Introduction
“Cash can’t purchase happiness.” “You may’t choose a guide 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 sequence, I need to take in style myths/sayings and put them to the check utilizing real-world knowledge.
We’d affirm some sudden truths, or debunk some in style beliefs. Hopefully, in both case we are going to achieve 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 test between apple consumption per capita and physician visits per capita.
Knowledge sources
The info comes from:
Since knowledge 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, which means that in nations the place individuals eat extra apples, there’s a barely noticeable tendency to have decrease physician visits.
Sadly, the development 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 affirm what the scatterplot steered:
- The coefficient for apple consumption is -0.0107, which means that even when there may be 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 nearly zero, which means apple consumption explains nearly none of the variation in physician visits.
This doesn’t strictly imply that there isn’t a relationship, however quite that we can’t show one with the accessible knowledge. It’s potential that any actual impact is just too small to detect, that different elements we didn’t embrace play a bigger function, or that the info merely doesn’t mirror the connection properly.
Controlling for confounders
Are we performed? 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 may very well be influencing each variables, probably hiding a real relationship or creating a man-made one.
If we take into account this causal graph:
We’re assuming that apple consumption instantly impacts physician visits. Nonetheless, different hidden elements could be at play. If we don’t account for them, we danger failing to detect an actual relationship if one exists.
A widely known instance the place confounder variables are on show comes from a examine 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 quite a lot of 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 nations are likely to have each larger chocolate consumption and extra Nobel Prize winners. The noticed relationship wasn’t causal however quite on account of a hidden (confounding) issue.
The identical factor may very well be taking place in our case. There could be confounding variables that affect each apple consumption and physician visits, making it tough to see an actual relationship if one exists.
Two key confounders to think about are GDP per capita and median age. Wealthier nations have higher healthcare programs and totally different dietary patterns, and older populations have a tendency to go to medical doctors extra typically and will have totally different consuming habits.
To regulate for this, we modify 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 affirm what we noticed earlier:
- The coefficient for apple consumption stays very small(-0.0100), which means any potential impact is negligible.
- The p-value (85.5%) remains to be extraordinarily excessive, removed from statistical significance.
- We nonetheless can’t reject the null speculation, which means now we have no robust proof to assist the concept consuming extra apples results in fewer physician visits.
Similar as earlier than, this doesn’t essentially imply that no relationship exists, however quite that we can’t show one utilizing the accessible knowledge. It may nonetheless be potential that the true impact is just too small to detect or that there are but different elements we didn’t embrace.
One attention-grabbing commentary, nonetheless, 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 knowledge that wealth explains variations in healthcare utilization.
However, median age seems to be strongly related to physician visits, with a p-value of 0.001 (0.1%) and a optimistic coefficient (0.4952). This means that older populations have a tendency to go to medical doctors extra ceaselessly, which is definitely probably not shocking 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 growing old and healthcare utilization.
Median age → Physician visits
The outcomes from the OLS regression confirmed a powerful relationship between median age and physician visits, and the visualization under confirms this development.
There’s a clear upward development, indicating that nations with older populations are likely 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 could 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 think about explaining variations in physician visits throughout nations, impartial of GDP.
GDP → Apple consumption
Whereas in a roundabout way 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 recent merchandise. One other risk is that local weather and geography play a task, so it may very well be that many high-GDP nations are positioned in areas with robust apple manufacturing, making apples extra accessible and reasonably priced.
After all, different elements may very well be influencing this relationship, however we received’t dig deeper right here.
The scatterplot exhibits a optimistic correlation: as GDP per capita will increase, apple consumption additionally tends to rise. Nonetheless, in comparison with median age and physician visits, this development is weaker, with extra variation within the knowledge.
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 possible contribute.
Conclusion
The saying goes:
“An apple a day retains the physician away,”
However after placing this delusion to the check with real-world knowledge, the outcomes appear not consistent with this saying. Throughout a number of years, the outcomes had been constant: no significant relationship between apple consumption and physician visits emerged, even after controlling for confounders. It appears that evidently apples alone aren’t sufficient to maintain the physician away.
Nonetheless, this doesn’t utterly disprove the concept consuming extra apples may scale back physician visits. Observational knowledge, regardless of how properly 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 stage of granularity that may very well be actionable for a person, we would wish to conduct an A/B check.
In such an experiment, individuals 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 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 typically 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 recent produce, or as a result of apple-growing areas are typically extra developed.
So, whereas we are able to’t affirm the unique delusion, we are able to supply a much less poetic, however data-backed model:
“A younger age retains the physician away.”
Should you loved this evaluation and need to join, you could find me on LinkedIn.
The complete evaluation is obtainable 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, outdated methodology and inhabitants)”; Meals and Agriculture Group of the United Nations, “Meals Balances: Meals Balances (2010-)” [original data]. Licensed underneath CC BY 4.0.
Physician Visits: OECD (2024), Consultations, URL (accessed on January 22, 2025). Licensed underneath 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 Growth Indicators” [original data]. Retrieved January 31, 2025 from https://ourworldindata.org/grapher/gdp-per-capita-worldbank. Licensed underneath 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 underneath CC BY 4.0.
All photos, until in any other case famous, are by the creator.