Hearing Aid Usage and Satisfaction Among the Elderly - ELSA Dataset (Manipulated)

Dataset Overview

This dataset provides a modified version of variables related to hearing aid usage, hearing difficulties, and satisfaction levels among elderly individuals, based on the English Longitudinal Study of Ageing (ELSA), Wave 7. The dataset contains 1,164 samples and includes variables that examine hearing conditions, hearing aid adoption, interactions with healthcare professionals, and overall satisfaction with hearing aids.

Factors influencing the adaptation and continued use of hearing aids in the elderly population.

Dataset Structure

This dataset includes the following key variables:

Self_Reported_Hearing: Self-reported hearing quality (1 = Excellent, 5 = Poor).

Hearing_Difficulty: Whether the individual experiences hearing difficulties (1 = Yes, 2 = No).

Group_Conversation_Difficulty: Difficulty having a conversation in a group setting.

Background_Noise_Difficulty: Difficulty following conversations when there is background noise.

Doctor_Consultation: Whether the individual consulted a doctor or nurse about their hearing problems.

Hearing_Aid_Usage: Frequency of hearing aid usage (1 = Most of the time, 2 = Some of the time, 3 = No).

Satisfaction_Level: Satisfaction with hearing aids (1 = Very satisfied, 5 = Very dissatisfied).

Cochlear_Implant, Ear_Infection, Hearing_Test_Agreement, and more.

Additionally, the dataset includes variables related to hearing tests, such as the number of tones heard at different frequencies for both ears, as well as whether individuals were referred to a specialist or recommended a hearing aid by healthcare professionals.

Source

This dataset has been manipulated from the original English Longitudinal Study of Ageing (ELSA), Wave 7 dataset. The full original dataset, which includes a much larger set of variables and samples, is publicly available on the UK Data Service website for research and educational purposes: UK Data Service.

License

The modified data provided here is intended for educational and research purposes. Users are encouraged to refer to the original dataset and citation policies from the UK Data Service.

This dataset captures self-reported communication difficulties among individuals from both normal and hearing-impaired populations. It is derived from responses to a standardized self-assessment questionnaire designed to evaluate hearing handicap severity in real-life communication scenarios. Each response is categorized into four levels of difficulty: "Most of the time" (>75%), "Sometimes" (25%–75%), "Seldom" (<25%), and "Not Applicable."

The data encompasses a demographically diverse population, ensuring representation across age, gender, and socio-economic backgrounds. Statistical reliability is validated using Cronbach’s Alpha (α = 0.88), confirming strong internal consistency. Discriminant validity tests and factor correlation analysis further support the dataset's ability to distinguish between normal and impaired populations based on communication challenges.

The dataset has been successfully used to train and evaluate machine learning models for hearing impairment classification. Notably, a Neural Network model achieved superior performance with 97% accuracy, 96% precision, 98% recall, and a 97% F1-score, outperforming Logistic Regression and Decision Tree classifiers. This highlights the dataset’s value in developing data-driven auditory health assessment tools suitable for clinical and telehealth applications.

Purpose: Falls are considered a significant public health issue, and hearing loss has been shown to be an independent risk factor for falls. The primary objective of this study was to determine if hearing aid use modified (reduced) the association. We hypothesized that routine hearing aid use would reduce the impact of hearing loss on the odds of falling. If hearing aid users have reduced odds of falling, then that would have an important impact on falls prevention health care.Method: Data from 8,091 individuals 40 years of age and older who completed National Health and Nutrition Examination Survey (NHANES) cycles 1999–2004 were used. NHANES comprises a series of cross-sectional studies, each of which is representative of the total civilian noninstitutionalized population of children and adults in the United States, enabling unbiased national estimates of health that can be independently reproduced. Self-reported hearing, hearing aid status, falls history, and comorbidities were extracted and analyzed using regression modeling.Results: The 8,091 individuals were grouped based on a self-reported history of falls in the last year. Self-reported hearing loss was significantly associated with odds of falling. Categorizing individuals based on routine hearing aid use was included as an interaction term in the fully adjusted models and was not significant, suggesting no difference in falls based on hearing aid status.Conclusions: The unique results of the current study show that when examining self-reported hearing in a nationally representative sample, hearing aid use does not appear to mitigate or modify the association between self-reported hearing and falls. Future research designs are highlighted to address limitations identified using NHANES data for this research, and focus on the use of experimental designs to further understand the association between hearing loss and falls, and whether hearing loss may be a modifiable risk factor for falls.Supplemental Material S1. NHANES variables used to define measures of interest.Supplemental Material S2. Odds ratio of self-reported falls by hearing loss as measured by hearing handicap.Riska, K. M., Peskoe, S. B., Gordee, A., Kuchibhatla, M., & Smith, S. L. (2021). Preliminary evidence on the impact of hearing aid use on falls risk in individuals with self-reported hearing loss. American Journal of Audiology. Advance online publication. https://doi.org/10.1044/2021_AJA-20-00179

