Prevalence and patterns of multimorbidity in Australian baby boomers: the Busselton healthy ageing study.

BACKGROUND AND OBJECTIVE: Chronic medical conditions accumulate within individuals with age. However, knowledge concerning the trends, patterns and determinants of multimorbidity remains limited. This study assessed the prevalence and patterns of multimorbidity using extensive individual phenotyping in a general population of Australian middle-aged adults. METHODS: Participants (n = 5029, 55% female), born between 1946 and 1964 and attending the cross-sectional phase of the Busselton Healthy Ageing Study (BHAS) between 2010 and 2015, were studied. Prevalence of 21 chronic conditions was estimated using clinical measurement, validated instrument scores and/or self-reported doctor-diagnosis. Non-random patterns of multimorbidity were explored using observed/expected (O/E) prevalence ratios and latent class analysis (LCA). Variables associated with numbers of conditions and class of multimorbidity were investigated. RESULTS: The individual prevalence of 21 chronic conditions ranged from 2 to 54% and multimorbidity was common with 73% of the cohort having 2 or more chronic conditions. (mean ± SD 2.75 ± 1.84, median = 2.00, range 0-13). The prevalence of multimorbidity increased with age, obesity, physical inactivity, tobacco smoking and family history of asthma, diabetes, myocardial infarct or cancer. There were 13 pairs and 27 triplets of conditions identified with a prevalence > 1.5% and O/E > 1.5. Of the triplets, arthritis (> 50%), bowel disease (> 33%) and depression-anxiety (> 33%) were observed most commonly. LCA modelling identified 4 statistically and clinically distinct classes of multimorbidity labelled as: 1) "Healthy" (70%) with average of 1.95 conditions; 2) "Respiratory and Atopy" (11%, 3.65 conditions); 3) "Non-cardiometabolic" (14%, 4.77 conditions), and 4) "Cardiometabolic" (5%, 6.32 conditions). Predictors of multimorbidity class membership differed between classes and differed from predictors of number of co-occurring conditions. CONCLUSION: Multimorbidity is common among middle-aged adults from a general population. Some conditions associated with ageing such as arthritis, bowel disease and depression-anxiety co-occur in clinically distinct patterns and at higher prevalence than expected by chance. These findings may inform further studies into shared biological and environmental causes of co-occurring conditions of ageing. Recognition of distinct patterns of multimorbidity may aid in a holistic approach to care management in individuals presenting with multiple chronic conditions, while also guiding health resource allocation in ageing populations.

Clinical validation of automated audiometry with continuous noise-monitoring in a clinically heterogeneous population outside a sound-treated environment.

OBJECTIVE: Examine the accuracy of automated audiometry in a clinically heterogeneous population of adults using the KUDUwave automated audiometer. DESIGN: Prospective accuracy study. Manual audiometry was performed in a sound-treated room and automated audiometry was not conducted in a sound-treated environment. STUDY SAMPLE: 42 consecutively recruited participants from a tertiary otolaryngology department in Western Australia. RESULTS: Absolute mean differences ranged between 5.12-9.68 dB (air-conduction) and 8.26-15 dB (bone-conduction). A total of 86.5% of manual and automated 4FAs were within 10 dB (i.e. ±5 dB); 94.8% were within 15 dB. However, there were significant (p < 0.05) differences between automated and manual audiometry at 250, 500, 1000, and 2000 Hz (air-conduction) and 500 and 1000 Hz (bone-conduction). The effect of age (≥55 years) on accuracy (p = 0.014) was not significant on linear regression (p > 0.05; R(2) =( ) 0.11). The presence of a hearing loss (better ear ≥26 dB) did not significantly affect accuracy (p = 0.604; air-conduction), (p = 0.218; bone-conduction). CONCLUSIONS: This study provides clinical validation of automated audiometry using the KUDUwave in a clinically heterogeneous population, without the use of a sound-treated environment. Whilst threshold variations were statistically significant, future research is needed to ascertain the clinical significance of such variation.

False air-bone gaps at 4 kHz in listeners with normal hearing and sensorineural hearing loss.

OBJECTIVE: This report presents data from four studies to examine standard bone-conduction reference equivalent threshold force levels (RETFL), especially at 4 kHz where anomalous air-bone gaps are common. DESIGN: Data were mined from studies that obtained air- and bone-conduction thresholds from normal-hearing and sensorineural hearing loss (SNHL) participants, using commercial audiometers and standard audiometric transducers. STUDY SAMPLE: There were 249 normal-hearing and 188 SNHL participants. RESULTS: (1) Normal-hearing participants had small air-bone gaps at 0.5, 1.0, and 2.0 kHz (-1.7 to 0.3 dB) and larger air-bone gaps at 4 kHz (10.6 dB). (2) SNHL participants had small air-bone gaps at 0.5, 1.0, and 2.0 kHz (-0.7 to 1.7 dB) and a larger air-bone gap at 4 kHz (14.1 dB). (3) The 4-kHz air-bone gap grew with air-conduction threshold from 10.1 dB when the air-conduction threshold was 5-10 dB HL to 21.1 dB when the air-conduction threshold was greater than 60 dB. (4) With the 4-kHz RETFL corrected by the average SNHL air-bone gap, the relationship between RETFL and frequency is linear with a slope of - 12 dB per octave. CONCLUSIONS: The 4-kHz air-bone gaps for listeners with SNHL could be avoided by adjusting the 4-kHz RETFL by - 14.1 dB.

Clinical validation of the AMTAS automated audiometer.

OBJECTIVE: To validate the air- and bone-conduction AMTAS automated audiometry system. DESIGN: Prospective study. Test-retest reliability was determined by assessing adults with AMTAS air- and bone-conduction audiometry. Accuracy was determined by comparing AMTAS and manual audiometry conducted on adults. AMTAS testing was conducted in a quiet room and manual audiometry in a sound booth. STUDY SAMPLE: Ten participants for test-retest reliability tests and 44 participants to determine accuracy were included. Participants had varying degrees of hearing loss. RESULTS: For test-retest reliability the overall difference in air-conduction hearing thresholds (n = 119) was 0.5 dB. The spread of differences (standard deviation of absolute differences) was 4.9 dB. For bone-conduction thresholds (n = 99) the overall difference was - 0.2 dB, and the spread of differences 4.5 dB. For accuracy the overall difference in air-conduction hearing thresholds (n = 509) between the two techniques was 0.1 dB. The spread of differences was 6.4 dB. For bone-conduction thresholds (n = 295) the overall difference was 0 dB, and the spread of differences 7.7 dB. CONCLUSIONS: Variations between air- and bone-conduction audiometry for automated and manual audiometry were within normally accepted limits for audiometry. However, AMTAS thresholds were elevated but not significantly different compared to other contemporary studies that included an automated audiometer.