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Published in: European Journal of Nutrition 4/2019

Open Access 01-06-2019 | Original Contribution

Attenuation of the association between sugar-sweetened beverages and diabetes risk by adiposity adjustment: a secondary analysis of national health survey data

Authors: Yi Jing, Thang S. Han, Majid M. Alkhalaf, Michael E. J. Lean

Published in: European Journal of Nutrition | Issue 4/2019

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Abstract

Purpose

While weight gain and obesity are the dominant factors, dietary sugar and specifically sugar-sweetened beverages (SSB) has been implicated in causing type 2 diabetes (T2DM). We assessed how much of the apparent effect of SSB is explained by adiposity, but not captured by adjustment for BMI, which is a poor index of body fat.

Methods

We examined data from 5187 adults (mean age 50.8 years, SD = 16.4, 172 (3.3%) T2DM), from the Scottish Health Survey 2003 and 2008–2010 databases. Logistic regression was used to assess the association between SSB consumption and T2DM (non-insulin treated) and its attenuation (reduction in odds ratios, ORs), after entering published anthropometric indices of adiposity into the regression model, adjusted for age, sex, social class, education, smoking, alcohol consumption and physical activity.

Results

Compared with low SSB categories (“less often/never”, once/week or 1–3 times/month), the OR without adiposity adjustment for having T2DM in high SSB consumers (2–3, 4–5, ≥ 6/day) was 2.56 (95% CI 1.12–5.83; p = 0.026). That OR was marginally changed by adjusting for BMI (+ 4.3%), WC (+ 5.5%) or total body fat (− 4.3%), but greatly attenuated by adjusting for estimated %body fat (− 23.4%). These indices had similar influences on the associations between SSB and T2DM combining known T2DM patients with unknown HbA1c > 6.5%, > 48 mmol/mol.

