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Personal Insights
Author's profile photo David Lomanno

SocialHero: Good Health and Well-being

For the SAP contest, I initially was working with UN goal 2: Zero Hunger, but I changed my target goal to Goal 3: Health and Well Being.  During my analysis of the data I had aggregated, I realized my data better fit goal 3.

Within goal 3, I examined two key points:

  • By 2030, reduce the global maternal mortality ratio to less than 70 per 100,000 live births
  • By 2030, end preventable deaths of newborns and children under 5 years of age, with all countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live births and under-5 mortality to at least as low as 25 per 1,000 live births

Data Sources: World Data Bank, UN’s website

Visualizations & Key Insights

When the two sets of data were combined, the regression line and ANOVA showed that having a skilled medical staff was correlated with a reduced the rate of maternal death by 50 mothers per thousand.  (R^2 = 0.655, adj R^2 = 0.654)

Note that the two top charts are inverted, with higher percentages of people out of school on the left.  In the case of both primary and secondary school, a higher percentage of children out of school is significantly correlated with a higher child mortality rate.

On the bottom graph x-axis extends from under a thousand to just under the equivalent of two thousand US Dollars at 2010 levels, inflation adjusted.  At zero, the chart showed a death rate of about forty deaths per thousand.  At about thirty-five thousand dollars of income the mortality rate was effectively zero.

Within multiple linear regression, these three factors had a major impact.  For every ten percent of students in school, the mortality rate lowered by one percent.  And for every thousand dollars in income, the mortality rate lowered by two and a half percent.  (R^2 0.735, adj R^2 0.735)

What was surprising to me though was the first graph.  Across the globe, the number of skilled medical staff had no bearing on the mortality rate of newborns, until put into the context of other data.  When I ran multiple linear regression on that data, I was very surprised to find that skilled nurses and doctors made a material different on maternal mortality rates.  This tells me that there is more analysis to be done.

Applications of this Data

The data shows that the best way the UN can improve the chances of a infant surviving is to have them go to school.  Education is not only a way out of poverty, but also a way to ensure a physically safe environment for children in general across the world.

For the maternal death rates, the best course of action is to have well trained medical practitioners on staff ready to help. The UN and volunteer organizations could both help by sending people to places where skilled medical practitioners are not common.

SAP can help by sponsoring education.  I personally believe that SAP’s best course of action would be to encourage their employees to volunteer at schools and help tutor and teach students.

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