Introduction
“Cash can’t purchase happiness.” “You possibly can’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 take a look at the info? On this article collection, I need to take common myths/sayings and put them to the take a look at utilizing real-world knowledge.
We would verify some surprising truths, or debunk some common 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 should 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 verify between apple consumption per capita and physician visits per capita.
Knowledge sources
The info comes from:
Since knowledge availability varies by yr, 2017 was chosen because it supplied probably the most full by way of variety of nations. Nonetheless, the outcomes are constant throughout different years.
Visualizing the connection
To visualise whether or not greater apple consumption is related to fewer physician visits, we begin by taking a look at a scatter plot with a regression line.
The regression plot reveals 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 unbiased variable.
The outcomes verify what the scatterplot urged:
- 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 just about none of the variation in physician visits.
This doesn’t strictly imply that there isn’t any relationship, however quite that we can not show one with the out there knowledge. It’s potential that any actual impact is simply too small to detect, that different components we didn’t embody play a bigger position, or that the info merely doesn’t replicate the connection effectively.
Controlling for confounders
Are we carried out? Not fairly. To this point, we’ve solely checked for a direct relationship between apple consumption and physician visits.
As already talked about, many different components might be influencing each variables, doubtlessly hiding a real relationship or creating a man-made one.
If we take into account this causal graph:
We’re assuming that apple consumption immediately impacts physician visits. Nonetheless, different hidden components 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 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? In all probability not. The possible clarification was that GDP per capita was a confounder. That signifies that richer nations are inclined to have each greater chocolate consumption and extra Nobel Prize winners. The noticed relationship wasn’t causal however quite as a consequence of a hidden (confounding) issue.
The identical factor might be occurring in our case. There could 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 methods and completely different dietary patterns, and older populations have a tendency to go to medical doctors extra typically and will have completely different consuming habits.
To manage 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 verify 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 not reject the null speculation, which means we’ve no sturdy 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 not show one utilizing the out there knowledge. It may nonetheless be potential that the actual impact is simply too small to detect or that there are but different components we didn’t embody.
One attention-grabbing statement, nonetheless, is that GDP per capita additionally reveals 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 fable, the info does reveal an attention-grabbing relationship between growing older 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 inclined to have extra physician visits per capita.
Since we’re solely taking a look at 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 sturdy and statistically important.
This means that median age is a key consider explaining variations in physician visits throughout nations, unbiased of GDP.
GDP → Apple consumption
Whereas circuitously 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 task, so it might be that many high-GDP nations are situated in areas with sturdy apple manufacturing, making apples extra out there and reasonably priced.
After all, different components might be influencing this relationship, however we gained’t dig deeper right here.
The scatterplot reveals 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 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 important. 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 take a look at with real-world knowledge, the outcomes appear not according to 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. 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 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 potential confounders at a stage of granularity that might be actionable for a person, we would want to conduct an A/B take a look at.
In such an experiment, members can be randomly assigned to 2 teams, for instance one consuming a set quantity of apples each 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 members can be costly, and ethically forcing individuals to keep away from apples for science is unquestionably 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 contemporary 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 supply 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 beneath CC BY 4.0.
Physician Visits: OECD (2024), Consultations, URL (accessed on January 22, 2025). Licensed beneath 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 beneath 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 beneath CC BY 4.0.
All photographs, except in any other case famous, are by the creator.
