The Nutrient Composition of Some Cooked Dishes Eaten in Britain: A Supplementary Food Composition Table

Wiles, S. J.; Nettleton, P. A.; Black, A.; Paul, Alison; Bingham, S; Nelson, Michael; Ravenscroft, Catherine

doi:10.3109/09637488009143440

Cited by 56 publications

(38 citation statements)

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“…The intake data were coded for analysis, using the IFRN database, which is comprised mainly of nutrient data from The Composition of Foods' (Paul & Southgate, 1978) but supplemented with additional nutrient data (Wiles et al, 1980;Holland et al, 1988;Holland et al, 1989;Tan et al, 1985). Manufacturers' data for commercially produced baby foods/drinks were also entered into the database for this study.…”

Section: Assessment Of Dietary Intakementioning

confidence: 99%

Factors affecting iron stores in infants 4–18 months of age

et al. 1997

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Objectives: To determine the effects of dietary, physiological or environmental factors on body iron levels in infants aged 4±18 months. Design: The daily iron intake of the infants was measured from a diet history obtained by interview using a standardised question sheet, previously validated against weighed intake (minimum 3 days) in an independent sample of 8 and 18 month old infants. Capillary blood samples were analyzed for haemoglobin, mean cell volume, haematocrit, zinc protoporphyrin and plasma ferritin concentration. Ferritin values were log-transformed prior to analysis to give a better approximation to the normal distribution and forward stepwise multiple linear regression was carried out using SPSS. Setting: The city of Norwich, UK and some of its suburbs. Subjects: One hundred and eighty-one healthy infants in age groups 4, 8, 12 and 18 months. Results: Main determinants of iron stores in the 4 month old infants were birth weight ( ve (P`0.001)) and body weight (7ve (P`0.005)). In the 8 month old infants intake of cow's milk (7ve (P`0.05)), belonging to a smoking household (7ve (P`0.05)) and quantity of commercial babyfood consumed ( ve (P`0.05)) were signi®cant. In this age group there was a gender effect (girls b boys (P`0.01)) and the gender effect remained at 12 months (girls b boys (P`0.05)), but at 18 months only non-haem iron intake was a signi®cant factor (7ve (P`0.05)). Conclusions: At 4 months of age birth weight and body weight exert the greatest in¯uence on iron stores, whereas by 8 months components of the weaning diet have an effect (commercial babyfood ( ve), cow's milk (7ve)); there is also a gender effect (girls b boys), possibly re¯ecting the different growth rate between boys and girls. At 12 and 18 months the only signi®cant factors are gender (girls b boys) and non-haem iron intake (7ve) respectively. Sponsorship: Ministry of Agriculture, Fisheries and Food and the Biotechnology and Biological Sciences Research Council.

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Section: Assessment Of Dietary Intakementioning

confidence: 99%

Factors affecting iron stores in infants 4–18 months of age

et al. 1997

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“…Portions were quantified by verbal descriptions in terms of familiar volumes and sizes and by reference to photographs derived from a Swedish atlas of food portions. The publication of Crawley (1988) (Paul & Southgate, 1978) and supplements (Holland et al 1988(Holland et al , 1989) with additional recipes (Wiles et al 1980) and manufacturers' information.…”

Section: Dietary Assessmentmentioning

confidence: 99%

Validation of dietary intakes measured by diet history against24 h urinary nitrogen excretion and energy expenditure measuredby the doubly-labelled water method in middle-aged women

Black¹,

Welch²,

Bingham³

2000

Br J Nutr

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A diet history method for estimating energy and N intakes was validated against 24 h urinary N excretion and energy expenditure measured by the doubly-labelled water (DLW) method. Fortyeight women aged 50-65 years were studied over 1 year. Weighed diet records from 4 d and two 24 h urine collections, for measurement of urinary N excretion, were obtained in each of four seasons. At the end of the year, a diet history was obtained, BMR was measured by whole-body calorimetry, and, in sixteen women, total energy expenditure (EE) was measured by DLW. Energy intake (EI) and N intake (NI) were calculated using food tables. Using weighed records and diet history respectively mean NI were 11⋅21 (SD 2⋅09) g and 11⋅47 (SD 2⋅40) g (NS) and EI were 8⋅08 (SD 1⋅54) MJ and 8⋅20 (SD 1⋅86) MJ (NS). Mean urine N : NI and EI : BMR values indicated bias to under-reporting by weighed record and diet history techniques in some individuals, but there was no significant difference between these measures at the group level. The Pearson correlation coefficient (r) for urine N v. NI was 0⋅81 for the weighed record and 0⋅38 for the diet history. The correlation of EE v. EI was r 0⋅48 for weighed record and r 0⋅11 for diet history. In this study the diet history gave the same estimate of mean intake, but the weighed record appeared to perform better in ranking individuals. Diet history: Diet record: ValidationThe diet history method of assessing dietary intake is favoured for two reasons. First, as a retrospective questionnaire method, it places less burden on subjects than do prospective diet records. Second, it is believed to obtain a better measure of long-term habitual intake than diet records, which, of necessity, record intake on a limited number of days. The debate over the respective merits of the weighed diet record and the diet history is a long one and many studies over several decades have compared their relative validity. On balance the diet history tends to obtain higher mean energy intakes (EI) (see reviews by Bingham, 1987;Black et al. 1991). However, without external validation such studies have been unable to reach a firm conclusion as to which, if either, is valid in absolute terms.A valid dietary assessment should give an estimate of mean intake that is close to the true intake and also be able to rank individuals correctly for intake within acceptable limits of precision. The two requirements do not necessarily go together. For example, a dataset of valid 24 h recalls would give a valid estimate of mean intake but could not rank individuals correctly for habitual intake. A diet record of sufficient length to measure habitual intake might rank individuals correctly but give an invalid estimate of mean intake due to systematic bias across all subjects. If random errors are large and if systematic bias is variable across individuals, then ranking will also be poor. Studies of relative validity indicate whether one method gives a higher intake than another, and comparison with expected energy requirements can help determine ...

