Acute sickness
An illness or injury which caused the informant to cut down on any of the things he or she usually does about the house, at work or school or in his or her free time (in the two weeks prior to the interview).
Age standardisation
Age standardisation has been extensively used in this report in order to enable groups to be compared after adjusting for the effects of any differences in their age distributions.
When proportions are compared across different sub-groups in respect of a variable on which age has an important influence, any differences in age distributions between these sub-groups are likely to affect the observed differences in the proportions of interest. The objective of the direct age standardisation procedure used in this report was to enable proportions to be presented across sub-groups after adjustment for the effects of age. Direct standardisation estimates the values of the proportions of interest in the case where the compared sub-groups have the same age distribution. However, it should be stressed that age-standardised proportions provide only a summary reflecting the average relationship between the variables across all age bands and that age standardisation adjusts only for age and not for other factors that may affect the variable of interest.
Age standardisation was carried out (separately for men and women) by ten-year age groups. The standard population to which the age distribution of sub-groups was adjusted was the mid-1998 population estimates for Scotland. The age-standardised proportion P' was calculated as follows, where Pi is the age specific proportion in age group i and Ni is the standard population size in age group i:
Therefore p' can be viewed as a weighted mean of pi using the weights Ni . Age standardisation was carried out using the age groups: 16-24, 25-34, 35-44, 45-54, 55-64 and 65-74. The variance of the standardised proportion can be estimated by:
Body mass index
Body mass index (BMI) is weight in kilos divided by the square of height in metres. In adults, 'overweight' is defined by values of more than 25.0 but no greater than 30.0; 'Obese' is used to describe values over 30.0. In children, there are no generally accepted reference values.
Cholesterol
An important component of blood lipids transported in plasma. For the purpose
(total and HDL)
of this survey total cholesterol was considered to be raised at a level of 6.5 mmol/l or over. In a normal individual, high density lipoprotein (HDL) constitutes approximately 20% of total plasma cholesterol. HDL-cholesterol was considered low at a level of 0.9 mmol/l or less.
Cotinine
Cotinine is a metabolite of nicotine. It is one of several biological markers that are indicators of smoking (others include carbon monoxide and thiocyanate), and is generally considered the most useful. It can be measured in, among other things, saliva and serum. It has a half-life in the body of between 16 and 20 hours, which means that it will detect regular smoking but may not detect occasional smoking if the last occasion was several days ago. Saliva and serum yield different estimates of cotinine levels, but they are very highly correlated and experiments have enabled serum values to be converted to equivalents of saliva values, so that they can be aggregated in analysis. Using saliva values, anyone with a level of 15 nanograms per millilitre or more is highly likely to be a smoker.
C-reactive protein
C-reactive protein (CRP) is the major protein indicating inflammation activity in acute illness in humans. It is also a marker of cardiovascular risk. No recommendation for a C-reactive protein thresholds appear in the literature so quintile distributions have been presented in this report.
Demi-span
Demi-span is an alternative to height as a measure of skeletal size in elderly people. It is defined as the distance between the mid-point of the sternal notch and the finger roots with the arm outstretched laterally.
Ferritin
Ferritin is the main form in which iron is stored in the liver, spleen and bone marrow. A small fraction of ferritin circulates in the bloodstream and this fraction correlates well with body iron status.
FEV1
Forced Expiratory Volume: the amount of air (in litres) that a subject can breath out of his/her lungs during the first second of an expiration with maximal effort, starting from full inspiration.
FVC
Forced Vital Capacity: the volume of gas (in litres) delivered during an expiration made as forcefully and as completely as possible starting from full inspiration.
Fibrinogen
Fibrinogen is a soluble protein involved in the blood clotting mechanism. Prospective population studies have established that fibrinogen is an independent predictor for ischaemic heart disease and stroke.
Reference: Maresca G, Di Blasio A. Marchioli R, Di Minno G. Measuring plasma fibrinogen to predict stroke and myocardial infarction. Arterioscler Thromb Vasc Biol 1999; 19:1368-1377.
Geometric mean
The geometric mean is a measure of central tendency. It is sometimes preferable to the arithmetic mean, since it takes account of positive skewness in a distribution. The geometric mean of a continuous variable is calculated by taking the antilog of the mean of the logged values.
Haemoglobin
The iron-containing molecule in red blood cells. Low haemoglobin (anaemia) is most commonly caused by iron deficiency.
HDL-cholesterol
See Cholesterol.
Household
A household was defined as one person or a group of people who have the accommodation as their only or main residence and who either share at least one meal a day or share the living accommodation.
Logistic regression
Logistic regression was used to investigate the effect of two or more independent or predictor variables on a two-category (binary) outcome variable. The independent variables can be continuous or categorical (grouped) variables. The parameter estimates from a logistic regression model for each independent variable give an estimate of the effect of that variable on the outcome variable, adjusted for all other independent variables in the model.
