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503 results on '"Bhupathiraju, Shilpa N."'

101. The Mediterranean diet, plasma metabolome, and cardiovascular disease risk

Author

Li, Jun, primary, Guasch-Ferré, Marta, additional, Chung, Wonil, additional, Ruiz-Canela, Miguel, additional, Toledo, Estefanía, additional, Corella, Dolores, additional, Bhupathiraju, Shilpa N, additional, Tobias, Deirdre K, additional, Tabung, Fred K, additional, Hu, Jie, additional, Zhao, Tong, additional, Turman, Constance, additional, Feng, Yen-Chen Anne, additional, Clish, Clary B, additional, Mucci, Lorelei, additional, Eliassen, A Heather, additional, Costenbader, Karen H, additional, Karlson, Elizabeth W, additional, Wolpin, Brian M, additional, Ascherio, Alberto, additional, Rimm, Eric B, additional, Manson, JoAnn E, additional, Qi, Lu, additional, Martínez-González, Miguel Ángel, additional, Salas-Salvadó, Jordi, additional, Hu, Frank B, additional, and Liang, Liming, additional

Published
2020
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102. Metabolomic Links between Sugar-Sweetened Beverage Intake and Obesity

Author

Zhou, Bingjie, primary, Ichikawa, Reiko, additional, Parnell, Laurence D., additional, Noel, Sabrina E., additional, Zhang, Xiyuan, additional, Bhupathiraju, Shilpa N., additional, Smith, Caren E., additional, Tucker, Katherine L., additional, Ordovas, Jose M., additional, and Lai, Chao-Qiang, additional

Published
2020
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107. Abstract 52: Plasma Metabolomic Signatures of the American Heart Association Diet Score: Findings From the Boston Puerto Rican Health Study

Author

Haslam, Danielle E, primary, Li, Jun, additional, Liang, Liming, additional, Clish, Clary, additional, Lichtenstein, Alice H, additional, Lai, Chao-Qiang, additional, ORDOVAS, Jose M, additional, Manson, Joann E, additional, Wittenbecher, Clemens, additional, Hu, Frank B, additional, Qi, Qibin, additional, Tucker, Katherine L, additional, and Bhupathiraju, Shilpa N, additional

Published
2020
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109. Additive and Multiplicative Interactions Between Genetic Risk Score and Family History and Lifestyle in Relation to Risk of Type 2 Diabetes

Author

Ding, Ming, primary, Ahmad, Shafqat, additional, Qi, Lu, additional, Hu, Yang, additional, Bhupathiraju, Shilpa N, additional, Guasch-Ferré, Marta, additional, Jensen, Majken K, additional, Chavarro, Jorge E, additional, Ridker, Paul M, additional, Willett, Walter C, additional, Chasman, Daniel I, additional, Hu, Frank B, additional, and Kraft, Peter, additional

Published
2019
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110. Changes in Consumption of Sugary Beverages and Artificially Sweetened Beverages and Subsequent Risk of Type 2 Diabetes: Results From Three Large Prospective U.S. Cohorts of Women and Men

Author

Drouin-Chartier, Jean-Philippe, primary, Zheng, Yan, additional, Li, Yanping, additional, Malik, Vasanti, additional, Pan, An, additional, Bhupathiraju, Shilpa N., additional, Tobias, Deirdre K., additional, Manson, JoAnn E., additional, Willett, Walter C., additional, and Hu, Frank B., additional

Published
2019
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112. Plant-Based Dietary Patterns and Incidence of Type 2 Diabetes in US Men and Women: Results from Three Prospective Cohort Studies

Author

Satija, Ambika, Bhupathiraju, Shilpa N., Rimm, Eric B., Spiegelman, Donna, Chiuve, Stephanie E., Borgi, Lea, Willett, Walter C., Manson, JoAnn E., Sun, Qi, and Hu, Frank B.

