Hampton Gaddy

@hggaddy.bsky.social

Demographer | PhD student @lseechist.bsky.social‬ | Incoming postdoc @magdalenoxford.bsky.social | Usually working on the 1918 flu | he/him | https://hggaddy.github.io/

New research from a team I was part of w Lauren Steele, @andreatilstra.bsky.social, & other virologists & demographers: Research on flu pandemics has been heavily shaped by 1) the 1918 flu & 2) US-specific data for other pandemics. Turns out that way understates the variety of age patterns of risk!

Age-specific mortality patterns across influenza pandemics: evidence from all-cause mortality data across multiple populations

AbstractBackground. Understanding age-specific mortality patterns across historic influenza pandemics is crucial for future pandemic preparedness. Prior re

academic.oup.com

Really pleased to see our global stunting data up on our world in data. We hope it helps people contextualise child stunting in a much longer historical lens. Thanks to Hannah and Tuna for visualising and explaining the data so well! The link to the original paper is here: doi.org/10.1136/bmjg...

doi.org

Our World in Data@ourworldindata.org · 3mo ago

✍️ New article: “Childhood stunting fell dramatically over the 20th century” One in four children in the world today suffers from “stunting”. That’s 150 *million* children under five. A stunted child is too short for their age due to poor nutrition and frequent infections.

Line chart of childhood stunting rates in Japan by birth cohort from 1892 to 2011 where the rate falls from about 70% in the early 1900s to below 5% by the 2000s, illustrating Japan’s dramatic decline over the 20th century. Dashed horizontal lines show 2015 reference rates for other countries spanning 10 to 60% (examples: 60% in Burundi and East Timor; 50% in Guatemala and Niger; 10% in Thailand and Costa Rica), and a data gap is noted for the World War II cohort. Data source: Eric Schneider et al. (2026) via OurWorldInData.org.

Come join our workshop on excess mortality methodology! It will be two great days of expert talks, discussion groups, and me revealing the results of our many analyst project! 40+ teams have signed up to estimate 1918 pandemic deaths with the method of their choice -- results should be fascinating!

GREATLEAP COST Action@thegreatleap22116.bsky.social · 6mo ago

Workshop “Bridging methods to measure excess mortality: One Epidemic, Many Estimates (1EME)”. 21–22 May 2026, London School of Economics. In-person. Open to all; limited travel funding for UK/EU grad students & GREATLEAP members. Register by 15 Mar 2026 (funding: 15 Feb).🧵⬇️

My research means I spend a lot of timing thinking about the conditions under which people stop trying to preserve their health and well-being. Why do people continue to smoke even when they know the risks of cancer? Why do people refuse to wear a seatbelt or a helmet when they know the risks?

📣 Call for papers: We are inviting you to submit contributions to a Special Collection on the Socioeconomic Inequalities in Mortality in the Long-Run, organized by K. Thompson, T. Riswick & S. Clouston. Submissions to this collection are possible from January 28, 2026 until June 28, 2026. (1/2)

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Like the authors talk about, this also happened during the 1918 flu, with the 1919 cohort being poorer from birth than (at least in the US). As much as I wish differently, this casts doubt on the whole premise of cohort discontinuity studies of the effects of pandemics! (1/2)

Moritz Oberndorfer@moberndorfer.bsky.social · 7mo ago

New paper finally published! Using data on 78 million births from 15 countries, we found that babies conceived during the COVID-19 pandemic have a different parental socioeconomic composition than expected had the pandemic not occurred. doi.org/10.1038/s414... @natcomms.nature.com @helsinki.fi

Screenshot of the title and abstract:
Parental socioeconomic composition of birth cohorts changed during the COVID-19 pandemic.
The COVID-19 pandemic offers opportunities to study effects of in-utero and early life exposure to environmental changes. However, inferences from such studies may be flawed if the pandemic has changed the socioeconomic composition of parents. Analysing over 77.9 million live births from 15 countries, we estimate changes in the socioeconomic composition of the cohort born between December 2020 and December 2021 using interrupted time series analysis. We find that, compared with their counterfactual compositions, the December 2020-December 2021 birth cohort has a higher proportion of babies born to socioeconomically advantaged parents in Austria, England, Finland, the Netherlands, Scotland, Spain, Wales, and the United States while we observe the opposite change for Brazil, Colombia, Ecuador, and Mexico. These changes in cohort composition may cause between-cohort differences in life course outcomes that are influenced by parental socioeconomic circumstances even if early life exposure to the pandemic had no direct effect on this birth cohort.

Retraction Watch has covered the problem of the “national IQ” database. Should be noted I’m far from alone in working to remove these publications. The spreadsheet of pubs which use NIQ - linked to in the article - was started by @kohngregory.bsky.social; a project also worked on by Cathryn Townsend

Dalmeet Singh Chawla@dalmeet.bsky.social · 8mo ago

. @rebeccasear.bsky.social is on a mission to get all studies using a database linking #IQ and race retracted. I spoke to her for @retractionwatch.com to find out more: retractionwatch.com/2025/11/25/m...

If you want to channel your frustration with bad excess mortality modelling into some productive science, come join our "One Epidemic, Many Estimates" (1EME) project! Sign-ups are welcome through January/February! www.lse.ac.uk/Economic-His...

One epidemic, many estimates (1EME)

lse.ac.uk

Adam Kucharski@adamjkucharski.bsky.social · 9mo ago

NIH directors have pointed to below estimates as evidence that Sweden was 'best in the world at protecting human life' for COVID (www.city-journal.org/article/nih-...). But plot doesn't show what they apparently think it shows - and there is a big red flag that immediately jumps out... 🧵

Curious about using census microdata in your research? 📊 Join us for a webinar on IPUMS International, the world’s leading repository of harmonized census data. 🗓️ 12 Nov 2025 | 🕒 15:15–16:30 UK | 💻 Zoom Register: forms.gle/oqTDNU4Zpn2s... Hosted by the LSE Historical Economic Demography Group.

Register for IPUMs International Online Session

Please use this form to register for the IPUMs International Session hosted by the Historical Economic Demography Group at LSE. The session will be on Zoom from 15:15-16:30 UK Time on 12 November 202...

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I'd add that at least in China before the 20th century, polygyny probably wasn't as prevalent as commonly imagined. In our northeast Chinese rural datasets, it was very rare. By the late 19th century, it was also uncommon in the Imperial Lineage, except among close relatives of the Emperor. 1/3

Hampton Gaddy@hggaddy.bsky.social · 10mo ago

🚨 The Economist has been telling you for years that polygamy causes civil war by locking men out of marriage. A new article with @rebeccasear.bsky.social and @anthrolog.bsky.social explains that the demography of marriage markets doesn't actually work that way. 🧵 www.pnas.org/doi/10.1073/...