Researchers used logistic regression to examine associations between individual exposures to air pollutants and low birth weight during different gestational periods. They combined the analysis with a distributed lag nonlinear model to explore exposure timing and possible vulnerable windows. The abstract does not specify a particular vulnerable window or report the corresponding numerical results, so the available evidence does not establish when pollution exposure had the strongest association with low birth weight.

Mixed-exposure analyses were conducted using dual-pollutant models and weighted quantile sum regression. These models indicated that combined exposure to air pollutants during the first trimester, the second trimester and the full trimester was associated with higher odds of low birth weight. PM2.5 and CO contributed the most to the mixed-exposure association in the weighted quantile sum model. These findings concern statistical associations from observational analyses and do not demonstrate that pollution caused low birth weight.

Stratified analyses also reported associations between prenatal PM2.5 and CO exposure and higher odds of low birth weight among pregnant women younger than 35 years, although the abstract does not identify the exposure window for those subgroup estimates. Among pregnant women with gestational diabetes, exposure to PM2.5, particulate matter with an aerodynamic diameter of 10 micrometres or less and sulfur dioxide was positively associated with odds of low birth weight. The evidence summarized here comes from the study abstract, which does not describe exposure assignment, potential confounding, missing-data handling or other details needed for a full assessment. The retrospective, single-hospital design also limits how broadly the findings can be generalized. The authors proposed further research on the synergistic effects of multiple pollutants as a direction for future study, rather than as an additional result of the current analysis.

Subject of Research: Associations between prenatal air-pollution exposure and low birth weight in a retrospective Fujian cohort

Article Title: The association between air pollution exposure during pregnancy and low birth weight: a retrospective cohort study in southern China

Article References: Cai, Y., Lin, Y., Jiang, J., Li, H., Dong, Y., Zhang, Y., & Zhang, Q. (2026). The association between air pollution exposure during pregnancy and low birth weight: a retrospective cohort study in southern China. BMC Public Health. https://doi.org/10.1186/s12889-026-29842-4

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29842-4

Keywords: air pollution, pregnancy, low birth weight, PM2.5, carbon monoxide, Fujian, maternal health, retrospective cohort, mixed exposure, association, between, pollution

The review, led by Ginevra Chincarini and colleagues at RMIT University in Melbourne, Australia, alongside collaborators in Canada, systematically combed six major research databases for studies published between January 1985 and February 2025. The team was looking for something specific: research that followed people born at term with IUGR, small for gestational age (SGA), or low birth weight (LBW) into adolescence and young adulthood, measuring how they moved, thought, and felt. They also searched for animal studies in which IUGR had been experimentally induced through placental insufficiency and behavioral outcomes were assessed at developmental stages equivalent to human adolescence or early adulthood.

What emerged was a map of 28 studies—16 clinical and 12 preclinical—that collectively paint a picture of a field with significant strengths and equally significant gaps. Cognitive outcomes were the most frequently studied, appearing in 19 of the 28 investigations. Motor outcomes came second, assessed in 14 studies. Anxiety-related behaviors, however, were examined in only 11 studies overall—and the distribution was strikingly lopsided: just 3 of the 16 clinical studies looked at anxiety, while 8 of the 12 preclinical studies did.

This asymmetry is not merely an academic curiosity. It represents what the authors call a translational gap—a mismatch between what animal models are telling us and what human studies are actually measuring. Animal researchers have extensively probed anxiety-like behaviors in IUGR models using tools like the open field test, the elevated plus maze, and the light–dark box. Rabbit models of IUGR, in particular, consistently show increased anxiety-like behavior, characterized by reduced exploration and increased immobility. Rat models, by contrast, have shown no increase in anxiety-like behavior on standard measures, though some displayed increased locomotor activity—a finding that itself is ambiguous, since heightened movement in an open field could reflect hyperactivity, escape behavior, or stress rather than a primary motor deficit.

On the clinical side, the evidence for motor outcomes is suggestive but not uniform. Five clinical studies examined motor performance in adolescents and young adults born SGA or LBW, using standardized tools such as the Movement Assessment Battery for Children and the Beery-Buktenica Developmental Test of Visual-Motor Integration. Across these studies, reductions in fine motor coordination and manual dexterity were reported in growth-restricted groups compared with appropriately grown peers, while gross motor performance was largely preserved. One study, however, found no differences in total Movement ABC scores between SGA and appropriate-for-gestational-age groups, and in young adults, SGA was associated with lower scores on the Visual Motor Integration motor coordination subtest. Notably, none of these studies incorporated antenatal confirmation of IUGR.

Cognitive outcomes tell a somewhat more consistent story. Ten clinical studies evaluated cognition, most using standardized assessments such as the Wechsler Intelligence Scales or national academic testing frameworks. Reported outcomes included lower full-scale and verbal IQ scores on the WAIS-III, WISC-R, and Otis test, as well as reduced executive and attentional performance on tasks like the Trail Making Test, the Stroop test, and the Wisconsin Card Sorting Test in SGA and LBW groups compared with appropriately grown peers. Two studies that incorporated antenatal measures of growth or placental function identified greater cognitive differences in confirmed IUGR subgroups, though these subgroups were small—just five and six participants respectively.

Preclinical studies of cognition focused on more circumscribed domains, using paradigms like the Morris water maze, the Y-maze, the T-maze, and novel object recognition tasks. In rat models, several studies reported deficits in spatial or working memory and impaired recognition performance, particularly during adolescent-equivalent stages. Rabbit studies demonstrated short-term memory impairments on novel object recognition tasks but often normal performance on T-maze learning. In sheep—the only gyrencephalic species represented, meaning an animal with a folded, human-like brain cortex—mild spatial learning impairments were reported in males but not females, with normalization by adulthood. Few studies investigated sex differences systematically, but where they did, effects were inconsistent across species: some showed more prominent effects in female rats, others in male sheep.

The review also surfaced a methodological problem that has haunted the field for decades: the conflation of IUGR with SGA and LBW. These terms are not synonymous. IUGR reflects a pathological process of restricted growth due to compromised placental function, whereas SGA describes a statistical measure of low birthweight—below the 10th percentile for gestational age—that may occur in otherwise healthy fetuses. Yet the majority of clinical studies in this review classified participants as SGA or LBW without any antenatal confirmation of placental insufficiency. Only two of the sixteen clinical studies applied antenatal ultrasound or Doppler criteria to confirm IUGR. This diagnostic inconsistency, the authors argue, complicates interpretation of long-term neurodevelopmental outcomes and hinders precise translation between human and preclinical research.

