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Prospective Study of Nut Consumption and Incidence of Metabolic Syndrome: Tehran Lipid and Glucose Study.

ABSTRACT: This study aimed to assess the association of various types of nut per se, and total nut consumption with the incidence of metabolic syndrome (MetS). A 6.2 ± 0.7-year population-based prospective study was conducted among 1265 adults, aged 19-74 years, participants of the Tehran Lipid and Glucose Study. A 168-item semi-quantitative food frequency questionnaire was used to collect information on nut consumption. MetS was defined according to the Joint Interim Statement guidelines and 276 new cases of MetS were identified. Median ± interquartile range of nut consumption was 2.08 (0.88-5.68) servings/week. After adjusting for family history of diabetes, age, gender, smoking, physical activity, fasting serum glucose at baseline, serum high density lipoprotein cholesterol (HDL-C) at baseline, energy intake, fiber, macronutrients, cholesterol intake, fruit, vegetables, dairy products and body mass index (BMI), a statistically significant decrease was observed in MetS in the third (?5 servings/week) tertile of nuts (odds ratio: 0.68, 95% CI: 0.44-0.91, p trend: 0.03) compared with the lowest (?1 serving/week). Walnut consumption showed a significant, inverse association with MetS risk; associations for other nut varieties were not significant. For each additional serving/week of walnuts consumed, incidence of MetS decreased by 3% (ORs: 0.97 CI: 0.93-0.99), after adjusting for confounding factors. Total nut consumption, especially walnuts, reduces the risk of MetS.

SUBMITTER: Hosseinpour-Niazi S

PROVIDER: S-EPMC5691673 | biostudies-other | 2017 Sep

REPOSITORIES: biostudies-other

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Prospective Study of Nut Consumption and Incidence of Metabolic Syndrome: Tehran Lipid and Glucose Study.

Hosseinpour-Niazi Somayeh S Hosseini Shabnam S Mirmiran Parvin P Azizi Fereidoun F

Nutrients 20170923 10

This study aimed to assess the association of various types of nut per se, and total nut consumption with the incidence of metabolic syndrome (MetS). A 6.2 ± 0.7-year population-based prospective study was conducted among 1265 adults, aged 19-74 years, participants of the Tehran Lipid and Glucose Study. A 168-item semi-quantitative food frequency questionnaire was used to collect information on nut consumption. MetS was defined according to the Joint Interim Statement guidelines and 276 new case ...[more]

PMID: 28946607

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Project description:BackgroundNon-participation in cohort studies, if associated with both the exposure and occurrence of the event, can introduce bias in the estimates of interest. This study aims to identify factors associated with follow-up participation in Tehran Lipid and Glucose Study, a large-scale community-based prospective study in West Asia.MethodsA sample of 10,368 adults from TLGS was included in the analysis. All analyses were split according to sex and age groups (20-39, 40-59, and 60 years). The associations between socio-demographic, health, and lifestyle factors with response rate were identified using the Generalized Estimating Equations model.ResultsOver the median of 15.7 years of follow up the response rate was 64.5%. The highest response rate was observed in those aged 40-59 years for both sexes. Current smokers had lower odds of response in both sexes for all age groups, ranging from 0.51 to 0.74, p < 0.01. In young adults, being single (OR = 0.79, OR = 0.57, p ≤ 0.01, respectively for men and women) and unemployed (OR = 0.73, OR = 0.76, p ≤ 0.01, respectively for men and women) in both sexes, high physical activity in men (OR = 0.77, p < 0.01), high education (OR = 0.75, p = 0.02) and obesity (OR = 0.85, p = 0.05) in women were associated with lower response rate. For the middle-aged group, diabetes in men (OR = 0.77, p = 0.05) and hypertension (OR = 0.84, p = 0.05), and having a history of cancer (OR = 0.43, p = 0.03) in women were factors associated with lower response rates. Finally, interventions for both sexes (OR = 0.75, OR = 0.77, p ≤ 0.05, respectively for men and women) and being divorced/widow in women (OR = 0.77, p = 0.05) were the factors associated with the lower response rate in the elderly.ConclusionsLong-term participation was influenced by socio-demographic, health, and lifestyle factors in different sex- and age-specific patterns in TLGS. Recruitment strategies targeting these factors may improve participant follow-up in longitudinal studies.

Project description:OBJECTIVES:Diet and nutrition might play an important role in the aetiology of metabolic syndrome (MetS). Most studies that examine the effects of food intake on MetS have used conventional statistical analyses which usually investigate only a limited number of food items and are subject to sparse data bias. This study was undertaken with the goal of investigating the concurrent effect of numerous food items and related nutrients on the incidence of MetS using Bayesian multilevel modelling which can control for sparse data bias. DESIGN:Prospective cohort study. SETTING:This prospective study was a subcohort of the Tehran Lipid and Glucose Study. We analysed dietary intake as well as pertinent covariates for cohort members in the fourth (2008-2011) and fifth (2011-2014) follow-up examinations. We fitted Bayesian multilevel model and compared the results with two logistic regression models: (1) full model which included all variables and (2) reduced model through backward selection of dietary variables. PARTICIPANTS:3616 healthy Iranian adults, aged ?20 years. PRIMARY AND SECONDARY OUTCOME MEASURES:Incident cases of MetS. RESULTS:Bayesian multilevel approach produced results that were more precise and biologically plausible compared with conventional logistic regression models. The OR and 95% confidence limits for the effects of the four foods comparing the Bayesian multilevel with the full conventional model were as follows: (1) noodle soup (1.20 (0.67 to 2.14) vs 1.91 (0.65 to 5.64)), (2) beans (0.96 (0.5 to 1.85) vs 0.55 (0.03 to 11.41)), (3) turnip (1.23 (0.68 to 2.23) vs 2.48 (0.82 to 7.52)) and (4) eggplant (1.01 (0.51 to 2.00) vs 1?09?396 (0.152×10-6 to 768×1012)). For most food items, the Bayesian multilevel analysis gave narrower confidence limits than both logistic regression models, and hence provided the highest precision. CONCLUSIONS:This study demonstrates that conventional regression methods do not perform well and might even be biased when assessing highly correlated exposures such as food items in dietary epidemiological studies. Despite the complexity of the Bayesian multilevel models and their inherent assumptions, this approach performs superior to conventional statistical models in studies that examine multiple nutritional exposures that are highly correlated.

Dataset Information

Prospective Study of Nut Consumption and Incidence of Metabolic Syndrome: Tehran Lipid and Glucose Study.

Publications

Prospective Study of Nut Consumption and Incidence of Metabolic Syndrome: Tehran Lipid and Glucose Study.

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