2020
Worksite intervention study to prevent diabetes in Nepal: a randomised trial protocol
Pyakurel P, Shrestha A, Karmacharya BM, Budhathoki SS, Chaudhari RK, Tamrakar D, Shrestha A, Karmacharya RM, Shrestha A, Sharma S, Sharma SK, Spiegelman D. Worksite intervention study to prevent diabetes in Nepal: a randomised trial protocol. Open Heart 2020, 7: e001236. PMID: 32847993, PMCID: PMC7451278, DOI: 10.1136/openhrt-2019-001236.Peer-Reviewed Original ResearchMeSH KeywordsAdultBiomarkersBlood GlucoseDiabetes MellitusGlycated HemoglobinHealth BehaviorHealth Knowledge, Attitudes, PracticeHealthy LifestyleHumansMaleMiddle AgedMulticenter Studies as TopicNepalOccupational Health ServicesPatient Education as TopicPrediabetic StatePrimary PreventionRandomized Controlled Trials as TopicRisk Reduction BehaviorTime FactorsTreatment OutcomeConceptsBehavioral interventionsControl periodDiabetes risk reductionMonth control periodNepal Health Research CouncilBehavioral intervention groupWorksite intervention studiesT-testHealth Research CouncilInstitutional review boardTwo-sample t-testBlood sugarTrial protocolIntervention groupEthical approvalControl groupIntervention studiesType 2More monthsReview boardInterventionDiabetesParticipant changesPublic healthRisk reduction
2019
Glycemic Index and Microstructure Evaluation of Four Cereal Grain Foods
RamyaBai M, Wedick N, Shanmugam S, Arumugam K, Nagarajan L, Vasudevan K, Gunasekaran G, Rajagopal G, Spiegelman D, Malik V, Anjana R, Hu F, Unnikrishnan R, Willett W, Malleshi N, Njelekela M, Gimbi D, Krishnaswamy K, Henry C, Mohan V, Sudha V. Glycemic Index and Microstructure Evaluation of Four Cereal Grain Foods. Journal Of Food Science 2019, 84: 3373-3382. PMID: 31762024, DOI: 10.1111/1750-3841.14945.Peer-Reviewed Original ResearchConceptsGlycemic indexMedium glycemic indexTest foodGrain foodsCapillary blood samplesHigh glycemic indexCereal grain foodsWhole grain foodsHigh GI foodsMean ageBlood glucoseBlood samplesGI valuesGI foodsHealthy participantsSeparate occasionsHealthy optionsRegular brown riceWhole grainsStandard protocolLoss of intactnessHealthy alternativeLoss of integrityAvailable carbohydrateGlucoseSubstituting brown rice for white rice on diabetes risk factors in India: a randomised controlled trial
Malik V, Sudha V, Wedick N, RamyaBai M, Vijayalakshmi P, Lakshmipriya N, Gayathri R, Kokila A, Jones C, Hong B, Li R, Krishnaswamy K, Anjana R, Spiegelman D, Willett W, Hu F, Mohan V. Substituting brown rice for white rice on diabetes risk factors in India: a randomised controlled trial. British Journal Of Nutrition 2019, 121: 1389-1397. PMID: 31006420, PMCID: PMC6948352, DOI: 10.1017/s000711451900076x.Peer-Reviewed Original ResearchConceptsBrown rice groupMetabolic syndromePrimary outcomeRisk factorsHigh-sensitivity C-reactive proteinRandomised cross-over trialT2D risk factorsDiabetes risk factorsC-reactive proteinCross-over trialType 2 diabetesWhite rice groupMeals/dHs-CRPSecondary outcomesElevated BMIWashout periodInsulin resistanceBlood glucoseEpidemiological evidenceWhite riceT2D riskUrban South IndiaBMISyndrome
2018
Cashew Nut Consumption Increases HDL Cholesterol and Reduces Systolic Blood Pressure in Asian Indians with Type 2 Diabetes: A 12-Week Randomized Controlled Trial
Mohan V, Gayathri R, Jaacks LM, Lakshmipriya N, Anjana RM, Spiegelman D, Jeevan RG, Balasubramaniam KK, Shobana S, Jayanthan M, Gopinath V, Divya S, Kavitha V, Vijayalakshmi P, Bai R M, Unnikrishnan R, Sudha V, Krishnaswamy K, Salas-Salvadó J, Willett WC. Cashew Nut Consumption Increases HDL Cholesterol and Reduces Systolic Blood Pressure in Asian Indians with Type 2 Diabetes: A 12-Week Randomized Controlled Trial. Journal Of Nutrition 2018, 148: 63-69. PMID: 29378038, DOI: 10.1093/jn/nxx001.Peer-Reviewed Original ResearchConceptsSystolic blood pressureBlood pressureNut consumptionBody weightAsian IndiansHDL cholesterolDiabetic dietNut supplementationSelf-reported dietary intakeStandard diabetic dietClinical Trials RegistryHDL cholesterol concentrationsPlasma HDL cholesterolType 2 diabetesCashew nut consumptionBlood lipidsControlled TrialsTrials RegistryGlycemic variablesLipid variablesDietary intakeIntervention groupLipid profileCardiovascular diseaseRobust variance estimation
2011
Socio-economic status, urbanization, and cardiometabolic risk factors among middle-aged adults in Tanzania.
