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Introduction
“Cash can’t purchase happiness.” “You possibly can’t decide a guide by its cowl.” “An apple a day retains the physician away.”
You’ve most likely heard these sayings a number of occasions, however do they really maintain up after we have a look at the info? On this article sequence, I need to take fashionable myths/sayings and put them to the check utilizing real-world information.
We would verify some sudden truths, or debunk some fashionable beliefs. Hopefully, in both case we are going to acquire new insights into the world round us.
The speculation
“An apple a day retains the physician away”: is there any actual proof to help this?
If the parable is true, we should always anticipate a unfavorable correlation between apple consumption per capita and physician visits per capita . So, the extra apples a rustic consumes, the less physician visits folks ought to want.
Let’s look into the info and see what the numbers actually say.
Testing the connection between apple consumption and physician visits
Let’s begin with a easy correlation test between apple consumption per capita and physician visits per capita.
Knowledge sources
The information comes from:
Since information availability varies by yr, 2017 was chosen because it offered probably the most full when it comes to variety of international locations. Nonetheless, the outcomes are constant throughout different years.
Visualizing the connection
To visualise whether or not increased apple consumption is related to fewer physician visits, we begin by a scatter plot with a regression line.
The regression plot exhibits a really slim unfavorable correlation, that means that in international locations the place folks eat extra apples, there’s a barely noticeable tendency to have decrease physician visits. Sadly, the pattern is so weak that it can’t be thought of significant.
OLS regression
To check this relationship statistically, we run a linear regression (OLS), the place physician visits per capita is the dependent variable and apple consumption per capita is the unbiased variable.
The outcomes verify what the scatterplot recommended:
The coefficient for apple consumption is -0.0107, that means that even when there’s an impact, it is rather small.
The p-value is 0.860 (86%), excess of the usual significance threshold of 5%.
The R² worth is sort of zero, that means apple consumption explains just about not one of the variation in physician visits.
This doesn’t strictly imply that there isn’t a relationship, however relatively that we can’t show one with the accessible information. It’s attainable that any actual impact is simply too small to detect, that different components we didn’t embody play a bigger function, or that the info merely doesn’t replicate the connection effectively.
Controlling for confounders
Are we finished? Not fairly. Thus far, we’ve solely checked for a direct relationship between apple consumption and physician visits.
As already talked about, many different components may very well be influencing each variables, doubtlessly hiding a real relationship or creating a synthetic one.
If we think about this causal graph:
We’re assuming that apple consumption immediately impacts physician visits. Nonetheless, different hidden components may be at play. If we don’t account for them, we danger failing to detect an actual relationship if one exists.
A well known instance the place confounder variables are on show comes from a research by Messerli (2012), which discovered an fascinating correlation between chocolate consumption per capita and the variety of Nobel laureates.
So, would beginning to eat numerous chocolate assist us win a Nobel Prize? In all probability not. The possible clarification was that GDP per capita was a confounder. That signifies that richer international locations are inclined to have each increased chocolate consumption and extra Nobel Prize winners. The noticed relationship wasn’t causal however relatively on account of a hidden (confounding) issue.
The identical factor may very well be taking place in our case. There may be confounding variables that affect each apple consumption and physician visits, making it troublesome to see an actual relationship if one exists.
Two key confounders to think about are GDP per capita and median age. Wealthier international locations have higher healthcare techniques and totally different dietary patterns, and older populations have a tendency to go to docs extra usually and will have totally different consuming habits.
To regulate for this, we alter our mannequin by introducing these confounders:
Knowledge sources
The information comes from:
OLS regression (with confounders)
After controlling for GDP per capita and median age, we run a a number of regression to check whether or not apple consumption has any significant impact on physician visits.
The outcomes verify what we noticed earlier:
The coefficient for apple consumption stays very small(-0.0100), that means any potential impact is negligible.
The p-value (85.5%) continues to be extraordinarily excessive, removed from statistical significance.
We nonetheless can’t reject the null speculation, that means now we have no robust proof to help the concept that consuming extra apples results in fewer physician visits.
Similar as earlier than, this doesn’t essentially imply that no relationship exists, however relatively that we can’t show one utilizing the accessible information. It may nonetheless be attainable that the actual impact is simply too small to detect or that there are but different components we didn’t embody.
One fascinating remark, nevertheless, is that GDP per capita additionally exhibits no vital relationship with physician visits, as its p-value is 0.668 (66.8%), indicating that we couldn’t discover within the information that wealth explains variations in healthcare utilization.
Alternatively, median age seems to be strongly related to physician visits, with a p-value of 0.001 (0.1%) and a constructive coefficient (0.4952). This implies that older populations have a tendency to go to docs extra often, which is definitely not likely stunning if we give it some thought!
