How much do four risks explain US life-expectancy gaps?
Smoking, high blood pressure, high glucose, and adiposity help explain large US life-expectancy disparities across race–place groups (Eight Americas).
Source
The promise of prevention: the effects of four preventable risk factors on national life expectancy and life expectancy disparities by race and county in the United States
What they did
Using risk-factor and mortality data across the Eight Americas, investigators estimated how smoking, SBP, fasting glucose, and BMI contribute to national life expectancy and cross-group disparities.
What they found
These preventable risks are leading mortality drivers and contribute to disparities; bringing them to optimal levels would raise life expectancy and shrink disparity spread (e.g., lowering population-weighted SD of life expectancies).
The limits
What it doesn't show
Modeling attributable effects is not a randomized test of a specific prevention program’s real-world delivery.
Key terms
- Eight Americas
- Race–geography population groupings that capture much of US life-expectancy inequality.
- Preventable risk factors
- Modifiable exposures such as smoking, high BP, high glucose, and adiposity.
- Life expectancy disparity
- Gaps in expected lifespan across social or geographic groups.
- SBP
- Systolic blood pressure.
- FPG
- Fasting plasma glucose, a glycaemia marker.
Flashcards
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Quiz yourself
The four risks include all except:
Common questions
Which four risks?
Smoking, high blood pressure, high blood glucose, and adiposity.
What are Eight Americas?
Defined race–place population units used to study US longevity gaps.
Main equity claim?
These risks contribute to mortality disparities, not only average deaths.
If risks were optimal?
Models suggest higher life expectancy and smaller cross-group spread.
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