High Dietary Magnesium Intake Is Associated with Low Insulin Resistance in the Newfoundland Population
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{"title"=>"High Dietary Magnesium Intake Is Associated with Low Insulin Resistance in the Newfoundland Population", "type"=>"journal", "authors"=>[{"first_name"=>"Farrell", "last_name"=>"Cahill", "scopus_author_id"=>"6603233823"}, {"first_name"=>"Mariam", "last_name"=>"Shahidi", "scopus_author_id"=>"55615588700"}, {"first_name"=>"Jennifer", "last_name"=>"Shea", "scopus_author_id"=>"23006014000"}, {"first_name"=>"Danny", "last_name"=>"Wadden", "scopus_author_id"=>"55366150700"}, {"first_name"=>"Wayne", "last_name"=>"Gulliver", "scopus_author_id"=>"6701758508"}, {"first_name"=>"Edward", "last_name"=>"Randell", "scopus_author_id"=>"6602838078"}, {"first_name"=>"Sudesh", "last_name"=>"Vasdev", "scopus_author_id"=>"7007084673"}, {"first_name"=>"Guang", "last_name"=>"Sun", "scopus_author_id"=>"8689399700"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-84874637531", "doi"=>"10.1371/journal.pone.0058278", "sgr"=>"84874637531", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"23472169", "issn"=>"19326203", "pui"=>"368465607"}, "id"=>"ec202904-4791-3589-9752-16d055c6ef06", "abstract"=>"BACKGROUND: Magnesium plays a role in glucose and insulin homeostasis and evidence suggests that magnesium intake is associated with insulin resistance (IR). However, data is inconsistent and most studies have not adequately controlled for critical confounding factors. OBJECTIVE: The study investigated the association between magnesium intake and IR in normal-weight (NW), overweight (OW) and obese (OB) along with pre- and post- menopausal women. DESIGN: A total of 2295 subjects (590 men and 1705 women) were recruited from the CODING study. Dietary magnesium intake was computed from the Willett Food Frequency Questionnaire (FFQ). Adiposity (NW, OW and OB) was classified by body fat percentage (%BF) measured by Dual-energy X-ray absorptiometry according to the Bray criteria. Multiple regression analyses were used to test adiposity-specific associations of dietary magnesium intake on insulin resistance adjusting for caloric intake, physical activity, medication use and menopausal status. RESULTS: Subjects with the highest intakes of dietary magnesium had the lowest levels of circulating insulin, HOMA-IR, and HOMA-ß and subjects with the lowest intake of dietary magnesium had the highest levels of these measures, suggesting a dose effect. Multiple regression analysis revealed a strong inverse association between dietary magnesium with IR. In addition, adiposity and menopausal status were found to be critical factors revealing that the association between dietary magnesium and IR was stronger in OW and OB along with Pre-menopausal women. CONCLUSION: The results of this study indicate that higher dietary magnesium intake is strongly associated with the attenuation of insulin resistance and is more beneficial for overweight and obese individuals in the general population and pre-menopausal women. Moreover, the inverse correlation between insulin resistance and dietary magnesium intake is stronger when adjusting for %BF than BMI.", "link"=>"http://www.mendeley.com/research/high-dietary-magnesium-intake-associated-low-insulin-resistance-newfoundland-population", "reader_count"=>55, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>1, "Researcher"=>5, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>3, "Student > Postgraduate"=>4, "Student > Master"=>11, "Other"=>9, "Student > Bachelor"=>17, "Lecturer"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>1, "Researcher"=>5, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>3, "Student > Postgraduate"=>4, "Student > Master"=>11, "Other"=>9, "Student > Bachelor"=>17, "Lecturer"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>1, "Biochemistry, Genetics and Molecular Biology"=>6, "Nursing and Health Professions"=>5, "Materials Science"=>1, "Medicine and Dentistry"=>27, "Agricultural and Biological Sciences"=>13, "Psychology"=>1, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Materials Science"=>{"Materials Science"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>27}, "Psychology"=>{"Psychology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>13}, "Computer Science"=>{"Computer Science"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>5}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>6}, "Unspecified"=>{"Unspecified"=>1}}, "reader_count_by_country"=>{"Netherlands"=>1, "South Korea"=>1, "United States"=>2, "Australia"=>1}, "group_count"=>3}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1011744"], "description"=>"1<p>Data presented as mean ± SD. Homeostasis model assessment of insulin resistance (HOMA-IR) and β-cell function (HOMA-β). Gender differences were assessed with a one-way ANOVA. Subjects were also stratified into normal-weight, overweight and obese based upon %BF according to the Bray criteria (25). Adiposity differences were assessed with an ANCOVA controlling for caloric intake, physical activity, medication use, and menopause. <sup>2</sup>Significantly greater for men compared to women. <sup>3</sup>Significantly greater for women compared to men. <sup>4</sup>Statistical significance for one-way ANOVA and ANCOVA were set to p<0.05 (IBM SPSS Statistics 19).