Public health and development: Infrastructure, social norms, and health behaviours

4 What does the evidence say?

To learn more about reverse causality and some of the methods that researchers use to address this problem, read Section 5.1 of The Economy 2.0: Macroeconomics.

correlation

A statistical association in which knowing the value of one variable provides information on the likely value of the other, for example high values of one variable being commonly observed along with high values of the other variable. It can be positive or negative (it is negative when high values of one variable are observed with low values of the other). It does not mean that there is a causal relationship between the variables. See also: causality, correlation coefficient.

causality

A direction from cause to effect, establishing that a change in one variable produces a change in another. While a correlation is simply an assessment that two things have moved together, causation implies a mechanism accounting for the association, and is therefore a more restrictive concept. See also: natural experiment, correlation.

reverse causality

A two-way causal relationship in which A affects B and B also affects A.

An important policy question is how public health improvements affect well-being. One way is through productivity and growth: for example, better health correlates positively with income. Governments might therefore prioritize healthcare spending to promote economic growth. Nonetheless, determining causal mechanisms between income and health is complicated, because researchers face a reverse causality problem when studying how public health improvements affect long-term productivity and growth.^1 2 Income positively affects health because it allows individuals to improve their diets and afford better medical care. At the same time, better health improves productivity and performance on income-generating activities, which leads to higher wages. Furthermore, there are confounding factors that simultaneously affect income and health, such as education, environment, and genetic factors. For these reasons, causal evidence of the effect of health on income (either at the aggregate or the individual level) is hard to find.

Hookworms are parasitic worms that infect between 406 and 480 million people globally. A person infected with hookworm passes the eggs in their faeces. People get hookworm infections by walking barefoot on or consuming contaminated soil.

To learn more about the role of women in public health spending, read Section 22.10 of The Economy 1.0.

Still, evidence linking health outcomes to economic outcomes in a causal manner has increased since the 2000s. In the US, political and cultural conditions made possible massive infrastructure investment for major health improvements. For example, the research done by Hoyt Bleakley shows the improvement in economic outcomes in the US South resulting from hookworm eradication in the 1910s.³ School enrolment, attendance, and literacy increased significantly after the intervention. These outcomes are due to better health (less anaemia and lethargy) because students were no longer infected by hookworms. Throughout the US, behavioural changes such as handwashing, boiling water, food washing, and breastfeeding were encouraged via large-scale door-to-door campaigns.⁴ Women also played an important role in these shifts towards better public health: the rise of women’s suffrage in the US was followed by massive changes in public health spending, particularly on children’s healthcare programmes and door-to-door hygiene campaigns, which led to a reduction in child mortality.^5 6

For a comprehensive summary of interventions in low-income countries, and developing countries in general, read Pascaline Dupas and Edward Miguel. 2017. ‘Impacts and Determinants of Health Levels in Low-Income Countries’. In Handbook of Economic Field Experiments Vol. 2. Eds. Abhijit Banerjee and Esther Duflo. North Holland. pp. 3–93.

For a review of causal evidence linking child health and nutrition to educational performance, read Paul Glewwe and Edward A. Miguel. 2007. ‘The Impact of Child Health and Nutrition on Education in Less Developed Countries’. In Handbook of Development Economics Vol. 4. Eds. T. Paul Schultz and John A. Strauss. North Holland. , pp. 3561–3606.

In low-income countries, studies have used various interventions such as deworming, nutritional programmes, and iron supplementation to reduce anaemia to show the link between child health and nutrition and educational performance. For example, school-based deworming programmes in Kenya increased school attendance and grade progression.⁷ Rwanda has implemented a wide range of major health reforms, with positive effects on child mortality.⁸ In Uruguay, a country-wide pay-for-performance scheme helped to increase antenatal care controls.⁹ A similar programme was introduced in Argentina.¹⁰ But more research is needed to understand large-scale health reforms and health-related infrastructure programmes implemented in low-income countries, in line with the literature observed for high-income countries such as the US. Such studies will allow a better understanding of the institutional, organizational, and political economy issues that shape the health sector.

The prospect of low-income countries achieving results similar to those observed in high-income countries during the nineteenth and twentieth centuries is relatively grim. Disease eradication in high-income countries has involved major infrastructure investment and, to a lesser extent, behavioural change. While there are many small interventions in low-income countries with positive treatment effects, a big push in infrastructure investment is needed to magnify these small-scale efforts. Better infrastructure facilitates better health practices. For example, handwashing behaviour and latrine adequacy are facilitated by the availability of clean water. Lack of infrastructure investment (as shown in Figure 7) is one reason why most low-income countries find it difficult to replicate the advances experienced by OECD countries.

This idea is what economists Nick Chater and George Loewenstein call the i-frame and s-frame.^11 12 Many interventions rely on individual behaviours to achieve outcomes (the i-frame), like ‘nudges’ (low-cost, small changes in the decision-making environment) to get vaccinated. However, evidence on how to build and sustain systems and public policies that work (the s-frame) is scarce. The s-frame is important: vaccinations will not be taken if there are not enough clinics offering vaccines, regardless of an individual’s good health behaviour. Institutions to support adequate individual health decisions are also needed. Infectious diseases will not be reduced if individuals cannot afford better sanitation facilities such as desludging pits or water treatment plants.

natural experiment

An empirical study exploiting naturally occurring statistical controls in which researchers do not have the ability to assign participants to treatment and control groups, as is the case in conventional experiments. Instead, differences in law, policy, weather, or other events can offer the opportunity to analyse populations as if they had been part of an experiment. The validity of such studies depends on the premise that the assignment of subjects to the naturally occurring treatment and control groups can plausibly be argued to be random.

To sum up, most existing evidence highlights many behavioural pathways to improve some health outcomes. These interventions have been tested in controlled settings and on a small scale. While the evidence comes mainly from controlled experiments or natural experiments and can therefore be considered causal, researchers and policymakers should focus on investigating whether this evidence can be replicated in other contexts and scaling up promising interventions. The main challenges to scaling up interventions are related to several constraints faced by low-income countries, including low state capacity to implement country-wide reforms, lack of funding, and the complexity of implementing and sustaining behavioural change campaigns.