Background

0147763

2979

Circulation

0009-73221524-4539

21422385

4669039

10.1161/CIRCULATIONAHA.110.955922

NIHMS706590

Article

Association of DASH Diet With Cardiovascular Risk Factors in Youth With Diabetes Mellitus The SEARCH for Diabetes in Youth Study

Liese

Angela D.

PhDBortsov

Andrey

MD, PhDGünther

Anke L.B.

PhDDabelea

Dana

MD, PhDReynolds

Kristi

PhDStandiford

Debra A.

MSNLiu

Lenna

MDWilliams

Desmond E.

MD, PhDMayer-Davis

Elizabeth J.

PhDD'Agostino

Ralph B.

JrPhDBell

Ronny

PhDMarcovina

Santica

ScD, PhDUniversity of South Carolina, Columbia (A.D.L., A.B.); Fulda University of Applied Sciences, Fulda, Germany (A.L.B.G.); University of Colorado, Denver (D.D.); Kaiser Permanente Southern California, Pasadena (K.R.); Children's Hospital Medical Center, Cincinnati, OH (D.A.S.); Seattle Children's Hospital, Seattle, WA (L.L.); Center for Disease Control and Prevention, Atlanta, GA (D.E.W.); University of North Carolina, Chapel Hill (E.J.M.-D.); Wake Forest University, Winston-Salem, NC (R.B.D., R.B.); and University of Washington, Seattle (S.M.)

Correspondence to Angela D. Liese, PhD, MPH, FAHA, Center for Research in Nutrition and Health Disparities and Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, 921 Assembly St, Columbia, SC 29208. Liese@sc.edu

1072015

2132011

542011

03122015

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Background

We have shown that adherence to the Dietary Approaches to Stop Hypertension (DASH) diet is related to blood pressure in youth with type 1 and type 2 diabetes mellitus. We explored the impact of the DASH diet on other cardiovascular disease risk factors.

Methods and Results

Between 2001 and 2005, data on total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, low-density lipoprotein particle density, apolipoprotein B, body mass index, waist circumference, and adipocytokines were ascertained in 2130 youth aged 10 to 22 years with physician-diagnosed diabetes mellitus. Dietary intake was assessed by food frequency questionnaire, categorized into the DASH food groups, and assigned an adherence score. Among youth with type 1 diabetes mellitus, higher adherence to the DASH diet was significantly and inversely associated with low-density lipoprotein/high-density lipoprotein ratio and A_1c in multivariable-adjusted models. Youth in the highest adherence tertile had an estimated 0.07 lower low-density lipoprotein/high-density lipoprotein ratio and 0.2 lower A_1c levels than those in the lowest tertile adjusted for confounders. No significant associations were observed with triglycerides, low-density lipoprotein particle density, adipocytokines, apolipoprotein B, body mass index Z score, or waist circumference. Among youth with type 2 diabetes mellitus, associations were observed with low-density lipoprotein particle density and body mass index Z score.

Conclusions

The DASH dietary pattern may be beneficial in the prevention and management of cardiovascular disease risk in youth with diabetes mellitus.

diabetes mellituslipidslipoproteinsnutritionyouth

Youth with diabetes mellitus are at high risk of cardiovascular disease (CVD) because of accelerated atherosclerosis that can lead to coronary artery disease in young adulthood.¹ Comorbidities are very common; 14% of youth with type 1 diabetes mellitus (T1DM) and 92% of youth with type 2 diabetes mellitus (T2DM) have ≥2 CVD risk factors.² Hypertension affects ≈30% of youth with diabetes mellitus aged > 10 years, and lipid abnormalities are present in 19% of youth with T1DM and 33% of youth with T2DM.³ The American Heart Association recommends intense cardiovascular risk reduction in high-risk pediatric patients to improve long-term outcomes.⁴ Although aggressive medical treatment is the cornerstone of diabetes therapy and management of associated risk factors, management of dietary behavior is also an important part of medical nutritional therapy in persons with diabetes mellitus.⁵

The National Heart, Lung, and Blood Institute–funded Dietary Approaches to Stop Hypertension (DASH) trial demonstrated the efficacy of a whole-diet approach on hypertension prevention and blood pressure reduction,⁶ and observational studies have confirmed that adherence to a DASH-style diet benefits cardiovascular health.^7–12 We have shown previously that the DASH diet is associated with lower prevalence of hypertension in youth with T1DM.¹³ However, little is known about its impact on other CVD risk fac-tors.^6,14,15 The purpose of our study was to investigate the association of adherence to a DASH-like eating plan with blood lipid levels, lipoproteins, adipocytokines, and measures of adiposity and glycemic control in a large sample of youth with T1DM and T2DM.

Methods

The SEARCH for Diabetes in Youth Study is an ongoing multicenter study of physician-diagnosed diabetes mellitus in youth aged <20 years at diagnosis that began in 2001.¹⁶ The study was approved by the local institutional review boards at its 6 centers. Parents of participants aged < 18 years provided written informed consent with participant assent; all participants aged ≥18 years provided written informed consent.

Study Participants

This analysis is restricted to youth attending the SEARCH clinic visit and whose diabetes mellitus was prevalent in 2001 or incident in 2002–2005 (n=3354; 42% of 8031 ascertained by SEARCH surveillance system). We excluded those with (1) a missing food frequency questionnaire (n=280); (2) provider-defined diabetes mellitus other than type 1 or type 2 (maturity-onset diabetes of the young, hybrid, secondary, unknown type, and missing type; n=27); (3) diabetes duration <6 months (n=372); (4) fasting <8 hours (n=480); and (5) eating much more or much less than typical (n=154), leaving 2130 youth (1810 T1DM, 320 T2DM) for descriptive analyses. For regression analyses, youth missing key analytical variables were excluded, and outcome-specific sample sizes are presented within the tables. The higher proportion of missing data for low-density lipoprotein (LDL) particle density and adipocytokines was due to the limited time period during which these measures were conducted.

