Application of a New Statistical Method to Derive Dietary Patterns in Nutritional Epidemiology

Hoffmann, Kurt; Schulze, Matthias B.; Schienkiewitz, Anja; Nöthlings, Ute; Boeing, Heiner

doi:10.1093/aje/kwh134

Cited by 562 publications

(718 citation statements)

References 48 publications

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“…Similar comparison studies also showed that in general PCA-derived patterns explain more variance of the food groups but explain less of the variance in response variables (Hoffmann et al 2005;Hoffmann et al 2004). Our first RRR pattern explained 40.5% of the response variable variation, which is in line with results from other studies (Biesbroek et al 2015;Hoffmann et al 2005;Hoffmann et al 2004), but clearly leaves a proportion of the variance unexplained. Other factors, such as socioeconomic status, age, or gender might also impact GHG emissions of the diet and dietary quality.…”

Section: Discussionmentioning

confidence: 53%

“…Examples of these models are principle component analysis (PCA) or cluster analysis (CA) (Hearty and Gibney 2009;Newby and Tucker 2004;Stricker et al 2013). Both a priori and a posteriori techniques have been combined in a relatively new method: reduced rank regression (RRR) (Hoffmann et al 2004). When combining dietary information with known biomarkers for a disease, RRR was able to derive dietary patterns that showed stronger associations with a particular disease than PCA-based patterns (Hoffmann et al 2004;Nettleton et al 2007;Schulze and Hoffmann 2006).…”

Section: Introductionmentioning

confidence: 99%

“…Both a priori and a posteriori techniques have been combined in a relatively new method: reduced rank regression (RRR) (Hoffmann et al 2004). When combining dietary information with known biomarkers for a disease, RRR was able to derive dietary patterns that showed stronger associations with a particular disease than PCA-based patterns (Hoffmann et al 2004;Nettleton et al 2007;Schulze and Hoffmann 2006). This hybrid approach is partly theoretically driven, by using variables that are relevant to answer the research question, but still identifies dietary patterns based on the data.…”

Section: Introductionmentioning

confidence: 99%

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Identification of data-driven Dutch dietary patterns that benefit the environment and are healthy

et al. 2018

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More sustainable dietary patterns are needed to mitigate global warming. This study aims to identify data-driven healthy dietary patterns that benefit the environment. In EPIC-NL, diet was assessed using a 178-item FFQ in 36,203 participants aged 20-70 years between 1993 and 1997. The Dutch Healthy Diet index 2015 (DHD15-index) was used to score healthiness of the diet. As proxy for environmental impact, greenhouse gas (GHG) emissions were calculated using life cycle analysis. To determine patterns that are both healthy and environmentally friendly, reduced rank regression was applied. A BPlant-based Pattern^characterized by high consumption of fruits, vegetables, and legumes, and low consumption of fries, red meat, and processed meat and a BDairy-based Pattern^characterized by high consumption of dairy, and nuts and seeds and low consumption of coffee and tea, sugar-containing sodas, lowfiber bread, and savory sauces were derived. At equal energy intake, the diet of adherents (highest quartile) to the BPlant-based Pattern^were significantly healthier (89.8 points on the DHD15-index, p < 0.0001) and more sustainable (3.96 kg C0 2 -eq/day, p < 0.0001) compared to the average diet (76.2 points, 4.06 kg C0 2 -eq/day), whereas the BDairy-based Pattern^was somewhat healthier (77.9 points, p < 0.0001), but less sustainable (4.43 kg C0 2 -eq/day, p < 0.0001). When deriving dietary patterns based on health and environmental aspects of the diets, a BPlant-based^and a BDairy-based^pattern were observed in our study population. Of these, the plant-based diet benefits health as well as the environment.

