The Relationship of Health Aid to Population Health Improvements

Abstract

Importance

Foreign aid to the health sector is an important component of all health spending in many developing countries. The relationship between health aid and changes in population health among aid recipients remains unknown.

Objective

To quantify the relationship between health aid and changes in life expectancy and under-5 mortality among aid recipient nations.

Design

Cross-country panel data analysis of the relationship between longitudinal measures of health aid, life expectancy, and under-5 mortality. Using difference models for longitudinal data with fixed effects for countries and years, we estimate the unique relationship between health aid and changes in life expectancy and under-5 mortality, controlling for gross domestic product per capita, urbanization, and total fertility rate.

Setting and participants

140 aid-recipient countries between 1974 and 2010.

Main Exposures and Outcomes and Measures

The main exposure is the annual amount of development assistance directed to the health sector in constant 2010 US dollars; the principal outcomes are the improvements in under-5 mortality and life expectancy in in the period following aid receipt.

Results

We find that between 1974 and 2010, life expectancy increased by 0.24 months faster (95% CI 0.02-0.46, p=0.03) and under-5 mortality declined by 0.14 per 1,000 live births faster (95% CI 0.02-0.26, p=0.02) with each 1% increase in health aid. We also find that the association between health aid and health improvements has been strengthening over time, with the closest association between 2000 and 2010. We find that health improvements associated with health aid are measurable for 3-5 years after aid disbursement. These findings imply that an increase of $1 billion in health aid could be associated with 364,800 (95% CI 98,400-630,000) fewer under-5 deaths.

Conclusions

Foreign aid to the health sector is related to increasing life expectancy and declining under-5 mortality. The returns to aid appear to last for several years and have been greatest between 2000 and 2010, possibly because of improving health technologies or effective targeting of aid.

Introduction

Whether or not foreign aid promotes development in recipient countries is a topic of substantial debate.^1,2 Proponents of development aid argue that the world's poorest nations are trapped in a cycle of poverty and ill health, and that aid can propel those nations into a cycle of development.³ On the other hand, opponents of foreign aid claim that aid has been associated with delayed development, that it fails to reach its intended recipients, and that it interferes with the incentives for recipients to solve development challenges.⁴

Multiple studies have explored the relationship of foreign aid and economic growth, but there is little empirical evidence about the relationship between aid to the health sector and health outcomes.^5-7 The relative recency of aid to the health sector may explain the paucity of empirical studies: nearly 80% of all health aid documented between 1990 and 2010 was disbursed since 2000, and one analysis of health aid and child mortality examined trends only through 2004.^7,8 A positive relationship between health aid and health may be expected for recent years, when the majority of aid was earmarked for financing relatively new and highly efficacious technologies such as antiretroviral therapy, insecticidal-treated bed nets, and new vaccines.^9-12 On the other hand, misuse and displacement of aid from the health sector may undermine the ability to use these resources for health improvements.¹³ For some diseases like smallpox and polio, the close links between health aid and disease eradication efforts are obvious.¹⁴ We have previously explored the relationship between health aid for HIV and changes in adult and child mortality in Africa.^15,16 However, the overall relationship between health aid and health outcomes remains uncharacterized.

Foreign aid investments from all sources for health improvements in developing countries have grown substantially since 2000. The Institute for Health Metrics and Evaluation's Development Assistance for Health dataset indicates that health aid increased from $5.7 to $9.9 billion per year between 1990 and 1999, and from $10.7 billion to $28.2 billion between 2000 and 2010, an annual growth of approximately 10.2%.^8,17 Between 2007 and 2010 alone, during the global financial crisis, annual health aid increased by nearly $7 billion. In relative terms, health aid increased from approximately 6.8% of all non-military aid in 2000 to 12.9% in 2010.¹⁸ Between 2010 and 2011, however, health aid has plateaued, and future commitments are declining: in the US, the largest health aid donor, federal discretionary spending cuts mean that overall commitments to foreign aid decreasing.¹⁹

Understanding this relationship is important at a time when decisions about foreign aid allocation are facing tightening budget constraints and public discussions about investment priorities increasingly turn on questions of value and impact.²⁰ This paper approaches the issue of health aid effectiveness using broad definitions of health improvements. Our interest is to provide the first-order landscape on the relationship between money and health. While the ultimate causes of health improvements are many and complex, we provide several lines of evidence consistent with a role for health aid in population health improvements.