Outcome Measures

Physical examinations at the study visits were conducted according to standardized protocols by trained and certified staff. Height and weight were measured to the nearest 0.1 cm and 0.1 kg, respectively. Body mass index (BMI) was calculated as weight (kg)/height squared (m²) and converted to BMI Z score.¹⁷ Waist circumference was measured just above the uppermost lateral border of the right ilium following National Health and Nutrition Examination Survey protocol.¹⁸ A fiberglass tape was used for youth with a waist circumference up to 150 cm, and a flexible steel tape was used otherwise.

Blood A_1c samples were obtained only if there was no episode of diabetic ketoacidosis within the prior month. Specimens were processed at the site and shipped within 24 hours to the Northwest Lipid Metabolism and Diabetes Research Laboratories in Seattle, WA. Measurements of plasma cholesterol, triglycerides, and high-density lipoprotein (HDL) cholesterol were performed on a Hitachi 917 autoanalyzer (Boehringer Mannheim Diagnostics, Indianapolis, IN). LDL cholesterol was calculated by the Friedewald equation for individuals with triglyceride concentration <400 mg/dL (4.52 mmol/L) and by the BetaQuantification procedure for those with triglyceride concentration ≥400 mg/dL.¹⁹ Assessment of lipoprotein cholesterol distribution was performed after density gradient ultracentrifugation and calculation of the LDL relative flotation rate for characterization of LDL particle density. Adiponectin and leptin were measured with a commercial radioimmunoassay procedure.²⁰ Apolipoprotein B (apoB) was measured by a nephelometric system (BNII, Behring Diagnostics) calibrated with the World Health Organization international reference material for apoB.²¹ A_1c was measured by a dedicated ion-exchange high-performance liquid chromatography instrument (TOSOH, Bioscience, Inc., San Francisco, CA).

Dietary Assessment and DASH Score

The SEARCH food frequency questionnaire has been described.²² It consisted of 85 food lines for which the participant indicated whether the item(s) was consumed in the past week (yes/no) and, if yes, for how many days and in what average portion. Food groups were created by either collapsing food lines on the basis of their major components or by disaggregating composite foods into constituent foods. The food frequency questionnaire was primarily self-administered after staff instruction.

Adherence to the DASH diet was assessed with an index variable (ie, a score) comprising 8 DASH food groups (grains, vegetables, fruits, dairy, meat, nuts/seeds/legumes, fats/oils, and sweets),^23,24 as described in detail.¹³ For each food group, a maximum score of 10 could be achieved when the intake met the recommendation, and lower intakes were scored proportionately. Reverse scoring was applied for meat, fats/oils, and sweets, and a score of 0 was applied to intakes ≥200% of the upper recommended level. The resulting 8 component scores were summed to create the overall DASH adherence score, which ranged from 0 to 80. Following the DASH eating plan guidelines,²⁴ we assigned each individual the energy level closest to his or her estimated energy requirement on the basis of age, sex, and physical activity.¹³

Covariates

Race and ethnicity were obtained through self-report with the standard census questions.²⁵ Physical activity and sedentary behavior were assessed with questions identical to or slightly modified from those in the Youth Risk Behavior Surveillance System.^26,27 Smoking, parental education, and family income were based on self-report.

Statistical Analysis

Statistical analyses were conducted with the use of SAS (version 9.1, 2003; SAS Institute Inc, Cary, NC). Outcome variables with skewed distribution (eg, plasma triglycerides, adiponectin, leptin, and apoB) were log-transformed. We first evaluated a large number of potential confounders (age, gender, income, parental education, duration of diabetes mellitus, physical activity, sedentary behavior, missing doses of medication, type of diabetes treatment, study site, year of diabetes onset, lipid-lowering and antihypertensive treatment, family history of CVD and diabetes mellitus, smoking, and BMI Z score) and retained only those associated significantly (P<0.05) with at least 1 of the outcomes.

A series of multivariable linear regression models were fit, first adjusted for nonmodifiable confounders and subsequently adjusted for modifiable risk factors (physical activity, sedentary behavior, smoking, and, subsequently, BMI Z score). A_1c was included in the final models as a potential mediator. P<0.05 was considered significant. In addition, we estimated the level of the CVD risk factors using the least square means method at the median value of the lowest and highest tertiles of the DASH score and the differences between the tertile estimates. Back-transformations of log values were performed where applicable. We also investigated potential effect modification by race/ethnicity but found no evidence of this.

Results

Sample characteristics according to tertile of DASH adherence are summarized in Table 1. Higher levels of adherence to the DASH diet were significantly associated with race/ ethnicity, higher income, not smoking, more vigorous physical activity, and less television watching, but not with age or gender, in T1DM youth. The DASH score was associated only with vigorous physical activity in T2DM youth.

In both T1DM and T2DM children, the average DASH diet scores were low, with the second tertile mean at 39.9 and 36.4, respectively, on an 80-point scale (Table 2). As expected, intake of food groups included in the DASH score differed significantly between tertiles (P<0.05), shown per 1000 kilocalories because of the large differences in energy requirements across the age span. Youth in the highest tertiles consumed twice as many servings of fruit and low-fat dairy products and substantially more nuts and seeds than those in the lowest. A higher adherence to DASH was not related to total energy intake.

Mean levels of CVD risk factors according to diabetes type and DASH adherence tertile are shown in Table 3. With increasing DASH adherence, we observed decreasing levels of LDL cholesterol, LDL/HDL ratios, and A_1c in T1DM, decreasing levels of total cholesterol, apoB, and BMI Z score in T1DM and T2DM, and decreasing levels of triglycerides, HDL cholesterol, and waist circumference in T2DM.

