Linda Mtoto

Child growth faltering often begins in utero or soon after birth and is pronounced in the first 12 to 18 months. It may continue until 40 months and then levels off Grantham-McGregor et al. (2007). Most stunted children become adults of short stature Victora et al. (2008). 21% of global deaths and disability adjusted life-years in children younger than 5 years old globally are attributed to child under-nutrition Black et al. (2008). Sigman et al. (1989) find that in Kenya, there is an association between nutrition and the cognitive skills and attentional behaviour in children.

Malnutrition also has consequences in adulthood. It is estimated that stunted individuals have a reduction of about 66% of their lifetime consumption Hoddinott et al. (2013). Under-nutrition in adults is associated with reduced work capacity and a loss of productivity for both physical and mental labour. Haddad and Bouis (1991) finds that malnourished workers in the Philippines earn less than their counterparts. Bargain and Zeidan (2017) finds that in Indonesia, taller men have a wage premium because they sort into better occupations due to increased human capital. This is a result of higher cognitive skills and higher levels of education.

I attempt to answer the question: Did offering free maternity services improve child well-being? It is expected that increased access to health care improves well-being. Between the 2008-2009 Kenya Demographic and Health Survey (KDHS) Kenya National Bureau of Statistics (KNBS) et al. (2010) and the 2014 survey, Kenya National Bureau of Statistics et al. (2015), there is an increase in the proportion of women receiving antenatal care from a skilled professional from 92% to 96%. The proportion of deliveries which occur in a facility also increases from 43% to 61%. Postnatal care increases from 42% to 53% of women surveyed. The nutritional status of children also improved. In 2008, 35% of children under 5 were stunted but in 2014 this decreased to 26%. 7% were wasted but this declined to 4% and a similar decline from 16% to 11% for underweight children.

I attempt to establish a causal link between the apparent improvement in child well-being and the introduction of the free maternity services policy in June 2013. This policy removed user charges for maternal services in all public facilities countrywide. I also examine whether the increase in skilled birth attendance is a result of the said policy.

Evaluations of the outcomes of healthcare interventions are often conducted using single interrupted time series analyses Baicker and Svoronos (2019). However, this method may produce misleading results if there are other concurrent changes not related to the policy being studied. I instead use a differences-in-differences strategy where the treatment effect is a function of the competitiveness of the healthcare market in the sub-county. The removal of user charges for maternal care in public hospitals in Kenya reduced the costs of receiving antenatal care and skilled birth attendance in public facilities in Kenya. Economic theory predicts that a reduction in price increases the quantity demanded.

I use facility data from the Kenya Health Master Facility List (KMHFL) of 2015 to measure market concentration. This is determined using the Herfindahl-Hirschman Index. I then find the location quotient (LQ) which is the relative competitiveness of a sub-county compared to the county as a whole. Individuals are thereafter assigned to treatment groups based on the competitiveness of the market for healthcare in their sub-county of residence.

In more competitive markets, even small reductions in cost can lead to large increases in demand. Therefore, I expect that competitive markets will have a relatively larger number of deliveries demanded compared to concentrated markets. There should also be greater improvements in child well-being in competitive areas. However, an increase in demand without an equivalent increase in supply may lead to deterioration in quality of services. Thus it is possible that the use of facilities in competitive areas after introduction of the policy led to worse outcomes for children.

My analysis proceeds in two stages. I first find the effect on service utilisation in public facilities: antenatal appointments, deliveries in public facilities and postnatal appointments. Thereafter, I find the effect on child nutrition. To compare the quality of service, I restrict my sample to that of mothers who used public services. Finally, I take into account inequity in access to health by examining the outcomes in marginalised areas. I use the 2014 KDHS data-set to obtain data on individual outcomes before and after the policy.

I find that the probability of attending an antenatal appointment in a public facility increased by 5 percentage points. Similarly, the probability of attending postnatal appointments increased by 5 percentage points. On the other hand, the probability of delivering in a public facility did not change. This is inconsistent with the literature which finds an increase in deliveries. However, some find a level increase in deliveries but not a change in trend Orangi et al. (2021). In marginalised areas, there is an increased probability of attending antenatal and postnatal appointments. However, I find a null effect on the probability of delivery.