The preclinical evidence base, meanwhile, is narrow in its species representation. All twelve preclinical studies used rodents, rabbits, or sheep—seven rat studies, three rabbit studies, and two sheep studies. No studies were conducted in non-human primates. Only the sheep, as a gyrencephalic species, offered any anatomical comparability to the human brain. Moreover, all rodent and rabbit models induced placental insufficiency in mid-to-late gestation, capturing only late-onset growth restriction. The sheep carunclectomy model, which surgically reduces implantation sites before conception, is the exception, affecting placental function throughout gestation. This distinction matters because IUGR arising from early placental maldevelopment in humans may produce a different neurodevelopmental profile than late-onset insufficiency—a nuance the current preclinical evidence base does not capture.

The authors also note that seven of the sixteen clinical studies drew participants from the same Norwegian birth cohort born between 1986 and 1988, meaning the clinical evidence base represents approximately nine independent populations rather than sixteen. While this overlap limits diversity, it does enable comparison of outcomes from the same cohort at both adolescence and young adulthood across motor, cognitive, and anxiety domains. Looking forward, the review’s authors call for standardised diagnostic frameworks incorporating antenatal imaging and placental pathology, alignment of behavioural testing across species, systematic inclusion of sex and environmental modifiers, and expansion into gyrencephalic or large-animal models. Without these coordinated changes, the full neurobehavioural profile of growth restriction beyond childhood will remain stubbornly out of focus.

Subject of Research: Long-term neurobehavioural outcomes of term intrauterine growth restriction across human and animal studies

Article Title: Neurobehavioural outcomes after term IUGR from adolescence to adulthood: a cross-species scoping review

Article References: Chincarini, G., Gilchrist, C. P., Coyle, M. E., Walker, D. W., Tolcos, M., & Cumberland, A. (2026). Neurobehavioural outcomes after term IUGR from adolescence to adulthood: a cross-species scoping review. Pediatric Research. https://doi.org/10.1038/s41390-026-05583-3

Image Credits: AI Generated

DOI: 10.1038/s41390-026-05583-3

Keywords: intrauterine growth restriction, IUGR, neurodevelopment, placental insufficiency, small for gestational age, cognitive outcomes, motor coordination, anxiety, scoping review, cross-species comparison, Pediatric Research, developmental origins of health and disease

The research team, led by Cornelia C. Metges and colleagues working at German research institutes, used a carefully controlled piglet model to isolate the effects of birth weight and supplementation. At birth, the scientists selected 24 pairs of male littermates: in each pair, one piglet had a low birth weight of roughly 1.10 kilograms and the other a normal birth weight of about 1.50 kilograms. This paired design is powerful because littermates share genetics and much of their prenatal environment, so differences observed later can be attributed more confidently to birth weight itself or to the experimental diet. On the first day of life, litters were standardized to twelve piglets to equalize competition at the udder, and from that point each piglet received a daily oral supplement until the age of five days.

The supplement itself was designed with surgical precision. Half of the animals received glutamine at a dose of one gram per kilogram of body weight, while the others received an isonitrogenous dose of alanine, 1.22 grams per kilogram, which supplies the same amount of nitrogen but a different amino acid. This control matters enormously. Without it, any observed effect could simply reflect extra nitrogen rather than glutamine’s specific biochemistry. By day five, the piglets were euthanized and an extraordinary array of samples was collected: stomach contents, duodenal and liver tissue, colon tissue, and blood plasma. From these, the team measured free amino acids, protein-bound amino acids, amino acid metabolites, biochemical indices, the abundance of messenger RNA for glutamine transport and metabolism genes, and the fractional protein synthesis rate in the duodenum, colon and liver.

Fractional protein synthesis rate is the key metric here, because it captures how fast tissue proteins are actually being built, not just how much building material is present. The technique relies on a flooding dose of a labeled amino acid that rapidly equilibrates across tissues, allowing researchers to calculate the proportion of existing protein that was newly synthesized during a short window. For a study asking whether glutamine stimulates growth of the splanchnic tissues, the gut and liver that sit at the crossroads of nutrient absorption and metabolism, this measurement is the gold standard. Surprisingly, the results showed only modest effects on protein synthesis. Colon fractional protein synthesis was higher in normal birth weight piglets given alanine than in low birth weight piglets given the same supplement, but glutamine itself did not significantly boost synthesis rates in the duodenum, colon or liver.

What the study did find was a clear biochemical fingerprint of glutamine metabolism along the digestive tract. Glutamine and glutamate concentrations in stomach digesta were markedly higher in supplemented animals, confirming that the oral dose reached the stomach intact. But the data also showed that not all of the glutamine simply passed through to the small intestine unchanged. The pattern of free amino acids and metabolites in duodenal tissue indicated that glutamine is absorbed and metabolized right there in the duodenum, the first segment of the small intestine, rather than traveling further downstream before being taken up. This local metabolism has consequences: the researchers suggest it may alter the intracellular pH of duodenal cells, a subtle but potentially meaningful shift in the chemical environment of the gut lining.

Even more striking was the evidence pointing toward oxidative stress. When the team applied a sophisticated statistical method called Data Integration Analysis for Biomarker Discovery using Latent Variable Approaches for Omics Studies, or DIABLO, the analysis separated the supplementation groups cleanly using glutamine, carnosine, citrulline and alanine as the discriminating molecules. More provocatively, the same integrative approach separated glutamine-supplemented low birth weight piglets from their alanine counterparts using the messenger RNA abundance of glutathione reductase, glutathione synthetase and tight junction protein 1. Glutathione is the cell’s master antioxidant, and elevated expression of the enzymes that build and recycle it is a classic sign that cells are working harder to cope with oxidative pressure. Tight junction protein 1, meanwhile, is central to the seals between gut lining cells that keep the intestinal barrier intact.

Reading these signals together, the authors propose that glutamine supplementation appears to increase markers of oxidative stress in the duodenum of low birth weight piglets. This is not necessarily a harmful outcome in itself; transient activation of antioxidant defenses can reflect adaptive metabolic activity, and the gut lining of a newborn is constantly remodeling. But it complicates the assumption that more glutamine is simply better for fragile newborns. It also helps explain an earlier finding from the same research program: glutamine supplementation did raise body weight and plasma glutamine concentrations in low birth weight piglets, yet it left jejunal glutamine concentrations, glutamine transport and the expression of metabolism-related genes in the jejunum untouched. The new duodenal data suggest the action, and the metabolic cost, may be concentrated further up the intestine than previously appreciated.

