Energy expenditure estimation during activities of daily living in middle-aged and older adults using an accelerometer integrated into a hearing aid.

Background: Accelerometers were traditionally worn on the hip to estimate energy expenditure (EE) during physical activity but are increasingly replaced by products worn on the wrist to enhance wear compliance, despite potential compromises in EE estimation accuracy. In the older population, where the prevalence of hearing loss is higher, a new, integrated option may arise. Thus, this study aimed to investigate the accuracy and precision of EE estimates using an accelerometer integrated into a hearing aid and compare its performance with sensors simultaneously worn on the wrist and hip. Methods: Sixty middle-aged to older adults (average age 64.0 ± 8.0 years, 48% female) participated. They performed a 20-min resting energy expenditure measurement (after overnight fast) followed by a standardized breakfast and 13 different activities of daily living, 12 of them were individually selected from a set of 35 activities, ranging from sedentary and low intensity to more dynamic and physically demanding activities. Using indirect calorimetry as a reference for the metabolic equivalent of task (MET), we compared the EE estimations made using a hearing aid integrated device (Audéo) against those of a research device worn on the hip (ZurichMove) and consumer devices positioned on the wrist (Garmin and Fitbit). Class-estimated and class-known models were used to evaluate the accuracy and precision of EE estimates via Bland-Altman analyses. Results: The findings reveal a mean bias and 95% limit of agreement for Audéo (class-estimated model) of -0.23 ± 3.33 METs, indicating a slight advantage over wrist-worn consumer devices (Garmin: -0.64 ± 3.53 METs and Fitbit: -0.67 ± 3.40 METs). Class-know models reveal a comparable performance between Audéo (-0.21 ± 2.51 METs) and ZurichMove (-0.13 ± 2.49 METs). Sub-analyses show substantial variability in accuracy for different activities and good accuracy when activities are averaged over a typical day's usage of 10 h (+61 ± 302 kcal). Discussion: This study shows the potential of hearing aid-integrated accelerometers in accurately estimating EE across a wide range of activities in the target demographic, while also highlighting the necessity for ongoing optimization efforts considering precision limitations observed across both consumer and research devices.

Associations Between Cardiovascular Risk Factors and Audiometric Hearing: Findings From the Canadian Longitudinal Study on Aging.

OBJECTIVES: The objectives of the study were to determine, among a population-based sample of Canadian adults, if risk factors for cardiovascular disease (alone and in combination) were associated with hearing loss. Cross-sectional and longitudinal associations (the latter with about 3 years of follow-up) were examined. Risk factors considered included diabetes, dyslipidemia, hypertension, obesity, and smoking. We also aimed to determine if associations were modified by sex and age group (45 to 54, 55 to 64, 65 to 74, and 75 to 86 years old at baseline). DESIGN: A secondary analysis of data collected for the Canadian Longitudinal Study on Aging was performed. Data were collected in two waves, the first between 2012 and 2015, and the second between 2015 and 2018. Hearing was measured using screening air-conduction pure-tone audiometry. The outcome of interest was defined as the mid-frequency (1000, 2000, 3000, and 4000 Hz) pure-tone average for both ears. Diabetes was defined based on self-reported physician diagnosis, use of diabetes medications, or a hemoglobin A1c level ≥6.5%. Dyslipidemia was determined by blood lipid profile as defined using the Canadian guidelines for the diagnosis and treatment of dyslipidemia (low-density lipoprotein cholesterol ≥3.5 mmol/L or non-high-density lipoprotein cholesterol ≥4.3 mmol/L). Hypertension was determined by self-reported physician diagnosis or an average systolic blood pressure ≥140 mm Hg or an average diastolic blood pressure ≥90 mm Hg. Obesity was defined as a waist-to-height ratio ≥0.6. Smoking history was determined by self-report (current/former/never-smoker). Two composite measures of cardiovascular risk were also constructed: a count of the number of risk factors and a general cardiovascular risk profile (Framingham) score. Independent associations between risk factors for cardiovascular disease and hearing were determined using multivariable regression models. Survey weights were incorporated into the analyses. All results were disaggregated by sex. Effect modification according to age was determined using multiplicative interaction terms between the age group and each of the risk factor variables. A complete case (listwise deletion) approach was performed for the primary analysis. We then repeated the multivariable regression analyses using multiple imputation using chained equations to determine if the different approaches to dealing with missing data qualitatively changed the outcomes. RESULTS: In longitudinal analyses, hypertension and the general cardiovascular risk profile score were associated with greater loss of hearing over the 3-year follow-up period for both sexes. In addition, smoking in males and obesity in females were associated with faster rates of hearing decline. In cross-sectional analyses, smoking, obesity, diabetes, and composite measures were each independently associated with worse hearing for both sexes (although for females, obesity was only associated with hearing loss in the 55 to 64-year-old age group). The results were similar for the complete case and multiple imputation approaches, but more cross-sectional associations were observed using multiple imputation. CONCLUSIONS: Diabetes, obesity, hypertension, and smoking were associated with hearing loss. Higher combinations of risk factors increased the risk of hearing loss. Further studies are needed to confirm age and sex differences and whether interventions to address these risk factors could slow the progression of hearing loss in older adults.

