Sameera Talegawkar

Dr. Sameera Talegawkar


Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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24 August 2016 in BMC Public Health
Verified
Journal Article
Open access
PDF file
ATAngela Trude
Angela Trude
AKAnna Yevgenyevna Kharmats
Anna Yevgenyevna Kharmats
KHKristen Marie Hurley
Kristen Marie Hurley
Elizabeth Anderson SteevesElizabeth Anderson Steeves
Elizabeth Anderson Steeves
STSameera Talegawkar
Sameera Talegawkar
JGJoel Gittelsohn
Joel Gittelsohn
Childhood obesity, one of the greatest challenges to public health, disproportionately affects low-income urban minority populations. Fruits and vegetables (FV) are nutrient dense foods that may be inversely associated with excessive weight gain. We aimed to identify the individual characteristic, psychosocial, and household factors influencing FV and fiber consumption in low-income African-American (AA) youth in Baltimore, MD. Cross-sectional analysis of data collected from 285 low-income AA caregiver-youth (age range: 10–14 y) dyads participating in the baseline evaluation of the B’More Healthy Communities for Kids obesity prevention trial. The Kid's Block FFQ was used to estimate daily intakes of FV (including 100 % fruit juice) and dietary fiber. Questionnaires were used to assess household socio-demographics, caregiver and youth food purchasing and preparation behavior, and youth psychosocial information. Ordered logit regression analyses were conducted to examine psychosocial and food-related behavior associated with FV and dietary fiber intake (quartile of intake) controlling for youth age, sex, BMI percentile, total calorie intake and household income. On average, youth consumed 1.5 ± 1.1 (M ± SD) servings of fruit, 1.8 ± 1.7 serving of vegetables, and 15.3 ± 10.9 g of fiber/day. There were no differences by gender, age or household income. Greater youth’s healthy eating intentions and self-efficacy scores were associated with greater odds ratio for higher intake of FV and fiber (Intention: ORfruit 1.22; 95 % CI: 1.06–1.41, ORvegetable 1.31; 1.15–1.51 and ORfiber 1.46; 1.23–1.74, Self-efficacy: ORfruit 1.07; 1.03–1.12, ORvegetable 1.04; 1.01–1.09, ORfiber 1.10; 1.04–1.16). Youth receiving free/low-cost breakfast were more than twice as likely to have higher fiber intake than those who did not receive free breakfast (OR 2.7; 1.10; 6.9). In addition, youth shopping more frequently at supermarkets were more likely to have greater vegetable and fiber intake (OR 1.26; 1.06–1.50; OR 1.28; 1.03–1.58, respectively). Also, youth with parents who shopped more frequently at fast-food stores had 7 % lower odds for higher vegetable intake (95 % CI: 0.88–0.99). In this study, both, youth and household factors were associated with youth FV and fiber intake, underscoring the need for a multi-level approach to increasing youths’ diet quality. These results will inform and shape an effective intervention program for improving youth dietary intakes.

27 May 2022 in Nutrients
Verified
Journal Article
Open access
PDF file
TTToshiko Tanaka
Toshiko Tanaka
STSameera Talegawkar
Sameera Talegawkar
YJYichen Jin
Yichen Jin
Julián CandiaJulián Candia
Julián Candia
QTQu Tian
Qu Tian
LFLuigi Ferrucci
Luigi Ferrucci
Diet quality has been associated with slower rates of aging; however, the mechanisms underlying the role of a healthy diet in aging are not fully understood. To address this question, we aimed to identify plasma metabolomic biomarkers of dietary patterns and explored whether these metabolites mediate the relationship between diet and healthy aging, as assessed by the frailty index (FI) in 806 participants of the Baltimore Longitudinal Study of Aging. Adherence to different dietary patterns was evaluated using the Mediterranean diet score (MDS), Mediterranean–DASH Diet Intervention for Neurodegenerative Delay (MIND) score, and Alternate Healthy Eating Index-2010 (AHEI). Associations between diet, FI, and metabolites were assessed using linear regression models. Higher adherence to these dietary patterns was associated with lower FI. We found 236, 218, and 278 metabolites associated with the MDS, MIND, and AHEI, respectively, with 127 common metabolites, which included lipids, tri/di-glycerides, lyso/phosphatidylcholine, amino acids, bile acids, ceramides, cholesterol esters, fatty acids and acylcarnitines, indoles, and sphingomyelins. Metabolomic signatures of diet explained 28%, 37%, and 38% of the variance of the MDS, MIND, and AHEI, respectively. Signatures of MIND and AHEI mediated 55% and 61% of the association between each dietary pattern with FI, while the mediating effect of MDS signature was not statistically significant. The high number of metabolites associated with the different dietary patterns supports the notion of common mechanisms that underly the relationship between diet and frailty. The identification of multiple metabolite classes suggests that the effect of diet is complex and not mediated by any specific biomarkers. Furthermore, these metabolites may serve as biomarkers for poor diet quality to identify individuals for targeted dietary interventions.

30 March 2021 in Nutrients
Verified
Journal Article
Open access
PDF file
TTToshiko Tanaka
Toshiko Tanaka
STSameera Talegawkar
Sameera Talegawkar
YJYichen Jin
Yichen Jin
SBStephania Bandinelli
Stephania Bandinelli
LFLuigi Ferrucci
Luigi Ferrucci
Identifying modifying protective factors to promote healthy aging is of utmost public health importance. The frailty index (FI) reflects the accumulation of health deficits and is one widely used method to assess health trajectories in aging. Adherence to a Mediterranean-type diet (MTD) has been associated with favorable health trajectories. Therefore, this study explored whether adherence to a MTD is negatively associated with FI in the InCHIANTI study. Participants (n = 485) included individuals over 65 years of age at baseline with complete data over a follow-up period of 10 years. MTD was computed on a scale of 0–9 and categorized based on these scores into three groups of low (≤3), medium (4–5), and high (≥6) adherence. Being in a high or medium adherence group was associated with 0.03 and 0.013 unit lower FI scores over the follow-up period, compared to the low adherence group. In participants with a low FI at baseline, being in a high or medium MTD-adherence group had 0.004 and 0.005 unit/year slower progression of FI compared to the low adherence group. These study results support adherence to a MTD as a protective strategy to maintain a lower FI.