Subjects
Type 2 diabetes -- Risk factors -- Research, Americans -- Health aspects -- Food and nutrition, Vegetarianism -- Health aspects -- Research, Biological sciences
Abstract

Background Plant-based diets have been recommended to reduce the risk of type 2 diabetes (T2D). However, not all plant foods are necessarily beneficial. We examined the association of an overall plant-based diet and hypothesized healthful and unhealthful versions of a plant-based diet with T2D incidence in three prospective cohort studies in the US. Methods and Findings We included 69,949 women from the Nurses' Health Study (1984-2012), 90,239 women from the Nurses' Health Study 2 (1991-2011), and 40,539 men from the Health Professionals Follow-Up Study (1986-2010), free of chronic diseases at baseline. Dietary data were collected every 2-4 y using a semi-quantitative food frequency questionnaire. Using these data, we created an overall plant-based diet index (PDI), where plant foods received positive scores, while animal foods (animal fats, dairy, eggs, fish/seafood, poultry/red meat, miscellaneous animal-based foods) received reverse scores. We also created a healthful plant-based diet index (hPDI), where healthy plant foods (whole grains, fruits, vegetables, nuts, legumes, vegetable oils, tea/coffee) received positive scores, while less healthy plant foods (fruit juices, sweetened beverages, refined grains, potatoes, sweets/desserts) and animal foods received reverse scores. Lastly, we created an unhealthful plant-based diet index (uPDI) by assigning positive scores to less healthy plant foods and reverse scores to healthy plant foods and animal foods. We documented 16,162 incident T2D cases during 4,102,369 person-years of follow-up. In pooled multivariable-adjusted analysis, both PDI and hPDI were inversely associated with T2D (PDI: hazard ratio [HR] for extreme deciles 0.51, 95% CI 0.47-0.55, p trend < 0.001; hPDI: HR for extreme deciles 0.55, 95% CI 0.51-0.59, p trend < 0.001). The association of T2D with PDI was considerably attenuated when we additionally adjusted for body mass index (BMI) categories (HR 0.80, 95% CI 0.74-0.87, p trend < 0.001), while that with hPDI remained largely unchanged (HR 0.66, 95% CI 0.61-0.72, p trend < 0.001). uPDI was positively associated with T2D even after BMI adjustment (HR for extreme deciles 1.16, 95% CI 1.08-1.25, p trend < 0.001). Limitations of the study include self-reported diet assessment, with the possibility of measurement error, and the potential for residual or unmeasured confounding given the observational nature of the study design. Conclusions Our study suggests that plant-based diets, especially when rich in high-quality plant foods, are associated with substantially lower risk of developing T2D. This supports current recommendations to shift to diets rich in healthy plant foods, with lower intake of less healthy plant and animal foods., Author(s): Ambika Satija 1,2,*, Shilpa N. Bhupathiraju 1, Eric B. Rimm 1,2,3, Donna Spiegelman 1,2,3,4,5, Stephanie E. Chiuve 1,2,6, Lea Borgi 7, Walter C. Willett 1,2,3, JoAnn E. Manson 2,6,8, [...]

Published
2016
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118. Body-mass index and all-cause mortality - Authors' reply

Author

Di Angelantonio, Emanuele, Bhupathiraju, Shilpa N, Hu, Frank B, Danesh, John, Peto, Richard, Lewington, Sarah, Global BMI Mortality Collaboration, Di Angelantonio, Emanuele [0000-0001-8776-6719], Danesh, John [0000-0003-1158-6791], and Apollo - University of Cambridge Repository

Subjects
Humans, Obesity, Body Mass Index
Published
2017
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121. Duration of obesity and overweight and risk of type 2 diabetes among US women

Author

Hu, Yang, Bhupathiraju, Shilpa N, de Koning, Lawrence, and Hu, Frank B

Subjects
Adult, Time Factors, Body Weight, nutritional and metabolic diseases, Nurses, Type 2 diabetes, Obesity duration, Middle Aged, Overweight, Article, United States, Body Mass Index, Diabetes Mellitus, Type 2, Risk Factors, Disease Progression, Humans, Female, Obesity, Overweight duration, Proportional Hazards Models
Abstract

Objective The purpose of this study was to examine the association between duration of adiposity and risk of type 2 diabetes (T2D) in US women. Methods We prospectively followed 61,821 participants from the Nurses' Health Study (1984-2008) and 63,653 participants from Nurses' Health Study II (1991-2011). Participants were considered overweight (BMI 25-30 kg/m2) or obese (BMI >= 30 kg/m2) if their BMI was above the cutoffs for two successive assessments. We used time-dependent Cox proportional hazard models to assess associations between excess weight duration and T2D risk. Results In pooled multivariable analyses of the two cohorts, each two extra years of being overweight was associated with 9% (RR=1.09, 95% CI 1.08 - 1.09) increased risk of developing T2D. For each 2-year increment in obesity duration, the risk of T2D was increased by 14% (RR=1.14, 95% CI 1.14 - 1.15). Adjustment for current BMI greatly attenuated the association for obesity duration (RR =1.02, 95% CI 1.01 - 1.03), although the attenuation was less for overweight duration (RR =1.04, 95% CI 1.04 - 1.05). Conclusions Both overweight and obesity duration were associated with a significantly higher risk of T2D, and these associations were mainly explained by current BMI, especially for obesity duration.

