Literature DB >> 23364487

Under-reporting of energy intake in elderly Australian women is associated with a higher body mass index.

X Meng1, D A Kerr, K Zhu, A Devine, V A Solah, J Wright, C W Binns, R L Prince.   

Abstract

OBJECTIVES: Identify the extent of under-reporting of energy intake and the characteristics associated with implausible intakes in elderly women.
DESIGN: Dietary intake was assessed using a 3-day weighed food record. Protein intake was validated by 24-hour urinary nitrogen. To examine under-reporting, participants were grouped according to their energy intake and compared to the Goldberg cut-off equation. Logistic regression was performed to assess the influence of body mass index (BMI) and social-demographic factors on under-reporting.
SETTING: Community dwelling elderly women from Perth, Western Australia. PARTICIPANTS: 217 elderly women aged 70-80 years.
RESULTS: Under-reporters had a higher physical activity level (p<0.001) compared with acceptable-reporters. The under-reporters also had a higher body weight (p=0.006), body mass index (BMI) (p=0.001), waist (p=0.011), hip circumference (p<0.001), whole body fat mass (p<0.001) and percentage body fat (p<0.001) than acceptable-reporters. Under-reporters had a significantly lower intakes of protein, fat, carbohydrate and alcohol (p<0.001) and fewer reported food items, compared with acceptable reporters. However, 24-hour urinary nitrogen was only marginally different between the two groups (p=0.053). Participants with a higher BMI were more likely to under-report their energy intake (BMI=25-29.9: odds ratio=2.98[95% CI=1.46-6.09]; BMI≥30: 5.84[2.41-14.14]).
CONCLUSION: Under-reporting energy intake in elderly women was associated with a higher BMI, body fat and higher self-reported physical activity levels. A higher BMI (≥25) appears to be most significant factor in determining if elderly women will underreport their food intake and may be related to body image. These results have implications for undertaking surveys of food intake in elderly women.

Entities:  

Mesh:

Substances:

Year:  2013        PMID: 23364487     DOI: 10.1007/s12603-012-0382-8

Source DB:  PubMed          Journal:  J Nutr Health Aging        ISSN: 1279-7707            Impact factor:   4.075


  41 in total

1.  Underreporting of habitual food intake is explained by undereating in highly motivated lean women.

Authors:  A H Goris; K R Westerterp
Journal:  J Nutr       Date:  1999-04       Impact factor: 4.798

Review 2.  Validity of the assessment of dietary intake: problems of misreporting.

Authors:  Klaas R Westerterp; Annelies H C Goris
Journal:  Curr Opin Clin Nutr Metab Care       Date:  2002-09       Impact factor: 4.294

3.  The sensitivity and specificity of the Goldberg cut-off for EI:BMR for identifying diet reports of poor validity.

Authors:  A E Black
Journal:  Eur J Clin Nutr       Date:  2000-05       Impact factor: 4.016

4.  Assessing the effect of underreporting energy intake on dietary patterns and weight status.

Authors:  Regan L Bailey; Diane C Mitchell; Carla Miller; Helen Smiciklas-Wright
Journal:  J Am Diet Assoc       Date:  2007-01

5.  Characteristics of women who frequently under report their energy intake: a doubly labelled water study.

Authors:  F B Scagliusi; E Ferriolli; K Pfrimer; C Laureano; C S F Cunha; B Gualano; B H Lourenço; A H Lancha
Journal:  Eur J Clin Nutr       Date:  2009-07-15       Impact factor: 4.016

6.  Literacy and body fatness are associated with underreporting of energy intake in US low-income women using the multiple-pass 24-hour recall: a doubly labeled water study.

Authors:  R K Johnson; R P Soultanakis; D E Matthews
Journal:  J Am Diet Assoc       Date:  1998-10

7.  Urine nitrogen as an independent validatory measure of dietary intake: a study of nitrogen balance in individuals consuming their normal diet.

Authors:  S A Bingham; J H Cummings
Journal:  Am J Clin Nutr       Date:  1985-12       Impact factor: 7.045

8.  Misreporting of energy intake in the elderly using doubly labeled water to measure total energy expenditure and weight change.

Authors:  Danit R Shahar; Binbing Yu; Denise K Houston; Stephen B Kritchevsky; Anne B Newman; Deborah E Sellmeyer; Frances A Tylavsky; Jung Sun Lee; Tamara B Harris
Journal:  J Am Coll Nutr       Date:  2010-02       Impact factor: 3.169

9.  Biased over- or under-reporting is characteristic of individuals whether over time or by different assessment methods.

