Health Search Volume by State and Region
Zooming in further, geologically, we can see which states and cities have displayed more interest in searching for health issues online.
Certain regions showed a more significant increase in search interest than others did.
The increase in search activity was greatest in California, Texas, and New York.
One reason could be that Texas and California have two of the largest state populations in the US.
Health Search Volume by Year
It could be observed that the online searching volume of the diseases overall simply showed an increasing tendency
from the line chart. From 2004 to 2017, the data showed that search interest gradually increased over the years.
This result coincides and could be explained by the growth of Internet and technological development in terms of on telehealth.
Health Search in Each State
Overall, it is observed that the online health search interest has been and presumably will be increasing in the United
States, especially in the more metropolitan areas such as New York, California, and Texas.
Apart from the main effects where California, Texas, and New York had the largest overall online search volumes,
it is shown that cancer had been overwhelmingly the most searched health condition among all in most of the states.
The following visualization confirms that cancer's popularity in online search. (Check out the "cancer" arm in the diagram.)
Overall, in terms of the total amount of deaths, the most "deadly" diseases have been malignant neoplasms (i.e.,
tumors) and heart diseases,
as shown in the diagram.
Search Trends of Each Health Condition
How has the online searching interest in each disease changed in themselves per se?
Unsurprisingly, in the multiple line chart, all of the observed diseases demonstrated an upward tendency in online search
over the years from 2004 to 2017 in the United States.
(Hint: In the diagram, you can click on the multiple health conditions of your interest in the legend to highlight and compare them.
Double-click on one disease to see the display of this disease only.)
It appears that diabetes for one has showed one of the most dramatic increases. Assuming
the change of the diabetic population size has been stable, such that the increase in search has mostly been caused by the increasing
popularity of telemedicine,
this upward trend, on the other hand, illuminates the prevalence of diabetes in the United States.
The detailed searching statistics of each disease are displayed below, with the median, the maximum, and the minimum computed.
Furthermore, many diseases tend to have comorbidities; that is, they tend to co-occur with other diseases.
For example, obesity and diabetes often co-occur and in the population are strongly correlated.
Our data illuminates this correlation aspect as well.
Correlations Among the Searches of Health Conditions
So, more comprehensively, how do the searches of the health conditions correlate with each other?
The following diagram shows the online search correlations among all the observed diseases according to our data.
The stonger correlations are in the darker shades.
Notably, the correlations we observed are between "searches", not between "diseases".
For example, we know obesity and diabetes are correlated, but how does the "search volume of obesity" correlate with the "search volume of diabetes",
when they are appear to be independent events of each other?
We assume that this correlation rests not on the searchers or the people per se, but on the inherent association of the two diseases.
That is, when a person does an online research for obesity out of their personal concern (for example, to see if s/he is obese),
s/he is likely to search for diabetes as well, because they might suspect that they have also contract diabetes at the same time,
as obesity and diabetes tend to co-occur.
Importantly, however, correlation of course does not necessarily entail causation,
so some of these correlations might just be coincidental and meaningless.
Our visualization only provides a reference of information, not a confirmation of the relatablity of two diseases.
Therefore, we choose not to interpret too much about the correlation results for the possibility of lurking variables.
Top 10 Leading Causes of Death in Real Life
The following diagram shows the total amount of people (in millions) died of each disease from 2004 to 2017.
Unlike the online search volumes of each disease, the real-life death-causing diseases have shown much more variant changing patterns
over the same period of time.
Diseases such as Cerebrovascular, Diabetes, heart diseases, malignant neoplasms, nephrosis, nephrosis, respiratory diseases,
influenza and pneumonia (not counting the unfortunate year fo 2020 of course) have all been demonstrating a downward change,
i.e., all thing being equal, the amount of people died of those diseases have been decreasing.
The only exceptions include the condition releted to mental health like Suicide and Alzheimer.The number of people died of Alzheimer's disease and suicide have been steadily increasing.
This should flag up attention for people's mental health conditions and the importance of cognitively healthy aging.
According to National Center for Health Statistics's report in 2018,
from 1999 through 2017, the age-adjusted suicide rate increased 33% from 10.5 to 14.0 per million.
Since 2008, suicide has ranked as the 10th leading cause of death for all ages in the United States.
It is deeply worrying trend.
Overall, in terms of the total amount of deaths, the most "deadly" diseases have been malignant neoplasms (i.e., tumors) and heart diseases,
as shown in the diagram.