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Accuracy of Parents' Perceptions of Their Two-to Five-Year-Old Child's Body Size and Weight Status
SUNDAY, OCTOBER 26
POSTER SESSION: PROFESSIONAL SKILLS/NUTRITION ASSESSMENT/MEDICAL NUTRITION THERAPY Title: ACCURACY OF PARENTS’ PERCEPTIONS OF THEIR TWO-TO FIVE-YEAR-OLD CHILD’S BODY SIZE AND WEIGHT STATUS
Title: NUTRITIONAL RISK PREDICTING QUALITY OF LIFE AMONG COMMUNITY-LIVING OLDER CHINESE AMERICANS IN SOUTH FLORIDA
Author(s): C. S. Rachal,1 J. Weber,2 R. Fournet1; 1Dietetics, University of Louisiana at Lafayette, Lafayette, LA, 2Sociology and Anthropology, University of Louisiana at Lafayette, Lafayette, LA
Author(s): Y. L. Pan,1 F. L. Newman,2 S. P. Himburg,1 Z. Dixon1; 1 Dietetics and Nutrition, FIU, Miami, FL, 2Health Policy and Management, FIU, Miami, FL
Learning Outcome: To determine how accurately parents perceive their preschool-age child’s body size and weight status and if certain demographic variables are related to their degree of accuracy.
Learning Outcome: To determine applicability of a nutritional risk screening tool for assessing quality of life.
Text: Studies show that parents often underestimate their child’s measured weight status and several demographic factors may relate to inaccurate perception. This study examines how accurately parents perceive their 2-to-5 year-old child’s body size and weight status, and whether certain demographic variables relate to parental accuracy. The sample consisted of 53 parent-child dyads. Children’s mean Body Mass Index (BMI)-for-Age was the 63rd percentile; parents’ mean BMI was 25 kg/m2. A questionnaire was used to gather demographic data regarding parent-child dyads; the Body Image Distortion Program (BIDP) and Visual Analog Scale (VAS) were adapted to measure parental perception of their child’s body size and weight status, respectively. Using the BIDP, 59% of parents perceived their child’s body size within 5% of accuracy; using the VAS, 11.6% were accurate within 5 percentile points and 82.7% underestimated their child’s weight status. Accuracy of parents’ perception of child’s weight status inversely related to child’s BMI-for-Age percentile (r ⫽ ⫺.881, p ⫽ .000) and parent’s BMI (r ⫽ ⫺.332, p ⫽ .018). Employing multiple regression analysis, child’s measured weight status explained 77.7% of variability in parental accuracy. No other significant correlations were found. The results indicate parents more accurately perceive their child’s body size and underestimate weight status. Parental accuracy is likely influenced by the subjectivity inherent in perceiving weight status. A better indicator of what body size parents would consider “overweight” in their child is needed before steps can be taken to improve parental accuracy. Funding Disclosure: None
Title: DIETARY CALCIUM-TO-PROTEIN RATIO AMONG COLLEGE STUDENTS Author(s): R. C. Bessinger; Human Nutrition, Winthrop University, Rock Hill, SC Learning Outcome: To understand that college students may have a calcium-to-protein ratio that is lest than optimal for providing adequate protection for bone. Text: Whether or not protein is associated with bone loss may depend upon the ratio of calcium-to-protein intake and not just the amount of protein consumed. The purpose of this study was to determine calcium-to-protein ratios in college students. Calcium and protein intake was determined by analysis of 3-day food records kept by 50 females and 22 males. The average caloric intake was 2300 for females and 2755 for males. The calcium-to-protein ratio (mg of calcium to grams of protein), for the females and males respectively was 11:1 and 9.9:1. Twentytwo percent of the females had a calcium intake of 500 mg/day or less and a ratio of 7:1. These low ratios may be insufficient to protect bone. While ideal ratios have not been determined, it appears reasonable, based on Dietary Reference Intakes of calcium and protein for males and females 19-50, an optimal or “ideal” ratio might be approximately 22:1 for women and 18:1 for men. These values can at least be used for comparison purposes. A ratio of 20:1, based on 1997 recommended intakes, was suggested a decade ago as an adequate value for protecting bone. Ratios lower than the above values may be less than optimal and lead to calcium losses that are great enough to affect bone health. While bone was not measured in this study, other research has reported that excessive protein intake along with low calcium intake compromises bone. Thus, it may be useful for dietitians to look at the calcium-to-protein ratio when counseling clients. Funding Disclosure: None A-22 / September 2008 Suppl 3—Abstracts Volume 108 Number 9
