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RESEARCH ARTICLE

Fried food intake and risk of nonfatal acute

myocardial infarction in the Costa Rica Heart

Study

Peter Hu 1,2

, Yanping Li 1 , Hannia Campos

1,3*

1 Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States

of America, 2 Cornell University College of Human Ecology, Ithaca, New York, United States of America,

3 Centro de Investigación e Innovación en Nutrición Traslacional y Salud (CIINT), Universidad

Hispanoameriana, San Jose, Costa Rica

* [email protected]

Abstract

Economic development in middle-income countries has led to a noticeable rise in the avail-

ability of commercial deep fried foods and lifestyles that require eating meals “on the go”

and outside of the home. Yet, data from these countries where fried foods were traditionally

prepared at home are scarce, despite several studies showing the potential adverse effects

of fried food consumption on risk for heart disease. We aimed to examine whether consump-

tion of fried foods inside or outside of the home is associated with an increased risk of myo-

cardial infarction (MI) among Hispanic/Latinos living in Costa Rica. Participants were

incident cases of a first acute MI (n = 2,154) and randomly selected controls matched for

age, sex, and residence (n = 2,154). After adjustment for traditional cardiovascular risk fac-

tors, including history of diabetes, history of hypertension, smoking, abdominal obesity,

income, educational years, occupation, alcohol intake, dietary intakes of saturated fatty

acid, fiber intake, and total energy intake, the multivariable-adjusted odds ratio (OR, 95%

CI) for risk of MI were 1.00 (reference), 1.02 (0.86–1.21), 1.26 (0.81–1.95), and 1.58 (1.08–

2.30) for intake of fried foods outside of the home <1/week, 1-3/week, 4-6/week, and 1/day, respectively (P trend = 0.02); and 1.00, 0.81 (0.65–1.00), 0.81 (0.61–1.09), and 0.93 (0.72–

1.19), respectively (P for trend = 0.65) for intake of fried foods inside the home. The data

suggest that consumption of fried foods outside of the home, a practice that has been asso-

ciated with economic development, could have adverse effects on cardiovascular disease.

Introduction

Historically, food preparation and consumption in low- and middle-income countries has

been restricted to the home. Costa Rican families prepare meals by various means, including

frying, a method in which food is submerged in hot oil [1]. More recently, economic develop-

ment in low- and middle-income countries has resulted in changes to food preparation and

consumption, including higher intake of refined grains, sodium, and red meat [2,3]. These

foods are characteristic of being highly processed and packaged for “on the go” eating or eating

PLOS ONE | https://doi.org/10.1371/journal.pone.0192960 February 15, 2018 1 / 13

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OPEN ACCESS

Citation: Hu P, Li Y, Campos H (2018) Fried food

intake and risk of nonfatal acute myocardial

infarction in the Costa Rica Heart Study. PLoS ONE

13(2): e0192960. https://doi.org/10.1371/journal.

pone.0192960

Editor: Manuel Portero-Otin, Universitat de Lleida-

IRBLLEIDA, SPAIN

Received: July 1, 2017

Accepted: February 1, 2018

Published: February 15, 2018

Copyright: © 2018 Hu et al. This is an open access article distributed under the terms of the Creative

Commons Attribution License, which permits

unrestricted use, distribution, and reproduction in

any medium, provided the original author and

source are credited.

Data Availability Statement: Data from this study

is available from Harvard Dataverse (https://

dataverse.harvard.edu/dataset.xhtml?persistentId=

doi:10.7910/DVN/LBWNY0).

Funding: This study was supported by grants

HL49086 and HL60692 from the National Heart,

Lung, and Blood Institute (NHLBI) at the National

Institutes of Health (HC), and the CIINT Research

Fund from Universidad Hispanoamericana de

Costa Rica.

Competing interests: The authors have declared

that no competing interests exist.

outside of the home. In fact, the entire food system, lifestyles, cooking methods, and eating

practices are changing rapidly [1,2]. For example, in China, the energy contributions from

snacks, foods eaten outside of home, and foods prepared outside of home have increased over

time [4]. In Latin America, retail food sales increased from 15% in 1990 to 60% by 2000 in

Latin American supermarkets [5]. While frying is not a new technique in Costa Rica, people

are currently eating more fried foods and foods outside the home compared to 30 years ago

[6]. Higher consumption of fried food outside the home, resulting from modernization, eco-

nomic development and urbanization, could be associated with increased risk of cardiovascu-

lar disease CVD.

