7 research outputs found
Making the Revolution: The Young Lords and the Creation of a New Puerto Rican Identity
No full textIn this paper, I provide a critique of the Young Lords by dissecting how the Young Lords shifted Puerto Rican identity from an assimilationist perspective to a politicized and decolonial one. Through understanding Puerto Rico (and consequently, Puerto Ricans) as an extension of what Anibal Quijano calls the \u27coloniality of power’, I argue that the Young Lord’s develop a dichotomy between good vs. bad Puerto Ricans, where good Puerto Ricans are affirmed and legitimized as genuine Puerto Ricans, while bad Puerto Ricans are discredited and excluded from the movement. I identify four archetypes to show how the Young Lords divided \u27good\u27 and \u27bad\u27 Puerto Ricans: Revolutionaries, Passive Dissenters, Traitors, and Martyrs. I examined online archived newspapers published by the Young Lords in New York and Chicago in 1970 and found that Puerto Rican identity is formulated through a process of culturally and politically distancing oneself from “American” identity. This paper highlights the pervasiveness of colonialism as a driving factor in identity formation by centering the unique situation of Puerto Ricans -- what Ramon Grosfoguel calls \u27colonial subjects.\u27 Ultimately, this paper asks us to reflect upon how we put meaning behind our identities as we engage in movements of resistance and, by extension, builds upon other critiques of revolutionary movements within the United States
Bioimpedance Minimally Improves Prediction of Bone Mineral Density Beyond Demographic Information Alone
No full textBone mineral content (BMC) serves as an important indicator of osteoporosis risk. Traditional methods of BMC estimation include using demographic information within prediction equations, which draw from population trends but may not reflect individual variance in BMC. Dual-energy X-ray absorptiometry (DXA) provides a more accurate assessment of BMC but may pose challenges in clinical settings due to certification requirements, cost, and space requirements. Bioelectrical impedance analysis (BIA) has shown promise in correlating with BMC and may offer an intriguing alternative due to its accessibility, but its efficacy compared to traditional methods remains largely unexplored. PURPOSE: Quantify the contribution of BIA assessment on accuracy of BMC estimations compared to the traditional demographic information alone. METHODS: Three-hundred and twelve adults (n=193 F, n=119 M; [mean ± SD] age: 30.2 ± 13.0 y; body mass: 71.2 ± 14.7 kg; height: 169.6 ± 9.1 cm; body fat: 27.8 ± 8.7%) completed DXA and standing multi-frequency bioelectrical impedance analysis (MFBIA) assessments in a single laboratory visit. Two multiple linear regression models were fit to predict DXA BMC. The demographic model included age, sex, weight, and height as predictors, while the demographic + bioimpedance model additionally included total body bioelectrical resistance at the 50 kHz frequency. Regression model performance was quantified by the R2, root mean square error (RMSE), and Akaike information criterion (AIC). RESULTS: In both models, weight, height and the male sex were positively related to BMC, while age was negatively related to BMC (p\u3c0.01 for all). Although bioelectrical resistance was negatively related to DXA BMC (p\u3c0.01), it exerted a minimal improvement in the overall regression model performance (demographic model: R2: 0.79, RMSE: 241 g, AIC: 4321; demographic + bioimpedance model: R2: 0.82, RMSE: 225 g, AIC: 4280). CONCLUSIONS: The inclusion of bioelectrical impedance analysis (BIA) resulted in only a modest improvement in model performance compared to the demographic model. These findings suggest that BIA-derived BMC estimations may not provide clinically significant benefit, nor should the BMC estimation provided by BIA hold substantially greater weight in the minds of clinicians and patients alike. Though this study did not indicate the need for widespread implementation of BIA-derived BMC assessments, further experimentation involving a more diverse population, particularly for those at greater risk of osteoporosis, could offer valuable insight into the potential of BIA in accurate monitoring and detection
Validity of a Portable Metabolic Analyzer for Estimating Resting Metabolic Rate in Muscular Resistance-trained Adults
No full textAn individual’s resting metabolic rate (RMR) is commonly the largest contributor to total daily energy expenditure. The accepted reference method for in vivo measurement of RMR is indirect calorimetry (IC). However, the accessibility of traditional IC analyzers is limited to select settings; therefore, portable indirect calorimeters are also applied to estimate RMR. Limited data are available to inform the validity of the VO2 Master for estimating RMR in muscular resistance-trained adults. PURPOSE: The purpose of this study was to determine the validity of the VO2 Master portable metabolic analyzer for estimating RMR in muscular resistance-trained adults. METHODS: A sample of 38 resistance-trained adults (15 F, 23 M; [mean ± SD] age 28.0 ± 7.9 y, height 172.0 ± 9.6 cm, weight 77.6 ± 12.9 kg, body fat% 17.5 ± 5.2, fat-free mass index 21.5 ± 2.9 kg/m2) underwent metabolic assessment via a metabolic cart (IC) and a portable metabolic analyzer (VO2 Master) in a single visit. RMR estimates obtained from IC were considered the reference values. Equivalence testing was used to evaluate whether the VO2 Master demonstrated