Abstract
Objective
To index levels of hearing loss with respect to area-level indices of deprivation in a Welsh population.
Design
A cross-sectional observational study of all adults (aged >18) that attended Abertawe Bro Morgannwg University (ABMU) Health Board audiology services between 2016 and 2018. Service access, first hearing aid fitting appointment rates and hearing loss at time of first hearing aid provision were used to index population hearing loss versus area-level indices of deprivation based on patient postcode.
Setting
Primary and secondary care.
Participants
59 493 patient entries met the inclusion criteria. Patient entries were grouped by age (18–30, 31–40, 41–50, 51–60, 61–70, 71–80, >80 years) and deprivation decile.
Results
The interaction between age group and deprivation decile predicted access rate to ABMU audiology services (b=−0.24, t(6858) = −2.86, p<0.01) with audiology services accessed more frequently by the most deprived versus the least deprived decile in every age group (p<0.05), except the >80 years. First hearing aid fitting rates were highest among the most deprived in the four youngest age groups (p<0.05). Severity of hearing loss at the time of first hearing aid fitting was worse among the most deprived in the five oldest age groups (p<0.01).
Conclusions
Hearing health inequalities are prevalent among adults accessing ABMU audiology services. Our findings suggest that deprivation increases the likelihood of developing hearing loss, brings earlier onset of hearing loss and is linked to delays in getting help for hearing problems. However, it is not possible to know the true scale of these disparities without knowing the hearing health of the Welsh adult population including those who do not seek help for hearing problems.
Keywords: Audiology, EPIDEMIOLOGY, Health Equity
STRENGTHS AND LIMITATIONS OF THIS STUDY.
We analysed 137 029 audiology appointments attended by 37 831 patients, representing 1.5% of the adult population of Wales.
Investigating total service utilisation is a novel approach to index population hearing health needs.
We analysed first hearing aid provision rates in conjunction with audiometric thresholds at time of first hearing aid provision.
The use of an area-level deprivation index may obscure individual-level variation in deprivation.
This study was restricted to individuals that had accessed audiology services, likely underestimating deprivation-related hearing health inequalities.
Introduction
Hearing loss (HL) is the second-leading cause of years lived with disability globally,1 with one in five adults in the UK estimated to be living with HL.2 The effect of untreated HL extends beyond poor speech detection and comprehension, being associated with poorer quality of life, increased depression and anxiety, increased cognitive decline and risk of dementia, and lower workforce productivity.3–8 The burden of HL, however, is not evenly distributed, with higher rates of HL observed among the most deprived.9–11 Low socioeconomic status (SES) is a long-standing source of health inequalities in the UK and is known to have a detrimental impact on multiple aspects of health.12 The relationship between HL and deprivation is complex, bidirectional and influential throughout the life course though ‘social causation’ and ‘health selection’ mechanisms.8 13–17
The Medical Research Council’s National Study of Hearing conducted during the 1980s remains the ‘gold standard’ for UK HL prevalence data.18–20 Davis21 found that age, gender and socioeconomic group have a significant effect on the prevalence of hearing impairment, though the effect of socioeconomic group was stronger for men than for women. Over the last four decades UK Government policies have created safer working environments, promoted healthier lifestyles and behaviours, and gradually decreased the proportion of adults living in poverty.22–24 What impact (if any) this has had on the prevalence and severity of HL among adults is unknown.
There is a national imperative to complete new epidemiology research to understand the hearing health needs of the present adult population particularly with respect to hearing health inequalities. Large-scale audiometric studies such as the National Study of Hearing, however, require substantial time and resources (eg, specialist equipment, soundproof facilities and trained staff) meaning that it may never be possible to replicate the National Study of Hearing. Attempts to estimate the prevalence of HL in the UK using biomedical and national survey databases have produced results similar to publications from other high-income countries.15 25–27 Though such methods typically rely on screening tools that do not accurately record the type or severity of HL potentially underestimating or overestimating prevalence rates. Electronic health records are becoming ever more frequently used in a secondary capacity for research purposes.28 29 Audiological health records have the potential to complement clinical research by informing population hearing health needs and are an underused resource in audiological research.30 31 In Wales, the majority of the adult population acquire hearing aids through the National Health Service (NHS), though private dispensers are available nationally.32 Data routinely collected during NHS audiology clinics may, therefore, reveal unique insights into the wider hearing health needs of service users and further our understanding of HL disease progression.
