ReviewReproductive sciences (Thousand Oaks, Calif.)2023
Developmental Programming in Animal Models: Critical Evidence of Current Environmental Negative Changes.
Review in Reproductive sciences (Thousand Oaks, Calif.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Remodeling Cardiovascular Research: Ready to Sacrifice Animal Models?Journal of cardiovascular pharmacology · 2025Article
- Animal Models for Studying Developmental Origins of Cardiovascular-Kidney-Metabolic Syndrome.Biomedicines · 2025Review
- Animal models for understanding the mechanisms of malnutrition: a literature review.Frontiers in nutrition · 2025Review
- Key questions and gaps in understanding adipose tissue macrophages and early-life metabolic programming.American journal of physiology. Endocrinology and metabolism · 2024Review
- Health position paper and redox perspectives - Disease burden by transportation noise.Redox biology · 2024Review
- A comprehensive review on endocrine toxicity of gaseous components and particulate matter in smog.Frontiers in endocrinology · 2024Review
- The Legacy of Parental Obesity: Mechanisms of Non-Genetic Transmission and Reversibility.Biomedicines · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Developmental Origins of Health and Disease (DOHaD) approach answers questions surrounding the early events suffered by the mother during reproductive stages that can either partially or permanently influence the developmental programming of children, predisposing them to be either healthy or exhibit negative health outcomes in adulthood. Globally, vulnerable populations tend to present high obesity rates, including among school-age children and women of reproductive age. In addition, adults suffer from high rates of diabetes, hypertension, cardiovascular, and other metabolic diseases. The increase in metabolic outcomes has been associated with the combination of maternal womb conditions and adult lifestyle-related factors such as malnutrition and obesity, smoking habits, and alcoholism. However, to date, "new environmental changes" have recently been considered negative factors of development, such as maternal sedentary lifestyle, lack of maternal attachment during lactation, overcrowding, smog, overurbanization, industrialization, noise pollution, and psychosocial stress experienced during the current SARS-CoV-2 pandemic. Therefore, it is important to recognize how all these factors impact offspring development during pregnancy and lactation, a period in which the subject cannot protect itself from these mechanisms. This review aims to introduce the importance of studying DOHaD, discuss classical programming studies, and address the importance of studying new emerging programming mechanisms, known as actual lifestyle factors, during pregnancy and lactation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.