BackgroundBarriers to communication significantly reduce access to health services for people with deafness or hearing loss (PDHL). These barriers contribute to reduced healthcare-seeking behaviour, poorer access to health information, and adverse health outcomes. In response, a multidisciplinary working group of patients, clinicians, researchers, and charity representatives was established to investigate accessibility, communication, and deaf awareness within the United Kingdom’s (UK) National Health Service (NHS).MethodologyA cross-sectional survey was conducted to explore the communication and accessibility experiences of PDHL NHS patients, and their perceived impact on well-being. The survey used rating scales and open-ended questions and data were analysed using descriptive statistics and thematic analysis. The survey was made available in British Sign Language (BSL).ResultsThe online survey was completed by 556 PDHL, including 50 parents, carers, or family members who had accompanied PDHL friends or relatives to NHS appointments. All respondents had used NHS services within the last 24 months, with 10% identifying BSL as their preferred language. Qualitative analysis of the open-ended responses generated three key themes: 1) Accessibility challenges, 2) Impact of communication difficulties across the service pathway, and 3) Lack of consistent, effective deaf-aware communication. Overall, 64.4% of PDHL NHS patients reported missing 50% or more of the important information provided during their NHS appointments, and 32% were satisfied with the communication skills of healthcare staff.ConclusionThis study presents the largest UK-wide dataset of its kind, and findings highlight the widespread non-compliance with the legally mandated Accessible Information Standards (AIS) within NHS services. The communication barriers identified in this study have significant and long-term implications for the well-being of PDHL patients. Utilising these findings, our working group has developed a set of ‘Recommendations For Change’ to improve deaf awareness and effective communication across the NHS.

This measure represents the percentage of identified as having deaf & hard of hearing impairments who were competitively employed after receiving services from Iowa Vocational Rehabilitation Services.

Search strategies for a review article on communication between people with hearing loss and health personnel are described.

After decades of effort by shareholders, including government agencies, patient advocacy groups, and professional organizations, the U.S. Food and Drug Administration (FDA) established a new medical device category for over-the-counter (OTC) hearing aids on October 17, 2022. This FDA regulation allows adults aged 18 years or older with perceived mild-to-moderate hearing loss to purchase OTC hearing aids without a prescription or even a hearing test. The goal is to increase hearing aid accessibility, potentially leading to improved hearing and a better quality of life. In our analysis of the FDA Establishment Registration & Device Listing database, we found that the current OTC hearing aid market is still dominated by traditional hearing aid manufacturers, with limited disruptor from major consumer electronics and startup companies. Our technological analyses showed that the relatively high-level output specification without gain limitation allows sufficient amplification even for people with severe-to-profound hearing loss. Additionally, borrowing from the cochlear implant mapping strategy, we propose novel amplification algorithms for fitting OTC hearing aids without an audiogram. We argue that smartphones and true-wireless-stereo earbuds can functionally serve as OTC hearing aids, further increasing accessibility and affordability while reducing the stigma associated with hearing aids, especially in low- and mid-income countries. By treating more people at a younger age with less hearing loss than traditional prescription hearing aids, OTC hearing aids can potentially have a significant impact beyond hearing care, such as delaying or preventing cognitive decline in the elderly.