Methods and Results

This paper proceeds through a series of empirical probes into health aid and population health outcomes. Each analysis builds on limitations and new questions raised by the previous findings. For clarity of exposition, following the description of data sources, we combine the Methods and Results and juxtapose each analysis' approaches and results. The Appendix contains additional descriptions of data sources, variable definitions, model specifications, and sensitivity analyses.

Data Sources

The principal data source for development aid for health is the Organisation for Economic Co-operation and Development's Creditor Reporting System (CRS).¹⁸ Member nations of the Development Assistance Committee, the forum of developed donor nations, report all development assistance grants to the CRS.^21-23 With information on over 2 million grants and loans between 1973 and 2011, the CRS is the most extensive source of primary information on development assistance. We identified health aid disbursements (actual outlays) deflated to 2010 USD by restricting the CRS to those grants with the following keywords in the “purpose name” variable: basic drinking water supply and basic sanitation, basic health care, basic health infrastructure, basic nutrition, basic sanitation, health education, health personnel development, health policy & admin. management, infectious disease control, malaria control, medical education/training, medical research, medical services, population policy and admin. mgmt, reproductive health care, social mitigation of hiv/aids, std control including hiv/aids, tuberculosis control, and family planning.

The CRS is most complete after 2001. An alternative health aid dataset is available from the Institute for Health Metrics and Evaluation. This Development Assistance for Health (DAH) dataset complements CRS data with information from United Nations agencies, foundations, and non-governmental organizations starting in 1990.¹⁷ The DAH also uses data harmonization and imputation techniques to complete missing data.

We use the CRS in the main analyses because of its methodological transparency and longer coverage period. We address the concerns over data completeness with two supplementary analyses: we repeat the analyses using the DAH, and we modify the CRS using information from the DAH and from separate analyses on the pattern of missing data in the CRS (Appendix SA4.5 and 4.6).⁷

We analyze two primary health measures: under-5 mortality and total life expectancy. Total life expectancy numbers come from the United Nations' World Population Prospects, and under-5 mortality, represented as 5q0 (the probability of death before age 5 per 1,000 live births) from the United Nations Inter-agency Group for Child Mortality Estimation (IGME).^24,25 We focus on these measures because of their broad reflection of population health, the extensive efforts to improve their measurement, and their relevance to policy-makers.^26,27 Estimates of both health measures involve demographic transformations of imperfect data, especially for data-poor countries, and we test our findings using alternative data sources (Appendix SA4.7).^28,29

The Association of Health Aid and Health Improvements between 2000-2010

We start with a straightforward exploration of the associations between health aid and health improvements during the era of rapid growth in health aid. Our sample includes all countries that received any health aid between 1974 and 2010 and for which estimates of under-5 mortality and life expectancy exist in our data sources, a total of 140 countries observed over a median of 18 years. We use quartiles of total health aid received between 2000 and 2010 by country to examine the association (we also examine the association with health aid per capita in Appendix SA4.1). Over the decade between 2000 and 2010, we observe a consistent pattern of greater improvements in life expectancy and child mortality associated with greater amounts of total or per capita health aid (Figure 1 and Appendix SA4.1). These findings were also apparent when using health aid as a continuous instead of a categorical variable (Appendix SA4.2).

Figure 1.

Health improvements in the decade from 2000 to 2010 by total health aid quartile (1 is the lowest health aid quartile, 4 is the highest). Panel A shows the mean increase in total life expectancy. Panel B shows the mean reduction in under-5 mortality, defined as the probability of death before age 5 per 1,000 live births. Error bars represent 95% confidence intervals.

