final-graph

Amidst a sea of reports linking mobile phone usage to various health problems, an alternative analysis I performed using data from The World Bank and UNDP shows that there is actually a positive correlation between the number of mobile phone subscriptions per 100 people and a country’s average life expectancy.

This simple scatterplot shows that on average, most countries where mobile phone subscription increases, life expectancy (for both male and female) also increases. The data from regression analysis describes that 41% of the variance in life expectancy is explained by the number of mobile subscriptions per 100 people. It also shows that the data points are generally within 7 points of the fitted regression line (shown in red). The p-value, which gives us a probability that the regression really does not explain life expectancy, is .000.  If a p-value is less than .05, it is considered statistically significant, since this means that the chance we are wrong in using it is less than 5%.

The statistical data also shows the correlation coefficient to be .64. The correlation can fall anywhere from 0 to 1; 1 being perfect correlation. This doesn’t explain whether one variable causes the other, but simply shows that they are positively correlated. Unfortunately, it’s not possible to make any statistical inference beyond that.

There are two obvious outliers on either end of the data; Cuba, where cell phone ownership is very low (8.9 per 100 people) but life expectancy is higher (78), and South Africa, where there is a relatively higher rate of cell phone ownership (100 per 100 people) but considerably low life expectancy (53.5). Cuba’s position may be explained by their low-cost and nationally accessible healthcare system.

Despite trade and economic setbacks in Cuba on the whole, their life expectancy has continued to rise, and is comparable to the United States. The low life expectancy in South Africa may be caused by the fact that they have the highest number of people living with HIV/AIDS in the world at 5.6 million (2009 est.), and the most deaths caused by HIV/AIDS, at 310,000. The life expectancy is also decreasing; 2012 estimates falling to 50.3 for males and 48.5 for females.

There are multiple factors that can influence an indicator as broad as life expectancy, such as a country’s GDP, access to health care, sanitation, etc. However, it is interesting that as cell phone usage grows, the change in life expectancy is positive. Over time, this relationship may become more pronounced–especially as access to healthcare via mobile platforms grows and as it expands further into emerging markets where the life expectancy is currently lower.

You can also explore these (and many other) variables in an interactive time-lapse graph by GapMinder and see the change in mobile subscriptions from 1980-2008.

 

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