INTRODUCTION: Hearing loss may impair the development of a child. The rehabilitation process for individuals with hearing loss depends on effective interventions.OBJECTIVE: To describe the linguistic profile and the hearing skills of children using hearing aids, to characterize the rehabilitation process and to analyze its association with the children's degree of hearing loss.METHODS: Cross-sectional study with a non-probabilistic sample of 110 children using hearing aids (6-10 years of age) for mild to profound hearing loss. Tests of language, speech perception, phonemic discrimination, and school performance were performed. The associations were verified by the following tests: chi-squared for linear trend and Kruskal-Wallis.RESULTS: About 65% of the children had altered vocabulary, whereas 89% and 94% had altered phonology and inferior school performance, respectively. The degree of hearing loss was associated with differences in the median age of diagnosis; the age at which the hearing aids were adapted and at which speech therapy was started; and the performance on auditory tests and the type of communication used.CONCLUSION: The diagnosis of hearing loss and the clinical interventions occurred late, contributing to impairments in auditory and language development.

This table contains 324 series, with data for years 2013 - 2015 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada) Measures (3 items: Low-frequency hearing loss; High-frequency hearing loss; Speech-frequency hearing loss) Sex (3 items: Both sexes; Males; Females) Age group (6 items: Ages 6 to 79; Ages 6 to 11; Ages 12 to 19; Ages 20 to 39; ...) Categories (2 items: Hearing loss; No hearing loss) Characteristics (3 items: Estimate; Low 95% confidence interval, estimate; High 95% confidence interval, estimate)

This measure counts the closed Iowa vocational rehabilitation cases where the individual received services, and was determined to have deaf & hard of hearing Impairments.

Supplementary files for article "Can Hearing Aids Improve Physical Activity in Adults with Hearing Loss? A Feasibility Study"Background/Objectives: Adults with hearing loss demonstrate poorer overall health outcomes (e.g., physical health, cognitive functioning and wellbeing) and lower levels of physical activity/function compared to those without hearing loss. Hearing aids have the potential to improve cognitive and wellbeing factors, but there is a dearth of evidence on their impact on physical health outcomes. Evidence on the association between hearing aid provision and physical activity is mostly limited to cross-sectional studies. This research aimed to assess whether a study can be performed to identify whether the provision of hearing aids can improve physical activity.Methods: This study employed a preregistered observational (prospective cohort) study design of ten older adults (51–75 years) completed assessments at baseline and again at a six-week follow-up. The participants wore an accelerometer (ActiGraph GT9X) without feedback for the full duration of the study. Feasibility was determined using pre-defined criteria, including study drop-out, adherence to accelerometer use and willingness. A battery of health outcomes was also assessed at baseline and follow-up.Conclusions: Overall, this study was perceived favourably, with all participants reporting that they enjoyed taking part. Participant retention was 100%, and adherence to the wrist-worn accelerometers was “good” (70%). However, recruitment was challenging, and some participants found the accelerometers to be burdensome. Descriptive statistics for all outcome measures showed non-significant changes in the expected direction (e.g., improved physical activity, cognition and wellbeing). Although the study was well received by participants, modifications to the recruitment strategy and activity tracking procedures are necessary before future large-scale trials assessing the effectiveness of hearing aids on physical activity can be undertaken.© The Author(s), CC BY 4.0

Contains detailed information on people registered with Councils that have Social Services Responsibilities (CSSRs) in England as being severely hearing impaired (deaf) or hearing impaired (hard of hearing). This data was collected every three years, but was discontinued from 2010. Further details can be found in the accompanying report.

