Skip to main content Accessibility help
×
Home

Evaluation of methodologies for assessing the overall diet: dietary quality scores and dietary pattern analysis

  • Marga C. Ocké (a1)

Abstract

This paper aims to describe different approaches for studying the overall diet with advantages and limitations. Studies of the overall diet have emerged because the relationship between dietary intake and health is very complex with all kinds of interactions. These cannot be captured well by studying single dietary components. Three main approaches to study the overall diet can be distinguished. The first method is researcher-defined scores or indices of diet quality. These are usually based on guidelines for a healthy diet or on diets known to be healthy. The second approach, using principal component or cluster analysis, is driven by the underlying dietary data. In principal component analysis, scales are derived based on the underlying relationships between food groups, whereas in cluster analysis, subgroups of the population are created with people that cluster together based on their dietary intake. A third approach includes methods that are driven by a combination of biological pathways and the underlying dietary data. Reduced rank regression defines linear combinations of food intakes that maximally explain nutrient intakes or intermediate markers of disease. Decision tree analysis identifies subgroups of a population whose members share dietary characteristics that influence (intermediate markers of) disease. It is concluded that all approaches have advantages and limitations and essentially answer different questions. The third approach is still more in an exploration phase, but seems to have great potential with complementary value. More insight into the utility of conducting studies on the overall diet can be gained if more attention is given to methodological issues.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

      Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Evaluation of methodologies for assessing the overall diet: dietary quality scores and dietary pattern analysis
      Available formats
      ×

      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

      Evaluation of methodologies for assessing the overall diet: dietary quality scores and dietary pattern analysis
      Available formats
      ×

      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

      Evaluation of methodologies for assessing the overall diet: dietary quality scores and dietary pattern analysis
      Available formats
      ×

Copyright

Corresponding author

Corresponding author: Dr Marga Ocké, fax +31 30 274 4466, email marga.ocke@rivm.nl