In 2000, life expectancy was 69.8 (SD 4.7) in the lowest aid quartile countries, and 57.5 (SD 9.5) in the highest aid quartile countries; over the next decade, life expectancy increased by 2.7 years in the lowest aid quartile group and 4.8 years in the highest aid quartile group. Under-5 mortality averaged 31.6 per 1,000 (SD 25.7) in the lowest aid quartile countries and 109.2 per 1,000 (SD 53.6) in the highest aid quartile countries in 2000; over the next decade, under-5 mortality decreased by 8.4 per 1,000 in the lowest aid quartile and 36.8 per 1,000 in the highest aid quartile (Table 1).

Table 1. Summary Statistics.

Measure	Aid quartile	1990	2000	2010	Total
		Mean (SD)	Mean (SD)	Mean (SD)	Mean (SD)
Life expectancy
	1	67.5 (5.4)	69.8 (4.7)	72.5 (4.5)	69.9 (5.3)
	2	63.1 (8)	65 (9)	67.8 (8.8)	65.3 (8.8)
	3	59 (10)	60.9 (10.1)	63.9 (9.6)	61.3 (10)
	4	55.7 (8.8)	57.5 (9.5)	62.3 (8)	58.5 (9.1)
Under-5 mortality
	1	43.6 (33.4)	31.6 (25.7)	23.2 (19.7)	32.8 (27.9)
	2	75.4 (54.4)	60.4 (48.4)	43.9 (39.1)	59.9 (49)
	3	115.1 (78.1)	92.2 (65.5)	64.3 (51)	90.5 (68.4)
	4	132.5 (59.7)	109.2 (53.6)	72.4 (40.3)	104.7 (57)
GDP per capita (2010USD)
	1	4806 (3712)	5831 (4301)	6925 (5014)	5875 (4427)
	2	1947 (1324)	2098 (1717)	3113 (2919)	2380 (2134)
	3	1494 (1393)	1566 (1653)	2055 (1963)	1707 (1690)
	4	689 (876)	808 (862)	1020 (1126)	845 (966)
Total Fertility Rate
	1	4 (1.5)	3 (1.1)	2.6 (0.9)	3.2 (1.3)
	2	4.1 (1.6)	3.4 (1.6)	3 (1.4)	3.5 (1.6)
	3	5.1 (1.8)	4.3 (1.9)	3.7 (1.7)	4.4 (1.9)
	4	5.6 (1.3)	4.8 (1.6)	4.1 (1.5)	4.9 (1.6)
Urban (%)
	1	48.4 (21)	52.1 (21.8)	55 (22.8)	51.8 (21.9)
	2	48.4 (18.7)	50.8 (19.1)	53.9 (19.3)	51 (19)
	3	38.2 (18.1)	42.1 (19.2)	46.1 (19.6)	42.1 (19.1)
	4	30 (17.1)	33.6 (16.7)	37.7 (17.1)	33.8 (17.1)

Targeting of Health Aid to Countries on a Trajectory of Improvement

One potential explanation for these findings is that aid was directed to countries already on a trajectory of improvement, and therefore the observed effect is unrelated to aid. To explore this possibility, we examine whether health improvement trajectories preceded aid receipt between 2000 and 2010. In Figure 2 we show the health improvement trajectories during the preceding two decades (1980-1990 and 1990-2000) by quartile of aid receipt after 2000. The figure suggests that the positive association between health aid quartile and life expectancy is most apparent for the 2000-2010 period, and not apparent in the previous decades. This is supported statistically: non-parametric tests for trend of life expectancy changes across the health aid quartiles based on the Wilcoxon rank-sum test between 1980-1990, 1990-2000, and 2000-2010 (separate model for each decade) favors a trend during the decade between 2000-2010 (p<0.001) and fails to support a trend during the previous periods (p=0.63 for 1980-1990 and p=0.90 for 1990-2000).

Figure 2.

Association between quartile of total health aid and changes in life expectancy and under-5 mortality by decade between 1980 and 2010. The quartiles are calculated from the total health aid between 2000 and 2010 (1 is the lowest health aid quartile, 4 is the highest). Panel A shows life expectancy, and panel B shows under-5 mortality. A positive association with improving life expectancy and declining under-5 mortality is most apparent between 2000 and 2010. The figure suggests that pre-existing trends in the association between health aid and health improvements do not explain the association in the 2000s.