BackgroundHearing loss and tinnitus have been linked to mild cognitive impairment (MCI); however, the evidence is constrained by ethical and temporal constraints, and few prospective studies have definitively established causation. This study aims to utilize Mendelian randomization (MR) and cross-sectional studies to validate and analyze this association.MethodsThis study employs a two-step approach. Initially, the genetic data of the European population from the Genome-wide association studies (GWAS) database is utilized to establish the causal relationship between hearing loss and cognitive impairment through Mendelian randomization using the inverse variance weighted (IVW) method. This is achieved by identifying strongly correlated single nucleotide polymorphisms (SNPs), eliminating linkage disequilibrium, and excluding weak instrumental variables. In the second step, 363 elderly individuals from 10 communities in Qingdao, China are assessed and examined using methods questionnaire survey and pure tone audiology (PTA). Logistic regression and multiple linear regression were used to analyze the risk factors of MCI in the elderly and to calculate the cutoff values.ResultsMendelian randomization studies have shown that hearing loss is a risk factor for MCI in European populations, with a risk ratio of hearing loss to MCI loss of 1. 23. The findings of this cross-sectional study indicate that age, tinnitus, and hearing loss emerged as significant risk factors for MCI in univariate logistic regression analysis. Furthermore, multivariate logistic regression analysis identified hearing loss and tinnitus as potential risk factors for MCI. Consistent results were observed in multiple linear regression analysis, revealing that hearing loss and age significantly influenced the development of MCI. Additionally, a notable finding was that the likelihood of MCI occurrence increased by 9% when the hearing threshold exceeded 20 decibels.ConclusionThis study provides evidence from genomic and epidemiological investigations indicating that hearing loss may serve as a risk factor for cognitive impairment. While our epidemiological study has found both hearing loss and tinnitus as potential risk factors for cognitive decline, additional research is required to establish a causal relationship, particularly given that tinnitus can manifest as a symptom of various underlying medical conditions.

ABSTRACT Objective: to explore the communication of family health team professionals in providing healthcare for deaf people. Methods: this cross-sectional study was comprised of 39 Family Health teams located in urban and rural areas. A census was conducted and some questionnaires were applied to the Family Health Professionals (31 doctors, 30 nurses, 27 dental surgeons and 4 pharmacists) from the Family Health Support Centers. Results: the great majority of the personnel (60.8%) reported being aware of the existence of Brazilian Sign Language, but none of the interviewees had used it to communicate. Most of the Family Health Team personnel (68.5%) had provided care to a deaf person at some time. However, none of them had taken a complementary course or received any specialized training. Conclusion: the relational dimension is fundamental in developing individual therapy plans. From this perspective, the communication barriers that deaf people face can compromise the necessary bonding for healthcare, which may adversely affect early diagnosis, timely treatment, and adherence to required treatment.

Introduction: Although hearing loss is associated with dementia, the exact causal relationship between hearing loss and dementia remains unclear. Early detection and prevention of hearing loss are essential. In this study, data from the National Health Insurance Research Database (NHIRD) of Taiwan were used to monitor patients with hearing loss for 15 years to determine whether hearing loss leads to dementia. Methods: This retrospective matched-cohort study involved 208,570 individuals, divided into 41,714 patients with hearing loss and 166,856 controls matched by sex, age, and chronic diseases. Cox regression analysis was conducted on data obtained from the NHIRD for the period 2000–2015 to determine the hazard ratio (HR) associated with dementia. Results: The percentage of patients with hearing loss who developed dementia was higher than that of the control group (18.67% vs. 14.10%). The onset age of dementia was younger in the hearing loss group (69.95 vs. 70.31 years, p = 0.001). Middle-aged individuals (45–65 years) with hearing loss were more likely to develop dementia compared with those without hearing loss (48.53% vs. 47.94%, p = 0.03). Compared with the controls, the patients with hearing loss were more likely to develop hyperlipidemia and stroke. In the patients with hearing loss, the adjusted HRs for Alzheimer’s disease (AD), vascular dementia, and other types of dementia were significant. The patients were followed up for an average of 7.82 years. Compared with the controls, the patients with hearing loss exhibited a shorter mean time to dementia onset (5.21 vs. 5.49 years, p < 0.001). Conclusion: Hearing loss may increase the risks of AD, dementia, hyperlipidemia, and stroke. Therefore, health-care providers should closely monitor cardiovascular complications in patients with hearing loss.