So whereas we discover no help for the apple fable, the info does reveal an fascinating relationship between growing old and healthcare utilization.
Median age → Physician visits
The outcomes from the OLS regression confirmed a robust relationship between median age and physician visits, and the visualization under confirms this pattern.
There’s a clear upward pattern, indicating that international locations with older populations are inclined to have extra physician visits per capita.
Since we’re solely median age and physician visits right here, one may argue that GDP per capita may be a confounder, influencing each. Nonetheless, the earlier OLS regression demonstrated that even when GDP was included within the mannequin, this relationship remained robust and statistically vital.
This implies that median age is a key consider explaining variations in physician visits throughout international locations, unbiased of GDP.
GDP → Apple consumption
Whereas circuitously associated to physician visits, an fascinating secondary discovering emerges when wanting on the relationship between GDP per capita and apple consumption.
One attainable clarification is that wealthier international locations have higher entry to recent merchandise. One other risk is that local weather and geography play a task, so it may very well be that many high-GDP international locations are positioned in areas with robust apple manufacturing, making apples extra accessible and reasonably priced.
After all, different components may very well be influencing this relationship, however we gained’t dig deeper right here.
The scatterplot exhibits a constructive correlation: as GDP per capita will increase, apple consumption additionally tends to rise. Nonetheless, in comparison with median age and physician visits, this pattern is weaker, with extra variation within the information.
The OLS confirms the connection: with a 0.2257 coefficient for GDP per capita, we are able to estimate a rise of round 0.23 kg in apple consumption per capita for every improve of $1,000 in GDP per capita.
The three.8% p-value permits us to reject the null speculation. So the connection is statistically vital. Nonetheless, the R² worth (0.145) is comparatively low, so whereas GDP explains some variation in apple consumption, many different components possible contribute.
Conclusion
The saying goes:
“An apple a day retains the physician away,”
However after placing this fable to the check with real-world information, the outcomes appear not according to this saying. Throughout a number of years, the outcomes have been constant: no significant relationship between apple consumption and physician visits emerged, even after controlling for confounders. Plainly apples alone aren’t sufficient to maintain the physician away.
Nonetheless, this doesn’t utterly disprove the concept that consuming extra apples may scale back physician visits. Observational information, regardless of how effectively we management for confounders, can by no means absolutely show or disprove causality.
To get a extra statistically correct reply, and to rule out all attainable confounders at a stage of granularity that may very well be actionable for a person, we would want to conduct an A/B check. In such an experiment, contributors can be randomly assigned to 2 teams, for instance one consuming a set quantity of apples day by day and the opposite avoiding apples. By evaluating physician visits over time amongst these two teams, we may decide if any distinction between them come up, offering stronger proof of a causal impact.
For apparent causes, I selected to not go that route. Hiring a bunch of contributors can be costly, and ethically forcing folks to keep away from apples for science is certainly questionable.
Nonetheless, we did discover some fascinating patterns. The strongest predictor of physician visits wasn’t apple consumption, however median age: the older a rustic’s inhabitants, the extra usually folks see a physician.
In the meantime, GDP confirmed a light connection to apple consumption, probably as a result of wealthier international locations have higher entry to recent produce, or as a result of apple-growing areas are typically extra developed.
So, whereas we are able to’t verify the unique fable, we are able to provide a much less poetic, however data-backed model:
“A younger age retains the physician away.”
In case you loved this evaluation and need to join, you could find me on LinkedIn.
The total evaluation is on the market on this pocket book on GitHub.
Knowledge Sources
Fruit Consumption: Meals and Agriculture Group of the United Nations (2023) — with main processing by Our World in Knowledge. “Per capita consumption of apples — FAO” [dataset]. Meals and Agriculture Group of the United Nations, “Meals Balances: Meals Balances (-2013, previous methodology and inhabitants)”; Meals and Agriculture Group of the United Nations, “Meals Balances: Meals Balances (2010-)” [original data]. Licensed below CC BY 4.0.
Physician Visits: OECD (2024), Consultations, URL (accessed on January 22, 2025). Licensed below CC BY 4.0.
GDP per Capita: World Financial institution (2025) — with minor processing by Our World in Knowledge. “GDP per capita — World Financial institution — In fixed 2021 worldwide $” [dataset]. World Financial institution, “World Financial institution World Improvement Indicators” [original data]. Retrieved January 31, 2025 from https://ourworldindata.org/grapher/gdp-per-capita-worldbank. Licensed below CC BY 4.0.
Median Age: UN, World Inhabitants Prospects (2024) — processed by Our World in Knowledge. “Median age, medium projection — UN WPP” [dataset]. United Nations, “World Inhabitants Prospects” [original data]. Licensed below CC BY 4.0.
All photos, until in any other case famous, are by the writer.
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