scholarly journals Cohort Characteristics and Factors Associated With Cannabis Use Among Adolescents in Canada Using Pattern Discovery and Disentanglement Method

2021 ◽  
Author(s):  
Peiyuan Zhou ◽  
Andrew K.C. Wong ◽  
Yang Yang ◽  
Scott T. Leatherdale ◽  
Kate Battista ◽  
...  
Keyword(s):  
Population Health ◽  
Common Sense ◽  
Pattern Discovery ◽  
Health Data ◽  
Cannabis Use ◽  
Minority Class ◽  
Factors Associated ◽  
Special Cases ◽  
Significant Patterns ◽  
Imbalanced Class Distribution

Abstract Background: COMPASS is a longitudinal, prospective cohort study collecting data annually from students attending high school in jurisdictions across Canada. We aimed to discover significant frequent/rare associations of behavioral factors among Canadian adolescents related to cannabis use.Methods: We use a subset of the COMPASS dataset which contains 18,761 records of students in grades 9 to 12 with 31 selected features (attributes) involving various characteristics, from living habits to academic performance. We then used the Pattern Discovery and Disentanglement (PDD) algorithm to detect strong and rare (yet statistically significant) associations from the dataset.Results: Cohort characteristics and factors associated with cannabis use and other associations detected by PDD show consistent results with common sense and literature surveys. In addition, PDD outperformed methods using other criteria (i.e. support and confidence) popular as reported in the literature. Association results showed that PDD could discover: i) a smaller set of succinct significant associations in clusters; ii) frequent and rare, yet significant, patterns supported by population health relevant study; iii) patterns from a dataset with extremely imbalanced groups (majority class (None-user): minority class (Regular) = 88.3%: 11.7%). Conclusions: Results on the COMPASS dataset have validated PDD’s efficacy in discovering succinct interpretable frequent associations with comprehensive coverage and rare yet significant associations from datasets with extremely imbalanced class distribution without relying on any balancing process. The frequent associations show consistent results with common sense and literature surveys, while the rare patterns show very special cases. The success of PDD on this project indicates that PDD has great potential for population health data analysis.

scholarly journals Assessing and piloting interoperability for population health research

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
F Estupiñán-Romero ◽  
J Gonzalez-García ◽  
E Bernal-Delgado
Keyword(s):  
Case Studies ◽  
Population Health ◽  
Health Research ◽  
Network Architecture ◽  
Digital Health ◽  
Data Extraction ◽  
Health Data ◽  
Research Network ◽  
Technical Solution ◽  
Privacy And Security

Abstract Issue/problem Interoperability is paramount when reusing health data from multiple data sources and becomes vital when the scope is cross-national. We aimed at piloting interoperability solutions building on three case studies relevant to population health research. Interoperability lies on four pillars; so: a) Legal frame (i.e., compliance with the GDPR, privacy- and security-by-design, and ethical standards); b) Organizational structure (e.g., availability and access to digital health data and governance of health information systems); c) Semantic developments (e.g., existence of metadata, availability of standards, data quality issues, coherence between data models and research purposes); and, d) Technical environment (e.g., how well documented are data processes, which are the dependencies linked to software components or alignment to standards). Results We have developed a federated research network architecture with 10 hubs each from a different country. This architecture has implied: a) the design of the data model that address the research questions; b) developing, distributing and deploying scripts for data extraction, transformation and analysis; and, c) retrieving the shared results for comparison or pooled meta-analysis. Lessons The development of a federated architecture for population health research is a technical solution that allows full compliance with interoperability pillars. The deployment of this type of solution where data remain in house under the governance and legal requirements of the data owners, and scripts for data extraction and analysis are shared across hubs, requires the implementation of capacity building measures. Key messages Population health research will benefit from the development of federated architectures that provide solutions to interoperability challenges. Case studies conducted within InfAct are providing valuable lessons to advance the design of a future pan-European research infrastructure.

scholarly journals Factors Associated With Cannabis Use During the Reproductive Cycle: A Retrospective Cross-Sectional Study of Women in States With Recreational and Medical Cannabis Legalization

2021 ◽  
Author(s):  
Danica Loralyn Taylor ◽  
Janice F. Bell ◽  
Susan L. Adams ◽  
Christiana Drake
Keyword(s):  
Substance Use ◽  
Prenatal Care ◽  
Post Partum ◽  
Cannabis Use ◽  
Provider Education ◽  
Substance Use Prevention ◽  
Cross Sectional ◽  
Factors Associated ◽  
Adequacy Of Prenatal Care ◽  
The Impact

