# Scottish Health Survey - topic report: lung function

This report presents data from objective measurement of lung function in adults, measured by portable spirometers, using data from the 2008-

2011 Scottish Health Surveys.

### Annex A Glossary

Age Standardisation |
Age standardisation has been used in order to enable groups to be compared after adjusting for the effects of any differences in their age distributions When different sub-groups are compared 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. Age standardisation was carried out, using the direct standardisation method. The standard population to which the age distribution of sub-groups was adjusted was the mid-2011 population estimates for Scotland. All age standardisation has been undertaken separately within each sex. The age-standardised proportion was calculated as follows, where is the age specific proportion in age group
Therefore can be viewed as a weighted mean of using the weights . Age standardisation was carried out using the age groups: 16-24, 25-34, 35-44, 45-54, 55-64, 65-74 and 75 and over. The variance of the standardised proportion can be estimated by:
where . |

Bronchodilator |
Medications that relax the bronchial muscles |

Centiles |
Quintiles are percentiles which divide a distribution into one hundreths,i.e., the 1st, 2^{nd}, 3^{rd}… and 98^{th}, 99th centiles. |

Chronic Obstructive Pulmonary Disease (COPD) |
COPDis defined by the World Health Organisation (WHO) as 'a lung disease characterised by chronic obstruction of lung airflow that interferes with normal breathing and is not fully reversible.' It is associated with symptoms and clinical signs that in the past have been called 'chronic bronchitis' and 'emphysema,' including regular cough (at least three consecutive months of the year) and production of phlegm. Chronic bronchitis is defined as cough and production of sputum for 3 months for 2 consecutive years |

Equivalised Household income |
Making precise estimates of household income, as is done for example in the Family Resources Survey, requires far more interview time than was available in the Health Survey. Household income was thus established by means of a card (see Volume 2, Appendix A) on which banded incomes were presented. Information was obtained from the household reference person (HRP) or their partner. Initially they were asked to state their own (HRPand partner) aggregate gross income, and were then asked to estimate the total household income including that of any other persons in the household. Household income can be used as an analysis variable, but there has been increasing interest recently in using measures of equivalised income that adjust income to take account of the number of persons in the household. Methods of doing this vary in detail: the starting point is usually an exact estimate of net income, rather than the banded estimate of gross income obtained in the Health Survey. The method used in the present report was as follows. It utilises the widely used McClements scoring system, described below. 1. A score was allocated to each household member, and these were added together to produce an overall household McClements score. Household members were given scores as follows. 2. The equivalised income was derived as the annual household income divided by the McClements score. 3. This equivalised annual household income was attributed to all members of the household, including children. 4. Households were ranked by equivalised income, and quintiles q1- q5 were identified. Because income was obtained in banded form, there were clumps of households with the same income spanning the quintiles. It was decided not to split clumps but to define the quintiles as 'households with equivalised income up to q1', 'over q1 up to q2'etc. 5. All individuals in each household were allocated to the equivalised household income quintile to which their household had been allocated. Insofar as the mean number of persons per household may vary between tertiles, the numbers in the quintiles will be unequal. Inequalities in numbers are also introduced by the clumping referred to above, and by the fact that in any sub-group analysed the proportionate distribution across quintiles will differ from that of the total sample. Reference: McClements, D. (1977). Equivalence scales for children. |

FEV _{1} |
Forced Expiratory Volume: The volume of air that can be blown out in one second during a forced manoeuvre |

FVC |
Forced Vital Capacity: The total volume of air that can forcibly be blown out after a full inspiration |

FEV _{1}/FVC |
FEV_{1}/FVC is the ratio of FEV_{1} and FVC |

Household Reference Person |
The household reference person (HRP) is defined as the householder (a person in whose name the property is owned or rented) with the highest income. If there is more than one householder and they have equal income, then the household reference person is the oldest. |

Income |
See Equivalised household income |

Ischaemic heart disease |
Participants were classified as having ischaemic heart disease (IHD) if they reported ever having angina or a heart attack diagnosed by a doctor. |

Latent Class Analysis |
Latent class analysis is a statistical approach which categorises people into different groups or 'latent classes' based on responses to a series of questions.LCAoperates by identifying the number of classes or groups that best fit the data and generating probabilities membership of each group for every eligible participant. Once this is done, a participant is assigned to the class for which they have the highest probability of membership. |