Conclusions

Associations between SSB and T2DM are attenuated more markedly by adjustment with estimated %body fat than with BMI, indicating an adiposity effect not captured using BMI. Future research should employ best available estimates of adiposity.
Literature
1.
go back to reference World Health Organization (2016) Global report on diabetes. WHO Press, Geneva World Health Organization (2016) Global report on diabetes. WHO Press, Geneva
2.
go back to reference Forouzanfar MH, Alexander L, Anderson HR et al (2015) Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 386:2287–2323CrossRef Forouzanfar MH, Alexander L, Anderson HR et al (2015) Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 386:2287–2323CrossRef
3.
go back to reference Torgerson JS, Hauptman J, Boldrin MN, Sjöström L (2004) XENical in the prevention of diabetes in obese subjects (XENDOS) study: a randomized study of orlistat as an adjunct to lifestyle changes for the prevention of type 2 diabetes in obese patients. Diabetes Care 27:155–161CrossRefPubMed Torgerson JS, Hauptman J, Boldrin MN, Sjöström L (2004) XENical in the prevention of diabetes in obese subjects (XENDOS) study: a randomized study of orlistat as an adjunct to lifestyle changes for the prevention of type 2 diabetes in obese patients. Diabetes Care 27:155–161CrossRefPubMed
4.
go back to reference Tuomilehto J, Lindström J, Eriksson JG; Finnish Diabetes Prevention Study Group et al (2001) Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 344:1343–1350CrossRefPubMed Tuomilehto J, Lindström J, Eriksson JG; Finnish Diabetes Prevention Study Group et al (2001) Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 344:1343–1350CrossRefPubMed
6.
go back to reference Basu S, Yoffe P, Hills N, Lustig RH (2013) The relationship of sugar to population-level diabetes prevalence: an econometric analysis of repeated cross-sectional data. PLoS One 8:e57873CrossRefPubMedPubMedCentral Basu S, Yoffe P, Hills N, Lustig RH (2013) The relationship of sugar to population-level diabetes prevalence: an econometric analysis of repeated cross-sectional data. PLoS One 8:e57873CrossRefPubMedPubMedCentral
7.
go back to reference Lean ME, Han TS, Deurenberg P (1996) Predicting body composition by densitometry from simple anthropometric measurements. Am J Clin Nutr 63:4–14CrossRefPubMed Lean ME, Han TS, Deurenberg P (1996) Predicting body composition by densitometry from simple anthropometric measurements. Am J Clin Nutr 63:4–14CrossRefPubMed
8.
go back to reference Braam LA, Ocké MC, Bueno-de-Mesquita HB, Seidell JC (1998) Determinants of obesity-related underreporting of energy intake. Am J Epidemiol 147:1081–1086CrossRefPubMed Braam LA, Ocké MC, Bueno-de-Mesquita HB, Seidell JC (1998) Determinants of obesity-related underreporting of energy intake. Am J Epidemiol 147:1081–1086CrossRefPubMed
9.
go back to reference Heerstrass DW, Ocké MC, Bueno-de-Mesquita HB et al (1998) Underreporting of energy, protein and potassium intake in relation to body mass index. Int J Epidemiol 27:186–193CrossRefPubMed Heerstrass DW, Ocké MC, Bueno-de-Mesquita HB et al (1998) Underreporting of energy, protein and potassium intake in relation to body mass index. Int J Epidemiol 27:186–193CrossRefPubMed
10.
go back to reference Kvaavik E, Andersen LF, Klepp KI (2005) The stability of soft drinks intake from adolescence to adult age and the association between long-term consumption of soft drinks and lifestyle factors and body weight. Public Health Nutr 8:149–157CrossRefPubMed Kvaavik E, Andersen LF, Klepp KI (2005) The stability of soft drinks intake from adolescence to adult age and the association between long-term consumption of soft drinks and lifestyle factors and body weight. Public Health Nutr 8:149–157CrossRefPubMed
11.
go back to reference Mourao DM, Bressan J, Campbell WW, Mattes RD (2007) Effects of food form on appetite and energy intake in lean and obese young adults. Int J Obes 31:1688–1695CrossRef Mourao DM, Bressan J, Campbell WW, Mattes RD (2007) Effects of food form on appetite and energy intake in lean and obese young adults. Int J Obes 31:1688–1695CrossRef
12.
go back to reference Imamura F, O’Connor L, Ye Z et al (2016) Consumption of sugar sweetened beverages, artificially sweetened beverages, and fruit juice and incidence of type 2 diabetes: systematic review, meta-analysis, and estimation of population attributable fraction. Br J Sports Med 50:496–504CrossRefPubMedPubMedCentral Imamura F, O’Connor L, Ye Z et al (2016) Consumption of sugar sweetened beverages, artificially sweetened beverages, and fruit juice and incidence of type 2 diabetes: systematic review, meta-analysis, and estimation of population attributable fraction. Br J Sports Med 50:496–504CrossRefPubMedPubMedCentral
