Paediatric and perinatal epidemiology最新文献

Background: Severe maternal morbidity (SMM) and its racial and ethnic inequities are the result of a mixture of risk factors ranging from clinical comorbidities to socio-economic contexts. One under-explored dimension is neighbourhood contexts.

Objectives: In order to understand the impact of neighbourhood contexts on SMM, this study investigates the relationship between a 20-year history of neighbourhood poverty and SMM among 8.6 million births in California from 2000 to 2018 and assesses effect measure modification by race/ethnicity and nativity.

Methods: Data include hospital live births in California from 2000 to 2018 from the California Department of Public Health. The final sample for this study consisted of 8,632,436 live births. Mixed-effects logistic regression models accounting for area-level clustering were used to compare the odds of SMM across neighbourhood poverty histories, adjusting for sociodemographic and pregnancy-related factors and comorbidities.

Results: The prevalence of SMM was 1.2%. In fully adjusted models, neighbourhoods with persistent high poverty had 32% higher odds of SMM (OR 1.32, 95% confidence interval [CI] 1.28, 1.37), and those with persistent moderate poverty had 9% higher odds (OR 1.09, 95% CI 1.06, 1.12), compared to neighbourhoods with a persistent low poverty history. The odds of SMM were also higher in neighbourhoods with increasing poverty; 23% higher for early increase (OR 1.23, 95% CI 1.19, 1.27) and 13% higher for late increase (OR 1.13, 95% CI 1.09, 1.16). In contrast, neighbourhoods with early decreasing poverty had 11% lower odds of SMM (OR 0.89, 95% CI 0.84, 0.94) compared to persistent lowpoverty neighbourhoods.

Conclusions: The findings indicate that persistent high poverty in neighbourhoods is associated with higher odds of SMM, independent of individual sociodemographic and clinical factors. The strongest associations were found among Asian, Hispanic, Pacific Islander and white birthing people. These results underscore the significance of neighbourhood poverty histories and their impact on maternal health.

Background: The few studies that have examined the impact of PM_2.5 on reduced birthweight across different percentiles of the conditional birthweight distribution have produced equivocal findings, and only two assessed whether these associations varied by race/ethnicity or by racial/ethnic composition of the neighbourhood where mothers lived.

Objective: We evaluated racial/ethnic differences in the association between prenatal PM_2.5 exposure and birthweight across the birthweight distribution in a retrospective cohort study comprising 102,986 full-term singleton births in Harris County, Texas (2019-2020).

Methods: Census tract-level daily PM_2.5 concentrations were estimated using 'XGBoost-IDW Synthesis', and averaged exposures over pregnancy. Neighbourhood racial/ethnic composition was defined by whether ≥ 50% (i.e., majority) of non-Hispanic white residents lived in a census tract. Quantile regression models, adjusted for covariates, were applied to examine changes in birthweight [ $\hat{\beta }$ and 95% confidence interval (CI)] associated with an interquartile range increase in ambient air levels of PM_2.5 at selected percentiles of the conditional birthweight distribution. Stratified analyses explored differential associations by maternal race/ethnicity and neighbourhood racial/ethnic composition.

Results: An inverted hook pattern was observed in the associations between prenatal PM_2.5 exposure and reduced birthweight, with the strongest among infants born at the lowest ( $\hat{\beta }$  = -14 g, 95% CI: -20, -8; 10th percentile) and highest ( $\hat{\beta }$  = -11 g, 95% CI: -19, -4; 90th percentile) percentiles of the birthweight distribution, and a weaker association at the 75th percentile. In stratified analyses, the strongest association at the lowest percentile was observed among infants of Hispanic mothers or those living in neighbourhoods with less than a majority of non-Hispanic white residents.

Conclusions: This study provides evidence that associations of prenatal PM_2.5 exposure with reductions in birthweight varied among infants at the lowest, middle and highest percentiles of the conditional birthweight distribution; further, these associations varied by maternal race/ethnicity and neighbourhood racial/ethnic composition.

Background: Studies of child mortality that employ minimally invasive tissue sampling (MITS) produce highly accurate cause of death data; however, selection bias may render these as non-representative of their underlying populations.

Objectives: Estimate cause-specific mortality fractions and rates for the five most frequent causes-underlying and others in the chain of events leading to death-among stillbirths, neonatal, infant and child deaths-in Sub-Saharan Africa and South Asia, adjusted for any identified selection biases.

Methods: The Child Health and Mortality Prevention Surveillance (CHAMPS) Network collects standardised, population-based, longitudinal data on causes of death among stillbirths and under-five children in 12 catchments in seven countries in Sub-Saharan Africa and South Asia. Cause-specific mortality fractions and rates were calculated for the five most frequent causes among stillbirths, neonatal, infant and child deaths, and for the five most frequent maternal conditions among perinatal deaths; all estimates were subsequently adjusted for selection bias. Selection probabilities were estimated from membership in subgroups defined by factors hypothesised to affect selection.

Results: In 2017-2020, of 10,122 deaths ascertained, 5847 (57.8%) were enrolled in CHAMPS and 2654 (26.2%) additionally consented to MITS. Estimates were calculated for 265 and 65 site/age-specific causes of death and maternal conditions, respectively; five (1.9%) and four (6.2%) required adjustment, respectively, but they did not meaningfully change. Estimates were calculated for 34 site-specific causes of death among all stillbirths and under-five deaths combined; 28 (82.4%) required adjustment (all included age at death), and change-in-estimates demonstrated considerable variability.

