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4807.0.30.001 - Microdata: National Nutrition Survey, 1995 Quality Declaration 
Latest ISSUE Released at 11:30 AM (CANBERRA TIME) 14/06/2013   
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A list of data items available for use with the CURF, including relevant population and classification details, can be found on the Downloads tab.

Some data items directly reflect responses to individual questions contained in the survey questionnaire while others may have been derived from responses to two or more questions. Because of the volume and complexity of the derivations, and the need to understand the logic and intentions underlying them, the derivations have not been presented in this documentation. If you have any queries about the derivation of particular items, please contact the Health Section email: Listing of the SAS code used to derive items is available on request.


SEIFA index of relative social disadvantage

The Index of Relative Social Disadvantage was derived from the 1991 Census. It assigns an index to geographic areas based on socio-economic variables such as economic resources of households, education, occupation, family structure and ethnicity. It is one of five indexes derived by the ABS from the 1991 Census to assist in the analysis of socio-economic characteristics. Details of the indexes are contained in Census: Socio-Economic Indexes for Areas.

Each person on the file was allocated an index score, based on the Collectors District (CD) in which they were enumerated (in most cases their usual residence). The score was grouped by quintile. The quintile relates to the area in which the person was enumerated, not to the socio-economic characteristics of the individual. A high quintile score suggests that the area has fewer families of low income and fewer people with little training and in unskilled occupations, whereas a low score suggests that the area has more families and people of this type.

Equivalent income

An indicator of equivalent income for income units has also been placed on each person record on the CURF. The indicator relates to the decile of equivalent income of the income unit to which that person belongs. This has been calculated from the NHS income data collected from all people within a household, and then applied to NNS participants.

The indicator has been derived by summing the individual dollar income of all members of the income unit, and then applying factors from the Henderson Simplified Equivalence Scales. These factors vary according to the composition of the income unit and the labour force status of adult members of the unit. The resulting dollar equivalent income of the unit was then classified by decile. The adoption of the Henderson Simplified Equivalence Scales in this derivation does not necessarily imply ABS endorsement of the scale.

Equivalent income and household income were derived from all income units and households. Approximately 260 NNS participants came from households which did not have complete participation in the NHS (see p. 13). Household and equivalent income has been derived for these households, based on those household members who participated in the NHS. Incomplete households are those with an ABSHID of 20818 or greater.

Food codes

Foods and beverages consumed in the 24-hour dietary recall were allocated eight-digit codes to uniquely identify each food. The first four digits can be used to categorise foods and beverages into a hierarchical classification system. (This classification has been published in the NNS Users' Guide.) Digits five to seven were used to uniquely identify a food. The last digit of the eight-digit food code indicates whether the food is a modifiable recipe (value of '2') or a single item food/unmodifiable recipe (value of '1'). The file ACBDES.TXT contains a full listing of the food codes and their descriptions (see Appendix 1).

For example, the code for pear juice is 11312801. The first two digits of '11' indicates the fruit juice is a non-alcoholic beverage, the first three digits of '113' indicate that it is a fruit and vegetable juice or drink, and the first four digits of '1131' indicate that it is a single fruit juice. The last digit of '1' indicates that it is a single item food/unmodifiable recipe.

There are two fields which indicate the food code. Most food records will contain an 8-digit code in the field FOODCOD1. However, modified recipes have a 6-digit code in FOODCOD1 and then have the 8-digit code of the base recipe in FOODCOD2. Recipes were generally only modified if the fat or fibre content in the individual's recipe differed significantly from the existing recipe. For most purposes, the 8-digit code of modified recipes is suitable for categorising foods as recipe modifications did not alter the nature of the food/beverage. FOODCOD1 and FOODCOD2 can be combined into a new field NEWCODE using the following criteria:

IF FOODCOD1 < 10,000,000 then NEWCODE=FOODCOD2;

Plain drinking water

The 24-hour recall collected information on each food and beverage consumed the previous day except for plain drinking water (i.e. tap or uncarbonated bottled water with nothing added). The amount of plain drinking water consumed the previous day was collected as a single amount at the end of the 24-hour recall. Additional information, such as eating occasion or time of consumption, was not collected for plain drinking water. Each person who reported consuming plain drinking water had an extra food/nutrition record added, which contains FOODCOD1 equal to 77777777 and PSZGRAMS equal to the amount drank. No adjustment has been made to the field MOISTUR. Their person record also contains the amount of plain drinking water in the field AMTWATER, and plain drinking water has not been added to TMOISTUR and KMOISTUR.

