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Nutrient patterns and their relation to general and abdominal obesity in Iranian adults: findings from the SEPAHAN study

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Abstract

Background

Few studies have linked major dietary nutrient patterns to chronic diseases. Despite the growing evidence of associations between dietary patterns and obesity, we are aware of no study that examined the association between patterns of nutrient intake and obesity.

Objective

To identify major nutrient patterns in Iranian adults and investigate their association with general and abdominal obesity.

Methods

In this cross-sectional study that was conducted under the framework of the Study on the Epidemiology of Psychological Alimentary Health and Nutrition (SEPAHAN), dietary data were collected using a validated dish-based 106-item semi-quantitative food frequency questionnaire in 8691 subjects aged 18–55 years. Complete data of 6724 and 5203 adults were available for general and abdominal obesity, respectively. Data on anthropometric measures were collected through a self-administered questionnaire. General obesity was defined as body mass index ≥ 30 kg/m2, and abdominal obesity as waist circumference > 102 cm for men and >88 cm for women. Daily intakes of 38 nutrients and bioactive compounds were calculated for each participant. Factor analysis, followed by a varimax rotation, was applied to derive major nutrient patterns.

Results

Three major nutrient patterns were identified: (1) The first pattern was high in fatty acids (including saturated, monounsaturated and polyunsaturated fatty acids), cholesterol, vitamin B12, vitamin E, zinc, choline, protein, pyridoxine, phosphorus and pantothenic acid; (2) the second pattern was high in thiamine, betaine, starch, folate, iron, selenium, niacin, calcium, and manganese; and (3) the third pattern was high in glucose, fructose, sucrose, vitamin C, potassium, total dietary fiber, copper and vitamin K. Men in the highest quintile of the second pattern were less likely to be generally obese in the fully adjusted model [odds ratio (OR) 0.39, 95 % confidence interval (CI) 0.20–0.76]. After adjustment for potential confounders, a significant positive association was observed between the third pattern and general obesity among men (OR 1.77, 95 % CI 1.04–3.04), but not women (OR 1.18, 95 % CI 0.74–1.88). No overall association was seen between patterns of nutrient intake and abdominal obesity in both genders.

Conclusion

Major nutrient patterns were significantly associated with general, but not abdominal obesity among male participants of the SEPAHAN study. Further studies in other populations, along with future prospective studies, are required to confirm these findings.

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Abbreviations

NP:

Nutrient pattern

BMI:

Body mass index

WC:

Waist circumference

CVDs:

Cardiovascular diseases

SEPAHAN:

Study on the epidemiology of psychological alimentary health and nutrition

DS-FFQ:

Dish-based Semi-quantitative Food Frequency Questionnaire

USDA:

United States Department of Agriculture

SFAs:

Saturated fatty acids

MUFAs:

Monounsaturated fatty acids

PUFAs:

Polyunsaturated fatty acids

TFAs:

Trans fatty acids

NCEP:

National Cholesterol Education Program

GPPAQ:

General Practice Physical Activity Questionnaire

ANCOVA:

Analysis of covariance

PAI:

Physical activity index

References

  1. Jacobs DR Jr, Steffen LM (2003) Nutrients, foods, and dietary patterns as exposures in research: a framework for food synergy. Am J Clin Nutr 78:508S–513S

    CAS  Google Scholar 

  2. Hu FB (2002) Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol 13:3–9

    Article  CAS  Google Scholar 

  3. Newby PK, Tucker KL (2004) Empirically derived eating patterns using factor or cluster analysis: a review. Nutr Rev 62:177–203

    Article  CAS  Google Scholar 

  4. De Stefani E, Boffetta P, Fagundes RB, Deneo-Pellegrini H, Ronco AL, Acosta G, Mendilaharsu M (2008) Nutrient patterns and risk of squamous cell carcinoma of the esophagus: a factor analysis in uruguay. Anticancer Res 28:2499–2506

    Google Scholar 

  5. De Stefani E, Boffetta P, Ronco AL, Deneo-Pellegrini H, Acosta G, Gutierrez LP, Mendilaharsu M (2008) Nutrient patterns and risk of lung cancer: a factor analysis in Uruguayan men. Lung Cancer 61:283–291. doi:10.1016/j.lungcan.2008.01.004

    Article  Google Scholar 

  6. Edefonti V, Decarli A, La Vecchia C, Bosetti C, Randi G, Franceschi S, Dal Maso L, Ferraroni M (2008) Nutrient dietary patterns and the risk of breast and ovarian cancers. International journal of cancer. J Int du Cancer 122:609–613. doi:10.1002/ijc.23064