Text: This study was designed to examine which aspects of quality of life could be predicted by evaluating nutritional risk among older Chinese Americans. In this cross-sectional study, Chinese adults aged 60 and over, residing in Miami, Florida were recruited through community-based organizations and chain referral. Subjects were rated on the DETERMINE Your Nutritional Health checklist and the Medical Outcomes Study 36-Item Short Form Health Survey (SF-36) via face-toface interviews. The 100 subjects included 59% females, 98% foreignborn, 23% non-English speakers, 68% residents of Florida for at least 20 years, with a mean age of 70.9⫾6.8 years. Results showed 52% at moderate or high levels of nutritional risk. All eight dimensions of the SF-36, except for general health, showed significant correlations with nutritional risk (r⫽ ⫺.434 to ⫺.198). A multivariate ANOVA (p ⬍.001) and the follow-up univariate analyses found that nutritional risk accounted for significant effects with small to strong effect sizes (employing 2) for social functioning [F(2, 97)⫽11.41, p⬍.001, 2 ⫽.19, strong], physical functioning [F(2, 97)⫽5.31, p⬍.01, 2 ⫽.10, moderate], bodily pain [F(2, 97)⫽3.85, p⬍.05, 2 ⫽.07, moderate], role limitations due to emotional problems [F(2, 97)⫽3.34, p⬍.05, 2 ⫽.06, small], and mental health [F(2, 97)⫽3.23, p⬍.05, 2 ⫽.06, small]. These findings suggest that the DETERMINE checklist is a useful nutritional screening tool for predicting quality of life of older Chinese Americans, especially when monitoring social and physical functionality. It is recommended that dietetics professionals address nutritional risk issues by promoting the social and physical functionality of their clients. Funding Disclosure: This project was supported in part by a grant (90AM2768) from the Administration on Aging, US Department of Health and Human Services, Washington, DC
Title: A RESTING METABOLIC RATE EQUATION INCLUDING LEAN BODY MASS PROVIDES A BETTER PREDICTION IN AFRICAN-AMERICAN FEMALES Author(s): M. W. Valliant,1 D. K. Tidwell,2 S. G. Owens,3 L. F. Chitwood3; 1Family and Consumer Sciences, The University of Mississippi, University, MS, 2Department of Food Science, Nutrition and Health Promotion, Mississippi State University, Starkville, MS, 3 Health, Exercise Science and Recreation Management, The University of Mississippi, University, MS Learning Outcome: Understand the development and accuracy of a new resting metabolic rate equation appropriate for minority populations. Text: An equation including fat free mass (FFM) for predicting RMR in African-American (AA) females was developed. The objective was to compare the prediction accuracy of this new equation and three previously published equations Harris-Benedict, FAO, and University of Memphis against the indirect calorimetry measured RMR (mRMR). One hundred AA female subjects, ages 18 to 40, with various body mass indices participated in this study. Fifty subjects were randomly selected for developing the new equation and fifty subjects to test all four equations. Subjects’ height (ht), weight (wt), and age were obtained and fat-mass (FM) and fat-free mass (FFM) were measured by bioelectrical impedance. A forward stepwise multiple regression analysis was performed with mRMR as the dependent variable and age, ht, wt, FM, and FFM serving as independent variables to develop the following new equation: RMR⫽460.61⫹2.22FFM⫹8.189ht⫹3.139age⫹2.082FM⫹1.685wt SEE 126.4. The mean mRMR was compared to the mean of predicted RMR (pRMR) for each equation using ANOVA. When significant F values were obtained, Tukey’s post hoc test was used to identify significant differences between the means. The new equation’s pRMR was the only one that did not differ significantly from mRMR and had the largest R2 (.59) and smallest SEM (26.64). When selecting a prediction equation to estimate RMR, it is imperative to select the equation that provides the best estimate of RMR for the population considered. It appears that this new equation with the inclusion of FM and FFM is more accurate than previous equations in estimating RMR in AA females. Funding Disclosure: This research was funded in part by the School of Applied Sciences, The University of Mississippi
POSTER SESSION: PROFESSIONAL SKILLS/NUTRITION ASSESSMENT/MEDICAL NUTRITION THERAPY Title: ACCURACY OF PARENTS’ PERCEPTIONS OF THEIR TWO-TO FIVE-YEAR-OLD CHILD’S BODY SIZE AND WEIGHT STATUS
Title: NUTRITIONAL RISK PREDICTING QUALITY OF LIFE AMONG COMMUNITY-LIVING OLDER CHINESE AMERICANS IN SOUTH FLORIDA
Author(s): C. S. Rachal,1 J. Weber,2 R. Fournet1; 1Dietetics, University of Louisiana at Lafayette, Lafayette, LA, 2Sociology and Anthropology, University of Louisiana at Lafayette, Lafayette, LA
Author(s): Y. L. Pan,1 F. L. Newman,2 S. P. Himburg,1 Z. Dixon1; 1 Dietetics and Nutrition, FIU, Miami, FL, 2Health Policy and Management, FIU, Miami, FL
Learning Outcome: To determine how accurately parents perceive their preschool-age child’s body size and weight status and if certain demographic variables are related to their degree of accuracy.
