Provincial Data Research Articles

Research on Medium- and Long-Term Hydropower Generation Forecasting Method Based on LSTM and Transformer

Hydropower generation is influenced by various factors such as precipitation, temperature, and installed capacity, with hydrometeorological factors exhibiting significant temporal variability. This study proposes a hydropower generation forecasting method based on Transformer and SE-Attention for different provinces. In the model, the outputs of the Transformer and SE-Attention modules are fed into an LSTM layer to capture long-term data dependencies. The SE-Attention module is reintroduced to enhance the model’s focus on important temporal features, and a linear layer maps the hidden state of the last time step to the final output. The proposed Transformer-LSTM-SE model was tested using provincial hydropower generation data from Yunnan, Sichuan, and Chongqing. The experimental results demonstrate that this model achieves high accuracy and stability in medium- and long-term hydropower forecasting at the provincial level, with an average accuracy improvement of 33.79% over the LSTM model and 24.30% over the Transformer-LSTM model.

Mortality after treatment of malignant pleural effusions with indwelling pleural catheters versus chemical pleurodesis: a population-based study.

Little is known about patient outcomes following treatment of malignant pleural effusions (MPE) in the real-world setting. We aimed to compare post-procedure all-cause mortality between individuals who received indwelling pleural catheter (IPC) insertion versus chemical pleurodesis for managing MPEs. We performed a retrospective population-based study using provincial health administrative data (Ontario, Canada) of adults with a MPE who underwent IPC insertion or chemical pleurodesis between 2015 and 2019. Individuals were followed until death or March 31, 2021. Difference in post-procedure mortality was calculated using inverse probability of treatment weighting (IPTW)-adjusted Cox proportional hazard regression analysis to balance potential confounders at baseline. We identified 4,790 (77.3%) individuals who received an IPC and 1,407 (22.7%) who had chemical pleurodesis for MPE. IPC insertions are increasing and chemical pleurodesis procedures are decreasing. The majority of IPCs were inserted in outpatients (61%), by pulmonologists (64.2%) and at sites with higher annual IPC volume, while chemical pleurodesis procedures were generally done by thoracic surgeons (74%) and at sites with higher annual pleurodesis volumes. In unadjusted comparison median time from initial cancer diagnosis to intervention was significantly longer in the IPC group (244 days, interquartile range [IQR]:33-903) compared to pleurodesis group (81 days, IQR:10-737; p < 0.0001). Unadjusted median time from index procedure to death was significantly longer in the pleurodesis group (165[IQR:48-457] days vs. 81[IQR:29-256] days, p < 0.0001), however the difference between groups became insignificant after the IPTW was applied (HR 1.27, 95%CI 0.95-1.69). 35% of IPCs were removed prior to death or end of follow-up. After adjusting for differences in baseline characteristics there was no difference in post-procedure mortality between IPC and chemical pleurodesis groups. In the real world, there are significant differences in the characteristics of patients who receive these two procedures and notable regional practice variation between procedure use. Future research should evaluate these variations in care and their effect on patient outcomes.

Abstract 4134957: Survival and Cardiac Recovery in Pediatric Dilated Cardiomyopathy: A Long-term Cohort Study of Risk Factors, Prognosis, and Health Outcomes Followed into Adulthood

Background: Dilated cardiomyopathy (DCM) is the most common cause of pediatric heart failure (HF), but there is limited literature on its long-term prognosis and treatment outcomes. We examined risk factors for long-term morbidity and mortality and outcomes of care in childhood-onset DCM. Methods: Electronic medical records from a tertiary care pediatric hospital (SickKids, Toronto, Canada) were used to retrospectively follow children ages 0–18 years with DCM from January 1, 2001 to July 1, 2017. Provincial healthcare administrative data was used to monitor outcomes recorded outside of SickKids, following patients during the same time period and into adulthood (age &gt;18 years) until August 31, 2023. We compared DCM cases, with or without echocardiographic recovery (LVEDD z score &lt; 2 and LVEF ≥ 55%), and controls matched on sex, age, and urban/rural residence on a range of health and health service outcomes. Primary outcomes included all-cause mortality, heart transplant (HT), and inpatient admission for HF. Among cases, Cox proportional hazards regression with backwards selection was used to identify demographic, disease, and treatment characteristics associated with each primary outcome, with candidate variables selected based on univariate analysis and clinical judgment. Results: We studied 156 patients with DCM and 780 controls for a median of 14.8 years. Median age at the end of follow-up was 16.2 years. Compared with controls, DCM cases had higher rates of all-cause death, HT, and HF admission (all P &lt;0.001), as well as chronic kidney disease ( P &lt;0.001) and diabetes ( P =0.002). Compared to cases with recovered DCM (n=53), non-recovered cases had higher rates of death, HT, and HF admission (all P &lt;0.001). On multivariable analysis, beta blockers were associated with reduced mortality risk (HR 0.343, 95% CI 0.162–0.727). Using any HF medication (HR 0.205, 95% CI 0.102–0.412) and living in an urban versus a rural area (HR 0.166, 95% CI 0.048–0.573) decreased HT risk. Idiopathic (HR 4.16, 95% CI 1.42–12.2) or sarcomeric mutation-related (HR 9.86, 95% CI 2.30–42.3) DCM were associated with higher HT risk than myocarditis-related DCM. Conclusions: While childhood DCM is associated with long-term adverse health and increased health care utilization, patients who recover have improved morbidity and mortality. Treatment (e.g. medication or access to urban specialist care) was associated with lower mortality and HT risk in DCM.

