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GENDER BIAS KEEPS MORTALITY RATES OF NEW MOTHERS HIGH

In countries where there are still strong prejudices against women, mortality rates of new mothers remain high despite the easy availability of post-partum treatment. Research by Sonia Bhalotra and Joseph Gomes, to be presented at the Royal Economic Society”s 2015 annual conference, shows that higher maternal mortality rates – as well as lower life expectancy advantages for women over men – are a direct consequence of gender bias.

Their study analyses differences in the maternal mortality rates and life expectancy advantages of women across countries – and links the differences to three measures of gender prejudice: one based on centuries old gender attitudes revealed by language; the second based on parents” expressed preference for sons over daughters; and the third based on policies enacted in support of women”s rights.

According to the research:

• The rate at which new mothers die and the life expectancy of women vary a lot across countries and over time. For example, in 2000, the maternal mortality rate in India was 390 per 100,000 births, while it was 84 in Brazil, which adopted women-centric health programmes earlier.

• This variation in maternal mortality rates and life expectancy can be explained by varying degrees of gender prejudice across nations after controlling for economic and cultural factors. The mortality rates of new mothers increase as gender bias increases.

• All three measures show that the more gender inequality there is, the higher the rate of maternal mortality. For example, a one standard deviation increase in the preference for a male child over a female child – roughly the difference between India and Zimbabwe – is associated with 90 additional maternal deaths and decreases the average female life expectancy advantage by 7.8%.

Sonia Bhalotra comments:

”Reducing maternal mortality may be low on a list of global health priorities because it is woman-specific.

”Yet it has very significant effects. There is evidence that lower maternal mortality not only contributes to raising female life expectancy and improving child outcomes, it also contributes to raising women”s education, labour force participation and fertility – and boosts economic growth.”

More…

Maternal mortality rates (MMR) have fallen sharply in the last decade but still remain unnecessarily high, at around 800 deaths a day. The average MMR in low-income countries in 2010 was estimated to be 452 deaths per 100,000 births, similar to the rates that prevailed in England and Wales in 1930 before the introduction of antibiotics. This is pertinent given that 40-50% of maternal deaths are on account of post-partum puerperal sepsis, which is treatable with antibiotics. Infant mortality, which is also largely determined by infectious disease, claimed policy attention much earlier and, apparently with more commitment.

This study investigates whether the relative neglect of maternal mortality stems from gender prejudice: MMR may be low on a list of global health priorities because it is woman-specific. Although there appears to be no systematic test of this hypothesis, it is consistent with some anecdotal evidence.

For example, in 2000, MMR in India was 390 deaths per 100,000 and women”s life expectancy advantage was 0.59 years. In stunning contrast, MMR in Brazil was 84 and women”s life expectancy advantage was 6.1 years. Brazil adopted the Right to Health and implemented universal health coverage and an emphasis on women”s health ahead of other poor countries.

The research shows that female and male life expectancy each exhibit a snug linear fit to income in country*year data, but that the ratio of female to male life expectancy (and MMR, which contributes to this ratio) exhibit a weaker relationship with income. In the OECD, the average female advantage in life expectancy during 1960-2011 is 6 years. In sub-Saharan Africa, it is 2-3 years, and in South Asia, it is close to zero. Overall, there is massive variation in MMR (and the gender gap in life expectancy) across countries and years conditional on income.

The researchers” hypothesis is that this variation is a function of gender prejudice. The challenge in testing this is to find changes in gender inequality that occur exogenously, that is, independently of factors that may directly influence changes in MMR. In previous work, the researchers show that exogenous increases in women”s education created by education programmes are associated with large declines in MMR (Bhalotra and Clarke, 2013).

The new study uses two approaches. First, its rest on the premise that language structure embeds gender differentiation (Givati and Troiano, 2012), and uses variation in language at birth to proxy deep-set (centuries old) gender attitudes. Second, it uses cohort-country variation in (a) stated son preference from cross-country fertility surveys and (b) institutionalised political, economic and social rights of women, relying on the variation within countries over time to avoid the problem that differences in gender prejudice across countries may be correlated with all sorts of other cultural and economic factors that predict MMR but not necessarily through prejudice.

The results reveal that for each of the three measures of gender inequality, that MMR is increasing in gender inequality.

Consider, for example, women”s reported desired sex ratio (DSR) of their births, an indicator of son preference that, unusually, is available across countries. The study creates cohort variation within countries by exploiting the fact that women of different birth cohorts are respondents in the surveys. A DSR of one implies gender-neutral child preferences, while a desired sex ratio of greater than one implies son preference and the magnitude of the measure gives the degree of son preference.

South Asian countries have a very high degree of son preference with Pakistan (1.52), Nepal (1.5) and India (1.39) occupying 3 out of the top 5 spots. A one standard deviation increase in DSR, which is roughly the difference in DSR between Zimbabwe or Congo and India, reduces the female life expectancy advantage by 7.8% of its mean, and leads to 90 additional maternal deaths, which is around 20.5% of the mean MMR in the sample. Moreover, under gender-neutral preferences, girl infants have a 1.4 percentage point lower probability of dying than their male counterparts, but a one standard deviation increase in son preference lowers the girl infant survival advantage by 61%.

The investigations use tuberculosis (TB) as a placebo disease, a disease that, in general, is as likely among men as among women. There are no impacts of DSR or the other measures of gender prejudice on TB rates.

MMR decline not only contributes to raising female life expectancy and improving child outcomes, it also contributes to raising women”s education (Jayachandran and Lleras-Muney, 2009), labour force participation (Alabanesi and Olivetti, 2009), fertility (Bhalotra et al, 2014) and economic growth (Amiri and Gerdtham, 2013).

International policy initiatives directed at MMR reduction began as late as 1987 with the Safe Motherhood Initiative (Hogan et al, 2010), and commitment was enhanced after the 1994 International Conference on Population & Development selected MMR set as a Millennium Development Goal. While progress was initially limited, there were substantial declines in MMR in the 2000s. But rates of decline varied a lot across countries.

Sonia Bhalotra

srbhal@essex.ac.uk

Joseph Gomes

jgomes@essex.ac.uk

References

Albanesi, S. and C. Olivetti (2009). Gender roles and medical progress. Working Paper,
National Bureau of Economic Research.

Amiri, A. and U.-G. Gerdtham (2013). Impact of maternal and child health on economic growth: New evidence-based Granger causality and DEA analysis. Available at: http://www.who.int/pmnch/topics/part_publications/201303_Econ_benefits_econometric_study.pdf .

Bhalotra, Sonia and Clarke, Damian (2013). Maternal Education and Maternal Mortality: Evidence from a Large Panel and Various Natural Experiments. Mimeo, Universities of Essex and Oxford.

Bhalotra, Sonia; Hollywood, David; and Venkataramani A. (2014). Fertility, Health Endowments and Returns to Human Capital: Quasi Experimental Evidence from 20th Century America. Mimeo, University of Essex.

Givati, Y. and U. Troiano (2012). Law, economics, and culture: Theory of mandated benefits and evidence from maternity leave policies. Journal of Law and Economics 55 (2), 339-364.

Jayachandran, S. and A. Lleras-Muney (2009). Life expectancy and human capital investments: Evidence from maternal mortality declines. Quarterly Journal of Economics, February 2009, vol 124 (1), pp. 349-397.