Table 4 shows the association of the DASH diet score with CVD risk factors in youth with T1DM based on a prespeci-fied, hierarchical series of analytical models. We observed significant associations of DASH diet score with LDL/HDL ratio and A_1c. No association was observed with HDL cholesterol, triglycerides, LDL particle density, adiponectin, or leptin (data not shown for adipocytokines), BMI Z score, or waist circumference. The association with total cholesterol and LDL cholesterol was inconsistent. For most outcomes, adjustment for BMI Z score had very little impact on the model. In absolute terms, we estimated that youth with T1DM with a DASH score in the top tertile had a 0.07 lower LDL/HDL ratio and 0.2 lower A_1c compared with those with a DASH score in the lowest tertile, independent of confounders. We also evaluated the role of A_1c as a potential intermediate factor in the relationship between DASH score and lipid levels. Adjustment for A_1c either attenuated or removed all significant associations with lipid levels.

As shown in Table 5, in youth with T2DM, higher DASH diet adherence was associated significantly with LDL particle density and BMI Z score but not with LDL or HDL cholesterol, apoB, triglycerides, waist circumference, A_1c, adiponectin, or leptin (data not shown). The association with cholesterol was inconsistent. In absolute terms, youth with a DASH score in the top tertile had 0.01 higher LDL particle density and a 0.24 lower BMI Z score than youth in the lowest DASH score tertile, independent of confounders.

Discussion

Several observational studies in adults have shown that adherence to a DASH-like diet has positive effects on cardiovascular health, including reduced risk of hypertension, T2DM, heart failure, coronary heart disease, stroke, and overall mortality.^7–12 However, few data exist on its effect on more proximal or intermediate risk factors,^6,14,15 or for youth.^28,29

Our study found significant associations of adherence to DASH diet with LDL/HDL ratio in youth with T1DM and with LDL particle density in youth with T2DM. Our findings with total cholesterol were suggestive of an association, but require replication. To the best of our knowledge, the only large studies of the effect of the DASH diet on lipids are the DASH and PREMIER trials, in which it was shown that the DASH intervention group experienced significant and remarkably large reductions in total (13.7 mg/dL), LDL (10.7 mg/dL), and HDL (3.7 mg/dL) cholesterol compared with the control group but no changes in triglycerides or LDL/HDL ratio.⁶ The PREMIER trial reported similar findings with marked reductions in total and LDL cholesterol but no changes in triglycerides.³⁰ A smaller intervention study in patients with metabolic syndrome has shown significant increases in HDL cholesterol and decreases in triglycerides but used a calorie-restricted version of the DASH diet.¹⁵

One of the mechanisms by which a dietary pattern may affect cardiovascular risk factors may be via changes in energy intake, which in turn affect weight. In youth with T1DM, the initial inverse association of DASH diet with BMI Z score was explained by physical activity, sedentary behavior, and smoking. There was no association of DASH diet with waist circumference in this group. However, in T2DM youth, BMI Z score was strongly associated with DASH diet independent of lifestyle and other factors, whereas the association with waist circumference was inconsistent.

Similar to the findings of the national Youth Risk Behavior Surveillance System, we observed relatively high reports of vigorous physical activity.³¹ Compared with objective assessment methods, it has been suggested that self-report of vigorous activity with the use of the Youth Risk Behavior Surveillance System questions may lead to overreport-ing.³² It is conceivable that inaccuracies in measurement of physical activity impeded our ability to disentangle the mediating role of physical activity in the relationship of DASH diet and adiposity.

We observed a marked association of adherence to DASH diet with A_1c in youth with T1DM, a finding that, to the best of our knowledge, has not been shown before. It is tempting to speculate that a higher-quality diet may affect glucose control physiologically via nutrient constituents such as fiber that slow digestion time. Alternatively, it is conceivable that both A_1c and DASH scores reflect a latent construct related to general health behaviors and quality of diabetes care, but do not have a causal relation.

Previous cross-sectional and prospective studies have shown associations of A_1c with lipid levels,^33–36 apoB, and dense LDL.³⁷ In the Diabetes Control and Complications Trial, intensive glucose control significantly reduced total and LDL cholesterol and triglycerides in patients with T1DM.^34,35 Likewise, in the SEARCH population, glycemic control predicted short-term changes in lipid levels.³⁶ We therefore presented data on the associations between DASH diet and lipids with and without adjustment for A_1c. Our findings suggest that there may be multiple pathways linking dietary intake to lipid levels, some operating via concomitant changes in A_1c and some operating independently.

Our study has several limitations. Because of the cross-sectional design, determinations of sequence of events and causal inferences were limited. Our sample of T2DM youth was still limited and might have influenced our ability to reach definitive conclusions. Assessment of dietary intake is prone to error, resulting in misclassification of exposure measurement; however, it is unlikely that such misclassification would be differential in relation to the outcomes considered. Sodium intake is generally not well assessed by food frequency questionnaire. The association magnitudes were of moderate clinical significance. Finally, we did not explicitly adjust for multiple comparisons. We fitted our models in a hierarchical sequence from simpler to more complex and thus used a systematic approach for examining whether associations were significant. However, given the large number of CVD risk factors studied, we cannot exclude the possibility that some of the observed associations with marginal P values may be due to chance and could become marginally nonsignificant if replicated.

We have previously shown that dietary intake in youth with diabetes mellitus falls markedly short of current recommenda-tions,²² and the overall adherence score for the DASH diet is quite low.¹³ It has been suggested that very high DASH adherence levels like those in intervention settings may be needed to affect health outcomes. However, the low overall dietary quality in our population did not preclude us from finding associations. In T1DM, higher adherence to the DASH diet was significantly associated with LDL/HDL ratio and A_1c. In youth with T2DM, DASH adherence was significantly associated with LDL particle density and BMI. In conclusion, the DASH dietary pattern may prove beneficial in the prevention and management of CVD risk in this vulnerable population of youth with diabetes mellitus, among whom there is clearly much room for improvement in the quality of dietary intake.