Research on the Impact of Environmental Inequality on Labor Mobility—A Study Based on the China General Social Survey (CGSS)

In recent years, as the capital-driven economic growth model gradually encounters bottlenecks and regional economic competition intensifies, governments at all levels have turned to attracting high-quality talent to promote economic transformation and upgrading. Against this backdrop, the quality of the ecological environment has gradually become an important factor affecting labor mobility. This paper explores the impact of environmental inequality on labor mobility by matching provincial and municipal data with micro-data from the Chinese General Social Survey (CGSS), especially focusing on how environmental inequality affects labor decision-making through cognitive and non-cognitive abilities. The results from the benchmark regression confirm that environmental inequality significantly suppresses labor mobility, while robustness tests further validate these findings. Additionally, the mediation mechanism analysis reveals that environmental inequality influences labor mobility through impairments in both cognitive and non-cognitive abilities. The study also conducts an analysis of the heterogeneity of different social groups, finding that environmental inequality has a particularly significant impact on groups with higher levels of education, property owners, and residents living in economically disadvantaged areas. Based on this, the paper puts forward policy recommendations for different groups, emphasizing the importance of optimizing environmental quality, improving education levels, and enhancing the social support system. The research conclusions provide theoretical support for local governments in enhancing regional competitiveness and attracting high-quality labor.

Carbon Footprint Accounting and Verification of Seven Major Urban Agglomerations in China Based on Dynamic Emission Factor Model

Amidst the prevailing trends in environmental conservation and the imperatives of energy conservation and emission reduction, the precision in assessing and forecasting carbon emissions has acquired heightened significance. The conventional emission factors, typically derived from historical data and empirical knowledge, often remain unchanged and fail to swiftly account for the reductions in emissions that are a consequence of technological advancements and green innovations. (1) This paper establishes a dynamic emission factor model, then uses city data and provincial data to verify the model, and compares the research results of other relevant researchers. The research results show that this method not only considers the different characteristics of energy types, but also considers regional differences and industry characteristics, making the emission factor more suitable for the actual situation. The results show that the method takes into account not only the different characteristics of energy types, but also regional differences and industry characteristics, making the emission factor more suitable for the actual situation. (2) This paper systematically compares the diverse methods for calculating the carbon footprints of Chinese provinces and cities. It encompasses a spectrum of methods, including carbon footprint accounting based on emission factors, accounting based on dynamically adjusted emission factors, and accounting from the perspective of carbon sinks. Each of these methods possesses its own set of applicable scenarios and inherent limitations. The emission factor method is apt for basic carbon emission accounting, while the adjusted emission factor method is tailored for scenarios where the evolution of technology and shifts in energy paradigms are pivotal. Concurrently, the carbon sink accounting framework is optimally suited for the evaluation of the carbon footprint within the realm of natural ecosystems.