The findings for child mortality show that receipt of aid between 2000 and 2010 was associated with declines between 2000 and 2010 (p<0.001). The trends between 1990 and 2000 approach statistical significance (p=0.08) and display a weak association with health aid quartile (Figure 2b), but not between 1980 and 1990 (p=0.51). That is, it is possible that health aid after 2000 was targeted to those countries with greater child mortality declines during the previous decade.

The Evolving Relationship Between Health Aid and Health Improvements

The previous analyses are suggestive of the role of health aid, but only study the association by aid amounts over time. Other factors such as economic development may enable adoption of more effective health-improving interventions and greater investments in health, either privately or through public-sector investments. Moreover, convergence theory suggests that poorer countries develop faster than (converge towards) wealthier countries, and thus targeting aid to the poorest countries could appear to be associated with differential trends in life expectancy and under-5 mortality.³⁰ In addition, decadal associations may fail to detect underlying trends and non-linear temporal associations.

To study these issues, we fit the following first-difference model to a country-year panel dataset with information on life expectancy, under-5 mortality, and health aid to each country i in year t:

$$H_{it}-H_{it-1}={\beta }_0+{\beta }_1{\mathit{\text{Aid}}}_{it}+{\beta }_2{\mathit{\text{GDPpc}}}_{it}+{\beta }_3{\mathit{\text{Urban}}}_{it}+{\beta }_4{\mathit{\text{TFR}}}_{it}+{\eta }_i+{\delta }_t+{\varepsilon }_{it}$$ (1)

In the model, H_it represents our measures of health – life expectancy or under-5 mortality (fit separately). H_it–1 is a 1-year lag of the health measure, and their difference represents the change in the specified health measure; we included one lag after examination of autocorrelation plots suggested the data was stationary with one autoregressive component.³¹ Aid_it is the log of the total health aid, GDPpc_it is the log of GDP per capita, Urban_it is the percent living in urban environments, TFR_it is the total fertility rate, and η_i and δ_t are country and year fixed effects. ε_it is the error term. The main parameter of interest is the coefficient on the Aid_it term. Because Aid_it is logged, the coefficient can be interpreted as the change in the health outcome with each 1% increase in health aid. Data for health aid and health outcomes from 1974 to 2011 was used in this analysis.

This modeling approach estimates the relationship between the total amount of aid and changes in health outcomes. The three principal covariates represent time-varying measures with direct relevance to human and economic development that were available for the entire study period. Relevant indicators of health system performance such as antenatal care attendance or government health expenditures were available for fewer than half the observations, and were not used. Female educational attainment was available through 2009 and used in a sensitivity analysis (Appendix SA4.8). We weighted the models by population size and calculated robust standard errors throughout.

Our estimates suggest that, over the period from 1974 to 2011, each 1% increase in health aid was associated with 0.24 months greater increase in life expectancy (p=0.03) and 0.14 faster decline in the probability of under-5 deaths per 1,000 live births (p=0.02). Neither urbanization, total fertility rate, nor GDP per capita were significantly associated with improvements in life expectancy or under-5 mortality. It is important to note that the relationship of health improvements with within-country changes in these covariates is not well characterized and differs conceptually from the large cross sectional differences in health by GDP per capita or fertility rates. For example, some evidence suggests that within-country health improvements may occur more rapidly during times of poor economic growth.³²

The rise of health aid has been most dramatic since 2000. We examine the extent to which health aid during the decade between 2000 and 2010 was associated with unique improvements in life expectancy and under-5 mortality by fitting models similar to the model specified above where the main coefficients of interest are on interaction terms between decade dummies and the log health aid variable. We note an increasingly strong association over the four decades, such that each 1% increase in health aid was associated with 0.76 (95% CI 0.21-1.31) fewer under-5 deaths per 1,000 live births between 2000 and 2010 (p=0.01) but only 0.27 (95% CI -0.17-0.70) fewer deaths between 1980 and 1989 (p=0.22; Table 2).

Table 2. Relationship of health aid on life expectancy and under-5 mortality.