Although frying improves taste and aroma, fried foods may have detrimental cardiovascular

effects [7]. A cross-sectional study in Spain found that food fried with re-used oils was associ-

ated with a higher prevalence of arterial hypertension [8]. Fried food intake was also associated

with higher body weight and risk of obesity [9,10] and type 2 diabetes among US men [11] and

women [11,12]. Italian adults with a higher intake of fried food had lower high density lipopro-

tein cholesterol levels and larger waist circumferences [13]. A positive association between

fried foods and risk of myocardial infarction (MI) was observed in INTERHEART, a case-con-

trol study of 52 countries [14]. In contrast, the Spanish cohort of the European Prospective

Investigation into Cancer and Nutrition (EPIC) study found no association between fried food

and risk of coronary heart disease [15]. The authors concluded that the type of frying oil was

the main reason for the differences between studies: olive and sunflower oils are the most com-

monly used fats for frying in Spain and are less prone to oxidation than other edible oils or fats

[16].

Interestingly, results from two large, prospective cohorts that evaluated consumption of

fried foods inside versus outside the home showed that fried food intake was significantly asso-

ciated with risk of incident type 2 diabetes and coronary artery disease, primarily when the

fried foods were eaten outside of the home [11]. These studies suggest that unique characteris-

tics of foods fried away from home such as the type and amount of oil used, portion size, and

the carbohydrate quality of the food being fried may be responsible for their potential adverse

effects [17]. Our previous study in Costa Rica found no association between consumption of

fried foods and risk of nonfatal acute MI, but we did not distinguish between eating fried

foods inside and outside of the home [1]. Since fried foods eaten away from home may have a

unique impact on risk of MI [11], the purpose of the present study was to examine whether

intake of fried foods inside and outside the home is associated with the risk of MI in the Costa

Rica Heart Study.

Methods

Study population and design

The study design and population of the Costa Rica study has been described previously [1,18].

In summary, all subjects were Hispanic Americans of Mestizo background who lived in the

Central Valley of Costa Rica. Eligible cases were men and women who were determined to be

survivors of a first acute MI by 2 independent cardiologists at any of the 6 recruiting hospitals

in the catchment area. To achieve 100% ascertainment, fieldworkers visited the 6 hospitals

daily. All cases met the World Health Organization criteria for MI, which require typical

symptoms plus either elevations in cardiac biomarker concentrations or diagnostic changes on

an electrocardiogram [19]. Cases were ineligible if they 1) died during hospitalization, 2) were

75 y or older on the day of their first MI, or 3) were physically or mentally unable to answer

the questionnaire. Enrollment was carried out while the cases were in the hospital’s step-down

unit. Cases were matched by age (±5 y), sex, and area of residence to population control

Fried foods and myocardial infarction

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subjects who were randomly identified with data from the National Census and Statistics

Bureau of Costa Rica. Because of the comprehensive social services provided in Costa Rica, all

persons living in the catchment area had access to medical care regardless of income. There-

fore, the control subjects came from the source population that gave rise to the cases and were

not likely to have had undiagnosed cardiovascular disease because of poor access to medical

care. Control subjects were ineligible if they ever experience a MI or if they were physically or

mentally unable to complete the questionnaires. After enrollment of cases at the hospital step-

down unit, all cases and controls were visited at their homes for the collection of dietary and

health information, anthropometric measurements, and biological specimens [1,18]. All sub-

jects gave informed consent on documents approved by the Human Subjects Committee of

the Harvard School of Public Health and the University of Costa Rica. To avoid the potential

for recall bias among the cases, data were collected as close to the diagnosis of MI as possible.

Data collection

Socio-demographic characteristics, smoking status, socioeconomic status, physical activity,

and medical history data were collected at the in-home interview. Dietary data was collected

by using a semi-quantitative food-frequency questionnaire (FFQ) that was developed and vali-

dated specifically to assess nutrient intake in the Costa Rican population [20]. In addition to

foods, the FFQ inquired about the frequency of eating fried foods outside of the home as well

as inside the home: <1 times/week or never, 1–3 times/week, 4–6 times/week, or daily.

Statistical analysis

The original population consisted of 2,274 case-control pairs and 27% of them were women.

Participants with missing values for fried food consumption inside or outside the home were

deleted (n = 123); if a case or control was missing, the whole pair was deleted. If among the

deleted controls a participant that had complete data matched a deleted case by age, sex, and

area of residence, the two participants were rematched and added to the data set. Thus, 3 cases

and 3 rematched controls with complete data were included in the final data set for a total of

2,154 case-control pairs. The present study was based on the fixed sample size of the 2,154

case-control pairs.