References

Hide All
1. Newby, PK & Tucker, KL (2004) Empirically derived eating patterns using factor or cluster analysis: a review. Nutr Rev 62, 177203.
2. Kant, AK (2004) Dietary patterns and health outcomes. J Am Diet Assoc 104, 615635.
3. Schulze, MB & Hoffmann, K (2006) Methodological approaches to study dietary patterns in relation to risk of coronary heart disease and stroke. Br J Nutr 95, 860869.
4. Jacobs, DR Jr & Steffen, LM (2003) Nutrients, foods, and dietary patterns as exposures in research: a framework for food synergy. Am J Clin Nutr 78, Suppl. 3, 508S513S.
5. World Health Organisation (2003) Diet, Nutrition and the Prevention of Chronic Diseases. Joint WHO–FAO Expert Consulation. World Health Organisation Technical Report Series No. 916. Geneva: WHO.
6. Moeller, SM, Reedy, J, Millen, AE et al. (2007) Dietary patterns: challenges and opportunities in dietary patterns research an Experimental Biology workshop, April 1, 2006. J Am Diet Assoc 107, 12331239.
7. Waijers, PM, Feskens, EJ & Ocke, MC (2007) A critical review of predefined diet quality scores. Br J Nutr 97, 219231.
8. Hoffmann, K, Schulze, MB, Schienkiewitz, A et al. (2004) Application of a new statistical method to derive dietary patterns in nutritional epidemiology. Am J Epidemiol 159, 935944.
9. Hearty, AP & Gibney, MJ (2008) Analysis of meal patterns with the use of supervised data mining techniques–artificial neural networks and decision trees. Am J Clin Nutr 88, 16321642.
10. Arvaniti, F & Panagiotakos, DB (2008) Healthy indexes in public health practice and research: a review. Crit Rev Food Sci Nutr 48, 317327.
11. Wirt, A & Collins, CE (2009) Diet quality – what is it and does it matter? Public Health Nutr 12, 24732492.
12. Lazarou, C & Newby, PK (2011) Use of dietary indexes among children in developed countries. Adv Nutr 2, 295303.
13. Guenther, PM, Reedy, J & Krebs-Smith, SM (2008) Development of the healthy eating index-2005. J Am Diet Assoc 108, 18961901.
14. Kennedy, ET, Ohls, J, Carlson, S et al. (1995) The healthy eating index: design and applications. J Am Diet Assoc 95, 11031108.
15. Trichopoulou, A, Kouris-Blazos, A, Wahlqvist, ML et al. (1995) Diet and overall survival in elderly people. BMJ 311, 14571460.
16. Krebs-Smith, S, Guenther, P, O'Connell, K et al. (2012) Development and evaluation of the Healthy Eating Index-2010. In Eight International Conference on Diet and Activity Methods, 14–17 May 2012, FAO, Rome. Abstract book OC 038, 34–35.
17. Glanville, NT & McIntyre, L (2006) Diet quality of Atlantic families headed by single mothers. Can J Diet Pract Res 67, 2835.
18. Feskanich, D, Rockett, HR & Colditz, GA (2004) Modifying the Healthy Eating Index to assess diet quality in children and adolescents. J Am Diet Assoc 104, 13751383.
19. Keys, A & Grande, F (1957) Role of dietary fat in human nutrition. III. Diet and the epidemiology of coronary heart disease. Am J Public Health Nations Health 47, 15201530.
20. Mila-Villarroel, R, Bach-Faig, A, Puig, J et al. (2011) Comparison and evaluation of the reliability of indexes of adherence to the Mediterranean diet. Public Health Nutr 14, 23382345.
21. Bach, A, Serra-Majem, L, Carrasco, JL et al. (2006) The use of indexes evaluating the adherence to the Mediterranean diet in epidemiological studies: a review. Public Health Nutr 9, 132146.
22. Trichopoulou, A, Kouris-Blazos, A, Vassilakou, T et al. (1995) Diet and survival of elderly Greeks: a link to the past. Am J Clin Nutr 61, 1346S1350S.
23. Sofi, F, Abbate, R, Gensini, GF et al. (2010) Accruing evidence on benefits of adherence to the Mediterranean diet on health: an updated systematic review and meta-analysis. Am J Clin Nutr 92, 11891196.
24. Kant, AK (1996) Indexes of overall diet quality: a review. J Am Diet Assoc 96, 785791.
25. Guenther, PM, Reedy, J, Krebs-Smith, SM et al. (2008) Evaluation of the Healthy Eating Index-2005. J Am Diet Assoc 108, 18541864.
26. Fransen, HP & Ocke, MC (2008) Indices of diet quality. Curr Opin Clin Nutr Metab Care 11, 559565.
27. Kourlaba, G & Panagiotakos, DB (2009) Dietary quality indices and human health: a review. Maturitas 62, 18.
28. Zhang, S, Midthune, D, Guenther, PM et al. (2011) A new multivariate measurement error model with zero-inflated dietary data, and its application to dietary assessment. Ann Appl Stat 5, 14561487.
29. Kipnis, V, Subar, AF, Midthune, D et al. (2003) Structure of dietary measurement error: results of the OPEN biomarker study. Am J Epidemiol 158, 1421; discussion 22–16.
30. Apovian, CM, Murphy, MC, Cullum-Dugan, D et al. (2010) Validation of a web-based dietary questionnaire designed for the DASH (dietary approaches to stop hypertension) diet: the DASH online questionnaire. Public Health Nutr 13, 615622.
31. Kennedy, G, Berardo, A, Papavero, C et al. (2010) Proxy measures of household food consumption for food security assessment and surveillance: comparison of the household dietary diversity and food consumption scores. Public Health Nutr 13, 20102018.
32. Devlin, UM, McNulty, BA, Nugent, AP et al. (2012) The use of cluster analysis to derive dietary patterns: methodological considerations, reproducibility, validity and the effect of energy mis-reporting. Proc Nutr Soc 71, 599609.
33. Gorst-Rasmussen, A, Dahm, CC, Dethlefsen, C et al. (2011) Exploring dietary patterns by using the treelet transform. Am J Epidemiol 173, 10971104.
34. Imamura, F & Jacques, PF (2011) Invited commentary: dietary pattern analysis. Am J Epidemiol 173, 11051108.
35. Bailey, RL, Gutschall, MD, Mitchell, DC et al. (2006) Comparative strategies for using cluster analysis to assess dietary patterns. J Am Diet Assoc 106, 11941200.
36. Balder, HF, Virtanen, M, Brants, HA et al. (2003) Common and country-specific dietary patterns in four European cohort studies. J Nutr 133, 42464251.
37. Northstone, K, Ness, AR, Emmett, PM et al. (2008) Adjusting for energy intake in dietary pattern investigations using principal components analysis. Eur J Clin Nutr 62, 931938.
