Assessment of dietary patterns in celiac disease patients using factor analysis method and their relationship with dietary intakes and body mass index.

BACKGROUND/OBJECTIVES: Celiac disease (CD) is a systemic and autoimmune enteropathy of the gastrointestinal tract with malabsorption characteristics. The only effective treatment for CD is adhere strictly to a gluten-free diet (GFD) throughout life. We evaluated the dietary patterns in celiac disease patients and their association with dietary intakes and anthropometric measurements in Iran. SUBJECTS/METHODS: This is a case-control study on 182 participants who were referred to the Khuzestan Celiac Association, Iran. Nutritional information was collected using a validated 147-item semi-quantitative food frequency questionnaire (FFQ). The software Stata (StataCorp, Version 14.0) was used to analyze the data. Principal component analysis (PCA) was used to obtain participants' dietary patterns. RESULTS: A significant relationship was observed between age and body mass index (BMI) across quartiles of the healthy dietary pattern score (P < 0.001, P = 0.001, and P = 0.001, respectively), indicating that as age and BMI increased, participants demonstrated greater adherence to the healthy dietary pattern. Individuals with the highest adherence to the healthy dietary pattern had the lowest odds ratio for celiac disease (CD) (Q1: reference; Q2: 1.96, 95% CI: 0.84-4.55; Q3: 0.61, 95% CI: 0.27-1.42; Q4: 0.10, 95% CI: 0.03-0.33, P trend < 0.001), and this association remained significant after adjusting for BMI (adjusted P trend = 0.003) and energy intake (adjusted P trend < 0.001). Moreover, there was a significant association between the lowest odds ratio for CD and the highest adherence to the unhealthy dietary pattern after adjustment for energy intake (Q1: reference; Q2: 0.38, 95% CI: 0.13-1.12; Q3: 0.21, 95% CI: 0.06-0.71; Q4: 0.07, 95% CI: 0.02-0.29, adjusted P trend < 0.001). Additionally, a significant association was observed between the odds ratio for CD and the mixed dietary pattern score (Q1: reference; Q2: 6.01, 95% CI: 2.29-15.72; Q3: 2.47, 95% CI: 0.93-6.55; Q4: 4.84, 95% CI: 1.84-12.66, P trend = 0.02), and this association remained significant after adjustment for energy intake (adjusted P trend < 0.001). CONCLUSIONS: The findings of the present study indicate that individuals who adhere to healthy dietary patterns have a lower incidence of celiac disease.

Glycemic index, glycemic load, dietary insulin index, and dietary insulin load in relation to cardiometabolic risk factors among participants with atherosclerosis: a cross-sectional study.

BACKGROUND: We examined the cross-sectional associations of dietary Glycemic Index (GI), Glycemic Load (GL), Dietary Insulin Index (DII), and Dietary Insulin Load (DIL) with cardiovascular disease (CVD) factors in subjects with atherosclerosis. METHODS: The present cross-sectional study was conducted on subjects with atherosclerosis. Regular dietary intake was assessed using a 168-item semi-quantitative food frequency questionnaire (FFQ) and GI, GL, DIL, and DII were also calculated. Odds Ratio (OR) and 95% Confidence Intervals (CIs) were estimated for general and central obesity according to the GI, GL, DII, and DIL. RESULTS: According to the continuous score of GL, there was a significant positive association between GL and central obesity for women in all models. Regarding the association between DIL score and biochemical variables, there was a significant positive association between Na and Aspartate transaminase (AST) with DII. Moreover, there was a significant positive association between LDL-c(p = 0.03) and AST (p = 0.04)with DIL score in all 3 models. CONCLUSION: In this study, GL was associated with greater odds of central obesity in women, but not in men. Neither dietary DII nor DIL was associated with BMI and central obesity. GI, GL, DII, and DIL were significantly associated with some CVD risk biomarkers in subjects with atherosclerosis.

The Association between Diet Quality Scores with Sleep Quality among Employees: A Cross-Sectional Study.

