Low-Fat Dietary Pattern and Risk of Cardiovascular Disease

Howard, Barbara V.; Horn, Linda Van; Hsia, Judith; Manson, JoAnn E.; Stefanick, Marcia L.; Wassertheil‐Smoller, Sylvia; Kuller, Lewis H.; LaCroix, Andrea Z.; Langer, Róbert; Lasser, Norman L.; Lewis, Cora E.; Limacher, Marian C.; Margolis, Karen L.; Mysiw, W. Jerry; Ockene, Judith K.; Parker, Lawrence N.; Perri, Michael G.; Phillips, Lawrence S.; Prentice, Ross L.; Robbins, John A.; Rossouw, Jacques E.; Sarto, Gloria E.; Schatz, Irwin J.; Snetselaar, Linda; Stevens, Victor J.; Tinker, Lesley F.; Trevisan, Maurizio; Vitolins, Mara Z.; Anderson, Garnet L.; Assaf, Annlouise R.; Bassford, Tamsen; Beresford, Shirley A.A.; Black, Henry R.; Brunner, Robert L.; Brzyski, Robert G.; Caan, Bette J.; Chlebowski, Rowan T.; Gass, Margery; Granek, Iris A.; Greenland, Philip; Hays, J. Ray; Heber, David; Heiss, Gerardo; Hendrix, Susan L.; Hubbell, F. Allan; Johnson, Karen C.; Kotchen, Jane Morley

doi:10.1001/jama.295.6.655

Cited by 932 publications

(219 citation statements)

References 41 publications

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“…Adherence to a Mediterranean diet (which is more prevalent in southern Italy) has been convincingly associated with a reduction in cardiovascular risk (37,38). Postmenopausal women may be inherently more resistant to a diet-related risk reduction, as suggested by a recent study (39). Interactions among risk factors may be distinct in men and women such as smoking causing a higher risk in men or menopause doing the same with dyslipidemia in women.…”

Section: Avogaro and Associatesmentioning

confidence: 99%

Incidence of Coronary Heart Disease in Type 2 Diabetic Men and Women

Avogaro

Giorda²,

Maggini³

et al. 2007

Diabetes Care

151

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OBJECTIVE -Cardiovascular disease (CVD) is the main cause of morbidity/mortality in diabetes. We set forth to determine incidence and identify predictors (including microvascular complications and treatment) of first coronary heart disease (CHD) event in CVD-free type 2 diabetic patients. RESEARCH DESIGN AND METHODS-A cohort of 6,032 women and 5,612 men, sampled from a nationwide network of hospital-based diabetes clinics, was followed up for 4 years. Baseline assessment included retinopathy, nephropathy, and foot ulcers. First CHD events (myocardial infarction, coronary artery bypass grafting, percutaneous transluminal coronary angioplasty, and electrocardiogram-proven angina) were analyzed for 29,069 person-years.RESULTS -The age-standardized incidence rate (per 1,000 person-years) of first CHD event (n ϭ 881) was 28.8 (95% CI 5.4 -32.2) in men and 23.3 (20.2-26.4) in women. Major CHD (myocardial infarction, coronary artery bypass grafting, and percutaneous transluminal coronary angioplasty) was less frequent in women (5.8 [4.3-7.2]) than in men (13.1 [10.9 -15.4]; a sex ratio of 0.5 [0.4 -0.6]). Incidence rates of all outcomes were higher in patients with microvascular complications (for major CHD, age-adjusted rate ratios were 1.6 [1.2-2.21] in men and 1.5 [1.0 -2.2] in women). By multivariate Cox analysis, age and diabetes duration were risk predictors common in both sexes. In men, glycemic control and treated hypertension were additional independent risk factors, but residing in the south was associated with a significant 29% risk reduction. In women, higher triglycerides/lower HDL cholesterol and microvascular complications were independent risk factors.CONCLUSIONS -In CVD-free patients with type 2 diabetes, risk of first CHD event depends on sex, geographic location, and presence of microvascular disease. Hyperglycemia and hypertension, particularly in men, and diabetic dyslipidemia, especially in women, are risk factors amenable to more aggressive treatment. Diabetes Care 30:1241-1247, 2007D iabetes is estimated to be responsible for 5.2% of all deaths (1). Since the Framingham Study (2), epidemiology has consistently shown that diabetes confers an increased risk for coronary heart disease (CHD) and cardiac mortality (3-6). Salient features of this association are the following: 1) relative risk of CHD (7) and fatal CHD (8) is higher in diabetic women than in diabetic men, 2) classical and diabetes-related risk factors both contribute to total CHD risk (6), and 3) insulin treatment may be associated with a worse cardiovascular prognosis (9,10). The reasons for the excessive relative CHD risk in diabetic women compared with diabetic men are not completely understood. In the Strong Heart Study (11), the greater risk for cardiovascular disease (CVD) in women was explained in part by an apparent larger negative impact of diabetes on CVD risk factors. With regard to diabetes-related risk, the World Health Organization (WHO) multinational study found that in type 2 diabetic patients, proteinuria and retinopat...

