Browsing by Author "Li, Jing"

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    Does industrialization promote the emission mitigation agenda of East Africa? a pathway toward environmental sustainability
    (Frontiers Research Foundation, 2024-03) Yu, Yan Musah, Mohammed; Owusu-Akomeah, Michael; Nkyi, Joseph Akwasi; Li, Jing; Appiagyei Ampong, George Oppong; Kumah, Emmanuel Attah; Cao, Siqi; Xu, Yuxiang; Shi, Yingfang; Wang, Liqi; Hui, Can; Li, Kaodui
    One macroeconomic variable that has been proven to be a major driver of environmental quality in the world is industrialization. However, despite the numerous explorations on the connection between industrialization and ecological quality, limited studies have examined the linkage amidst the series in East Africa. This study was therefore conducted to help fill that gap. In accomplishing this goal, econometric techniques that control for cross-sectional correlations, heterogeneity and endogeneity among others, were engaged for the analysis. From the results, the panel under consideration was heterogeneous and cross-sectionally correlated. Also, the studied series were first differenced stationary and cointegrated in the long-run. The elasticities of the regressors were explored via the cross-sectionally augmented autoregressive distributed lag (CS-ARDL) estimator, cross-sectionally augmented distributed lag (CS-DL) estimator and the augmented mean group (AMG) estimator. From the results, industrialization reduced environmental quality in the region via high CO2 emissions. Also, financial development, foreign direct investments, urbanization and energy consumption were not environmentally friendly in the bloc. On the causal linkages amid the series, bidirectional causalities between industrialization and CO2 emissions; between energy consumption and CO2 secretions; and between foreign direct investments and CO2 exudates were detected. Finally, one-way causal movements from financial development and urbanization to the effluents of CO2 were unraveled. Based on the findings the study recommended among others that, national policies that can promote energy conservation at the industrial level, and can convert the industrial structure of the region to a low carbon-intensive one should be formulated.
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    PIERS Proteinuria: Relationship With Adverse Maternal and Perinatal Outcome
    (Journal of Obstetrics and Gynaecology, 2011) Payne, Beth; Magee, Laura A.; Côté, Anne-Marie; Hutcheon, Jennifer A.; Li, Jing; Kyle, Phillipa M.; Menzies, Jennifer M.; Moore, Peter; Parker, Claire; Pullar, Barbra; Dadelszen, Peter von; Walters, Barry N.
    To examine the ability of three different proteinuria assessment methods (urinary dipstick, spot urine protein:creatinine ratio [Pr/Cr], and 24-hour urine collection) to predict adverse pregnancy outcomes Methods: We performed a prospective multicentre cohort study, PIERS (Preeclampsia Integrated Estimate of RiSk), in seven academic tertiary maternity centres practising expectant management of preeclampsia remote from term in Canada, New Zealand, and Australia- Eligible women were those admitted with preeclampsia who had at least one antenatal proteinuria assessment by urinary dipstick, spot urine Pr/Cr ratio, and/or 24-hour urine collection Proteinuria assessment was done either visually at the bedside (by dipstick) or by hospital clinical laboratories for spot urine Pr/Cr and 24-hour urine collection- We calculated receiver operating characteristic area under the curve (95% CI) for each proteinuria method and each of the combined adverse maternal outcomes (within 48 hours) or adverse perinatal outcomes (at any time) Models with AUC ≥ 0-70 were considered of interest- Analyses were run for all women who had each type of proteinuria assessment and for a cohort of women (“ALL measures”) who had all three proteinuria assessments
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    A Risk Prediction Model for the Assessment and Triage of Women with Hypertensive Disorders of Pregnancy in Low-Resourced Settings: The miniPIERS (Pre-eclampsia Integrated Estimate of RiSk) Multi-country Prospective Cohort Study
    (PLOS Medicine, 2014-01) Payne, Beth A.; Hutcheon, Jennifer A.; Ansermino, J. Mark; Hall, David R.; Bhutta, Zulfiqar A.; Bhutta, Shereen Z.; Biryabarema, Christine; Grobman, William A.; Groen, Henk; Haniff{, Farizah; Li, Jing; Magee, Laura A.; Merialdi, Mario; Nakimuli, Annettee; Qu, Ziguang; Sikandar, Rozina; Sass, Nelson; Sawchuck, Diane; Steyn, D. Wilhelm; Widmer, Mariana; Zhou, Jian; Dadelszen, Peter von
    Background: Pre-eclampsia/eclampsia are leading causes of maternal mortality and morbidity, particularly in low- and middle- income countries (LMICs). We developed the miniPIERS risk prediction model to provide a simple, evidence-based tool to identify pregnant women in LMICs at increased risk of death or major hypertensive-related complications. Methods and Findings: From 1 July 2008 to 31 March 2012, in five LMICs, data were collected prospectively on 2,081 women with any hypertensive disorder of pregnancy admitted to a participating centre. Candidate predictors collected within 24 hours of admission were entered into a step-wise backward elimination logistic regression model to predict a composite adverse maternal outcome within 48 hours of admission. Model internal validation was accomplished by bootstrapping and external validation was completed using data from 1,300 women in the Pre-eclampsia Integrated Estimate of RiSk (fullPIERS) dataset. Predictive performance was assessed for calibration, discrimination, and stratification capacity. The final miniPIERS model included: parity (nulliparous versus multiparous); gestational age on admission; headache/visual disturbances; chest pain/dyspnoea; vaginal bleeding with abdominal pain; systolic blood pressure; and dipstick proteinuria. The miniPIERS model was well-calibrated and had an area under the receiver operating characteristic curve (AUC ROC) of 0.768 (95% CI 0.735–0.801) with an average optimism of 0.037. External validation AUC ROC was 0.713 (95% CI 0.658–0.768). A predicted probability $25% to define a positive test classified women with 85.5% accuracy. Limitations of this study include the composite outcome and the broad inclusion criteria of any hypertensive disorder of pregnancy. This broad approach was used to optimize model generalizability. Conclusions: The miniPIERS model shows reasonable ability to identify women at increased risk of adverse maternal outcomes associated with the hypertensive disorders of pregnancy. It could be used in LMICs to identify women who would benefit most from interventions such as magnesium sulphate, antihypertensives, or transportation to a higher level of care.