The SEARCH for Diabetes in Youth Study is indebted to the many youth and their families and their healthcare providers, whose participation made this study possible.

Sources of Funding: The authors wish to acknowledge the involvement of the General Clinical Research Centers at the Medical University of South Carolina (grant M01 RR01070); Seattle Children's Hospital and the University of Washington School of Medicine (grants M01RR00037 and M01RR001271); Colorado Pediatric General Clinical Research Center (grant M01 RR00069); and the Institutional Clinical and Translational Science Award, National Institutes of Health/National Center for Research Resources at the University of Cincinnati (grant 1UL1RR026314-01). The SEARCH for Diabetes in Youth Study is funded by the Centers for Disease Control and Prevention (PA No. 00097 and DP-05-069) and supported by the National Institute of Diabetes and Digestive and Kidney Diseases. Site contract numbers are as follows: Kaiser Permanente Southern California (U01 DP000246), University of Colorado Health Sciences Center (U01 DP000247), Pacific Health Research Institute (U01 DP000245), Children's Hospital Medical Center (Cincinnati) (U01 DP000248), University of North Carolina at Chapel Hill (U01 DP000254), University of Washington School of Medicine (U01 DP000244), and Wake Forest University School of Medicine (U01 DP000250). The contents of this article are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention and the National Institute of Diabetes and Digestive and Kidney Diseases.

Disclosures: None.

Orchard

Forrest

Kuller

Becker

Lipid and blood pressure treatment goals for type 1 diabetes: 10-year incidence data from the Pittsburgh Epidemiology of Diabetes Complications Study

Diabetes Care20012410531059

11375370

Rodriguez

Fujimoto

Mayer-Davis

Imperatore

Williams

Bell

Wadwa

Palla

Liu

Kershnar

Daniels

Linder

Prevalence of cardiovascular disease risk factors in U.S. children and adolescents with diabetes: the SEARCH for Diabetes in Youth Study

Diabetes Care20062918911896

16873798

Kershnar

Daniels

Imperatore

Palla

Petitti

Pettitt

Marcovina

Dolan

Hamman

Liese

Pihoker

Rodriguez

Lipid abnormalities are prevalent in youth with type 1 and type 2 diabetes: the SEARCH for Diabetes in Youth Study

J Pediatr2006149314319

16939739

Kavey

REW

Allada

Daniels

Hayman

McCrindle

Newburger

Parekh

Steinberger

Cardiovascular risk reduction in high-risk pediatric patients: a scientific statement from the American Heart Association Expert Panel on Population and Prevention Science; the Councils on Cardiovascular Disease in the Young, Epidemiology and Prevention, Nutrition, Physical Activity and Metabolism, High Blood Pressure Research, Cardiovascular Nursing, and the Kidney in Heart Disease; and the Interdisciplinary Working Group on Quality of Care and Outcomes Research: endorsed by the American Academy of Pediatrics

Circulation20061142710

17130340

Bantle

Wylie-Rosett

Albright

Apovian

Clark

Franz

Hoogwerf

Lichtenstein

Mayer-Davis

Mooradian

Wheeler

Nutrition recommendations and interventions for diabetes: a position statement of the American Diabetes Association

Diabetes Care200831S61S78

18165339

Obarzanek

Sacks

Vollmer

Bray

Miller

IIILin

Karanja

Most-Windhauser

Moore

Swain

Bales

Proschan

Effects on blood lipids of a blood pressure-lowering diet: the Dietary Approaches to Stop Hypertension (DASH) Trial

Am J Clin Nutr2001748089

11451721

Fung

Chiuve

McCullough

Rexrode

Logroscino

Adherence to a DASH-style diet and risk of coronary heart disease and stroke in women

Arch Intern Med2008168713720

18413553

Forman

Stampfer

Curhan

Diet and lifestyle risk factors associated with incident hypertension in women

JAMA2009302401411

19622819

Levitan

Wolk

Mittleman

Consistency with the DASH diet and incidence of heart failure

Arch Intern Med2009169851857

19433696

Parikh

Lipsitz

Natarajan

Association between a DASH-like diet and mortality in adults with hypertension: findings from a population-based follow-up study

Am J Hypertens200922409416

19197247

Hollis

Gullion

Stevens

Brantley

Appel

Ard

Champagne

Dalcin

Erlinger

Funk

Laferriere

Lin

Loria

Samuel-Hodge

Vollmer

Svetkey

Weight loss during the intensive intervention phase of the weight-loss maintenance trial

Am J Prev Med200835118126

18617080

Liese

Nichols

Sun

D'Agostino

JrHaffner

Adherence to the DASH diet is inversely associated with incidence of type 2 diabetes: the Insulin Resistance Atherosclerosis Study

Diabetes Care20093214341436

19487638

Guenther

Liese

Bell

Dabelea

Lawrence

Rodriquez

Standiford

Mayer-Davis

Association between the dietary approaches to hypertension diet and hypertension in youth with diabetes mellitus

Hypertension200953612

19029488

Ard

Grambow

Liu

Slentz

Kraus

Svetkey

The effect of the PREMIER interventions on insulin sensitivity

Diabetes Care200427340347

14747211

Azadbakht

Mirmiran

Esmaillzadeh

Azizi

Beneficial effects of a Dietary Approaches to Stop Hypertension eating plan on features of the metabolic syndrome

Diabetes Care20052828232831

16306540

SEARCH Study Group

SEARCH for Diabetes in Youth: a multicenter study of the prevalence, incidence and classification of diabetes mellitus in youth

Control Clin Trials200425458471

15465616

Ogden

Kuczmarski

Flegal

Mei

Guo

Wei

Grummer-Strawn

Curtin

Roche

Johnson

Centers for Disease Control and Prevention 2000 growth charts for the United States: improvements to the 1977 National Center for Health Statistics version