Published
2014

122. Metabolite profiles of plant-based diets and cardiometabolic risk in the Mediators of Atherosclerosis in South Asians Living in America (MASALA) Study

Author

Sawicki, Caleigh M., Ren, Yin, Kanaya, Alka M., Kandula, Namratha, Gadgil, Meghana, Liang, Liming, Haslam, Danielle E., and Bhupathiraju, Shilpa N.

Abstract

Healthy plant-based diets have been associated with lower risk of type 2 diabetes (T2D). Metabolomics can be leveraged to identify potential pathways through which diet influences disease risk.

Published
2024
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123. Additive and Multiplicative Interactions Between Genetic Risk Score and Family History and Lifestyle in Relation to Risk of Type 2 Diabetes.

Author

Ding, Ming, Ahmad, Shafqat, Qi, Lu, Hu, Yang, Bhupathiraju, Shilpa N, Guasch-Ferré, Marta, Jensen, Majken K, Chavarro, Jorge E, Ridker, Paul M, Willett, Walter C, Chasman, Daniel I, Hu, Frank B, and Kraft, Peter

Subjects
CONFIDENCE intervals, GENETICS, TYPE 2 diabetes, PUBLIC health, RESEARCH, MATHEMATICAL variables, LIFESTYLES, FAMILY history (Medicine), DESCRIPTIVE statistics, DISEASE risk factors
Abstract

We examined interactions between lifestyle factors and genetic risk of type 2 diabetes (T2D-GR), captured by genetic risk score (GRS) and family history (FH). Our initial study cohort included 20,524 European-ancestry participants, of whom 1,897 developed incident T2D, in the Nurses' Health Study (1984–2016), Nurses' Health Study II (1989–2016), and Health Professionals Follow-up Study (1986–2016). The analyses were replicated in 19,183 European-ancestry controls and 2,850 incident T2D cases in the Women's Genome Health Study (1992–2016). We defined 2 categories of T2D-GR: high GRS (upper one-third) with FH and low GRS or without FH. Compared with participants with the healthiest lifestyle and low T2D-GR, the relative risk of T2D for participants with the healthiest lifestyle and high T2D-GR was 2.24 (95% confidence interval (CI): 1.76, 2.86); for participants with the least healthy lifestyle and low T2D-GR, it was 4.05 (95% CI: 3.56, 4.62); and for participants with the least healthy lifestyle and high T2D-GR, it was 8.72 (95% CI: 7.46, 10.19). We found a significant departure from an additive risk difference model in both the initial and replication cohorts, suggesting that adherence to a healthy lifestyle could lead to greater absolute risk reduction among those with high T2D-GR. The public health implication is that a healthy lifestyle is important for diabetes prevention, especially for individuals with high GRS and FH of T2D. [ABSTRACT FROM AUTHOR]

Published
2020
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128. Nut Consumption and Risk of Cardiovascular Disease

Author

Guasch-Ferré, Marta, primary, Liu, Xiaoran, additional, Malik, Vasanti S., additional, Sun, Qi, additional, Willett, Walter C., additional, Manson, JoAnn E., additional, Rexrode, Kathryn M., additional, Li, Yanping, additional, Hu, Frank B., additional, and Bhupathiraju, Shilpa N., additional

Published
2017
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139. A Healthy Lifestyle Score Is Associated with Cardiometabolic and Neuroendocrine Risk Factors among Puerto Rican Adults123

Author

Sotos-Prieto, Mercedes, Bhupathiraju, Shilpa N, Falcón, Luis M, Gao, Xiang, Tucker, Katherine L, and Mattei, Josiemer