Outcome	Change in life expectancy, mo	Change in under-5 mortality, 5q0	Decade interactions2
			Change in life expectancy, mo	Change in under-5 mortality, 5q0
Health aid (log USD)	0.24	-0.14
	(0.03)	(0.02)
Period effect 1980-1989			0.80	1.57
			(0.44)	(0.11)
Period effect 1990-2000			-0.43	1.75
			(0.83)	(0.14)
Period effect 2000-2010			-0.39	1.19
			(0.90)	(0.47)
Health aid prior to 1980			-0.76	0.34
			(0.04)	(0.11)
Health aid 1980-1989			0.52	-0.27
			(0.17)	(0.22)
Health aid 1990-1999			1.12	-0.63
			(0.00)	(0.02)
Health aid 2000-2010			1.52	-0.76
			(0.00)	(0.01)
GDP per capita (log USD)	-1.81	0.16	-2.81	0.59
	(0.14)	(0.77)	(0.05)	(0.38)
Urban (%)	-0.09	-0.03	-0.03	-0.06
	(0.18)	(0.48)	(0.63)	(0.20)
Total fertility rate	0.94	-0.16	0.88	-0.06
	(0.23)	(0.71)	(0.26)	(0.89)
Observations	2,502	2,507	2,502	2,513
R-squared	0.10	0.18	0.13	0.08
Number of countries	136	138	136	138
Country fixed effects	Yes	Yes	Yes	Yes
Year fixed effects	Yes	Yes	Yes	Yes

Notes:

¹The values in the table represent the coefficients from regression analysis, and the values in parentheses represent the p-value around the coefficient.

²The analysis with decade interactions tests the extent to which the association between health aid and health outcomes changed over the decades from the 1970s to the 2000s. The regression used to estimate this relationship can be represented as. $H_{it}-H_{it-1}={\beta }_0+{\beta }_1{\mathit{\text{Aid}}}_{it}+\sum _{d=1}^4{\alpha }_d{\mathit{\text{Decade}}}_d+\sum _{d=1}^4{\gamma }_d{\mathit{\text{Decade}}}_d\times {\mathit{\text{Aid}}}_{it}+\cdots (\mathit{\text{GDPpc}},\mathit{\text{Urban}},\mathit{\text{and TFR as above}})$. In this specification, each decade is coded as binary dummy variable. The main effects on the “Decade” dummies represents the changes in the outcome in the decade relative to the base period in the 1970s in the absence of any health aid. Thus, life expectancy increased more in the 80s compared with the 70s, but less in the 90s and 2000s compared with the 70s. Similarly, under-5 mortality has declined less in each subsequent decade compared with the 70s. The coefficients on the decade-aid interactions indicate the health improvements associated with 1% increase in health aid during the decade. The main effect on the “Aid” variable (β) represents the effect of aid in the 70s. This analysis suggests that health aid was associated with life expectancy losses during the 70s, but has been associated with life expectancy gains and under-5 mortality improvements in the 1990s and 2000s. These improvements have been greatest in the 2000s, such that each 1% increase in health aid has been associated with greater life expectancy gains and under-5 mortality declines in the 2000s compared with prior decades.

This information can be used to estimate the number of under-5 deaths that could be averted in association with an additional $1 billion in health aid, approximately a 4% increase over current levels. About 120 million births took place in the study countries in 2011.³³ A 4% increase in health aid, then, would be associated with a decline of 0.76×4=3.04 deaths per 1,000 live births (95% CI 0.82-5.25), or 364,800 fewer under-5 deaths (98,400-630,000).

Finally, to examine the temporality of the association, we performed a Granger-causality test. This test helps with determining the time directionality of an association between two variables.³⁴ This test suggests that the temporal pattern favors a path from health aid to health improvements rather than vice versa (Appendix SA4.3).

The Lasting Effects of Health Aid

The benefits of effective health aid may last beyond the year in which it is committed or disbursed. Aid grants are often spent over several years, and additional delayed effects may be due to lags in the provision of health services and the realization of health benefits over time. We examined this phenomenon by running the primary regression model above with health aid lags of varying lengths. The model with each lag was fit separately. Figure 3 shows the lasting association between health aid and health improvements. The association of health aid with both life expectancy and under-5 mortality fades gradually. The Figure suggests that in our data, health aid remains significantly associated with under-5 mortality reductions for up to three years, and up to five years for overall life expectancy.