Combination foods

Combination foods are those where two or more components are combined, usually just prior to consumption, and eaten as a single unit (e.g. tea with sugar and milk). Each member of a combination has a separate food record on the CURF, with these food records having the same value in the field CMBSEQNO (combination sequence number). All foods in the first combination consumed by a person have a CMBSEQNO of 1, foods in the second combination have a CMBSEQNO of 2 and so on.

Portion sizes

The field PSZGRAMS on the food record contains the amount of food/beverage consumed. This amount was calculated during data entry from several fields which contained information about the amount eaten.


HOWMANY Amount preparedAmount of the measure or gram weight description that was prepared.
MEASURE Allowed food measureFood measures allowed for the food, from the set of 14 possible options for all foods. The system calculated PSZGRAMS from the most relevant gram weight description for that food. Conversion factors were applied if the allowed food measure did not directly match a gram weight description (e.g. 1 cup (250 ml)=12.5 tablespoons (20ml)=50 teaspoons (5ml)).
NOEATENAmount eatenAmount eaten, as a proportion of the amount prepared.
DIMENSN1Dimension 1Used if the following ruler measurements were recorded in the
DIMENSN2Dimension 2MEASURE field:
- RR (ruler rectangle) — used for rectangular servings of food such as cake and cheese.
- RR (ruler rectangle) — used for rectangular servings of food such as cake and cheese.
- RC (ruler circumference) — used for flat circular foods such as pikelets or cylindrical foods such as a slice of meat roll.
- RW (ruler wedge) — used for wedge shaped foods (e.g. piece of pie or pizza).
- RT (ruler triangle) — used for triangular foods or wedges where the diameter and fraction of whole was not known.
DIMENSN3Dimension 3The dimensions are in centimetres and contain the following information:
- Dimension 1 contains the length (for RR and RT) or circumference (RC and RW).
- Dimension 2 contains the width (RR and RT) or the fraction the piece represents of the whole (RW).
- Dimension 3 contains the height/thickness.
GWTDSCNOGram weight description numberThe gram weight description field contains codes which link different types of measures (e.g. cup, litre, serving not specified) to an amount in grams for particular food codes.
GUIDELINGuideline numberThis is used when an unknown measure was reported. There were several options available (e.g. handful, squirt and small bowl). The system applied conversion factors which either represented the guideline description in terms of allowed food measures (e.g. a 'swallow' is equal to one tablespoon) or gram weight descriptions (e.g. a large serving is equal to 1.5 times the serving not specified amount). (Serving not specified was the answer coded when a respondent could not recall the amount consumed and the food was eaten as a single item)

Some biscuits and confectionery used subcodes to derive gram consumption. Subcodes indicate specific foods associated with a particular generic food code. These foods have the same nutrient profiles but may have different measure descriptions and gram weights.

Nutrient derivation

The Australia New Zealand Food Authority (ANZFA) developed a customised nutrient composition database to enable the 24-hour food records to be converted into nutrient intakes. The database was developed in collaboration with HFS and updated in tandem with the coding of the survey food intakes.

The nutrient composition database was applied to the food intake data and the amount of each nutrient consumed per food per person was calculated (this is at the end of each food record). In addition, the following items were calculated as totals across all foods consumed by each individuals and are on the person record:
  • amount of each nutrient consumed per person;
  • nutrient density per 1000 kJ energy for each nutrient (except energy) per person. This was calculated as: total nutrient / total energy * 1000; and
  • Percent contribution to total energy per person per day for protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, carbohydrate, total sugars, starch and alcohol. The energy from each of these nutrients was estimated by multiplying each gram of protein, fats, carbohydrates and alcohol by a conversion factor to determine the kilojoules of energy generated. The conversion factors are set out below. The energy from each of the listed nutrients was divided by total energy per day and multiplied by 100.

