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Figure 1.
Self-reported Number of Visits to a Physician Within the Previous Year Among US Adult Apple Eaters vs Non–Apple Eaters
Self-reported Number of Visits to a Physician Within the Previous Year Among US Adult Apple Eaters vs Non–Apple Eaters

χ2 Test was used in comparison of proportions.

aP = .03.

Figure 2.
Percentage of US Adult Apple Eaters vs Non–Apple Eaters Who Did Not Use Each Specific Health Care Service in the Past Year
Percentage of US Adult Apple Eaters vs Non–Apple Eaters Who Did Not Use Each Specific Health Care Service in the Past Year

χ2 Test was used in comparison of proportions.

aPersons who avoided more than 1 physician visit in the past year (P = .03).

bPersons who avoided any use in the past year (overnight hospital stay P = .64; mental health visit P = .11).

cPersons who avoided using a prescription medication in past month (P = .01).

Figure 3.
Crude and Adjusted Odds Ratios for the Association Between Daily Apple Consumption and Avoidance of Health Care Services
Crude and Adjusted Odds Ratios for the Association Between Daily Apple Consumption and Avoidance of Health Care Services

Adjusted models include covariates for age, sex, race or ethnicity, educational attainment, body mass index, smoking status, and health insurance type.

aPersons who avoided more than 1 physician visit in the past year.

bPersons who avoided any use in the past year.

cPersons who avoided using a prescription medication in past month.

Figure 4.
Crude Odds Ratios for the Association Between Dose Response of Daily Apple Consumption and Avoidance of Health Care Services
Crude Odds Ratios for the Association Between Dose Response of Daily Apple Consumption and Avoidance of Health Care Services

Apple eating according to consuming no apples (<149 g) or a small (149-181 g of raw apple), medium (182-222 g), or large (≥223 g) apple per day. P values are for the trend across apple categories.

aPersons who avoided more than 1 physician visit in the past year.

bPersons who avoided any use in the past year.

cPersons who avoided using a prescription medication in past month.

