Latent variable modelling of personality-health associations: measures, models and extensions

Functional health status, morbidity and mortality are determined partly by health behaviours (World Health Organization, 2002), which have determinants of their own. Personality traits, such as Conscientiousness, have a strong association with health behaviours (Bogg & Roberts, 2004). There is a less consistent and generally weaker association between traits and health outcomes (e.g. Neuroticism and mortality). The central problem in this thesis is how to measure, model, maximize, and extend trait-health associations. Conceptual issues associated with modelling traits and health are discussed in chapter one. The next three chapters concern such measurement issues about: personality traits (chapter two), health behaviours (chapter three) and health outcomes, with particular reference to functional health status (chapter four). These chapters are followed by a move to modelling (chapter five), with particular reference to the generalized latent variable modelling (LVM) framework (Muth´en & Muth´en, 1998–2007). The HAPPLE study is introduced (chapter six) which is used to model associations between Conscientiousness and health criteria within the LVMframework (chapter seven). Moving beyond self-reported outcomes, which are a mono-method approach, the role of multiple health behaviours in predicting cardiovascular mortality is considered (chapter eight). In a third section, cortisol is introduced, which is a biomarker of stress reactivity. The diurnal profile of cortisol output is described (chapter nine). Latent growth curve modelling is used to illustrate its association with Neuroticism, in a sample of student volunteers (chapter 10). Taken together, the results highlight the need for a general framework of modelling techniques, in personality-health research. I conclude that biopsychosocial models with excellent explanatory power, which are still parsimonious, can be achieved with LVM and its extensions. However, trait researchers will need to state more clearly the intended destinations of their work in order to attract contributions from, and share knowledge with, other disciplines

The impact of prescribed psychotropics on youth

Many psychotropics prescribed to children are unlicensed or off-label. This article uses the two most prescribed psychotropics (MPH and SSRIs) to illustrate various concerns about their impact on youth. Many mental illnesses begin in childhood or early adulthood, warranting a treatment of some kind. However, commentators have argued that prescribing is influenced by five myths: (1) children are little adults; (2) children have no reason to develop depression or anxiety; (3) psychiatric disorders are the same across adults and children; (3) children can be prescribed lower doses of the same drug; (5) drugs are preferable to alternative treatments and are more successful. Several lines of evidence suggest that these are incorrect assumptions. We update readers with recent research in relation to these myths, concluding that researchers should clarify child/adult differences for psychotropics, attend to the growth of "cosmetic" use of psychotropics in children and adolescents, and address concerns about the diagnostic validity of mental illness in the current DSM classification system

Utilising identifier error variation in linkage of large administrative data sources.

BACKGROUND: Linkage of administrative data sources often relies on probabilistic methods using a set of common identifiers (e.g. sex, date of birth, postcode). Variation in data quality on an individual or organisational level (e.g. by hospital) can result in clustering of identifier errors, violating the assumption of independence between identifiers required for traditional probabilistic match weight estimation. This potentially introduces selection bias to the resulting linked dataset. We aimed to measure variation in identifier error rates in a large English administrative data source (Hospital Episode Statistics; HES) and to incorporate this information into match weight calculation. METHODS: We used 30,000 randomly selected HES hospital admissions records of patients aged 0-1, 5-6 and 18-19 years, for 2011/2012, linked via NHS number with data from the Personal Demographic Service (PDS; our gold-standard). We calculated identifier error rates for sex, date of birth and postcode and used multi-level logistic regression to investigate associations with individual-level attributes (age, ethnicity, and gender) and organisational variation. We then derived: i) weights incorporating dependence between identifiers; ii) attribute-specific weights (varying by age, ethnicity and gender); and iii) organisation-specific weights (by hospital). Results were compared with traditional match weights using a simulation study. RESULTS: Identifier errors (where values disagreed in linked HES-PDS records) or missing values were found in 0.11% of records for sex and date of birth and in 53% of records for postcode. Identifier error rates differed significantly by age, ethnicity and sex (p < 0.0005). Errors were less frequent in males, in 5-6 year olds and 18-19 year olds compared with infants, and were lowest for the Asian ethic group. A simulation study demonstrated that substantial bias was introduced into estimated readmission rates in the presence of identifier errors. Attribute- and organisational-specific weights reduced this bias compared with weights estimated using traditional probabilistic matching algorithms. CONCLUSIONS: We provide empirical evidence on variation in rates of identifier error in a widely-used administrative data source and propose a new method for deriving match weights that incorporates additional data attributes. Our results demonstrate that incorporating information on variation by individual-level characteristics can help to reduce bias due to linkage error