New horizons in holistic, person-centred health promotion for hearing healthcare.

Over the course of a lifetime, the risk of experiencing multiple chronic conditions (multimorbidity) increases, necessitating complex healthcare regimens. Healthcare that manages these requirements in an integrated way has been shown to be more effective than services that address specific diseases individually. One such chronic condition that often accompanies ageing is hearing loss and related symptoms, such as tinnitus. Hearing loss is not only highly prevalent in older adults but is also a leading cause of disability. Accumulating evidence demonstrates an interplay between auditory function and other aspects of health. For example, poorer cardiometabolic health profiles have been shown to increase the risk of hearing loss, which has been attributed to microvascular disruptions and neural degeneration. Additionally, hearing loss itself is associated with significantly increased odds of falling and is a potentially modifiable risk factor for cognitive decline and dementia. Such evidence warrants consideration of new possibilities-a new horizon-for hearing care to develop a holistic, person-centred approach that promotes the overall health and wellbeing of the individual, as well as for audiology to be part of an interdisciplinary healthcare service. To achieve this holistic goal, audiologists and other hearing healthcare professionals should be aware of the range of conditions associated with hearing loss and be ready to make health promoting recommendations and referrals to the appropriate health practitioners. Likewise, healthcare professionals not trained in audiology should be mindful of their patients' hearing status, screening for hearing loss or referring them to a hearing specialist as required.

User characteristics associated with use of wrist-worn wearables and physical activity apps by adults with and without impaired speech-in-noise recognition: a cross-sectional analysis.

Objective: To study weekly use of smartwatches, fitness watches and physical activity apps among adults with and without impaired speech-in-noise (SIN) recognition, to identify subgroups of users. Design: Cross-sectional study. Study sample: Adults (aged 28-80 years) with impaired (n = 384) and normal SIN recognition (n = 341) as measured with a web-based digits-in-noise test, from the Netherlands Longitudinal Study on Hearing. Multiple logistic regression analyses were used to study differences and to build an association model. Results: Employed adults in both groups are more likely to use each type of fitness technology (all ORs >3.4, all p-values < 0.004). Specific to fitness watch use, adults living with others use it more (OR 2.5, 95%CI 1.1;5.8, p = 0.033) whereas those abstaining from alcohol (OR 0.3, 95%CI 0.1;0.6) or consuming >2 glasses/week (OR 0.4, 95%CI 0.2;0.81, overall p = 0.006) and hearing aid users (OR 0.5, 95%CI 0.2;0.9, p = 0.024) make less use. Conclusions: Subgroups of adults more and less likely to use fitness technology exist, but do not differ between adults with and without impaired SIN recognition. More research is needed to confirm these results and to develop interventions to increase physical activity levels among adults with hearing loss.

A Comparison of the Use of Smart Devices, Apps, and Social Media Between Adults With and Without Hearing Impairment: Cross-sectional Web-Based Study.