13.
go back to reference Scottish Health Survey, 2010 NHS Health Scotland (2010) Questionnaires and showcards. UK Data Archive Study Number 6987—a survey carried out on behalf of The Scottish Government Health Directorates and NHS Health Scotland. Scottish Centre for Social Research Department of Epidemiology and Public Health, University College London and The MRC Social and Public Health Sciences Unit, Glasgow Scottish Health Survey, 2010 NHS Health Scotland (2010) Questionnaires and showcards. UK Data Archive Study Number 6987—a survey carried out on behalf of The Scottish Government Health Directorates and NHS Health Scotland. Scottish Centre for Social Research Department of Epidemiology and Public Health, University College London and The MRC Social and Public Health Sciences Unit, Glasgow
14.
go back to reference Al-Gindan YY, Hankey CR, Govan L et al (2015) Derivation and validation of simple anthropometric equations to predict adipose tissue mass and total fat mass with MRI as the reference method. Br J Nutr 114:1852–1867CrossRefPubMedPubMedCentral Al-Gindan YY, Hankey CR, Govan L et al (2015) Derivation and validation of simple anthropometric equations to predict adipose tissue mass and total fat mass with MRI as the reference method. Br J Nutr 114:1852–1867CrossRefPubMedPubMedCentral
15.
go back to reference Ruanpeng D, Thongprayoon C, Cheungpasitporn W, Harindhanavudhi T (2017) Sugar and artificially-sweetened beverages linked to obesity: a systematic review and meta-analysis. QJM 110:513–520CrossRefPubMed Ruanpeng D, Thongprayoon C, Cheungpasitporn W, Harindhanavudhi T (2017) Sugar and artificially-sweetened beverages linked to obesity: a systematic review and meta-analysis. QJM 110:513–520CrossRefPubMed
16.
go back to reference Singh GM, Micha R, Khatibzadeh S, Shi P; Global Burden of Diseases Nutrition and Chronic Diseases Expert Group (NutriCoDE) et al (2015) Global, regional, and national consumption of sugar-sweetened beverages, fruit juices, and milk: a systematic assessment of beverage intake in 187 countries. PLoS One 10:e0124845CrossRefPubMedPubMedCentral Singh GM, Micha R, Khatibzadeh S, Shi P; Global Burden of Diseases Nutrition and Chronic Diseases Expert Group (NutriCoDE) et al (2015) Global, regional, and national consumption of sugar-sweetened beverages, fruit juices, and milk: a systematic assessment of beverage intake in 187 countries. PLoS One 10:e0124845CrossRefPubMedPubMedCentral
17.
go back to reference O’Connor L, Imamura F, Lentjes MA et al (2015) Prospective associations and population impact of sweet beverage intake and type 2 diabetes, and effects of substitutions with alternative beverages. Diabetologia 58:1474–1483CrossRefPubMedPubMedCentral O’Connor L, Imamura F, Lentjes MA et al (2015) Prospective associations and population impact of sweet beverage intake and type 2 diabetes, and effects of substitutions with alternative beverages. Diabetologia 58:1474–1483CrossRefPubMedPubMedCentral
18.
go back to reference Al-Gindan YY, Hankey C, Govan L et al (2014) Derivation and validation of simple equations to predict total muscle mass from simple anthropometric and demographic data. Am J Clin Nutr 100:1041–1051CrossRefPubMedPubMedCentral Al-Gindan YY, Hankey C, Govan L et al (2014) Derivation and validation of simple equations to predict total muscle mass from simple anthropometric and demographic data. Am J Clin Nutr 100:1041–1051CrossRefPubMedPubMedCentral
19.
go back to reference Han TS, Lean MEJ (2002) Anthropometric indices of obesity and regional distribution of fat depots, chap. 4. In: Björntorp P (ed) International textbook of obesity, 1st edn. Wiley, Chichester, pp 51–65 Han TS, Lean MEJ (2002) Anthropometric indices of obesity and regional distribution of fat depots, chap. 4. In: Björntorp P (ed) International textbook of obesity, 1st edn. Wiley, Chichester, pp 51–65
20.
go back to reference Wolf HA (1959) Sugar: excise taxes, tariffs, quotas, and program payments. South Econ J 25:416–424CrossRef Wolf HA (1959) Sugar: excise taxes, tariffs, quotas, and program payments. South Econ J 25:416–424CrossRef
21.
go back to reference Snape RH (1969) Sugar: costs of protection and taxation. Econ New Ser 36:29–41CrossRef Snape RH (1969) Sugar: costs of protection and taxation. Econ New Ser 36:29–41CrossRef
24.