    Article  CAS  Google Scholar 

  7. Freisling H, Fahey MT, Moskal A, Ocke MC, Ferrari P, Jenab M, Norat T, Naska A, Welch AA, Navarro C, Schulz M, Wirfalt E, Casagrande C, Amiano P, Ardanaz E, Parr C, Engeset D, Grioni S, Sera F, Bueno-de-Mesquita B, van der Schouw YT, Touvier M, Boutron-Ruault MC, Halkjaer J, Dahm CC, Khaw KT, Crowe F, Linseisen J, Kroger J, Huybrechts I, Deharveng G, Manjer J, Agren A, Trichopoulou A, Tsiotas K, Riboli E, Bingham S, Slimani N (2010) Region-specific nutrient intake patterns exhibit a geographical gradient within and between European countries. J Nutr 140:1280–1286. doi:10.3945/jn.110.121152

    Article  CAS  Google Scholar 

  8. Gnagnarella P, Maisonneuve P, Bellomi M, Rampinelli C, Bertolotti R, Spaggiari L, Palli D, Veronesi G (2013) Nutrient intake and nutrient patterns and risk of lung cancer among heavy smokers: results from the COSMOS screening study with annual low-dose CT. Eur J Epidemiol 28:503–511. doi:10.1007/s10654-013-9803-1

    Article  CAS  Google Scholar 

  9. Ishimoto H, Nakamura H, Miyoshi T (1994) Epidemiological study on relationship between breast cancer mortality and dietary factors. Tokushima J Exp Med 41:103–114

    CAS  Google Scholar 

  10. Palli D, Russo A, Decarli A (2001) Dietary patterns, nutrient intake and gastric cancer in a high-risk area of Italy. Cancer Causes Control 12:163–172

    Article  CAS  Google Scholar 

  11. Samieri C, Ginder Coupez V, Lorrain S, Letenneur L, Alles B, Feart C, Paineau D, Barberger-Gateau P (2013) Nutrient patterns and risk of fracture in older subjects: results from the Three-City Study. Osteoporos Int 24:1295–1305. doi:10.1007/s00198-012-2132-5

    Article  CAS  Google Scholar 

  12. World Health Organization. WHO Media center. Obesity and overweight. In: World Health Organization, Geneva

  13. Kilpi F, Webber L, Musaigner A, Aitsi-Selmi A, Marsh T, Rtveladze K, McPherson K, Brown M (2013) Alarming predictions for obesity and non-communicable diseases in the Middle East. Public Health Nutr 1–9. doi:10.1017/S1368980013000840

  14. Esteghamati A, Khalilzadeh O, Mohammad K, Meysamie A, Rashidi A, Kamgar M, Abbasi M, Asgari F, Haghazali M (2010) Secular trends of obesity in Iran between 1999 and 2007: national surveys of risk factors of non-communicable diseases. Metab Syndr Rel Disord 8:209–213. doi:10.1089/met.2009.0064

    Article  Google Scholar 

  15. Moleres A, Ochoa MC, Rendo-Urteaga T, Martinez-Gonzalez MA, Azcona San Julian MC, Martinez JA, Marti A, Genoi (2012) Dietary fatty acid distribution modifies obesity risk linked to the rs9939609 polymorphism of the fat mass and obesity-associated gene in a Spanish case–control study of children. Br J Nutr 107:533–538. doi:10.1017/S0007114511003424

    Article  CAS  Google Scholar 

  16. Youn S, Woo HD, Cho YA, Shin A, Chang N, Kim J (2012) Association between dietary carbohydrate, glycemic index, glycemic load, and the prevalence of obesity in Korean men and women. Nutr Res 32:153–159. doi:10.1016/j.nutres.2011.12.009

    Article  CAS  Google Scholar 

  17. Merchant AT, Anand SS, Vuksan V, Jacobs R, Davis B, Teo K, Yusuf S, Share InvestigatorsS-A (2005) Protein intake is inversely associated with abdominal obesity in a multi-ethnic population. J Nutr 135:1196–1201

    CAS  Google Scholar 

  18. Liu S, Willett WC, Manson JE, Hu FB, Rosner B, Colditz G (2003) Relation between changes in intakes of dietary fiber and grain products and changes in weight and development of obesity among middle-aged women. Am J Clin Nutr 78:920–927

    CAS  Google Scholar 

  19. Garcia OP, Ronquillo D, Caamano Mdel C, Camacho M, Long KZ, Rosado JL (2012) Zinc, vitamin A, and vitamin C status are associated with leptin concentrations and obesity in Mexican women: results from a cross-sectional study. Nutr Metab 9:59. doi:10.1186/1743-7075-9-59