Learning Outcome: To determine applicability of a nutritional risk screening tool for assessing quality of life.
Text: Studies show that parents often underestimate their child’s measured weight status and several demographic factors may relate to inaccurate perception. This study examines how accurately parents perceive their 2-to-5 year-old child’s body size and weight status, and whether certain demographic variables relate to parental accuracy. The sample consisted of 53 parent-child dyads. Children’s mean Body Mass Index (BMI)-for-Age was the 63rd percentile; parents’ mean BMI was 25 kg/m2. A questionnaire was used to gather demographic data regarding parent-child dyads; the Body Image Distortion Program (BIDP) and Visual Analog Scale (VAS) were adapted to measure parental perception of their child’s body size and weight status, respectively. Using the BIDP, 59% of parents perceived their child’s body size within 5% of accuracy; using the VAS, 11.6% were accurate within 5 percentile points and 82.7% underestimated their child’s weight status. Accuracy of parents’ perception of child’s weight status inversely related to child’s BMI-for-Age percentile (r ⫽ ⫺.881, p ⫽ .000) and parent’s BMI (r ⫽ ⫺.332, p ⫽ .018). Employing multiple regression analysis, child’s measured weight status explained 77.7% of variability in parental accuracy. No other significant correlations were found. The results indicate parents more accurately perceive their child’s body size and underestimate weight status. Parental accuracy is likely influenced by the subjectivity inherent in perceiving weight status. A better indicator of what body size parents would consider “overweight” in their child is needed before steps can be taken to improve parental accuracy. Funding Disclosure: None
Title: DIETARY CALCIUM-TO-PROTEIN RATIO AMONG COLLEGE STUDENTS Author(s): R. C. Bessinger; Human Nutrition, Winthrop University, Rock Hill, SC Learning Outcome: To understand that college students may have a calcium-to-protein ratio that is lest than optimal for providing adequate protection for bone. Text: Whether or not protein is associated with bone loss may depend upon the ratio of calcium-to-protein intake and not just the amount of protein consumed. The purpose of this study was to determine calcium-to-protein ratios in college students. Calcium and protein intake was determined by analysis of 3-day food records kept by 50 females and 22 males. The average caloric intake was 2300 for females and 2755 for males. The calcium-to-protein ratio (mg of calcium to grams of protein), for the females and males respectively was 11:1 and 9.9:1. Twentytwo percent of the females had a calcium intake of 500 mg/day or less and a ratio of 7:1. These low ratios may be insufficient to protect bone. While ideal ratios have not been determined, it appears reasonable, based on Dietary Reference Intakes of calcium and protein for males and females 19-50, an optimal or “ideal” ratio might be approximately 22:1 for women and 18:1 for men. These values can at least be used for comparison purposes. A ratio of 20:1, based on 1997 recommended intakes, was suggested a decade ago as an adequate value for protecting bone. Ratios lower than the above values may be less than optimal and lead to calcium losses that are great enough to affect bone health. While bone was not measured in this study, other research has reported that excessive protein intake along with low calcium intake compromises bone. Thus, it may be useful for dietitians to look at the calcium-to-protein ratio when counseling clients. Funding Disclosure: None A-22 / September 2008 Suppl 3—Abstracts Volume 108 Number 9
