Topic: Good Health & Wellbeing

Varibles Used :

A researchers tried to understand the difference in health area in cities with varying rates of sustainable development. Municipal Sustainable development index (imds) was used to identify 5 cities with highest and 5 cities with lowest levels of sustainable development in Bolivia. The bar plot was visualized and it was determined that cities with high sustainable development had scores from 70 to 80, while cities with low sustainable development had scores from 30 to 40, showing a significant difference in development.

The heatmap visualization was used to identify healthcare variables that strongly correlated with sustainable development index. It was determined that Children mortality rate and Chronic Malnutrition rates in children are variables that have the strongest and negative correlation with Municipal Sustainable development index in Bolivia areas. Furthemore it was also identified that both Children mortality and Chronic Malnutrition rates have strong and negative relationship with Access to 3 basic services (sanitation, water and energy) and No poverty index (sdg1). As these variables increase, instances of healthcare issues decrease in Bolivia.

Two scatterplot diagrams were created to show the negative relationship between health care indicators (child mortality & malnutrition) and municipal sustainable development index in Bolivia. Both scatterplot graphs also show strong negative correlation between healthcare indicators and sustainable development index in Bolivia.

Barplot visualization was used to analyze the differences in patterns of health variables in 5 cities with the highest levels of sustainable development and 5 cities with the lowest levels of sustainable development. It was determined that there is a significant difference in instances of chronic malnutrition and mortality rates among children between highly developed and least developed cities in Bolivia. Cities with the lowest rates of sustainable development have much higher rates of children mortality and chronic malnutrition than cities with the highest levels of sustainable development.

Next, researchers wanted to understand to what extent a lack of access to basic three services and high poverty rate causes a high instances of child mortality and chronic malnutrition in least developed cities of Bolivia. Furthermore, it was also important to understand if no-poverty and access to three basic services indexes are high in the most developed cities.

Using the bar plot visualization, it was showed that cities with the high sustainable development have relatively high access to sanitation, water and energy. Along with that, the no-poverty index is very high in the most developed areas, which shows that cities with the highest sustainable development levels have low rates of poverty by population. Oppositely, cities with the lowest rate of sustainable development suffer from a lack of access to three basic services and a high poverty, as contribution to the no-poverty goal is very low in such cities.

High poverty rates and lack of access to life-important services causes high instances of child mortality rates and chronic malnutrition rates in Bolivia areas with the lowest levels of sustainable development. Cities with the highest sustainable development levels have a high rates of access to three basic services and low poverty and therefore these cities do not have high rates of children chronic malnutrition and mortality.

This story investigates how a few factors relate to child mortality rates.

I see a variety of features that are closely correlated. I can interpret these features in different groups.

First, the indexes (SDG1 & SDG3 Indexes, and Bolivia Index Ranking) are likely to be created from other variables, which I am unable to find information on. I can speculate that the variables used to create the indexes may be the best predictors for Child Mortality Rate. However, without knowing what goes in, I should not look further into this.

Next, Infant Mortality Rate should not be used as those numbers will be directly included into Child Mortality Rate. This relationship will not provide us with much insight as the same causes of infant mortality will also influence child mortality.

This leaves us with Institutional Childbirth Coverage, Household w/o toilet, etc., Obesity in Women, Access to the 3 Basic Services, Non-Spanish Speaking Population, and Coord_X.

To interpret these, in locations where childbirth coverage or access to the 3 basic services increases, child mortality decreases. This makes sense that additional services lead to a greater survival rate.

Coord_X’s correlation explains that the western side of Bolivia faces greater child mortality. This may be due to geographical features, as the West of Bolivia is very mountainous.

Finally, the remaining features offer insights to high correlations between Child Mortality Rate and low amounts of toilets, etc., less obesity in women, and high non-spanish speaking populations. We can estimate from this that populations facing the most child mortality will likely consist of low spanish speaking populations, low obesity rates, and low amounts of toilets in houses.

A glaring omitted variable that is likely playing a role in all of these correlations is wealth of the communities as wealthier communities often face more obesity, have more toilets, and may also speak more Spanish. However, it is interesting to note that none of the poverty variables had high correlations with Child Mortality, so maybe the variables listed above have a more closely connected relationship than poverty in general.