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Are malaria treatment expenditures catastrophic to different socio-economic and geographic groups and how do they cope with payment? A study in southeast Nigeria

2009; Wiley; Linguagem: Inglês

10.1111/j.1365-3156.2009.02418.x

1365-3156

Obinna Onwujekwe, Kara Hanson, Benjamin Uzochukwu, Hyacinth E. Ichoku, Edith Ike, Benjamin Onwughalu,

Child Nutrition and Water Access

Objectives To determine the inequities in the household income depletion resulting from malaria treatment expenditures, the sacrifice of basic household needs (catastrophe) and the differences in payment strategies among different socio-economic and geographic groups in southeast Nigeria. Methods Data were gathered through pre-tested, structured questionnaires from a random sample of 2 250 householders in rural and urban parts of southeast Nigeria. The level of catastrophic malaria treatment expenditure was computed as the percentage of average monthly malaria treatment expenditure divided by the average monthly non-food household expenditure, using a threshold of 5%. Socio-economic inequity was established using a socio-economic status (SES) index, while a rural-urban comparison examined geographic disparities. Results The average cost to treat a case of malaria was 796.5 Naira ($6.64) for adults and 789.0 Naira ($6.58) for children. The monthly malaria treatment expenditure as a proportion of monthly household non-food expenditure was 7.8%, 8.5%, 5.5% and 3.9% for the most poor, very poor, poor and least poor SES groups respectively. Malaria treatment accounted for 7.1% and 5.0% of non-food expenditures for rural and urban dwellers, respectively. More than 95% of the people financed their treatment through out-of-pocket payment (OOP), with no SES and rural–urban variance, as opposed to insurance payment mechanisms and fee exemptions. Conclusion There were socio-economic and geographic inequities in the financial burden resulting from malaria treatment. The treatment expenditure depleted more of the aggregate income of the two worse-off SES (Q1 and Q2) and of the rural dwellers. Government and donor agencies should institute the abolition of user fees for malaria, the transition from OOP to pre-payment mechanisms and the improvement of physical access to appropriate malaria treatment services, as well as subsidies and deferrals in order to engender financial risk protection from malaria treatment. Objectifs: Déterminer les inégalités dans l’appauvrissement des revenus des ménages résultant des dépenses pour le traitement de la malaria, le sacrifice des besoins domestiques de base (la catastrophe) et les différences dans les stratégies de paiement dans les différents groupes socio-économiques et géographiques dans le sud du Nigeria. Méthodes: Les données ont été collectées grâce des questionnaires structurés pré testés, soumis à un échantillon aléatoire de 2250 ménages dans les régions rurales et urbaines du sud-est du Nigeria. Le niveau des dépenses catastrophiques pour le traitement de la malaria a été calculé comme le pourcentage de la moyenne des dépenses mensuelles pour le traitement de la malaria divisée par la moyenne mensuelle des dépenses alimentaires des ménages, en utilisant un seuil de 5%. L’inégalité socio-économique a étéétablie en utilisant un indice de statut socio-économique (SSE), alors qu’une comparaison rurale-urbaine a examiné les disparités géographiques. Résultats: Le coût moyen pour traiter un cas de malaria était de 796,5 Naira (6,64 $) pour les adultes et 789,0 Nairas (6,58 $) pour les enfants. Les dépenses mensuelles pour le traitement de la malaria en tant que proportion des dépenses mensuelles non alimentaires des ménages étaient de 7,8%; 8,5%; 5,5% et 3,9% pour les groupes SSE les plus pauvres, les très pauvres, les pauvres et les moins pauvres, respectivement. Le traitement de la malaria représentait 7,1% et 5,0% des dépenses non alimentaires pour les habitants des zones rurales et urbaines, respectivement. Plus de 95% des gens ont financé leur traitement au moyen de paiements directs de leur poche, sans variance entre SSE et zones rurale-urbaine, par opposition aux mécanismes de paiement via des assurances et des exemptions de frais. Conclusion: Il y avait des inégalités socio-économiques et géographiques dans la charge financière résultant du traitement de la malaria. Les dépenses de traitement appauvrissaient plus le revenu total des deux groupe SSE (Q1 et Q2) les plus pauvres et des habitants des zones rurales. Les gouvernement et organismes donateurs devraient instituer l’abolition des frais pour le traitement de la malaria, la transition du paiement direct de la poche vers des mécanismes de prépaiement et l’amélioration de l’accès physique aux services de traitement approprié de la malaria, ainsi