BACKGROUND: Numerous factors such as nutrition and diet can affect the quality of sleep of people, especially employees. The aim of this study was to investigate the relationship between university employees' sleep quality and their dietary quality scores (HEI, DII and DASH score). MATERIALS AND METHODS: This cross-sectional study was performed on 211 employees with a mean age of 38.75±11.31. Nutritional status of individuals was determined through the Food Frequency Questionnaire (FFQ) and to assess sleep quality, the Pittsburgh Sleep Quality Index (PSQI) was used. The quality of sleep decreases with increasing Pittsburgh index score. The calculated dietary quality scores include DASH Index, Healthy Nutrition Index (HEI) and Diet Inflammation Index (DII). RESULTS: The results of this study after adjusting for confounding showed a significant positive relationship between DASH diet score and sleep duration (p <0.001). There was a significant negative relationship between HEI score and total score of PSQI (P = 0.003). Also, HEI score had a significant positive relationship with sleep duration in the unmodified and modified models (p <0.001), and a significant negative relationship was seen in unadjusted and modified model between DII score and sleep duration (p <0.001). CONCLUSION: It can be concluded that with increasing the diet quality in employees, the sleep quality also increases. This was the first study in south of Iran that examined the quality of sleep and diet of employees and the result of this study can affect the general health and improve the quality of foods consumed by employees.

Associations between new and old anthropometric indices with type 2 diabetes mellitus and risk of metabolic complications: a cross-sectional analytical study.

BACKGROUND: Obesity can increase the risk of diabetes mellitus and complications associated with it. OBJECTIVES: The aim of this study was to estimate the associations between new and old anthropometric indices and the risk of type 2 diabetes mellitus (T2DM) and its metabolic complications. METHODS: In this cross-sectional analytical study, 110 T2DM subjects and 110 healthy controls were selected by convenience sampling. Metabolic factors were evaluated including the atherogenic index of plasma (AIP), glycemic status, lipid profile, blood pressure, kidney indices, new anthropometric indices (abdominal volume index [AVI], body shape index [ABSI], lipid accumulation product [LAP], body adiposity index [BAI], and conicity index [CI]), and old anthropometric indices (weight, body mass index [BMI], and waist and hip circumference [WC and HC]). RESULTS: Significant positive correlations were observed between AVI, LAP, and BAI and fasting blood glucose and HbA1c in the T2DM group (p < 0.001 for all associations). The odds ratio (OR) for T2DM elevated significantly with increasing BMI (OR: 1.30, 95% CI: 1.20-1.42), LAP (OR: 1.20, 95% CI: 1.13-1.27), and BAI (OR: 1.32, 95% CI: 1.21-1.43). The indices AVI (OR: 1.90, 95% CI: 1.57-2.29), LAP (OR: 1.19, 95% CI: 1.13-1.27), BAI (OR: 1.19, 95% CI: 1.12-1.26), WC (OR: 1.29, 95% CI: 1.18, 1.42), and HC (OR: 1.07, 95% CI: 1.01, 1.14) significantly increased the risk of metabolic syndrome (MetS). CONCLUSIONS: Associations were identified between obesity indices and diabetes. These indices could be used in clinical practice for evaluation and control of T2DM.

CONTEXTO: A obesidade pode aumentar o risco de diabetes melito e complicações associadas. OBJETIVOS: O objetivo deste estudo foi estimar a associação de índices antropométricos novos e antigos com o risco de diabetes melito tipo 2 (DM2) e suas complicações metabólicas. MÉTODOS: Neste estudo analítico transversal, 110 indivíduos com DM2 e 110 controles saudáveis foram selecionados por amostragem de conveniência. Foram avaliados os fatores metabólicos, incluindo índice aterogênico plasmático, estado glicêmico, perfil lipídico, pressão arterial, índices renais, índices antropométricos novos [índice de volume abdominal (AVI), índice de formato corporal (ABSI), produto de acumulação lipídica (LAP), índice de adiposidade corporal (BAI) e índice de conicidade (CI)] e índices antropométricos antigos [peso, índice de massa corporal (IMC), circunferência de cintura e quadril]. RESULTADOS: Foi observada uma correlação positiva significativa de AVI, LAP e BAI com glicemia de jejum e hemoglobina glicada no grupo DM2 (p para todos < 0,001). A odds ratio (OR) do grupo DM2 foi significativamente elevada com aumento de IMC [OR: 1,30, intervalo de confiança (IC) de 95%: 1,20-1,42], LAP (OR: 1,20, IC95%: 1,13-1,27) e BAI (OR: 1,32, IC95%: 1,21-1,43). Os índices AVI (OR: 1,90, IC95%: 1,57-2,29), LAP (OR: 1,19, IC95%: 1,13-1,27), BAI (OR: 1,19, IC95%: 1,12-1,26), WC (OR: 1,29, IC95%: 1,18-1,42) e HC (OR: 1,07, IC95%: 1,01-1,14) aumentaram significativamente o risco de síndrome metabólica. CONCLUSÕES: Foi reconhecida uma associação entre índices de obesidade e diabetes. Esses índices podem ser usados na prática clínica para avaliação e controle do DM2.