Because of the matched design, the significance of differences in the distributions of cate-

gorical variables by case-control status and frequency of eating fried foods outside of the home

was tested using McNemar’s test. If normally distributed, continuous variables were tested by

the paired t test; otherwise, the Wilcoxon signed rank test was used. Differences were consid-

ered significant at P< 0.05. To quantify a linear trend, we conducted a Wald test for linear trends by assigning the median value to each category of frequency of eating fried foods out-

side of the home and modeling this variable as a continuous variable. We applied the condi-

tional logistic regression model to estimate the odds ratios (OR) and 95% confidence intervals

(CI) for MI comparing participants with different frequencies of eating fried foods inside or

outside of home, with participants who ate fried food inside or outside of the home <once per

week as the reference group. In our multivariable analyses, we adjusted for established cardio-

vascular risk factors: history of diabetes (yes/no), hypertension (yes/no), smoking (never, past,

<10 cigarettes/d, 10–19 cigarettes/d, and �20 cigarettes/d), waist-hip-ratio (quintiles), physi-

cal activity (quintiles), income (quintiles), educational duration (years), occupation (retired,

agriculture, plumbers, semi-skilled or driver, managers and administrators, professionals and

others), and intake of alcohol (never, past, and tertile of alcohol intake among current

drinkers).

Fried foods and myocardial infarction

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To examine the extent to which dietary factors explained the association between frequency

of eating fried foods inside or outside of the home and risk of MI, we estimated the magnitude

of change in the regression coefficient for eating fried foods inside or outside of the home with

and without adjustment for each individual potential mediator, including dietary energy

intake, dietary fiber intake, and energy contribution from saturated fat. The association

between the percentage of eating fried foods outside of home and MI was explained by the die-

tary intermediate variables was computed as follows: (1 –(βmediator-adjusted model / βmulti- variable model)) X 100% [21]. A positive change in the regression coefficient indicates a

change in the rate ratio towards the null. SAS macro %MEDIATE was applied (publicly avail-

able at www.hsph.harvard.edu/faculty/spiegelman/mediate.html) [21].

To address the possibility of residual confounding, we applied the propensity score method

in the sensitivity analysis. We estimated the probability of fried food intake conditional on

observed covariates [22], using frequencies of fried food intake as a dependent variable and all

the covariates listed above for model 4 as independent variables. The propensity scores of dif-

ferent frequencies of fried food intake were included in the analysis as continuous variables

and the effect of fried food intake on outcomes was estimated based on the adjustment of these

propensity scores [22,23].

In the sensitivity analysis, we also further adjusted for the type of cooking oil and simulta-

neously adjusted for the frequency of eating fried foods inside and outside of the home. In

order to maximally control the residual confounding from other dietary intakes, we also did

another sensitivity analysis: instead of adjustment for individual food and nutrient items, we

adjusted for the index of factors of the dietary pattern identified by principal component analy-

sis, which had been found to be associated with risk of MI in our study [24]. We also per-

formed subgroup analyses to explore the effects of eating fried foods outside of the home

stratified by several covariates. In these stratification analyses, because the matched pairs

might be separated into different subgroups, we used unconditional logistic regression with

matching variables and other potential confounders in the model for each subgroup analysis.

In all unconditional analyses, we computed the Hosmer-Lemeshow statistic to test for the

goodness of-fit of the models. We examined potential interactions of eating fried foods outside

of the home with the stratifying variables (smoking, physical activity, sex, and obesity) on risk

of MI by including a multiplicative term in the model with adjustment for other potential con-

founders. We applied the conditional logistic regression model in the test of interactions,

which were based on the whole study population.

SAS software version 9.4 (SAS Institute Inc, Cary, NC) was used for all statistical analyses,

and all P values presented are two-tailed.

Results

General characteristics

The characteristics of the cases and population-based matched controls in Costa Rica are

shown in Table 1. Compared to controls, the cases were more likely to have abdominal obesity,

history of diabetes and hypertension, lower physical activity, and less income. Cases had fewer

current drinkers but were more likely to smoke and have a less formal education, and were

more likely to consume a diet high in total energy and saturated fat, but low in polyunsaturated

fat and fiber.

The general characteristics and potential confounders among population controls are

shown in Table 2.

Compared to those who ate fried foods less than once per week inside or outside the home,

controls who ate fried food daily either inside or outside the home were younger, less likely to

Fried foods and myocardial infarction

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Table 1. Characteristics of nonfatal MI cases and population-based matched control in the Costa Rica Heart Study 1 .