Other findings underscore how much birth weight alone shapes neonatal metabolism, independent of diet. Duodenal RNA content was lower and the protein-to-RNA ratio higher in glutamine-supplemented low birth weight piglets compared with alanine controls, hinting at differences in cellular composition or translational activity in that tissue. And in a study that measured hundreds of plasma metabolites, the circulating metabolome was essentially unaffected by supplementation, meaning the systemic metabolic ripple of the daily glutamine dose was small even though local gut chemistry shifted measurably. For anyone designing neonatal nutrition interventions, that dissociation between local tissue effects and the plasma picture is a cautionary lesson: what happens in the gut wall does not necessarily show up in a blood draw.

Why does this matter beyond the barn? Piglets are widely regarded as one of the best translational models for human neonatal physiology, particularly for studies of the gut, nutrition and low birth weight in premature infants. Intrauterine growth restriction affects millions of human babies each year and is linked to long-term metabolic and neurodevelopmental consequences. If glutamine, one of the most studied conditionally essential amino acids in neonatal nutrition, can reshape antioxidant gene expression and barrier-related signals in the newborn duodenum, then the timing, dose and tissue-specific consequences of such supplementation deserve closer scrutiny in both veterinary and pediatric contexts. The finding that glutamine is metabolized locally in the duodenum, potentially shifting intracellular pH, also gives formulators a concrete mechanism to consider when deciding whether to deliver glutamine orally, enterally further downstream, or parenterally.

The study’s limitations are those inherent to any tightly controlled animal trial: the piglets were five days old at sampling, the intervention window was short, and the paired male-only design, while rigorous, limits generalization to females and to older animals. Yet the sheer breadth of the measurements, spanning stomach contents, three splanchnic tissues, transcript-level markers and an untargeted plasma metabolome, makes this one of the most complete assessments of neonatal glutamine supplementation to date. The take-home message is nuanced but clear. Glutamine does reach and engage the newborn gut, it is processed in the duodenum, and it leaves detectable molecular traces in the intestinal lining of low birth weight piglets, including signs of heightened oxidative stress handling. But it does not dramatically rev up protein synthesis in the gut and liver within five days, and it leaves the circulating metabolome largely untouched. For the smallest piglets in the litter, the road to catch-up growth, it seems, will not be paved by glutamine alone, and the next generation of neonatal supplements will need to account for the gut’s own metabolic response to what it is fed.

Subject of Research: Effects of neonatal glutamine supplementation on amino acid profiles, protein synthesis and the plasma metabolome in low birth weight piglets

Article Title: Relationship between neonatal glutamine supplementation and amino acid profiles, protein synthesis in splanchnic tissues and the plasma metabolome in 5-day-old piglets with low birth weight

Article References: Sciascia, M., Buchallik-Schregel, J., Li, Z., Görs, S., Tuchscherer, A., Hoeflich, A., Henning, A.-K., Zentek, J., & Metges, C. C. (2026). Relationship between neonatal glutamine supplementation and amino acid profiles, protein synthesis in splanchnic tissues and the plasma metabolome in 5-day-old piglets with low birth weight. PLOS One, 21(10), e0359788. https://doi.org/10.1371/journal.pone.0359788

Image Credits: AI Generated

DOI: 10.1371/journal.pone.0359788

Keywords: glutamine, low birth weight, piglets, neonatal nutrition, duodenum, protein synthesis, amino acids, oxidative stress, plasma metabolome, splanchnic tissues, gut barrier, PLOS One

The stakes are far from academic. Perinatal risk factors such as preterm birth, intrauterine growth restriction, and low birth weight affect a substantial share of all births worldwide, and decades of epidemiological work have linked them to elevated risks of hypertension, ischemic heart disease, heart failure, type 1 and type 2 diabetes, obesity, and neurodevelopmental difficulties later in life. Large cohort studies, including national registries from Scandinavia, have shown that people born preterm carry measurably higher odds of cardiovascular disease well into middle age. If HRV could serve as an early, noninvasive marker of the autonomic consequences of an adverse perinatal start, clinicians might one day identify which NICU graduates need closer cardiovascular surveillance decades before symptoms appear.

HRV is not a single number but a family of metrics. Time-domain measures quantify the statistical spread of beat-to-beat intervals over a recording, while frequency-domain methods decompose those fluctuations into bands that roughly reflect sympathetic and parasympathetic, or vagal, contributions. Vagal tone, in particular, has fascinated researchers because it tracks not only cardiac health but also self-regulation, attention, and social engagement, themes explored in frameworks such as polyvagal theory. In newborns, HRV matures rapidly, and disruptions during the NICU period, from procedural pain to prolonged hospital stays and surgery, are well documented. What remained murky was what happens after discharge, when the monitors come off and the child, adolescent, or adult lives in the ordinary world.

To bring order to that murkiness, the Leuven team searched PubMed, EMBASE, Web of Science, Scopus, and APA PsycArticles through April 2025, supplemented by ClinicalTrials.gov and backward reference screening. They included peer-reviewed studies that compared HRV between perinatal risk populations and healthy full-term controls after hospital discharge, ultimately extracting 156 effect sizes from 27 studies. The scale matters: this is the first meta-analysis to quantify HRV differences across perinatal risk groups from infancy all the way to adulthood, focusing specifically on the post-discharge window that most families actually inhabit.

The headline result is a shrug with a twist. Across all studies, the pooled effect was small and statistically non-significant, a standardized mean difference of d equal to minus 0.21 with a p-value of 0.14, and the heterogeneity between studies was enormous, with an I-squared of 89.3 percent. In plain language, on average, perinatal risk populations did not show reliably lower HRV than controls, and the individual studies disagreed so wildly that any single pooled number is almost meaningless. For a field that has produced dozens of seemingly contradictory papers, this is both a humbling verdict and a clarifying one: the inconsistency is not noise to be wished away but a signal about where and when to look.

That signal becomes visible when the data are sliced by condition. The most consistent HRV reductions appeared in growth-related risk groups, namely children and infants who were born small for gestational age or with intrauterine growth restriction. This makes physiological sense. Fetal growth restriction typically reflects chronic compromise of the placental blood supply, a stressor that can reshape cardiovascular regulation before the first breath. Studies of growth-restricted children, from recordings during sleep and wake stages to antenatal hemodynamic findings tracked into school age, repeatedly found blunted variability, suggesting that the autonomic imprint of restricted growth persists well beyond the neonatal period.