que des subsides et des reports dans le but d’engendrer des protections contre les risques financiers dus au traitement de la malaria. Objetivos: Determinar las inequidades en las pérdidas de ingresos en los hogares como resultado de los gastos en el tratamiento de la malaria, el sacrificio de necesidades básicas del hogar (catástrofe) y las diferencias en estrategias de pago entre los diferentes grupos socio-económicos y geográficos en el sudeste de Nigeria. Métodos: Los datos se recolectaron mediante cuestionarios estructurados, previamente probados, en una muestra aleatoria de 2250 hogares en zonas rurales y urbanas del sudeste de Nigeria. El nivel de gasto catastrófico en el tratamiento de la malaria se computó como el porcentaje del promedio mensual del gasto en tratamiento para la malaria dividido por el promedio mensual de gastos no relacionados con la alimentación, utilizando un umbral del 5%. Las inequidades socio-económicas se establecieron utilizando un índice de estatus socio-económico (ESE), mientras que la comparación urbano-rural examinó disparidades geográficas. Resultados: El coste promedio de tratar un caso de malaria fue de 796.5 Naira ($6.64) en adultos y 789.0 Naira ($6.58) en niños. El gasto mensual en el tratamiento de la malaria como una proporción del gasto mensual del hogar (sin incluir gasto en alimentación) fue del 7.8%, 8.5%, 5.5% y 3.9% para los grupos de ESE más pobres, muy pobres, pobres y menos pobres respectivamente. El tratamiento de la malaria correspondió al 7.1% y 5.0% de los gastos no relacionados con la alimentación para los hogares rurales y urbanos respectivamente. Más del 95% de las personas financiaron su tratamiento mediante pago con dinero de bolsillo (PDB), sin variación en grupos ESE o geográficos, en contraposición a pagos de seguros o exención de pago. Conclusión: Había inequidades socio-económicas y geográficas en la carga financiera que resulta del tratamiento de la malaria. El gasto del tratamiento redujo más el ingreso agregado de los dos grupos de ESE peor parados (Q1 y Q2) y el de los habitantes de zonas rurales. Las agencias gubernamentales y agencias donantes deberían abolir las tarifas para usuarios en el tratamiento de la malaria, instituir la transición de pagos con dinero de bolsillo a mecanismos de pre-pago y la mejora del acceso físico a los servicios apropiados del tratamiento de malaria, al igual que subsidios y aplazamiento de pagos con el fin de engendrar protección de riesgos financieros para el tratamiento de la malaria. In Nigeria, malaria causes more than 50% of the disease burden (FMOH 2005), almost 50% of all-cause health expenditure (Onwujekwe et al. 2000), 20% of all hospital admissions, 30% of outpatient visits and 10% of hospital deaths (Okeke et al. 2006). Half of Nigeria’s population is exposed to at least one episode of malaria every year (FMOH 2005). The federal and some state governments in Nigeria have abolished user fees for children under five and for pregnant women in public health facilities, in an effort to reduce the economic burden of malaria. However, this policy does not apply in many states of the country and neither to private facilities, which serve more than 70% of malaria cases. The policy does not differentiate between socio-economic status and geographic location; there are many people outside of the target groups of pregnant women and children under five years at risk of incurring catastrophic costs due to malaria. A study found that households spent an average of $1.84 per month on malaria and households’ incomes are depleted by 7.03% on average by the costs incurred because of malaria (Onwujekwe et al. 2000). These high levels of household income depletion contribute to the vicious cycle of poverty and disease. The high level of economic burden of malaria coupled with high expenditures and paying mostly through out-of-pocket spending (OOPS) may prevent people from seeking and obtaining needed care because they cannot afford to pay the charges levied for diagnosis and treatment (Xu et al. 2007; Castillo-Riquelme et al. 2008). The associated high levels of financial expenses due to malaria potentially lead households, especially very poor ones, to incurring catastrophic costs in treating the disease, which can lead to ‘to financial hardship and even impoverishment because people are too ill to work’ (Xu et al. 2007). The situation is exacerbated by the lack of financial risk protection, where people currently pay primarily out-of-pocket for health expenditures (Feder et al. 1987). In Nigeria, OOPS accounts for more than 65% healthcare payments (Soyibo 2004; Onwujekwe & Uzochukwu 2005; FMOH 2006). As described by Xu et al. (2003), as the volume of total health expenditure met by out-of-pocket payments increases, the range of catastrophic payments also