    Energy from protein17kJ per gram
    Energy from fats37kJ per gram
    Energy from carbohydrate17kJ per gram of starch and
    16kJ per gram of sugar
    Energy from alcohol29kJ per gram

Acknowledgment of British nutrient data

Official permission was obtained for the use of up to 4,000 total folate values and general nutrient data for up to 1,000 foods from the UK Ministry of Agriculture, Fisheries and Food and the Royal Society of Chemistry. The following acknowledgment should be provided for any use of the nutrient intake data: "Data from the The Composition of Foods, 5th Edition, and its supplements as produced with the permission of The Royal Society of Chemistry and the Controller of Her Majesty's Stationary Office".

The Food Frequency Questionnaire (FFQ) was offered to people aged 12 years and over on a voluntary basis. The FFQ data has been stored on the person record. There were 9,096 people who returned a usable FFQ and 237 people who returned an unusable FFQ. A person's FFQ was classified as unusable if more than 20 out of the 107 food-lines had a '0' (which means they either didn't respond to the particular food line or gave an unusable response). These unusable records are on the CURF but have not been included in any estimates produced by the ABS.

If you want to analyse people who completed a usable FFQ, then select cases where FFQFLAG=3. A separate set of expansion factors, or weights, was calculated for the FFQ, as participation in the FFQ was voluntary. See pages 26–29 for more information on how to use the weights.

All decimal places have been removed from items on the CURF by multiplying the decimal place out. This needs to be reversed when conducting analysis on these items. The table below details the fields affected and what number the field needs to be divided by.


Divide by 100 (Food record) PSZGRAMS
Divide by 1,000 (Food record) ALCOHOLIRONPOTASSITOTMFAT
Divide by 10,000 (Person record)FFQNSFWT FFQSFWT FFQWT
Divide by 10,000 (Food record)DIMENSN1DIMENSN3 HOWMANY NOEATEN
Divide by 100,000BODYMIXN
Divide by 1,000,000WHRATIOBMR


A large number of variables have codes which indicate either that: the question was not applicable to the respondent (e.g. pregnancy status for males); or the respondent did not answer that particular question. In most cases, these are categorical variables. However, there are some continuous variables on the NNS data files (e.g. height) that used these codes. When calculations such as means, medians or percentiles are done on these variables, you need to exclude the people with not stated or not applicable codes. The variables affected are outlined below.

AMTWATER Not stated=9999
BMR Not applicable=0
Not stated=88.888888(b) or 99.999999
BODYMIXN Not applicable=0
Not stated =88.88888(b) or 99.99999
Not applicable=0
Not stated=999
EIBMR Not applicable=0
Not stated=8.888(b) or 9.999
HEIGHTHNot applicable=0
Not stated=999
Not applicable=0
Not stated=999.9
HGHTAVE Not applicable=0
Not stated=999.99
Not applicable=0
Not stated=999.9
HIPAVE Not applicable=0
Not stated=999.99
PERSONWTNot applicable=0
Not stated=888.8 (b) or 999.9
RAWBMIHNot applicable=0
Not stated=99.99
Not applicable=0
Not stated=999
Not applicable=0
Not stated=999.9
WAISTAVENot applicable=0
Not stated=999.99
WEIGHTHNot applicable=0
Not stated=999
WHRATIONot applicable=0
Not stated=9.999999
Not applicable=88.88
Not stated=99.99
ZWTHT Not applicable=8.88
Not stated=9.99

(a) Code when decimal place is restored to the variable.
(b) Person over the limit of the scales used to measure weight.

The item DAYOFWEE indicates which day of week (Sunday–Saturday) the interview was conducted on. The 24-hour recall collected information on intake on the day prior to interview. Therefore, the intake day is one day before the interview day. For example, if the interview day was Monday, then the intake day was Sunday.
The item MINTAKE indicates the month of intake, rather than the month of interview.

Approximately 1,500 people completed the Day 2 NNS. The ABS has used this data to produce a series of factors that can be applied to Day 1 intake to remove the effect of within-person variation on the distribution of one day intakes. The adjusted distribution provides a better indication of the 'usual' distribution of intakes in the population. It is therefore more appropriate for estimating the likelihood of nutrient deficiency or excess in the population when the data are based on only a single day's intake for each person.