A study of the enablers and barriers to the collection of sociodemographic data by public health units in Ontario, Canada during the COVID-19 pandemic

BackgroundCollection and use of sociodemographic data (SDD), including race, ethnicity and income, are foundational to understanding health inequities. Ontario’s public health units collected SDD as part of COVID-19 case management and vaccination activities. This research aimed to identify enablers and barriers to collecting SDD during COVID-19 case management and vaccination.MethodsAs part of a larger mixed-method research study [1], qualitative methods were used to identify enablers and barriers to SDD collection during the COVID-19 pandemic. Purposive sampling was used to recruit participants from Ontario’s 34 public health units. Sixteen focus groups and eight interviews were conducted virtually using Zoom. Interview data were transcribed and analyzed using inductive and deductive qualitative description.ResultsSDD collection enablers included: legally mandating SDD collection and having dedicated data systems, technological and legal supports, senior management championing SDD collection, establishing rapport and trust between staff and clients, and gaining insight from the experiences from local communities and other jurisdictions. Identified barriers to SDD collection included: provincial data systems being perceived as lacking user-friendliness, SDD collection “was not a priority,” time and other constraints on building staff and client rapport, and perceived discomfort with asking and answering personal SDD questions.ConclusionA combination of provincial and local organizational strategies including supportive data systems, training, and frameworks for data collection and use, are needed to normalize and scale up SDD collection by local health units beyond the context of the COVID-19 pandemic.

Impact of Digital Villages on Agricultural Green Growth Based on Empirical Analysis of Chinese Provincial Data

The construction of digital villages has progressed in tandem with the transformation of traditional production methods, offering new perspectives for agricultural green growth and sustainable development. This study employs the entropy value method alongside the super-efficient global SBM (Slacks-Based Measure) mixed function model, which assesses efficiency by accounting for both inputs and outputs, thereby facilitating a comprehensive evaluation of agricultural green growth. This methodology facilitates the examination of the correlation between digital villages and agricultural green growth, as well as the influence of digital villages on this growth. Furthermore, the utilization of financial resources is employed as a mediating variable to elucidate the mechanism of action. The utilization of green finance and agricultural insurance can be facilitated by the establishment of digital villages, and that has been shown to promote agricultural green growth. Additionally, the promotion of agricultural green growth by digital village construction is stronger in middle-altitude regions, non-grain-producing regions, and regions where the digital literacy of the rural labor force is higher than average, as well as areas where the use of agricultural film is higher than average. Accelerating the construction of digital villages and promoting the utilization of rural financial resources while adapting the digital village development to local conditions are crucial for effectively fostering agricultural green growth and sustainable agricultural development.

Higher Education Investment, Human Capital Level, and High-Quality Economic Development: Evidence from Chinese Provincial Data

While extensive research has examined economic growth in China, the complex relationship between knowledge-based inputs and comprehensive development remains poorly understood, particularly at the provincial level. Previous studies have largely focused on traditional economic indicators, overlooking how education investment and human capital collectively shape multidimensional development outcomes across China's diverse regions. To address this gap, we construct a novel development index incorporating innovation, sustainability, and social progress metrics, analyzing panel data from 31 Chinese provinces (2000-2020) through two-way fixed effects models with instrumental variables. Our findings reveal that higher education investment significantly enhances comprehensive development, with this effect amplified in regions with greater human capital accumulation. Notably, regional heterogeneity analysis demonstrates stronger investment effectiveness in eastern provinces compared to central regions, while western provinces show no significant relationship. These results underscore the importance of regionally differentiated approaches to educational investment and human capital development, offering valuable insights for policymakers seeking to promote balanced growth across China's economically diverse landscape.

Assessing the impact of three emission (3E) parameters on environmental quality in Canada: A provincial data analysis using the quantiles via moments approach

ABSTRACT Existing studies rarely examine the simultaneous effects of three emitting indicators (3E) – full emitting non-renewable, non-emitting renewable, and low-emitting nuclear - on three specific greenhouse gases: CO2, CH4, and N2O. We investigate the impact of three energy types on environmental quality, using Canadian data from 1990-2022. It incorporates macroeconomic policies, economic uncertainty, geopolitical risks, and eco-innovation, and employs the quantiles via moments method to explore the evolving relationships among these factors, considering provincial variances. Findings reveal that non-renewable energy sources deteriorate environmental quality by increasing CO2, CH4, and N2O emissions across all quantiles (from q.5 to q.95), while renewable and nuclear energies, along with eco-innovation initiatives, have a beneficial effect by reducing greenhouse gas emissions across all quantiles. Economic policy uncertainty is a contributing factor to greenhouse gas emissions across all quantiles, whereas geopolitical risks primarily impact the middle to upper quantiles (from q.50 to q.95). To counteract the lack of cross-sectional dependence in the quantiles via moments methodology, this paper employs Driscoll and Kraay’s standard errors approach to fortify its findings’ reliability. It concludes with policy suggestions promoting renewable energy and eco-innovation through increased investment, vibrant long-term policies, provincial collaboration, and adoption of green technologies.