Pediatrics20021094560

11773541

Fernandez

Redden

Pietrobelli

Allison

Waist circumference percentiles in nationally representative samples of African-American, European-American, and Mexican-American children and adolescents

J Pediatr2004145439444

15480363

Hainline

JrMiller

Mather

The Coronary Drug Project: role and methods of the central laboratory

Control Clin Trials19834377

6327187

Diez

Iglesias

Fernandez-Reyes

Aguilera

Bajo

varez-Fidalgo

Codoceo

Selgas

Serum concentrations of leptin, adi-ponectin and resistin, and their relationship with cardiovascular disease in patients with end-stage renal disease

Clin Endocrinol200562242249

Marcovina

Albers

Kennedy

Mei

Henderson

Hannon

International Federation of Clinical Chemistry standardization project for measurements of apolipoproteins AI and BIV: comparability of apolipoprotein B values by use of international reference material

Clin Chem199440586592

8149615

Mayer-Davis

Nichols

Liese

Bell

Dabelea

Johansen

Pihoker

Rodriguez

Thomas

Williams

Dietary intake among youth with diabetes: the SEARCH for Diabetes in Youth Study

J Am Diet Assoc2006106689697

16647326

Windhauser

Ernst

Karanja

Crawford

Redican

Swain

Karimbakas

Champagne

Hoben

Evans

DASH Collaborative Research Group

Translating the Dietary Approaches to Stop Hypertension diet from research to practice: dietary and behavior change techniques

J Am Diet Assoc199999S90S95

10450300

US Department of Health and Human ServicesYour Guide to Lowering Your Blood Pressure: DASH Eating PlanWashington, DC

US Dept of Health and Human Services

2009NIH publication 06-4082

Grieco

Cassidy

Overview of Race and Hispanic Origin: Census 2000 BriefWashington, DC

US Census Bureau

2001

Krowchuk

Kreiter

Woods

Sinal

DuRant

Problem dieting behaviors among young adolescents

Arch Pediatr Adolesc Med1998152884888

9743034

Eisenmann

Bartee

Wang

Physical activity, TV viewing, and weight in US youth: 1999 Youth Risk Behavior Survey

Obesity200210379385

Moore

Singer

Bradlee

Djousse

Proctor

Cupples

Ellison

Intake of fruits, vegetables, and dairy products in early childhood and subsequent blood pressure change

Epidemiology200516411

15613939

Couch

Saelens

Levin

Dart

Falciglia

Daniels

The efficacy of a clinic-based behavioral nutrition intervention emphasizing a DASH-type diet for adolescents with elevated blood pressure

J Pediatr2008152494501

18346503

Lien

Brown

Ard

Loria

Erlinger

Feldstein

Lin

Champagne

King

McGuire

Effects of PREMIER lifestyle modifications on participants with and without the metabolic syndrome

Hypertension200750609

17698724

Eaton

Kann

Kinchen

Ross

Hawkins

Harris

Lowry

McManus

Chyen

Shanklin

Lim

Grunbaum

Wechsler

Youth Risk Behavior Surveillance: United States, 2005

MMWR Surveill Summ2006551108

16760893

Troped

Wiecha

Fragala

Matthews

Finkelstein

Kim

Peterson

Reliability and validity of YRBS physical activity items among middle school students

Med Sci Sports Exerc200739416425

17473767

Petitti

Imperatore

Palla

Daniels

Dolan

Kershnar

Marcovina

Pettitt

Pihoker

Serum lipids and glucose control: the SEARCH for Diabetes in Youth Study

Arch Pediatr Adolesc Med2007161159165

17283301

The DCCT Research Group

Lipid and lipoprotein levels in patients with IDDM diabetes control and complication: trial experience

Diabetes Care199215886894

1516509

The DCCT Research Group

Effect of intensive diabetes management on macrovascular events and risk factors in the Diabetes Control and Complications Trial

Am J Cardiol199575894903

7732997

Maahs

Dabelea

D'Agostino

JrAndrews

Crimmins

Mayer-Davis

Marcovina

Imperatore

Wadwa

Daniels

Reynolds

Dolan

Glycemic control predicts short-term change in lipid profile in youth with type 1 diabetes

Paper presented at: 69th Annual Scientific Sessions of the American Diabetes Association

June 5–9, 2009

New Orleans, LA

Diabetes200958A76

Albers

Marcovina

Imperatore

Snively

Stafford

Fujimoto

Mayer-Davis

Petitti

Pihoker

Dolan

Prevalence and determinants of elevated apolipoprotein B and dense low-density lipoprotein in youths with type 1 and type 2 diabetes

J Clin Endocrinol Metab200893735

18089692

Table 1Characteristics of the 2130 Youth in the Study Sample by Diabetes Type and DASH Adherence Score

