This caught my eye because it brings together things I’ve seen in two very different spheres of research – stress in social determinants research and HIV in Cape Town (I also know some of the authors – it’s always social networks in the end…).
No in-depth analysis from me here, but it’s really interesting how widely teleomere research is going and how it is being used to quantify the impact of a wide range of exposures on the broadest of health outcome measures (i.e. ‘biological aging’). I don’t know enough details about teleomeres to know how we meaningfully convert length to life expectancy (or quality of life), but it both bothers me a little that we may be focusing on something because it is measurable, and intrigues me that we may be able show previously only-hypothesised stress effects of HIV, and in particular antiretroviral treatment, on the body.
Maybe the most interesting line for me, showing my personal interests I guess, was:
Socio-economic factors were not associated with biological aging in HIV-infected participants
My prior would have been that this is in contrast to the general population, however a recent review suggests the evidence for a link between SES and teleomere length is mixed. And in this study, SES was unrelated for both those with and without HIV.
Still lots of interesting work out there to do on this…
I had expected this week to be quiet, what with the upcoming festive season and all, but I was pleasantly surprised to find a few titbits to look over and decide ‘yes, I should definitely read this some time soon’. Therefore, without further ado, I present:
1. A simple, yet elegant, study of the interplay of individual and national income in determining who volunteers to be tested for HIV (this paper has been around for a year or so it seems). It looks like the positive income gradient seen within countries (more income = more testing) is less pronounced in richer countries. The analysis uses individual income in within-country quintiles, which makes interpretation difficult. As the authors suggest, one way to look at things is to see this as evidence for the need to focus on poorer people in poor countries. Another angle would be to see this as evidence that there may be a positive but decreasing slope to the overall relationship internationally – i.e. there is a positive relationship up to some income threshold internationally, and then the relationship levels out. Which would suggest that focus needs to be on poor people everywhere. Either way, food for thought.
2. A recent paper on drinking and STI acquisition in the US has me thinking about the causal relationships around sex and drugs (and rock and roll) again. The paper finds various alcohol-related activities in adolescence linked to various risky behaviours (non-condom use) and self-reported STIs in early adulthood. The temporality of this relationship is clear, but the almost syndemic nature of the package of behaviours that goes with alcohol and sex – can I call it a lifestyle without implying too much or too little agency? – makes me loath to attribute any direct causal effect from the alcohol to the sex/STI. Not that the authors of this piece are claiming this, but I remain very unclear on how we might make an impact on STIs through interventions on adolescent behavioural patterns. Of course, this may just be me banging my ‘social epi’ drum, so you may wish to let me bang it in peace.
3. Here’s something from another field that interests me greatly, but I have never had the time to get into deeply enough. This is a nice conceptual effort to link human and pathogen behaviour together in an Ordinary Differential Equations setup to consider the mitigating/conflagratory effects of the former on the later in studies of dynamic disease spread. It doesn’t look too technical for the non-mathematicians amongst us, so might be worth a skim for thought-provocation, if nothing else.
This week I have three possibilities to tantalize you with, one of which I am immediately set against, but feel I should read.
1. This piece in AIDS Care worries me for two surface reasons. First, the abstract suggests that it is a quantitative analysis of DHS data being published in AIDS Care, a journal I usually turn to for depth and richness, not number crunching. But I would never write something off based only on this. Of more concern is the line “Contrary to the public health literature, women of high SES were also vulnerable to HIV risk”. I am pretty there is a large literature highlighting this relationship already, which leads me to question the level of background research conducted.
2. A reminder that prevention interventions are acutely context-dependent.
3. I find it strange/disturbing how infrequently we consider the disease context of a community in measuring risk factors for HIV across large areas. This paper from Zimbabwe, via UNC Chapel Hill, is a nice reminder of the importance of cross-level interactions.
Disclaimer. These posts are based on my reading of titles and abstracts, and all papers may be of much greater/lesser interest/quality than I have concluded based on reading 200 words or fewer.