In this study, we used NHS audiological health records as an efficient and cost-effective means to explore the demographics of HL in the general population. Leveraging service-level hearing healthcare data to understand population-level hearing needs is informative with both scientific and clinical application.33 Audiology service utilisation and hearing aid (HA) uptake may be informative with respect to population demographics of HL in the UK, as several previous studies indicated that SES does not impact audiology service use and HA uptake in countries with socially subsidised hearing healthcare, including the UK.34
This cross-sectional observational study had two objectives: to compare levels of (1) HL (indexed by access to NHS audiology services) and (2) HL severity at first hearing aid fitting according to SES across all adult age groups. Knowing that HL prevalence is inversely correlated with SES, we expected audiology services to be used more by persons living in the most deprived areas. We sought to quantify hearing health inequalities in Wales by observing a large clinical cohort of the adult audiology patients.
Methods
Eligible population
The audiological health records of adult patients aged >18 years old accessing Abertawe Bro Morgannwg University (ABMU) Health Board audiology services between 1 January 2016 and 30 December 2018 formed the population for this study. The ABMU Health Board provided audiology services for the local authorities of Swansea, Neath Port Talbot, and Bridgend between 2012 and 2019. Service provision across all sites was consistent and audiological health records stored electronically using Auditbase software (Auditdata A/S, Copenhagen).
Patient data were mined using SAP Crystal Reports (V.11.0.0.1282) software. Individual patient data were categorised by age group (18–30, 31–40, 41–50, 51–60, 61–70, 71–80, >80 years) and lower super output area (LSOA) using patients date of birth and postcode, respectively. Wales (population 3.2 million) is divided into 1909 LSOAs based on the Office for National Statistics Census geographies, each LSOA has an average population of 1600 people. Within the ABMU Health Board boundary there are 327 LSOAs. All identifiable information (ie, individual date of birth and postcode) was then removed to anonymise the data. The postcode which defines the LSOA is the residence at the time of the data collection.
Deprivation score
The Welsh Index of Multiple Deprivation (WIMD) is the Welsh Government’s official measure of relative deprivation for small geographical areas in Wales.35 The WIMD ranks all the LSOAs in Wales from 1 (most deprived) to 1909 (least deprived), and then groups the LSOAs into deciles, with decile 1 being the most deprived and decile 10 the least deprived.35 WIMD rank is calculated using 8 separate domains of deprivation composed of 47 underlying indicator datasets relating to both material and social aspects of deprivation.36 The WIMD is similar to other UK Indices of Multiple Deprivation though it is not directly comparable as it uses different indices and weighting formulae. A limitation of all Indices of Multiple Deprivation is that they do not provide a measure of the amount of deprivation in any given area, and therefore, cannot be used to compare how deprived one area is to another.
The WIMD is typically updated every 3–5 years and several publications are publicly available. The 2019 WIMD publication was used for this study. Every patient was assigned a WIMD decile according to the LSOA associated with their postcode at the time of the data collection. Some cases will have moved address between the time that they accessed the service and the time of the data collection. It was assumed that the number of cases affected would be small.
Cross-sectional observation
Patients who met the sample criteria were organised chronologically by date of appointment. The sample data were copied to create two identical datasets and processed separately. For the accessing audiology services dataset a patient could be included every year they accessed audiology, the earliest date of access per year for each individual was used and all subsequent points of access within the same year removed. For the first HA fitting dataset, individuals could only be considered to have completed one first HA fitting appointment, any subsequent first HA fitting appointments at later dates were removed. Data were then tallied by age group and LSOA for both datasets. Incidence proportion rates (per 1000 persons) were calculated for the accessing audiology services and first HA fitting using national population estimates.37–39
Accessing audiology services
A patient was considered to have accessed ABMU Health Board audiology services if they attended a scheduled audiology appointment, used a ‘walk in’ clinic, or were seen by an audiologist providing clinical support for ear, nose and throat clinicians.
First hearing aid fitting
A patient was considered a new HA user if they attended a first HA fitting appointment. For an individual within the ABMU Health Board boundary to be provided an NHS hearing aid(s) they must be seen by an ABMU Health Board audiologist and the audiologist must use their clinical judgement to decide whether the patient would gain benefit from a hearing aid(s). There were no formal audiometric criteria for hearing aid(s) eligibility. Any patient without a recent audiogram (within 2 years of fitting appointment) was excluded from the sample.
