Types of diabetes during pregnancy and risk of depression and anxiety in offspring from childhood to young adulthood.

AIMS: To assess maternal pre-existing type 1 diabetes (T1D), type 2 diabetes (T2D), gestational diabetes mellitus (GDM) during pregnancy and risk of depression and anxiety from childhood to young adulthood in offspring. MATERIALS AND METHODS: This birth cohort included singletons born during 1995-2015, followed using electronic medical records through 2020. Cox regression was used to estimate hazard ratio (HR) of depression or anxiety diagnosis during follow-up associated with in-utero exposure to maternal diabetes. RESULTS: Among 439 590 offspring, 29 891 (6.8%) had depression and 51 918 (11.8%) had anxiety. T1D, followed by T2D and GDM requiring antidiabetes medication were associated with risk of depression and anxiety in offspring. Compared with no diabetes during pregnancy, the adjusted HRs (95% confidence interval) of depression in offspring associated with T1D, T2D or GDM requiring medications were 1.44 (1.09-1.91), 1.30 (1.15-1.47) and 1.18 (1.11-1.26) respectively; conversely, HRs were 0.97 (0.82-1.15) for T2D and 0.99 (0.94-1.04) for GDM without medications. The associations with anxiety followed similar patterns. The significant associations were observed for offspring ages 5-12 and >12-18 years and attenuated for 18-25 years. CONCLUSION: These data suggest that the severity of diabetes (T1D vs. T2D requiring medications vs. GDM requiring medications) during pregnancy may increase the vulnerability of offspring for depression or anxiety.

Powerful tool or too powerful? Early public discourse about ChatGPT across 4 million tweets.

BACKGROUND: This paper investigates initial exuberance and emotions surrounding ChatGPT's first three months of launch (1 December 2022-1 March 2023). The impetus for studying active discussions surrounding its implications, fears, and opinions is motivated by its nascent popularity and potential to disrupt existing professions; compounded by its significance as a crucial inflexion point in history. Capturing the public zeitgeist on new innovations-much like the advent of the printing press, radio, newspapers, or the internet-provides a retrospective overview of public sentiments, common themes, and issues. OBJECTIVES: Since launch, few big data studies delved into initial public discourse surrounding the chatbot. This report firstly identifies highest-engagement issues and themes that generated the most interaction; secondly, identifies the highest-engaged keywords on both sides of the sentiment valence scale (positive and negative) associated with ChatGPT. METHODS: We interrogate a large twitter corpus (n = 4,251,662) of all publicly available English-language tweets containing the ChatGPT keyword. Our first research aim utilizes a prominent peaks model (upper-quartile significance threshold of prominence>20,000). Our second research aim utilized sentiment analysis to identify, week-on-week, highest-frequency negative, and positive keywords and emojis. RESULTS: Six prominent peaks were identified with the following themes: 'hype and hesitance', 'utility and misuse in professional and academic settings', 'demographic bias', 'philosophical thought experiments on morality' and 'artificial intelligence as a mirror of human knowledge'. Of high-frequency valence, negativity included credibility concerns, implicit bias, environmental ethics, employment rights of data annotators and programmers, the ethicality of neural network datasets. Positivity included excitement over application, especially in coding, as a creative tool, education, and personal productivity. CONCLUSIONS: Overall, sentiments and themes were double-edged, expressing excitement over this powerful new tool and wariness toward its potential for misuse.

News media coverage of LGBT identities over 10 years in a 400-million-word corpus.

