Combining education and income into a socioeconomic position score for use in studies of health inequalities.

BACKGROUND: In studies of social inequalities in health, there is no consensus on the best measure of socioeconomic position (SEP). Moreover, subjective indicators are increasingly used to measure SEP. The aim of this paper was to develop a composite score for SEP based on weighted combinations of education and income in estimating subjective SEP, and examine how this score performs in predicting inequalities in health-related quality of life (HRQoL). METHODS: We used data from a comprehensive health survey from Northern Norway, conducted in 2015/16 (N = 21,083). A composite SEP score was developed using adjacent-category logistic regression of subjective SEP as a function of four education and four household income levels. Weights were derived based on these indicators' coefficients in explaining variations in respondents' subjective SEP. The composite SEP score was further applied to predict inequalities in HRQoL, measured by the EQ-5D and a visual analogue scale. RESULTS: Education seemed to influence SEP the most, while income added weight primarily for the highest income category. The weights demonstrated clear non-linearities, with large jumps from the middle to the higher SEP score levels. Analyses of the composite SEP score indicated a clear social gradient in both HRQoL measures. CONCLUSIONS: We provide new insights into the relative contribution of education and income as sources of SEP, both separately and in combination. Combining education and income into a composite SEP score produces more comprehensive estimates of the social gradient in health. A similar approach can be applied in any cohort study that includes education and income data.

Explaining subjective social status in two countries: The relative importance of education, occupation, income and childhood circumstances.

In the literature on social inequalities in health, subjective socioeconomic position (SEP) is increasingly applied as a determinant of health, motivated by the hypothesis that having a high subjective SEP is health-enhancing. However, the relative importance of determinants of subjective SEP is not well understood. Objective SEP indicators, such as education, occupation and income, are assumed to determine individuals' position in the status hierarchy. Furthermore, an extensive literature has shown that past childhood SEP affects adult health. Does it also affect subjective SEP? In this paper, we estimate the relative importance of i) the common objective SEP indicators (education, occupation and income) in explaining subjective SEP, and ii) childhood SEP (childhood financial circumstances and parents' education) in determining subjective SEP, after controlling for objective SEP. Given that the relative importance of these factors is expected to differ across institutional settings, we compare data from two countries: Australia and Norway. We use data from an online survey based on adult samples, with N ≈ 1400 from each country. Ordinary least squares regression is conducted to assess how objective and childhood SEP indicators predict subjective SEP. We use Shapley value decomposition to estimate the relative importance of these factors in explaining subjective SEP. Income was the strongest predictor of subjective SEP in Australia; in Norway, it was occupation. Of the childhood SEP variables, childhood financial circumstances were significantly associated with subjective SEP, even after controlling for objective SEP. This association was the strongest in the Norwegian sample. Only the mother's education had a significant impact on subjective SEP. Our findings highlight the need to understand the specific mechanisms between objective and subjective SEP as determinants of inequalities in health, and to assess the role of institutional factors in influencing these complex relationships.

Health and wellbeing in Norway: Population norms and the social gradient.

Measures of health-related quality of life are important in health technology assessments, and useful when analysing health inequalities across population sub-groups. This paper provides population norms on health and wellbeing in Norway based on two waves of a comprehensive health survey: Wave 6 of The Tromsø Study conducted in 2007/08 (N = 12,981) and Wave 7 conducted in 2015/16 (N = 21,083). By use of these data, the paper aims to provide new insight on how different measures of health and wellbeing, and different indicators for socio-economic position, will affect the magnitude of a reported social gradient in health. We apply validated multi-item instruments for measuring health and subjective well-being; the health state utility instrument EQ-5D, and the satisfaction with life scale, as well as a direct valuation of health on a visual analogue scale. We apply three indicators for socio-economic position; education, occupation and household income, each measured along four levels. After descriptive statistics, regression analyses are performed separately for men and women, adjusted for age, to explain the magnitude of the social gradient along each socio-economic indicator. The social gradient in health showed a consistent positive trend, along all three socio-economic indicators; it was strongest with income, and weakest with education. When health had been valued directly on a visual analogue scale, the gradient was steeper than when valued indirectly via the EQ-5D descriptive system. The social gradient in subjective well-being also showed consistent positive trends, except with education as the socio-economic indicator. We have shown that the magnitude of the social gradient critically depends on which socio-economic indicator is used, and whether health is being measured indirectly via the EQ-5D descriptive system or directly on a visual analogue scale. The strongest gradient in subjective well-being was observed with income as the socio-economic indicator.

eRegTime, Efficiency of Health Information Management Using an Electronic Registry for Maternal and Child Health: Protocol for a Time-Motion Study in a Cluster Randomized Trial.

BACKGROUND: Paper-based routine health information systems often require repetitive data entry. In the West Bank, the primary health care system for maternal and child health was entirely paper-based, with care providers spending considerable amounts of time maintaining multiple files and client registers. As part of the phased national implementation of an electronic health information system, some of the primary health care clinics are now using an electronic registry (eRegistry) for maternal and child health. The eRegistry consists of client-level data entered by care providers at the point-of-care and supports several digital health interventions that are triggered by the documented clinical data, including guideline-based clinical decision support and automated public health reports. OBJECTIVE: The aim of the eRegTime study is to investigate whether the use of the eRegistry leads to changes in time-efficiency in health information management by the care providers, compared with the paper-based systems. METHODS: This is a substudy in a cluster randomized controlled trial (the eRegQual study) and uses the time-motion observational study design. The primary outcome is the time spent on health information management for antenatal care, informed and defined by workflow mapping in the clinics. We performed sample size estimations to enable the detection of a 25% change in time-efficiency with a 90% power using an intracluster correlation coefficient of 0.1 and an alpha of .05. We observed care providers for full workdays in 24 randomly selected primary health care clinics-12 using the eRegistry and 12 still using paper. Linear mixed effects models will be used to compare the time spent on health information management per client per care provider. RESULTS: Although the objective of the eRegQual study is to assess the effectiveness of the eRegistry in improving quality of antenatal care, the results of the eRegTime study will contribute to process evaluation, supplementing the findings of the larger trial. CONCLUSIONS: Electronic health tools are expected to reduce workload for the care providers and thus improve efficiency of clinical work. To achieve these benefits, the implementation of such systems requires both integration with existing workflows and the creation of new workflows. Studies assessing the time-efficiency of electronic health information systems can inform policy decisions for implementations in resource-limited low- and middle-income settings. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/13653.