Effects of Land and Labor Costs Growth on Agricultural Product Prices and Farmers’ Income

Widespread attention has been paid to the continuous rounds of rising agricultural product prices in China since 2003. During this period, rising prices were affected by input costs and international market prices; therefore, the degree of benefits obtained by farmers from the rise in agricultural product prices has been questioned. However, limited studies have examined the effect and relationship between rising agricultural product prices and farmers’ income. The purpose of the study was to provide empirical evidence on how the rise in agricultural product prices affects farmers’ income and to understand the role of land and labor costs in this context using provincial data from 2003 to 2020. The findings reveal that there is a threshold effect on the impact of the rise in agricultural product prices on farmers’ income. A moderate rise in agricultural product prices can increase farmers’ income, but excessive price increases have an insignificant effect. The causes behind the price rise significantly influence farmers’ income. An increase attributed to higher land and labor costs can improve farmers’ income, whereas a rise driven by international market prices or the cost of agricultural production inputs is unlikely to benefit farmers.

Can the digital economy empower the transportation sector to improve green total factor productivity?

The digital economy has the potential to facilitate digitization and green transformation within the transportation sector, but further research is warranted on how it can enhance the sector’s green total factor productivity (GTFP). Utilizing provincial data from China spanning 2013 to 2021, this study investigates the impact of the digital economy on the transportation sector’s GTFP. The findings are as follows: (1) The transportation sector exhibits a U-shaped relationship between the digital economy and GTFP. The inflection point of the U-shaped curve is at 0.441, with 81.11% of the samples falling to the left of this point. It is primarily through technological progress and innovation, rather than changes in technological efficiency, that the digital economy influences the improvement of GTFP. (2) The U-shaped relationship exhibits heterogeneity and varies depending on the mode and content of transportation. The U-shaped relationship is more pronounced in regions with lower total traffic volume on highways and railways or higher traffic volume on waterways. For transportation content, DEEI and GTFP show a significant U-shaped relationship in areas with high traffic volumes of passengers and freights. (3) Government intervention can attenuate the U-shaped relationship, which leads to a flatter curve. The market-driven level has the capability to strengthen the U-shaped relationship, resulting in a steeper curve. In conclusion, these findings contribute to deeper insights into the U-shaped relationship between the digital economy and GTFP, offering valuable guidance for policymakers seeking to improve GTFP in the transportation sector.

Do environmental crimes contribute to air pollution? Empirical evidence and effects on health

AbstractThis paper investigates the effect of environmental crimes on ambient air pollution in Italy, using annual provincial data over the period 2010–2016. While the impact of ambient air pollution on health has been the focus of a significant amount of literature, a nascent body of works is focusing on the impact of illegal behavior on environmental quality. Our work is ideally divided in two steps: firstly, we identify and assess empirically the potential correlation between environmental crimes and four different kinds of ambient air pollution. Secondly, we identify the health impacts that may be triggered by environmentally harmful illegal activities, through their impact on ambient air pollution, by linking them to existing contributions. Our findings suggest that the existence of such an “indirect” link may indeed be confirmed. We find that higher levels of PM2.5, PM10, and O3 concentration are associated with higher levels of environmental crimes related to forest fires and landscape violations (except for PM10 in the latter case), while NO2 concentration is not significantly associated with any environmental crime. On the other hand, we also find non-linearities in the estimated correlations. We conclude our analysis by providing a straightforward quantification of health-related impacts of ambient air pollution changes potentially triggered by criminal environmental behaviors. We hope that our findings could contribute to a more accurate evaluation of environmental crime impacts and, subsequently, inform future criminal environmental enforcement and environmental policies.

Greenhouse gas emissions and mitigation potential of crop production in Northeast China

Agricultural management practices that reduce greenhouse gas (GHG) emissions have been identified as effective mitigation strategies. However, research on carbon emissions from major crops in Northeast China focuses on national and provincial data, overlooking city-scale variability and uncertainties, which prevents fine-scale assessment of crop emissions reduction potential. To address this, a life cycle assessment (LCA) combined with the Monte Carlo method was conducted to estimate the carbon footprint of rice, maize, and soybean production for different cities in Northeast China from 1991 to 2020. The results showed that the top one-third of cities with the highest total carbon emissions (TCE) account for approximately 40 % of the region's TCE. Nitrogen losses and production processes related to nitrogen fertilizer application were identified as the primary contributors to TCE from crop production, accounting for 29.6–62.5 % of the total, with a relative importance of 58.5–78.2 %. Scenario analysis indicated that optimizing nitrogen fertilizer management and reducing active nitrogen losses are the most effective strategies for reducing TCE from major crop production, offering a reduction potential of 34.5–60.6 %. Recommended strategies include phased application of nitrogen fertilizer, the addition of nitrification inhibitors, or using slow-release nitrogen fertilizers, combined with appropriate increases in crop planting density, straw return decomposition technologies and water-saving irrigation methods to reduce GHG emissions. These strategies aim to achieve low-carbon sustainable grain production and provide a foundation for exploring the emissions reduction potential of agricultural inputs and optimizing regional crop layouts, offering new insights for developing more effective GHG reduction strategies.