Hearing impairment at time of first hearing aid provision
Hearing impairment at time of first HA provision was derived from the average of air conduction thresholds at 0.5, 1, 2 and 4 kHz in the better hearing ear measured in dB HL using the audiogram obtained prior to the first HA fitting appointment. Samples with audiogram data for one ear only were excluded (77 cases, 1%).
Analysis and statistical tests
The assumptions of parametric tests were tested for each sample. In any instance of non-normality transformations were explored and equivalent non-parametric tests considered. Normality was assumed for any samples n>30 according to the central limit theorem.40
Multilevel linear models were constructed to assess whether age group, deprivation decile or the interaction between the two variables are important in predicting access rates to audiology services, first HA fitting appointment rates or better ear average at time of first HA provision. Any variables found to have a significant (p<0.05) effect were explored further using appropriate parametric and non-parametric tests.
Parametric testing included the one-way independent analysis of variance (ANOVA) or Welch’s F test, depending on whether homogeneity of variance was violated. Trend analysis was completed on any significant ANOVA or Welch’s F test results. If the sample data did not meet the assumptions of parametric tests the Kruskal-Wallis test was used in conjunction with the Jonckheere-Terpstra test for trend analysis. All analyses were conducted in R (V.3.6.2).
Patient and public involvement
None.
Results
Study population
There are 327 LSOAs within the ABMU boundary representing all WIMD decile groups. In 2018 the adult (>18 years old) ABMU population was estimated to be 429 644, representing 17.1% of the Welsh adult population. This study analysed 137 029 audiology appointments attended by 37 831 patients, representing 8.8% of the adult ABMU population. Table 1 compares the distribution of the adult population and LSOAs between WIMD decile groups within the ABMU boundary with that of Wales. The deprivation distribution for the ABMU population is like the general Welsh population, although with a slightly higher proportion of those at the two extremes of deprivation.
Table 1.
ABMU population characteristics compared with the Welsh population38
| Deprivation (WIMD decile) | Adult population (>18 years old) | No of LSOAs | ||
| ABMU | Wales | ABMU | Wales | |
| 1 (most deprived) | 44 955 (10.4%) | 226 025 (9%) | 37 (11.3%) | 191 (10%) |
| 2 | 58 282 (13.5%) | 241 373 (9.6%) | 46 (14.1%) | 191 (10%) |
| 3 | 49 286 (11.4%) | 241 587 (9.6%) | 39 (11.9%) | 191 (10%) |
| 4 | 44 875 (10.4%) | 248 564 (9.9%) | 34 (10.4%) | 191 (10%) |
| 5 | 31 493 (7.3%) | 257 357 (10.3%) | 24 (7.3%) | 191 (10%) |
| 6 | 27 268 (6.3%) | 266 345 (10.6%) | 20 (6.1%) | 191 (10%) |
| 7 | 34 128 (7.9%) | 263 584 (10.5%) | 23 (7.0%) | 191 (10%) |
| 8 | 36 947 (8.6%) | 256 673 (10.2%) | 26 (8.0%) | 191 (10%) |
| 9 | 45 511 (10.5%) | 262 929 (10.5%) | 34 (10.4%) | 191 (10%) |
| 10 (least deprived) | 58 899 (13.7%) | 244 409 (9.7%) | 44 (13.5%) | 190 (10%) |
| Total | 431 644 | 2 508 846 | 327 | 1909 |
ABMU, Abertawe Bro Morgannwg University; LSOA, lower super output area; WIMD, Welsh Index of Multiple Deprivation.
Accessing audiology services
There were 59 493 patient entries that met the criteria for the evaluation of access to services. The mean access rate between the years 2016–2018 was 69.11 per 1000 persons (95% CI: 67.08 to 71.14). Figure 1A, B illustrates how the access rate means varied by deprivation decile and age group.
Figure 1.
(A) Mean access rate to audiology services per 1000 persons by deprivation decile and age group. (B) Zoomed in section of figure 1A (y axis: 0–50). (C) Mean first hearing aid fitting rate per 1000 persons by deprivation decile and age group. (D) Mean better hearing ear average when obtaining first NHS hearing aid by deprivation decile and age group. All four graphs display linear lines of best fit with 95% CI error bars. Deprivation decile group 1=most deprived, deprivation decile group 10=least deprived. NHS, National Health Service.
