Intergenerational transmission of height in a historical population: from taller mothers to larger offspring at birth (and as adults)

Background Changes in growth and height reflect changes in nutritional status and health. The systematic surveillance of growth can suggest areas for interventions. Moreover, phenotypic variation has a strong intergenerational component. There is a lack of historical family data that can be used to track the transmission of height over subsequent generations. Maternal height is a proxy for conditions experienced by one generation that relates to the health/growth of future generations. Cross-sectional/cohort studies have shown that shorter maternal height is closely associated with lower birthweight of offspring. Objective/Methods We analyzed the maternal height and offspring weight at birth in the maternity hospital in Basel, Switzerland, from 1896–1939 (N=ca. 12,000) using GAMs. Results We observed that average height of the mothers increased by ca. 4 cm across 60 birth years, and that average birthweight of their children shows a similarly shaped and upward trend 28 years later. Our final model (adjusted for year, parity, sex of the child, gestational age, and maternal birthyear) revealed a significant and almost linear association between maternal height and birthweight. Maternal height was the second most important variable modeling birthweight, after gestational age. In addition, we found a significant association between maternal height and aggregated average height of males from the same birth years at time of conscription, 19 years later. Conclusions Our results have implications for public health: When (female/maternal) height increases due to improved nutritional status, size at birth—and subsequently also the height in adulthood of the next generation—increases as well. However, the directions of development in this regard may currently differ depending on the world region

Health of neonates born in the maternity hospital in Bern, Switzerland, 1880-1900 and 1914-1922.

The identification of factors impeding normal fetal development and growth is crucial for improving neonatal health. Historical studies are relevant because they show which parameters have influenced neonatal health in the past in order to better understand the present. We studied temporal changes of neonatal health outcomes (birth weight, gestational age, stillbirth rate) and the influence of different cofactors in two time periods. Moreover, we investigated particularly neonatal health in the wake of the 1918/19 influenza pandemic. Data were transcribed from the Bern Maternity Hospital and consists of two time periods: A) The years 1880, 1885, 1890, 1895 and 1900 (N = 1530, births' coverage 20%); B) The years 1914-1922 (N = 6924, births' coverage 40-50%). Linear regression models were used to estimate the effect of birth year on birth weight, and logistic regression models to estimate the effect of birth year and of the exposure to the pandemic on premature birth, stillborn and low birth weight (LBW). Mean birth weight increased only minimally between the two datasets; whereas, in the years 1914-1922, the preterm birth and stillbirth rates were markedly reduced compared with the years 1880-1900. Sex, parity, gestational age and maternal age were significantly associated with birth weight in both time periods. The probability of LBW was significantly increased in 1918 (OR 1.49 (95% CI 1.00-2.23)) and in 1919 (OR 1.55 (95% CI 1.02-2.36)) compared to 1914. Mothers who were heavily exposed to the influenza pandemic during pregnancy had a higher risk of stillbirth (OR 2.27 (95% CI 1.32-3.9)). This study demonstrated that factors influencing neonatal health are multifactorial but similar in both time periods. Moreover, the exposure to the 1918/19 pandemic was less associated with LBW and more associated with an increased risk of stillbirth. If this trend is confirmed by further studies, it could indicate some consistency across pandemics, as similar patterns have recently been shown for COVID-19

Health of neonates born in the maternity hospital in Bern, Switzerland, 1880–1900 and 1914–1922

The identification of factors impeding normal fetal development and growth is crucial for improving neonatal health. Historical studies are relevant because they show which parameters have influenced neonatal health in the past in order to better understand the present. We studied temporal changes of neonatal health outcomes (birth weight, gestational age, stillbirth rate) and the influence of different cofactors in two time periods. Moreover, we investigated particularly neonatal health in the wake of the 1918/19 influenza pandemic. Data were transcribed from the Bern Maternity Hospital and consists of two time periods: A) The years 1880, 1885, 1890, 1895 and 1900 (N = 1530, births’ coverage 20%); B) The years 1914–1922 (N = 6924, births’ coverage 40–50%). Linear regression models were used to estimate the effect of birth year on birth weight, and logistic regression models to estimate the effect of birth year and of the exposure to the pandemic on premature birth, stillborn and low birth weight (LBW). Mean birth weight increased only minimally between the two datasets; whereas, in the years 1914–1922, the preterm birth and stillbirth rates were markedly reduced compared with the years 1880–1900. Sex, parity, gestational age and maternal age were significantly associated with birth weight in both time periods. The probability of LBW was significantly increased in 1918 (OR 1.49 (95% CI 1.00–2.23)) and in 1919 (OR 1.55 (95% CI 1.02–2.36)) compared to 1914. Mothers who were heavily exposed to the influenza pandemic during pregnancy had a higher risk of stillbirth (OR 2.27 (95% CI 1.32–3.9)). This study demonstrated that factors influencing neonatal health are multifactorial but similar in both time periods. Moreover, the exposure to the 1918/19 pandemic was less associated with LBW and more associated with an increased risk of stillbirth. If this trend is confirmed by further studies, it could indicate some consistency across pandemics, as similar patterns have recently been shown for COVID-19

Reinfections and Cross-Protection in the 1918/19 Influenza Pandemic: Revisiting a Survey Among Male and Female Factory Workers