Associations between new and old anthropometric indices with type 2 diabetes mellitus and risk of metabolic complications: a cross-sectional analytical study / Associação de índices antropométricos novos e antigos com diabetes melito tipo 2 e risco de complicações metabólicas: um estudo analítico de corte transversal

Abstract Background Obesity can increase the risk of diabetes mellitus and complications associated with it. Objectives The aim of this study was to estimate the associations between new and old anthropometric indices and the risk of type 2 diabetes mellitus (T2DM) and its metabolic complications. Methods In this cross-sectional analytical study, 110 T2DM subjects and 110 healthy controls were selected by convenience sampling. Metabolic factors were evaluated including the atherogenic index of plasma (AIP), glycemic status, lipid profile, blood pressure, kidney indices, new anthropometric indices (abdominal volume index [AVI], body shape index [ABSI], lipid accumulation product [LAP], body adiposity index [BAI], and conicity index [CI]), and old anthropometric indices (weight, body mass index [BMI], and waist and hip circumference [WC and HC]). Results Significant positive correlations were observed between AVI, LAP, and BAI and fasting blood glucose and HbA1c in the T2DM group (p < 0.001 for all associations). The odds ratio (OR) for T2DM elevated significantly with increasing BMI (OR: 1.30, 95% CI: 1.20-1.42), LAP (OR: 1.20, 95% CI: 1.13-1.27), and BAI (OR: 1.32, 95% CI: 1.21-1.43). The indices AVI (OR: 1.90, 95% CI: 1.57-2.29), LAP (OR: 1.19, 95% CI: 1.13-1.27), BAI (OR: 1.19, 95% CI: 1.12-1.26), WC (OR: 1.29, 95% CI: 1.18, 1.42), and HC (OR: 1.07, 95% CI: 1.01, 1.14) significantly increased the risk of metabolic syndrome (MetS). Conclusions Associations were identified between obesity indices and diabetes. These indices could be used in clinical practice for evaluation and control of T2DM.

Resumo Contexto A obesidade pode aumentar o risco de diabetes melito e complicações associadas. Objetivos O objetivo deste estudo foi estimar a associação de índices antropométricos novos e antigos com o risco de diabetes melito tipo 2 (DM2) e suas complicações metabólicas. Métodos Neste estudo analítico transversal, 110 indivíduos com DM2 e 110 controles saudáveis foram selecionados por amostragem de conveniência. Foram avaliados os fatores metabólicos, incluindo índice aterogênico plasmático, estado glicêmico, perfil lipídico, pressão arterial, índices renais, índices antropométricos novos [índice de volume abdominal (AVI), índice de formato corporal (ABSI), produto de acumulação lipídica (LAP), índice de adiposidade corporal (BAI) e índice de conicidade (CI)] e índices antropométricos antigos [peso, índice de massa corporal (IMC), circunferência de cintura e quadril]. Resultados Foi observada uma correlação positiva significativa de AVI, LAP e BAI com glicemia de jejum e hemoglobina glicada no grupo DM2 (p para todos < 0,001). A odds ratio (OR) do grupo DM2 foi significativamente elevada com aumento de IMC [OR: 1,30, intervalo de confiança (IC) de 95%: 1,20-1,42], LAP (OR: 1,20, IC95%: 1,13-1,27) e BAI (OR: 1,32, IC95%: 1,21-1,43). Os índices AVI (OR: 1,90, IC95%: 1,57-2,29), LAP (OR: 1,19, IC95%: 1,13-1,27), BAI (OR: 1,19, IC95%: 1,12-1,26), WC (OR: 1,29, IC95%: 1,18-1,42) e HC (OR: 1,07, IC95%: 1,01-1,14) aumentaram significativamente o risco de síndrome metabólica. Conclusões Foi reconhecida uma associação entre índices de obesidade e diabetes. Esses índices podem ser usados na prática clínica para avaliação e controle do DM2.