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Section: Avogaro and Associatesmentioning

confidence: 99%

Incidence of Coronary Heart Disease in Type 2 Diabetic Men and Women

Avogaro

Giorda²,

Maggini³

et al. 2007

Diabetes Care

151

View full text Add to dashboard Cite

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“…It turned out this was based on biased estimates. When randomized data from a large study was released in 2006, this result was seriously weakened (Prentice et al, 2006;Beresford et al, 2006;Howard et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Unobservable Selection and Coefficient Stability: Theory and Validation

Oster¹

2013

220

278

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Inferring causal treatment effects in the presence of possible omitted variable bias is as well-known problem. Altonji, Elder and Taber (2005) suggest that the degree of selection on observable variables might be used as a guide to the remaining bias in controlled regressions. I expand on their setup and demonstrate how, with an equal selection assumption, a causal effect can be recovered using coefficients, R-squared values from controlled and uncontrolled regressions and an estimate of the iid noise in the outcome. I discuss the relationship between this technique and the heuristic procedure of adding sequential controls until coefficients stabilize. I consider two validation exercises which explore whether coefficients adjusted in this way are closer to the truth. First, I estimate the impact of early life and prenatal influences on child IQ. Simple controlled regressions give misleading estimates; the bias-adjusted estimates are significantly better. However, I show that the progressive adding of controls in this setting is not effective. Second, I match observational and randomized trial data for 31 treatment-outcome pairs in three public health settings. I estimate a best-fit degree of adjustment across all settings (the free parameter is the amount of iid noise in the outcome). I show that the bias-adjusted coefficients preform much better than simple controlled coefficients; the total error reduction is 30% and a number of false-positive results are rejected without significant loss in true-positive results. The magnitude of the best-fit adjustment suggests adjusting the controlled coefficient by approximately the same amount as the movement between uncontrolled and controlled coefficients.

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“…Despite many major advances, the public's perception is one of conflicting and confusing nutrition and health messages, which may be further worsened by unsubstantiated health claims for functional foods and supplements (e.g. [29,30]), and of premature claims for personalised health [31,33]. Against this background of a complex and rapidly growing, but still immature science base, many nutrition scientists feel unable to meet expectations for clear, evidence-based dietary recommendations for health promotion that the healthcare, functional foods and supplement providers, as well as the public, clearly require.…”

Section: Introduction: the Nutrition And Health Equationmentioning

confidence: 99%

The challenges for molecular nutrition research 1: linking genotype to healthy nutrition

Williams¹,

Ordovas

Lairon

et al. 2008

Genes Nutr

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Nutrition science finds itself at a major crossroad. On the one hand we can continue the current path, which has resulted in some substantial advances, but also many conflicting messages which impair the trust of the general population, especially those who are motivated to improve their health through diet. The other road is uncharted and is being built over the many exciting new developments in life sciences. This new era of nutrition recognizes the complex relation between the health of the individual, its genome, and the life-long dietary exposure, and has lead to the realisation that nutrition is essentially a gene-environment interaction science. This review on the relation between genotype, diet and health is the first of a series dealing with the major challenges in molecular nutrition, analyzing the foundations of nutrition research. With the unravelling of the human genome and the linking of its variability to a multitude of phenotypes from ''healthy'' to an enormously complex range of predispositions, the dietary modulation of these propensities has become an area of active research. Classical genetic approaches applied so far in medical genetics have steered away from incorporating dietary effects in their models and paradoxically, most genetic studies analyzing diet-associated phenotypes and diseases simply ignore diet. Yet, a modest but increasing number of studies are accounting for diet as a modulator of genetic associations. These range from observational cohorts to intervention studies with prospectively selected genotypes. New statistical and All authors are member of The European Nutrigenomics Organisation (http://www.nugo.org). bioinformatics approaches are becoming available to aid in design and evaluation of these studies. This review discusses the various approaches used and provides concrete recommendations for future research. C. M. Williams (&)Hugh

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Low-Fat Dietary Pattern and Risk of Cardiovascular Disease

Abstract: ClinicalTrials.gov Identifier: NCT00000611.

Cited by 932 publications

References 41 publications

Incidence of Coronary Heart Disease in Type 2 Diabetic Men and Women

Incidence of Coronary Heart Disease in Type 2 Diabetic Men and Women

Unobservable Selection and Coefficient Stability: Theory and Validation

The challenges for molecular nutrition research 1: linking genotype to healthy nutrition

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