Probabilistic linkage to enhance deterministic algorithms and reduce data linkage errors in hospital administrative data.

BACKGROUND: The pseudonymisation algorithm used to link together episodes of care belonging to the same patients in England (HESID) has never undergone any formal evaluation, to determine the extent of data linkage error. OBJECTIVE: To quantify improvements in linkage accuracy from adding probabilistic linkage to existing deterministic HESID algorithms. METHODS: Inpatient admissions to NHS hospitals in England (Hospital Episode Statistics, HES) over 17 years (1998 to 2015) for a sample of patients (born 13/28th of months in 1992/1998/2005/2012). We compared the existing deterministic algorithm with one that included an additional probabilistic step, in relation to a reference standard created using enhanced probabilistic matching with additional clinical and demographic information. Missed and false matches were quantified and the impact on estimates of hospital readmission within one year were determined. RESULTS: HESID produced a high missed match rate, improving over time (8.6% in 1998 to 0.4% in 2015). Missed matches were more common for ethnic minorities, those living in areas of high socio-economic deprivation, foreign patients and those with 'no fixed abode'. Estimates of the readmission rate were biased for several patient groups owing to missed matches, which was reduced for nearly all groups. CONCLUSION: Probabilistic linkage of HES reduced missed matches and bias in estimated readmission rates, with clear implications for commissioning, service evaluation and performance monitoring of hospitals. The existing algorithm should be modified to address data linkage error, and a retrospective update of the existing data would address existing linkage errors and their implications

Life-course pathways to psychological distress: a cohort study

Objectives Early life factors, like intelligence and socioeconomic status (SES), are associated with health outcomes in adulthood. Fitting comprehensive life-course models, we tested (1) the effect of childhood intelligence and SES, education and adulthood SES on psychological distress at midlife, and (2) compared alternative measurement specifications (reflective and formative) of SES. Design Prospective cohort study (the Aberdeen Children of the 1950s). Setting Aberdeen, Scotland. Participants 12 500 live-births (6282 boys) between 1950 and 1956, who were followed up in the years 2001–2003 at age 46–51 with a postal questionnaire achieving a response rate of 64% (7183). Outcome measures Psychological distress at age 46–51 (questionnaire). Results Childhood intelligence and SES and education had indirect effects on psychological distress at midlife, mediated by adult SES. Adult SES was the only variable to have a significant direct effect on psychological distress at midlife; the effect was stronger in men than in women. Alternative measurement specifications of SES (reflective and formative) resulted in greatly different model parameters and fits. Conclusions Even though formative operationalisations of SES are theoretically appropriate, SES is better specified as reflective than as a formative latent variable in the context of life-course modelling

Sexual orientation identity and tobacco and hazardous alcohol use: findings from a cross-sectional English population survey