Objectives: The COVID-19 pandemic highlights questions regarding reinfections and immunity resulting from vaccination and/or previous illness. Studies addressing related questions for historical pandemics are limited.Methods: We revisit an unnoticed archival source on the 1918/19 influenza pandemic. We analysed individual responses to a medical survey completed by an entire factory workforce in Western Switzerland in 1919.Results: Among the total of n = 820 factory workers, 50.2% reported influenza-related illness during the pandemic, the majority of whom reported severe illness. Among male workers 47.4% reported an illness vs. 58.5% of female workers, although this might be explained by varied age distribution for each sex (median age was 31 years old for men, vs. 22 years old for females). Among those who reported illness, 15.3% reported reinfections. Reinfection rates increased across the three pandemic waves. The majority of subsequent infections were reported to be as severe as the first infection, if not more. Illness during the first wave, in the summer of 1918, was associated with a 35.9% (95%CI, 15.7–51.1) protective effect against reinfections during later waves.Conclusion: Our study draws attention to a forgotten constant between multi-wave pandemics triggered by respiratory viruses: Reinfection and cross-protection have been and continue to be a key topic for health authorities and physicians in pandemics, becoming increasingly important as the number of waves increases

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Data for "The ups and downs of birth rate in Switzerland 2020 to 2023 in a historical context"

<p>The data contains the aggregated birth data and the Swiss population figures for total births and  several subgroups (Language Region, Swiss vs non-Swiss, etc) . Subgroups have existed since 1987 and the number of parities since 2005. For 2023, there is only data up to September and no information on subgroups. The population figure for 2023 was taken from 2022 as it was not yet available at the time of publication.</p&gt

Health of singleton neonates in Switzerland through time and crises: a cross-sectional study at the population level, 2007-2022.

BACKGROUND Being exposed to crises during pregnancy can affect maternal health through stress exposure, which can in return impact neonatal health. We investigated temporal trends in neonatal outcomes in Switzerland between 2007 and 2022 and their variations depending on exposure to the economic crisis of 2008, the flu pandemic of 2009, heatwaves (2015 and 2018) and the COVID-19 pandemic. METHODS Using individual cross-sectional data encompassing all births occurring in Switzerland at the monthly level (2007-2022), we analysed changes in birth weight and in the rates of preterm birth (PTB) and stillbirth through time with generalized additive models. We assessed whether the intensity or length of crisis exposure was associated with variations in these outcomes. Furthermore, we explored effects of exposure depending on trimesters of pregnancy. RESULTS Over 1.2 million singleton births were included in our analyses. While birth weight and the rate of stillbirth have remained stable since 2007, the rate of PTB has declined by one percentage point. Exposure to the crises led to different results, but effect sizes were overall small. Exposure to COVID-19, irrespective of the pregnancy trimester, was associated with a higher birth weight (+12 grams [95% confidence interval (CI) 5.5 to 17.9 grams]). Being exposed to COVID-19 during the last trimester was associated with an increased risk of stillbirth (odds ratio 1.24 [95%CI 1.02 to 1.50]). Exposure to the 2008 economic crisis during pregnancy was not associated with any changes in neonatal health outcomes, while heatwave effect was difficult to interpret. CONCLUSION Overall, maternal and neonatal health demonstrated resilience to the economic crisis and to the COVID-19 pandemic in a high-income country like Switzerland. However, the effect of exposure to the COVID-19 pandemic is dual, and the negative impact of maternal infection on pregnancy is well-documented. Stress exposure and economic constraint may also have had adverse effects among the most vulnerable subgroups of Switzerland. To investigate better the impact of heatwave exposure on neonatal health, weekly or daily-level data is needed, instead of monthly-level data

Presentation1_Reinfections and Cross-Protection in the 1918/19 Influenza Pandemic: Revisiting a Survey Among Male and Female Factory Workers.pdf

Objectives: The COVID-19 pandemic highlights questions regarding reinfections and immunity resulting from vaccination and/or previous illness. Studies addressing related questions for historical pandemics are limited.Methods: We revisit an unnoticed archival source on the 1918/19 influenza pandemic. We analysed individual responses to a medical survey completed by an entire factory workforce in Western Switzerland in 1919.Results: Among the total of n = 820 factory workers, 50.2% reported influenza-related illness during the pandemic, the majority of whom reported severe illness. Among male workers 47.4% reported an illness vs. 58.5% of female workers, although this might be explained by varied age distribution for each sex (median age was 31 years old for men, vs. 22 years old for females). Among those who reported illness, 15.3% reported reinfections. Reinfection rates increased across the three pandemic waves. The majority of subsequent infections were reported to be as severe as the first infection, if not more. Illness during the first wave, in the summer of 1918, was associated with a 35.9% (95%CI, 15.7–51.1) protective effect against reinfections during later waves.Conclusion: Our study draws attention to a forgotten constant between multi-wave pandemics triggered by respiratory viruses: Reinfection and cross-protection have been and continue to be a key topic for health authorities and physicians in pandemics, becoming increasingly important as the number of waves increases.</p

Estimation of vaccine doses for different vaccination strategies in Kandal and Battambang province.

Estimation of vaccine doses for different vaccination strategies in Kandal and Battambang province.</p