</p>", "links"=>[], "tags"=>["dietary", "intake", "obese"], "article_id"=>672149, "categories"=>["Chemistry", "Physiology", "Biotechnology", "Immunology"], "users"=>["Farrell Cahill", "Mariam Shahidi", "Jennifer Shea", "Danny Wadden", "Wayne Gulliver", "Edward Randell", "Sudesh Vasdev", "Guang Sun"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0058278.t001", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Physical_Biochemical_and_Dietary_Intake_Characteristics_of_Normal_weight_Overweight_and_Obese_Participants_/672149", "title"=>"Physical, Biochemical, and Dietary Intake Characteristics of Normal-weight, Overweight, and Obese Participants.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-05 00:35:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1011701"], "description"=>"1<p>Data presented as mean ± SD. Homeostasis model assessment of insulin resistance (HOMA-IR) and β-cell function (HOMA-β).</p>2<p>Subjects were stratified into a tertile (low, medium and high) based upon magnesium intake (mg/day).</p>3<p>Magnesium intake group differences were assessed with an ANCOVA controlling for caloric intake, physical activity, medication use, menopause and %BF.</p>4<p>Statistical significance for one-way ANCOVA was set to p<0.05 (IBM SPSS Statistics 19).</p>", "links"=>[], "tags"=>["dietary", "intake", "magnesium"], "article_id"=>672110, "categories"=>["Chemistry", "Physiology", "Biotechnology", "Immunology"], "users"=>["Farrell Cahill", "Mariam Shahidi", "Jennifer Shea", "Danny Wadden", "Wayne Gulliver", "Edward Randell", "Sudesh Vasdev", "Guang Sun"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0058278.t002", "stats"=>{"downloads"=>4, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Physical_Biochemical_and_Dietary_Intake_Characteristics_According_to_Magnesium_Intake_/672110", "title"=>"Physical, Biochemical, and Dietary Intake Characteristics According to Magnesium Intake.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-05 00:35:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1011721"], "description"=>"1<p>Regression model adjusted for caloric intake, physical activity, medication use and menopausal status.</p>2<p>β = Unstandardized Beta (standard error), β* = Standardized Beta (standard error), Magnesium intake (g/day/kg).</p>3<p>Normal-weight, overweight and obese groups are based upon %BF according to the Bray criteria (25).</p>4<p>Magnesium intake (Pre-Menopause 360.63±209.8 mg/day, Post-Menopause 353.82±192.9 mg/day) (Entire cohort, Normal-weight, Overweight, & Obese – See Table.1).</p>5<p>Statistical significance was set to p<0.05 (IBM SPSS Statistics 19).</p>", "links"=>[], "tags"=>["magnesium", "intake", "insulin"], "article_id"=>672131, "categories"=>["Chemistry", "Physiology", "Biotechnology", "Immunology"], "users"=>["Farrell Cahill", "Mariam Shahidi", "Jennifer Shea", "Danny Wadden", "Wayne Gulliver", "Edward Randell", "Sudesh Vasdev", "Guang Sun"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0058278.t003", "stats"=>{"downloads"=>1, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Regression_Models_of_Magnesium_Intake_on_Insulin_Resistance_/672131", "title"=>"Regression Models of Magnesium Intake on Insulin Resistance.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-05 00:35:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/1011681"], "description"=>"1<p>Regression model adjusted for caloric intake, physical activity, medication use and menopausal status.Subjects were also stratified into a tertiles(Low, Medium and High) based upon %BF and BMI.</p>2<p>β = Unstandardized Beta (standard error), β* = Standardized Beta (standard error), Magnesium intake (g/day/kg).</p>3<p>Magnesium intake (Low BMI 409.78±243.5 mg/day, Medium BMI 353.24±180.9 mg/day, High BMI 342.76±196.1 mg/day) (Low %BF 387.5±230.3 mg/day, Medium %BF 360.54±187.5 mg/day, High %BF 357.68±210.7 mg/day).</p>4<p>Statistical significance was set to p<0.05 (IBM SPSS Statistics 19).</p>", "links"=>[], "tags"=>["magnesium", "intake", "insulin"], "article_id"=>672087, "categories"=>["Chemistry", "Physiology", "Biotechnology", "Immunology"], "users"=>["Farrell Cahill", "Mariam Shahidi", "Jennifer Shea", "Danny Wadden", "Wayne Gulliver", "Edward Randell", "Sudesh Vasdev", "Guang Sun"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0058278.t004", "stats"=>{"downloads"=>4, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Regression_Models_of_Magnesium_Intake_on_Insulin_Resistance_based_upon_BF_and_BMI_/672087", "title"=>"Regression Models of Magnesium Intake on Insulin Resistance based upon %BF and BMI.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-05 00:34:47"}

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