It's the right moment to implement this policy in the UK, where every year fewer and fewer people smoke, thanks to previous public health action. Countries with higher smoking prevalence will need to drive it down before they can consider implementing this policy.
This huge public health win happened despite strong lobbying from the tobacco industry, that of course prioritises its financial interests over our health.
A landmark moment for #PublicHealth: people born after 2008 will be banned from buying tobacco in the UK – once they turn 18 and forever, even when they will be 30, 40, and older.
www.bbc.co.uk/news/article...
Data Organization in Spreadsheets Karl W. Broman & Kara H. Woo Pages 2-10 | Received 01 Jun 2017, Accepted author version posted online: 29 Sep 2017, Published online: 24 Apr 2018 1. Introduction 2. Be Consistent 3. Choose Good Names for Things 4. Write Dates as YYYY-MM-DD 5. No Empty Cells 6. Put Just One Thing in a Cell 7. Make it a Rectangle 8. Create a Data Dictionary 9. No Calculations in the Raw Data Files 10. Do Not Use Font Color or Highlighting as Data 11. Make Backups 12. Use Data Validation to Avoid Errors 13. Save the Data in Plain Text Files ABSTRACT Spreadsheets are widely used software tools for data entry, storage, analysis, and visualization. Focusing on the data entry and storage aspects, this article offers practical recommendations for organizing spreadsheet data to reduce errors and ease later analyses. The basic principles are: be consistent, write dates like YYYY-MM-DD, do not leave any cells empty, put just one thing in a cell, organize the data as a single rectangle (with subjects as rows and variables as columns, and with a single header row), create a data dictionary, do not include calculations in the raw data files, do not use font color or highlighting as data, choose good names for things, make backups, use data validation to avoid data entry errors, and save the data in plain text files.
Every day is a good day for sharing one of the most useful papers about research data ever written. PLEASE get your people to understand and follow this advice.
www.tandfonline.com/doi/full/10....
Trying to analyse seven semi‑structured interviews for my health needs assessment and honestly... why is this taking longer than an entire epi dataset? Never going to look down on qual research ever again!
The medium-term aim would be to inform studies that can better give causal answers (I'd love to learn what those are, when looking at these systemic factors) and ultimate aim is of course inform public health action and policy
Thanks Simon (hi!)
The short-term aim would be hypothesis generation. I feel that when we identify and quantify health inequalities by deprivation we often stop there, without even trying to determine which of the countless possible mechanisms are more relevant. Complexity paralyses us
My question is: would you find this method acceptable? Is there a better way of doing this?
6/6
I'm aware that I can't actually answer my causal question with what is essentially an ecological study. And that deprivation domains are closely linked, so chucking them all in a model is bound to infuriate the causal inference goddesses.
5/6
If some domains have very small p-values, I'd then consider them as having statistical evidence for an association with my outcome.
4/6
I could calculate counts and denominators at the LSOA level, and then fit a negative binomial regression model with the count as dependent variable and the decile of each deprivation domain as covariates (and obviously log population as offset).
3/6
The health outcome I'm analysing is strongly linked to IMD (to the surprise of no one).
However, I'd like to know which deprivation domains are more relevant in this health inequality.
So I thought of this possible approach:
2/6
A question for social epidemiologists. #episky #publichealth
As we know, the English Index of Multiple Deprivation is a composite metric, including domains such as education, income, environment, etc. And these are often closely linked. 1/6
If you push hard enough, anything can squeeze into a logistic regression model
The final line of the article made me chuckle
Annual epi update on bloodstream infections and C. difficile infections in England.
Continuing worrying trend of increasing rates of most of these infections, especially for community-onset cases
People are less likely to believe conspiracy theories when they get clear, simple, and early information from trusted sources. Using tools like “prebunking” and reaching people where they are (like on social media) can help build trust and reduce misinformation.
www.sciencedirect.com/science/arti...
Botox, lifestyle medicine, and future general practice. Some years ago I taught an exceptionally bright young GP on a course. She seemed to grasp the values of the specialty intuitively. I hadn't heard news of her for a while, but I discovered recently that she runs a private aesthetics clinic, offering botox, fillers, and so forth to people who want to look younger and are happy to pay for this. Forgive me, but my heart sank. It wasn't the kind of career I'd hoped she might pursue. At the same time, I recognised she may have made the choice for her own good. We hear a lot about doctors emigrating, but I'm hearing of far more who stay in the UK but leave the NHS. Some are already thinking about it during their specialty training. I come across others when I do their appraisals two or three years later: they're carrying out sessions in aesthetics, lifestyle medicine, wellbeing clinics, or various screening services. Some are doing this part time to supplement their income or between spells of locum work, but a significant number are moving into full time private work. My perception is that these doctors include some of the best of their generation. Their motives vary. These often include feeling overwhelmed by the punishing pace of NHS work. However, in some localities these doctors are finding the opposite: they can't make a living because different professions are taking over GP work, and practices are engaging far fewer sessional doctors. Many who do private work are parents who simply want to spend more time with their children.
An interesting piece by @johnlauner.bsky.social in the @bmj.com recently.
I know GP trainees who have done this too. Not all our younger doctors are leaving for Australia & NZ. Some are staying here but leaving the NHS.
Somehow, the system has gone horribly wrong that this is happening.
#MedSky
First day as Public Health Medicine Registrar (=resident) done ✅
Exciting to start!
Stunning!
This podcast episode has some interesting commentary of the "nanny state" critique against public health policies.
In its 10 Year Health Plan, the government recommitted to halving the gap in healthy life expectancy (HLE) between the poorest and richest regions. But how? Our new analysis with the ONS points to the underlying factors which any plan will need to take account of. 🧵
😂
"And when the number of years of experience in the workforce were taken into account, master’s holders in any field earned slightly more than those with PhDs."
www.nature.com/articles/d41...
Springer-Nature launched a series of "Discover" journals that closely mimic MDPI titles -- sharing *identical* journal names, and likely similar business model.
What is going on, and why researcher will - as always - fall for it?
A 🧵
the-strain-on-scientific-publishing.github.io/website/post...
Tricky!
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Thank you and your colleagues for sharing your findings. I'm completely unfamiliar with behavioural research but it seems essential (and fascinating!)
Thanks for sharing. Disappointing but of course good to know.
Are there any approaches to counteract/prevent misinfo with some evidence of effectiveness?