Text: This study was designed to examine which aspects of quality of life could be predicted by evaluating nutritional risk among older Chinese Americans. In this cross-sectional study, Chinese adults aged 60 and over, residing in Miami, Florida were recruited through community-based organizations and chain referral. Subjects were rated on the DETERMINE Your Nutritional Health checklist and the Medical Outcomes Study 36-Item Short Form Health Survey (SF-36) via face-toface interviews. The 100 subjects included 59% females, 98% foreignborn, 23% non-English speakers, 68% residents of Florida for at least 20 years, with a mean age of 70.9⫾6.8 years. Results showed 52% at moderate or high levels of nutritional risk. All eight dimensions of the SF-36, except for general health, showed significant correlations with nutritional risk (r⫽ ⫺.434 to ⫺.198). A multivariate ANOVA (p ⬍.001) and the follow-up univariate analyses found that nutritional risk accounted for significant effects with small to strong effect sizes (employing 2) for social functioning [F(2, 97)⫽11.41, p⬍.001, 2 ⫽.19, strong], physical functioning [F(2, 97)⫽5.31, p⬍.01, 2 ⫽.10, moderate], bodily pain [F(2, 97)⫽3.85, p⬍.05, 2 ⫽.07, moderate], role limitations due to emotional problems [F(2, 97)⫽3.34, p⬍.05, 2 ⫽.06, small], and mental health [F(2, 97)⫽3.23, p⬍.05, 2 ⫽.06, small]. These findings suggest that the DETERMINE checklist is a useful nutritional screening tool for predicting quality of life of older Chinese Americans, especially when monitoring social and physical functionality. It is recommended that dietetics professionals address nutritional risk issues by promoting the social and physical functionality of their clients. Funding Disclosure: This project was supported in part by a grant (90AM2768) from the Administration on Aging, US Department of Health and Human Services, Washington, DC
Title: A RESTING METABOLIC RATE EQUATION INCLUDING LEAN BODY MASS PROVIDES A BETTER PREDICTION IN AFRICAN-AMERICAN FEMALES Author(s): M. W. Valliant,1 D. K. Tidwell,2 S. G. Owens,3 L. F. Chitwood3; 1Family and Consumer Sciences, The University of Mississippi, University, MS, 2Department of Food Science, Nutrition and Health Promotion, Mississippi State University, Starkville, MS, 3 Health, Exercise Science and Recreation Management, The University of Mississippi, University, MS Learning Outcome: Understand the development and accuracy of a new resting metabolic rate equation appropriate for minority populations. Text: An equation including fat free mass (FFM) for predicting RMR in African-American (AA) females was developed. The objective was to compare the prediction accuracy of this new equation and three previously published equations Harris-Benedict, FAO, and University of Memphis against the indirect calorimetry measured RMR (mRMR). One hundred AA female subjects, ages 18 to 40, with various body mass indices participated in this study. Fifty subjects were randomly selected for developing the new equation and fifty subjects to test all four equations. Subjects’ height (ht), weight (wt), and age were obtained and fat-mass (FM) and fat-free mass (FFM) were measured by bioelectrical impedance. A forward stepwise multiple regression analysis was performed with mRMR as the dependent variable and age, ht, wt, FM, and FFM serving as independent variables to develop the following new equation: RMR⫽460.61⫹2.22FFM⫹8.189ht⫹3.139age⫹2.082FM⫹1.685wt SEE 126.4. The mean mRMR was compared to the mean of predicted RMR (pRMR) for each equation using ANOVA. When significant F values were obtained, Tukey’s post hoc test was used to identify significant differences between the means. The new equation’s pRMR was the only one that did not differ significantly from mRMR and had the largest R2 (.59) and smallest SEM (26.64). When selecting a prediction equation to estimate RMR, it is imperative to select the equation that provides the best estimate of RMR for the population considered. It appears that this new equation with the inclusion of FM and FFM is more accurate than previous equations in estimating RMR in AA females. Funding Disclosure: This research was funded in part by the School of Applied Sciences, The University of Mississippi