    Article  CAS  Google Scholar 

  20. Zhou SS, Li D, Zhou YM, Sun WP, Liu QG (2010) B-vitamin consumption and the prevalence of diabetes and obesity among the US adults: population based ecological study. BMC Public Health 10:746. doi:10.1186/1471-2458-10-746

    Article  Google Scholar 

  21. Saneei P, Salehi-Abargouei A, Esmaillzadeh A (2013) Serum 25-hydroxy vitamin D levels in relation to body mass index: a systematic review and meta-analysis. Obes Rev 14:393–404. doi:10.1111/obr.12016

    Article  CAS  Google Scholar 

  22. Huang L, Xue J, He Y, Wang J, Sun C, Feng R, Teng J, He Y, Li Y (2011) Dietary calcium but not elemental calcium from supplements is associated with body composition and obesity in Chinese women. PLoS One 6:e27703. doi:10.1371/journal.pone.0027703

    Article  CAS  Google Scholar 

  23. Adibi P, Keshteli AH, Esmaillzadeh A, Afshar H, Roohafza H, Bagherian-Sararoudi R, Daghaghzadeh H, Soltanian N, Feinle-Bisset C, Boyce P, Talley NJ (2012) The study on the epidemiology of psychological, alimentary health and nutrition (SEPAHAN): Overview of methodology. J Res Med Sci 17:S291–S297

    Google Scholar 

  24. Willett W (2013) Nutritional epidemiology. Oxford University Press, Oxford

    Google Scholar 

  25. Keshteli A, Esmaillzadeh A, Rajaie S, Askari G, Feinle-Bisset C, Adibi P (2014) A dish-based semi-quantitative food frequency questionnaire for assessment of dietary intakes in epidemiologic studies in Iran: design and development. Int J Prev Med 5:29–36

    Google Scholar 

  26. Ghaffarpour M, Houshiar-Rad A, Kianfar H (1999) The manual for household measures, cooking yields factors and edible portion of foods. Tehran: Nashre Olume Keshavarzy 1–40

  27. Kimura Y, Wada T, Okumiya K, Ishimoto Y, Fukutomi E, Kasahara Y, Chen W, Sakamoto R, Fujisawa M, Otsuka K, Matsubayashi K (2012) Eating alone among community-dwelling Japanese elderly: association with depression and food diversity. J Nutr Health Aging 16:728–731. doi:10.1007/s12603-012-0067-3

    Article  CAS  Google Scholar 

  28. Lean ME, Han TS, Morrison CE (1995) Waist circumference as a measure for indicating need for weight management. BMJ 311:158–161

    Article  CAS  Google Scholar 

  29. National Cholesterol Education Program Expert Panel on Detection E, Treatment of High Blood Cholesterol in A (2002) Third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III) final report. Circulation 106:3143–3421

    Google Scholar 

  30. Department of Health (2006) The general practice physical activity questionnaire. Department of Health, London

  31. J-o Kim, Mueller CW (1978) Factor analysis: statistical methods and practical issues. Sage, Newbury Park

    Google Scholar 

  32. Hajizadeh B, Jessri M, Akhoondan M, Moasheri SM, Rashidkhani B (2012) Nutrient patterns and risk of esophageal squamous cell carcinoma: a case–control study. Dis Esophagus 25:442–448. doi:10.1111/j.1442-2050.2011.01272.x

    Article  CAS  Google Scholar 

  33. Malik VS, Schulze MB, Hu FB (2006) Intake of sugar-sweetened beverages and weight gain: a systematic review. Am J Clin Nutr 84:274–288

    CAS  Google Scholar 

  34. Stanhope KL (2012) Role of fructose-containing sugars in the epidemics of obesity and metabolic syndrome. Annu Rev Med 63:329–343. doi:10.1146/annurev-med-042010-113026

    Article  CAS  Google Scholar 

  35. Hu FB (2003) Plant-based foods and prevention of cardiovascular disease: an overview. Am J Clin Nutr 78:544S–551S

    CAS  Google Scholar 

  36. Craig SA (2004) Betaine in human nutrition. Am J Clin Nutr 80:539–549

    CAS  Google Scholar 

  37. Mahabir S, Ettinger S, Johnson L, Baer DJ, Clevidence BA, Hartman TJ, Taylor PR (2008) Measures of adiposity and body fat distribution in relation to serum folate levels in postmenopausal women in a feeding study. Eur J Clin Nutr 62:644–650. doi:10.1038/sj.ejcn.1602771