Variable Controls Cases P�

Age (y) 2

58.2(11.3) 58.5(11.0) N/A

Women (%) 2

27 27 N/A

Living in Rural Area (%) 2

26 26 N/A

History of Diabetes (%) 14 25 < .0001

History of Hypertension (%) 29 39 < .0001

Current smoker (%) 21 40 < .0001

Current alcohol drinker (%) 53 48 0.004

Alcohol intake among drinkers (g/day) 3

11.2(17.1) 13.2(23.9) 0.02

Waist circumference (cm) 90.9(10.0) 90.8(9.3) 0.95

Physical activity (METs) 4

35.5(16.2) 34.3(16.2) 0.02

Formal education (y) 7.5(5.3) 7.1(5.4) 0.009

Occupation (%) 0.15

Retired 18.7 19.5

Agriculture 6.7 6.6

Plumbers, semi-skilled, driver 24.3 27.1

Managers and administrators 20.9 18.2

Professionals 26.7 26.2

Students or others 2.7 2.6

Monthly household income (US$) 569(426) 496(392) < .0001

Dietary intake

Energy (kcal) 2443(765) 2703(947) < .0001

Saturated fat (% of energy) 11.7(2.9) 12.4(3.1) < .0001

Polyunsaturated fat (% of energy) 7.1(2.3) 6.8(2.3) 0.0005

Trans fat (% of energy) 1.31(0.64) 1.33(0.64) 0.30 Cholesterol (mg/1000 kcal) 118(52) 126(58) < .0001

Carbohydrate (% of energy) 55.4(7.3) 54.4(7.5) < .0001

Protein (% of energy) 12.9(2.1) 13.2(2.2) 0.0004

Fiber (g/d) 3

25.1(6.1) 24.1(6.4) < .0001

Alpha linolenic acid (g/d) 3

1.59(0.77) 1.69(0.85) < .0001

Eating fried foods at home <0.0001

<1 time/week 12.9 13.8

1–3 times/week 53.4 47.2

4–6 times/week 10.8 9.8

daily 22.9 29.2

Eating fried food outside the home <0.0001

< 1 time/week 69.9 65.5

1–3 times/week 25.4 25.4

4–6 times/week 2.1 3.3

daily 2.9 5.8

1 Values are means (SD) or %.

� Significance for different between cases and controls (McNe-mar’s or paired t test or Wilcoxon signed rank test P <0.05). 2 Matching variable

3 Adjusted for total energy intake using the residual method

4 METs, Metabolic Equivalent of Tasks

https://doi.org/10.1371/journal.pone.0192960.t001

Fried foods and myocardial infarction

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Table 2. Characteristics of population-based matched controls by frequency of fried food intake at home and outside of the home 1 .

<1 time/week 1–3 times/week 4–6 times/week Daily P for trend Frequency of eating fried foods inside home

N 277 1,150 233 494

Women (%) 2

43 26 24 21 < .0001

Living in urban area (%) 2

75 73 78 74 0.56

Age (years) 2

61(11) 58(11) 57(11) 57(12) 0.0004

Waist Circumference (cm) 89.8(9.5) 90.8(10.2) 91.3(10.4) 91.3(9.8) 0.09

Physical Activity (METs) 3

33.1(13.0) 35.1(15.5) 36.3(14.7) 37.3(19.3) 0.0003

Current smoker (%) 20 21 19 23 0.45

Current alcohol drinker (%) 46 53 53 55 0.12

Monthly household income (US$) 557(456) 571(436) 620(411) 547(392) 0.74

Education (years completed) 7.09(5.45) 7.55(5.34) 8.31(5.49) 7.42(5.10) 0.46

History of diabetes (%) 16 11 13 16 0.05

History of hypertension (%) 34 30 27 25 0.006

Total energy (kcal) 2029(663) 2378(695) 2544(743) 2781(837) < .0001

Saturated fat (% of energy) 10.7(3.1) 11.5(2.8) 12.2(2.9) 12.5(2.9) < .0001

Polyunsaturated fat (% of energy) 6.9(2.4) 7.0(2.3) 7.0(2.3) 7.3(2.4) 0.004

Trans Fat (% of energy) 1.17(0.61) 1.34(0.67) 1.29(0.58) 1.36(0.62) 0.04 Alpha linolenic acid (g/d)