	T1DM (n=1810) Tertiles of DASH Score				T2DM (n=320) Tertiles of DASH Score

	1 (Lowest)	2 (Medium)	3 (Highest)	P*	1 (Lowest)	2 (Medium)	3 (Highest)	P*
DASH score, mean (SD)	30.0 (4.6)	39.9 (2.4)	49.9 (4.7)	<0.0001	25.9 (4.9)	36.4 (2.3)	46.7 (5.0)	<0.0001
Age, mean (SD), y	15.0 (3.0)	14.7 (3.1)	14.9 (3.1)	0.304	16.8 (2.8)	16.8 (2.8)	16.3 (3.0)	0.323
Female, %	52.6	46.8	47.1	0.080	66.0	65.4	63.5	0.924
Race/ethnicity, %				<0.0001				0.087
Non-Hispanic white	72.3	79.3	81.9		17.0	22.4	14.9
Black	12.1	5.9	4.6		41.5	38.3	29.0
Hispanic	10.9	9.9	9.9		13.2	19.6	25.2
Other	4.6	4.8	3.5		28.3	19.6	30.8
Household income, %				<0.0001
<$25 000	15.2	12.7	8.6		50.0	42.7	51.1	0.299
$25 000–$74 999	47.7	44.8	40.1		44.2	44.9	35.2
≥$75 000	37.0	42.4	51.2		5.8	12.4	13.6
No high school diploma, %	4.2	3.5	3.3	0.712	16.0	13.1	14.0	0.821
Watch television >2 h/d, %	60.6	55.6	48.3	<0.0001	79.8	75.5	72.0	0.413
Vigorous physical activity ≥2 d/wk, %	70.5	76.2	83.9	0.0001	62.3	62.6	79.4	0.009
Smoking, %	12.1	7.4	4.6	<0.0001	15.1	17.8	9.3	0.195

DASH indicates Dietary Approaches to Stop Hypertension; T1DM, type 1 diabetes mellitus; and T2DM, type 2 diabetes mellitus.

P ANOVA or χ² test.

Table 2Mean Energy, Food Group, and Nutrient Intakes According to Diabetes Type and DASH Adherence Score

	T1DM (n = 1810) Tertiles of DASH Score			T2DM (n=320) Tertiles of DASH Score

Diet Characteristic	1 (Lowest)	2 (Medium)	3 (Highest)	1 (Lowest)	2 (Medium)	3 (Highest)
DASH score, mean (SD)	30 (4.6)	39.9 (2.4)	49.9 (4.7)	25.9 (4.9)	36.4 (2.3)	46.7 (5.0)
Energy, mean (SD), kcal/d	1987 (906)	1944 (1019)	1907 (767)	1961 (1031)	1764 (811)	1905 (1130)
Food groups, mean (SD), servings per 1000 kcal
Total grains	2.16 (0.75)	2.25 (0.77)	2.21 (0.71)*	2.02 (0.78)	2.18 (0.81)	2.12 (0.73)
High-fiber grains	0.04 (0.1)	0.05 (0.1)	0.07 (0.2)*	0.04 (0.1)	0.04 (0.1)	0.04 (0.1)
Vegetables	1.1 (0.8)	1.1 (0.8)	1.3 (1.0)*	1.3 (0.9)	1.3 (1.0)	1.7 (1.6)
Fruit	0.7 (0.6)	1.0 (0.8)	1.3 (0.8)*	0.6 (0.6)	0.9 (0.7)	1.3 (1.1)*
Total dairy	0.9 (0.6)	1.0 (0.6)	1.2 (0.6)*	0.6 (0.5)	0.8 (0.6)	0.8 (0.5)*
Low-fat dairy	0.4 (0.5)	0.6 (0.5)	0.7 (0.6)*	0.1 (0.3)	0.3 (0.6)	0.5 (0.5)*
Meat	1.6 (0.6)	1.3 (0.6)	1.1 (0.5)*	1.8 (0.7)	1.5 (0.6)	1.4 (0.6)*
Nuts and seeds	0.1 (0.3)	0.4 (0.5)	0.7 (0.8)*	0.1 (0.4)	0.3 (0.6)	0.5 (0.5)*
Fats and oils	2.4 (1.5)	2.1 (1.5)	1.7 (1.5)*	2.5 (1.5)	2.0 (1.7)	1.8 (1.7)*
Sweets	1.1 (0.8)	0.9 (0.6)	0.8 (0.5)*	1.3 (1.0)	1.1 (0.9)	0.9 (0.7)*
Nutrients, mean (SD), per 1000 kcal
Carbohydrates, g	114 (19)	118 (18)	124 (17)*	114 (22)	119 (21)	123 (22)*
Total fat, g	44 (6)	42 (6)	41 (6)*	44 (8)	42 (7)	41 (7)*
Saturated fat, g	16 (3)	15 (2)	14 (2)*	16 (3)	15 (3)	14 (3)*
Protein, g	40 (7)	39 (5)	39 (5)*	39 (8)	38 (7)	39 (7)
Fiber, g	6 (2)	7 (2)	8 (3)*	6 (2)	7 (2)	8 (3)*
Calcium, mg	539 (223)	610 (242)	669 (242)*	378 (159)	429 (199)	510 (237)*
Magnesium, mg	123 (27)	138 (27)	155 (31)*	109 (24)	122 (25)	140 (31)*
Potassium, mg	2332 (1168)	2524 (1303)	2765 (1152)*	2077 (1225)	2066 (1025)	2591 (1516)*

DASH indicates Dietary Approaches to Stop Hypertension; T1DM, type 1 diabetes mellitus; and T2DM, type 2 diabetes mellitus. DASH-recommended servings per 1000 kcal per day: ≥3 servings of grains; ≥2 servings of fruits; ≥2 servings of vegetables; ≥1 serving of dairy; ≤1 serving of lean meats, poultry, or fish; ≥0.3 servings of nuts, seeds, or legumes; ≤1.5 servings of fats and oils; ≤0.3 servings of sweets and added sugar.

P<0.05.

