European Journal of Nutrition

, Volume 53, Issue 2, pp 557–566 | Cite as

Traditional dietary pattern of South America is linked to breast cancer: an ongoing case–control study in Argentina

  • Natalia Tumas
  • Camila Niclis
  • Laura R. Aballay
  • Alberto R. Osella
  • María del Pilar Díaz
Original Contribution

Abstract

Introduction

Several studies have shown the effect of dietary patterns on breast cancer risk, but none has been conducted in Argentina. The aim of this study was to extract dietary patterns from Food Frequency Questioner, to estimate their effect on breast cancer occurrence while taking into account aggregation factors (family history of breast cancer) and to explore the sensitivity of the estimates to changes in the assumptions.

Methods

A principal component exploratory factor analysis was applied to identify dietary patterns, which were then included as covariates in a multilevel logistic regression. Family history of BC was considered as a clustering variable. A multiple probabilistic sensitivity analysis was also performed.

Results

The study included 100 cases and 294 controls. Four dietary patterns were identified. Traditional (fat meats, bakery products, and vegetable oil and mayonnaise) (OR III tertile vs I 3.13, 95 % CI 2.58–3.78), Rural (processed meat) (OR III tertile vs I 2.02, 95 % CI 1.21–3.37) and Starchy (refined grains) (OR III tertile vs I 1.82, 95 % CI 1.18–2.79) dietary patterns were positively associated with BC risk, whereas the Prudent pattern (fruit and non-starchy vegetables) (OR III tertile vs I 0.56, 95 % CI 0.41–0.77) showed a protective effect. For Traditional pattern, the median bias-adjusted ORs (3.52) were higher than the conventional (2.76).

Conclusions

While the Prudent pattern was associated with a reduced risk of BC, Traditional, Rural and Starchy patterns showed a promoting effect. Despite the threats to validity, the nature of associations was not strongly affected.

Keywords

Dietary patterns Breast cancer Argentina Multilevel Sensitivity analysis 

Abbreviations

BC

Breast cancer

OR

Odds ratio

Py

Person-years

EECC

Environmental Epidemiology of Cancer in Córdoba

METs

Metabolic equivalent of tasks

FFQ

Food Frequency Questioner

PCFA

Principal component factor analysis

KMO

Kaiser–Meyer–Olkin

AIC

Akaike information

BIC

Bayesian information

MLR

Multilevel logistic regression

BMI

Body mass index

TI

Tertile I

Notes

Acknowledgments

Natalia Tumas and CamilaNiclis’s research was supported by fellowships provided by the National Scientific and Technical Research Council (CONICET) and by the Science and Technology Secretary of the National University of Córdoba. This research was supported by the National Science and Technology Agency, FONCyT Grant PICT 2008-1814, PICT-O 2005-36035, and Science and Technical Secretariat of the University of Córdoba (SECyT-UNC) Grant 05/H207. The authors also would like to acknowledge the following institutions and physicians: Hospital Misericordia, Maternidad Nacional, Hospital La Calera, EMERCO, Clínica Privada Jesús María, Dispensarios Municipales of La Calera, Cuesta Colorada, Salsipuedes and La Granja, Drs. Perazzolo A, Chalimond E, Roldán E. and Sarmiento J.

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Natalia Tumas
    • 1
    • 2
    • 3
  • Camila Niclis
    • 1
    • 4
    • 3
  • Laura R. Aballay
    • 1
    • 3
  • Alberto R. Osella
    • 5
    • 6
  • María del Pilar Díaz
    • 1
    • 3
  1. 1.Statistics and Biostatistics Unit, School of Nutrition, Faculty of Medical SciencesNational University of CórdobaCórdobaArgentina
  2. 2.Center of Research and Studies in Culture and SocietyNational Council of Scientific and Technical Research (CONICET)CórdobaArgentina
  3. 3.Enrique Barros ESQ. Enfermera GordilloCiudad UniversitariaCórdobaArgentina
  4. 4.National Council of Scientific and Technical Research (CONICET)CórdobaArgentina
  5. 5.Laboratorio di Epidemiologia E BiostatisticaIRCCS Saverio de BellisCastellana GrotteItaly
  6. 6.Castellana Grotte, BariItaly

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