Authors:  A E Black; T J Cole
Journal:  J Am Diet Assoc       Date:  2001-01

10.  The accuracy of the Goldberg method for classifying misreporters of energy intake on a food frequency questionnaire and 24-h recalls: comparison with doubly labeled water.

Authors:  J A Tooze; S M Krebs-Smith; R P Troiano; A F Subar
Journal:  Eur J Clin Nutr       Date:  2011-11-30       Impact factor: 4.016

View more
  11 in total

1.  Identification of dietary patterns associated with blood pressure in a sample of overweight Australian adults.

Authors:  S Anil; K E Charlton; L C Tapsell; Y Probst; R Ndanuko; M J Batterham
Journal:  J Hum Hypertens       Date:  2016-03-24       Impact factor: 3.012

2.  Assessment of energy intake in women with chronic obstructive pulmonary disease: a doubly labeled water method study.

Authors:  N Farooqi; F Slinde; L Håglin; T Sandström
Journal:  J Nutr Health Aging       Date:  2015-05       Impact factor: 4.075

3.  Usability of a smartphone food picture app for assisting 24-hour dietary recall: a pilot study.

Authors:  Nobuko Hongu; Benjamin T Pope; Pelin Bilgiç; Barron J Orr; Asuka Suzuki; Angela Sarah Kim; Nirav C Merchant; Denise J Roe
Journal:  Nutr Res Pract       Date:  2014-12-12       Impact factor: 1.926

4.  Assessment of mineral intake in the diets of Polish postmenopausal women in relation to their BMI-the RAC-OST-POL study : Mineral intake in relation to BMI.

Authors:  Dominika Głąbska; Dariusz Włodarek; Aleksandra Kołota; Aleksandra Czekajło; Bogna Drozdzowska; Wojciech Pluskiewicz
Journal:  J Health Popul Nutr       Date:  2016-08-02       Impact factor: 2.000

5.  Effect of Fibre Supplementation on Body Weight and  Composition, Frequency of Eating and Dietary  Choice in Overweight Individuals.

Authors:  Vicky A Solah; Deborah A Kerr; Wendy J Hunt; Stuart K Johnson; Carol J Boushey; Edward J Delp; Xingqiong Meng; Roland J Gahler; Anthony P James; Aqif S Mukhtar; Haelee K Fenton; Simon Wood
Journal:  Nutrients       Date:  2017-02-16       Impact factor: 5.717

6.  Dietary Intake and Beliefs of Pregnant Women with Gestational Diabetes in Cape Town, South Africa.

Authors:  Stephanie M Krige; Sharmilah Booley; Naomi S Levitt; Tawanda Chivese; Katherine Murphy; Janetta Harbron
Journal:  Nutrients       Date:  2018-08-28       Impact factor: 5.717

7.  Association between progranulin serum levels and dietary intake.

Authors:  Bruna Bellincanta Nicoletto; Roberta Aguiar Sarmento; Elis Forcellini Pedrollo; Thaiana Cirino Krolikowski; Luis Henrique Canani
Journal:  PLoS One       Date:  2018-08-17       Impact factor: 3.240

8.  Time trends in nutrient intake and dietary patterns among five birth cohorts of 70-year-olds examined 1971-2016: results from the Gothenburg H70 birth cohort studies, Sweden.

Authors:  Jessica Samuelsson; Elisabet Rothenberg; Lauren Lissner; Gabriele Eiben; Anna Zettergren; Ingmar Skoog
Journal:  Nutr J       Date:  2019-11-06       Impact factor: 3.271

9.  Validation of a pre-coded food diary used among 60-80 year old men: comparison of self-reported energy intake with objectively recorded energy expenditure.

Authors:  Tonje H Stea; Lene F Andersen; Gøran Paulsen; Ken J Hetlelid; Hilde Lohne-Seiler; Svanhild Adnanes; Thomas Bjørnsen; Svein Salvesen; Sveinung Berntsen
Journal:  PLoS One       Date:  2014-07-14       Impact factor: 3.240

10.  The effects of strength training on cognitive performance in elderly women.

Authors:  André de Camargo Smolarek; Luis Henrique Boiko Ferreira; Luis Paulo Gomes Mascarenhas; Steven R McAnulty; Karla Daniele Varela; Mônica C Dangui; Marcelo Paes de Barros; Alan C Utter; Tácito P Souza-Junior
Journal:  Clin Interv Aging       Date:  2016-06-01       Impact factor: 4.458

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.