4 1.33(0.66) 1.51(0.71) 1.66(0.71) 1.88(0.89) < .0001

Cholesterol (mg/1000 kcal) 97(48) 114(45) 118(42) 139(64) < .0001

Carbohydrate (% of energy) 57.4(8.5) 55.8(7.1) 54.6(6.9) 53.8(6.9) < .0001

Protein (% of energy) 12.8(2.6) 12.9(2.0) 12.9(2.0) 13.1(2.0) 0.03

Fiber (g/d) 4

25.7(6.5) 25.2(5.7) 24.4(6.0) 24.6(6.6) 0.006

Type of cooking oil in home (%) < .0001

Sunflower 23 24 17 17

Palm 19 22 26 27

High trans soybean oil 18 25 16 19

Low trans soybean oil 32 26 36 35

Others 8 3 5 2

Occupation (%) 0.002

Retired 19 19 19 17

Agriculture 4 7 7 8

Plumbers, semi-skilled, driver 18 25 22 28

Managers and administrators 18 22 19 21

Professionals 38 25 27 23

Others 3 2 5 2

Frequency of eating fried foods outside of the home

N 1,499 546 46 63

Women (%) 2

30 20 11 8 < .0001

Living in urban area (%) 2

73 77 70 86 0.03

Age (years) 2

60(11) 54(12) 52(12) 51(11) < .0001

Waist Circumference (cm) 90.3(10.0) 92.0(10.0) 93.2(9.5) 91.8(9.8) 0.005

Physical Activity (METs) 3

35.4(16.1) 35.8(16.7) 33.9(15.4) 36.0(12.5) 0.85

Current smoker (%) 20 23 30 27 0.14

Current alcohol drinker (%) 48 62 70 65 < .0001

Monthly household income (US$) 528(410) 656(446) 793(479) 610(437) < .0001

Education (years completed) 7.05(5.18) 8.69(5.51) 8.72(5.44) 8.44(5.24) < .0001

History of diabetes (%) 16 10 13 16 0.03

(Continued )

Fried foods and myocardial infarction

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be women, less likely to report hypertension, and had higher dietary intakes of total energy,

saturated fat and ALA. Controls who ate fried foods daily also had less intakes of dietary fiber

and carbohydrates, and were more likely to use soybean and sunflower oil than palm oil

(Table 2). Compared to controls who seldom ate fried food at home, controls who ate fried

foods daily at home were more physically active and had higher intakes of polyunsaturated fat,

trans fat, cholesterol and protein. Controls with frequent fried food consumption outside of

the home had lower family incomes, lower educational levels, and were more likely to drink

alcohol compared to controls who ate fried food outside of the home less than once per week.

The proportion of plumbers, semi-skilled workers, and drivers was higher among controls

who ate fried food daily outside the home than the proportion among controls who ate fried

food daily inside the home.

The associations between intake of foods inside and outside the home and risk of MI are

shown in Table 3.

Compared to fried food intake <once per week at home (reference), daily intake of fried

foods inside the home was associated with a 25% increase in the risk of MI (P for trend = 0.0005), whereas a 118% increase in risk was observed for those with daily intake of

fried foods outside the home, after adjustment for non-dietary cardiovascular risk factors,

including history of diabetes, history of hypertension, smoking, abdominal obesity, income,

Table 2. (Continued )

<1 time/week 1–3 times/week 4–6 times/week Daily P for trend History of hypertension (%) 32 25 28 16 0.002

Total energy (kcal) 2323(695) 2630(766) 3062(920) 3222(1157) < .0001

Saturated fat (% of energy) 11.3(3.0) 12.3(2.6) 13.4(2.9) 13.8(2.6) < .0001

Polyunsaturated fat (% of energy) 7.0(2.4) 7.2(2.1) 6.8(2.4) 7.5(2.3) 0.14

Trans Fat (% of energy) 1.30(0.65) 1.34(0.63) 1.30(0.47) 1.34(0.59) 0.52 Alpha linolenic acid (g/d)