BACKGROUND: This study is the first to analyze LGBT portrayals in a news media dataset over a decade (2010-2020). We selected Singapore as a country of interest, emblematic of a nation grappling with state-encouraged heteronormativity and a remnant colonial law against homosexuality (377A), fraught with calls for its repeal that was only enacted in 2022. Our study is interested in this period bookended by challenge and change, particularly in newspaper portrayals of LGBT narratives. Newspapers are an important source of current information and have the power to shape societal perceptions. We lay the groundwork and provide a framework to analyze news media narratives of other Commonwealth nations with colonial pasts and inherited laws criminalizing LGBT communities. OBJECTIVES: This study analyzes LGBT portrayals in a 400-million-word news media dataset over a decade (2010-2020). First, we aimed to track the volume of LGBT media coverage over time and elucidate differences in coverage of different identity markers. Second, we aimed to track sentiments on LGBT portrayals. Third, we aimed to track salient narratives circulated about LGBT stories. METHODS: The study leveraged a 400-million-word corpus from news media in Singapore, identifying the following target keywords: LGBT, Lesbian, Gay, Bisexual, Transgender, Pink Dot (a local Pride event), 377A. First, coverage volume was tracked using annual changes in keyword mentions per million, elucidating differences in coverage of different sub-groups. Second, sentiment analysis on a valence scale was conducted on LGBT collocates. Third, we distilled salient narratives about LGBT identities using thematic labelling of top-frequency collocates. RESULTS: First, overall coverage of LGBT steadily increased over the decade, though Gay identities evidenced asymmetrical coverage-outstripping 'Bisexual' keywords by seven times, 'Lesbian' by four, 'Transgender' by two. Second, sentiment scores for Pink Dot (a local pride event) were most positive; Lesbian, Gay, LGBT, Transgender were neutral; Bisexual and 377A dipped slightly negative. Third, topics differed across the four identities: uniquely, 'Lesbian' collocates related to sensationalized cinema; 'Gay' about hate crimes; 'Bisexual' about population surveys; 'Transgender' about challenges (transitioning, alienation, suicide). CONCLUSIONS: Practically, we presented a decade-long barometer of LGBT sentiments and themes on a national level, providing a framework to analyze media for more effective communication strategies-applicable to Commonwealth countries with similar inherited colonial laws. Salient repetition through media association may unwittingly frame certain issues negatively; caution is prudent in representing each sub-group adequately, rather than portraying the LGBT identity as monolithic.

Trends in the Prevalence of Autism Spectrum Disorder in California: Disparities by Sociodemographic Factors and Region Between 1990-2018.

Autism Spectrum Disorders (ASD) prevalence has risen globally, with regional variation and sociodemographic disparities affecting diagnosis and intervention. This study examines ASD trends from 1990 to 2018 in California (CA), focusing on sociodemographic factors that may inform policy/interventions. Using CA Department of Public Health birth records (1990-2018) and Developmental Services ASD cases (1994-2022), we analyzed diagnosis incidence by age 4 or 8, stratified by sociodemographic and regional factors. From 1990 to 2018, for each birth year the cumulative incidence of ASD by 4 and 8 years of age in CA increased while the diagnosis age decreased. Distinct patterns emerged over these three decades. Children born to White and Asian and Pacific Islander (API) mothers, or to mothers with higher education or living in high socioeconomic status (SES) neighborhoods exhibited higher ASD cumulative incidences throughout the 1990s and early 2000s. However, in the mid-2000s, ASD incidence in children born to Black or Hispanic mothers, with low education, or living in low SES neighborhoods surpassed that of White/API children or those living in high SES neighborhoods. Black or Hispanic children now have the highest ASD cumulative incidence, even though age at first diagnosis remains lowest in high SES regions, for the highly educated, and for White/API children. ASD cumulative incidence in CA from 1990 to 2018 exhibited demographic reversals with higher rates in children born to Black or Hispanic mothers or lower SES neighborhoods. Black and Hispanic children still have delayed age at diagnosis compared to White/API children.

Exposure to gestational diabetes mellitus in utero impacts hippocampal functional connectivity in response to food cues in children.

Objectives: Intrauterine exposure to gestational diabetes mellitus (GDM) increases the risk of obesity in the offspring, but little is known about the underlying neural mechanisms. The hippocampus is crucial for food intake regulation and is vulnerable to the effects of obesity. The purpose of the study was to investigate whether GDM exposure affects hippocampal functional connectivity during exposure to food cues using functional magnetic resonance imaging. Methods: Participants were 90 children age 7-11 years (53 females) who underwent an fMRI-based visual food cue task in the fasted state. Hippocampal functional connectivity (FC) was examined using generalized psychophysiological interaction in response to high-calorie food versus non-food cues. Food-cue induced hippocampal FC was compared between children with and without GDM exposure, while controlling for possible confounding effects of age, sex and waist-to-hip ratio. Results: Children with GDM exposure exhibited stronger hippocampal FC to the insula and striatum (i.e., putamen, pallidum and nucleus accumbens) compared to unexposed children, while viewing high caloric food cues. Conclusions: Intrauterine exposure to GDM was associated with higher food-cue induced hippocampal FC to reward processing regions. Future studies with longitudinal measurements are needed to clarify whether increased hippocampal FC to reward processing regions may raise the risk of the development of metabolic diseases later in life.

Preeclampsia Onset, Days to Delivery, and Autism Spectrum Disorders in Offspring: Clinical Birth Cohort Study.