    Article  CAS  Google Scholar 

  38. Mojtabai R (2004) Body mass index and serum folate in childbearing age women. Eur J Epidemiol 19:1029–1036

    Article  CAS  Google Scholar 

  39. McClung JP, Karl JP (2009) Iron deficiency and obesity: the contribution of inflammation and diminished iron absorption. Nutr Rev 67:100–104. doi:10.1111/j.1753-4887.2008.00145.x

    Article  Google Scholar 

  40. Alasfar F, Ben-Nakhi M, Khoursheed M, Kehinde EO, Alsaleh M (2011) Selenium is significantly depleted among morbidly obese female patients seeking bariatric surgery. Obes Surg 21:1710–1713. doi:10.1007/s11695-011-0458-2

    Article  Google Scholar 

  41. Song Q, Sergeev IN (2012) Calcium and vitamin D in obesity. Nutr Res Rev 25:130–141. doi:10.1017/S0954422412000029

    Article  CAS  Google Scholar 

  42. Li D, Sun WP, Zhou YM, Liu QG, Zhou SS, Luo N, Bian FN, Zhao ZG, Guo M (2010) Chronic niacin overload may be involved in the increased prevalence of obesity in US children. World J Gastroenterol 16:2378–2387

    Article  CAS  Google Scholar 

  43. Institute of Medicine (US) Standing Committee on the Scientific Evaluation of Dietary Reference Intakes and its Panel on Folate, Other B Vitamins, and Choline (1998) Dietary reference intakes for thiamin, riboflavin, niacin, vitamin B6, Folate, Vitamin B12, pantothenic acid, biotin, and Choline. National Academies Press, Washington, DC

    Google Scholar 

  44. van Dam RM, Seidell JC (2007) Carbohydrate intake and obesity. Eur J Clin Nutr 61(Suppl 1):S75–S99. doi:10.1038/sj.ejcn.1602939

    Google Scholar 

  45. Rezazadeh A, Rashidkhani B (2010) The association of general and central obesity with major dietary patterns of adult women living in Tehran, Iran. J Nutr Sci Vitaminol 56:132–138

    Article  CAS  Google Scholar 

  46. Paradis AM, Godin G, Perusse L, Vohl MC (2009) Associations between dietary patterns and obesity phenotypes. Int J Obes 33:1419–1426. doi:10.1038/ijo.2009.179

    Article  Google Scholar 

  47. Esmaillzadeh A, Azadbakht L (2008) Major dietary patterns in relation to general obesity and central adiposity among Iranian women. J Nutr 138:358–363

    CAS  Google Scholar 

  48. Jain N, Minhajuddin AT, Neeland IJ, Elsayed EF, Vega GL, Hedayati SS (2014) Association of urinary sodium-to-potassium ratio with obesity in a multiethnic cohort. Am J Clin Nutr 99:992–998. doi:10.3945/ajcn.113.077362

    Article  CAS  Google Scholar 

  49. Shea MK, Booth SL, Gundberg CM, Peterson JW, Waddell C, Dawson-Hughes B, Saltzman E (2010) Adulthood obesity is positively associated with adipose tissue concentrations of vitamin K and inversely associated with circulating indicators of vitamin K status in men and women. J Nutr 140:1029–1034. doi:10.3945/jn.109.118380

    Article  CAS  Google Scholar 

  50. Lovejoy JC, Sainsbury A, Stock Conference Working G (2009) Sex differences in obesity and the regulation of energy homeostasis. Obes Rev 10:154–167. doi:10.1111/j.1467-789X.2008.00529.x

    Article  CAS  Google Scholar 

  51. Beer-Borst S, Hercberg S, Morabia A, Bernstein MS, Galan P, Galasso R, Giampaoli S, McCrum E, Panico S, Preziosi P, Ribas L, Serra-Majem L, Vescio MF, Vitek O, Yarnell J, Northridge ME (2000) Dietary patterns in six european populations: results from EURALIM, a collaborative European data harmonization and information campaign. Eur J Clin Nutr 54:253–262

    Article  CAS  Google Scholar 

  52. O’Doherty Jensen K, Holm L (1999) Preferences, quantities and concerns: socio-cultural perspectives on the gendered consumption of foods. Eur J Clin Nutr 53:351–359

    Article  Google Scholar 

  53. Marks GC, Hughes MC, van der Pols JC (2006) Relative validity of food intake estimates using a food frequency questionnaire is associated with sex, age, and other personal characteristics. J Nutr 136:459–465

