushed further into poverty. Such action could include:
governments, civil society organizations, and others making
access to essential medicines more of a priority and to
consider this strategy as an integral part of reducing poverty;
the development, implementation, and enforcement of
sound national and international price policies; actively
promoting the use of quality assured, low-cost generic
drugs; ensuring the availability of essential medicines in the
public sector at little or no charge to poor people;
establishing health insurance systems with outpatient
medicine benefits; encouraging pharmaceutical companies
to differentially price medicines that are still subject to
Additional Information. Please access these Web sites via
the online version of this summary at http://dx.doi.org/10.
N For a comprehensive resource for medicine prices,
availability, and affordability, see Health Action
N Guidelines about access to essential medicines and
pharmaceutical policies can be found at WHO
N Access to essential medicines has become a key campaign
topic; for more information see Me decins Sans Frontie` res
(Doctors without Borders)
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