Objectives: To assess the association between tobacco and hazardous alcohol use and sexual orientation and whether such an association could be explained by other sociodemographic characteristics. Design: Cross-sectional household survey conducted in 2014–2016. Setting: England, UK. Participants: Representative English population sample (pooled n=43 866). Main outcomes: Sexual orientation identity (lesbian/gay, bisexual, heterosexual, prefer-not-to-say); current tobacco and hazardous alcohol use (defined as Alcohol Use Disorders Identification Test Score ≥8). All outcomes were self-reported. Results: Due to interactions between sexual orientation and gender for substance use, analyses were stratified by gender. Tobacco use prevalence was significantly higher among lesbian/gay (women: 24.9%, 95% CI 19.2% to 32.6%; men: 25.9%, 95% CI 21.3% to 31.0%) and bisexual participants (women: 32.4%, 95% CI 25.9% to 39.6%; men: 30.7%, 95% CI 23.7% to 30.7%) and significantly lower for prefer-not-to-say participants in women (15.5%, 95% CI 13.5% to 17.8%) but not men (22.7%, 95% CI 20.3% to 25.3%) compared with heterosexual participants (women: 17.5%, 95% CI 17.0% to 18.0%; men: 20.4%, 95% CI 19.9% to 21.0%; p<0.001 for omnibus test). Similarly, hazardous alcohol use was significantly more prevalent for lesbian/gay (women: 19.0%, 95% CI 14.0% to 25.3%; men: 30.0%, 25.2%–35.3%) and bisexual participants (women: 24.4%, 95% CI 18.7% to 31.3%; men: 24.3%, 95% CI 17.9% to 32.1%) and lower for prefer-not-to-say participants (women: 4.1%, 95% CI 3.0% to 5.4%; men: 13.7%; 95% CI 11.8% to 16.0%) compared with heterosexuals (women: 8.3%, 95% CI 7.9% to 8.7%; men: 18.4%, 95% CI 17.9% to 18.9%; p<0.001 for omnibus test). However, after adjusting for sociodemographic confounders, tobacco use was similar across all sexual orientation groups among both women and men. By contrast, sexual orientation differences in hazardous alcohol use remained even after adjustment among women but not for bisexual and gay men. Conclusions: In England, higher rates of tobacco use among sexual minority men and women appear to be attributable to other sociodemographic factors. Higher rates of hazardous alcohol use among sexual minority men may also be attributable to these factors, whereas this is not the case for sexual minority women

Local area unemployment, individual health and workforce exit: ONS Longitudinal Study

This work was jointly funded by the Economic and Social Research Center (ESRC) and the United Kingdom’s Medical Research Council, under the Lifelong Health and Wellbeing Cross-Council Programme initiative [ES/L002892/1]. CeLSIUS is supported by the ESRC Census of Population Programme (Award Ref: ES/ K000365/1)

Sitting time, fidgeting and all-cause mortality in the UK Women's Cohort Study

Introduction: Sedentary behaviours (including sitting) may increase risk of mortality independently of physical activity level. Little is known about how fidgeting behaviours might modify the association. Methods: Data were drawn from the UK Women’s Cohort Study. In 1999/2002, 12,778 women (age 37 to 78) provided data on average daily sitting time, overall fidgeting (irrespective of posture), and a range of relevant covariates including physical activity, diet, smoking status and alcohol consumption. Participants were followed for mortality over a mean of 12 years. Proportional hazards Cox regression models were used to estimate the relative risk of mortality in the high (vs. low) and medium (vs. low) sitting time groups. Results: Fidgeting modified the risk associated with sitting time (p value for interaction = 0.04), leading us to separate groups for analysis. Adjusting for a range of covariates, sitting for 7+ hours/day (vs. <5 hours/day) was associated with 30% increased risk of all-cause mortality (HR = 1.30, 95% CI 1.02, 1.66) only among women in the low fidgeting group. Among women in the high fidgeting group, sitting for 5/6 (vs. <5 hrs/day) was associated with decreased risk of mortality (HR = 0.63, 95% CI 0.43, 0.91), adjusting for a range of covariates. There was no increased risk of mortality from longer sitting time in the middle and high fidgeting groups. Conclusions: Fidgeting may reduce the risk of all-cause mortality associated with excessive sitting time. More detailed and better validated measures of fidgeting should be identified in other studies in order to replicate these findings and identity mechanisms, particularly measures that distinguish fidgeting in a seated from standing posture

GUILD: Guidance for Information about Linking Data sets

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