On child nutrition, the policy had a null effect. This is also supported by the literature where the impact of the removal of user fees on health outcomes is often ambiguous. Furthermore, my period of study (one year after introduction of the policy) may be too short to witness meaningful change. There is also a null effect on malnutrition. This implies that although the policy was pro-poor, it was insufficient to overcome the barriers that prevent mothers from accessing healthcare during delivery. I also find that providing maternal and neonatal care is insufficient to improve child nutritional outcomes. It is also insufficient to prevent malnutrition even in marginalised areas.

References

Baicker, Katherine, and Theodore Svoronos. 2019. “Testing the Validity of the Single Interrupted Time Series Design.” Working Paper. Working Paper Series. National Bureau of Economic Research. https://doi.org/10.3386/w26080 .

Bargain, Olivier, and Jinan Zeidan. 2017. “Stature, Skills and Adult Life Outcomes: Evidence from Indonesia.” The Journal of Development Studies 53 (6): 873–90. https://doi.org/10.1080/00220388.2016.1208173 .

Black, Robert E, Lindsay H Allen, Zulfiqar A Bhutta, Laura E Caulfield, Mercedes de Onis, Majid Ezzati, Colin Mathers, and Juan Rivera. 2008. “Maternal and Child Undernutrition: Global and Regional Exposures and Health Consequences.” The Lancet 371 (9608): 243–60. https://doi.org/10.1016/S0140-6736(07)61690-0 .

Grantham-McGregor, Sally, Yin Bun Cheung, Santiago Cueto, Paul Glewwe, Linda Richter, and Barbara Strupp. 2007. “Developmental Potential in the First 5 Years for Children in Developing Countries.” The Lancet 369 (January): 60–70. https://doi.org/10.1016/S0140-6736(07)60032-4 .

Haddad, Lawrence J., and Howarth E. Bouis. 1991. “The Impact of Nutritional Status on Agricultural Productivity: Wage Evidence from the Philippines.” Oxford Bulletin of Economics and Statistics 53 (1): 45–68. https://doi.org/10.1111/j.1468-0084.1991.mp53001004.x .

Hoddinott, John, Harold Alderman, Jere R Behrman, Lawrence Haddad, and Susan Horton. 2013. “The Economic Rationale for Investing in Stunting Reduction.” Maternal and Child Nutrition 9 (September): 69–82. https://doi.org/10.1111/mcn.12080 .

Kenya National Bureau of Statistics (KNBS), National AIDS Control Council/Kenya, National AIDS/STD Control Programme/Kenya, Ministry of Public Health and Sanitation/Kenya, and Kenya Medical Research Institute. 2010. “Kenya Demographic and Health Survey 2008-09.” KNBS; ICF Macro. http://dhsprogram.com/pubs/pdf/FR229/FR229.pdf .

Kenya National Bureau of Statistics, Ministry of Health/Kenya, National AIDS Control Council/Kenya, Kenya Medical Research Institute, and National Council for Population and Development/Kenya. 2015. “Kenya Demographic and Health Survey 2014.” http://dhsprogram.com/pubs/pdf/FR308/FR308.pdf .

Orangi, Stacey, Angela Kairu, Lucas Malla, Joanne Ondera, Boniface Mbuthia, Nirmala Ravishankar, and Edwine Barasa. 2021. “Impact of Free Maternity Policies in Kenya: An Interrupted Time-Series Analysis.” BMJ Global Health 6 (6). https://doi.org/10.1136/bmjgh-2020-003649 .

Sigman, Marian, Charlotte Neumann, Ake A. J. Jansen, and Nimrod Bwibo. 1989. “Cognitive Abilities of Kenyan Children in Relation to Nutrition, Family Characteristics, and Education.” Child Development 60 (December): 1463. https://doi.org/10.2307/1130935 .

Victora, Cesar G, Linda Adair, Caroline Fall, Pedro C Hallal, Reynaldo Martorell, Linda Richter, and Harshpal Singh Sachdev. 2008. “Maternal and Child Undernutrition: Consequences for Adult Health and Human Capital.” The Lancet 371 (January): 340–57. https://doi.org/10.1016/S0140-6736(07)61692-4 .