Capturing the Asymmetrical Effect of Macroeconomic Factors on Public-Sector Innovation in Chinese Local Government: A Dynamic Technology Forecasting Approach

Despite the considerable investments in Chinese public sector innovation in China and its social impact, there is insufficient information on how asymmetries in macroeconomic factors and business cycles affect public sector innovation. Based on provincial data from thirty regions (2000–2016), the study proposes a dynamic model to capture the asymmetrical impact of macroeconomic factors on local government innovation. The innovation-based predictive model indicated that a positive shock to macro-economic factors (i.e., gross domestic product, government administration expenditures, provincial degree of openness in economies, provincial degree of openness in society, higher education research and development expenditures, local revenue, and local expenditure) upsurge government innovation. In contrast, a negative shock to these factors disrupts local government innovation. Third, the model indicated a pro-cyclical relationship between positive and negative shocks to government administration expenditures and provincial government innovation during the boom and recession periods. The study offers an essential policy tool and some important implications for local government officials, future researchers, and policymakers to understand how cyclic and asymmetric behavior in local government innovation shapes the innovation efficiency of the public sector in China. Subject Classification Codes: O30, O31, O32, 01, O38, O36, O35, O38, P25, Q01, H72.

Characteristics of walk-in clinic physicians and patients in Ontario: Cross-sectional study.

To describe family physicians who primarily practise in a walk-in clinic setting and compare them with family physicians who provide longitudinal care. A cross-sectional study that linked results from a 2019 physician survey to provincial administrative health care data in Ontario. The characteristics, practice patterns, and patients of physicians primarily working in a walk-in clinic setting were compared with those of family physicians providing longitudinal care. Ontario. Physicians who primarily worked in a walk-in clinic setting in 2019, as indicated by an annual physician survey. Physician demographic and practice characteristics, as well as their patients' demographic and health care utilization characteristics, were reported according to whether the physician was a walk-in clinic physician or a family physician who provided longitudinal care. Compared with the 9137 family physicians providing longitudinal care, the 597 physicians who self-identified as practising primarily in walk-in clinics were more frequently male (67% vs 49%) and more likely to speak a language other than English or French (43% vs 32%). Walk-in clinic physicians tended to have more encounters with patients who were younger (mean 37 vs 47 years), who had lower levels of prior health care utilization (15% vs 19% in highest band), who resided in large urban areas (87% vs 77%), and who lived in highly ethnically diverse neighbourhoods (45% vs 35%). Walk-in clinic physicians tended to have more encounters with unattached patients (33% vs 17%) and with patients attached to another physician outside their group (54% vs 18%). Physicians who primarily work in walk-in clinics saw many patients from historically underserved groups and many patients who were attached to another family physician.

How One Community Exercise Program for People Living With Cancer Impacted Health Care Utilization

In Brief Survival rates for patients with cancer have increased, meaning more patients are living with the effects of their disease and treatment. Initiatives to enhance the long-term quality of life are critically needed. Exercise is known to help with short-term outcomes, but less is known about long-term outcomes. This retrospective study based on administrative data included a total of 203 patients with cancer who participated in a 12-week supervised, community-based exercise program, called Stay Strong; it was offered as an adjunctive therapy during the first 5 years of their cancer journey. The main objectives were to investigate the number of hospitalizations, the length of hospital stays, and the number of physician service claims up to 2 years following the program, and to compare that data to a control group. Participants were matched using provincial administrative data based on sex, age (+ 5 years old), and admissions to the hospital (+ 2) in the year prior to the program. Over the 2-year follow-up period, patients with cancer who participated in Stay Strong had a significant reduction in hospital admissions, shorter length of hospital stays, and a reduced number of physician service claims compared with the control group. These findings suggest that there are potential benefits of participating in a community-based exercise program during a patient's cancer journey for both the patient and the health care system.