Abstract Introduction Passage of cannabis laws may impact cannabis use and the use of other substances. The suggested association is of particular concern in pregnant women where exposure to substances can cause harm to both the pregnant woman and fetus. The present study contributes to the minimal literature on factors associated with cannabis use during the preconception, prenatal, and postpartum periods including state legalization status, concurrent use of tobacco and e-cigarettes and adequacy of prenatal care. Methods We conducted a cross-sectional analysis using combined survey data from the 2016–2018 Pregnancy Risk Assessment Monitoring System (PRAMS) collected from 36,391 women. Logistic regression was used to estimate the impact of state-legalization, adequacy of prenatal care, and other substance use on cannabis use during the preconception, prenatal, and post-partum periods. Results In the preconception model, residence in a recreationally legal state (OR: 2.37; 95% CI, 2.04–2.75) or medically legal state (OR:3.32; 95% CI, 2.90–3.80) compared to a non-legal state was associated with higher odds of cannabis use. In the prenatal model, residence in a recreationally legal state was associated with higher odds of cannabis use (OR: 1.51; 95% CI, 1.29–1.79) whereas there was no association with residence in a medically legal state. Tobacco use including e-cigarettes and moderate prenatal alcohol use were also significantly associated with cannabis use. Conclusion Recreational cannabis legalization is associated with the use of cannabis prior to, during, and after pregnancy. Renewed clinical and policy efforts may be warranted to update prenatal substance use prevention programs, educational campaigns, and provider education as cannabis legalization evolves.

scholarly journals Estimating Health over Space and Time: A Review of Spatial Microsimulation Applied to Public Health

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 182-192
Author(s):  
Dianna M. Smith ◽  
Alison Heppenstall ◽  
Monique Campbell
Keyword(s):  
Population Health ◽  
Spatial Scales ◽  
Local Level ◽  
Health Data ◽  
Future Planning ◽  
Academic Researchers ◽  
Quality Health ◽  
Spatial Microsimulation ◽  
Dynamic Populations ◽  
Economic Studies

There is an ongoing demand for data on population health, for reasons of resource allocation, future planning and crucially to address inequalities in health between people and between populations. Although there are regular sources of data at coarse spatial scales, such as countries or large sub-national units such as states, there is often a lack of good quality health data at the local level. One method to develop reliable estimates of population health outcomes is spatial microsimulation, an approach that has its roots in economic studies. Here, we share a review of this method for estimating health in populations, explaining the different approaches available and examples where the method is applied successfully for creating both static and dynamic populations. Recent notable advances in the method that allow uncertainty to be represented are highlighted, along with the evolving approaches to validation that are an ongoing challenge in small-area estimation. The summary serves as a primer for academics new to the area of research as well as an overview for non-academic researchers who consider using these models for policy evaluations.

scholarly journals S101. CLINICAL FACTORS ASSOCIATED WITH CANNABIS USE IN A CHILEAN SAMPLE OF FIRST EPISODE PSYCHOSIS PATIENTS

2018 ◽  
Vol 44 (suppl_1) ◽  
pp. S364-S364
Author(s):  
Barbara Iruretagoyena ◽  
Nicolas Crossley ◽  
Alfonso Gonzalez-Valderrama ◽  
Cristian Mena ◽  
Carmen Castañeda ◽  
...  
Keyword(s):  
First Episode Psychosis ◽  
Cannabis Use ◽  
First Episode ◽  
Clinical Factors ◽  
Factors Associated ◽  
Episode Psychosis

scholarly journals Planting the S.E.E.D.S of Indigenous Population Health Data Linkage

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Robyn K Rowe ◽  
Jennifer D Walker
Keyword(s):  
Population Health ◽  
Indigenous Peoples ◽  
Health Care Policy ◽  
Indigenous Population ◽  
Data Linkage ◽  
Indigenous Health ◽  
Population Data ◽  
Health Data ◽  
Indigenous Populations ◽  
Data Stewardship

IntroductionThe increasing accessibility of data through digitization and linkage has resulted in Indigenous and allied individuals, scholars, practitioners, and data users recognizing a need to advance ways that assert Indigenous sovereignty and governance within data environments. Advances are being talked about around the world for how Indigenous data is collected, used, stored, shared, linked, and analysed. Objectives and ApproachDuring the International Population Data Linkage Network Conference in September of 2018, two sessions were hosted and led by international collaborators that focused on regional Indigenous health data linkage. Notes, discussions, and artistic contributions gathered from the conference led to collaborative efforts to highlight the common approaches to Indigenous data linkage, as discussed internationally. This presentation will share the braided culmination of these discussions and offer S.E.E.D.S as a set of guiding Indigenous data linkage principles. ResultsS.E.E.D.S emerges as a living and expanding set of guiding principles that: 1) prioritizes Indigenous Peoples’ right to Self-determination; 2) makes space for Indigenous Peoples to Exercise sovereignty; 3) adheres to Ethical protocols; 4) acknowledges and respects Data stewardship and governance, and; 5) works to Support reconciliation between Indigenous Peoples and settler states. S.E.E.D.S aims to centre and advance Indigenous-driven population data linkage and research while weaving together common global approaches to Indigenous data linkage. Conclusion / ImplicationsEach of the five elements of S.E.E.D.S interweave and need to be enacted together to create a positive Indigenous data linkage environment. When implemented together, the primary goals of the S.E.E.D.S Principles is to guide positive Indigenous population health data linkage in an effort to create more meaningful research approaches through improved Indigenous-based research processes. The implementation of these principles can, in turn, lead to better measurements of health progress that are critical to enhancing health care policy and improving health and wellness outcomes for Indigenous populations.

