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Abstract El Niño Southern Oscillation (ENSO) has been shown to relate to the epidemiology of childhood infectious diseases, but evidence for whether they increase child deaths is limited. Here, we investigate the impact of mothers’ ENSO exposure during and prior to delivery on child mortality by constructing a retrospective cohort study in 38 low- and middle-income countries. We find that high levels of ENSO indices cumulated over 0–12 lagged months before delivery are associated with significant increases in risks of under-five mortality; with the hazard ratio ranging from 1.33 (95% confidence interval [CI], 1.26, 1.40) to 1.89 (95% CI, 1.78, 2.00). Child mortality risks are particularly related to maternal exposure to El Niño-like conditions in the 0th–1st and 6th–12th lagged months. The El Niño effects are larger in rural populations and those with unsafe sources of drinking water and less education. Thus, preventive interventions are particularly warranted for the socio-economically disadvantaged.

Oil palm contributes to various global needs as one of the most productive oil crops, but there exist ongoing concerns regarding its yield reductions and associated environmental impacts resulting from land conversion. This is the first detailed report investigating the nonlinear threats to estate-level oil palm yields posed by El Niño Southern Oscillation (ENSO) in the equatorial Pacific Ocean, a major driver of climate variability. Using the Malaysian Palm Oil Board administrative records on monthly performances reported by oil palm estates through the e-submissions portal spanning from January 2015 to June 2023, we focused on elucidating the impacts of ENSO on fresh fruit bunch yield, oil extraction rate, and oil yield. We found that both El Niño and La Niña conditions, characterized by extreme levels of ENSO indices cumulated over lags of 0–23 months prior to harvest, were associated with statistically significant reductions in yields. Lag association patterns unveiled that production risks were linked to pre-harvest exposure to extreme ENSO indices in various time windows. Subgroup analyses further revealed that the effects were pronounced in labor-intensive estates and those lacking fertilizer investments. This study underscores the necessity for adaptation strategies in response to future climate anomalies.

Town development, a crucial stage of urbanization, has been increasingly prioritized in recent sustainable socio-economic growth strategies. Vitality, especially the one measured by aggregate crowd behaviors, is widely recognized as a crucial development element. Conducting comprehensive assessments of the drivers of town vitality, particularly crowd vitality, is thus essential for addressing challenges and monitoring progress. This study examines representative towns in China and employs multiple datasets along with XGBoost-SHAP to investigate the mechanisms of development environment factors on aggregate crowd vitality. Key findings highlight the study’s novelty and broader implications: (1) The degree of industrial agglomeration is the most significant factor impacting the dependent measures, providing new data-driven insights into the role of economic clustering in town development. (2) Other indicators, such as the minimum distance to the town center, the enclosure, and car and pedestrian friendliness, can effectively predict town vitality, offering practical considerations for town planning. (3) Industrial innovation and diversification, rational planning of living circles, and enhancement of town conditions emerge as three crucial strategies for promoting urbanization. This study enhances empirical insights with strategies for addressing urbanization challenges, emphasizing how crowd data can be used to inform urbanization policies and planning practices, aiding urban planners in building more sustainable systems.

In the context of urban development, bridging the gap between urban regeneration and people’s demand for high-quality built environments is a current focus of research. Exploring the vitality of certain kinds of urban districts is imperative for comprehending human needs for specific built environments and fostering urban renaissance and advancement. This urgency arises from the prevailing lack of in-depth studies on district vitality, as current research primarily provides a general assessment of street vitality. Thus, this study aims to explore the correlations between indicators of urban vitality in cultural districts and built environments, using Haikou and Suzhou as case studies and employing multiple data sources (e.g., Baidu heat maps and nighttime light) and measurements. By applying a logit regression model, we find the following: (1) Traffic network integration has a positive impact on daytime vitality in Haikou and nighttime vitality in Suzhou, but it negatively affects nighttime vitality in Haikou. (2) In terms of nighttime vitality, both commercial density and greenery positively influence the overall blocks and various subgroups. (3) The proportion of cultural facilities in Suzhou has a detrimental effect on daytime vitality, especially for blocks with fewer permanent residents and lower land values. The present study, while limited to selected cultural blocks in Suzhou and Haikou, establishes the groundwork for a better comprehension of how spatial vitality can be enhanced at the street segment level, thereby contributing to the investigation of the varying impacts that built environment factors have on urban vitality in tourism cities at different stages of development. It uncovers the inherent latent characteristics found within cultural blocks across diverse regions and offers innovative perspectives and recommendations for optimizing the sustainable development of urban blocks.

OBJECTIVE: This longitudinal study aimed to measure precarious employment in the US using a multidimensional indicator. METHODS: We used data from the National Longitudinal Survey of Youth (1988–2016) and the Occupational Information Network database to create a longitudinal precarious employment score (PES) among 7568 employed individuals over 18 waves (N=101 290 observations). We identified 13 survey indicators to operationalize 7 dimensions of precarious employment, which we included in our PES (range: 0–7, with 7 indicating the most precarious): material rewards, working-time arrangements, stability, workers’ rights, collective organization, interpersonal relations, and training. Using generalized estimating equations, we estimated the mean PES and changes over time in the PES overall and by race/ethnicity, gender, education, income, and region. RESULTS: On average, the PES was 3.17 [standard deviation (SD) 1.19], and was higher among women (3.34, SD 1.20), people of color (Hispanics: 3.24, SD 1.23; non-Hispanic Blacks: 3.31, SD 1.23), those with less education (primary: 3.99, SD 1.07; high school: 3.43, SD 1.19), and with lower-incomes (3.84, SD 1.08), and those residing in the South (3.23, SD 1.17). From 1988 to 2016, the PES increased by 9% on average [0.29 points; 95% confidence interval (CI) 0.26–0.31]. While precarious employment increased over time across all subgroups, the increase was largest among males (0.35 points; 95% CI 0.33–0.39), higher-income (0.39 points; 95% CI 0.36–0.42) and college-educated (0.37 points; 95% CI 0.33–0.41) individuals. CONCLUSIONS: Long-term decreases in employment quality are widespread in the US. Women and those from racialized and less-educated populations remain disproportionately precariously employed; however, we observed the largest increases among men, college graduates and higher-income individuals.