When you become data curious you begin to notice the vagueness of descriptors and measures in the clinical and political literature. I see surveys where the very thing they intend to measure lacks a definition. Or headlines lacking clarification of what the numerator and denominator might be in their claim. Alarming reductions and increases in benefits or risks lack context but still our heart rates increase and we lean into the new normal of agitation and fear.
We can become data literate and seek the answers we need. As an analyst, if I am asked to discuss poverty for example, this requires a longer, deeper and often existential conversation.
We have advanced in our understanding of the complexity of poverty. Not unlike how we talk about health and social correlates of health, poverty is not simply one thing. When we analyze a numerical variable and consider those values as representative of our analyses we are being short-sighted. The categorical variables need to be included as well.
"...deprivation comes in many forms and use a new multi-dimensional measure that not
The U.S. income data determines the poverty level and from there federal aid is indexed and provided for a variety of programs such as SNAP, health insurance, etc... "a lot of power for a statistic that is out of touch with reality" as described by the New York Times back in 2001.
A simple tool within US Census called Abacus will let you examine 2 variables at the US or state level over a specific time on your mobile device!
I rely on the American Community Survey to explore expanded measures of poverty. I prefer my analyses outside of the IPUMS website and rely on Python or Tableau Prep to quickly clean up data from the larger dataset.
You can observe below how the expanded Household-Economic Characteristics contribute additional granularity to discussions of poverty--beyond a simple calculation that allocates a household either above or below an arbitrary income cut-off.
I plan to dig into the census data more and more over the coming months. It is an under-utilized resource in our discussions about healthcare inequality and a granular understanding of the societal poverty line and determinants of health.
*I love the musings of what data is from this website--key concepts in information and knowledge--defining data. I am aware of datum as singular and data as plural but defer to common usage.
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In a world of "evidence-based" medicine I am a bigger fan of practice-based evidence.
Remember the quote by Upton Sinclair...
“It is difficult to get a man to understand something, when his salary depends upon his not understanding it!”