Age group predicted access to audiology services, with older groups associated with greater access rate, b=33.83, t(5) = 4.99, p<0.01. Deprivation decile did not predict access to audiology services independently, b=−0.13, t(6858)=−0.35, p>0.05. However, the interaction between age group and deprivation decile did predict access rate, indicating that the effect of deprivation decile on access rate to audiology services depends on age group, b=−0.24, t(6858)=−2.86, p<0.01. Linear models for each age group revealed that deprivation decile predicted access rate to audiology services in every age group. As deprivation decile increased (less deprived), access rates decreased in every age group except the ‘>80’ group.
First hearing aid fitting
There were 7775 patient entries that met the criteria for the first HA fitting evaluation. First HA fitting appointments accounted for 5.7% of total service utilisation (137 029 appointments). The mean first HA fitting appointment rate between the years 2016–2018 was 8.42 per 1000 persons (95% CI 8.11 to 8.72). First HA fitting appointment rates per 1000 persons varied by deprivation decile in the four youngest age groups (figure 1C). Jonckheere-Terpstra testing revealed linear trends in all four of these age groups; as deprivation decile increased (less deprived) first HA fitting appointment rate decreased.
Hearing impairment at time of first hearing aid provision
There were 7698 patient entries that met the criteria for the evaluation of hearing impairment at time of first HA provision. The mean better hearing ear average at time of first HA provision between the years 2016–2018 was 37.0 dB HL (95% CI 36.8 to 37.4). Better hearing ear average at time of first HA provision (figure 1D) was predicted by age group, b=0.26, t(5) = 7.43, p<0.01, and deprivation decile, b=−0.08, t(7689)=−5.38, p<0.01. This indicates that with increasing age and deprivation, better hearing ear average deteriorated. There was a significant interaction between age group and deprivation with better hearing ear average at time of first HA provision, indicating more severe HL among young, more deprived groups, b=0.01, t(7689)=2.69, p<0.01. Linear models revealed that as deprivation decile increased (less deprived), better hearing ear average decreased in the five oldest age groups explored.
Discussion
This population-level investigation found that (1) NHS audiology service utilisation was higher among the most deprived (except for the very oldest age group), (2) HA provision was higher for the most deprived among the four youngest age groups and (3) hearing impairment was more severe at the time of first HA provision among the most deprived. Previous studies have reported HL being associated with lower SES in the UK.10 11 21 The findings of this study are novel in suggesting that HL is not only more prevalent but has earlier onset and is more severe among people from more deprived backgrounds. The inequalities observed in this study are likely underestimates of the true extent of SES hearing health inequalities in the general population as specialist outpatient services are typically accessed more by affluent individuals after taking individual health needs into account.41 In addition, reporting hearing problems is the strongest determinant of seeking help for hearing.42–44 People from low SES backgrounds, however, tend to under report health conditions,45 including HL,41 42 further supporting the pessimistic interpretation of the authors.
Earlier onset of HL in people from more deprived backgrounds
HL with advancing age is common.46 However, the rate of HL is influenced by factors including unhealthy diet, smoking, excess alcohol consumption, exposure to noise or ototoxic drugs, whereby insults to the auditory system accumulate over time through the life course.47 As low SES is associated with more frequent unhealthy behaviours that impact hearing, these lifestyle factors may at least partially explain why HL occurs more commonly among low SES groups.48–51 Our observation that HL is particularly prevalent at earlier ages among low SES individuals is consistent with evidence that deprivation accelerates the ageing process in general, with higher levels of illness and frailty among more deprived people at earlier ages compared with more affluent people.52 53
The Welsh government has announced a comprehensive national strategy, supported by legislation, to achieve a fairer society and reduce health inequalities.54–58 The health impacts of this national strategy are yet to be seen, though addressing the social determinants of poor general health associated with low SES would likely also improve hearing levels. To address hearing health inequalities in the short term, health policies should aim to encourage persons living in the most deprived areas to recognise hearing impairment earlier and report symptoms sooner. Uptake of NHS health screening programmes is historically poor among the most deprived,59–61 though advances in internet-based testing offers a cost-effective means to improve participation as internet use nears ubiquity in the UK.62 The method of screening should, therefore, be carefully considered with respect to accessibility and equity if designing an adult national programme for hearing impairment to avoid marginalising the most deprived further. Alternatively, placing hearing services in primary care settings may offer potential for easier access to hearing care. Primary care audiology services have been successfully piloted in Wales and have shown potential to increase accessibility by reducing waiting times and simplifying patient referral pathways, while improving clinical outcomes through earlier intervention.63 64
The primary limitation of this study was the use of audiology service utilisation to index population hearing levels. We argue that service utilisation is a valid proxy for population levels of hearing impairment because previous studies suggested that SES is not associated with use of audiology services in the UK.33 To describe the full extent of the hearing health inequalities observed in this study, one would have to conduct an audiometric survey of hearing levels in a representative population sample.
