📢 Check out these two new publications involving PSG members Maria Gargiulo (@thegargiulian.bsky.social) and José Manuel Aburto!

Check out this great thread summarizing our recent paper "Temporary Shock or Lasting Scar?" 👇

New LCDS Preprint Asks: Has COVID-19 Left a Lasting Scar on Life Expectancy? Five years after the onset of the COVID-19 pandemic, an important question remains: was COVID-19 a short-lived mortality shock, or has it more permanently altered life expectancy trajectories? A new p...

Five years after the pandemic began, have countries returned to their pre-COVID life expectancy trajectories?

New research shows 31 of 34 high-income countries still have life expectancy deficits in 2024, suggesting lasting effects on population health.

www.demography.ox.ac.uk/news/new-lcd...

📈 New preprint on life expectancy trajectories in high-income countries since 2020. 📉

Joint work with a great team from
@mpidr.bsky.social @oxforddemsci.bsky.social @psglshtm.bsky.social @camunicampop.bsky.social

Link below. 👇

I am grateful for this recognition of my work. Congratulations to everyone whose work has been honored in memory of our late fellow student Julia Mead Knox.

Happy birth, TPN! Really great line-up. 👏

Collage of journal covers: "What matters more to politicians: the quantity or quality of public opinion signals?", "Fertility, birth, reproduction: Connecting formal demographic frameworks", and "Sexual Inactivity in Japan: a Scoping Review."

Is it really #OpenAccessWeek if you haven't read some of our newly published #OpenAccess articles?

🎤 What matters to politicians: spr.ly/6000AsV7a

🍼 Fertility, birth, reproduction: spr.ly/6000AsnDY

🗾 Sexual inactivity in Japan: spr.ly/6008AsnHQ

Happy reading & researching!

Many thanks to everyone who contributed to the session for their valuable insights and engaging discussions!💡

Thank you, Vanessa! 🙌

Very kind reading recommendation from @amandajean.bsky.social: My new paper "Fertility, birth, reproduction: Connecting formal demographic frameworks" with Annette Baudisch. 🤓 Just out in Population Studies. doi.org/10.1080/0032...

Fertility, birth, reproduction: Connecting formal demographic frameworks The conventional framework of fertility research conceptualizes childbirth from the mother’s perspective. From her perspective, birth is an uncertain and potentially recurring event. In contrast, t...

Maybe these functions are useful for forecasting fertility? Or for jointly modeling fertility and mortality? We do not fully know yet—but there’s plenty of exciting applied work ahead. Give our paper a read, try out the functions, and let us know what you think! 👇 6/n
doi.org/10.1080/0032...

What are the density, survival, and hazard functions good for? They capture fertility age patterns without individual birth histories, complex models, or parity-specific data. All you need are age-specific fertility rates, e.g. from the Human Fertility Database or UN World Population Prospects. 5/n

Density, survival, and hazard functions calculated from birth counts (B1D1) and fertility rates (Conventional), by maternal cohort (1880–1960), Sweden. The lowest panels show the ratios of the functions.

What’s the difference between density, survival, and hazard functions based on birth counts vs fertility rates? We show that birth counts carry information on mortality in the maternal cohort; the fertility rates do not. That means if mortality is high, the two sets of functions will differ. 4/n

The 'Born once, die once' framework described above uses birth counts. Most demographers, however, work with fertility rates. Can we apply the 'life table logic' directly to these rates to get density, survival, and hazard functions of fertility? Yes! And we show exactly how in the paper. 3/n

Every person dies only once—and is also born only once. We apply life table logic to all births in a cohort of women, treating birth (not death) as the event, and using maternal age as the time axis. The result: density, survival, and hazard functions that capture the timing of reproduction. 2/n

Fertility, birth, reproduction: Connecting formal demographic frameworks The conventional framework of fertility research conceptualizes childbirth from the mother’s perspective. From her perspective, birth is an uncertain and potentially recurring event. In contrast, t...

✍️ Just out: Annette Baudisch & I delve into the formal demography of fertility, birth, & reproduction timing. 👶 We use methods from mortality research to summarize when in the parental life course children are born. 📆 1/n
doi.org/10.1080/0032...
@sdu.dk @oxforddemsci.bsky.social @mpidr.bsky.social

Feeling bittersweet as I read this wonderful thread and reflect on my time at @oxforddemsci.bsky.social, @nuffieldcollege.bsky.social, + @sociologyoxford.bsky.social coming to a close. Immensely grateful to my supervisors, assessors, colleagues, + friends for making this journey so meaningful. 👨‍🎓📜

Thanks so much, @drjenndowd.bsky.social! Fortunately, one thing I learned during my time at @oxforddemsci.bsky.social is that you never really leave. Here's to a long collaboration! 🤓

👋👋👋WelcomeWeeks @mpidr.bsky.social!