increases. The extent to which malaria expenditures are catastrophic in many sub-Saharan African (SSA) countries, such as Nigeria, particularly to different socioeconomic status (SES) and geographic groups, is unknown. It is possible that ‘people who do seek care suffer financial catastrophe and impoverishment as a result of meeting the costs’ (Xu et al. 2007). Enormous bills mean catastrophe to anyone, but even small bills can be catastrophic to people with limited means (Feder et al. 1987). A relatively small payment can result in a large financial catastrophe to poor households, forcing them to reduce other basic expenses such as food, shelter or their children’s education (Xu et al. 2007). Similarly, large healthcare payments can lead to financial catastrophe and bankruptcy even for the rich (Xu et al. 2007). Although, many studies have examined the level of households’ expenditures and cost of treating malaria both in Nigeria and elsewhere (Onwujekwe et al. 2000; Chima et al. 2003; Onwujekwe & Uzochukwu 2005; Worrall et al. 2005), there is almost no available information as to the extent that treatment of malaria leads households to incur catastrophic expenditures. The catastrophe due to malaria may also have geographic dimensions. Where locations can be associated with increased malaria risk for both epidemiological and socioeconomic reasons, urban residence can be accompanied by potentially protective socio-economic variables against malaria risk, such as education and income (Worrall et al. 2005). Catastrophic costs due to healthcare or malaria treatment refer to households spending more than a stated percentage threshold of their income (or non-food expenditure) on healthcare or malaria as the case may be. Deciding what share of income constitutes catastrophe is a question of values (Feder et al. 1987). Some might define catastrophe as expenses that threaten a person’s existing standard of living; others as expenses that threaten some ‘reasonable’ standard of living. In either case, share of income may vary with people’s circumstances and with their incomes (Feder et al. 1987). Several thresholds have been proposed: Gertler and van der Gaag (1990) suggest that, typically, the price elasticity of demand for healthcare services exceeds unity at prices higher than 5% of non-food expenditure, implying that at this level financing healthcare would become a heavy burden for a typical household. However, many household surveys suggest that the average households contribution to per capita health expenditure in most economies is about 3–5% of its income (Russel 1996). Ranson (2002), Pradhan and Prescott (2002), Wagstaff and van Doorslaer (2002) and O’Donnell et al. (2005) used a threshold of 10%. Xu et al. (2003), used a threshold of 40% of ‘capacity to pay’, which was defined as income after subsistence needs are met, in practice as income minus food expenditure. Castillo-Riquelme et al. (2008) used a threshold of 10% of household income and 40% of non-food income. According to Feder et al. (1987), expenses of 10 or 20% of income are typically defined as in the catastrophic range and they used a threshold of 15–20% of income in their study. However, one could argue that expenditures of less than 40% to 10%, or even any expenditure, to some very poor households in Nigeria, especially those already living below the poverty line, are catastrophic. At this level of poverty, households may not have money to spend on any household need aside from food. In the presence of the high incidence of poverty in Nigeria, with more than 50% of the people living below the poverty line, most health expenditures are catastrophic and the threshold for assuming catastrophe may be less than 2% (Ichoku 2005). This paper demonstrates the extent that malaria treatment expenditures are catastrophic to different socio-economic groups and people living in urban and rural areas. In order to provide a holistic picture of the situation, the paper also presents the levels of socio-economic and geographic differentials in malaria treatment expenditure, payment strategies and payment coping mechanisms for the treatment of malaria in southeast Nigeria. It has been argued that poor (Breman et al. 2004) and rural dwellers have higher risk factors and greater malaria burden (Holtz et al. 2002). It has also been postulated that between 6% and 28% of the malaria burden may occur in cities, which comprise less than 2% of the African surface (Breman et al. 2004). It is hoped that the results will be used by policy makers and programme staff to develop initiatives to reduce the burden of payment for malaria treatment to poor households and, additionally, develop better financing arrangements. These will ensure that every malaria patient has prompt access to appropriate treatment and are not deterred