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Background Previous studies have indicated increased risk of mental disorder symptoms, suicide and substance misuse in lesbian, gay and bisexual (LGB) adults, compared to heterosexual adults. Our aims were to determine an estimate of the association between sexual orientation identity and poor mental health and wellbeing among adults from 12 population surveys in the UK, and to consider whether effects differed for specific subgroups of the population. Methods Individual data were pooled from the British Cohort Study 2012, Health Survey for England 2011, 2012 and 2013, Scottish Health Survey 2008 to 2013, Longitudinal Study of Young People in England 2009/10 and Understanding Society 2011/12. Individual participant meta-analysis was used to pool estimates from each study, allowing for between-study variation. Results Of 94,818 participants, 1.1 % identified as lesbian/gay, 0.9 % as bisexual, 0.8 % as 'other' and 97.2 % as heterosexual. Adjusting for a range of covariates, adults who identified as lesbian/gay had higher prevalence of common mental disorder when compared to heterosexuals, but the association was different in different age groups: apparent for those under 35 (OR = 1.78, 95 % CI 1.40, 2.26), weaker at age 35–54.9 (OR = 1.42, 95 % CI 1.10, 1.84), but strongest at age 55+ (OR = 2.06, 95 % CI 1.29, 3.31). These effects were stronger for bisexual adults, similar for those identifying as 'other', and similar for 'low wellbeing'. Conclusions In the UK, LGB adults have higher prevalence of poor mental health and low wellbeing when compared to heterosexuals, particularly younger and older LGB adults. Sexual orientation identity should be measured routinely in all health studies and in administrative data in the UK in order to influence national and local policy development and service delivery. These results reiterate the need for local government, NHS providers and public health policy makers to consider how to address inequalities in mental health among these minority groups.

Abstract Background Previous studies have indicated increased risk of mental disorder symptoms, suicide and substance misuse in lesbian, gay and bisexual (LGB) adults, compared to heterosexual adults. Our aims were to determine an estimate of the association between sexual orientation identity and poor mental health and wellbeing among adults from 12 population surveys in the UK, and to consider whether effects differed for specific subgroups of the population. Methods Individual data were pooled from the British Cohort Study 2012, Health Survey for England 2011, 2012 and 2013, Scottish Health Survey 2008 to 2013, Longitudinal Study of Young People in England 2009/10 and Understanding Society 2011/12. Individual participant meta-analysis was used to pool estimates from each study, allowing for between-study variation. Results Of 94,818 participants, 1.1 % identified as lesbian/gay, 0.9 % as bisexual, 0.8 % as 'other' and 97.2 % as heterosexual. Adjusting for a range of covariates, adults who identified as lesbian/gay had higher prevalence of common mental disorder when compared to heterosexuals, but the association was different in different age groups: apparent for those under 35 (OR = 1.78, 95 % CI 1.40, 2.26), weaker at age 35–54.9 (OR = 1.42, 95 % CI 1.10, 1.84), but strongest at age 55+ (OR = 2.06, 95 % CI 1.29, 3.31). These effects were stronger for bisexual adults, similar for those identifying as 'other', and similar for 'low wellbeing'. Conclusions In the UK, LGB adults have higher prevalence of poor mental health and low wellbeing when compared to heterosexuals, particularly younger and older LGB adults. Sexual orientation identity should be measured routinely in all health studies and in administrative data in the UK in order to influence national and local policy development and service delivery. These results reiterate the need for local government, NHS providers and public health policy makers to consider how to address inequalities in mental health among these minority groups.