We are happy to welcome @polizzan.bsky.social! He is a new member in the Laboratory of Population Health at the Department of Social Demography. Welcome Antonino!
www.demogr.mpg.de/en/news_even...

Top 25 Social Science & Human Behavior Articles of 2024 Browse the 25 most downloaded Nature Communications articles in social science and human behavior published in 2024

👏 Kudos to @andreatilstra.bsky.social @polizzan.bsky.social @sanderwagner.bsky.social and Eva Akimova whose @naturecomms.bsky.social paper is among the top 25 most downloaded in social science and human behaviour for 2024 buff.ly/NmynGFV

Graph showing how changes in COVID-19 and non-COVID-19 mortality affected life expectancy in 24 countries in the periods 2015-19, 2019-20, 2020-21, 2021-22.

New @pnasnexus.org: How did non-COVID causes of death affect life expectancy (LE) in 2015-2022? 📑

tl;dr: By 2022, many of the 24 countries examined had NOT recovered to pre-pandemic levels. Rising cardiovascular and substance/external mortality prevented larger LE gains. 📉

doi.org/10.1093/pnas...

Thanks so much for this, @evangelinewarren.com! Could you please add me to the list? Thank you. ☺️

New @socarxiv.bsky.social preprint! 🚨 In "An integrated formal demographic fertility framework", A. Baudisch & I present new functions to describe population-level fertility age patterns—useful for modeling & forecasting? 🌟

📖 doi.org/10.31235/osf...
@oxforddemsci.bsky.social @imprs-phds.bsky.social

You can also read Abrams et al.’s response here: https://doi.org/10.1073/pnas.2320028121
Let's keep the conversation going! 🗨️ #mortality #demography #lifeexpectancy

Different counterfactuals provide different perspectives, neither is ‘right’ or ‘wrong’. What do you think is the best way to analyze US life expectancy stagnation? Read our letter: https://doi.org/10.1073/pnas.2318276121
@leverhulme.bsky.social @popassocamerica.bsky.social @eapsphd.bsky.social (6)

BOTTOM LINE: Working-age mortality is still an important driver of US life expectancy stagnation globally, but as Abrams et al. rightfully point out, we need to explore older-age slowdowns too. 📉 (5)

Figure 2 from Polizzi/Dowd (2024), showing counterfactual US life expectancy values for females and males in 2010-2019. USA panel replicates Figure 1 from Abrams et al. (2023).

We calculate an alternative counterfactual: What would US life expectancy be if 2010-19 age-specific mortality improved like in other high-income countries? 🌍 We find the opposite pattern: 25-64 mortality is more important than 65+ for explaining counterfactual differences. (4)

Figure 1 from Polizzi/Dowd (2024), showing rates of mortality improvement in 2000-2009 and 2010-2019 for females and males in five high-income countries.

We question whether this within-US counterfactual tells the whole story for 2 reasons:
- 25-64 US mortality was already stagnating in 2000-09, so less room to get worse.
- 2010-19 slowdowns in 65+ mortality improvements were common globally, but rising 25-64 mortality wasn’t. (3)

Figure 1 from Abrams et al. (2023), showing counterfactual US life expectancy values for women and men in 2010-2019.

Abrams et al. calculated counterfactual US life expectancy in 2010-19 if annual age-specific mortality changes followed 2000-09 trends. Surprise finding: Slowdowns in 65+ mortality improvements explain more post-2010 stagnation than 25-64 mortality. https://doi.org/10.1073/pnas.2308360120 (2)

Figure 1 from Polizzi/Dowd (2024), showing rates of mortality improvement in 2000-2009 and 2010-2019 for females and males in five high-income countries.

What’s the best way to analyze #lifeexpectancy stagnation in the US? 🤔 In PNAS, @drjenndowd.bsky.social & I share our thoughts on a recent paper by Abrams, Myrskylä & Mehta. https://doi.org/10.1073/pnas.2318276121
@oxforddemsci.bsky.social @nuffieldlibrary.bsky.social @mpidr.bsky.social (1)