A separate set of factors has been produced for each nutrient except alcohol. These factors are in:
  • NUTADJ.TXT, which is a column delimited text file containing the factors for most nutrients; and
  • LOGADJ.TXT, which is a column delimited text file containing the factors for the three forms of vitamin A. These are in the natural log scale.

Each nutrient has three variables or factors:
mean, calculated from the Day 1 sample;
observed standard deviation, calculated from the Day 1 sample; and
between person standard deviation, calculated from the Day 2 sample.

People wishing to use these factors need to merge them onto the NNS Day 1 person record by age and sex. The factors for each nutrient can be applied to the relevant files using the following formula:
Adjusted value= x + (xi – x) * (sb/sobs),
where x is the group mean for the weighted Day 1 sample,
xi is the individual's day 1 intake,
sb is the between person standard deviation, and
sobs is the group standard deviation for the Day 1 sample.

Methodology used to calculate factors

The adjustment factors were calculated for each nutrient except alcohol. Alcohol was excluded from the analysis because of concerns about estimating within-person variation in alcohol intake from only two days' intakes. It was recognised that an adjustment model based on the entire population was not necessarily appropriate for particular sub-groups. Therefore, adjustment classes based on age and sex were used in the analysis. Although it would have been possible to choose groupings appropriate to each separate nutrient, common groupings was used across most nutrients.

Adjustment factors have been calculated for males and females for the following age groups: 2-3 years; 4-7 years; 8-11 years; 12-15 years; 16-18 years; 19-24 years; 25-44 years; 45-64 years; and 65 years and over. The group mean within each of these age by sex groups was calculated from the total weighted Day 1 sample.

However, collapsed age groups were used to calculate the standard deviation values. This was because the between-person standard deviation was calculated from the replicate sample and therefore some cells had insufficient sample for the finer age groups. The collapsed age groups were: 2-11 years; 12-24 years; 25-44 years; 45-64 years; and 65 years and over. Standard deviation was calculated as the collapsed group standard deviation for the Day 1 sample. The between-person standard deviation was calculated as the collapsed group between-person standard deviation for the Day 2 sample.

Between-person variance (s2b) was calculated from the Day 2 sample, using the SAS ANOVA procedure. Person was the independent variable (each person had a Day 1 and a Day 2 record) and nutrient intake was the dependent variable. Between person variance was estimated as: (s2b) = (MSA - MSE)/n, where MSA and MSE are defined according to the table on the following page.

All calculations for vitamin A expressed as retinol equivalents, preformed vitamin A and provitamin A were done on natural log transformed data, because of the particularly skewed nature of their distributions. A value of 5 was added prior to the log transformation, because there were a small number of zero values and logs are defined for only positive non-zero numbers.

Mean1SSMMSM=SSM2 + nσ2α + σ2e
Classesa - 1SSAMSA=SSA(a-1)2α + σ2e
Residual errora(n - 1)SSAMSE=SSE/a(n-1)σ2e

where a is the number of people , n is the number of replicates, N is a*n, μ is the group mean, σ2α is the between person variation and σ2e is the residual or within person sampling error after removing mean and between person effects.
Source: Searle (1971).
Note: SSM, SSA and SST are calculated directly from data collected. SSE is calculated by subtraction.

Structure of the adjustment factors files

The following two column delimited text files have been provided for those people wishing to apply the nutrient adjustment factors to the NNS data file :
  • NUTADJ.TXT — this contains the nutrient adjustment factors for most nutrients; and
  • LOGADJ.TXT — this contains the factors for the three forms of vitamin A.

These need to be applied differently to the other nutrients. As previously outlined, each nutrient except alcohol has three variables or factors: mean; observed standard deviation; and between person standard deviation. People wishing to use these factors need to merge them onto the NNS Day 1 person record by age and sex.

Note that the factors for the three forms of vitamin A are in the natural log scale. To apply the adjustment factors to the three forms of vitamin A, the following steps should be followed:

1. Add 5 to recorded intakes (to make all intakes non zero numbers).
2. Log transform (base e) the intakes.
3. Apply the factors.
4. Convert the adjusted intakes back into the original scale (ex), and then subtract 5.