Table.  
Characteristics of US Adults 18 Years or Older According to Apple vs Non–Apple Eater Statusa
Characteristics of US Adults 18 Years or Older According to Apple vs Non–Apple Eater Statusa
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Zackrisson  S, Andersson  I, Janzon  L, Manjer  J, Garne  JP.  Rate of over-diagnosis of breast cancer 15 years after end of Malmö mammographic screening trial: follow-up study. BMJ. 2006;332(7543):689-692.
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Wang  L, Lee  IM, Zhang  SM, Blumberg  JB, Buring  JE, Sesso  HD.  Dietary intake of selected flavonols, flavones, and flavonoid-rich foods and risk of cancer in middle-aged and older women. Am J Clin Nutr. 2009;89(3):905-912.
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Oude Griep  LM, Stamler  J, Chan  Q,  et al; INTERMAP Research Group.  Association of raw fruit and fruit juice consumption with blood pressure: the INTERMAP Study. Am J Clin Nutr. 2013;97(5):1083-1091.
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Mink  PJ, Scrafford  CG, Barraj  LM,  et al.  Flavonoid intake and cardiovascular disease mortality: a prospective study in postmenopausal women. Am J Clin Nutr. 2007;85(3):895-909.
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Conceição de Oliveira  M, Sichieri  R, Sanchez Moura  A.  Weight loss associated with a daily intake of three apples or three pears among overweight women. Nutrition. 2003;19(3):253-256.
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Gao  X, Cassidy  A, Schwarzschild  MA, Rimm  EB, Ascherio  A.  Habitual intake of dietary flavonoids and risk of Parkinson disease. Neurology. 2012;78(15):1138-1145.
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He  X, Liu  RH.  Triterpenoids isolated from apple peels have potent antiproliferative activity and may be partially responsible for apple’s anticancer activity. J Agric Food Chem. 2007;55(11):4366-4370.
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Jedrychowski  W, Maugeri  U, Popiela  T,  et al.  Case-control study on beneficial effect of regular consumption of apples on colorectal cancer risk in a population with relatively low intake of fruits and vegetables. Eur J Cancer Prev. 2010;19(1):42-47.
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Le Marchand  L, Murphy  SP, Hankin  JH, Wilkens  LR, Kolonel  LN.  Intake of flavonoids and lung cancer. J Natl Cancer Inst. 2000;92(2):154-160.
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Nöthlings  U, Murphy  SP, Wilkens  LR, Henderson  BE, Kolonel  LN.  Flavonols and pancreatic cancer risk: the multiethnic cohort study. Am J Epidemiol. 2007;166(8):924-931.
PubMedArticle
22.
Xing  N, Chen  Y, Mitchell  SH, Young  CY.  Quercetin inhibits the expression and function of the androgen receptor in LNCaP prostate cancer cells. Carcinogenesis. 2001;22(3):409-414.
PubMedArticle
23.
Willers  SM, Devereux  G, Craig  LC,  et al.  Maternal food consumption during pregnancy and asthma, respiratory and atopic symptoms in 5-year-old children. Thorax. 2007;62(9):773-779.
PubMedArticle
24.
Woods  RK, Walters  EH, Raven  JM,  et al.  Food and nutrient intakes and asthma risk in young adults. Am J Clin Nutr. 2003;78(3):414-421.
PubMed
25.
Chai  SC, Hooshmand  S, Saadat  RL, Payton  ME, Brummel-Smith  K, Arjmandi  BH.  Daily apple versus dried plum: impact on cardiovascular disease risk factors in postmenopausal women. J Acad Nutr Diet. 2012;112(8):1158-1168.
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26.
Hyson  D, Studebaker-Hallman  D, Davis  PA, Gershwin  ME.  Apple juice consumption reduces plasma low-density lipoprotein oxidation in healthy men and women. J Med Food. 2000;3(4):159-166.
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27.
Lairon  D, Arnault  N, Bertrais  S,  et al.  Dietary fiber intake and risk factors for cardiovascular disease in French adults. Am J Clin Nutr. 2005;82(6):1185-1194.
PubMed
28.
Li  G, Zhu  Y, Zhang  Y, Lang  J, Chen  Y, Ling  W.  Estimated daily flavonoid and stilbene intake from fruits, vegetables, and nuts and associations with lipid profiles in Chinese adults. J Acad Nutr Diet. 2013;113(6):786-794.
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29.
Briggs  ADM, Mizdrak  A, Scarborough  P.  A statin a day keeps the doctor away: comparative proverb assessment modelling study. BMJ. 2013;347:f7267. doi:10.1136/bmj.f7267.Article
30.
Wennberg  JE, Staiger  DO, Sharp  SM,  et al.  Observational intensity bias associated with illness adjustment: cross sectional analysis of insurance claims. BMJ. 2013;346:f549.
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Phelps  CE.  An apple a day: a futuristic parable. N Engl J Med. 1994;330(11):797-799.
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United States Department of Agriculture. National Fruit and Vegetable Retail Report. Washington, DC: United States Department of Agriculture; 2013.
33.
Moshfegh  AJ, Rhodes  DG, Baer  DJ,  et al.  The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes. Am J Clin Nutr. 2008;88(2):324-332.
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United States Environmental Protection Agency. Food Commodity Intake Database: what we eat in America.http://fcid.foodrisk.org/. Accessed September 10, 2013.
35.
09003: Apples, raw, with skin. The USDA National Nutrient Database for Standard Reference. http://ndb.nal.usda.gov/. Accessed September 1, 2013.
36.
Frame  PS.  The complete annual physical examination refuses to die. J Fam Pract. 1995;40(6):543-545.
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Howden  LM, Meyer  JA. United States Census Bureau: Age and Sex Composition. Washington, DC: United States Census Bureau; 2010.
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Cohen  JW, Cohen  SB, Banthin  JS.  The medical expenditure panel survey: a national information resource to support healthcare cost research and inform policy and practice. Med Care. 2009;47(7, suppl 1):S44-S50.Article
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Cody  SH, Glynn  MK, Farrar  JA,  et al.  An outbreak of Escherichia coli O157:H7 infection from unpasteurized commercial apple juice. Ann Intern Med. 1999;130(3):202-209.
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Millard  PS, Gensheimer  KF, Addiss  DG,  et al.  An outbreak of cryptosporidiosis from fresh-pressed apple cider. JAMA. 1994;272(20):1592-1596.
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Original Investigation
May 2015

Association Between Apple Consumption and Physician VisitsAppealing the Conventional Wisdom That an Apple a Day Keeps the Doctor Away

Author Affiliations
  • 1The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire
  • 2Division of Systems Leadership and Effectiveness Science, University of Michigan School of Nursing, Ann Arbor
  • 3Veteran Affairs Medical Center Outcomes Group, White River Junction, Vermont
JAMA Intern Med. 2015;175(5):777-783. doi:10.1001/jamainternmed.2014.5466
Abstract

Importance  Fruit consumption is believed to have beneficial health effects, and some claim, “An apple a day keeps the doctor away.”

Objective  To examine the relationship between eating an apple a day and keeping the doctor away.

Design, Setting, and Participants  A cross-sectional study of a nationally representative sample of the noninstitutionalized US adult population. A total of 8728 adults 18 years and older from the 2007-2008 and 2009-2010 National Health and Nutrition Examination Survey completed a 24-hour dietary recall questionnaire and reported that the quantity of food they ate was reflective of their usual daily diet.

Exposures  Daily apple eaters (consuming the equivalent of at least 1 small apple daily, or 149 g of raw apple) vs non–apple eaters, based on the reported quantity of whole apple consumed during the 24-hour dietary recall period.

Main Outcomes and Measures  The primary outcome measure was success at “keeping the doctor away,” measured as no more than 1 visit (self-reported) to a physician during the past year; secondary outcomes included successful avoidance of other health care services (ie, no overnight hospital stays, visits to a mental health professional, or prescription medications).

Results  Of 8399 eligible study participants who completed the dietary recall questionnaire, we identified 753 adult apple eaters (9.0%)—those who typically consume at least 1 small apple per day. Compared with the 7646 non–apple eaters (91.0%), apple eaters had higher educational attainment, were more likely to be from a racial or ethnic minority, and were less likely to smoke (P < .001 for each comparison). Apple eaters were more likely, in the crude analysis, to keep the doctor (and prescription medications) away: 39.0% of apple eaters avoided physician visits vs 33.9% of non–apple eaters (P = .03). After adjusting for sociodemographic and health-related characteristics, however, the association was no longer statistically significant (OR, 1.19; 95% CI, 0.93-1.53; P = .15). In the adjusted analysis, apple eaters also remained marginally more successful at avoiding prescription medications (odds ratio, 1.27; 95% CI, 1.00-1.63). There were no differences seen in overnight hospital stay or mental health visits.

Conclusions and Relevance  Evidence does not support that an apple a day keeps the doctor away; however, the small fraction of US adults who eat an apple a day do appear to use fewer prescription medications.

Introduction

The aphorism, “An apple a day keeps the doctor away,” originated in Wales, first appearing in a publication in 1866 in a different rhyming format: “Eat an apple on going to bed and you’ll keep the doctor from earning his bread.”1 The saying reappeared in 1913 in its current form.2,3 Medical practice in the 19th and 20th centuries was crude, and the public sensibly sought to keep physicians (and other health practitioners) away—a sentiment that may not be out of place in the 21st century.47 Through the ages, the apple has come to symbolize health and healthy habits, and has been used by government and private health organizations to symbolize lifestyle choices that lead to health and wellness.8,9

Promoted by the lay media and powerful special interest groups, including the US Apple Association,10 the beneficial effects of apple consumption have been variably attributed to fiber, essential vitamins and minerals, and flavonoids (particularly quercetin), a group of molecular compounds thought to be beneficial in the prevention of cancer and other health conditions.11 Although evidence is mixed,1215 apple consumption has been previously associated with positive health effects as far reaching as weight loss,16 prevention of neurologic degradation,17 cancer suppression,1822 reduction in asthma symptoms,23,24 and improved cardiovascular health.15,2529

All of this, however, raises the question of whether an apple a day actually keeps the doctor away—that is, is apple consumption associated with reduced health care use? Prior studies showing improved health related to apple eating may not necessarily translate into lower health care use,30 a goal sought by policy makers and, doubtless, many individual Americans. To our knowledge, the association between daily apple consumption and use of health care services has never been rigorously examined. Although some may jest,31 considering the relatively low cost of apples (currently $1.13 per pound of Red Delicious apples32), a prescription for apple consumption could potentially reduce national health care spending if the aphorism holds true.

We used nationally representative data from the National Health and Nutrition Examination Survey (NHANES) to examine the association between daily apple consumption and self-reported avoidance of physicians.

Methods

We used publicly available deidentified data from the NHANES to examine the relationship between the regular consumption of an apple per day and the avoidance of health care services. The NHANES is a continuous, cross-sectional, multistage probability interview survey of the civilian noninstitutionalized US population that provides nationally representative estimates of health measures, including detailed information on diet. For this study, we used 2007-2008 and 2009-2010 NHANES survey data from the demographics, in-person dietary questionnaire, examination, and health questionnaire files. This study was granted an exemption from institutional board review by Dartmouth College’s Committee for the Protection of Human Subjects.

Study Sample

We analyzed data from all adults 18 years and older who participated in the NHANES survey from 2007 to 2010. During this time, a total of 12 755 adults participated, and the overall unweighted response rate for the entire survey was 75.4% and 77.3% for the 2007-2008 and 2009-2010 surveys, respectively. All NHANES study participants are eligible to participate in the 24-hour dietary recall questionnaire, which collects comprehensive information on everything the participant consumed in the preceding 24 hours, including the type of food and amount.33 In addition, the NHANES asks participants whether the amount of food reported in the 24-hour recall period is reflective of the study participant’s usual diet; only those who responded in the affirmative were included in our study. We also excluded participants with incomplete dietary data, yielding a sample size of 8728.

Outcome Measures
Identification of Apple Eaters in the NHANES Dietary Data

For each food item listed in the 24-hour dietary recall period, the NHANES reports a United States Department of Agriculture’s food code and the amount (in grams) of that food consumed. We linked each food code to the US Environmental Protection Agency’s Food Commodity Intake Database,34 allowing us to estimate the total grams of raw apple contained in 100 g of the corresponding food. Summing these amounts for each food item consumed, we calculated the total grams of raw apple consumed by each study participant during the 24-hour dietary recall period (eAppendix in the Supplement).

We categorized study participants as either apple eaters or non–apple eaters using a cutoff point of 149 g/d, which corresponds to eating at least 1 small apple (7.0 cm in diameter), according to the United States Department of Agriculture’s National Nutrient Database for Standard Reference.35 In subanalyses to evaluate a potential dose-response relationship by apple size, we compared the effect of daily consumption of 1 small vs 1 medium (182 g, or approximately 7.6 cm in diameter) vs 1 large (223 g, or 8.3 cm in diameter) apple compared with no apples (ie, less than 1 small apple).

Because previous studies examining the potential health effects of apple consumption have used various forms of apple (eg, whole apple, apple juice, and applesauce),18,25,26 we also performed a sensitivity analysis based on consumption of raw vs processed apple compared with no apples (eAppendix in the Supplement). The analysis presented excludes the 329 study participants whose apple consumption was derived entirely from apple juice and applesauce. Therefore, our final study sample consisted of 8399 adults.

Avoidance of Health Care Services

To examine whether an apple a day keeps the doctor (and other health care services) away, we examined self-reported use of selected health care services according to apple-eater status. During the in-person interview, the NHANES asks how many times in the past year the study participants saw “a doctor or other health professional” about their health at any location (excluding hospitalizations), offering 6 categories of response ranging from none to 13 or more. Since it has been decades since standard health maintenance for US adults evolved to include 1 annual visit to a physician,36 we operationalized our primary outcome measure as successful avoidance of more than 1 physician visit in the past year—that is, we dichotomized the responses as 0 or 1 visit (kept the doctor away) vs any other response (did not). We also examined self-reported avoidance of other health care services in the past year, defined as no overnight hospital stays (vs any stays); no visits to mental health care professionals, including those in psychiatry, psychology, and social work (vs any visits); and no (vs any) prescription medications taken in the past month.

Covariates

We collected data on sociodemographic characteristics (age, sex, race or ethnicity, educational attainment, marital status, and annual family income), body mass index, self-reported health status, smoking status, and health insurance. We classified race and ethnicity as non-Hispanic white, non-Hispanic black, Mexican American, and other, multiple races.

Statistical Analysis

To account for the NHANES sampling methods, we used complex survey design methods in Stata, version 13.1 (StataCorp), for all analyses. These methods account for a study participant’s probability of selection and clustering of study participants within primary sampling units. We adjusted the NHANES person-weight variables from the 2007-2008 and 2009-2010 surveys so our sample represented the estimated size of the US adult population in 2010 (234.6 million).37

For crude comparisons, we used a t test for continuous variables and a χ2 test for categorical variables; we used logistic regression to model the relationship between eating an apple a day and successfully avoiding health care. Our primary dependent variable was avoiding more than 1 visit to a physician in the previous year. Secondary dependent variables included avoidance of an overnight hospital stay, a visit to a mental health professional, and prescription medication use. Our primary independent variable was daily consumption of the equivalent of at least 1 small whole apple. Our adjusted models included age (continuous), sex, race or ethnicity (non-Hispanic white vs non-Hispanic black; Mexican American; or other, or multiple races), educational attainment (high school or less vs some college or college or more), body mass index (within the normal range vs overweight, or obese), smoking status (nonsmoker vs current or former smoker), and health insurance type (private vs public or uninsured). For all analyses, we used complete case analysis and set the significance at P = .05 (2-sided).

Results
Characteristics of Apple Eaters

An estimated 19.3 million US adults (SE, 1.6) are apple eaters who consume the equivalent of approximately 26.9 million small apples daily, weighing 8.8 million pounds (Table). We estimate that 207.2 million adults are non–apple eaters (eating less than 1 small apple daily).

Compared with non–apple eaters, apple eaters were more likely to be from racial or ethnic minorities (14.8% vs 9.7%; P  < .001). The Table also demonstrates that apple eaters had higher educational attainment and were less likely to smoke.

Apple Eating and Avoiding Health Care Services

Figure 1 shows the distribution of the number of physician visits in the previous year among apple eaters vs non–apple eaters. In unadjusted analyses, apple eaters were more likely to keep the doctor away (39.0% vs 33.9%; odds ratio [OR], 1.25; 95% CI, 1.03-1.53; P = .03) (Figures 1, 2, and 3). Daily apple eaters were also more likely to successfully avoid prescription medication use (47.7% vs 41.8%; OR, 1.29; 95% CI, 1.07-1.55). There was no difference between apple eaters and non–apple eaters in the likelihood of avoiding an overnight hospital stay or a visit to a mental health professional.

Adjustment for sociodemographic and health-related characteristics attenuated the observed associations. The relationship between apple eating and keeping the doctor away was no longer statistically significant after adjustment (OR, 1.19; 95% CI, 0.93-1.53; P = .15) (Figure 3). Although mildly attenuated, the association between apple eating and avoidance of prescription medications remained marginally significant after adjustment: apple eaters were somewhat more likely to avoid prescription medication use than non–apple eaters (OR, 1.27; 95% CI, 1.00-1.63).

In our evaluation of a potential dose-response relationship between daily apple intake and success in avoiding health care services, Figure 4 shows no relationship between apple “dose” and the likelihood of avoiding health care services except for avoidance of prescription medications (P = .02). Similarly, we did not observe a threshold effect, although such an effect is hinted at in the case of avoidance of physician visits by eaters of a medium or large apple a day (for which the P value for the trend across apple categories is marginal).

Discussion

To our knowledge, this is the first study to thoroughly examine whether an apple a day keeps the doctor away. Our findings may imperil the veracity of this time-worn (but not time-tested) adage. We estimate that in the United States, the equivalent of 26.9 million small apples are eaten daily by nearly 20 million adult apple eaters. While the direction of the associations we observed supports the superiority of apple eaters over non–apple eaters at avoiding the use of health care services, these differences largely lacked statistical significance. Our findings suggest that the promotion of apple consumption may have limited benefit in reducing national health care spending. In the age of evidence-based assertions, however, there may be merit to saying, “An apple a day keeps the pharmacist away.”

Prescription medication costs represent approximately 30% of out-of-pocket US health care spending.38 If the observed association between apple consumption and reduced use of prescription medication were causal, the promotion of apple consumption could, at least in theory, help contain costs associated with prescription medication use.