38. Devlin, UM, McNulty, BA, Nugent, AP et al. (2012) The use of cluster analysis to derive dietary patterns: methodological considerations, reproducibility, validity and the effect of energy mis-reporting. Proc Nutr Soc, 111.
39. Reedy, J, Wirfalt, E, Flood, A et al. (2010) Comparing 3 dietary pattern methods – cluster analysis, factor analysis, and index analysis – with colorectal cancer risk: the NIH-AARP Diet and Health Study. Am J Epidemiol 171, 479487.
40. Hu, FB (2002) Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol 13, 39.
41. Hu, FB, Rimm, E, Smith-Warner, SA et al. (1999) Reproducibility and validity of dietary patterns assessed with a food-frequency questionnaire. Am J Clin Nutr 69, 243249.
42. Lo Siou, G, Yasui, Y, Csizmadi, I et al. (2011) Exploring statistical approaches to diminish subjectivity of cluster analysis to derive dietary patterns: The Tomorrow Project. Am J Epidemiol 173, 956967.
43. Lau, C, Glumer, C, Toft, U et al. (2008) Identification and reproducibility of dietary patterns in a Danish cohort: the Inter99 study. Br J Nutr 99, 10891098.
44. Quatromoni, PA, Copenhafer, DL, Demissie, S et al. (2002) The internal validity of a dietary pattern analysis. The Framingham Nutrition Studies. J Epidemiol Community Health 56, 381388.
45. Hearty, AP & Gibney, MJ (2009) Comparison of cluster and principal component analysis techniques to derive dietary patterns in Irish adults. Br J Nutr 101, 598608.
46. Engeset, D, Alsaker, E, Ciampi, A et al. (2005) Dietary patterns and lifestyle factors in the Norwegian EPIC cohort: the Norwegian Women and Cancer (NOWAC) study. Eur J Clin Nutr 59, 675684.
47. van Dam, RM, Grievink, L, Ocke, MC et al. (2003) Patterns of food consumption and risk factors for cardiovascular disease in the general Dutch population. Am J Clin Nutr 77, 11561163.
48. Hoffmann, K, Zyriax, BC, Boeing, H et al. (2004) A dietary pattern derived to explain biomarker variation is strongly associated with the risk of coronary artery disease. Am J Clin Nutr 80, 633640.
49. Camp, NJ & Slattery, ML (2002) Classification tree analysis: a statistical tool to investigate risk factor interactions with an example for colon cancer (United States). Cancer Causes Control 13, 813823.
50. Vujkovic, M, Steegers, EA, Looman, CW et al. (2009) The maternal Mediterranean dietary pattern is associated with a reduced risk of spina bifida in the offspring. BJOG 116, 408415.
51. Kroke, A (2004) Re: ‘Application of a new statistical method to derive dietary patterns in nutritional epidemiology’. Am J Epidemiol 160, 1132.
52. Lemon, SC, Roy, J, Clark, MA et al. (2003) Classification and regression tree analysis in public health: methodological review and comparison with logistic regression. Ann Behav Med 26, 172181.
53. Teng, JH, Lin, KC & Ho, BS (2007) Application of classification tree and logistic regression for the management and health intervention plans in a community-based study. J Eval Clin Pract 13, 741748.
54. Cooper, JG & Purcell, GP (2006) Data mining for correlations between diet and Crohn's disease activity. AMIA Annu Symp Proc 2006, 897.
55. Valavanis, IK, Mougiakakou, SG, Grimaldi, KA et al. (2010) A multifactorial analysis of obesity as CVD risk factor: use of neural network based methods in a nutrigenetics context. BMC Bioinformatics 11, 453.
56. Huang, S, Xu, Y, Yue, L et al. (2010) Evaluating the risk of hypertension using an artificial neural network method in rural residents over the age of 35 years in a Chinese area. Hypertens Res 33, 722726.
57. Park, J & Edington, DW (2004) Application of a prediction model for identification of individuals at diabetic risk. Methods Inf Med 43, 273281.
58. Tucker, KL (2010) Dietary patterns, approaches, and multicultural perspective. Appl Physiol Nutr Metab 35, 211218.
59. DiBello, JR, Kraft, P, McGarvey, ST et al. (2008) Comparison of 3 methods for identifying dietary patterns associated with risk of disease. Am J Epidemiol 168, 14331443.
60. Manios, Y, Kourlaba, G, Grammatikaki, E et al. (2010) Comparison of two methods for identifying dietary patterns associated with obesity in preschool children: the GENESIS study. Eur J Clin Nutr 64, 14071414.
61. Nettleton, JA, Steffen, LM, Schulze, MB et al. (2007) Associations between markers of subclinical atherosclerosis and dietary patterns derived by principal components analysis and reduced rank regression in the Multi-Ethnic Study of Atherosclerosis (MESA). Am J Clin Nutr 85, 16151625.
62. Hoffmann, K, Boeing, H, Boffetta, P et al. (2005) Comparison of two statistical approaches to predict all-cause mortality by dietary patterns in German elderly subjects. Br J Nutr 93, 709716.
63. Kant, AK (2010) Dietary patterns: biomarkers and chronic disease risk. Appl Physiol Nutr Metab 35, 199206.
64. van Dam, RM (2005) New approaches to the study of dietary patterns. Br J Nutr 93, 573574.
65. Dasgupta, A, Sun, YV, Konig, IR et al. (2011) Brief review of regression-based and machine learning methods in genetic epidemiology: the Genetic Analysis Workshop 17 experience. Genet Epidemiol 35, Suppl. 1, S5S11.
66. Jacques, PF & Tucker, KL (2001) Are dietary patterns useful for understanding the role of diet in chronic disease? Am J Clin Nutr 73, 12.
67. van Ommen, B, Keijer, J, Heil, SG et al. (2009) Challenging homeostasis to define biomarkers for nutrition related health. Mol Nutr Food Res 53, 795804.
68. Gallagher, AM, Meijer, GW, Richardson, DP et al. (2011) A standardised approach towards PROving the efficacy of foods and food constituents for health CLAIMs (PROCLAIM): providing guidance. Br J Nutr 106, Suppl. 2, S16S28.

Keywords

Evaluation of methodologies for assessing the overall diet: dietary quality scores and dietary pattern analysis

  • Marga C. Ocké (a1)

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed