Skip to main content
Log in

Epidemiology

RETRACTED ARTICLE: Dietary patterns and their associations with socio-demographic and lifestyle factors in Tasmanian older adults: a longitudinal cohort study

  • Article
  • Published:
European Journal of Clinical Nutrition Submit manuscript

A Retraction to this article was published on 05 December 2019

This article has been updated

Abstract

Background/Objectives:

We aimed to examine dietary patterns and their longitudinal associations with socio-demographic and lifestyle factors in older adults.

Subjects/Methods:

A cohort of 1098 participants aged 50–80 years were followed for 5 years. Dietary intake was assessed at baseline, 2.6 and 5 years using a validated food frequency questionnaire. Dietary patterns were identified at baseline using exploratory factor analysis and pattern scores for each calculated using the weighted sum score method. Associations of dietary pattern scores with participants’ characteristics were assessed using linear mixed-effects models.

Results:

The three dietary patterns identified and the food groups of which they were predominantly composed were as follows: a healthy dietary pattern (vegetables, fruits, nuts, and whole grains); a western dietary pattern (pizza, hamburgers, chips, and potatoes); and a meat and vegetable dietary pattern (red meat, fish, poultry, vegetables, potatoes, and legumes). Being a man, unemployed, a current smoker, less educated, and residing in a socially disadvantaged area were associated with lower healthy dietary pattern scores, but these differences lessened over time, except in current smokers (p < 0.03 for interactions with time). Being a man was associated with higher, but being a current smoker with lower western dietary pattern scores (β = 8.0, 95% CI: 5.3,10.7 and − 6.7: − 10.1,− 3.3, respectively). For the meat and vegetable dietary pattern, being a man and a current smoker were associated with lower scores (β = − 24.9, 95% CI: − 44.9,− 4.9 and − 66.8: − 98.3,− 35.3, respectively), while being unemployed was associated with higher scores but this difference lessened over time (p = 0.018 for interaction with time).

Conclusions:

In older adults, men, smokers, and those experiencing social disadvantage could be target groups for interventions to improve diets.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Change history

  • 05 December 2019

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

References

  1. Iburg KM. Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017;390:1260–344.

    Article  Google Scholar 

  2. Epidemiology Unit, Tasmanian Department of Health and Human Services. Health IndicatorsTasmania 2013. Hobart, Tasmania: Government of Tasmania; 2013.

  3. Uauy R, Kain J, Mericq V, Rojas J, Corvalán C. Nutrition, child growth, and chronic disease prevention. Ann Med. 2008;40:11–20.

    Article  CAS  Google Scholar 

  4. Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2224–60.

    Article  Google Scholar 

  5. Flood A, Rastogi T, Wirfält E, Mitrou PN, Reedy J, Subar AF, et al. Dietary patterns as identified by factor analysis and colorectal cancer among middle-aged Americans. Am J Clin Nutr. 2008;88:176–84.

    Article  CAS  Google Scholar 

  6. Kim J, Yu A, Choi B, Nam J, Kim M, Oh D, et al. Dietary patterns and cognitive function in Korean older adults. Eur J Nutr. 2015;54:309–18.

    Article  Google Scholar 

  7. Cade JE, Taylor EF, Burley VJ, Greenwood DC. Does the Mediterranean dietary pattern or the Healthy Diet Index influence the risk of breast cancer in a large British cohort of women? Eur J Clin Nutr. 2011;65:920–8.

    Article  CAS  Google Scholar 

  8. Ocké MC. Evaluation of methodologies for assessing the overall diet: dietary quality scores and dietary pattern analysis. Proc Nutr Soc. 2013;72:191–9.

    Article  Google Scholar 

  9. Newby P, Tucker KL. Empirically derived eating patterns using factor or cluster analysis: a review. Nutr Rev. 2004;62:177–203.

    Article  CAS  Google Scholar 

  10. Jomaa L, Hwalla N, Itani L, Chamieh MC, Mehio-Sibai A, Naja F. A Lebanese dietary pattern promotes better diet quality among older adults: findings from a national cross-sectional study. BMC Geriatr. 2016;16:85.

    Article  Google Scholar 

  11. De Castro MBT, Vilela AAF, de Oliveira ASD, Cabral M, de Souza RAG, Kac G, et al. Sociodemographic characteristics determine dietary pattern adherence during pregnancy. Public Health Nutr. 2016;19:1245–51.

    Article  Google Scholar 

  12. Fabian C, Pagan I, Rios JL, Betancourt J, Cruz SY, González AM, et al. Dietary patterns and their association with sociodemographic characteristics and perceived academic stress of college students in Puerto Rico. PR Health Sci J. 2013;32:36–43.

    Google Scholar 

  13. Yang J, Dang S, Cheng Y, Qiu H, Mi B, Jiang Y, et al. Dietary intakes and dietary patterns among pregnant women in Northwest China. Public Health Nutr. 2017;20:282–93.

    Article  Google Scholar 

  14. Olinto MTA, Willett WC, Gigante DP, Victora CG. Sociodemographic and lifestyle characteristics in relation to dietary patterns among young Brazilian adults. Public Health Nutr. 2011;14:150–9.

    Article  Google Scholar 

  15. Deshmukh-Taskar PR, O’Neil CE, Nicklas TA, Yang S-J, Liu Y, Gustat J, et al. Dietary patterns associated with metabolic syndrome, sociodemographic and lifestyle factors in young adults: the Bogalusa Heart Study. Public Health Nutr. 2009;12:2493–503.

    Article  Google Scholar 

  16. Naja F, Nasreddine L, Itani L, Chamieh MC, Adra N, Sibai AM, et al. Dietary patterns and their association with obesity and sociodemographic factors in a national sample of Lebanese adults. Public Health Nutr. 2011;14:1570–8.

    Article  Google Scholar 

  17. Rezazadeh A, Rashidkhani B, Omidvar N. Association of major dietary patterns with socioeconomic and lifestyle factors of adult women living in Tehran, Iran. Nutr. 2010;26:337–41.

    Article  Google Scholar 

  18. Markussen MS, Veierød MB, Kristiansen AL, Ursin G, Andersen LF. Dietary patterns of women aged 50–69 years and associations with nutrient intake, sociodemographic factors and key risk factors for non-communicable diseases. Public Health Nutr. 2016;19:2024–32.

    Article  Google Scholar 

  19. Andreeva VA, Allès B, Feron G, Gonzalez R, Sulmont-Rossé C, Galan P, et al. Sex-specific sociodemographic correlates of dietary patterns in a large sample of French elderly individuals. Nutrients. 2016;8:484.

    Article  Google Scholar 

  20. Hsiao PY, Mitchell DC, Coffman DL, Allman RM, Locher JL, Sawyer P, et al. Dietary patterns and diet quality among diverse older adults: The university of Alabama at Birmingham study of aging. J Nutr Health Aging. 2013;17:19–25.

    Article  CAS  Google Scholar 

  21. Harrington JM, Dahly DL, Fitzgerald AP, Gilthorpe MS, Perry IJ. Capturing changes in dietary patterns among older adults: A latent class analysis of an ageing Irish cohort. Public Health Nutr. 2014;17:2674–86.

    Article  Google Scholar 

  22. Gardener SL, Rainey-Smith SR, Barnes MB, Sohrabi HR, Weinborn M, Lim YY, et al. Dietary patterns and cognitive decline in an Australian study of ageing. Mol Psychiatry. 2015;20:860–6.

    Article  CAS  Google Scholar 

  23. Keogh JB, Lange K, Syrette J. Comparative analysis of two FFQ. Public Health Nutr. 2010;13:1553–8.

    Article  Google Scholar 

  24. Hebden L, Kostan E, O’Leary F, Hodge A, Allman-Farinelli M. Validity and reproducibility of a food frequency questionnaire as a measure of recent dietary intake in young adults. PLoS ONE. 2013;8:e75156.

    Article  CAS  Google Scholar 

  25. Ding C, Quinn S, Jones G, Cicuttini F, Parameswaran V, Burgess J. Serum levels of vitamin D, sunlight exposure, and knee cartilage loss in older adults: The Tasmanian Older Adult Cohort Study. Arthritis Rheum. 2009;60:1381–9.

    Article  Google Scholar 

  26. Dore D, Quinn S, Ding C, Winzenberg T, Jones G. Correlates of subchondral BMD: a cross‐sectional study. J Bone Miner Res. 2009;24:2007–15.

    Article  Google Scholar 

  27. Brennan S, Winzenberg T, Pasco J, Wluka A, Dobbins A, Jones G. Social disadvantage, bone mineral density and vertebral wedge deformities in the Tasmanian Older Adult Cohort. Osteoporos Int. 2013;24:1909–16.

    Article  CAS  Google Scholar 

  28. Australian Bureau of Statistics Census of population and housing: Socio-economic indexes for areas; Australia 2001 number 2039.0. Canberra, Australia: Australian Bureau of Statistics; 2001.

    Google Scholar 

  29. Scott D, Blizzard L, Fell J, Jones G. Prospective associations between ambulatory activity, body composition and muscle function in older adults. Scand J Med Sci Sports. 2011;21:e168–e175.

    Article  CAS  Google Scholar 

  30. Osborne JW. What is rotating in exploratory factor analysis? Prac Assess Res Eval. 2015;20:2.

    Google Scholar 

  31. Beavers AS, Lounsbury JW, Richards JK, Huck SW, Skolits GJ, Esquivel SL, Practical considerations for using exploratory factor analysis in educational research. Prac Assess Res Eval. 2013;18:1–13.