BACKGROUND: Maternal preeclampsia is associated with a risk of autism spectrum disorders (ASD) in offspring. However, it is unknown whether the increased ASD risk associated with preeclampsia is due to preeclampsia onset or clinical management of preeclampsia after onset, as clinical expectant management of preeclampsia allows pregnant women with this complication to remain pregnant for potentially weeks depending on the onset and severity. Identifying the risk associated with preeclampsia onset and exposure provides evidence to support the care of high-risk pregnancies and reduce adverse effects on offspring. OBJECTIVE: This study aimed to fill the knowledge gap by assessing the ASD risk in children associated with the gestational age of preeclampsia onset and the number of days from preeclampsia onset to delivery. METHODS: This retrospective population-based clinical cohort study included 364,588 mother-child pairs of singleton births between 2001 and 2014 in a large integrated health care system in Southern California. Maternal social demographic and pregnancy health data, as well as ASD diagnosis in children by the age of 5 years, were extracted from electronic medical records. Cox regression models were used to assess hazard ratios (HRs) of ASD risk in children associated with gestational age of the first occurrence of preeclampsia and the number of days from first occurrence to delivery. RESULTS: Preeclampsia occurred in 16,205 (4.4%) out of 364,588 pregnancies; among the 16,205 pregnancies, 2727 (16.8%) first occurred at <34 weeks gestation, 4466 (27.6%) first occurred between 34 and 37 weeks, and 9012 (55.6%) first occurred at ≥37 weeks. Median days from preeclampsia onset to delivery were 4 (IQR 2,16) days, 1 (IQR 1,3) day, and 1 (IQR 0,1) day for those first occurring at <34, 34-37, and ≥37 weeks, respectively. Early preeclampsia onset was associated with greater ASD risk (P=.003); HRs were 1.62 (95% CI 1.33-1.98), 1.43 (95% CI 1.20-1.69), and 1.23 (95% CI 1.08-1.41), respectively, for onset at <34, 34-37, and ≥37 weeks, relative to the unexposed group. Within the preeclampsia group, the number of days from preeclampsia onset to delivery was not associated with ASD risk in children; the HR was 0.995 (95% CI 0.986-1.004) after adjusting for gestational age of preeclampsia onset. CONCLUSIONS: Preeclampsia during pregnancy was associated with ASD risk in children, and the risk was greater with earlier onset. However, the number of days from first preeclampsia onset to delivery was not associated with ASD risk in children. Our study suggests that ASD risk in children associated with preeclampsia is not increased by expectant management of preeclampsia in standard clinical practice. Our results emphasize the need to identify effective approaches to preventing the onset of preeclampsia, especially during early pregnancy. Further research is needed to confirm if this finding applies across different populations and clinical settings.

Associations between brake and tire wear-related PM2.5 metal components, particulate oxidative stress potential, and autism spectrum disorder in Southern California.

BACKGROUND: Air pollution is a global health concern, with fine particulate matter (PM2.5) constituents posing potential risks to human health, including children's neurodevelopment. Here we investigated associations between exposure during pregnancy and infancy to specific traffic-related PM2.5 components with Autism Spectrum Disorder (ASD) diagnosis. METHODS: For exposure assessment, we estimated PM2.5 components related to traffic exposure (Barium [Ba] as a marker of brake dust and Zinc [Zn] as a tire wear marker, Black Carbon [BC]) and oxidative stress potential (OSP) markers (Hydroxyl Radical [OPOH] formation, Dithiothreitol activity [OPDTT], reactive oxygen species [ROS]) modeled with land use regression with co-kriging based on an intensive air monitoring campaign. We assigned exposures to a cohort of 444,651 children born in Southern California between 2016 and 2019, among whom 11,466 ASD cases were diagnosed between 2018 and 2022, Odds ratios (ORs) and 95% confidence intervals (CIs) were obtained with logistic regression for single pollutant and PM2.5 mass co-adjusted models, also adjusting for sociodemographic characteristics. RESULTS: Among PM2.5 components, we found the strongest positive association with ASD for our brake wear marker Ba (ORper IQR = 1.29, 95 % CI: 1.24, 1.34). This was followed by an increased risk for all PM2.5 oxidative stress potential markers; the strongest association was with ROS formation (ORper IQR = 1.22, 95 % CI: 1.18, 1.25). PM2.5 mass was linked to ASD in Hispanic and Black children, but not White children, while traffic-related PM2.5 and OSP markers increased ASD risk across all groups. In neighborhoods with the lowest socioeconomic status (SES), associations with ASD were stronger for all examined pollutants compared to higher SES areas. CONCLUSIONS: Our findings suggest that brake wear-related PM2.5 and PM2.5 OSP are associated with ASD diagnosis in Southern California. These results suggest that strategies aimed at reducing the public health impacts of PM2.5 need to consider specific sources.