equivalence with IC. Null hypothesis significance testing was also performed, and Bland-Altman analysis was used alongside linear regression to assess the degree of proportional bias. Constant error (CE), mean absolute error (MAE), and 95% limits of agreement (LOA) were also calculated. RESULTS: The mean ± SD RMR estimates for IC and the VO2 Master were 2192.7 ± 408.8 kcal/d and 1798.2 ± 418.8 kcal/d, respectively. The CE and MAE were -394.6 kcal/d and 419.1 kcal/d, respectively. Additionally, no proportional bias was observed, but wide LOA were present, and the VO2 Master did not demonstrate equivalence with IC. CONCLUSION: Given these findings, the consistent underestimation by the VO2 Master indicates that it may not be suitable for application in muscular resistance-trained adults. While noteworthy, fat-free mass contributes to a considerable portion of variance within RMR, and it has been suggested that the relationship between underprediction bias and RMR is likely a result of greater fat-free mass
Comparing the Validity of Five Different Resting Metabolic Rate Prediction Equations in Active Women
No full textResting metabolic rate (RMR) prediction equations are often used in settings where the measurement of RMR through indirect calorimetry (IC) may not be feasible. However, commonly used equations developed in less active populations may not accurately predict RMR in active individuals who have a higher proportion of lean tissue. PURPOSE: The purpose of this study was to determine the validity of RMR prediction equations by Harris & Benedict (1918), Cunningham (1980 and 1991), DeLorenzo (1999), and ten Haaf & Weijs (2014) against a criterion model (IC) in a population of active women. METHODS: Forty-one generally healthy women were included in this analysis. All participants self-attested to engaging in two or more hours of moderate- to vigorous-intensity exercise per week, of any modality, for the past three months or more. Participants abstained from all food, fluid, caffeine, and alcohol for at least 8 hours and from exercise for at least 24 hours prior to their visit. Body fat percentage (BFP) was obtained via dual-energy x-ray absorptiometry (DXA; Lunar iDXA, General Electric). RMR was measured using a metabolic cart (Parvo Medics TrueOne 2400) with ventilated hood. After 30 minutes of supine rest, gas was collected for a minimum of ten minutes with the first five minutes discarded. Data were collected until a coefficient of variation \u3c10% for VO2 and VCO2 and \u3c5% for RMR was achieved, with the average of the final five minutes used. Total error (TE) was calculated as the root mean square error between the estimate of each prediction equation and that obtained via IC. Constant error (CE) was calculated as the average difference between the estimate of each equation and that obtained via IC. Equivalence was assessed using two one-sided t-tests (TOST) assuming a ±100-kcal region of equivalence. Finally, Bland-Altman plots were generated for each equation and the slope and statistical significance of the linear regression line reported. RESULTS: Participants (mean ±SD age: 21.7±3.7 years, height: 164.4±6.1 cm; weight of 64.8±9.3 kg; BFP: 33.2±5.9%) had an average measured RMR of 1624±191 kcal/day. In the entire sample, TE ranged from 143 (ten Haaf & Weijs) to 353 (Cunningham 1991) kcal/day. CE ranged from -324±142 (Cunningham 1991) to +25±145 (DeLorenzo) kcal/day. Only the DeLorenzo and ten Haaf & Weijs equations were statistically equivalent via TOST. For all five equations, the slope of the Bland-Altman plot was negative and significantly different from zero (i.e., showed negative proportional bias), with most equations overestimating RMR in those with lower measured values and underestimating RMR in those with higher measured values. CONCLUSION: Equations developed more recently and in active populations (i.e., DeLorenzo 1999 and ten Haaf & Weijs 2014) exhibited greater validity overall. Both the DeLorenzo (1999) and ten Haaf & Weijs (2014) equations may be more suitable to use when predicting RMR in a population of generally healthy, active young women
Correlations Between Measured-to-Predicted Resting Metabolic Rate Ratio and Psychological Variables in Active Women
No full textRMRratio provides an indication of energy availability by comparing measured resting metabolic rate (RMR) to that predicted by an equation using values such as age, height, and lean mass. RMRratio has been associated with psychological variables such as cognitive restraint (CR) and Drive for Thinness (DT) in young, active women. PURPOSE: The purpose of this study was to assess the strength of correlation between these psychometric variables and RMRratio values using a variety of RMR prediction equations. METHODS: Forty-one generally healthy women were included in this analysis. All participants self-attested to engaging in two or more hours of moderate- to vigorous-intensity exercise per week, of any modality, for the past three months or more. Participants abstained from all food, fluid, caffeine, and alcohol for at least 8 hours and from exercise for at least 24 hours prior to their visit. Body fat percentage (BFP) was obtained via dual-energy X-ray absorptiometry (DXA; Lunar iDXA, General Electric). RMR was measured using a metabolic cart (TrueOne 2400, Parvo Medics) with ventilated hood. After 30 minutes of supine rest, gas was collected for a minimum of ten minutes with the first five minutes discarded. Data were collected until coefficients of variation \u3c10% for VO2 and VCO2 and \u3c5% for RMR were achieved, with the average of the final five minutes used. CR was assessed using the Three-Factor Eating Questionnaire Revised 18-item form (possible range: 6-24) and DT was assessed using the raw score generated from the Eating Disorder Inventory 91-item questionnaire (possible range: 0-21). RMRratio values were calculated using five equations (Harris-Benedict 1918; Cunningham 1980 and 1991; DeLorenzo 1999; and ten Haaf & Weijs 2014). As CR and DT scores were considered non-parametric data, correlations were analyzed using Spearman\u27s ρ corrected for multiple comparisons. RESULTS: Participants (mean ±SD age: 21.7±3.7 years, height: 164.4±6.1 cm; weight: 64.8±9.3 kg; BFP: 33.2±5.9%) had an average measured RMR of 1624±191 kcal/day, CR score of 12.4±4.0, and DT score of 4.2±5.6. Correlation values with CR ranged from -0.39 (ten Haaf & Weijs) to -0.29 (Cunningham 1991) and were statistically significant (p\u3c0.05) for only the Delorenzo and ten Haaf & Weijs equations (ps≤0.04). Correlation values with DT ranged from -0.27 (ten Haaf & Weijs) to -0.14 (Cunningham 1991) but were not statistically significant for any equation (all ps≥0.31). CONCLUSION: In previous research, RMRratio has been correlated with psychological variables traditionally associated with low energy availability, namely CR and DT. In our sample of young, exercising women, RMRratio using the ten Haaf & Weijs (2014) equation was most strongly correlated with CR and equally unassociated with DT when compared to four other equations. Future research using this equation within RMRratio analyses is warranted
Validity of Body Volume Estimates from a Smartphone 3-Dimensional Scanning Application
No full textBody volume (BV) indicates the total 3-dimensional (3D) space an individual occupies. BV is either used alongside body mass in density-based two-compartment models or in conjunction with other body components in multi-compartment models to estimate body composition (BC). BV estimates are typically produced by costly laboratory methods, such as hydrostatic weighing or air-displacement plethysmography (ADP). However, more accessible options are emerging. Smartphone-based 3D scanning uses the phone’s built-in camera to provide a BV estimate in a time-efficient and cost-effective manner. However, few investigations have validated this method against an accepted laboratory technique. PURPOSE: To determine the validity of BV from a 3D scanning smartphone application. METHODS: ADP and a 3D scanning smartphone application were used to estimate BV in 60 adults (28 F, 32 M; [mean ± SD] age 24.4 ± 6.5 y, body mass index 24.7 ± 4.3 kg/m2). The 3D scanning application required participants to rotate in place in front of the smartphone camera while serial images were collected, and avatars were produced from approximately 30 images using non-rigid avatar reconstruction. BV was estimated from the avatars, then corrected for estimated thoracic gas volume through published equations using basic demographic and anthropometric variables. ADP was conducted using standard practices recommended by the manufacturer. The relationship between ADP and 3D scanning BV was quantified by Deming regression, the concordance correlation coefficient (CCC), equivalence testing, and Bland-Altman analysis. RESULTS: Mean ± SD BV was 67.1 ± 10.9 L for ADP and 66.8 ± 9.9 L for 3D scanning. The Deming regression line for ADP vs. 3D scanning BV (3D=1.1×ADP - 6.5) did not significantly differ from the line of identity (i.e., y=1x + 0). The CCC between BV estimates was 0.96, and statistical equivalence was demonstrated using 2.5% equivalence regions (pCONCLUSION: The present study indicates BV estimated by a 3D scanning smartphone application may be a potential alternative to BV measured by ADP. This could increase the accessibility of BV values for BC estimation in two-compartment models and incorporation into field-based multi compartment models
Chronic Thermogenic Dietary Supplement Consumption: Effects on Body Composition, Anthropometrics, and Metabolism
No full text© 2023 by the authors. cc-byMulti-ingredient thermogenic supplements can acutely increase resting energy expenditure (REE) and subjective energy. However, less is understood about the effects of chronic consumption on body composition, metabolism, and subjective variables such as mood, sleep quality, and eating behaviors. Fifty-two healthy, exercise-trained participants (50% female; mean ± SD age: 23.5 ± 3.0 years; body fat percentage: 27.3 ± 8.0%) were randomized 2:2:1 to take a whey protein supplement alone (PRO; n = 20), in combination with a thermogenic supplement (PRO + FB; n = 19), or no supplement at all (CON; n = 13) for four weeks. Body composition, anthropometric, metabolic, hemodynamic, and subjective outcomes were collected before and after the intervention. Greater changes in REE occurred in PRO + FB as compared to CON (111.2 kcal/d, 95% CI 2.4 to 219.9 kcal/d, p = 0.04), without significant differences between PRO and CON (42.7 kcal/d, 95% CI −65.0 to 150.3 kcal/d, p = 0.61) or between PRO + FB and PRO (68.5 kcal/d, 95% CI −28.3, 165.3, p = 0.21). No changes in hemodynamic outcomes (blood pressure and heart rate) were observed. In exercising adults, four weeks of supplementation with protein and a multi-ingredient thermogenic product maintained fasted REE as compared to no supplementation, for which a decrease in REE was observed, without differential effects on body composition, anthropometrics, or subjective variables