Logistic regression models the log 'odds' of a binary outcome variable. The 'odds' of an outcome is the ratio of the probability of its occurring to the probability of its not occurring. The parameter estimates obtained from a logistic regression model have been presented as odds ratios for ease of interpretation.
For continuous independent variables, the odds ratio gives the change in the odds of the outcome occurring for a one unit change in the value of the predictor variable.
Parameter estimates for categorical independent variables may be presented in two ways. One category of the categorical variable may be selected as a baseline or reference category, with all other categories compared to it. Therefore there is no parameter estimate for the reference category and odds ratios for all other categories are the ratio of the odds of the outcome occurring between each category and the reference category, adjusted for all other variables in the model. In other cases, where there is no obvious reference category, the odds ratios for a given category of a categorical independent variable gives the change in the odds of the outcome occurring compared to the overall odds ('to average').
The statistical significance of independent variables in models was assessed by the likelihood ratio test and its associated p value. 95% confidence intervals were also calculated for the odds ratios. These can be interpreted as meaning that there is a 95% chance that the given interval for the sample will contain the true population parameter of interest. In logistic regression a 95% confidence interval which does not include 1.0 indicates the given parameter estimate is statistically significant.
References: Norusis MJ. SPSS for Windows: Advanced statistics release 6.0. SPSS Inc, Chicago, 1993.
Hosmer DW Jr. and Lemeshow. Applied logistic regression. John Wiley & Sons, New York, 1989.
Mean
Unless otherwise specified, means in this report are arithmetic means (the sum of the values for cases divided by the number of cases).
Median
The value of a distribution which divides it into two equal parts such that half the cases have values below the median and half the cases have values above the median.
Mid-upper arm
The circumference taken at the mid-point between the shoulder and elbow of the
circumference
child's bare left arm using an insertion tape, as described in Appendix B.
Moving averages
The large sample sizes in the Scottish Health Survey provide the opportunity to analyse by individual years of age instead of the more usual discrete age groups. However, even with several hundred per group there is necessarily some random fluctuation that may obscure the underlying trends or patterns. The amount of such fluctuation varies from one variable to another, and depends to a considerable extent, though not solely, on the size of the sub-group to whom the question is addressed. To minimise random variation and to bring out the underlying pattern more clearly, the method of moving averages has been adopted in the construction of graphs. In some cases three years have been averaged and in others five, depending on, among other things, the amount of perceived variability in the data.
In constructing a three year moving average, the percentages shown for each of the first three age years (often but not always 2, 3 and 4) are summed and divided by three to give the first value, which is plotted against the central year (age 3). The next value is obtained by summing the percentages for ages 3, 4 and 5, dividing by three, and plotting the result against age 4. The procedure continues to the final value, which is plotted against the last but one year in the span covered.
Alternative methods of construction are possible, for example weighting the percentage shown for each individual year by the (estimated) proportion of the sample falling into that year.
The advantage of moving averages is the removal of 'noise' in the data, and they work well when change is relatively slow and uniform. Their disadvantage is that if the real underlying pattern involves sharp changes of direction (for example, if values of a variable initially decline sharply with age, then increase to a marked peak and then decrease) moving averages will tend to iron out the turning points. Five year moving averages will have a greater tendency to do this than three year periods, but they also remove more of the 'noise'.
Odds ratio
See Logistic regression.
PEF
Peak Expiratory Flow: the maximal flow in litres per minute recorded during a forced expiration. In healthy subjects this index reflects the calibre of central airways and the force exerted by the expiratory muscles.
Percentile
The value of a distribution which partitions the cases into groups of a specified size. For example, the 20th percentile is the value of the distribution where 20 percent of the cases have values below the 20th percentile and 80 percent have values above it. The 50th percentile is the median.
Phlegm
Phlegm was classified according to the MRC Respiratory Questionnaire as phlegm produced in the morning or during the day or at night for at least three consecutive months.
Quintile
Quintiles are percentiles which divide a distribution into fifths i.e. the 20th, 40th, 60th and 80th percentiles.
Tertiles
Tertiles are percentiles which divide a distribution into thirds.
Unit of alcohol
A unit of alcohol is 8 gms. of ethanol, and is the amount contained in half a pint of ordinary beer or lager, or in a small glass of wine, or in a measure of spirits.
Waist-hip ratio
Waist-hip ratio (WHR) was defined as the waist circumference divided by the hip circumference, i.e. waist girth (m)/ hip girth (m). WHR is a measure of deposition abdominal fat ie. "central obesity". Unlike BMI there is no consensus to define cut-off point for WHR and several were proposed in a recent review. For consistency the cut-off values as in the 1995 report have been used. A raised WHR has been taken to be 0.95 or more in men and 0.85 or more in women.
Reference: Molarius A, Seidell JC. Selection of anthropometric indicators for classification of abdominal fatness - a critical review. Int J Obes 1998; 22:719-727.