Table 3Mean Cardiovascular Disease Risk Factor Levels According to Diabetes Type and DASH Adherence Score

	T1DM Tertiles of DASH Score				T2DM Tertiles of DASH Score

Cardiovascular Disease Risk Factor	n	1 (Lowest)	2 (Medium)	3 (Highest)	n	1 (Lowest)	2 (Medium)	3 (Highest)
Total cholesterol, mg/dL	1615	171.4 (32.8)	169.4 (33.4)	166.6 (34.1)	313	186.6 (42)	185.4 (45.3)	172.5 (37.6)
LDL cholesterol, mg/dL	1615	100.4 (25.6)	99.2 (27.8)	96.8 (26.2)	313	106.4 (30.6)	111.4 (34.4)	101.9 (31.2)
HDL cholesterol, mg/dL	1616	54.4 (13.5)	53.9 (12)	54.3 (12.2)	313	43 (12.5)	43.2 (10.6)	41.8 (9.1)
LDL/HDL ratio	1615	1.95 (0.68)	1.94 (0.75)	1.86 (0.63)	313	2.60 (0.88)	2.67 (0.87)	2.52 (0.94)
Triglycerides, mg/dL	1615	84.7 (82.6)	86.2 (133.3)	78.1 (56)	254	257.4 (508.4)	153.8 (143.3)	157.6 (135.3)
LDL particle density, flotation rate	1302	0.28 (0.02)	0.28 (0.02)	0.28 (0.02)	182	0.24 (0.04)	0.26 (0.03)	0.26 (0.03)
Apolipoprotein B, mg/dL	1317	77.7 (21.7)	76.3 (22.4)	74.9 (20.9)	184	106.2 (75.8)	96.8 (27.8)	86.1 (25.1)
Body mass index Z score	1518	0.64 (0.86)	0.66 (0.87)	0.57 (0.89)	224	2.22 (0.63)	1.99 (0.74)	1.93 (0.77)
Waist circumference, cm	1578	78.7 (11.8)	78.8 (11.8)	78.5 (11.2)	254	114.8 (27.5)	110.6 (18.1)	106.4 (21.9)
A_1c,%	1518	8.57 (1.69)	8.33 (1.66)	8.16 (1.47)	224	7.42 (2.41)	7.86 (2.45)	7.12 (2.08)

Values are mean (SD). DASH indicates Dietary Approaches to Stop Hypertension; T1DM, type 1 diabetes mellitus; T2DM, type 2 diabetes mellitus; LDL, low-density lipoprotein; and HDL, high-density lipoprotein.

Table 4Association of DASH Score With Cardiovascular Disease Risk Factors in Youth With Type 1 Diabetes Mellitus

Cardiovascular Disease Risk Factor	β*	SE	P	Tertile 1†	Tertile 3†	Mean Difference (Tertile 3–Tertile 1)
Total cholesterol, mg/dL (n=1615)
Model 1	−2.05	0.92	0.026	171.1	167.4	−3.7
Model 2	−1.53	0.93	0.101	170.7	168	−2.7
Model 3	−2.37	0.97	0.014	171.6	167.4	−4.2
Model 4	−0.95	0.89	0.285	171.5	169.8	−1.7
LDL cholesterol, mg/dL (n=1615)
Model 1	−1.76	0.74	0.017	100.5	97.3	−3.2
Model 2	−1.42	0.75	0.060	100.2	97.7	−2.5
Model 3	−1.85	0.78	0.017	101.2	97.9	−3.3
Model 4	−1.00	0.72	0.166	100.9	99.1	−1.8
HDL cholesterol, mg/dL (n=1615)
Model 1	0.25	0.34	0.473	53.8	54.2	0.4
Model 2	0.17	0.35	0.625	53.8	54.1	0.3
Model 3	−0.14	0.35	0.689	53.4	53.2	−0.2
Model 4	0.20	0.35	0.573	53.6	54	0.4
LDL/HDL ratio (n=1615)
Model 1	−0.05	0.02	0.008	1.97	1.88	−0.09
Model 2	−0.04	0.02	0.034	1.97	1.89	−0.08
Model 3	−0.04	0.02	0.050	2	1.93	−0.07
Model 4	−0.03	0.02	0.080	1.98	1.92	−0.06
Log triglycerides, mg/dL (n=1615)‡
Model 1	−0.022	0.014	0.117	71.8	69.1	−2.7
Model 2	−0.008	0.014	0.544	71.1	70	−1.1
Model 3	−0.010	0.014	0.508	72.4	71.2	−1.2
Model 4	−0.001	0.013	0.923	72.5	72.4	−0.1
LDL particle density, flotation rate (n=1302)
Model 1	0.0006	0.0006	0.336	0.28	0.28	0
Model 2	0.0002	0.0006	0.736	0.28	0.28	0
Model 3	0.0003	0.0006	0.682	0.28	0.28	0
Model 4	−0.00002	0.0006	0.979	0.28	0.28	0
Log apolipoprotein B, mg/dL (n=1317)‡
Model 1	−0.012	0.0081	0.037	74.7	72.5	−2.2
Model 2	−0.012	0.0082	0.149	74.5	72.9	−1.6
Model 3	−0.017	0.0085	0.051	75.2	73	−2.2
Model 4	−0.007	0.0077	0.361	74.9	74	−0.9
Body mass index Z score (n=1518)
Model 1	−0.045	0.025	0.075	0.67	0.59	−0.08
Model 2	−0.039	0.026	0.128	0.66	0.59	−0.07
Model 3
Model 4	−0.042	0.026	0.102	0.9	0.83	−0.07
Waist circumference, cm (n=1578)
Model 1	−0.28	0.29	0.320	79.4	78.9	−0.5
Model 2	−0.20	0.29	0.480	79.3	79	−0.3
Model 3	0.17	0.18	0.319	79.6	79.9	0.3
Model 4	−0.22	0.29	0.455	79.6	79.2	−0.4
A_1c, % (n=1518)
Model 1	−0.12	0.04	0.007	8.51	8.30	−0.21
Model 2	−0.11	0.04	0.016	8.50	8.31	−0.19
Model 3	−0.11	0.04	0.014	8.49	8.29	−0.20
Model 4

DASH indicates Dietary Approaches to Stop Hypertension; LDL, low-density lipoprotein; and HDL, high-density lipoprotein.

Model 1 is adjusted for age, sex, race, site, diabetes mellitus duration, income; model 2, model 1 +television time, vigorous physical activity, smoking; model 3, model 2+body mass index Zscore; and model 4, model 3+A_1c.