BACKGROUND: eHealth and social media could be of particular benefit to adults with hearing impairment, but it is unknown whether their use of smart devices, apps, and social media is similar to that of the general population. OBJECTIVE: Our aim is to study whether adults with normal hearing and those with impaired hearing differ in their weekly use of smart devices, apps, and social media; reasons for using social media; and benefits from using social media. METHODS: We used data from a Dutch cohort, the National Longitudinal Study on Hearing. Data were collected from September 2016 to April 2020 using a web-based questionnaire and speech-in-noise test. The results from this test were used to categorize normal hearing and hearing impairment. Outcomes were compared using (multiple) logistic regression models. RESULTS: Adults with impaired hearing (n=384) did not differ from normal hearing adults (n=341) in their use of a smartphone or tablet. They were less likely to make use of social media apps on a smartphone, tablet, or smartwatch (age-adjusted odds ratio [OR] 0.67, 95% CI 0.48-0.92; P=.02). Use of social media on all devices and use of other apps did not differ. Adults with hearing impairment were more likely to agree with using social media to stay in touch with family members (OR 1.54, 95% CI 1.16-2.07; P=.003) and friends (age-adjusted OR 1.35, 95% CI 1.01-1.81; P=.046). Furthermore, they were more likely to agree with using social media to perform their work (age-adjusted OR 1.51, 95% CI 1.04-2.18; P=.03). There were no differences in the experienced benefits from social media. CONCLUSIONS: The potential for eHealth is confirmed because adults with hearing impairment are not less likely to use smart devices than their normal hearing peers. Adults with hearing impairment are less likely to use social media apps on a smart device but not less likely to use social media on all types of internet-connected devices. This warrants further research on the types of social media platforms that adults with hearing impairment use and on the type of device on which they prefer to use social media. Given that participants with hearing impairment are more likely than their normal hearing peers to use social media to perform their work, use of social media may be seen as an opportunity to enhance vocational rehabilitation services for persons with hearing impairment.

Comorbidities of hearing loss and the implications of multimorbidity for audiological care.

With increasing age, the risk of developing chronic health conditions also increases, and many older people suffer from multiple co-existing health conditions, i.e., multimorbidity. One common health condition at older age is hearing loss (HL). The current article reflects on the implications for audiological care, when HL is one of several health conditions in a multimorbidity. An overview of health conditions often co-existing with HL, so called comorbidities, is provided, including indications for the strength of the associations. The overview is based on a literature study examining cohort studies that were published in the years 2010-2018 and examined associations of hearing loss with other health conditions, namely Visual impairment, Mobility restrictions, Cognitive impairment, Psychosocial health problems, Diabetes, Cardiovascular diseases, Stroke, Arthritis, and Cancer. This selection was based on previous publications on common chronic health conditions at older age and comorbidities of hearing loss. For all of these health conditions, it was found that prevalence is larger in people with a HL and several longitudinal studies also found increased incident rates in people with a HL. The examined publications provide little information on how hearing loss should be managed in the clinical care of its comorbidities and vice versa. The current article discusses several options for adaptations of current care. Nonetheless, solutions for an integrated audiology care model targeting HL in a multimorbidity are still lacking and should be subject to future research.

A case-control field study on the relationships among type 2 diabetes, sleepiness and habitual caffeine intake.

OBJECTIVES: The purpose of this study was to examine the possible links between type 2 diabetes, daytime sleepiness, sleep quality and caffeine consumption. METHODS: In this case-control field study, comparing type 2 diabetic ( n=134) and non-type 2 diabetic ( n=230) participants, subjects completed detailed and validated questionnaires to assess demographic status, health, daytime sleepiness, sleep quality and timing, diurnal preference, mistimed circadian rhythms and habitual caffeine intake. All participants gave saliva under standardised conditions for CYP1A2 genotyping and quantification of caffeine concentration. Hierarchical linear regression analyses examined whether type 2 diabetes status was associated with caffeine consumption. RESULTS: Type 2 diabetic participants reported greater daytime sleepiness ( p=0.001), a higher prevalence of sleep apnoea ( p=0.005) and napping ( p=0.008), and greater habitual caffeine intake ( p<0.001), derived from the consumption of an extra cup of coffee each day. This finding was confirmed by higher saliva caffeine concentration at bedtime ( p=0.01). Multiple regression analyses revealed that type 2 diabetes status was associated with higher self-reported caffeine consumption ( p<0.02) and higher salivary caffeine ( p<0.02). Next to male sex, type 2 diabetes status was the strongest predictor of caffeine intake. Subjective sleep and circadian estimates were similar between case and control groups. CONCLUSIONS: Type 2 diabetic patients may self-medicate with caffeine to alleviate daytime sleepiness. High caffeine intake reflects a lifestyle factor that may be considered when promoting type 2 diabetes management.