Njelekela MA, Liu E, Mpembeni R, Muhihi A, Mligiliche N, Spiegelman D, Finkelstein JL, Fawzi WW, Willett WC, Mtabaji J. Socio-economic status, urbanization, and cardiometabolic risk factors among middle-aged adults in Tanzania. East African Journal Of Public Health 2011, 8: 216-23. PMID: 23120960.Peer-Reviewed Original ResearchMeSH KeywordsAdultBlood GlucoseBlood PressureBody Mass IndexCardiovascular DiseasesCross-Sectional StudiesDietExerciseFemaleHealth BehaviorHumansLife StyleLipidsLogistic ModelsMaleMetabolic SyndromeMiddle AgedObesityResidence CharacteristicsRisk FactorsSocioeconomic FactorsSurveys and QuestionnairesTanzaniaUrban HealthUrbanizationWaist CircumferenceConceptsCardiometabolic risk factorsPoorer lipid profileHigher socioeconomic statusRisk factorsLipid profileSocioeconomic statusUrban residenceCardio-metabolic risk factorsWorld Health Organization criteriaHigher total cholesterolHigh waist circumferenceRisk of obesityHealth screening strategiesMiddle-aged adultsMetabolic syndromeTotal cholesterolWaist circumferenceLDL cholesterolHigher BMIPrimary preventionLower triglyceridesOrganization criteriaDietary factorsCardiovascular diseaseGlucose levels
2003
A Cross-Sectional Study of Alcohol Consumption Patterns and Biologic Markers of Glycemic Control Among 459 Women
Kroenke CH, Chu NF, Rifai N, Spiegelman D, Hankinson SE, Manson JE, Rimm EB. A Cross-Sectional Study of Alcohol Consumption Patterns and Biologic Markers of Glycemic Control Among 459 Women. Diabetes Care 2003, 26: 1971-1978. PMID: 12832298, DOI: 10.2337/diacare.26.7.1971.Peer-Reviewed Original ResearchConceptsHealth Study IIGlycemic controlAlcohol intakeBiologic markersNurses' Health Study IIBeneficial glycemic effectsAverage alcohol intakeModerate alcohol consumptionMain outcome measuresCross-sectional studyYears of ageAlcohol consumption patternsOverweight womenGlycemic effectsInsulin levelsLifestyle factorsInsulin resistanceDietary factorsInverse associationC-peptideAverage daily consumptionOutcome measuresPhysical activityBlood samplesAlcohol consumptionAlcohol Consumption Patterns and HbA1c, C-Peptide and Insulin Concentrations in Men
Meyer KA, Conigrave KM, Chu NF, Rifai N, Spiegelman D, Stampfer MJ, Rimm EB. Alcohol Consumption Patterns and HbA1c, C-Peptide and Insulin Concentrations in Men. Journal Of The American Nutrition Association 2003, 22: 185-194. PMID: 12805244, DOI: 10.1080/07315724.2003.10719292.Peer-Reviewed Original ResearchConceptsC-peptideInsulin concentrationsAverage alcohol consumptionAlcohol consumptionAlcohol consumption patternsBlood samplesStudy participantsDrinking patternsDisease-free menC-peptide concentrationsModerate alcohol consumptionCross-sectional studyYears of ageFrequent alcohol consumptionFrequency of consumptionEffects of alcoholInsulin levelsBiologic markersInsulin sensitivityInverse associationAverage daily consumptionIrregular drinkersObservational studyAnalysis of insulinHealth professionals
1997
Dietary Fiber, Glycemic Load, and Risk of NIDDM in Men
Salmerón J, Ascherio A, Rimm E, Colditz G, Spiegelman D, Jenkins D, Stampfer M, Wing A, Willett W. Dietary Fiber, Glycemic Load, and Risk of NIDDM in Men. Diabetes Care 1997, 20: 545-550. PMID: 9096978, DOI: 10.2337/diacare.20.4.545.Peer-Reviewed Original ResearchConceptsRisk of NIDDMHigh glycemic loadGlycemic loadCereal fiberRelative riskHigher cereal fiber intakeSemiquantitative food frequency questionnaireCereal fiber intakeLarge glycemic responseDietary glycemic indexFood frequency questionnaireIncidence of NIDDMIntake of carbohydratesTotal energy intakeLow glycemic loadYears of ageDietary fiberFrequency questionnaireIncident casesLowest quintileCardiovascular diseaseFamily historyFiber intakeNIDDMPhysical activity
1992
Correction of Logistic Regression Relative Risk Estimates and Confidence Intervals for Random Within-Person Measurement Error
Rosner B, Spiegelman D, Willett WC. Correction of Logistic Regression Relative Risk Estimates and Confidence Intervals for Random Within-Person Measurement Error. American Journal Of Epidemiology 1992, 136: 1400-1413. PMID: 1488967, DOI: 10.1093/oxfordjournals.aje.a116453.Peer-Reviewed Original ResearchConceptsRelative risk estimatesRisk factorsLogistic regressionRisk estimatesCoronary risk factorsCoronary heart diseaseGold standardConfidence intervalsFramingham Heart StudyExamination 4Extreme quintilesHeart diseaseOdds ratioHeart StudyExamination 2Exposure assessmentSubstudyCovariatesMenMain studyReproducibility dataRegressionFactorsQuintileIncidenceAbsolute fat mass, percent body fat, and body-fat distribution: which is the real determinant of blood pressure and serum glucose?
Spiegelman D, Israel R, Bouchard C, Willett W. Absolute fat mass, percent body fat, and body-fat distribution: which is the real determinant of blood pressure and serum glucose? American Journal Of Clinical Nutrition 1992, 55: 1033-1044. PMID: 1595574, DOI: 10.1093/ajcn/55.6.1033.Peer-Reviewed Original ResearchConceptsBody mass indexBlood pressurePercent body fatAbsolute fat massFat massSerum glucoseBody fatBlood glucoseDiastolic blood pressureBody fat distributionCigarette smoking statusCurrent cigarette smoking statusRegional fat distributionMultiple skinfold thicknessesRelative fat massMass indexFat distributionOverall body massSkinfold thicknessBody compositionStudy centersGold standardHip girthStrongest predictorUnderwater weighing