Estimating measurement equivalence of the 12-item General Health Questionnaire across ethnic groups in the UK.

BACKGROUND: This study investigates the extent to which the GHQ-12 exhibits configural, metric and scalar invariance across six ethnic groups in Britain and Northern Ireland, using the UK Household Longitudinal Study (N = 35 410). METHODS: A confirmatory factor analysis was carried out on a white British group in order to establish an adequate measurement model. Secondly, a multi-group confirmatory factor analysis was conducted in order to assess measurement invariance. A sensitivity analysis comparing summated and latent means across groups was carried out. Finally, revised estimates of scale reliability were derived using two different methods. RESULTS: A one-factor model including correlated error terms on the negatively phrased items showed superior fit in all ethnic groups. Tests for equal factor loadings and intercepts also showed adequate fit demonstrating metric and scalar invariance. Latent and summated scale estimates of mean group differences were similar for all groups. Scale reliability using McDonald's ω is lower than when using the more conventional Cronbach's α. Reliability across groups is reasonably consistent. CONCLUSIONS: We find that the GHQ-12 does not display obvious bias in regard to ethnic groups in the UK and that valid comparisons across these groups can be made for the purposes of population research. Caution is needed when using as a screening tool for individuals.

Nurse effects on measurement error in household biosocial surveys.

BACKGROUND: Biosocial survey data are in high demand, yet little is known about the measurement quality of health measures collected by nurses in respondents' homes. Our objective was to analyze the degree to which nurses influence measurement in anthropometric and physical performance indicators collected from respondents in two nationally-representative UK biosocial surveys. METHODS: The English Longitudinal Survey of Ageing and the UK Household Longitudinal Study - Understanding Society were used to analyze fourteen anthropometric and physical performance measures covering weight, height, pulse, grip strength, and lung capacity. Cross-classified multilevel models were used to estimate "nurse effects" on measurement error. RESULTS: Overall, there is a medium effect of nurses on measurement. Across all measures collected in both studies, nurses explain around 13% of all measurement variation. Variation in specific measures range between approximately 2 and 25%. Grip strength and lung capacity are more heavily influenced by nurses than are height, weight, and pulse. Lastly, nurse characteristics explain only a very small proportion of nurse measurement variation. CONCLUSION: Objective health measures collected by nurses in household biosocial surveys are susceptible to non-trivial amounts of measurement variation. Nurse ID numbers should be regularly included in biosocial data releases to allow researchers to account for this unnecessary source of variation. Further, researchers are advised to conduct sensitivity analyses using control variables that account for nurse variation to confirm whether their substantive findings are influenced by nurse measurement effects.

Interviewer Effects on the Measurement of Physical Performance in a Cross-National Biosocial Survey.

Biosocial surveys increasingly use interviewers to collect objective physical health measures (or "biomeasures") in respondents' homes. While interviewers play an important role, their high involvement can lead to unintended interviewer effects on the collected measurements. Such interviewer effects add uncertainty to population estimates and have the potential to lead to erroneous inferences. This study examines interviewer effects on the measurement of physical performance in a cross-national and longitudinal setting using data from the Survey of Health, Ageing and Retirement in Europe. The analyzed biomeasures exhibited moderate-to-large interviewer effects on the measurements, which varied across biomeasure types and across countries. Our findings demonstrate the necessity to better understand the origin of interviewer-related measurement errors in biomeasure collection and account for these errors in statistical analyses of biomeasure data.

Is social disadvantage a chronic stressor? Socioeconomic position and HPA axis activity among older adults living in England.