Preterm birth and low birth weight told a different story. Neither showed a significant overall effect, yet both displayed substantial between-study heterogeneity across age groups, hinting that timing is everything. The meta-analysis found that younger samples showed larger group differences than older samples, with pronounced HRV alterations in preterm-born infants that shrank and became more variable in older children, adolescents, and adults. One provocative thread in the underlying literature is the possibility of premature parasympathetic decline: adults born at extremely low birth weight have shown reduced respiratory sinus arrhythmia, a vagal index, compared with their normal-birth-weight peers, raising the question of whether early risk accelerates an age-related drift rather than producing a static deficit. A key limitation acknowledged by the authors is that the included studies were overwhelmingly cross-sectional, so they compare groups at single time points and cannot distinguish true within-individual catch-up growth from survivor bias, in which the frailest infants do not reach later-life follow-up.

Methodologically, the review also pushes back against a common reflex in the field: blaming disagreement on the choice of HRV parameter. According to the authors, timing and etiology, rather than parameter choice, drive the inconsistencies across studies. Whether researchers used time-domain or frequency-domain metrics mattered far less than which perinatal condition was studied and at what developmental stage. That reframing carries practical weight for study design. It argues for age- and condition-specific assessment rather than lumping all at-risk births into one category, and it suggests that a single HRV snapshot at any arbitrary age may mislead more than it informs.

The broader vision connects to the developmental origins of health and disease, the idea that early-life conditions program long-term physiological risk. Autonomic function sits at the crossroads of that program, influencing not only cardiovascular outcomes but also stress reactivity, cortisol regulation, and even social skills and psychopathology, links documented in studies of very preterm children during school age. Wearable devices, which can now capture HRV continuously outside the clinic, promise to turn this research from episodic snapshots into movies of autonomic development, and recent work in healthy preterm-born young adults has already demonstrated the feasibility of such approaches. If validated, HRV could become a kind of early-warning dashboard for NICU graduates, flagging those whose autonomic trajectory warrants cardiology follow-up before blood pressure or metabolic problems emerge.

For now, the authors’ conclusions are deliberately restrained. Autonomic associations with perinatal risk appear condition-specific and age-dependent, and the field needs longitudinal follow-up that follows the same children over time, separating genuine developmental change from the distortions introduced by differential survival. Parents of preterm or growth-restricted children should not read this work as a verdict on their child’s heart. Rather, it is a map of where science should dig next: with growth-restricted children showing the most consistent signatures, infancy emerging as the most revealing window, and adulthood still largely unmapped, the beats between the beats are telling a story, and researchers are finally learning how to read it.

Subject of Research: Heart rate variability after hospital discharge in preterm, low-birth-weight, and growth-restricted populations

Article Title: Heart rate variability after hospital discharge in perinatal risk populations: a systematic review and meta-analysis

Article References: Gistelinck, L., Van den Broeck, R., Verhelst, C., De Vos, M., Wass, S., Naulaers, G., & Boets, B. (2026). Heart rate variability after hospital discharge in perinatal risk populations: a systematic review and meta-analysis. Pediatric Research. https://doi.org/10.1038/s41390-026-05416-3

Image Credits: AI Generated

DOI: 10.1038/s41390-026-05416-3

Keywords: heart rate variability, preterm birth, low birth weight, intrauterine growth restriction, small for gestational age, autonomic nervous system, meta-analysis, neonatology, cardiovascular risk, developmental origins of health and disease, vagal tone, Pediatric Research

The research, conducted by Fabricio González-Andrade of Universidad Tecnológica Indoamérica in Quito, took the form of a retrospective ecological time-series study, a design that aggregates population-level data rather than following individual patients. The investigator drew on thirteen annual national hospital discharge datasets from Ecuador’s National Institute of Statistics and Censuses, using registered live births as the denominator to calculate hospitalization rates, and paired these with six annual mortality datasets covering 2019 through 2024. Because the analysis relied exclusively on publicly available, de-identified administrative and vital statistics data, no individual informed consent or ethics committee approval was required under Ecuadorian regulations governing observational health research. The methodological rigor of the approach was reinforced by adherence to internationally recognized reporting standards for observational studies conducted with routinely collected health data.

The headline finding concerns respiratory distress of the newborn, classified under ICD-10 code P22, which towered over the other conditions in every measure of burden examined. Over the study period, this single condition accounted for 110,091 hospitalizations, more than 1.03 million hospital days, 2,381 deaths, and an estimated 220,778 disability-adjusted life years lost. To put those numbers in perspective, respiratory distress alone generated roughly forty-four percent of all the hospital discharges captured in the analysis. Its hospitalization rate climbed from 25.90 to 41.57 per 1,000 registered live births across the thirteen-year window, a statistically significant overall annual percent change of 3.15 percent, with a confidence interval running from 1.33 to 5.00 percent. That trajectory suggests a steady, compounding pressure on neonatal services rather than a sudden shock, and it implies that demand for surfactant therapy, mechanical ventilation, and specialized nursing care has been growing year after year regardless of other disruptions to the health system.

Birth asphyxia, coded P21, told a very different and arguably more alarming story. Although it did not dominate hospitalization counts, it recorded the highest ecological deaths-to-hospitalizations ratio in the study at 11.22 percent, meaning that for every hundred hospitalizations attributed to asphyxia, more than eleven infant deaths were registered nationally. More significantly, it was the only one of the four conditions to show a statistically significant increase in mortality over the period analyzed, with an annual percent change of 9.60 percent and a confidence interval of 4.33 to 15.13 percent, yielding a P value of 0.007. Birth asphyxia, which results from a failure of oxygen delivery around the time of delivery, is in many settings considered a marker of the quality of intrapartum care, including fetal monitoring, timely recognition of distress, and access to emergency obstetric and neonatal resuscitation services. A rising mortality signal in this category therefore points toward systemic weaknesses in the chain of care surrounding childbirth rather than merely changes in how illnesses are coded.

The two remaining conditions added further nuance to the national picture. Disorders related to short gestation and low birth weight, the P07 category that captures the consequences of prematurity, and bacterial sepsis of the newborn, coded P36, each followed their own trajectories. Sepsis in particular increased rapidly in the early years of the series before reaching a statistical joinpoint in 2017, after which it declined modestly. This pre-existing deceleration proved methodologically important: when the investigator applied exploratory interrupted time-series estimates to the pandemic years of 2020 through 2024, the results for sepsis had to be interpreted against the backdrop of a trend that was already flattening before COVID-19 arrived. In other words, apparent pandemic-era changes in sepsis hospitalizations cannot be straightforwardly attributed to the disruption itself, a caution that applies to many observational studies attempting to isolate the effects of the pandemic on health services.