Figure 3.

The strength of the association between health aid and health improvements with increasing time lag between aid disbursement and health outcome. Each point in the figure is the coefficient (and 95% confidence intervals) on aid from a regression of the change in life expectancy or under-5 mortality on lagged health aid. The x-axis indicates the lag. The graph shows a gradual decline in the relationship of aid with both outcomes, suggesting a lasting relationship between health aid and health improvements.

The analytic code for all the investigations reported in the paper is available from the authors upon request. The sponsor of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Discussion

This exploration of the relationship between health aid and health improvements provides consistent evidence supporting the position that health aid has played a role in the extension of life expectancy and the reduction of under-5 mortality, especially since 2000. For practitioners of global health programs supported by health aid, this outcome may confirm the links between the observed health improvements and the large expansion of activities over the past decade. For development and policy analysts, these findings could provide evidence supporting aid effectiveness in the health sector.

While this analysis only provides suggestive associations, the potential drivers of this relationship are worth noting. Health aid directed for HIV has increased by over $6 billion dollars between 2000 and 2010, more than twice the increase to any other health sector. The population-level mortality decline associated with health aid for HIV and the provision of antiretroviral therapy have been previously demonstrated.¹⁵ In comparison, aid targeted for malaria, maternal, newborn, and child health had started increasing prior to 2000, potentially explaining the observed association between aid and under-5 mortality in the 1990s as well as after 2000.

We also observe that the link between health aid and health improvements was strongest between 2000 and 2010. Increasing returns to aid would be expected if each dollar spent were associated with greater health benefits. Two dynamics may help explain increasing returns to health aid: improved targeting, and improved health technologies. Targeting could have been improved through better geographical allocation enabled by data about the distribution of disease.³⁵ It could also have been achieved through improved disease targeting. While many studies highlighted the mismatches between disease-specific aid and overall disease burden, our findings suggest that aid was spent more efficiently between 2000 and 2010 compared with the 1990s.^36,37 In that sense, the disease-specific funding structures that dominated the 2000s may have been more efficient at reducing mortality than previous approaches to health aid allocation.

In addition, improved health interventions enabled each dollar invested to translate into greater health improvements. Antiretroviral therapy, insecticide-treated bed nets, and the expansion of directly observed treatment short course (DOTS) for tuberculosis have been mainstays of aid-financed interventions over the past 20 years. Health aid for malaria, for example, has been shown to be associated with expanded use of insecticide-treated bed nets and credited with reductions in under-5 mortality.^38,39

While this study's findings are consistent with our hypothesis that health aid has been an important driver of health improvements, the data and methodological limitations of this analysis deserve additional consideration. The life expectancy and under-five mortality estimates come from trusted sources, but the underlying data quality used for generating these estimates is limited in comparison with mortality data available in more developed countries. Most low- and middle-income countries lack vital and health registration systems, and this study's outcomes often rely on household surveys and sophisticated demographic approaches. To the extent that alternative demographic approaches account for different shortcomings of the underlying data, this study's findings are stable to alternative sources of health outcome estimates.

An important issue is the possibility that health aid and health in the recipient countries have changed contemporaneously but not causally. That is, other causal factors could explain the observed health improvements. We attempted to address this possibility by controlling for common time trends and for time-varying covariates that capture broad concurrent trends such as economic development and declining fertility, and none of these meaningfully modified the independent effect of health aid. Alternatively, a bi-directional relationship where health aid is allocated at least partly in response to health needs may bias the main estimator. The direction of the bias is unclear, but if donors prioritize countries with poor health, this analysis may underestimate the true effect size. Finally, the choice of first-difference models and Granger directionality tests aim to relax this concern.

The evidence we present is correlational but consistent: health aid is closely linked to improvements in life expectancy and under-5 mortality, the relationship has strengthened after 2000, and health aid investments are associated with health improvements that are measurable for 3 to 5 years. These findings have implications for the overall allocation of foreign aid as well as for health aid prioritization. To the extent that health improvements have implications for economic development, investing in health could have important returns for donors as well.⁴⁰