Dr Aaron Reeves

© 2017, The Author(s). In recent years, health behaviour interventions have received a great deal of attention in both research and policy as a means of encouraging people to lead healthier lives. The emphasis of such interventions has varied over time, in terms of level of intervention (e.g. individual vs community) and drawing on different disciplinary perspectives. Recently, a number of critiques have focused on how health behaviour interventions sometimes sideline issues of social context, framing health as a matter of individual choice and, by implication, a personal responsibility. Part of this criticism is that health behaviour interventions often do not draw on alternative social science understandings of the structured and contextual aspects of behaviour and health. Yet to our knowledge, no study has attempted to empirically assess the extent to which, and in what ways, the health behaviour intervention field has paid attention to social context. In this article, we undertake this task using bibliometric techniques in order to map out the health behaviour intervention field. We find that the number of health behaviour interventions has grown rapidly in recent years, especially since around 2006, and that references to social science disciplines and concepts that foreground issues of social context are rare and, relatively speaking, constitute less of the field post 2006. More quantifiable concepts are used most, and those more close to the complexities of social context are mentioned least. The document co-citation analysis suggests that pre 2006, documents referring to social context were relatively diffuse in the network of key citations, but post 2006 this influence had largely diminished. The journal co-citation analysis shows less disciplinary overlap post 2006. At present, health behaviour interventions are continuing to focus on individualised approaches drawn from behavioural psychology and behavioural economics. Our findings lend empirical support to a number of recent papers that suggest more interdisciplinary collaboration is needed to advance the field.

Inequalities in infant mortality rates (IMRs) are rising in some low- and middle-income countries (LMICs) and decreasing in others, but the explanation for these divergent trends is unclear. We investigate whether government expenditures and redistribution are associated with reductions in inequalities in IMRs. We estimated country-level fixed-effects panel regressions for 48 LMICs (142 country observations). Slope and Relative Indices of Inequality in IMRs (SII and RII) were calculated from Demographic and Health Surveys between 1993 and 2013. RII and SII were regressed on government expenditure (total, health and non-health) and redistribution, controlling for gross domestic product (GDP), private health expenditures, a democracy indicator, country fixed effects and time. Mean SII and RII was 39.12 and 0.69, respectively. In multivariate models, a 1 percentage point increase in total government expenditure (% of GDP) was associated with a decrease in SII of -2.468 [95% confidence intervals (CIs): -4.190, -0.746] and RII of -0.026 (95% CIs: -0.048, -0.004). Lower inequalities were associated with higher non-health government expenditure, but not higher government health expenditure. Associations with inequalities were non-significant for GDP, government redistribution, and private health expenditure. Understanding how non-health government expenditure reduces inequalities in IMR, and why health expenditures may not, will accelerate progress towards the Sustainable Development Goals.

© 2018, The Author(s) 2018. There are concerns that the recovery from the Great Recession in Europe has left growing numbers of people facing precarious housing situations. Yet, to our knowledge, there is no comparative measure of housing precariousness in contrast to an extensive body of work on labour market precariousness. Here, we draw on a comparative survey of 31 European countries from the 2012 wave of European Union Survey of Income and Living Conditions to develop a novel housing precariousness measure. We integrate four dimensions of housing precariousness: security, affordability, quality and access to services, into a scale ranging from 0 (not at all precarious) to 4 (most precarious). Over half of the European population report at least one element of housing precariousness; 14.7 percent report two dimensions and 2.8 percent three or more (equivalent to ~15 million people). Eastern European and small island nations have relatively greater precariousness scores. Worse precariousness tends to be more severe among the young, unemployed, single and those with low educational attainment or who live in rented homes and is associated with poor self-reported health. Future research is needed to strengthen surveillance of housing precariousness as well as to understand what policies and programmes can help alleviate it.

Persons engaged in the sex industry are at greater risk of HIV and other sexually transmitted infections than the general population. One major factor is exposure to higher levels of risky sexual activity. Expanding condom use is a critical prevention strategy, but this requires negotiation with those buying sex, which takes place in the context of cultural and economic constraints. Impoverished individuals who fear violence are more likely to forego condoms.Here we tested the hypotheses that poverty and fear of violence are two structural drivers of HIV infection risk in the sex industry. Using data from the European Centre for Disease Prevention and Control and the World Bank for 30 countries, we evaluated poverty, measured using the average income per day per person in the bottom 40% of the income distribution, and gender violence, measured using homicide rates in women and the proportion of women exposed to violence in the last 12 months and/or since age 16 years.We found that HIV prevalence among those in the sex industry was higher in countries where there were greater female homicide rates (β = 0.86; P = 0.018) and there was some evidence that self-reported exposure to violence was also associated with higher HIV prevalence (β = 1.37; P = 0.043). Conversely, HIV prevalence was lower in countries where average incomes among the poorest were greater (β = -1.05; P = 0.046).Our results are consistent with the theory that reducing poverty and exposure to violence may help reduce HIV infection risk among persons engaged in the sex industry.

Economic insecurity correlates with adverse health outcomes, but the biological pathways involved are not well understood. We examine how changes in economic insecurity relate to metabolic, inflammatory and liver function biomarkers.Blood analyte data were taken from 6520 individuals (aged 25-59 years) participating in Understanding Society. Economic insecurity was measured using an indicator of subjective financial strain and by asking participants whether they had missed any bill, council tax, rent or mortgage payments in the past year. We investigated longitudinal changes in economic insecurity (remained secure, increase in economic insecurity, decrease in economic insecurity, remained insecure) and the accumulation of economic insecurity. Linear regression models were calculated for nine (logged) biomarker outcomes related to metabolic, inflammatory, liver and kidney function (as falsification tests), adjusting for potential confounders.Compared with those who remained economically stable, people who experienced consistent economic insecurity (using both measures) had worsened levels of high-density lipoprotein (HDL)-cholesterol, triglycerides, C reactive protein (CRP), fibrinogen and glycated haemoglobin. Increased economic insecurity was associated with adverse levels of HDL-cholesterol (0.955, 95% CI 0.929 to 0.982), triglycerides (1.077, 95% CI 1.018 to 1.139) and CRP (1.114, 95% CI 1.012 to 1.227), using the measure of financial strain. Results for the other measure were generally consistent, apart from the higher levels of gamma-glutamyl transferase observed among those experiencing persistent insecurity (1.200, 95% CI 1.110 to 1.297).Economic insecurity is associated with adverse metabolic and inflammatory biomarkers (particularly HDL-cholesterol, triglycerides and CRP), heightening risk for a range of health conditions.