Introduction
“Cash can’t purchase happiness.” “You may’t decide a e-book by its cowl.” “An apple a day retains the physician away.”
You’ve most likely heard these sayings a number of instances, however do they really maintain up after we have a look at the info? On this article collection, I wish to take well-liked myths/sayings and put them to the take a look at utilizing real-world information.
We would verify some sudden truths, or debunk some well-liked 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 assist this?
If the parable is true, we must always count on a destructive correlation between apple consumption per capita and physician visits per capita . So, the extra apples a rustic consumes, the less physician visits individuals 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 examine between apple consumption per capita and physician visits per capita.
Knowledge sources
The info comes from:
Since information availability varies by 12 months, 2017 was chosen because it supplied essentially the most full when it comes to variety of nations. Nonetheless, the outcomes are constant throughout different years.
Visualizing the connection
To visualise whether or not larger apple consumption is related to fewer physician visits, we begin by a scatter plot with a regression line.
The regression plot exhibits a very slim destructive correlation, that means that in nations the place individuals 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 impartial variable.
The outcomes verify what the scatterplot urged:
- The coefficient for apple consumption is -0.0107, that means that even when there’s an impact, it’s very small.
- The p-value is 0.860 (86%), way over the usual significance threshold of 5%.
- The R² worth is sort of zero, that means apple consumption explains just about none of the variation in physician visits.
This doesn’t strictly imply that there is no such thing as a relationship, however fairly that we can not show one with the obtainable information. It’s potential that any actual impact is simply too small to detect, that different elements we didn’t embody play a bigger position, or that the info merely doesn’t mirror the connection nicely.
Controlling for confounders
Are we executed? Not fairly. Thus far, we’ve solely checked for a direct relationship between apple consumption and physician visits.
As already talked about, many different elements could possibly be influencing each variables, probably hiding a real relationship or creating a synthetic one.
If we contemplate this causal graph:
We’re assuming that apple consumption immediately impacts physician visits. Nonetheless, different hidden elements is likely to be at play. If we don’t account for them, we threat 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 attention-grabbing correlation between chocolate consumption per capita and the variety of Nobel laureates.
So, would beginning to eat a variety of chocolate assist us win a Nobel Prize? Most likely not. The seemingly clarification was that GDP per capita was a confounder. That implies that richer nations are inclined to have each larger chocolate consumption and extra Nobel Prize winners. The noticed relationship wasn’t causal however fairly resulting from a hidden (confounding) issue.
The identical factor could possibly be taking place in our case. There is likely to 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 contemplate are GDP per capita and median age. Wealthier nations have higher healthcare techniques and completely different dietary patterns, and older populations have a tendency to go to docs extra usually and should have completely different consuming habits.
To regulate for this, we alter our mannequin by introducing these confounders:
Knowledge sources
The info 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 not reject the null speculation, that means we’ve got no robust proof to assist the concept that consuming extra apples results in fewer physician visits.
Identical as earlier than, this doesn’t essentially imply that no relationship exists, however fairly that we can not show one utilizing the obtainable information. It might nonetheless be potential that the true impact is simply too small to detect or that there are but different elements we didn’t embody.
One attention-grabbing remark, nevertheless, is that GDP per capita additionally exhibits no important 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.
Then again, 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 means that older populations have a tendency to go to docs extra regularly, which is definitely not likely stunning if we give it some thought!
So whereas we discover no assist for the apple delusion, the info does reveal an attention-grabbing relationship between getting older 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 nations with older populations are inclined to have extra physician visits per capita.
Since we’re solely median age and physician visits right here, one might argue that GDP per capita is likely to 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 important.
This means that median age is a key consider explaining variations in physician visits throughout nations, impartial of GDP.
GDP → Apple consumption
Whereas indirectly associated to physician visits, an attention-grabbing secondary discovering emerges when wanting on the relationship between GDP per capita and apple consumption.
One potential clarification is that wealthier nations have higher entry to contemporary merchandise. One other chance is that local weather and geography play a job, so it could possibly be that many high-GDP nations are positioned in areas with robust apple manufacturing, making apples extra obtainable and inexpensive.
In fact, different elements could possibly be influencing this relationship, however we received’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 enhance of $1,000 in GDP per capita.
The three.8% p-value permits us to reject the null speculation. So the connection is statistically important. Nonetheless, the R² worth (0.145) is comparatively low, so whereas GDP explains some variation in apple consumption, many different elements seemingly contribute.
Conclusion
The saying goes:
“An apple a day retains the physician away,”
However after placing this delusion to the take a look at 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. Evidently apples alone aren’t sufficient to maintain the physician away.
Nonetheless, this doesn’t utterly disprove the concept that consuming extra apples might cut back physician visits. Observational information, irrespective of how nicely 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 potential confounders at a degree of granularity that could possibly be actionable for a person, we would wish to conduct an A/B take a look at.
In such an experiment, individuals can be randomly assigned to 2 teams, for instance one consuming a hard and fast quantity of apples day by day and the opposite avoiding apples. By evaluating physician visits over time amongst these two teams, we might 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 individuals can be costly, and ethically forcing individuals to keep away from apples for science is certainly questionable.
Nonetheless, we did discover some attention-grabbing patterns. The strongest predictor of physician visits wasn’t apple consumption, however median age: the older a rustic’s inhabitants, the extra usually individuals see a health care provider.
In the meantime, GDP confirmed a gentle connection to apple consumption, probably as a result of wealthier nations have higher entry to contemporary produce, or as a result of apple-growing areas are usually extra developed.
So, whereas we are able to’t verify the unique delusion, we are able to supply a much less poetic, however data-backed model:
“A younger age retains the physician away.”
In case you loved this evaluation and wish to join, you’ll find me on LinkedIn.
The total evaluation is on the market on this notebook 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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