A second limitation was the use of an area-level index of deprivation as a proxy for individual SES. Several studies have found that area-level and individual-level socioeconomic measurements do not always correlate well with the socioeconomic characteristics of the individual typically worse than those of the area they live in.65–67 Despite the potential to underestimate socioeconomic inequalities, area-level deprivation measures have been shown to be a sufficiently valid means of detecting health inequalities when individual-level data are not available.68 69
This report focused on one large Welsh health board. Collaboration between the seven Local Health Boards in Wales to produce a report representative of the entire country may reveal further insights about the hearing health needs of adults that are frequently under-represented in audiology studies (ie, young adults and ethnic minorities, in addition to those from low SES backgrounds).
Conclusion
HL is not only more prevalent but occurs at younger age among people from more deprived backgrounds. When they do present at audiology clinics, people from more deprived backgrounds exhibit more severe HL. People from more deprived backgrounds may, therefore, tend to wait longer before seeking help for hearing problems. HL is associated with very large burden due to impacts on quality of life and reduced productivity. People from more deprived backgrounds experience a disproportionate level of burden due to HL. There is an urgent imperative for audiologists and public health policy-makers to redress this iniquity.
Supplementary Material
Footnotes
Twitter: @JackAllum1, @PiersDawes
Contributors: JA acted as guarantor and was responsible for the design, data acquisition, analysis and interpretation of results, and writing of the original manuscript, review and editing. RM contributed to the design of the study, data acquisition, interpretation of results and revision of manuscript. KU contributed to the interpretation of results and revision of manuscript. JJK contributed to the analysis and interpretation of results, and revision of manuscript. PD contributed to the interpretation of results and revision of manuscript.
Funding: This research was supported by the NIHR Manchester Biomedical Research Centre.
Disclaimer: The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health.
Competing interests: None declared.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review: Not commissioned; externally peer reviewed.
Data availability statement
No data are available.
Ethics statements
Patient consent for publication
Not applicable.
Ethics approval
This cross-sectional observational study was completed within routine clinical auditing procedures and considered non-research when approved by the ABMU Health Board Joint Study Review Committee on 3 October 2018.
References
- 1.World Health Organization [Internet] . Prevention of blindness and deafness – facts about deafness. n.d. Available: https://www.who.int/pbd/deafness/facts/en/
- 2.RNID . Facts and figures. n.d. Available: https://rnid.org.uk/about-us/research-and-policy/facts-and-figures/
- 3.Mulrow CD, Aguilar C, Endicott JE, et al. Quality-Of-Life changes and hearing impairment. A randomized trial. Ann Intern Med 1990;113:188–94. 10.7326/0003-4819-113-3-188 [DOI] [PubMed] [Google Scholar]
- 4.Chisolm TH, Johnson CE, Danhauer JL, et al. A systematic review of health-related quality of life and hearing AIDS: final report of the American Academy of audiology Task force on the health-related quality of life benefits of amplification in adults. J Am Acad Audiol 2007;18:151–83. 10.3766/jaaa.18.2.7 [DOI] [PubMed] [Google Scholar]
- 5.Johnson CE, Danhauer JL, Ellis BB, et al. Hearing aid benefit in patients with mild sensorineural hearing loss: a systematic review. J Am Acad Audiol 2016;27:293–310. 10.3766/jaaa.14076 [DOI] [PubMed] [Google Scholar]