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“…Nutrient intake was calculated using the fourth edition of McCance & Widdowson's The Composition of Foods (Paul & Southgate, 1978) and the Dunn Nutrition Centre's supplementary database of additional recipes (Wiles et al, 1980) and manufacturers' information. The third (Holland et al, 1988) and fourth (Holland et al, 1989) supplements to the fourth edition were additionally used to calculate nutrient intake from the mens' data.…”

Section: Recruitment: Menmentioning

confidence: 99%

“…Diet records were analysed using McCance & Widdowson's The Composition of Food, fourth edition (Paul & Southgate, 1978) with additional recipes (Wiles et al, 1980) and manufacturers' information.…”

Section: Recruitment: Menmentioning

confidence: 99%

Validation of dietary intakes of protein and energy against 24 hour urinary N and DLW energy expenditure in middle-aged women, retired men and post-obese subjects: comparisons with validation against presumed energy requirements

et al. 1997

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Objectives: To compare validation of reported dietary intakes from weighed records against urinary nitrogen excretion and energy expenditure measured by DLW, and to examine the utility of the Goldberg cut-off for EI:BMR in the identi®cation of under-reporters. Design: Energy (EI) and nitrogen (protein) intake (NI) were measured by 16 d of weighed diet records collected over 1 y. They were validated against urinary nitrogen excretion in 5±8 (mean 6.0) 24 h urine collections and total energy expenditure (EE) measured by doubly labelled water (DLW). Basal metabolic rate (BMR) as measured by whole body calorimetry in women or bedside ventilated hood (Deltatrac) in men. Individual subjects were identi®ed as under-reporters if Urine N:NI was b 1.00 or if EI:EE was`0.79. The agreement between the two ratios in detecting under-reporting was examined. The results from the direct validation by DLW were also compared with validation using the Goldberg cut-off for EI:BMR . Subjects: Eighteen women aged 50±65 y and 27 men aged 55±87 y were selected from participants in two larger dietary surveys as representing the full range of dietary reporting as measured by Urine N:NI. Data from a previous study of 11 post-obese subjects were also included. Results: The two ratios, Urine N:NI and EI:EE, were signi®cantly related (r 70.48, P`0.01). Using the above cut-offs, seven (4F, 3M) subjects were identi®ed as under-reporters by both methods, one (1M) by Urine N:NI only and 8 (3F, 5M) by EI:EE only. There was close agreement in post-obese subjects where 6 subjects showed a substantial degree of under-reporting by both methods (r 70.87, P`0.001). The correlation between direct validation by DLW and EI:BMR est was 0.65 (P`0.001). Some limitations of the Goldberg cutoff for identifying individual under-reporters were demonstrated. Conclusions: EI:EE provides an estimate of the degree of under-reporting of energy at the group and individual level. Urine N:NI identi®es under-reporting of protein intake and the most obvious under-reporters of energy, but is probably of lesser value in estimating the overall degree of under-reporting of energy at group level. Good validation by EI:BMR depends on knowledge of physical activity at both group and individual level. However, the correlation of 0.65 between EI:EE and EI:BMR est suggests that EI:BMR could be usefully incorporated into analysis of data from epidemiological studies. Validation measures consisting of at least predicted EI:BMR ratios and urinary measures should be incorporated into dietary surveys.

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The Nutrient Composition of Some Cooked Dishes Eaten in Britain: A Supplementary Food Composition Table

Cited by 56 publications

References 0 publications

Factors affecting iron stores in infants 4–18 months of age

Factors affecting iron stores in infants 4–18 months of age

Validation of dietary intakes measured by diet history against24 h urinary nitrogen excretion and energy expenditure measuredby the doubly-labelled water method in middle-aged women

Validation of dietary intakes of protein and energy against 24 hour urinary N and DLW energy expenditure in middle-aged women, retired men and post-obese subjects: comparisons with validation against presumed energy requirements

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