go back to reference Te Morenga L, Howatson AJ, Jones RM, Mann JI (2014) Dietary sugars and cardiometabolic risk: systematic review and meta-analyses of randomized controlled trials of the effects on blood pressure and lipids. Am J Clin Nutr 100:165–179CrossRef Te Morenga L, Howatson AJ, Jones RM, Mann JI (2014) Dietary sugars and cardiometabolic risk: systematic review and meta-analyses of randomized controlled trials of the effects on blood pressure and lipids. Am J Clin Nutr 100:165–179CrossRef
25.
go back to reference Warfa K, Drake I, Wallström p, Engström G (2016) Association between sucrose intake and acute coronary event risk and effect modification by lifestyle factors: Malmö Diet and Cancer Cohort Study. Br J Nutr 116:1611–1620CrossRefPubMed Warfa K, Drake I, Wallström p, Engström G (2016) Association between sucrose intake and acute coronary event risk and effect modification by lifestyle factors: Malmö Diet and Cancer Cohort Study. Br J Nutr 116:1611–1620CrossRefPubMed
26.
go back to reference Te Morenga L, Mallard S, Mann J (2012) Dietary sugars and body weight: systematic review and meta-analyses of randomised controlled trials and cohort studies. BMJ 346:e7492CrossRefPubMed Te Morenga L, Mallard S, Mann J (2012) Dietary sugars and body weight: systematic review and meta-analyses of randomised controlled trials and cohort studies. BMJ 346:e7492CrossRefPubMed
27.
go back to reference Miller PE, Perez V (2014) Low-calorie sweeteners and body weight and composition: a meta-analysis of randomized controlled trials and prospective cohort studies. Am J Clin Nutr 100:765–777CrossRefPubMedPubMedCentral Miller PE, Perez V (2014) Low-calorie sweeteners and body weight and composition: a meta-analysis of randomized controlled trials and prospective cohort studies. Am J Clin Nutr 100:765–777CrossRefPubMedPubMedCentral
28.
29.
go back to reference Fowler SP (2016) Low-calorie sweetener use and energy balance: results from experimental studies in animals, and large-scale prospective studies in humans. Physiol Behav 164:517–523CrossRefPubMedPubMedCentral Fowler SP (2016) Low-calorie sweetener use and energy balance: results from experimental studies in animals, and large-scale prospective studies in humans. Physiol Behav 164:517–523CrossRefPubMedPubMedCentral
30.
go back to reference Drewnowski A, Brunzell JD, Sande K et al (1985) Sweet tooth reconsidered: taste responsiveness in human obesity. Physiol Behav 35:617–622CrossRefPubMed Drewnowski A, Brunzell JD, Sande K et al (1985) Sweet tooth reconsidered: taste responsiveness in human obesity. Physiol Behav 35:617–622CrossRefPubMed
31.
go back to reference Lee SS (2004) A study on dietary behavior of children according to their preferences for fast food. Korean J Community Nutr 9:204–221 Lee SS (2004) A study on dietary behavior of children according to their preferences for fast food. Korean J Community Nutr 9:204–221
32.
go back to reference Wing RR, Goldstein MG, Acton KJ et al (2001) Behavioral science research in diabetes: lifestyle changes related to obesity, eating behavior, and physical activity. Diabetes Care 24:117–123CrossRefPubMed Wing RR, Goldstein MG, Acton KJ et al (2001) Behavioral science research in diabetes: lifestyle changes related to obesity, eating behavior, and physical activity. Diabetes Care 24:117–123CrossRefPubMed
33.
go back to reference Peel E, Parry O, Douglas M, Lawton J (2005) Taking the biscuit? A discursive approach to managing diet in type 2 diabetes. J Health Psychol 10:779–791CrossRefPubMed Peel E, Parry O, Douglas M, Lawton J (2005) Taking the biscuit? A discursive approach to managing diet in type 2 diabetes. J Health Psychol 10:779–791CrossRefPubMed
34.
go back to reference Lawton J, Ahmad N, Hanna L et al (2008) ‘We should change ourselves, but we can’t’: accounts of food and eating practices amongst British Pakistanis and Indians with type 2 diabetes. Ethn Health 13:305–319CrossRefPubMed Lawton J, Ahmad N, Hanna L et al (2008) ‘We should change ourselves, but we can’t’: accounts of food and eating practices amongst British Pakistanis and Indians with type 2 diabetes. Ethn Health 13:305–319CrossRefPubMed
Metadata
Title
Attenuation of the association between sugar-sweetened beverages and diabetes risk by adiposity adjustment: a secondary analysis of national health survey data
Authors
Yi Jing
Thang S. Han
Majid M. Alkhalaf
Michael E. J. Lean
Publication date
01-06-2019
Publisher
Springer Berlin Heidelberg
Published in
European Journal of Nutrition / Issue 4/2019
Print ISSN: 1436-6207
Electronic ISSN: 1436-6215
DOI
https://doi.org/10.1007/s00394-018-1716-z

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