- 6.Lin FR, Metter EJ, O’Brien RJ, et al. Hearing loss and incident dementia. Arch Neurol 2011;68:214–20. 10.1001/archneurol.2010.362 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Kramer SE, Kapteyn TS, Houtgast T. Occupational performance: comparing normally-hearing and hearing-impaired employees using the Amsterdam checklist for hearing and work. Int J Audiol 2006;45:503–12. 10.1080/14992020600754583 [DOI] [PubMed] [Google Scholar]
- 8.Nachtegaal J, Festen JM, Kramer SE. Hearing ability in working life and its relationship with sick leave and self-reported work productivity. Ear Hear 2012;33:94–103. 10.1097/AUD.0b013e318228033e [DOI] [PubMed] [Google Scholar]
- 9.Stevens G, Flaxman S, Brunskill E, et al. Global and regional hearing impairment prevalence: an analysis of 42 studies in 29 countries. Eur J Public Health 2013;23:146–52. 10.1093/eurpub/ckr176 [DOI] [PubMed] [Google Scholar]
- 10.Dawes P, Fortnum H, Moore DR, et al. Hearing in middle age: a population snapshot of 40- to 69-year olds in the United Kingdom. Ear Hear 2014;35:e44–51. 10.1097/AUD.0000000000000010 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Scholes S, Biddulph J, Davis A, et al. Socioeconomic differences in hearing among middle-aged and older adults: cross-sectional analyses using the health survey for England. BMJ Open 2018;8:e019615. 10.1136/bmjopen-2017-019615 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Marmot M, Allen J, Goldblatt P, et al. Fair Society Healthy Lives: The Marmot Review. Strategic review of health inequalities in England post-2010. London: Department of International Development, 2010. [Google Scholar]
- 13.Kröger H, Pakpahan E, Hoffmann R. What causes health inequality? A systematic review on the relative importance of social causation and health selection. Eur J Public Health 2015;25:951–60. 10.1093/eurpub/ckv111 [DOI] [PubMed] [Google Scholar]
- 14.Fransen E, Topsakal V, Hendrickx J-J, et al. Occupational noise, smoking, and a high body mass index are risk factors for age-related hearing impairment and moderate alcohol consumption is protective: a European population-based multicenter study. J Assoc Res Otolaryngol 2008;9:264–76; 10.1007/s10162-008-0123-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Agrawal Y, Platz EA, Niparko JK. Risk factors for hearing loss in US adults: data from the National health and nutrition examination survey, 1999 to 2002. Otol Neurotol 2009;30:139–45. 10.1097/MAO.0b013e318192483c [DOI] [PubMed] [Google Scholar]
- 16.Teasdale TW, Sorensen MH. Hearing loss in relation to educational attainment and cognitive abilities: a population study. Int J Audiol 2007;46:172–5. 10.1080/14992020601089484 [DOI] [PubMed] [Google Scholar]
- 17.Hogan A, O’Loughlin K, Davis A, et al. Hearing loss and paid employment: Australian population survey findings. Int J Audiol 2009;48:117–22. 10.1080/14992020802449008 [DOI] [PubMed] [Google Scholar]
- 18.Akeroyd MA, Foreman K, Holman JA. Estimates of the number of adults in England, Wales, and Scotland with a hearing loss. International Journal of Audiology 2014;53:60–1. 10.3109/14992027.2013.850539 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.RNID [Internet] . Action on hearing loss: hearing matters. 2015. Available: https://rnid.org.uk/about-us/research-and-policy/social-research-reports/hearing-matters/
- 20.James SL, Abate D, Abate KH, et al. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the global burden of disease study 2017. The Lancet 2018;392:1789–858. 10.1016/S0140-6736(18)32279-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Davis AC. Hearing in adults. London, UK: Whurr, 1995. [Google Scholar]
- 22.The control of noise at work regulations 2005 (UK). n.d.