ObjectivesSouth Korea's National Health Insurance has provided hearing aids to registered individuals with hearing disabilities since 1989. In 2015, hearing aid subsidies increased to approximately US$1,000. This study aimed to understand hearing loss categories in Korea by analyzing patients between 2010 and 2020 and the effect of the 2015 hearing aid policy change on the prevalence of hearing loss.MethodsThe participants were patients registered on the National Health Insurance Service database from 2010 to 2020 with hearing loss. A total of 5,784,429 patients were included in this study. Hearing loss was classified into conductive, sensorineural, and other categories. Patients with hearing loss were classified according to the International Classification of Diseases diagnostic code. Disability diagnosis and hearing aid prescription were defined using the National Health Insurance Disability and Hearing Aid Code.ResultsThe increase in hearing aid prescriptions and hearing disability registrations following the subsidy increase impacts hearing loss prevalence. Hearing aid prescription and hearing disability were found to have an effect on increasing hearing loss prevalence in univariate and multivariate analyses. The r-value of each analysis exceeded 0.95. Other hearing losses increased rapidly after the increased subsidy.ConclusionA hearing-impaired individual must be diagnosed with a hearing disability and prescribed a hearing aid to receive the subsidy. The prevalence of hearing loss was affected by increased hearing disabilities following changes in the hearing aid subsidy and the number of people prescribed hearing aids. Therefore, caution should be exercised when studying hearing loss prevalence over mid-long-term periods.

This dataset provides Census 2021 estimates that classify usual residents in Northern Ireland by long-term condition: deafness and partial hearing loss, and by broad age bands. The estimates are as at census day, 21 March 2021.

The census collected information on the usually resident population of Northern Ireland on census day (21 March 2021). Initial contact letters or questionnaire packs were delivered to every household and communal establishment, and residents were asked to complete online or return the questionnaire with information as correct on census day. Special arrangements were made to enumerate special groups such as students, members of the Travellers Community, HM Forces personnel etc. The Census Coverage Survey (an independent doorstep survey) followed between 12 May and 29 June 2021 and was used to adjust the census counts for under-enumeration.

Data are available for Northern Ireland and the 11 Local Government Districts.

ABSTRACT INTRODUCTION: Unilateral hearing loss is characterized by a decrease of hearing in one ear only. In the presence of ambient noise, individuals with unilateral hearing loss are faced with greater difficulties understanding speech than normal listeners. OBJECTIVE: To evaluate the speech perception of individuals with unilateral hearing loss in speech perception with and without competitive noise, before and after the hearing aid fitting process. METHODS: The study included 30 adults of both genders diagnosed with moderate or severe sensorineural unilateral hearing loss using the Hearing In Noise Test - Hearing In Noise Test-Brazil, in the following scenarios: silence, frontal noise, noise to the right, and noise to the left, before and after the hearing aid fitting process. RESULTS: The study participants had a mean age of 41.9 years and most of them presented right unilateral hearing loss. In all cases evaluated with Hearing In Noise Test, a better performance in speech perception was observed with the use of hearing aids. CONCLUSION: Using the Hearing In Noise Test-Brazil test evaluation, individuals with unilateral hearing loss demonstrated better performance in speech perception when using hearing aids, both in silence and in situations with a competing noise, with use of hearing aids.

The dataset comprises summary statistics from the meta-GWAS of 17 studies on age-related hearing impairement. The dataset accompanies the following paper:

Genome-wide association meta-analysis identifies 48 risk variants and highlights the role of the stria vascularis in age-related hearing impairment

Please cite the paper if using this dataset.

Phenotype of ARHI was established using ICD diagnoses and self-reported hearing loss. The study comprised 148,152 cases and 575,472 controls or European ancestry. Adult male and female participants were included from the following 17 population-based cohort studies: Age, Genes/Environment Susceptibility - Reykjavik (AGES), the Danish Twin Registry (DTR), the Estonian Genome Center at the University of Tartu (EGCUT), FinnGen, Framingham Heart Study (FHS), Health Aging and Body Composition (HABC), Italian Network of Genetic Isolates - Friuli Venezia Giulia (INGI-FVG), the Rotterdam Study (RS, cohorts 1 - 3), the Salus in Apulia study (SA; formerly known as Great Age study), Screening Across the Lifespan Twin (SALT and SALTY - young), Screening Twin Adults: Genes and Environment (STAGE), TwinsUK, UK Biobank (UKBB), and the Women’s Genome Health Study (WGHS).

UK Biobank data have been used under project #11516.

Individual GWASs have been QC'd and harmonyzed using EasyQC followed by fixed-effects IVW meta-analysis using METAL. The dataset includes the results of meta-analysis for n = 8,244,938 SNV with MAF >0.001 and present in at least 9 cohorts.

Dataset columns:

SNP, rsID

CHR, chromosome

BP, genomic position (hg19)

Allele1, effect allele

Allele2, other allele

Freq1, mean frequency of Allele1

FreqSE, standard error of Freq1

MinFreq, minimal frequency of Allele1 in the study cohorts

MaxFreq, maximal frequency of Allele1 in the study cohorts

Effect, effect size from the meta-analysis for Allele1

StdErr, standard error of Effect

P.value, corresponding p-value for meta-analysis

Direction, direction of effects in individual studies

HetISq, I² statistic for heterogeneity between studies

HetChiSq, chi² statistic for heterogeneity between studies

HetDf, degrees of freedom for the chi² statistic

HetPval, p-value for heterogeneity between studies

N, summary sample size

Dataset columns description:

Seventeen studies included:

Context

Health care in the United States is provided by many distinct organizations. Health care facilities are largely owned and operated by private sector businesses. 58% of US community hospitals are non-profit, 21% are government owned, and 21% are for-profit. According to the World Health Organization (WHO), the United States spent more on healthcare per capita ($9,403), and more on health care as percentage of its GDP (17.1%), than any other nation in 2014. Many different datasets are needed to portray different aspects of healthcare in US like disease prevalences, pharmaceuticals and drugs, Nutritional data of different food products available in US. Such data is collected by surveys (or otherwise) conducted by Centre of Disease Control and Prevention (CDC), Foods and Drugs Administration, Center of Medicare and Medicaid Services and Agency for Healthcare Research and Quality (AHRQ). These datasets can be used to properly review demographics and diseases, determining start ratings of healthcare providers, different drugs and their compositions as well as package informations for different diseases and for food quality. We often want such information and finding and scraping such data can be a huge hurdle. So, Here an attempt is made to make available all US healthcare data at one place to download from in csv files.

Content

• Nhanes Survey (National Health and Nutrition Examination Survey) - The National Health and Nutrition Examination Survey (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The survey is unique in that it combines interviews and physical examinations. NHANES is a major program of the National Center for Health Statistics (NCHS). NCHS is part of the Centers for Disease Control and Prevention (CDC) and has the responsibility for producing vital and health statistics for the Nation. The NHANES interview includes demographic, socioeconomic, dietary, and health-related questions. The examination component consists of medical, dental, and physiological measurements, as well as laboratory tests administered by highly trained medical personnel. The diseases, medical conditions, and health indicators to be studied include: Anemia, Cardiovascular disease, Diabetes, Environmental exposures, Eye diseases, Hearing loss, Infectious diseases, Kidney disease, Nutrition, Obesity, Oral health, Osteoporosis, Physical fitness and physical functioning, Reproductive history and sexual behavior, Respiratory disease (asthma, chronic bronchitis, emphysema), Sexually transmitted diseases, Vision. 10000 individuals are surveyed to represent US statistics. Five files in this datasets represent current recent Nhanes data -
  Nhanes_2005_2006.csv
  Nhanes_2007_2008.csv
  Nhanes_2009_2010.csv
  Nhanes_2011_2012.csv
  Nhanes_2013_2014.csv
  
  • Data fields' description -
    • Nhanes_2005_2006.csv - Demographic, Dietary, Examinations, Laboratory
    • Nhanes_2007_2008.csv - Demographic, Dietary, Examinations, Laboratory
    • Nhanes_2009_2010.csv - Demographic, Dietary, Examinations, Laboratory
    • Nhanes_2011_2012.csv - Demographic, Dietary, [Examinations](http://https://wwwn.cdc.gov/nchs/nhanes/search/variab...