One of the study’s notable technical strengths is that it avoided the imputation problems that have plagued similar analyses elsewhere. Because complete national hospitalization data were available for every year from 2012 through 2024, including the pandemic period, all years were analyzed as directly observed records. This eliminated the need to model or estimate missing pandemic-era values, a source of considerable uncertainty in time-series research from countries where routine data collection faltered during 2020 and 2021. The analytical toolkit was correspondingly rich: segmented regression to identify joinpoints where trends changed direction, negative binomial regression suited to overdispersed count data, incidence rate ratios to quantify relative risk, deviations from prepandemic projections, and an acute disability-adjusted life year metric combining years of life lost with years lived with disability to translate hospitalizations and deaths into a single measure of population health burden.

The concept of the deaths-to-hospitalizations ratio deserves particular attention, because it illustrates both the power and the limits of ecological surveillance. As a ratio computed from two independent national datasets, it cannot identify whether the infants who died were the same individuals who had been hospitalized, and it cannot distinguish between a condition becoming more lethal, patients arriving at hospitals sicker, or deaths occurring outside hospital settings entirely. The author is explicit on this point, noting that linked birth, hospital, and mortality records are needed to separate true changes in disease occurrence from shifts in referral patterns, diagnostic coding practices, and access to care. Ecuador, like many middle-income countries, has expanded health insurance coverage and hospital infrastructure over the past decade, and such expansions can plausibly increase recorded hospitalizations for conditions like respiratory distress simply because more newborns reach facilities where the diagnosis is made and coded.

Even with those caveats, the policy implications are difficult to ignore. The finding that respiratory distress dominates hospital days is essentially a statement about intensive care capacity: more than a million accumulated hospital days over thirteen years represents an enormous commitment of neonatal cots, ventilators, and skilled staff, and the upward trend in hospitalization rates suggests that this commitment will need to grow. Meanwhile, the rising mortality from birth asphyxia signals a different kind of intervention, one aimed upstream at labor wards, rural referral systems, and the training of birth attendants rather than at neonatal units. The study’s central conclusion, that distinct perinatal conditions generate different patterns of frequency, lethality, and resource use, amounts to an argument against managing infant health through a single aggregate indicator. A national infant mortality rate that appears stable or slowly improving could conceal a worsening asphyxia problem offset by gains elsewhere, and only condition-specific surveillance would reveal it.

The research also arrives at a moment of broader reflection in global health about the architecture of newborn survival programs. Worldwide, the leading causes of neonatal death, prematurity, birth asphyxia and trauma, and infection, have proven stubbornly resistant to interventions that succeeded against infectious diseases of later childhood. Ecuador’s experience, documented here with unusual completeness for the region, offers a case study in how middle-income health systems experience that resistance at the level of hospital wards and vital statistics registries. The absence of external funding for the work, and its foundation entirely in publicly available government data, underscore that the findings reflect the country’s own administrative record rather than a specially constructed research cohort.

For the scientific community, the study stands as a demonstration of how much can be extracted from routine data when the analytical methods are matched to the question. Segmented time-series analysis, negative binomial modeling, and burden estimation with disability-adjusted life years are not exotic techniques, but applying them coherently to thirteen years of national discharge data and six years of mortality data produced findings that no single-year report or aggregate mortality statistic could have surfaced. The author’s call for linked national surveillance, connecting birth registries, hospital discharges, and death certificates at the individual level, is the natural next step, and it would transform ratios like the 11.22 percent asphyxia figure from a population-level signal into a traceable clinical pathway. Until then, Ecuador’s neonatal wards, and the policymakers who fund them, now have a clearer map of where the burden lies: a rising tide of respiratory illness filling hospital beds, and a quieter but more lethal rise in birth asphyxia that demands attention where babies are born, not just where they are treated afterward.

Subject of Research: National trends in infant hospitalization, mortality, and health-service burden from four major perinatal conditions in Ecuador, 2012–2024

Article Title: National trends in hospitalization, mortality, and health-service burden from selected perinatal conditions among infants in Ecuador: a retrospective ecological time-series study, 2012–2024

Article References: González-Andrade, F. (2026). National trends in hospitalization, mortality, and health-service burden from selected perinatal conditions among infants in Ecuador: a retrospective ecological time-series study, 2012–2024. BMC Pediatrics. https://doi.org/10.1186/s12887-026-07780-9

Image Credits: AI Generated

DOI: 10.1186/s12887-026-07780-9

Keywords: infant mortality, hospital discharge, respiratory distress of newborn, birth asphyxia, neonatal sepsis, premature birth, low birth weight, Ecuador, time-series analysis, disability-adjusted life years, neonatology, health services research

The research team, led by Aysheshim Fentu Yeshalem of Jigjiga University’s Department of Pediatrics and Child Health, combed through the medical records of every preterm neonate admitted to the hospital’s neonatal intensive care unit over a two-year window running from February 9, 2024 to February 7, 2026. In total, 440 preterm babies were included in the analysis, a complete enumeration of admissions during the study period rather than a sample. By reconstructing each infant’s clinical course from admission to discharge or death, the investigators were able to calculate the overall mortality rate and, crucially, to identify which characteristics and treatments were statistically linked to survival.

The headline number is sobering: 30.3 percent of the preterm neonates died, with a 95 percent confidence interval of 25.9 to 34.8 percent. In practical terms, for every hundred premature babies wheeled into the unit, roughly thirty did not leave. Preterm birth is defined as delivery before thirty-seven completed weeks of gestation, and babies born early face a cascade of physiological challenges: their lungs may lack sufficient surfactant to stay inflated, their immune systems are immature, their skin is thin and loses heat rapidly, and their digestive systems often cannot coordinate sucking and swallowing. In high-resource settings, incubators, mechanical ventilation, and surfactant therapy have driven preterm mortality down dramatically. In settings like Jigjiga, where such technologies may be limited or unavailable, survival depends far more heavily on basic supportive care.

To untangle which factors mattered most, the researchers used binary logistic regression, a statistical technique that estimates the odds of an outcome, in this case death, while adjusting for the influence of other variables. They screened the candidate variables for multicollinearity, the phenomenon in which predictors overlap so heavily that their individual effects become impossible to separate, using the variance inflation factor, and found all values below four, comfortably under conventional thresholds of concern. They then checked whether the final model fit the observed data using the Hosmer-Lemeshow test, which returned a p-value of 0.53, indicating no significant departure between predicted and actual outcomes. Associations were considered statistically significant at a p-value below 0.05.