- 23.HM Government . Healthy lives, healthy people; our strategy for public health in England. 2010. Available: https://www.gov.uk/government/publications/healthy-lives-healthy-people-our-strategy-for-public-health-in-england
- 24.Francis-Devine B. House of commons library: poverty in the UK: statistics. Briefing Paper 2020;7095. Available: https://researchbriefings.files.parliament.uk/documents/SN07096/SN07096.pdf [Google Scholar]
- 25.Cruickshanks KJ, Nondahl DM, Tweed TS, et al. Education, occupation, noise exposure history and the 10-yr cumulative incidence of hearing impairment in older adults. Hear Res 2010;264:3–9. 10.1016/j.heares.2009.10.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Rigters SC, Metselaar M, Wieringa MH, et al. Contributing determinants to hearing loss in elderly men and women: results from the population-based Rotterdam study. Audiol Neurootol 2016;21 Suppl 1:10–5. 10.1159/000448348 [DOI] [PubMed] [Google Scholar]
- 27.Goman AM, Lin FR. Prevalence of hearing loss by severity in the United States. Am J Public Health 2016;106:1820–2. 10.2105/AJPH.2016.303299 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Jones KH, Ford DV, Thompson S, et al. A profile of the Sail databank on the UK secure research platform. Int J Popul Data Sci 2019;4:1134. 10.23889/ijpds.v4i2.1134 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Kim E, Rubinstein SM, Nead KT, et al. The evolving use of electronic health records (EHR) for research. Semin Radiat Oncol 2019;29:354–61. 10.1016/j.semradonc.2019.05.010 [DOI] [PubMed] [Google Scholar]
- 30.Singh G, Launer S. Social context and hearing aid adoption. Trends Hear 2016;20:2331216516673833. 10.1177/2331216516673833 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Saunders GH, Dillard LK, Zobay O, et al. Electronic health records as a platform for audiological research: data validity, patient characteristics, and hearing-aid use persistence among 731,213 U.S. veterans. Ear Hear 2021;42:927–40. 10.1097/AUD.0000000000000980 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Dillon H, Day J, Bant S, et al. Adoption, use and non-use of hearing AIDS: a robust estimate based on Welsh national survey statistics. International Journal of Audiology 2020;59:567–73. 10.1080/14992027.2020.1773550 [DOI] [PubMed] [Google Scholar]
- 33.Dillard LK, Saunders GH, Zobay O, et al. Insights into conducting audiological research with clinical databases. Am J Audiol 2020;29:676–81. 10.1044/2020_AJA-19-00067 [DOI] [PubMed] [Google Scholar]
- 34.Sawyer CS, Armitage CJ, Munro KJ, et al. Biopsychosocial classification of hearing health seeking in adults aged over 50 years in England. Ear Hear 2020;41:1215–25. 10.1097/AUD.0000000000000839 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Welsh Government . WIMD 2019: guidance. 2019a. Available: https://gov.wales/welsh-index-multiple-deprivation-index-guidance
- 36.Welsh Government . WIMD 2019: technical report. 2019. Available: https://gov.wales/welsh-index-multiple-deprivation-index-guidance
- 37.Office for National Statistics . Mid-2016: superseded [ xls document. 2017. Available: https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/populationestimatesforukenglandandwalesscotlandandnorthernireland
- 38.Office for National Statistics . Mid-2017 [ xls document ]. 2018. Available: https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/populationestimatesforukenglandandwalesscotlandandnorthernireland
- 39.Office for National Statistics . Mid-2018: 2018 La boundaries [ xls document ]. 2019. Available: https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/populationestimatesforukenglandandwalesscotlandandnorthernireland
- 40.Field D, Miles J, Field Z. Discovering Statistics Using R. London, UK: SAGE Publications Ltd, 2012. [Google Scholar]
- 41.Cookson R, Propper C, Asaria M, et al. Socio-Economic inequalities in health care in England. Fiscal Studies 2016;37:371–403. 10.1111/j.1475-5890.2016.12109 [DOI] [Google Scholar]
- 42.Scholes S, Mindell J. Health Survey for England 2014, Volume 1, health, social care and lifestyles. Leeds, UK: Health and Social Care Information Centre, 2015. [Google Scholar]
- 43.Knudsen LV, Oberg M, Nielsen C, et al. Factors influencing help seeking, hearing aid uptake, hearing aid use and satisfaction with hearing AIDS: a review of the literature. Trends Amplif 2010;14:127–54. 10.1177/1084713810385712 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Meyer C, Hickson L. What factors influence help-seeking for hearing impairment and hearing aid adoption in older adults? Int J Audiol 2012;51:66–74. 10.3109/14992027.2011.611178 [DOI] [PubMed] [Google Scholar]
- 45.Chatterji P, Joo H, Lahiri K. Examining the education gradient in chronic illness. Educ Econ 2015;23:735–50. 10.1080/09645292.2014.944858 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Wilson BS, Tucci DL, Merson MH, et al. Global hearing health care: new findings and perspectives. The Lancet 2017;390:2503–15. 10.1016/S0140-6736(17)31073-5 [DOI] [PubMed] [Google Scholar]
- 47.Gates GA, Mills JH. Presbycusis. The Lancet 2005;366:1111–20. 10.1016/S0140-6736(05)67423-5 [DOI] [PubMed] [Google Scholar]
- 48.Schuit AJ, van Loon AJM, Tijhuis M, et al. Clustering of lifestyle risk factors in a general adult population. Preventive Medicine 2002;35:219–24. 10.1006/pmed.2002.1064 [DOI] [PubMed] [Google Scholar]
- 49.Wardle J, Steptoe A. Socioeconomic differences in attitudes and beliefs about healthy lifestyles. Journal of Epidemiology & Community Health 2003;57:440–3. 10.1136/jech.57.6.440 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Huurre T, Aro H, Rahkonen O. Well-Being and health behaviour by parental socioeconomic status. Social Psychiatry and Psychiatric Epidemiology 2003;38:249–55. 10.1007/s00127-003-0630-7 [DOI] [PubMed] [Google Scholar]
- 51.Poortinga W. The prevalence and clustering of four major lifestyle risk factors in an English adult population. Preventive Medicine 2007;44:124–8. 10.1016/j.ypmed.2006.10.006 [DOI] [PubMed] [Google Scholar]
- 52.Whitley E, Benzeval M, Popham F. Associations of successful aging with socioeconomic position across the life-course: the West of Scotland twenty-07 prospective cohort study. J Aging Health 2018;30:52–74. 10.1177/0898264316665208 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Kok AAL, Aartsen MJ, Deeg DJH, et al. Socioeconomic inequalities in a 16-year longitudinal measurement of successful ageing. J Epidemiol Community Health 2016;70:1106–13. 10.1136/jech-2015-206938 [DOI] [PubMed] [Google Scholar]
- 54.Wellbeing of future generations (Wales) act. 2015.