Subjects
Metabolic Syndrome, Health Behavior, Puerto Rico, Feeding Behavior, Middle Aged, Motor Activity, Cross-Sectional Studies, Socioeconomic Factors, Allostasis, Cardiovascular Diseases, Risk Factors, Nutritional Epidemiology, Humans, Waist Circumference, Life Style, Aged, Boston, Follow-Up Studies
Abstract

Although individual healthy lifestyle behaviors may reduce cardiovascular disease risk, few studies have analyzed the combined effect of multiple lifestyle components as one all-inclusive measure on such outcomes, much less in minority populations.We aimed to develop a Healthy Lifestyle Score (HLS) that included several lifestyle recommendations and to test its association with metabolic syndrome (MetS) and allostatic load (AL) and their cardiometabolic and neuroendocrine factors in Puerto Ricans.In a cross-sectional study in 787 Puerto Ricans living in Boston (aged 45-75 y), we developed an HLS that ranged from 0 to 190 (higher score indicative of healthier lifestyle) and included 5 components (diet, physical activity and sedentary behaviors, smoking, social support and network, and sleep). Multivariable-adjusted models were used to test associations between the HLS and biomarkers of dysregulation and odds of MetS and high AL (≥4 out of 10 components).The HLS showed adequate internal consistency (ρ = 0.31-0.69) and was inversely associated with urinary cortisol (β ± SE = -0.22 ± 0.11; P = 0.042), epinephrine (-0.20 ± 0.09; P = 0.017), and norepinephrine (-0.26 ± 0.11; P = 0.016); waist circumference (-0.014 ± 0.004; P = 0.003); and serum insulin (-0.30 ± 0.13; P = 0.028) and positively associated with plasma HDL cholesterol (0.007 ± 0.003; P = 0.021) after adjustment for potential confounders. For each 20-unit increase in HLS, participants had 19% (95% CI: 2%, 33%) and 25% (11%, 36%) lower odds of MetS or AL, respectively. Healthier scores for social support and network and smoking components were associated with lower odds of high AL (P0.005). No significant associations were observed for other individual lifestyle components.Following an overall healthy lifestyle that comprises a combination of multiple behaviors may provide stronger protection against MetS and AL in Puerto Rican adults than individual components. The HLS may be a useful tool for examining health-related outcomes. This trial was registered at clinicaltrials.gov as NCT01231958.

Published
2015

143. Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents

Author

Di Angelantonio, Emanuele, primary, Bhupathiraju, Shilpa N, additional, Wormser, David, additional, Gao, Pei, additional, Kaptoge, Stephen, additional, de Gonzalez, Amy Berrington, additional, Cairns, Benjamin J, additional, Huxley, Rachel, additional, Jackson, Chandra L, additional, Joshy, Grace, additional, Lewington, Sarah, additional, Manson, JoAnn E, additional, Murphy, Neil, additional, Patel, Alpa V, additional, Samet, Jonathan M, additional, Woodward, Mark, additional, Zheng, Wei, additional, Zhou, Maigen, additional, Bansal, Narinder, additional, Barricarte, Aurelio, additional, Carter, Brian, additional, Cerhan, James R, additional, Collins, Rory, additional, Smith, George Davey, additional, Fang, Xianghua, additional, Franco, Oscar H, additional, Green, Jane, additional, Halsey, Jim, additional, Hildebrand, Janet S, additional, Jung, Keum Ji, additional, Korda, Rosemary J, additional, McLerran, Dale F, additional, Moore, Steven C, additional, O'Keeffe, Linda M, additional, Paige, Ellie, additional, Ramond, Anna, additional, Reeves, Gillian K, additional, Rolland, Betsy, additional, Sacerdote, Carlotta, additional, Sattar, Naveed, additional, Sofianopoulou, Eleni, additional, Stevens, June, additional, Thun, Michael, additional, Ueshima, Hirotsugu, additional, Yang, Ling, additional, Yun, Young Duk, additional, Willeit, Peter, additional, Banks, Emily, additional, Beral, Valerie, additional, Chen, Zhengming, additional, Gapstur, Susan M, additional, Gunter, Marc J, additional, Hartge, Patricia, additional, Jee, Sun Ha, additional, Lam, Tai-Hing, additional, Peto, Richard, additional, Potter, John D, additional, Willett, Walter C, additional, Thompson, Simon G, additional, Danesh, John, additional, and Hu, Frank B, additional

Published
2016
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