Increasing labour market participation among older workers is embedded in government policy in the United Kingdom and many other industrialised countries with rises in the state pension age in response to increasing life expectancy. Despite this, many workers stop working before state pension age with around a 20% reduction in the proportion of adults in work between ages 50 and 60 in 2011 in England and Wales. This paper considers the risk of remaining in work by region and gender between 2001 and 2011 for adults aged 40–49 in 2001. Men had significantly higher risk of extended working in the East Midlands (1.4×) East of England (1.5×), South East (1.6×), and South West (1.6×) compared with the North East. Women in all regions apart from London and Wales had significantly higher risk of extended working compared with the North East: ranging from 1.15 times in the North West and West Midlands to 1.6 times in the South West. Adjustment for nonemployment‐related socio‐economic status, housing tenure, qualifications, and car ownership, and employment status in 2001 attenuated all significant regional differences in extended working in men and in women in most regions. Workplace characteristics attenuated most of the remaining regional differences in women: women working in larger employers in 2001 or working at distances of 200 km or more, abroad or from home, had lower risk of remaining in work, whereas access to a car and higher working hours increased risk. Policies to increase qualifications and skills among older adults are recommended.

ABSTRACTObjectivesData linkage algorithms are used to link together multiple episodes of care belonging to the same patient. For example, the HESID algorithm is used to generate Hospital Episode Statistics (HES) in England. HESID is a deterministic algorithm, requiring identifiers to agree or disagree at each step. Data linkage errors occur when episodes belonging to two patients are incorrectly linked (a false match) or when episodes belonging to the same patient are not linked (a missed match). This typically occurs because patient identifiers (e.g. NHS number, postcode) contain errors or have missing data. We previously showed that HESID has a low false match rate (0.2%) but a high missed match rate (4.1%) when applied to paediatric intensive care data. This biased the true readmission rate, particularly for some patient groups including ethnic minorities. The aim of our study was to evaluate whether an additional step involving probabilistic matching would lower the missed match rate in HES without increasing the false matched rate.
ApproachWe simulated three datasets having the same characteristics as HES, for three age groups expected to have different levels of postcode stability (at age 0/1, 5/6 and 18/19). We compared the deterministic algorithm to a probabilistic algorithm, and then to a deterministic algorithm with an additional probabilistic step. In sensitivity analyses, we evaluated the algorithms under different data quality scenarios.
ResultsResults show that deterministic followed by probabilistic matching is the best solution for reducing missed matches, particularly in scenarios where errors in patient identifiers are more common.
ConclusionData linkage algorithms need to be evaluated against good quality reference standard data sets. For hospital data in England, the Personal Demographics Service (PDS) could be used to evaluate our approach, because it contains many of the same patient identifiers used in HES. Reducing data linkage error will improve monitoring of hospital activity in England.

Record linkage of administrative and survey data is increasingly used to generate evidence to inform policy and services. Although a powerful and efficient way of generating new information from existing data sets, errors related to data processing before, during and after linkage can bias results. However, researchers and users of linked data rarely have access to information that can be used to assess these biases or take them into account in analyses. As linked administrative data are increasingly used to provide evidence to guide policy and services, linkage error, which disproportionately affects disadvantaged groups, can undermine evidence for public health. We convened a group of researchers and experts from government data providers to develop guidance about the information that needs to be made available about the data linkage process, by data providers, data linkers, analysts and the researchers who write reports. The guidance goes beyond recommendations for information to be included in research reports. Our aim is to raise awareness of information that may be required at each step of the linkage pathway to improve the transparency, reproducibility, and accuracy of linkage processes, and the validity of analyses and interpretation of results.

Record linkage of administrative and survey data is increasingly used to generate evidence to inform policy and services. Although a powerful and efficient way of generating new information from existing data sets, errors related to data processing before, during and after linkage can bias results. However, researchers and users of linked data rarely have access to information that can be used to assess these biases or take them into account in analyses. As linked administrative data are increasingly used to provide evidence to guide policy and services, linkage error, which disproportionately affects disadvantaged groups, can undermine evidence for public health. We convened a group of researchers and experts from government data providers to develop guidance about the information that needs to be made available about the data linkage process, by data providers, data linkers, analysts and the researchers who write reports. The guidance goes beyond recommendations for information to be included in research reports. Our aim is to raise awareness of information that may be required at each step of the linkage pathway to improve the transparency, reproducibility, and accuracy of linkage processes, and the validity of analyses and interpretation of results.