- 55.Social services and wellbeing (Wales) act. 2014.
- 56.Regulation and inspection of social care (Wales) act. 2016.
- 57.Welsh Government . Prosperity for all: economic action plan. 2017. Available: https://gov.wales/prosperity-all-economic-action-plan
- 58.Welsh Government . A healthier Wales: our plan for health and social care. 2019c. Available: https://gov.wales/healthier-wales-long-term-plan-health-and-social-care
- 59.Maheswaran R, Pearson T, Jordan H, et al. Socioeconomic deprivation, travel distance, location of service, and uptake of breast cancer screening in North derbyshire, UK. J Epidemiol Community Health 2006;60:208–12. 10.1136/jech.200X.038398 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Jacomelli J, Summers L, Stevenson A, et al. Editor’s choice-inequalities in abdominal aortic aneurysm screening in England: effects of social deprivation and ethnicity. Eur J Vasc Endovasc Surg 2017;53:837–43. 10.1016/j.ejvs.2017.03.006 [DOI] [PubMed] [Google Scholar]
- 61.Lal N, Singh HK, Majeed A, et al. The impact of socioeconomic deprivation on the uptake of colorectal cancer screening in London. J Med Screen 2021;28:114–21. 10.1177/0969141320916206 [DOI] [PubMed] [Google Scholar]
- 62.Dawes P, Munro KJ, Frank TL, et al. Uptake of internet-delivered UK adult hearing assessment. Int J Audiol 2021;60:885–9. 10.1080/14992027.2021.1886353 [DOI] [PubMed] [Google Scholar]
- 63.Health Technology Wales . TER078-primary-care-audiology. 2020. Available: https://healthtechnology.wales/reports-guidance/primary-care-audiology/
- 64.Loescher T, Allum J, Phillips N. Prudent healthcare in practice: integration of audiology services into primary care. BMJ Open Qual 2022;11:e001884. 10.1136/bmjoq-2022-001884 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65.Hanley GE, Morgan S. On the validity of area-based income measures to proxy household income. BMC Health Serv Res 2008;8:79. 10.1186/1472-6963-8-79 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Marra CA, Lynd LD, Harvard SS, et al. Agreement between aggregate and individual-level measures of income and education: a comparison across three patient groups. BMC Health Serv Res 2011;11:69. 10.1186/1472-6963-11-69 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67.Behanova M, Reijneveld SA, Nagyova I, et al. Are area-level and individual-level socioeconomic factors associated with self-rated health in adult urban citizens? Evidence from Slovak and Dutch cities. Eur J Public Health 2017;27(suppl_2):86–92. 10.1093/eurpub/ckv095 [DOI] [PubMed] [Google Scholar]
- 68.Krieger N. Overcoming the absence of socioeconomic data in medical records: validation and application of a census-based methodology. Am J Public Health 1992;82:703–10. 10.2105/ajph.82.5.703 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69.Domínguez-Berjón F, Borrell C, Rodríguez-Sanz M, et al. The usefulness of area-based socioeconomic measures to monitor social inequalities in health in southern Europe. Eur J Public Health 2006;16:54–61. 10.1093/eurpub/cki069 [DOI] [PubMed] [Google Scholar]
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