    Google Scholar 

  32. Williams B, Onsman A, Brown T. Exploratory factor analysis: A five-step guide for novices. Australasian J Paramed. 2010;8:1–13.

    Google Scholar 

  33. StataCorp. In. Texax 77845 USA ed: College Station, 2016.

  34. Thorpe MG, Milte CM, Crawford D, McNaughton SA. A comparison of the dietary patterns derived by principal component analysis and cluster analysis in older Australians. Int J Behav Nutr Phys Act. 2016;13:1–14.

    Article  Google Scholar 

  35. Junor A. The meat and veg complex: food and national progress in Australian print media, 1930–65. Hist Aust. 2016;13:474–89.

    Article  Google Scholar 

  36. Allen P, Sachs C, Women and food chains: The gendered politics of food. Int J Sciol Agri Food. 2007;15:1–23.

    Article  Google Scholar 

  37. Wardle J, Haase AM, Steptoe A, Nillapun M, Jonwutiwes K, Bellisle F. Gender differences in food choice: the contribution of health beliefs and dieting. Ann Behav Med. 2004;27:107–16.

    Article  Google Scholar 

  38. Campos S, Doxey J, Hammond D. Nutrition labels on pre-packaged foods: a systematic review. Public Health Nutr. 2011;14:1496–506.

    Article  Google Scholar 

  39. Kettings C, Sinclair AJ, Voevodin M. A healthy diet consistent with Australian health recommendations is too expensive for welfare‐dependent families. Aust N Z J Public Health. 2009;33:566–72.

    Article  Google Scholar 

  40. Darmon N, Drewnowski A. Does social class predict diet quality? Am J Clin Nutr. 2008;87:1107–17.

    Article  CAS  Google Scholar 

  41. Mayén AL, Paccaud F, Bovet P, Stringhini S, Marques-Vidal P. Socioeconomic determinants of dietary patterns in low- and middle-income countries: a systematic review. Am J Clin Nutr. 2014;100:1520–31.

    Article  Google Scholar 

Download references

Acknowledgements

We thank all organizations that have provided funding for this research.

Funding:

Fundings were provided by National Health and Medical Research Council of Australia (302204); Arthritis Foundation of Australia (MRI0616); Tasmanian Community Fund (D0015018); Masonic Centenary Medical Research Foundation; and University of Tasmania Institutional Research Grants Scheme (D0015019). Sharon L Brennan-Olsen was supported by a National Health and Medical Research Council (NHMRC) of Australia Career Development Fellowship (GNT1107510). Feitong Wu is supported by an Arthritis Foundation Australia – Australian Rheumatology Association Heald Fellowship, funded by the Australian Rheumatology Association and Vincent Fairfax Family Foundation

Author contributions:

TW assisted in developing the research proposal, editing the manuscript, and provision of analytical advice. GJ, Chief Investigator of TASOAC contributed access to the study, and expertise in identifying exposures, confounders and outcomes. KW contributed expertise in analyzing and interpreting the dietary patterns. WO provided advice relating to interpretation of the dietary patterns identified in this study, and reviewed drafts of the manuscript. FW contributed to the interpretation of findings and revised the draft of the manuscript. SB-O cross-matched and coded the SEIFA data, contributed to the interpretation of findings relating to those data, and revised the draft of this manuscript. HHN wrote research proposal and manuscript, analyzed and interpreted data, and edited manuscript for publication.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tania Winzenberg.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

The authors have retracted this article [1] after discovering a major error in the data analysis made when generating the grouped items used in the factor analysis generating the dietary patterns. Because the error is in the foundations of the analysis, it means that the dietary patterns identified were themselves erroneous and their associations with socio-demographic factors are also incorrect. A re-analysis showed up major differences in outcomes when compared with those in [1]. The authors have been given the opportunity to submit a new manuscript for peer review. All authors agree with this retraction.

[1] Hoa H Nguyen, Feitong Wu, Wendy H Oddy, Karen Wills, Sharon L Brennan-Olsen, Graeme Jones & Tania Winzenberg. Dietary patterns and their associations with socio-demographic and lifestyle factors in Tasmanian older adults: a longitudinal cohort study. 2019 May;73(5):714-723

Electronic supplementary material

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nguyen, H.H., Wu, F., Oddy, W.H. et al. RETRACTED ARTICLE: Dietary patterns and their associations with socio-demographic and lifestyle factors in Tasmanian older adults: a longitudinal cohort study. Eur J Clin Nutr 73, 714–723 (2019). https://doi.org/10.1038/s41430-018-0264-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41430-018-0264-1

  • Springer Nature Limited

Navigation