by high costs or a lack of resources. Three urban towns (Awka, Nnewi and Onitsha) and three rural local government areas (Njikoka, Aguata and Ogbaru) were the study sites. One community from each of the three rural local government areas (LGAs): Enugwu-Ukwu (Njikoka LGA), Ekwulobia (Aguata LGA) and Okpoko (Ogbaru LGA) was selected using two-stage sampling, by first stratifying the communities according to the presence of a general hospital and then randomly selecting the sites from those that have general hospitals. Each site area houses an array of providers, from hospitals to pharmacy shops, patent medicine dealers, laboratories, itinerant drug providers and herbalists. Pharmacy shops are legal drug outlets with an in-house pharmacist, whilst patent medicine dealers are also legal drug outlets without an in-house pharmacist. People also receive treatment from laboratories, although this is illegal. The state has a high malaria transmission rate throughout the year and an annual incidence rate of 10–35%. The Nigerian healthcare system is dominated by three groups of providers: the public sector, private-for-profit and private-not-for-profit providers. The public sector comprises federal, state and local government owned health facilities. These facilities include primary health centers (PHC) which are the responsibilities of the local government area (LGAs), the secondary health facilities including federal government and state owned hospitals and clinics, and tertiary health institutions which are supposed to be the responsibility of the federal government, though many states now own teaching hospitals in addition. These public health facilities are run partly on the subsidies from the responsible tier of government and partly on user charges collected through out-of-pocket spending (OOPS) by patients. In an effort to cope with the spiralling cost of health care, the Nigerian National Health Policy articulates funding of health sector from budgetary sources, and recognizes additional avenues of revenue such as health insurance schemes and direct financing by employers of labour. Presently, public expenditures funded through general tax revenue in Nigeria account for 20–30% of total health expenditures and private expenditures accounts for 70–80% of the expenditures and the dominant private expenditure is OOPS, which is about US$ 22.5 per capita and accounts for 9% of total household expenditures (Federal Office of Statistics 2004). Half of those who could not access care did not so because of its cost (Federal Office of Statistics 2004). A National Health Insurance Scheme was introduced in 2005 but it covers only federal government workers, who comprise less than 5% of the population of Nigeria. The collective coverage of other insurance mechanisms such as private health insurance and community-based health insurance, is less than 1% of the population. The dominant reliance on OOPs, the limited presence of financial risk-protection mechanisms and the clear absence of exemption mechanisms and pre-paid instruments transfer the largest financing burden on the poor and are largely responsible for impoverishing health expenditures (Velenyi 2005; Preker 2005). The population survey function in EPI Info 6 was used to calculate the necessary sample size. The estimated sample sizes were 400 per urban site (total of 1200) and 350 per rural site (total of 1050), an overall sample size of 2250. Two-stage sampling was used to select households in each community where the questionnaires were administered. The respondent was a female primary care giver or, in her absence, male head of household or, in his absence, an adult representative of the household. Written and signed informed consent was sought from the respondents before the questionnaire was administered. The questionnaire was structured as follows: general socio-economic and demographic characteristics of the households; current health seeking patterns and costs of treating malaria; and asset holding of the households. Information on the incidence of fever (presumptive malaria) and the treatment sought for any episodes within the 4 weeks previous to questioning was collected through the questionnaire. In order to help the respondents to recall their expenditures, an itemization of the expenditure items was presented to them and they were asked how much they spent on each item. The expenditures were then added to yield the total expenditure. The expenditure items were those incurred on: registration; consultation; investigations; drugs; and others. The household expenditure to treat fevers and malaria, where diagnosed, was solicited for the same month-long period. Additionally, information was collected on households’ expenditures on a wide range of goods and services, such as education, rent, clothing, fuel, and healthcare aside from malaria and fever treatment. One week, one month, quarterly, bi-annual and annual period codes were attached to all expenditures. After stating how much they spent, respondents stated whether the expenses were made weekly, monthly, quarterly, bi-annually or annually. All of the expenditures were then converted to both annual and monthly estimates. Household weekly food expenditures and the monetized value of home produced and consumed food was also collected. The scenarios that were used to examine catastrophe were: the percentage of average monthly malaria treatment expenditure as a proportion of average monthly non-food household expenditure and the percentage of monthly malaria treatment expenditure as a proportion of annual household health expenditure. Due to the high incidence of poverty in Nigeria, a catastrophic threshold of 5% was used in this study. In fact in the USA, the first dollar spending (any medical expenditure) was defined as being catastrophic to the very poor (Feder et al. 1987). For equity analysis, an urban–rural distinction and a socio-economic status (SES) index were used to examine the systematic differences in catastrophic costs. SES differences in the variables were compared using cross-tabulations, mean comparisons and non-parametric tests. The SES index was developed using principal components analysis (PCA). The input to the PCA was information on ownership of key assets such as a motorcar, a motorcycle, a radio, a refrigerator, a television set, a grinding machine and a bicycle together with the cost of food. In the bivariate analysis the index was analysed as a categorical variable (divided into quartiles), with the ratio of the lowest SES to the highest SES computed as the measure of inequity. Household expenditure was not used to measure SES because the data on the expenditures was collected after the malaria expenditure, so it is endogenous to the malaria expenditure. Females comprised 62.1% and 62.8% of the respondents in the urban and rural areas respectively. The average age of the respondents was 36.4 and 37.2 years in the urban and rural areas respectively. More than 85% of the respondents in the urban and rural areas had some formal education, with an average schooling duration of 10 years. The number of household residents ranged from 4.2 in Enugwu-Ukwu to 6.3 in Nnewi, but was 5.3 from the combined data from the six communities. The predominant occupation of the household heads was petty trading. Females also comprised the majority of respondents in the exit pool. The majority of the respondents were married and for the most part in their mid-thirties. Most of the respondents had some formal education and spent an average of 11.5 years in school. The household survey revealed that the most common sources of treatment for both adult and childhood presumptive malaria were patent medicine shops and private hospitals (Table 1). Public hospitals were used for the treatment of malaria in 11.6% and 10.6% cases of adult and childhood malaria respectively; and primary healthcare centres were rarely used for treatment. The average expenditure to treat malaria was approximately 790 Naira ($6.58). Expenditures on drugs followed by those on laboratory tests were the highest contributors to total treatment expenditure. If expenditures on transport and treatment are added, then the grand mean expenditures to treat adult and childhood malaria were 874.3 Naira ($7.29) and 863.9 Naira ($7.20) respectively. The average expenditure on treatment in different providers was lowest at patent medicine shops ($1.9) and highest in private hospitals ($13.2). The higher SES groups spent more money to treat malaria. These SES groups also spent more money on registration, consultation and laboratory tests, which infers they consumed more appropriate treatment than the lower SES groups who spent less money on tests and consultation. The higher SES groups also spent more on transportation implying that they were willing to travel farther in an effort to receive appropriate treatment. Urbanites spent more on treatment (P < 0.05). The better-off households had higher non-food expenditures (Table 2). The average monthly malaria treatment expenditure for the general population was $7.03, ranging from $8.03 for the least poor to $5.27 for the most poor. Similarly, the annual health expenditure for the general population was $28.37, ranging from $32.2 for the least poor to $17.68 for the most poor. The average monthly household non-food expenditure for the general population was $88.59, ranging from $127.11 for the least poor to $73.37 for the most poor. All the expenditures were higher in the urban area than the rural area. Malaria treatment expenditures most significantly depleted the aggregate income of the two poorest SES groups (Q1 and Q2) and of the rural dwellers, contributing to more than 20% of annual heath expenditures. Malaria treatment accounted for more than 10% of monthly household expenditure for Q2 and 8.2% for the general sample. Table 3 shows that out-of-pocket spending (OOPS) was the major payment mechanism respondents used to pay for the treatment of malaria. There was neither SES nor rural–urban differences in the use of OOPS. The next most common payment mechanism was by instalment and insurance; reimbursements were rarely used. Health insurance and payment by instalment were used more frequently by the very poor SES and rural dwellers. Households’ own money was the major financial source for health payments, followed distantly by payment by relatives and borrowing (Table 4). Own money was used more by the better-off SES (P < 0.05). The significant portion of household incomes spent treating presumptive malaria episodes and large numbers of people paying for treatment through out-of-pocket spending (OOPS), predispose households to catastrophe. This is compounded by the official user fee policy and the near absence of financial risk protection mechanisms in the country. With user fees in place in public facilities and people paying mostly through OOPS to both public and private providers in Nigeria, poorer SES groups suffer catastrophe after paying for treatment. This could lead to a reduction in their utilization of malaria treatment services. Also, strategies for abolishing user fees for malaria for the general population, moving from OOPS to pre-payment mechanisms, are required to decrease the portion of household payments spent on malaria. It has been argued that people, particularly those in poor households, can be protected from catastrophic expenditures by reducing a health system’s reliance on out-of-pocket payments and providing more financial risk protection (Xu et al. 2003). The high level of use of OOPS contributes significantly to incidence of catastrophic malaria treatment expenditures. It was also seen that the three key preconditions for catastrophic payments, the availability of health services requiring payment, low capacity to pay, and the lack of prepayment of health insurance (Xu et al. 2003), were found in this study. Services are available at a fee, mostly through OOPS, and there was almost no availability of health insurance or other prepayment payment mechanisms. Hence, improving access to malaria should also entail introducing payment mechanisms that will assure financial risk protection of the consumers, without causing inefficiency in treatment provision. However, since the study examined catastrophe in relationship to presumptive malaria, it is possible that when only malaria confirmed cases are used as the basis for the analysis, the level of catastrophe may be lower than computed. Hence future studies should also examine catastrophe among confirmed malaria cases as well as SES groups within the same particular geographic area e.g. urban, as distinct from rural or vice versa, as there is a possibility of the variations on the burden of malaria facing the different SES groups living in the same geographic area. The existence of catastrophic costs may adversely affect the health seeking pattern of households, especially those that are very poor or living in a rural area, as they may now consume less than the required amounts of treatment or cheap but inappropriate treatment. Makinen et al. (2000) and Mbugua et al. (1995) showed that the introduction of user fee resulted in a greater utilization reduction among poorer persons than by the rest of the population. In a different context, Feder et al. (1987) found that one-fifth of the elderly in the USA suffered catastrophic expenses, which was more common amongst the lower income stratum of the population. Patterns of treatment choice may be related to resource constraints amongst other factors (Worrall et al. 2005) and cost considerations are an important determinant of provider choice (Kamat & Brown 2002). According to O’Donnell et al. (2005), location is relevant to expenditures on health care. Proximity to health services tends to increase utilization of healthcare in urban areas and travel costs raise expenditures in rural areas, though such expenses are often not recorded in the data (Ichoku 2005). There were socio-economic and geographic inequities in the expenditures and catastrophic payments due to presumptive malaria treatment. The treatment expenditure depleted more of the aggregate income of the two poorest SES groups (Q1 and Q2) and of the rural dwellers. The unexpected findings that Q2 had the highest annual health expenditure and Q1 had more non-food expenditure than Q2 was arguably due to some Q2 households having very chronically ill people and some Q1 households spending a lot of money on clothing and school fees. Clearly, the burden that medical expenses impose is a function of peoples’ incomes (Feder et al. 1987). In the presence of the high incidence of poverty in Nigeria, with more than 50% of the people living below the poverty line, most health expenditures are catastrophic and the threshold for catastrophe may actually be less than 2%. It was seen that although the urbanites spent more on treatment, they suffered less catastrophe than the rural residents, most likely due to the higher income levels in the urban areas. This, however, does not imply that the level of catastrophe suffered by the urbanites is not impoverishing; there are many poor people in the urban area. Also, as a result of the high incidence of poverty in the country, the level of catastrophe in the urban areas should not be countenanced but should also be addressed. In Nigeria, where the incidence of poverty has been on the rise since the 1980s with a substantial increase in the proportion of those in extreme poverty, and where majority of the poor live in the rural areas, the effects of poverty on overall malaria treatment in rural areas may be abysmally detrimental. Pro-poor and pro-rural malaria treatment policies are needed to ensure equitable access to malaria treatment services, especially using artemisinin-based combination therapy. Poor people are usually less likely to be able to pay either for effective malaria treatment or for transportation to a health facility capable of treating the disease (WHO 2003). This creates barriers for easy access to treatment for the rural dwellers in remote areas, or for having treatment in a more efficient health facility. Therefore, both direct and indirect costs associated with a malaria episode represent a substantial burden on the poorer households. A study in northern Ghana found that, while the cost of malaria care was just 1% of the income of the rich, it was 34% of the income of poor households (Biritwum et al. 2000). Catastrophic payments can lead to loss in productivity and impoverishment for poor households and further impoverishment for the poorest SES households. An implication for a population that is frequently exposed to malaria is economic retardation (McCarthy et al. 2000). A large proportion of potential economic growth rate in many countries of SSA are lost to malaria (McCarthy et al. 2000). For example, Malawi, one of the poorest countries in the region lost about 3.22% of potential annual economic growth rate to malaria in 1993. Sachs (2001) estimate that about 1.3% of annual economic growth translating to about US$12 billion of the region is lost to malaria. The economic backwardness of the region, of all the regions of the world, has frequently been attributed to the prevalence of malaria (Olumese 2005; Sachs 2005). Although few would question the strong correlation between poor economic status and malaria, empirically establishing that malaria causes poverty is problematic because the causality between malaria and diminished living standards is bidirectional for both nations and households (Worrall et al. 2005; Olumese 2005; Sachs 2005). That is, although malaria may adversely affect economic activity and lead to poverty, it is also possible that the poor are less able to protect themselves from malaria and less able to seek effective treatment and therefore experience greater morbidity from the disease (Worrall et al. 2005). In order to reduce catastrophic spending on malaria treatment, policy actions to reduce the amount of money paid out-of-pocket should be instituted. The strategies to bring down the socio-economic and geographic inequities in expenditures of malaria treatment will involve priority interventions that will address problems of malaria treatment services amongst the poor SES groups (within urban and rural areas) and the rural dwellers, so as to reduce the overall economic burden on them. This will include promotion of health insurance, which is an efficient means of making medical care affordable and OOPS should be limited to the proportion of the income that society defines as catastrophic in order to protect the poor (Feder et al. 1987). Also, the cost of treatment should be reduced and there should possibly be the abolition of user fees for treatment of malaria for the general population, but especially for the poor and other vulnerable groups. This study was supported by a grant from the Gates Malaria Partnership, London School of Hygiene and Tropical Medicine. The authors are grateful to Professor Anne Mills for helping to develop the study protocols and to the Anambra State Ministry of Health for their collaboration in the work. We are grateful to the anonymous reviewers for their comments. We also thank Laura Fierce for helping to edit the paper.