Officials' Social Networks and Local Indebtedness - A Study Based on Provincial Data

This paper takes the average annual growth of indebtedness of provincial party secretaries and the places where they serve from 2006 to 2017, and aims to investigate whether the social network of officials significantly affects the indebtedness of places. This paper adopts the linear regression method and establishes a unique evaluation system of officials' social networks. It is finally found that officials' social networks have a significant impact on the indebtedness of local governments. At the same time, the provincial officials' tenure, during which the growth of the indebtedness of other provincial governments also significantly affects the indebtedness of that provincial government.

Indonesian SDGS Problems: Technical Inefficiency Due to Economic Crime and Income Inequality

Objective: The study objective is investigating the technical inefficiency resulted from economic crime and its association with income inequality, with the study aims are modeling a stochastic frontier aggregate production function, measuring inefficiency, and mapping the economic inefficiency due to economic crime with income inequality association. Theoretical Framework: The main concepts are Crime Economics, Stochastic Frontier Analysis, and Aggregate Production Function. Method: The methodology comprises a stochastic frontier aggregate production function modelling to calculate technical inefficiency due to economic crime and mapping technical inefficiency due to economic crime with income inequality association. The data is Indonesian provincial data from 2016 to 2019 provided by Indonesian Statistics. Results and Discussion: The modelling reveals that aggregate production stochastic frontier is established and technical inefficiency due to economic crime is calculated. The mapping shows that some provinces experience positive association between technical inefficiency due to economic crime with income inequality. Research Implications: This study implies the importance of concerning theoritically and practically to technical inefficiency due to economic crime and its association with income inequality. These implication can encompass economic, social, and security sectors. Originality/Value: This study contributes to the literature by modeling the stochastic frontier aggregate production function that accommodates economic crime, measuring technical inefficiency due to economic crime, and mapping the technical inefficiency due to the economic crime with income inequality association. The relevance and value of this research are evidenced by SDGs components such as decent work and economic growth, reduced inequalities, and peace, justice, and strong institutions.

Foreign waste ban and green development of Chinese manufacturing industry: Comprehensive evidence based on provincial data

Since the reform and opening up, imported solid wastes have pushed China's economic growth while also bringing about serious environmental problems. In this context, China has introduced a ban on “foreign waste” for imported solid waste. Based on the provincial panel data from 2010 to 2020, this paper calculates the Green Total Factor Productivity (GTFP) of the manufacturing industry to measure the level of green development of the manufacturing sector, and evaluates the comprehensive impact of the “foreign waste” ban on the green development of the manufacturing industry by using the continuous Difference-in-Differences method. The study finds that the foreign waste ban greatly promotes the greening of China's manufacturing sector, mechanism analysis shows that foreign waste ban stimulates innovation by innovation effects and increases production cost by cost effects, and the policy effect has heterogeneity as it is more prominent in coastal areas, areas with a lower proportion or a higher level of green development. This result suggests that the promotion of domestic solid waste recycling should be accompanied by further guidance on efficient factor mobility, with different measures based on regional heterogeneity.

Population perinatal substance use and an environmental scan of health services in British Columbia, Canada

BackgroundSubstance use during pregnancy is underreported globally and there is limited data on its prevalence and the availability of supportive services. This study determined population perinatal substance use in British Columbia (BC) by region and examined the availability of clinical and community-based programs. MethodsUsing linked provincial health administrative data, we conducted a population-based retrospective cohort study including all BC residents accessing care for substance use (alcohol, opioids, stimulants, sedatives, and cannabis) within 12 months of first perinatal care record to delivery during 2016–2021. We also conducted an environmental scan to identify all programs offering perinatal care and substance use treatment/support in BC as of December 2022 and described program components by region. ResultsThe population included 12,439 people with perinatal substance use with 13,814 linked livebirths during the study period. The incidence rate of perinatal substance use was nearly eight times higher in rural/remote Northern BC compared to the metropolitan Vancouver Coastal region (1044.2 vs. 131.3 per 100,000 population, respectively). We identified 29 related services (19 wrap-around programs, 8 supportive housing, and only 2 acute care programs). Residents outside of Metro Vancouver accounted for 60 % (N=1745) of people with perinatal substance use; however, these regions represented only 35 % of BC’s specialized acute care and supportive housing beds (N=140). ConclusionsExpanding supports for perinatal substance use - particularly acute care and supportive housing within more rural/remote regions in BC - will be critical to address geographic inequities in access to perinatal care and improve health outcomes for pregnant people who use substances and their infants.