Newer equations better predict lung age in smokers: a retrospective analysis using a cohort of randomly selected participants.

AIMS: To produce new lung age equations using four previously published predictive equations for forced expiratory volume in 1 second and to compare them with lung age equations published in 1985 and 2010. METHODS: Initial comparisons used phantom subjects of different ages and levels of lung function. Comparison of lung age equations by regression analysis used an independent dataset of 3,206 randomly selected community-dwelling adults aged >18 years in the North West Adelaide Health Study. RESULTS: The more recent equations estimated lung age as greater than chronological age as lung function decreased, whereas the oldest equations estimated lung age as less than chronological age until lung function was severely limited. Significant differences (p<0.001) were detected by regression analysis, with four newer lung age equations being significantly different from the 1985 equation and one being no different. CONCLUSIONS: Lung age estimates using six predictive equations spanning 50 years show differences attributable to cohort and period effects. This reinforces the need for regular updating of predictive equations for lung function. These results further confirm the need to use modern lung age equations which will provide a stronger message in smoking cessation counselling.

Spirometry and impulse oscillometry (IOS) for detection of respiratory abnormalities in metropolitan firefighters.

BACKGROUND AND OBJECTIVE: As firefighters are at increased risk of adverse health effects, periodic examination of their respiratory health is important. The objective of this study was to establish whether the use of impulse oscillometry (IOS) reveals respiratory abnormalities in metropolitan firefighters that go undetected during routine respiratory health screening by spirometry and assessment of respiratory symptoms. METHODS: This was a cross-sectional analysis of spirometry, IOS and questionnaire data from 488 male firefighters. Abnormal spirometry was defined as FEV(1), FEV(1)/FVC and/or FEF(50) below the lower limit of normal. Abnormal IOS was defined as resistance at 5 Hz (R5), frequency dependence of resistance (DeltaR5-R20) and/or reactance area (AX) above the upper limit of normal. Respiratory symptoms, smoking history, exposures and medical history were assessed. Data were analysed using logistic and linear regression models. RESULTS: The mean age of the firefighters was 43.8 (SD 8.4) years. There were 123 (25%) former smokers and 50 (10%) current smokers. Abnormal spirometry was detected in 12%, abnormal IOS in 9% and respiratory symptoms in 20% of firefighters. Current smoking was associated with all IOS parameters (OR for R5 = 3.1, OR for DeltaR5-R20 = 7.7, OR for AX = 4.3), and with FEF(50) (OR = 9.1), chronic productive cough (OR = 4.0) and breathlessness (OR = 5.4) (P < 0.05 for all). Exposure during firefighting duties was associated with chronic productive cough (OR = 2.6), but not with spirometry or IOS parameters. Interaction terms in the linear regression models indicated associations between smoking and DeltaR5-R20, and also between smoking and AX, in the lowest and second lowest quartiles of spirometry parameters. CONCLUSIONS: Application of IOS for the assessment of respiratory health in firefighters identified airways dysfunction in some individuals, even when spirometry values were within the normal range and there were no respiratory symptoms.

Exploring the need to update lung age equations.

AIMS: A renewed interest in lung age is evidenced by recent smoking cessation publications. This research compares the original Morris lung age equations (1985) with contemporary Australian lung age equations. METHODS: Both lung age equations were applied to the spirometry results of two sub-groups (never-smokers n=340, and current smokers n=50) from an independent dataset. Means of both lung age estimates were compared to the mean of the chronological age of each group by paired Student's t-test. RESULTS: The Morris lung age estimates were paradoxically lower (younger) than chronological age in both groups. The new Australian equation produced lung age estimates that were equivalent to chronological age in the never-smoker group and significantly higher (older) than chronological age in the current smoker group. CONCLUSIONS: These results strongly suggest that the Morris lung age equations are in need of review. The use of contemporary lung age equations may translate into greater success for smoking cessation programs. The new Australian equations seem to possess internal validity.

Management of recurrent depression.

BACKGROUND: Depression is a potentially recurring or chronic disorder. The provision of evidence based treatment and effective practice organisation is central to chronic disease management, and these principles can be applied to managing depression. OBJECTIVE: This article outlines the principles of chronic disease management, including the use of management plans and a team care approach, and their application to the management of depression. DISCUSSION: Treatment approaches that systematically assist patients in managing their chronic disease are more effective than those based on acute care. Depression treatment guidelines are available, as well as primary care initiatives which facilitate comprehensive and long term mental health care, including relapse prevention strategies. A number of risk factors for depression relapse have been identified, and research has recommended that novel intensive relapse prevention programs need to be developed.

A pilot study to evaluate Australian predictive equations for the impulse oscillometry system.

BACKGROUND AND OBJECTIVE: Impulse oscillometry (IOS) measures respiratory function during normal breathing by transmitting mixed frequency rectangular pressure impulses down the airways and measuring the resultant pressure and flow relationships, which describe the mechanical parameters of the lungs. Respiratory impedance and its components, airways resistance and reactance, at a range of frequencies from 0.1 to 150 Hz are calculated by computer analysis. The IOS software generates predictive normal values for each of the parameters measured, including total airway resistance (R5), proximal airway resistance (R20) and peripheral capacitive reactance (X5). However, these values are based on German data and no other Caucasian data or Australian normative data exist. METHODS: This was a cross-sectional study of over 100 community dwelling adults, with about 10 men and 10 women per 10-year cohort. Inclusion criteria were age between 25 and 74 years and apparently good respiratory health. Exclusion criteria were smoking, asthma and acute or chronic respiratory disease. IOS and spirometry were performed on all participants. RESULTS: Australian predictive normal equations were generated and compared with current published equations. The IOS parameters were correlated with the spirometric data. Results were analysed by gender, age, height and weight, and compared with the predicted normal values for each parameter provided by the German manufacturer of the IOS instrument. CONCLUSIONS: A preliminary set of Australian predictive equations have been produced for the IOS. These have been compared with international equations. IOS has potential applications in a range of respiratory diseases and in population screening for occupational health assessment.

Preventing relapse of depression in primary care: a pilot study of the "Keeping the blues away" program.

OBJECTIVES: To determine the effectiveness of "Keeping the blues away" (KBA), a manualised depression relapse prevention program for general practice, in reducing the relapse of depression compared with usual care (with the aim of halving the relapse rate), and in reducing depression severity and improving the process of care. DESIGN AND SETTING: A cluster randomised controlled trial conducted in 2004-2005 in South Australian general practices. PARTICIPANTS: 43 general practitioners from 23 urban and rural practices recruited 110 patients with depression (age range, 18-75 years). INTERVENTION: GP training manual or patient manual and relaxation CD; 20 hours of training on depression, the study protocol, assessment tools and skills. MAIN OUTCOME MEASURES: Relative risk (RR) of depression relapse; depression severity and quality of life scores. RESULTS: There were no significant differences in relapse rates between the groups (chi(2)(1) = 1.51; P = 0.23), although there was a non-significant tendency for relapse to be reduced in the KBA group (RR = 0.77; 95% CI, 0.50-2.05). Older patients (> or = 50 years) in the KBA group showed a significantly lower probability of relapse than those in the control group (P = 0.018). There was a decrease in depression scores in both groups. KBA participants had more severe depression at baseline, and the reduction in severity in those with symptoms for > 6 months was nearly significant (P = 0.06). KBA was positively received by GPs and patients. CONCLUSIONS: Although this pilot study of a small sample did not achieve its primary outcome of reducing depression relapse by 50%, KBA was found to be a promising program for older patients and for those with more severe or persistent symptoms.