β for 10-unit DASH increase.

†

Mean risk factor estimated at tertiles 1 and 3 of DASH score.

‡

Tertile 1 and 3 estimates back-transformed to original units.

Table 5Association of DASH Score With Cardiovascular Disease Risk Factors in Youth With Type 2 Diabetes Mellitus

Cardiovascular Disease Risk Factor	β*	SE	P	Tertile 1†	Tertile 3†	Mean Difference (Tertile 3–Tertile 1)
Total cholesterol, mg/dL (n=313)
Model 1	−4.81	2.90	0.099	185.7	176.7	−9
Model 2	−4.74	2.94	0.109	171.8	163.3	−8.5
Model 3	−7.36	3.08	0.018	186.5	173.3	−13.2
Model 4	−4.02	2.72	0.140	186.4	178.8	−7.6
LDL cholesterol, mg/dL (n=313)
Model 1	−2.47	2.33	0.291	108.8	104.1	−4.7
Model 2	−2.49	2.37	0.293	103.8	99.4	−4.4
Model 3	−4.32	2.55	0.092	110.8	103	−7.8
Model 4	−2.16	2.31	0.352	109.1	105	−4.1
HDL cholesterol, mg/dL (n=313)
Model 1	−0.26	0.69	0.708	42.7	42.2	−0.5
Model 2	−0.25	0.70	0.727	39.8	39.4	−0.4
Model 3	−0.77	0.72	0.289	47.1	45.8	−1.3
Model 4	−0.26	0.70	0.712	42.6	42.2	−0.4
LDL/HDL ratio (n=313)
Model 1	−0.05	0.06	0.391	2.65	2.55	−0.1
Model 2	−0.05	0.06	0.401	2.71	2.62	−0.09
Model 3	−0.06	0.07	0.328	2.45	2.33	−0.12
Model 4	−0.04	0.06	0.480	2.65	2.57	−0.08
Log triglycerides, mg/dL (n=254)‡
Model 1	−0.03	0.05	0.591	132.5	126.5	−6
Model 2	−0.03	0.05	0.517	121.6	115.2	−6.4
Model 3	−0.03	0.05	0.517	111.9	105.6	−6.3
Model 4	−0.02	0.04	0.635	134.8	129.5	−5.3
LDL particle density, flotation rate (n=182)
Model 1	0.01	0.003	0.003	0.25	0.27	0.02
Model 2	0.01	0.003	0.004	0.26	0.27	0.01
Model 3	0.01	0.003	0.015	0.26	0.27	0.01
Model 4	0.01	0.002	0.008	0.25	0.26	0.01
Log apolipoprotein B, mg/dL (n=184)‡
Model 1	−0.05	0.03	0.068	93.1	85.3	−7.8
Model 2	−0.04	0.03	0.093	82.9	76.7	−6.2
Model 3	−0.05	0.03	0.076	83.5	76.2	−7.3
Model 4	−0.03	0.02	0.256	91.6	87	−4.6
Body mass index Z score (n=224)
Model 1	−0.13	0.05	0.010	2.11	1.85	−0.26
Model 2	−0.14	0.05	0.009	2.05	1.81	−0.24
Model 3
Model 4	−0.14	0.05	0.009	2.1	1.84	−0.26
Waist circumference, cm (n=254)
Model 1	−2.89	1.55	0.064	108.6	103.4	−5.2
Model 2	−3.01	1.57	0.057	108.9	103.5	−5.4
Model 3	−1.16	1.08	0.286	74.3	72.3	−2
Model 4	−3.03	1.58	0.056	113.5	107.8	−5.7
A_1c, % (n=224)
Model 1	−0.007	0.16	0.965	7.67	7.66	−0.01
Model 2	−0.029	0.16	0.859	6.63	6.68	0.05
Model 3	−0.023	0.17	0.889	7.17	7.13	−0.04
Model 4

DASH indicates Dietary Approaches to Stop Hypertension; LDL, low-density lipoprotein; and HDL, high-density lipoprotein.

Model 1 is adjusted for age, sex, race, site, diabetes duration, income; model 2, model 1 +television time, vigorous physical activity, smoking; model 3, model 2+body mass index Z score; and model 4, model 3+A_1c.

β for 10-unit DASH increase.

†

Mean risk factor estimated at tertiles 1 and 3 of DASH score.

‡

Tertile 1 and 3 estimates back-transformed to original units.

Clinical Perspective

Since the publication of the landmark findings of the Dietary Approaches to Stop Hypertension (DASH) trial, the DASH diet has become well known as an effective whole-diet approach to hypertension prevention and blood pressure reduction. However, little is known about its impact on other cardiovascular disease risk factors, especially in youth with type 1 and type 2 diabetes mellitus. In this cross-sectional study, we explored the association of DASH diet with blood lipid levels, lipoproteins, adipocytokines, and measures of adiposity and glycemic control in 2130 youth aged 10 to 22 years with physician-diagnosed diabetes mellitus. Dietary intake was assessed by food frequency questionnaire, categorized into the DASH food groups, and assigned an adherence score. In both type 1 and type 2 diabetes mellitus youth, the average DASH diet scores were low, suggesting very poor dietary intake quality in this population. Of the various cardiovascular disease risk factors evaluated, we found that among youth with type 1 diabetes mellitus, higher adherence to the DASH diet was significantly associated with lower levels of low-density lipoprotein/high-density lipoprotein ratio and A_1c. In youth with type 2 diabetes mellitus, higher adherence to the DASH diet was significantly associated with higher low-density lipoprotein particle density and lower body mass index Z score. In conclusion, the DASH dietary pattern may prove beneficial in the prevention and management of cardiovascular disease risk in this vulnerable population of youth with diabetes mellitus, among whom there is clearly much room for improvement in the quality of dietary intake.