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 in all probability 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 standard myths/sayings and put them to the check utilizing real-world knowledge.
We’d verify some surprising truths, or debunk some standard 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 should always count on a adverse 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 offered probably the most full when it comes to variety of international locations. Nevertheless, 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 reveals a very slim adverse correlation, which means that in international locations 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 instructed:
- 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 sort of zero, which means apple consumption explains nearly 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 knowledge. It’s attainable that any actual impact is simply too small to detect, that different elements we didn’t embrace play a bigger position, or that the info merely doesn’t mirror the connection properly.
Controlling for confounders
Are we executed? 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 elements might be influencing each variables, probably hiding a real relationship or creating a man-made one.
If we contemplate this causal graph:
We’re assuming that apple consumption instantly impacts physician visits. Nevertheless, different hidden elements may 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 a variety of chocolate assist us win a Nobel Prize? In all probability not. The seemingly rationalization was that GDP per capita was a confounder. That signifies that richer international locations are inclined to have each larger chocolate consumption and extra Nobel Prize winners. The noticed relationship wasn’t causal however fairly on account of a hidden (confounding) issue.
The identical factor might be taking place in our case. There may 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 contemplate are GDP per capita and median age. Wealthier international locations have higher healthcare programs and totally different dietary patterns, and older populations have a tendency to go to docs extra typically and should have totally different consuming habits.
To manage 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), 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 got no robust proof to assist the concept 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 knowledge. It might nonetheless be attainable that the actual impact is simply 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 reveals no vital 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 implies that older populations have a tendency to go to docs extra steadily, 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 ageing 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 beneath 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 might argue that GDP per capita may be a confounder, influencing each. Nevertheless, 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, impartial of GDP.
GDP → Apple consumption
Whereas indirectly associated to physician visits, an attention-grabbing secondary discovering emerges when trying on the relationship between GDP per capita and apple consumption.
One attainable rationalization is that wealthier international locations have higher entry to recent merchandise. One other chance is that local weather and geography play a task, so it might be that many high-GDP international locations are situated in areas with robust apple manufacturing, making apples extra obtainable and inexpensive.
After all, different elements might be influencing this relationship, however we received’t dig deeper right here.
The scatterplot reveals a optimistic correlation: as GDP per capita will increase, apple consumption additionally tends to rise. Nevertheless, in comparison with median age and physician visits, this pattern 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 vital. Nevertheless, 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 fable to the check 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.
Nevertheless, this doesn’t utterly disprove the concept consuming extra apples might cut back physician visits. Observational knowledge, irrespective 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 attainable confounders at a stage of granularity that might be actionable for a person, we would wish to conduct an A/B check.
In such an experiment, members could 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 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 members could be costly, and ethically forcing individuals to keep away from apples for science is certainly questionable.
Nevertheless, 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, presumably as a result of wealthier international locations have higher entry to recent produce, or as a result of apple-growing areas are usually 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.”
Should you loved this evaluation and wish to join, you will discover me on LinkedIn.
The total evaluation is out there 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, outdated 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.
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