Three risk factors stood out as powerful predictors of death. The first was birth weight below 1,500 grams, the threshold clinicians call very low birth weight. Babies in this category faced roughly three times the odds of dying compared with heavier preterm infants, an adjusted odds ratio of 3.23. This makes biological sense: weight at birth is a composite proxy for gestational age, organ maturity, and nutritional reserves in utero, and the lightest babies have the least physiological buffer against complications such as respiratory distress, infection, and feeding intolerance.

The second major risk factor was a low Apgar score at five minutes of life. The Apgar score is a rapid assessment performed at one and five minutes after birth that rates a newborn’s appearance, pulse, grimace, activity, and respiration, each on a scale of zero to two, for a maximum of ten. A score below seven at five minutes signals that the baby has not transitioned smoothly to life outside the womb, often reflecting birth asphyxia or depressed physiological function. In the Jigjiga cohort, a five-minute Apgar below seven nearly quadrupled the odds of death, with an adjusted odds ratio of 4.09, making it the strongest intrinsic risk factor identified in the study.

The third and most striking risk factor was hypothermia during the hospital stay, which more than quintupled the odds of mortality, with an adjusted odds ratio of 5.09. Newborns, and especially preterm newborns, lose heat quickly because of their high surface-area-to-weight ratio, thin skin, and limited subcutaneous fat. Hypothermia is insidious because it worsens nearly every other problem a fragile infant faces: it impairs the ability to breathe, slows metabolism, increases the risk of hypoglycemia, and weakens immune defenses. The World Health Organization has long championed the so-called warm chain, a sequence of simple measures from immediate drying and skin-to-skin contact to delayed bathing and appropriate covering, precisely because maintaining a normal body temperature is one of the cheapest and most effective lifesaving measures in neonatal care.

Just as important as the risk factors, however, were the protective ones, and here the study delivers a genuinely hopeful message. Preterm babies who received kangaroo mother care, the practice of continuous skin-to-skin contact between mother and infant combined with frequent breastfeeding, had 83 percent lower odds of death, with an adjusted odds ratio of 0.17. Kangaroo mother care was pioneered in resource-limited settings and has since been validated in trials worldwide; for stable low-birth-weight babies it can match or exceed the survival benefits of conventional incubator care while also promoting breastfeeding, weight gain, and maternal bonding. Its strong protective association in Jigjiga reinforces calls to make the practice universal in neonatal units across the region.

Two other interventions were also linked to dramatically better survival. Babies who were resuscitated at birth had 72 percent lower odds of dying, an adjusted odds ratio of 0.28, a finding that highlights the life-or-death importance of having trained personnel and functioning resuscitation equipment in every delivery room. And infants who began feeding within twenty-four hours of birth had 81 percent lower odds of death, with an adjusted odds ratio of 0.19. Early feeding, ideally with the mother’s own milk, stabilizes blood sugar, protects the immature gut, reduces the risk of sepsis, and prevents the catabolic weight loss that can spiral into further complications. The fact that resuscitation, kangaroo care, and early feeding all emerged as independent protective factors suggests that the pathway to lower mortality in this setting runs not through expensive technology but through the disciplined, consistent delivery of care that is already known to work.

The authors conclude that mortality among preterm neonates at the hospital was high, and they call for proper labor follow-up, resuscitation at birth, prevention and treatment of hypothermia, kangaroo mother care, and early initiation of feeding to be implemented as standard practice. They also recommend prospective, multicenter studies to build on their findings, noting that a retrospective, single-center design has inherent limits: it can identify associations but cannot fully establish causation, and it reflects the experience of one hospital’s catchment population. Even so, the study fills an important evidence gap for Ethiopia’s Somali region and adds to a growing body of research showing that the global burden of preterm death is concentrated precisely where the simplest interventions are least consistently available. For the roughly one in ten babies born too soon worldwide, the difference between life and death, this study suggests, may come down to warmth, milk, and a pair of trained hands in the first minutes and days of life.

Subject of Research: Neonatal mortality and associated risk and protective factors among preterm neonates in eastern Ethiopia

Article Title: Neonatal mortality and associated factors among preterm neonates admitted to Jigjiga University Sheikh Hassan Yabare Comprehensive Specialized Hospital, Ethiopia: a retrospective cross-sectional study

Article References: Yeshalem, A. F., Alemu, H. G., Roble, A. K., Ahmed, M., Muse, A. I., Eshetu, B. G., Ma,alin, M. S., & Abdulahi, A. A. (2026). Neonatal mortality and associated factors among preterm neonates admitted to Jigjiga University Sheikh Hassan Yabare Comprehensive Specialized Hospital, Ethiopia: a retrospective cross-sectional study. BMC Pediatrics. https://doi.org/10.1186/s12887-026-07781-8

Image Credits: AI Generated

DOI: 10.1186/s12887-026-07781-8

Keywords: preterm birth, neonatal mortality, Ethiopia, kangaroo mother care, hypothermia, APGAR score, low birth weight, neonatal intensive care, early feeding, birth asphyxia, resuscitation, BMC Pediatrics

The study, led by Chelsea Hartman and Jeffrey Perlman of Weill Cornell Medicine-NewYork-Presbyterian Hospital together with colleagues at Kilimanjaro Christian Medical Centre (KCMC) in Moshi, Tanzania, set out with what the team calls a SMART aim: to reduce the rate of neonatal hypothermia by 50 percent and to raise the mean delivery room temperature of newborns by 0.6 degrees Celsius. The investigators also set out to explore whether reducing hypothermia would translate into lower early neonatal mortality, defined as death within the first seven days of life. The results exceeded the temperature goal by a wide margin, while the mortality findings delivered a more sobering lesson about the limits of single-intervention quality improvement.

The scale of the baseline problem is striking. Before any intervention, the mean neonatal temperature in the delivery room was 35.9 degrees Celsius, with a standard deviation of 0.24 degrees, well below the World Health Organization’s recommended threshold of at least 36.5 degrees Celsius. Ninety-nine percent of the newborns studied were hypothermic at birth. Sixty-six percent fell into the mild category, with temperatures between 36.0 and 36.4 degrees Celsius, while a full 33 percent were moderately hypothermic, with temperatures between 32.0 and 35.9 degrees Celsius. In other words, essentially every vulnerable baby born at the facility was losing heat faster than it could be replaced, and one in three was cold enough to face clinically significant risk.

