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      Red meat consumption and risk of type 2 diabetes: 3 cohorts of US adults and an updated meta-analysis.

      The American Journal of Clinical Nutrition

      Adult, Aged, Cohort Studies, Diabetes Mellitus, Type 2, epidemiology, etiology, prevention & control, Diet, adverse effects, Female, Follow-Up Studies, Food Handling, Humans, Incidence, Male, Meat, Middle Aged, Prospective Studies, Questionnaires, Reproducibility of Results, Risk, United States

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          Abstract

          The relation between consumption of different types of red meats and risk of type 2 diabetes (T2D) remains uncertain. We evaluated the association between unprocessed and processed red meat consumption and incident T2D in US adults. We followed 37,083 men in the Health Professionals Follow-Up Study (1986-2006), 79,570 women in the Nurses' Health Study I (1980-2008), and 87,504 women in the Nurses' Health Study II (1991-2005). Diet was assessed by validated food-frequency questionnaires, and data were updated every 4 y. Incident T2D was confirmed by a validated supplementary questionnaire. During 4,033,322 person-years of follow-up, we documented 13,759 incident T2D cases. After adjustment for age, BMI, and other lifestyle and dietary risk factors, both unprocessed and processed red meat intakes were positively associated with T2D risk in each cohort (all P-trend <0.001). The pooled HRs (95% CIs) for a one serving/d increase in unprocessed, processed, and total red meat consumption were 1.12 (1.08, 1.16), 1.32 (1.25, 1.40), and 1.14 (1.10, 1.18), respectively. The results were confirmed by a meta-analysis (442,101 participants and 28,228 diabetes cases): the RRs (95% CIs) were 1.19 (1.04, 1.37) and 1.51 (1.25, 1.83) for 100 g unprocessed red meat/d and for 50 g processed red meat/d, respectively. We estimated that substitutions of one serving of nuts, low-fat dairy, and whole grains per day for one serving of red meat per day were associated with a 16-35% lower risk of T2D. Our results suggest that red meat consumption, particularly processed red meat, is associated with an increased risk of T2D.

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          Most cited references 25

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          Food-based validation of a dietary questionnaire: the effects of week-to-week variation in food consumption.

          The reproducibility and validity of responses for 55 specific foods and beverages on a self-administered food frequency questionnaire were evaluated. One hundred and seventy three women from the Nurses' Health Study completed the questionnaire twice approximately 12 months apart and also recorded their food consumption for seven consecutive days, four times during the one-year interval. For the 55 foods, the mean of correlation coefficients between frequencies of intake for first versus second questionnaire was 0.57 (range = 0.24 for fruit punch to 0.93 for beer). The mean of correlation coefficients between the dietary records and first questionnaire was 0.44 (range = 0.09 for yellow squash to 0.83 for beer and tea) and between the dietary records and the second questionnaire was 0.52 (range = 0.08 for spinach to 0.90 for tea). Ratios of within- to between-person variance for the 55 foods were computed using the mean four one-week dietary records for each person as replicate measurements. For most foods this ratio was greater than 1.0 (geometric mean of ratios = 1.88), ranging from 0.25 (skimmed milk) to 14.76 (spinach). Correlation coefficients comparing questionnaire and dietary record for the 55 foods were corrected for the within-person variation (mean corrected value = 0.55 for dietary record versus first questionnaire and 0.66 versus the second). Mean daily amounts of each food calculated by the questionnaire and by the dietary record were also compared; the observed differences suggested that responses to the questionnaire tended to over-represent socially desirable foods. This analysis documents the validity and reproducibility of the questionnaire for measuring specific foods and beverages, as well as the large within-person variation for food intake measured by dietary records. Differences in the degree of validity for specific foods revealed in this type of analysis can be useful in improving questionnaire design and in interpreting findings from epidemiological studies that use the instrument.
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            Dietary fat and coronary heart disease: a comparison of approaches for adjusting for total energy intake and modeling repeated dietary measurements.

            Previous cohort studies of fat intake and risk of coronary heart disease (CHD) have been inconsistent, probably due in part to methodological differences and various limitations, including inadequate dietary assessment and incomplete adjustment for total energy intake. The authors analyzed repeated assessment of diet from the Nurses' Health Study to examine the associations between intakes of four major types of fat (saturated, monounsaturated, polyunsaturated, and trans fats) and risk of CHD during 14 years of follow-up (1980-1994) by using alternative methods for energy adjustment. In particular, the authors compared four risk models for energy adjustment: the standard multivariate model, the energy-partition model, the nutrient residual model, and the multivariate nutrient density model. Within each model, the authors compared four different approaches for analyzing repeated dietary measurements: baseline diet only, the most recent diet, and two different algorithms for calculating cumulative average diets. The substantive results were consistent across all models; that is, higher intakes of saturated and trans fats were associated with increased risk of CHD, while higher intakes of monounsaturated and polyunsaturated fats were associated with reduced risk. When nutrients were considered as continuous variables, the four energy-adjustment methods yielded similar associationS. However, the interpretation of the relative risks differed across models. In addition, within each model, the methods using the cumulative averages in general yielded stronger associations than did those using either only baseline diet or the most recent diet. When the nutrients were categorized according to quintiles, the residual and the nutrient density models, which gave similar results, yielded statistically more significant tests for linear trend than did the standard and the partition models.
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              Major dietary protein sources and risk of coronary heart disease in women.

              With the exception of fish, few major dietary protein sources have been studied in relation to the development of coronary heart disease (CHD). Our objective was to examine the relation between foods that are major dietary protein sources and incident CHD. We prospectively followed 84,136 women aged 30 to 55 years in the Nurses' Health Study with no known cancer, diabetes mellitus, angina, myocardial infarction, stroke, or other cardiovascular disease. Diet was assessed by a standardized and validated questionnaire and updated every 4 years. During 26 years of follow-up, we documented 2210 incident nonfatal infarctions and 952 deaths from CHD. In multivariable analyses including age, smoking, and other risk factors, higher intakes of red meat, red meat excluding processed meat, and high-fat dairy were significantly associated with elevated risk of CHD. Higher intakes of poultry, fish, and nuts were significantly associated with lower risk. In a model controlling statistically for energy intake, 1 serving per day of nuts was associated with a 30% (95% confidence interval, 17% to 42%) lower risk of CHD compared with 1 serving per day of red meat. Similarly, compared with 1 serving per day of red meat, a lower risk was associated with 1 serving per day of low-fat dairy (13%; 95% confidence interval, 6% to 19%), poultry (19%; 95% confidence interval, 3% to 33%), and fish (24%; 95% confidence interval, 6% to 39%). These data suggest that high red meat intake increases risk of CHD and that CHD risk may be reduced importantly by shifting sources of protein in the US diet.
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                Author and article information

                Journal
                21831992
                3173026
                10.3945/ajcn.111.018978

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