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Section: Discussionmentioning

confidence: 53%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Identification of data-driven Dutch dietary patterns that benefit the environment and are healthy

et al. 2018

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“…The utilization of both methods has gained increasing popularity in the past decade and the literature has burgeoned in recent years 7,8,9 . The main technique used in the "a posteriori" approach is the analysis of principal components and subsequent factor analysis 10 .…”

Section: Introductionmentioning

confidence: 99%

Dietary patterns and risk of oral and pharyngeal cancer: a case-control study in Rio de Janeiro, Brazil

Toledo

Koifman

et al. 2010

Cad. Saúde Pública

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The study investigated IntroductionOral and pharyngeal cancer, grouped together, represent the sixth most common cancer in the world 1 . The annual estimated incidence is around 275,000 for oral and 130,300 for pharyngeal cancers excluding nasopharynx, with twothirds of these cases occurring in developing countries 1 . There is a wide geographical variation (approximately 20-fold) in the incidence of this cancer, and parts of Latin America and the Caribbean (including Brazil, Uruguay and Puerto Rico) are characterized by high incidence rates for oral cancer (excluding lip) 1 . In Brazil, excluding skin cancer, oral and pharynx cancer represent the fifth incidence of cancer in men and the seventh in women. The incidence rates ranged from 2.9/100,000 in Belém, Pará State (1996-1998) to 7.6/100,000 in São Paulo (1997)(1998) 2 . The most recent Brazilian National Cancer Institute (INCA) estimates for Rio de Janeiro State are 1,510 new cases for men and 520 for women 3 . Most are squamous cell carcinomas that develop after exposure to carcinogens such as tobacco and alcohol 4 . Oral and pharyngeal cancer involves complex causality, but available evidences suggest that environmental factors are driving the geographic patterns 5 .The role of diet in the etiology of oral and pharyngeal cancer remains unresolved. A recent revision concluded that consumption of non-starchy vegetables, fruits, and foods containing carote-ARTIGO ARTICLE

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“…To investigate the effect of overall diet on chronic diseases, other studies have identified dietary patterns using factor analysis and/or cluster analysis or a more recent method called reduced rank regression (Hu, 2002;Hoffmann et al, 2004;Kant, 2004;Schulze and Hoffmann, 2006).…”

Section: Introductionmentioning

confidence: 99%

Dietary patterns and their sociodemographic and behavioural correlates in French middle-aged adults from the SU.VI.MAX cohort

et al. 2008

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Background/Objectives: Few studies have investigated dietary patterns among French adults. We aimed to identify dietary patterns and their relation with nutrient intakes, sociodemographic, lifestyle and other health indicators in a large population of middle-aged subjects living in France. Subjects/Methods: Dietary patterns were identified using factor analysis in 5194 women and men aged 45-60 years enrolled in the SU.VI.MAX (Supplémentation en Vitamines et Minéraux Antioxydants) study. Dietary data were based on repeated 24-h dietary records (at least six records during 2 years). Results: Four patterns were identified: (1) 'alcohol and meat products'; (2) 'prudent diet'; (3) 'convenience foods'; and (4) 'starch, sauces, and vegetables'. The first pattern was positively associated with low education, smoking and overweight in both genders, as well as with abdominal obesity in women and treated hyperlipidaemia and/or hypertension in men. The second pattern was positively correlated with high education and being older than 55 years and negatively correlated with current smoking. This pattern was also associated with overweight and low waist circumference in women and with hyperlipidaemia treatment in men. The third pattern was inversely related to age and positively related to higher education in both genders. In men, higher scores were related to living alone and an urban residence. The fourth pattern was associated with high education and an urban residence in men only. Conclusions: Our study identified four dietary patterns in this population of French middle-aged adults. Associations with sociodemographic, behavioural and health-related factors were found to differ according to dietary patterns. Sex-specific relationships were also found.

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Application of a New Statistical Method to Derive Dietary Patterns in Nutritional Epidemiology

Cited by 562 publications

References 48 publications

Identification of data-driven Dutch dietary patterns that benefit the environment and are healthy

Identification of data-driven Dutch dietary patterns that benefit the environment and are healthy

Dietary patterns and risk of oral and pharyngeal cancer: a case-control study in Rio de Janeiro, Brazil

Dietary patterns and their sociodemographic and behavioural correlates in French middle-aged adults from the SU.VI.MAX cohort

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