Assessment of CYP1A2 enzyme activity in relation to type-2 diabetes and habitual caffeine intake.

BACKGROUND: Coffee consumption is a known inducer of cytochrome P450 1A2 (CYP1A2) enzyme activity. We recently observed that a group of type-2 diabetes patients consumed more caffeine (coffee) on a daily basis than non-type-2 diabetes controls. Here, we investigated whether type-2 diabetes cases may metabolize caffeine faster than non-type-2 diabetes controls. METHODS: To estimate CYP1A2 enzyme activity, an established marker of caffeine metabolism, we quantified the paraxanthine/caffeine concentration ratio in saliva in 57 type-2 diabetes and 146 non-type-2 diabetes participants in a case-control field study. All participants completed validated questionnaires regarding demographic status, health and habitual caffeine intake, and were genotyped for the functional -163C > A polymorphism of the CYP1A2 gene. RESULTS: In the diabetes group, we found a larger proportion of participants with the highly inducible CYP1A2 genotype. Furthermore, the paraxanthine/caffeine ratio, time-corrected to mitigate the impact of different saliva sampling times with respect to the last caffeine intake, was higher than in the control group. Participants who reported habitually consuming more caffeine than the population average showed higher CYP1A2 activity than participants with lower than average caffeine consumption. Multiple regression analyses revealed that higher caffeine intake was potentially an important mediator of higher CYP1A2 activity. CONCLUSIONS: Estimated CYP1A2 enzyme activity, and thus speed of caffeine metabolism, was higher in our type-2 diabetes group; this was possibly due to higher intake of caffeine, a known inducer of CYP1A2 enzyme activity. Given the fairly small sample sizes, the results need to be considered as preliminary and require validation in larger populations.

Adenosine, caffeine, and performance: from cognitive neuroscience of sleep to sleep pharmacogenetics.

An intricate interplay between circadian and sleep-wake homeostatic processes regulate cognitive performance on specific tasks, and individual differences in circadian preference and sleep pressure may contribute to individual differences in distinct neurocognitive functions. Attentional performance appears to be particularly sensitive to time of day modulations and the effects of sleep deprivation. Consistent with the notion that the neuromodulator, adenosine , plays an important role in regulating sleep pressure, pharmacologic and genetic data in animals and humans demonstrate that differences in adenosinergic tone affect sleepiness, arousal and vigilant attention in rested and sleep-deprived states. Caffeine--the most often consumed stimulant in the world--blocks adenosine receptors and normally attenuates the consequences of sleep deprivation on arousal, vigilance, and attention. Nevertheless, caffeine cannot substitute for sleep, and is virtually ineffective in mitigating the impact of severe sleep loss on higher-order cognitive functions. Thus, the available evidence suggests that adenosinergic mechanisms, in particular adenosine A2A receptor-mediated signal transduction, contribute to waking-induced impairments of attentional processes, whereas additional mechanisms must be involved in higher-order cognitive consequences of sleep deprivation. Future investigations should further clarify the exact types of cognitive processes affected by inappropriate sleep. This research will aid in the quest to better understand the role of different brain systems (e.g., adenosine and adenosine receptors) in regulating sleep, and sleep-related subjective state, and cognitive processes. Furthermore, it will provide more detail on the underlying mechanisms of the detrimental effects of extended wakefulness, as well as lead to the development of effective, evidence-based countermeasures against the health consequences of circadian misalignment and chronic sleep restriction.