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 it occurring to the probability of it not occurring. The parameter estimates obtained from a logistic regression model have been presented as odds ratios for ease of interpretation. For For 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. Reference: Hosmer, D.W. Jr. and Lemeshow. S. (1989). |

LLN |
LLN stands for lower limit of normal. By definition, 5% of a 'normal' population will be deemed to fall outside the normal ('healthy') range of any value. In clinical situations, the 5^{th} centile (z-score less than -1.64) is generally considered the lower limit of normal (LLN) for spirometry as patients generally have symptoms or signs indicating a higher likelihood of disease. |

NS-SEC |
The National Statistics Socio-economic Classification (NS-SEC) is a social classification system that attempts to classify groups on the basis of employment relations, based on characteristics such as career prospects, autonomy, mode of payment and period of notice. There are fourteen operational categories representing different groups of occupations (for example higher and lower managerial, higher and lower professional) and a further three 'residual' categories for full-time students, occupations that cannot be classified due to lack of information or other reasons. The operational categories may be collapsed to form a nine, eight, five or three category system. This report mostly uses the five category system in which participants are classified as managerial and professional, intermediate, small employers and own account workers, lower supervisory and technical, and semi-routine and routine occupations. In some instances where there were insufficient numbers to use the five category classification, the three category system was used instead. In analyses presented in this report it is theNS-SECof the household reference person which is used.NS-SECwas introduced in 2001 and replaced Registrar General's Social Class (which had been used in the 1995 and 1998 surveys) as the main measure of socio-economic status. |

p value |
A p value is the probability of the observed result occurring due to chance alone. A p value of less than 5% is conventionally taken to indicate a statistically significant result (p<0.05). It should be noted that the p value is dependent on the sample size, so that with large samples differences or associations which are very small may still be statistically significant. Results should therefore be assessed on the magnitude of the differences or associations as well as on the p value itself. The p values given in this report take into account the clustered sampling design of the survey. |

Pack years |
Defined as defined as the number of packs smoked per day multiplied by the number of years smoked, pack years is used as a measure of smoking history in this report. |

Quintile |
Quintiles are percentiles which divide a distribution into fifths,i.e., the 20th, 40th, 60th and 80th percentiles. |

Scottish Index of Multiple Deprivation |
The Scottish Index of Multiple Deprivation (SIMD) is the Scottish Government's official measure of area based multiple deprivation. It is based on 37 indicators across 7 individual domains of current income, employment, housing, health, education, skills and training and geographic access to services and telecommunications.SIMDis calculated at data zone level, enabling small pockets of deprivation to be identified. The data zones are ranked from most deprived (1) to least deprived (6505) on the overallSIMDindex. The result is a comprehensive picture of relative area deprivation across Scotland. This report uses theSIMD2012. http://www.scotland.gov.uk/Topics/Statistics/SIMD |

Standard deviation |
The standard deviation is a measure of the extent to which the values within a set of data are dispersed from, or close to, the mean value. In a normally distributed set of data 68% of the cases will lie within one standard deviation of the mean, 95% within two standard deviations and 99% will be within 3 standard deviations. For example, for a mean value of 50 with a standard deviation of 5, 95% of values will lie within the range 40-60. |

Standard error |
The standard error is a variance estimate that measures the amount of uncertainty (as a result of sampling error) associated with a survey statistic. All data presented in this report in the form of means are presented with their associated standard errors (with the exception of theWEMWBS scores which are also presented with their standard deviations). Confidence intervals are calculated from the standard error; therefore the larger the standard error, the wider the confidence interval will be. |

Spirometry |
A measureof lungfunction, specifically the amount (volume) and/or speed (flow) of air that can be inhaled and exhaled and is a common test of pulmonary function. |

Standardisation |
In this report, standardisation refers to standardisation (or 'adjustment') by age (see Age standardisation). |

Z scores |
A Z-Score is a statistical measurement of a score's relationship to the mean in a group of scores. A Z-score of 0 means the score is the same as the mean. A Z-score can also be positive or negative, indicating whether it is above or below the mean and by how many standard deviations. |

### Contact

Email: Julie Landsberg

## There is a problem

**Thanks for your feedback**