Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: Research on health-related quality of life (HRQoL) trajectory patterns for people with disabilities (PwD) is scant. Understanding the HRQoL trajectory patterns for PwDs and investigating their relationship with disability types and socioeconomic factors can have important implications for Australia's welfare policy.
Methods: We analysed data from waves 11 to 21 of the Household, Income and Labour Dynamics in Australia (HILDA) survey of respondents aged 15 + years of the PwDs. The analytic sample consists of 3724 self-reported disabled individuals and 34,539 observations in total. The SF-6D utility score is our HRQoL measure. Group-based trajectory modelling was utilised to identify trajectory groups, and multinomial logistic regression was employed to determine the baseline factors associated with trajectory group membership.
Results: The study identified four distinct types of HRQoL trajectories (high, moderate improving, moderate deteriorating and low HRQoL trajectories). Psychosocial disability types followed by physical disability types had a high Relative Risk Ratio (RRR) in the low group compared with high trajectory group membership of PwDs (psychosocial: 6.090, physical: 3.524). Similar, results followed for the moderate improving group albeit with lower RRR (psychosocial: 2.868, Physical: 1.820). In the moderate deteriorating group, the disability types were not significant as this group has a similar profile to high group at the baseline. Compared with males, females had a higher RRR in low and moderate versus high improving HRQoL trajectories (low: 1.532, moderate improving: 1.237). Comparing the richest class to the poorest class, socioeconomic factors (income and education) predicted significantly lower exposure for the richer class to the low and medium HRQoL trajectories groups (RRR < 1).
Conclusion: Different forms of disability, demographic and socioeconomic factors have distinct effects on the HRQoL trajectories of disabled individuals. Healthcare and economic resource efficiency might be improved with targeted government policy interventions based on disability trajectories.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11286656 | PMC |
http://dx.doi.org/10.1007/s11136-024-03683-3 | DOI Listing |
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