Neonatal hypothermia is not a benign inconvenience. Newborns, and especially preterm and low-birth-weight infants, have a large surface-area-to-mass ratio, thin insulating fat layers, and immature mechanisms for generating heat, so they lose warmth rapidly through evaporation of amniotic fluid, conduction, convection, and radiation. Prior research, including systematic reviews and large cohort studies from Europe, Brazil, and South Asia, has linked admission hypothermia in very preterm infants to increased mortality, respiratory distress, and other morbidities. Studies in East Africa have repeatedly documented high prevalence, and a five-year review at Tanzanian centers underscored how gestational age, birth weight, and fetal heart rate abnormalities interact with thermal stress to shape early survival.

To attack the problem, the team applied the Model for Improvement, a widely used quality improvement framework built around iterative Plan-Do-Study-Act (PDSA) cycles. The study population consisted of neonates weighing less than 2000 grams at birth, the group at highest risk of rapid heat loss. Three sequential PDSA cycles were implemented, each refining the approach based on real-time audit data. The core interventions comprised three elements: a hypothermia prevention care bundle, in-person in-service training for delivery room staff, and a systematic audit implementation to track whether the bundle was actually being delivered as intended.

The care bundle drew on established thermal protection practices promoted by the World Health Organization and supported by randomized evidence. These include thorough drying immediately after birth to halt evaporative heat loss, delaying bathing, ensuring skin-to-skin contact where feasible, and the use of occlusive wrapping, approaches that trials in resource-poor settings have shown can meaningfully reduce heat loss even for term infants. Plastic barriers and wraps have proven particularly effective for preterm babies, and immediate kangaroo mother care has been shown in a landmark randomized trial to improve survival of low-birth-weight infants. The Tanzanian team’s contribution was not a novel technology but the disciplined packaging, teaching, and auditing of these known practices in a busy delivery room.

The impact was immediate and sustained. From the very first PDSA cycle onward, statistical process control charts showed a centerline shift in the mean delivery room neonatal temperature, rising from 35.9 degrees Celsius to 36.8 degrees Celsius, a gain of nearly a full degree that comfortably surpassed the 0.6-degree target. Simultaneously, the incidence of hypothermia shifted to 5.7 percent, and critically, all remaining cases were mild. Moderate hypothermia, which had affected a third of newborns at baseline, was eliminated entirely. In quality improvement terms, the intervention did not merely nudge the system; it moved the process to a new, stable level of performance that persisted across subsequent cycles.

The mortality data, however, tell a more complicated story. Despite the near-elimination of hypothermia at birth, early neonatal mortality rates, tracked as deaths within seven days, remained unchanged, with a control chart centerline of 12.3 percent throughout the initiative. The authors are careful and candid about this finding: because overall neonatal mortality did not fall, they conclude that there is insufficient evidence to support a causal relationship between hypothermia and early mortality in this setting. This does not mean hypothermia is harmless; rather, it reflects the reality that early deaths in this population are driven by multiple overlapping factors, including extreme prematurity, low birth weight, intrapartum complications, and fetal heart rate abnormalities, and that correcting one risk factor in isolation may not shift a composite outcome dominated by other forces.

The study nonetheless carries important lessons for the global effort to reduce newborn deaths, which still claims roughly four million lives annually by earlier estimates, with the majority occurring in low- and middle-income countries. Quality improvement initiatives in Ethiopia, India, Malaysia, and elsewhere have reported similar successes in reducing admission hypothermia using bundles, standardization, and PDSA methodology, and a Cochrane systematic review has concluded that interventions to prevent hypothermia at birth in preterm and low-birth-weight infants are effective. The Tanzanian experience adds a rigorous, chart-based demonstration that near-complete elimination of delivery room hypothermia is achievable with training, a defined bundle, and continuous audit, without expensive equipment.

For clinicians and program designers, the message is twofold. First, thermal protection is a solvable problem: a combination of drying, wrapping, warming the delivery environment, and staff engagement can move a facility from universal hypothermia to near-universal normothermia within a single improvement cycle. Second, measuring what matters requires patience and honesty; the unchanged mortality centerline is a reminder that quality improvement must be embedded in broader strategies addressing the many determinants of newborn survival. The work, funded in part by Bloomberg Philanthropies and carried out by midwives and physicians at KCMC alongside their American collaborators, stands as a template for how disciplined, data-driven care redesign can deliver dramatic physiological gains for the most vulnerable newborns, even where the ultimate outcome depends on conquering challenges far beyond the delivery room thermometer.

Subject of Research: A quality improvement initiative to reduce neonatal hypothermia at birth in Tanzania

Article Title: Reducing rates of neonatal hypothermia at birth in Tanzania: a quality improvement initiative

Article References: Hartman, C., Ngowi, E., Ahn, E., Shayo, A., Peter, N., Cypriane, J., Mlay, P., Tiwari, P., & Perlman, J. (2026). Reducing rates of neonatal hypothermia at birth in Tanzania: a quality improvement initiative. Journal of Perinatology. https://doi.org/10.1038/s41372-026-02904-6

Image Credits: AI Generated

DOI: 10.1038/s41372-026-02904-6

Keywords: neonatal hypothermia, quality improvement, Tanzania, delivery room, PDSA cycles, newborn thermoregulation, low birth weight, preterm infants, care bundle, Kilimanjaro Christian Medical Centre, neonatal mortality, Journal of Perinatology

The study, led by Fengxiang Qin, Xuemei Xu and Liangqin Mao with senior authors Guanghui Dong, Wu Jiang and Shun Liu, analyzed an extraordinary 194,284 mother-infant pairs drawn from Nanning, the capital of Guangxi in southern China, covering births between 2016 and 2022. That total included 97,142 sibling pairs, giving the researchers a uniquely powerful lens. The work was published in the journal Environmental Health as an open-access article, and it addresses three of the most closely watched adverse birth outcomes in public health: preterm birth, defined as delivery before 37 completed weeks of gestation; low birth weight; and small-for-gestational-age, or SGA, which describes infants whose weight falls below the tenth percentile for their gestational age and sex.

