Health screening for emerging non-communicable disease burdens among the global poor: Evidence from sub-Saharan Africa

Abstract

Evidence for the effectiveness of population health screenings to reduce the burden of non-communicable diseases in low-income countries remains very limited. We investigate the sustained effects of a health screening in Malawi where individuals received a referral letter if they had elevated blood pressure. Using a regression discontinuity design and a matching estimator, we find that receiving a referral letter reduced blood pressure and the probability of being hypertensive by about 22 percentage points four years later. These lasting effects are explained by a 20 percentage points increase in the probability of being diagnosed with hypertension. There is also evidence of an increase in the uptake of medication, while we do not identify improvements in hypertension-related knowledge or risk behaviors. On the contrary, we find an increase in sugar intake and a decrease in physical activity both of which are considered risky behaviors in Western contexts. The health screening had some positive effects on mental health. Overall, this study suggests that population-based hypertension screening interventions are an effective tool to improve health in low-income contexts.

Keywords: Health screening; Hypertension; Low-income countries; Malawi; Matching estimator; Non-communicable diseases; Regression discontinuity design.

Figure 1:. Prevalence of high blood pressure (systolic), by sex, 2015 (%, age-standardized)

Source: Adapted from The Economist (2017), based on NCD-RisC Collaboration (2017)

Figure 2:. Blood pressure of respondents of the 2013 MLSFH survey.

Notes: The graphs shows average of the three measures of systolic and diastolic blood pressure for respondents of the 2013 MLSFH-MAC survey. Dots represents mean values of systolic (x-axis) and diastolic (y-axis) blood pressure. Small triangles represent individuals whose maximum systolic blood pressure is at least 160 but their mean systolic blood pressure is below 160. Small red x represent the individuals who were given a referral letter because their diastolic blood pressure is at least 110.

Figure 3:. RDD estimates—Effects of receiving a referral letter on 2013–17 changes in blood pressure, on probability of being hypertensive, diagnosed with hypertension, or treated for hypertension in 2017

Notes: The graphs show average blood pressure outcomes conditional on the maximum systolic blood pressure in 2013. Individuals located to the right of the vertical line received the referral card in 2013. The outcome in the top-left graph represent the average changes in systolic blood pressure from 2013 to 2017. The outcome in the top-middle graph is the average changes in diastolic blood pressure from 2013 to 2017. In the top-right graph, we define someone as being hypertensive if the mean of the three systolic or diastolic blood pressure measurements was greater or equal to 140 and 90, respectively. The outcome in the bottom-left graph is whether individuals got diagnosed by a medical professional in the two years prior to 2017. The outcome in the bottom-right graph is whether individuals are currently taking medication during the follow-up survey in 2017. We employed Mean Square Error (MSE) optimal bandwidth selector and generated the plots above using first order local-polynomial and triangular kernels. Bins are derived optimally using variance evenly-spaced method using spacing estimators (Calonico et al. 2014a,b, 2015, 2017). Each dot represents the means of the respective outcome in a given bin.