INTRODUCTION: Living in socioeconomic disadvantage has been conceptualised as a chronic stressor, although this contradicts evidence from studies using hair cortisol and cortisone as a measure of hypothalamus-pituitary-adrenal (HPA)1 axis activity. These studies used complete case analyses, ignoring the impact of missing data for inference, despite the high proportion of missing biomarker data. The methodological limitations of studies investigating the association between socioeconomic position (SEP)2 defined as education, wealth, and social class and hair cortisol and cortisone are considered in this study by comparing three common methods to deal with missing data: (1) Complete Case Analysis (CCA),3 (2) Inverse Probability Weighting (IPW) 4and (3) weighted Multiple Imputation (MI).5 This study examines if socioeconomic disadvantage is associated with higher levels of HPA axis activity as measured by hair cortisol and cortisone among older adults using three approaches for compensating for missing data. METHOD: Cortisol and cortisone levels in hair samples from 4573 participants in the 6th wave (2012-2013) of the English Longitudinal Study of Ageing (ELSA)6 were examined, in relation to education, wealth, and social class. We compared linear regression models with CCA, weighted and multiple imputed weighted linear regression models. RESULTS: Social groups with certain characteristics (i.e., ethnic minorities, in routine and manual occupations, physically inactive, with poorer health, and smokers) were less likely to have hair cortisol and hair cortisone data compared to the most advantaged groups. We found a consistent pattern of higher levels of hair cortisol and cortisone among the most socioeconomically disadvantaged groups compared to the most advantaged groups. Complete case approaches to missing data underestimated the levels of hair cortisol in education and social class and the levels of hair cortisone in education, wealth, and social class in the most disadvantaged groups. CONCLUSION: This study demonstrates that social disadvantage as measured by disadvantaged SEP is associated with increased HPA axis activity. The conceptualisation of social disadvantage as a chronic stressor may be valid and previous studies reporting no associations between SEP and hair cortisol may be biased due to their lack of consideration of missing data cases which showed the underrepresentation of disadvantaged social groups in the analyses. Future analyses using biosocial data may need to consider and adjust for missing data.

CNG impact on combustion quality of a diesel engine fueled in diesel-gas mode.

The main objective of the paper is to reveal a few aspects related to combustion quality of a diesel engine fueled in diesel-gas mode with diesel fuel and compressed natural gas. The total amount of heat released per cycle will be higher when the engine is fueled in dual-fuel mode due to higher LHV and because of the gaseous state of CNG. For low and medium loads the total quality of heat released per cycle will increase with 10 % and for higher loads it will reach levels with 25 % higher. The heat release rate of the preformed mixture will double its value for low and medium loads and will reach thresholds up to 3.5 times higher (interval -15; -5°CA); admitting CNG into cylinder will help the preformed mixture to reach stoichiometric values and thus improving the fast combustion phase. Fueling the engine in dual fuel mode with diesel fuel and CNG will have a negative effect on the maximum heat release rate; there will be a 10 % drop in maximum HRR for low loads when the energetic substitution coefficient reaches 36 % and 14 % at high loads when the xc is 26 %. The gaseous state and a higher LHV of CNG will have a good impact on indicated mean effective pressure for all studied regimes when the engine is fueled in DG mode: for low and medium loads 30 % and for high loads 20 % increase will be recorded. Gaseous state of CNG will lead to a higher percentage of preformed mixture and thus the fast combustion phase will extend for longer periods for all studied regimes when the engine is fueled in DG mode (20 % longer for low and medium loads and 30 % for high loads). The diffusive combustion phase will become shorter due to a lower quantity of the main dose when CNG is injected into the intake manifold (10-15 % shorter for low loads and 7 % at high loads).

Estimation of Mode Effects in the Health and Retirement Study Using Measurement Models.

Using multiple modes to collect data is becoming a standard practice in survey agencies. While this should lower costs and reduce non-response error it may have detrimental effects on measurement quality. This is of special concern in panel surveys where a key focus is on measuring change over time and where changing modes may have an effect on key measures. In this paper we use a quasi-experimental design from the Health and Retirement Study to compare the measurement quality of two scales between face-to-face, telephone and Web modes. Panel members were randomly assigned to receive a telephone survey or enhanced face-to-face survey in the 2010 core wave, while this was reversed in the 2012 core wave. In 2011, panelists with Internet access completed a Web survey containing selected questions from the core waves. We examine the responses from 3251 respondents who participated in all three waves, using latent models to identify measurement mode effects. The two scales, depression and physical activity, show systematic differences between interviewer administered modes (i.e., face-to-face and telephone) and the self-administered one (i.e., Web). Possible explanations are discussed.