The methodological innovation at the heart of the study is the sibling-matched case-control design. Traditional studies of pollution and pregnancy compare unrelated mothers against one another, adjusting statistically for measured variables such as maternal age, income, or smoking status. But families differ in countless ways that researchers never capture: genetics, stable dietary patterns, housing quality, occupational exposures accumulated over decades, health behaviors, and access to care. When two such dissimilar groups are compared, any of these hidden differences can masquerade as a pollution effect. Sibling comparisons sidestep much of this problem. Because siblings share the same parents, largely the same genes, and the same household environment, comparing pregnancies within the same mother effectively holds the entire familial background constant, isolating the contribution of what changed between pregnancies, including ambient air quality.

Exposure assessment relied on the China High Air Pollutants dataset, known as CHAP, a high-resolution spatiotemporal product that estimates near-surface concentrations of multiple pollutants across China. The team examined six criteria pollutants: nitrogen dioxide, sulfur dioxide, carbon monoxide, ozone, and particulate matter, assigning each pregnancy trimester-specific exposure estimates based on where the mother lived. This trimester-resolved approach matters because fetal vulnerability is not uniform across gestation. The first trimester encompasses organogenesis and early placental development, the second involves rapid fetal growth, and the third sees the largest weight gain, so a pollutant that disrupts one window may leave another untouched.

Statistically, the researchers ran two parallel analyses on the same data. The first used a sibling-matched generalized linear mixed model, which estimates subject-specific conditional effects by comparing pregnancies within families. The second used conventional unmatched logistic regression, the workhorse of environmental epidemiology, which estimates population-averaged marginal effects across all unrelated subjects. The contrast between these two modeling frameworks proved to be one of the most revealing aspects of the entire investigation, because differences between their results reflect not only familial confounding but also inherent mathematical differences between conditional and marginal effect estimation.

The results were striking. In the sibling-matched analyses that control for unmeasured familial factors, first-trimester nitrogen dioxide exposure was associated with an increased risk of preterm birth, with an odds ratio of 1.004 per unit increase in exposure. Sulfur dioxide emerged as a consistent threat to fetal growth: exposure in the first, second and third trimesters each carried elevated odds of small-for-gestational-age birth, with odds ratios of 1.009, 1.009 and 1.010 respectively. Carbon monoxide showed even larger effects on fetal growth restriction, with second-trimester exposure yielding an odds ratio of 1.163 and third-trimester exposure an odds ratio of 1.157. These are associations measured at the population scale, where even modest per-unit odds ratios translate into substantial numbers of affected infants given how many pregnancies occur in polluted air every day.

Just as important as what survived sibling matching was what did not. Several associations that appeared robust in the conventional unmatched analysis, most notably links between carbon monoxide exposure across trimesters and preterm birth, attenuated to statistical non-significance once pregnancies were compared within families. The pattern of bias was not uniform: unmatched designs generally overestimated the associations between pollutants and preterm birth while underestimating the links between pollutants and SGA. The largest divergence between the two modeling approaches involved carbon monoxide, suggesting that this pollutant’s apparent effects are the most sensitive to how familial confounding and model structure are handled. For a field that has produced thousands of studies using unmatched designs, this is a sobering demonstration that the choice of statistical framework can materially change the scientific conclusion drawn from the same underlying data.

The biological plausibility of the surviving associations is well grounded. Nitrogen dioxide, a traffic-related pollutant, is a potent oxidant that drives systemic inflammation, and maternal inflammation is a recognized trigger of preterm labor through pathways involving prostaglandins and cytokines that can destabilize the fetal membranes. Sulfur dioxide, largely a byproduct of coal combustion and industrial activity, is associated with oxidative stress that can impair placental function, restricting the flow of oxygen and nutrients to the growing fetus and thereby promoting growth restriction. Carbon monoxide binds hemoglobin with an affinity more than two hundred times that of oxygen, forming carboxyhemoglobin and reducing the oxygen-carrying capacity of maternal blood; because the fetus is already at the hypoxic end of the oxygen delivery curve, even modest reductions in maternal oxygen content can compromise fetal growth, particularly during the second and third trimesters when oxygen demand peaks.

The authors are careful to note that the divergence between matched and unmatched results stems from two intertwined sources: genuine unmeasured familial confounding and the inherent mathematical differences between conditional and marginal statistical models. This dual explanation is a technical point with practical consequences. It means that researchers cannot simply assume that any discrepancy reflects confounding; part of it reflects the fact that odds ratios from conditional models and marginal models answer subtly different questions about risk. Disentangling these contributions is essential if environmental risk assessments are to produce effect estimates that regulators can trust when setting air quality standards.

The implications ripple outward from Nanning. Air pollution exposure during pregnancy is a global problem, with the World Health Organization estimating that the vast majority of the world’s population breathes air exceeding its guideline values, and the burden falls heaviest on low- and middle-income countries where coal combustion, traffic, and industrial emissions intersect with high fertility rates. If conventional studies have been overestimating some risks and underestimating others, then the benefit calculations underpinning air quality policy may need recalibration. The study’s authors argue that their findings underscore the critical need to control for familial confounders in environmental epidemiology and highlight the importance of methodological refinement in environmental risk assessment. In practical terms, that could mean more sibling-based and within-family designs, better exposure data at the individual level, and greater caution when translating population-averaged estimates into individual-level clinical advice. For expectant mothers, the actionable message remains consistent with longstanding public health guidance: reducing exposure to traffic exhaust, industrial emissions, and indoor combustion sources during pregnancy, particularly in the first trimester for nitrogen dioxide and in later trimesters for carbon monoxide and sulfur dioxide, remains a prudent strategy. And for the scientific community, the study stands as a reminder that in epidemiology, the design of a study can matter as much as the data it analyzes, and that the cleanest answers to environmental questions sometimes come from looking within families rather than across them.

Subject of Research: Prenatal air pollution exposure and adverse birth outcomes analyzed with a sibling-matched case-control design

Article Title: Associations between prenatal air pollution exposure and adverse birth outcomes: a siblings-matched case-control study

Article References: Qin, F., Xu, X., Mao, L., Huang, X., Wei, G., Lu, P., Chen, C., Chen, Y., Luo, D., Wang, B., Wang, X., Dong, G., Jiang, W., & Liu, S. (2026). Associations between prenatal air pollution exposure and adverse birth outcomes: a siblings-matched case-control study. Environmental Health. https://doi.org/10.1186/s12940-026-01336-1

Image Credits: AI Generated

DOI: 10.1186/s12940-026-01336-1

Keywords: air pollution, prenatal exposure, preterm birth, low birth weight, small for gestational age, sibling-matched design, nitrogen dioxide, sulfur dioxide, carbon monoxide, confounding factors, environmental epidemiology, birth outcomes