Calculations for all other nutrients were done in their original scale.Contents of NUTADJ.TXT


AGEYEARAge (years)
ENERMEANEnergy mean
ENERSOBSEnergy standard deviation
ENERSBETEnergy between-person standard deviation
ZINCSOBSZinc standard deviation
ZINCSBETZinc between-person standard deviation
PROTMEANProtein mean
PROTSOBSProtein standard deviation
PROTSBETProtein between-person standard deviation
TFATMEANTotal fat mean
TFATSOBSTotal fat standard standard deviation
TFATSBETTotal fat between-person standard deviation
SFATMEANSaturated fat mean
SFATSOBSSaturated fat standard deviation
SFATSBETSaturated fat between-person standard deviation
MFATMEANMonounsaturated fat mean
MFATSOBSMonounsaturated fat standard deviation
MFATSBETMonounsaturated fat between-person standard deviation
PFATMEANPolyunsaturated fat mean
PFATSOBSPolyunsaturated fat standard deviation
PFATSBETPolyunsaturated fat between-person standard deviation
CHOLMEANCholesterol mean
CHOLSOBSCholesterol standard deviation
CHOLSBETCholesterol between-person standard deviation
CARBMEANCarbohydrate mean
CARBSOBSCarbohydrate standard deviation
CARBSBETCarbohydrate between-person standard deviation
STARMEANStarch mean
STARSOBSStarch standard deviation
STARSBETStarch between-person standard deviation
SUGMEANSugar mean
SUGSOBS Sugar standard deviation
SUGSBETSugar between-person standard deviation
DFIBMEANDietary fibre mean
DFIBSOBSDietary fibre standard deviation
DFIBSBETDietary fibre between-person standard deviation
THIAMEANThiamin mean
THIASOBSThiamin standard deviation
THIASBETThiamin between-person standard deviation
RIBOMEANRiboflavin mean
RIBOSOBSRiboflavin standard deviation
RIBOSBETRiboflavin between-person standard deviation
NIAEMEANNiacin equivalents mean
NIAESOBSNiacin equivalents standard deviation
NIAESBETNiacin equivalents between-person standard deviation
NIAPMEANPreformed niacin mean
NIAPSOBSPreformed niacin standard deviation
NIAPSBETPreformed niacin between-person standard deviation
NIADMEANDerived niacin mean
NIADSOBSDerived niacin standard deviation
NIADSBETDerived niacin between-person standard deviation
FOLMEANFolate mean
FOLSOBSFolate standard deviation
FOLSBETFolate between-person standard deviation
VITCMEANVitamin C mean
VITCSOBVitamin C standard deviation
VITCSBETVitamin C between-person standard deviation
CALMEANCalcium mean
CALSOBS Calcium standard deviation
CALSBET Calcium between-person standard deviation
PHOSMEAN Phosphorous mean
PHOSSOBS Phosphorous standard deviation
PHOSSBETPhosphorous between-person standard deviation
MAGNMEAN Magnesium mean
MAGNSOBS Magnesium standard deviation
MAGNSBET Magnesium between-person standard deviation
IRONMEAN Iron mean
IRONSOBS Iron standard deviation
IRONSBET Iron between-person standard deviation
POTMEAN Potassium mean
POTSOBS Potassium standard deviation
POTSBET Potassium between-person standard deviation
MOISMEAN Moisture (incl plain water) mean
MOISSOBS Moisture (incl plain water) standard deviation
MOISSBET Moisture (incl plain water) between-person standard deviation

Contents of LOGADJ.TXT


AGEYEARAge (years)
MNVITAL(a)Vitamin A expressed as retinol equivalents mean
SDVITAL(a)Vitamin A expressed as retinol equivalents standard deviation
SBVITAL(a)Vitamin A retinol equivalents between-person standard deviation
MNAPREL(a)Preformed vitamin A mean
SDAPREL(a)Preformed vitamin A standard deviation
SBAPREL(a)Preformed vitamin A between-person standard deviation
MNAPROL(a)Provitamin A mean
SDAPROL(a)Provitamin A standard deviation
SBAPROL(a) Provitamin A between-person standard deviation

(a) These factors are in the natural log scale. They need to be applied to nutrient intakes also in the natural log scale (with a constant of 5 added to all values to make all numbers non-zero), and the inverse log performed on the adjusted intakes after the adjustment has been calculated.

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