    CAS  Google Scholar 

  54. Subar AF, Thompson FE, Kipnis V, Midthune D, Hurwitz P, McNutt S, McIntosh A, Rosenfeld S (2001) Comparative validation of the Block, Willett, and National Cancer Institute food frequency questionnaires: the Eating at America’s Table Study. Am J Epidemiol 154:1089–1099

    Article  CAS  Google Scholar 

  55. Hosseini-Esfahani F, Bahadoran Z, Mirmiran P, Hosseinpour-Niazi S, Hosseinpanah F, Azizi F (2011) Dietary fructose and risk of metabolic syndrome in adults: Tehran Lipid and Glucose study. Nutr Metab 8:50. doi:10.1186/1743-7075-8-50

    Article  CAS  Google Scholar 

  56. Koh-Banerjee P, Chu NF, Spiegelman D, Rosner B, Colditz G, Willett W, Rimm E (2003) Prospective study of the association of changes in dietary intake, physical activity, alcohol consumption, and smoking with 9-y gain in waist circumference among 16 587 US men. Am J Clin Nutr 78:719–727

    CAS  Google Scholar 

  57. Fung GJ, Steffen LM, Zhou X, Harnack L, Tang W, Lutsey PL, Loria CM, Reis JP, Van Horn LV (2012) Vitamin D intake is inversely related to risk of developing metabolic syndrome in African American and white men and women over 20 y: the Coronary Artery Risk Development in Young Adults study. Am J Clin Nutr 96:24–29. doi:10.3945/ajcn.112.036863

    Article  CAS  Google Scholar 

  58. Riserus U, Berglund L, Vessby B (2001) Conjugated linoleic acid (CLA) reduced abdominal adipose tissue in obese middle-aged men with signs of the metabolic syndrome: a randomised controlled trial. Int J Obes Rel Metab Disord J Int Assoc Study Obes 25:1129–1135. doi:10.1038/sj.ijo.0801659

    Article  CAS  Google Scholar 

  59. Jia WP, Lu JX, Xiang KS, Bao YQ, Lu HJ, Chen L (2003) Prediction of abdominal visceral obesity from body mass index, waist circumference and waist-hip ratio in Chinese adults: receiver operating characteristic curves analysis. Biomed Environ Sci 16:206–211

    Google Scholar 

  60. Rankinen T, Kim SY, Perusse L, Despres JP, Bouchard C (1999) The prediction of abdominal visceral fat level from body composition and anthropometry: ROC analysis. Int J Obes Rel Metab Disord J Int Assoc Study Obes 23:801–809

    Article  CAS  Google Scholar 

  61. Wu HY, Xu SY, Chen LL, Zhang HF (2009) Waist to height ratio as a predictor of abdominal fat distribution in men. Chin J Physiol 52:441–445

    Article  Google Scholar 

  62. Moskal A, Pisa PT, Ferrari P, Byrnes G, Freisling H, Boutron-Ruault MC, Cadeau C, Nailler L, Wendt A, Kuhn T, Boeing H, Buijsse B, Tjonneland A, Halkjaer J, Dahm CC, Chiuve SE, Quiros JR, Buckland G, Molina-Montes E, Amiano P, Huerta Castano JM, Gurrea AB, Khaw KT, Lentjes MA, Key TJ, Romaguera D, Vergnaud AC, Trichopoulou A, Bamia C, Orfanos P, Palli D, Pala V, Tumino R, Sacerdote C, de Magistris MS, Bueno-de-Mesquita HB, Ocke MC, Beulens JW, Ericson U, Drake I, Nilsson LM, Winkvist A, Weiderpass E, Hjartaker A, Riboli E, Slimani N (2014) Nutrient patterns and their food sources in an international study setting: report from the EPIC study. PLoS One 9:e98647. doi:10.1371/journal.pone.0098647

    Article  CAS  Google Scholar 

  63. Martinez ME, Marshall JR, Sechrest L (1998) Invited commentary: factor analysis and the search for objectivity. Am J Epidemiol 148:17–19

    Article  CAS  Google Scholar 

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Acknowledgments

The authors are thankful to participants of SEPAHAN project and authorities of Isfahan University of Medical Sciences for their excellent cooperation. We also appreciate the research council of Food Security Research Center for funding this project.

Conflict of interest

Authors had no personal or financial conflicts of interest to declare.

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Correspondence to Ahmad Esmaillzadeh.

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Salehi-Abargouei, A., Esmaillzadeh, A., Azadbakht, L. et al. Nutrient patterns and their relation to general and abdominal obesity in Iranian adults: findings from the SEPAHAN study. Eur J Nutr 55, 505–518 (2016). https://doi.org/10.1007/s00394-015-0867-4

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