4 1.53(0.75) 1.69(0.76) 1.70(0.74) 1.96(0.94) < .0001

Cholesterol (mg/1000 kcal) 117(54) 118(44) 129(67) 125(48) 0.09

Carbohydrate (% of energy) 56.4(7.2) 53.5(7.1) 52.1(7.0) 50.5(5.6) < .0001

Protein (% of energy) 12.9(2.1) 13.0(2.0) 12.2(1.8) 13.0(2.0) 0.55

Fiber (g/d) 4

25.5(5.7) 24.3(6.6) 21.3(5.6) 22.8(6.6) < .0001

Type of cooking oil in home (%) 0.86

Sunflower 21 22 24 22

Palm 24 21 28 27

High trans soybean oil 21 23 22 22

Low trans soybean oil 30 30 24 29

Others 4 4 2 0

Occupation (%) < .0001

Retired 23 11 2 5

Agriculture 7 5 4 3

Plumbers, semi-skilled, driver etcs 23 24 48 40

Managers and administrators 16 32 24 40

Professionals 28 25 20 11

Others 3 3 2 2

1 Values are means (SD) or % (percentage of population in each category);

2 Matching variable;

3 MET, metabolic equivalent of task

4 Adjusted for total energy intake using the residual method and does not include supplements.

https://doi.org/10.1371/journal.pone.0192960.t002

Fried foods and myocardial infarction

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educational years, occupation, and alcohol intake. The association between daily intake of

fried foods inside the home and risk of MI was attenuated and no longer significant after fur-

ther adjustment for significant dietary confounders (OR 0.93, 95% CI 0.72, 1.19). However,

the association between intake of fried foods outside of the home and risk of MI remained sta-

tistically significant (OR 1.55 95% CI 1.08, 2.30). The analysis using propensity score stratifica-

tion yielded similar results (OR 1.57 95% CI 1.11, 2.21), which compared daily intake versus

<1time/week of fried foods outside of the home. The OR for daily intake of fried foods versus

<1time/week was 0.87 (0.69, 1.08) (P for trend = 0.96) for intake inside the home and 1.56 (1.11, 2.19) (P for trend = 0.02) for intake outside the home. Adjusting for type of cooking oil did not materially change the association between eating fried foods inside or outside of home

and risk of MI. The OR for daily intake of fried foods versus <1time/week was 0.93 (0.72,

1.19) (P for trend = 0.71) for intake inside the home and 1.56 (1.06, 2.29) (P for trend = 0.02) for intake outside the home. In the sensitivity analysis of adjusting dietary patterns, the ORs

comparing daily versus <1time/week intake of fried foods were 0.87 (95%CI: 0.68–1.11, P for trend = 0.98) for intake inside the home and 1.55 (95%CI: 1.06–2.26, P for trend = 0.02) for intake outside the home. The interactions between eating fried foods outside of the home and

current smoking, physical activity, sex, and obesity on risk of MI were not significant (P for interaction >0.2 for all). The association between eating fried foods outside of the home and

risk of MI was consistent in analyses stratified by sex, smoking, BMI, or physical activity (S1

Fig).

The independent and joint effects for fried food intake inside the home and outside of the

home comparing intake �4 times/week to < 4 times/week are shown in Fig 1A (unadjusted

Table 3. Frequency of fried food intake and risk of nonfatal acute myocardial infarction in the Costa Rica Heart Study.

Frequency of eating fried foods <1 time/week 1–3 times /week 4–6 times /week daily P for trend

Inside home

Model 1 1

1.0 0.82(0.68, 0.98) 0.86(0.67, 1.10) 1.19(0.97, 1.46) 0.0002

Model 2 2

1.0 0.86(0.72, 1.06) 0.95(0.72, 1.25) 1.25(0.99, 1.57) 0.0005

Model 3 3

+ Fiber 1.0 0.86(0.70, 1.06) 0.94(0.71, 1.25) 1.20(0.95, 1.52) 0.002

+ Saturated fatty acid 1.0 0.83(0.67, 1.03) 0.88(0.67, 1.17) 1.09(0.86, 1.39) 0.03

+ Total energy intake 1.0 0.83(0.67, 1.02) 0.85(0.64, 1.13) 1.01(0.79, 1.28) 0.23

Model 4 4

1.0 0.81(0.65, 1.00) 0.81(0.61, 1.09) 0.93(0.72, 1.19) 0.65

Outside of the home

Model 1 1

1.0 1.09(0.94, 1.26) 1.63(1.11, 2.37) 2.20(1.59, 3.04) < .0001

Model 2 2

1.0 1.17(0.99, 1.37) 1.74(1.14, 2.66) 2.18(1.51, 3.13) < .0001

Model 3 3

+ Fiber 1.0 1.15(0.98, 1.36) 1.64(1.07, 2.52) 2.08(1.44, 2.99) <0.0001

+ Saturated fatty acid 1.0 1.09(0.93, 1.29) 1.52(0.99, 2.34) 1.86(1.28, 2.70) 0.0003

+ Total energy intake 1.0 1.05(0.89, 1.25) 1.37(0.89, 2.12) 1.73(1.19, 2.51) 0.003