Conclusions: Selection bias is not a concern in the CHAMPS Network. Deaths where MITS were performed accurately represent the distribution of causes of death in their respective target populations, specifically when stratified by age or adjusted accordingly. Future studies of child mortality that employ MITS should consider adjusting for age at death for their measures of frequency.

Background: Anaemia during pregnancy is common and increases the risk of adverse perinatal outcomes. Epidemiologic research on anaemia during pregnancy largely relies on International Classification of Diseases, Clinical Modification, 10th Revision (ICD-10) diagnosis codes, despite limited evidence on their validity.

Objective: Our objective was to assess the validity of ICD-10 codes against haemoglobin and haematocrit values in identifying anaemia during pregnancy.

Methods: We utilised the Merative™ MarketScan® Commercial Database, a national database of commercial insurance claims with laboratory values during 2018-2022. We included pregnancies with ≥ 1 haemoglobin or haematocrit value measured during pregnancy and excluded pregnancies with a hereditary anaemia diagnosis code. We used established criteria to define anaemia and assessed the validity of the diagnosis codes against laboratory values by calculating Cohen's kappa, sensitivity, specificity, and positive and negative predictive value.

Results: Among 71,160 pregnancies, concordance between anaemia identified through laboratory values and ICD-10 codes was 0.258 (95% confidence interval [CI]: 0.248, 0.268), sensitivity was 0.300 (95% CI: 0.294, 0.307), specificity was 0.918 (95% CI: 0.916, 0.921), positive predictive value was 0.551 (95% CI: 0.541, 0.561), and negative predictive value was 0.797 (95% CI: 0.794, 0.801).

Conclusions: We found in a nationwide commercial claims database with measured laboratory values that ICD-10 diagnosis codes for antepartum anaemia have low sensitivity and high specificity. Researchers should be cautious when using ICD-10 codes alone to identify antepartum anaemia and should consider bias analyses to reduce misclassification error.

Background: Lower respiratory infections (LRI) are a leading cause of death among children aged 0 to 14 globally. LRI burden estimates remain incomplete, especially in resource-limited settings.

Objective: To assess the global, regional, and national burden of LRI in children, analyse trends in incidence, mortality, and disability-adjusted life-years (DALYs), and predict future burden projections from 2022 to 2035, exploring variations in major bacterial pathogens.

Methods: This study utilises data from the 2021 Global Burden of Disease Study to analyse child LRI burden across 204 countries and regions. It assesses incidence, mortality, and DALYs, employing refined methods and forecasting future burdens using the Bayesian Age-Period-Cohort (BAPC) model, while examining variations in major bacterial pathogens affecting children's health.

Results: From 1990 to 2021, global child LRI incidence declined from 144.6 million infections to 69.9 million (estimated annual percentage change [EAPC] -2.4). Deaths fell from 2,033,975 to 1,271,013, with a mortality rate decline from 117 to 27.1 per 100,000 (EAPC -4.0). DALYs decreased from 180.7 million to 48.4 million, with the rate dropping from 10,389.6 to 2403.9 per 100,000 (EAPC -4.0). Western sub-Saharan Africa and South Asia reported the highest burdens, while East Asia showed the most reductions. Low- and middle-income countries faced greater burdens than high-income nations. Streptococcus pneumoniae remained the leading cause of LRI-related deaths in 2021. Projections indicate a further marked decline in child LRI deaths and age-standardised mortality rates globally by 2035, with under five mortality rates expected to remain the highest.

Conclusions: Despite reductions in LRI burden, it continues to threaten child health, particularly in resource-limited settings. Effective public health interventions and vaccination efforts are essential, with future research needed on evolving trends of bacterial pathogens to enhance child health outcomes.

Background: Approximately 20% of pregnancies end in spontaneous loss, an outcome associated with adverse health consequences. Statistically stable estimates of the risk of pregnancy loss are limited for nonmetropolitan populations due to small sample sizes.

Objectives: This study evaluated the utility of the enhanced Modified Kalman Filter (eMKF) in producing estimates of the risk of pregnancy loss for subgroups of US women with small sample sizes to examine recent trends.

Methods: Data from the National Survey of Family Growth (NSFG; 2006-2019) were used to estimate trends in the risk of self-reported pregnancy loss (miscarriage, stillbirth, ectopic pregnancy) among US women (15-44 years) who reported at least one completed pregnancy (excluding induced abortions) conceived during 2000-2018 (n = 17,314 women, 35,988 pregnancies) by metropolitan status and maternal age. The eMKF was used to smooth estimates over groups and time. We compared the relative 95% confidence intervals (95% CIs) of model-based estimates to direct estimates to assess improvements in precision.

Results: Among completed pregnancies conceived during 2000-2018, 21.6% ended in pregnancy loss. Relative 95% CIs for model-based estimates were 33.0% and 53.0% smaller for metropolitan and nonmetropolitan groups, respectively, than direct estimates. After adjustment, the risk of pregnancy loss for women ages 15-44 increased by a relative 1% annually for both metropolitan (risk ratio [RR] 1.01, 95% CI 1.01, 1.02) and nonmetropolitan (RR 1.01, 95% CI 1.00, 1.01) women. The risk of pregnancy loss increased for metropolitan women ages 15-19 (RR 1.01, 95% CI 1.00, 1.01), 20-24 (RR 1.01, 95% CI 1.00, 1.01), 25-29 (RR 1.02, 95% CI 1.01, 1.02), and 30-34 (RR 1.02, 95% CI 1.01, 1.03).

Conclusions: Risk of pregnancy loss increased by a relative 1% annually for women overall, and by 1%-2% annually among subgroups of women ages 15-34 in metropolitan areas. The eMKF provided improvements in estimate precision relative to direct estimates.