Monitoring the quality of maternity care: how well are labour and delivery events reported in population health data?

2009 ◽  
Vol 23 (2) ◽  
pp. 144-152 ◽  
Author(s):  
Christine L. Roberts ◽  
Jane C. Bell ◽  
Jane B. Ford ◽  
Jonathan M. Morris
Keyword(s):  
Population Health ◽  
Maternity Care ◽  
Health Data

Sociodemographic factors associated with food insecurity: data from the 2003–2014 New South Wales Population Health Survey

2020 ◽  
Vol 23 (11) ◽  
pp. 1857-1867
Author(s):  
Paraskevi Drakoulidou ◽  
Bradley Drayton ◽  
Leah Shepherd ◽  
Seema Mihrshahi
Keyword(s):  
Food Insecurity ◽  
Population Health ◽  
Health Survey ◽  
Smoking Status ◽  
New South ◽  
New South Wales ◽  
Sociodemographic Factors ◽  
Factors Associated ◽  
Self Rated Health ◽  
South Wales

AbstractObjective:To determine the prevalence and sociodemographic factors associated with food insecurity in the state of New South Wales (NSW), Australia.Design:Cross-sectional analysis of food insecurity data collected by the NSW Population Health Survey between 2003 and 2014. Multiple logistic regression was used to examine associations with key sociodemographic variables.Setting:NSW, Australia.Participants:212 608 survey participants responded to the food insecurity survey question between 2003 and 2014. 150 767 of them were aged ≥16 years. The survey sample was randomly selected and weighted to be representative of the NSW population.Results:On average 6 % of adults aged ≥16 years experienced food insecurity in NSW. The odds of food insecurity appeared to increase from one survey year to the next by a factor of 1·05. Food insecurity was found to be independently associated with age, sex, marital status, household size, education, employment status, household income, smoking status, alcohol intake and self-rated health. The association with income, smoking status and self-rated health appeared to be the strongest among all covariates and showed a gradient effect. Food insecurity appeared to increase significantly between the age of 16 and 19 years.Conclusions:The prevalence of food insecurity appears to be rising over time. Given the negative health consequences of food insecurity, more rigorous measurement and monitoring of food insecurity in NSW and nationally is strongly recommended. The findings provide support for interventions targeting low-income and younger population groups.

scholarly journals Association between maternal cannabis use and birth outcomes: an observational study

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Camilla A. Michalski ◽  
Rayjean J. Hung ◽  
Ryan A. Seeto ◽  
Cindy-Lee Dennis ◽  
Jennifer D. Brooks ◽  
...  
Keyword(s):  
Birth Outcomes ◽  
Gestational Age ◽  
Birth Outcome ◽  
Pain Medication ◽  
Outcome Data ◽  
Cannabis Use ◽  
Factors Associated ◽  
Cannabis Consumption ◽  
Pregnancy Status ◽  
Multivariable Adjustment

Abstract Background As cannabis consumption is increasing globally, including among pregnant women, there is a critical need to understand the effects of cannabis on fetal development and birth outcomes. We had two objectives: to determine 1) the factors associated with self-reported cannabis use in the pre/early-pregnancy period, and 2) whether cannabis use is associated with low birth weight, preterm birth, or small size for gestational age (GA) infants. Methods Maternal questionnaire and birth outcome data was gathered from 2229 women and 1778 singleton infants in the Ontario Birth Study, a hospital-based prospective cohort study (2013–2019). Women self-reported cannabis use within 3 months of learning their pregnancy status. Multivariable linear and logistic regression was conducted to 1) identify factors associated with cannabis use, and 2) determine the associations between cannabis use with the selected birth outcomes. Results Cannabis use increased in the cohort over time. Women who reported cannabis use (N = 216) were more likely to be younger and more likely to use alcohol, tobacco, and prescription pain medication, although most did not. These women had infants born at lower average birth weights and had 2.0 times the odds of being small for GA (95% confidence interval: 1.3, 3.3) after multivariable adjustment for socioeconomic factors and other substance use. Conclusion Our results suggest that women who use cannabis around the time of conception have higher odds of having infants that are small for gestational age. Targeted clinical messaging may be most applicable to women actively trying to conceive.

scholarly journals Are women with major depression in pregnancy identifiable in population health data?

2013 ◽  
Vol 13 (1) ◽  
Author(s):  
Lyn Colvin ◽  
Linda Slack-Smith ◽  
Fiona J Stanley ◽  
Carol Bower
Keyword(s):  
Major Depression ◽  
Population Health ◽  
Health Data ◽  
Depression In Pregnancy ◽  
In Pregnancy
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