Model 4 4

1.0 1.02(0.86, 1.21) 1.26(0.81, 1.95) 1.55(1.08, 2.30) 0.02

Odds Ratio (OR) of MI (95%CI) by frequency of fried food intake outside; All models used a fixed sample size of 2,154 case-control pairs 1

Model: ORs conditioned on matching variables (age, sex and area of residence). 2

Model 2: Adjusted for history of diabetes (yes/no), hypertension (yes/no), smoking (never, past, <10 cigarettes/d, 10–19 cigarettes/d, and �20 cigarettes/d), waist

circumference (quintiles), physical activity (quintiles), income (quintiles), educational years, intake of alcohol (never, past, and tertiles of current drinkers) and

occupation (retired, agriculture, plumbers, semi-skilled or driver, managers and administrators, professionals and others) 3

Model 3: Model 2 plus saturated fatty acid, fiber or total energy intake individually (all in quintile) 4

Model 4: Model 2 plus saturated fatty acid, fiber and total energy intake all together (all in quintile)

https://doi.org/10.1371/journal.pone.0192960.t003

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for non-dietary confounders) and with additional adjustment for dietary factors in Fig 1B. Par-

ticipants reporting fried food intake both inside the home and outside of the home �4 times/

week had 60% higher risk of MI compared to those reporting intake < 4 times/week after

adjustment for dietary and non-dietary confounders. A 27% increase in MI risk was found for

those reporting only fried food intake outside of the home, whereas no association was found

for those only reporting fried food intake inside the home.

Discussion

In this case control study conducted in the Central Valley of Costa Rica, higher intake of total

fried foods was associated with increased risk of MI. This association was mostly attributed to

intake of fried foods outside the home. Daily intake of fried foods outside the home was associ-

ated with a 55% higher risk of MI, whereas no association was observed with daily intake of

Fig 1. Joint effect of eating fried food �4 times/week at home and outside of the home. Odds Ratio (OR) of MI (95%CI) according to the joint category of fried

food intake at home and outside of the home; All models used a fixed sample size of 2,154 case-control pairs, ORs conditioned on matching variables (age, sex and

area of residence).

A:, Adjusted for history of diabetes (yes/no), hypertension (yes/no), smoking (never, past, <10 cigarettes/d, 10–19 cigarettes/d, and �20 cigarettes/d), waist-hip-

ratio (quintiles), physical activity (quintiles), income (quintiles), educational years, intake of alcohol (never, past, and tertile of current drinkers) and occupation

(retired, agriculture, plumbers, semi-skilled or driver, managers and administrators, professionals and others);

B: Further adjusted for saturated fat, fiber and total energy intake (all in quintile).

https://doi.org/10.1371/journal.pone.0192960.g001

Fried foods and myocardial infarction

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fried food inside the home after adjusting for smoking, physical activity, alcohol intake, educa-

tion, occupation, income, waist circumference, fiber, saturated fat, energy intake, and history

of diabetes or hypertension.

Total fried food intake has been associated with risk of heart disease in previous studies, a

finding consistent with our current results [11,14] In the Nurses’ Health Study and the Health

Professionals’ Follow-up Study [11] total fried food intake was associated with a 21% higher

risk of heart disease. INTERHEART [14], a standardized case-control study of acute MI

involving 5761 nonfatal MI cases and 10, 646 controls from 52 countries, observed a consistent

positive association between acute MI and intake of fried foods. The OR comparing the highest

with the lowest quartile of fried food intake was 1.13 (95%CI: 1.02–1.25, P for trend <0.0001) after multivariate adjustment. Intake of both fried foods inside and outside the home in our

study was higher than those in previous studies (OR, 1.60, 95% CI 1.08, 2.38). Although the

rationale for this result is uncertain, it is reasonable to hypothesize that the type of oil used for

cooking could explain some of these differences. The use of palm oil and high trans soybean

oil for cooking, previously associated with heart disease, is higher in Costa Rica than in other

countries where studies have been conducted [25,26]. In contrast to other previous studies, no

association between fried food intake and risk of heart disease was found in the Spanish

Cohort of the European Investigation into Cancer and Nutrition where olive oil is the main

type of fat used for cooking [15].

Consistent with our study, fried food intake away from home has been associated with risk

of heart disease in previous studies. In the Nurses’ Health Study and the Health Professionals’

Follow-up Study [11], fried food intake away from home was associated with heart disease.

The magnitude of the association in the Costa Rican Heart Study was greater than in the U.S

cohort study (OR 1.18, 95% CI 0.99, 1.39). The frequency of fried food intake away from home

was relatively low (< 10% reporting eating away from home >4 times per week) in our study.