In a back-of-the-envelope calculation, based on a mean medical prescription cost among US adults of $82.75 in 2010,39,40 we estimate the difference in annual prescription medication cost per capita between apple eaters ($1697) and non–apple eaters ($1925) to be $228 (95% CI, −$6 to $462). If all 234.6 million US adults were apple eaters, and if apples protect against prescription medication use, national prescription costs would be considerably lower (by approximately $47.2 billion). Based on the cost per pound of Red Delicious apples,32 1 small apple daily for each of the estimated 207.2 million adult non–apple eaters would cost approximately $28.0 billion—a potential net savings of up to $19.2 billion. Although impressive, this estimate does not account for the costs associated with potential adverse events associated with apple consumption such as outbreaks of infectious diseases.41,42

Our study has several important limitations. First, owing to the cross-sectional study design, we are unable to assess cause and effect in any observed relationships between daily apple consumption and successful avoidance of health care service use. We anticipate, however, that reverse causality is highly unlikely (ie, that individuals who take no prescription medications are impelled to eat apples).

Second, although we account in our analyses for a variety of characteristics, including healthy and unhealthy behaviors, we cannot dismiss the possibility of residual confounding in any associations observed between apple consumption and successful avoidance of health care services. Apple eaters were, in fact, measurably different from non–apple eaters (Table) and would be expected to differ in other, unmeasured ways. Specifically, individuals who eat apples may be more health conscious and otherwise healthier, which could entirely explain the associations we observed. On the other hand, individuals who are less healthy may, in subscribing to the “apple a day” adage, be more likely to consume apples, in which case we may have seriously underestimated the true salutary effect of apple consumption on health care use. Measurement of the true effect of apple eating would require prospective analyses or an experimental design. In the future, consideration could be given to studies based on natural experiments (eg, crop failure) or experimental designs (eg, an apple lottery) to more closely examine the relationship.

Finally, our reliance on self-reported estimates of apple consumption may raise concerns. Estimating usual diet is clearly a challenge, and different methods entail specific tradeoffs. While the NHANES 24-hour dietary recall offers detailed data (allowing us to identify all forms of apple consumption), it provides only a snapshot of an individual’s dietary pattern. Evidence suggests that, at least for fruit and vegetable consumption, a single 24-hour recall is comparable with other methods such as food frequency questionnaires and repeated 24-hour dietary recalls.43 Although we cannot rule out inaccurate reporting of either apple eating or health care use owing to social desirability, the likelihood of having introduced a bias away from the null appears quite low.

Conclusions

As the practice of medicine continues to advance in the 21st century, we believe it is important to examine what we can learn from the past. While the empirical evaluation of medical proverbs may allow us to profit from the wisdom of our predecessors, we were surprised to find a paucity of prior investigations of popular aphorisms. Our investigation has allowed us to update the well-known proverb to clarify that, if anything, apple eating may help keep the pharmacist away. Were this borne out, it certainly could have health policy implications. Perhaps not surprisingly, many widely accepted proverbs promote healthy lifestyle choices. Rigorously evaluating the clues handed down in these aphorisms—to wit, “Early to bed and early to rise, makes a man healthy, wealthy, and wise”—may provide important answers for improving population health and reducing health care expenditures in the future.

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Article Information

Accepted for Publication: February 17, 2014.

Corresponding Author: Matthew A. Davis, DC, MPH, PhD, University of Michigan School of Nursing, 400 N Ingalls, Ann Arbor, MI 48109 (mattadav@umich.edu).

Published Online: March 30, 2015. doi:10.1001/jamainternmed.2014.5466.

Author Contributions: Dr Davis had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: All authors.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: All authors.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Davis, Sirovich.

Administrative, technical, or material support: Davis.

Study supervision: All authors.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported by award number 5K01AT006162 from the National Institutes of Health (Dr Davis).

Role of the Funder/Sponsor: The National Institutes of Health had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The views expressed herein do not necessarily represent the official views of the National Institutes of Health, the United States Department of Agriculture, the US Environmental Protection Agency, the US Department of Veterans Affairs, or the US government.

Additional Contributions: We thank Todd A. Mackenzie, PhD, Geisel School of Medicine at Dartmouth, for review of statistical analyses and Lieutenant Aaron Niman, US Environmental Protection Agency, for assistance with the Food Commodity Intake Database. Neither received financial compensation.

References
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