However, the 55% increase in risk of MI observed in our study is of concern given that it is

likely that intake of foods outside of the home will continue to increase in middle-income

countries [2,6].

Frying is a commonly used cooking technique in Costa Rican homes. In fact, over 85% of

the studied population reported intake of fried foods inside the home at least once per week.

The most commonly fried foods in Costa Rican homes include plantains, potatoes, cassava,

maize turnovers, and rice. Interestingly, we did not find an association between intake of fried

foods inside the home and risk of MI despite of the potential detrimental health effects of fried

foods [26]. This null association could be explained in part by lower oxidation products in

fried foods inside the home. Frying increases the amount of cholesterol and other lipid oxida-

tion products mostly when cooking meat, fish, and vegetables, as opposed to carbohydrate rich

foods [27,28]. Frying foods inside the home involves shorter frying times, lower temperatures,

and pan-frying (versus deep frying). These characteristics of frying foods inside the home

could have contributed to the observed result [29,30]. In contrast, commercially prepared fried

foods are often more likely to re-use oil several times and deep-fry at higher temperatures

[31,32].

Major strengths of our study were the ability to evaluate fried food inside and outside of the

home in the context of a middle-income country with different dietary patterns and lifestyles

than previous studies. Other strengths include the large sample size, high validity and partici-

pation (98% among cases and 88% among controls), restriction of recruitment to survivors of

a first nonfatal MI in a pre-specified catchment area, and the use of randomly selected popula-

tion-based controls. In addition, we collected detailed information on diet using the standard-

ized FFQ designed and validated specifically for the studied population. Furthermore, our

Fried foods and myocardial infarction

PLOS ONE | https://doi.org/10.1371/journal.pone.0192960 February 15, 2018 10 / 13

study focused on eating patterns rather than specific nutrients, which translates more easily to

health recommendations and public understanding.

Several limitations also warrant consideration. First, the experience of having a MI could

have modified cases responses. To minimize possible recall bias, dietary data collection was

conducted in the subjects’ home as close as possible to hospital discharge (26±10 days after the MI). For most cases (81%), data collection was completed within <14 days [1,18,33]. Given

the observational nature of our study, we cannot prove causality. Similarly to other observa-

tional studies, it is difficult to rule out residual confounding, despite careful control for poten-

tial confounders in the analyses. Future prospective studies and clinical trials in this area are

warranted. Additionally, we did not take into account the specific fried foods our participants

ate, nor the duration, temperature, or methods in which they were cooked. Nonetheless, our

results might underestimate the true magnitude of the effect because of measurement error

and over-adjustment for covariates that might be on the causal pathway, such as hypertension,

diabetes or obesity.

In sum, we found that frequent consumption of fried foods outside of the home is associ-

ated with a higher risk of MI. This finding suggests that the trend towards higher consumption

of commercially available foods outside the home could have detrimental effects on the risk of

cardiovascular disease in middle-income countries.

Supporting information

S1 Fig. Multivariate-adjusted odds ratio of MI stratified by potential confounders1,2. 1

Odds ratio of MI comparing eating fried foods outside daily versus less than once per week by

conditional logistic regression adjusted for history of diabetes (yes/no), hypertension (yes/no),

smoking (never, past, <10 cigarettes/d, 10–19 cigarettes/d, and �20 cigarettes/d), waist-hip-

ratio (quintiles), physical activity (quintiles), income (quintiles), educational years, intake of

alcohol (never, past, and tertiles of current drinkers), and occupation (retired, agriculture,

plumbers, semi-skilled or driver, managers and administrators, professionals and others),

besides the stratification factor.

2 unconditional logistic regression adjusted variables listed above and age, sex and area of resi-

dence, besides the stratification factor.

(TIF)

Acknowledgments

The authors are grateful to the staffs and participants of the Costa Rica Heart Study for study

management in Costa Rica.

Author Contributions

Conceptualization: Peter Hu, Yanping Li, Hannia Campos.

Data curation: Hannia Campos.

Formal analysis: Peter Hu, Yanping Li.

Investigation: Yanping Li, Hannia Campos.

Methodology: Peter Hu, Yanping Li.

Project administration: Hannia Campos.

Resources: Hannia Campos.

Fried foods and myocardial infarction

PLOS ONE | https://doi.org/10.1371/journal.pone.0192960 February 15, 2018 11 / 13

Writing – original draft: Peter Hu.

Writing – review & editing: Peter Hu, Yanping Li, Hannia Campos.

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