Breast cancer, alcohol, and phosphate toxicity.

Alcohol consumption is associated with an increased risk of breast cancer, even at low alcohol intake levels, but public awareness of the breast cancer risk associated with alcohol intake is low. Furthermore, the causative mechanisms underlying alcohol's association with breast cancer are unknown. The present theoretical paper uses a modified grounded theory method to review the research literature and propose that alcohol's association with breast cancer is mediated by phosphate toxicity, the accumulation of excess inorganic phosphate in body tissue. Serum levels of inorganic phosphate are regulated through a network of hormones released from the bone, kidneys, parathyroid glands, and intestines. Alcohol burdens renal function, which may disturb the regulation of inorganic phosphate, impair phosphate excretion, and increase phosphate toxicity. In addition to causing cellular dehydration, alcohol is an etiologic factor in nontraumatic rhabdomyolysis, which ruptures cell membranes and releases inorganic phosphate into the serum, leading to hyperphosphatemia. Phosphate toxicity is also associated with tumorigenesis, as high levels of inorganic phosphate within the tumor microenvironment activate cell signaling pathways and promote cancer cell growth. Furthermore, phosphate toxicity potentially links cancer and kidney disease in onco-nephrology. Insights into the mediating role of phosphate toxicity may lead to future research and interventions that raise public health awareness of breast cancer risk and alcohol consumption.

Using random forest to identify correlates of depression symptoms among adolescents.

PURPOSE: Adolescent depression is a significant public health concern, and studying its multifaceted factors using traditional methods possess challenges. This study employs random forest (RF) algorithms to determine factors predicting adolescent depression scores. METHODS: This study utilized self-reported survey data from 56,008 Canadian students (grades 7-12) attending 182 schools during the 2021/22 academic year. RF algorithms were applied to identify the correlates of (i) depression scores (CESD-R-10) and (ii) presence of clinically relevant depression (CESD-R-10 ≥ 10). RESULTS: RF achieved a 71% explained variance, accurately predicting depression scores within a 3.40 unit margin. The top 10 correlates identified by RF included other measures of mental health (anxiety symptoms, flourishing, emotional dysregulation), home life (excessive parental expectations, happy home life, ability to talk to family), school connectedness, sleep duration, and gender. In predicting clinically relevant depression, the algorithm showed 84% accuracy, 0.89 sensitivity, and 0.79 AUROC, aligning closely with the correlates identified for depression score. CONCLUSION: This study highlights RF's utility in identifying important correlates of adolescent depressive symptoms. RF's natural hierarchy offers an advantage over traditional methods. The findings underscore the importance and additional potential of sleep health promotion and school belonging initiatives in preventing adolescent depression.

The Conceptual Framework for the International Food Policy Study: Evaluating the Population-Level Impact of Food Policy.

An unhealthy diet is among the leading global causes of death and disability. Globally, a range of policies are being implemented to support healthy food choices at a population level, including novel polices in the areas of food marketing, nutrition labeling, and taxation of less healthy foods. There is a need to evaluate and inform the implementation of these policies, including their impacts on marginalized population subgroups. The International Food Policy Study (IFPS) consists of repeated cross-sectional surveys conducted in 5 high- and upper-middle-income countries: Australia, Canada, Mexico, the United Kingdom, and the United States. In each country, approximately 4000 adults and 1200 children and youth (aged 10-17) were recruited from a global commercial panel to complete an online survey using consistent measures and methodologies across countries. The first annual IFPS surveys were conducted in 2017 with adults; annual surveys for young people aged 10-17 were launched in 2019 in the same countries, as well as in Chile. The design of the IFPS surveys creates a framework for evaluating "natural experiments" in food policies, including comparisons over time within countries implementing the policy and comparisons with countries in which the policy was not implemented. IFPS surveys have 3 primary areas of focus: 1) knowledge, attitudes, and beliefs associated with specific policies; 2) diet-related behaviors; and 3) dietary intake, including 24-hour dietary recalls for adults in 4 of the 5 countries. Surveys also assess food insecurity, income adequacy, sex and gender, race/ethnicity, and a range of other measures to assess trends among priority subgroups. Overall, the IFPS project has the potential to address important gaps in national monitoring surveys for dietary patterns, and to evaluate the impacts of novel food policies implemented in any of the 5 countries over the study period.

Elevated C-Peptides, Abdominal Obesity, and Abnormal Adipokine Profile are Associated With Higher Gleason Scores in Prostate Cancer.

BACKGROUND: Prostate cancer development is associated with numerous lifestyle factors (i.e., physical activity, nutrition intake) and metabolic perturbations. These factors have been studied independently; here, we used an integrative approach to characterize these lifestyle and metabolic parameters in men undergoing diagnostic prostate biopsies. METHODS: We prospectively evaluated 51 consecutive men for body composition, metabolic factors including glucose- and lipid-related measures, as well as lifestyle factors prior to prostate biopsy. Evaluations were performed in a blinded manner and were subsequently related to biopsy outcomes for: (i) presence or absence of cancer; and (ii) where cancer was present, Gleason score. RESULTS: Serum C-peptide concentrations were significantly greater in participants with Gleason scores ≥4 + 3 (2.8 ± 1.1 ng/ml) compared to those with Gleason 3 + 3 (1.4 ± 0.6 ng/ml) or Gleason 3 + 4 (1.3 ± 0.8 ng/ml, P = 0.002), suggesting greater insulin secretion despite lack of differences in fasting glucose concentrations. Central adiposity, measured by waist circumference, was significantly greater in participants with Gleason ≥4 + 3 (110.1 ± 7.4 cm) compared to those with Gleason 3 + 4 (102.0 ± 9.5 cm, P = 0.028). Men with Gleason ≥4 + 3 also had significantly greater leptin concentrations than those with lower Gleason scores (Gleason ≥4 + 3: 15.6 ± 3.3 ng/ml vs. Gleason 3 + 4: 8.1 ± 8.1 ng/ml, P < 0.05) and leptin:adiponectin ratio (Gleason ≥4 + 3: 9.7 ± 6.1 AU, Gleason 3 + 4: 2.9 ± 3.2, Gleason 3 + 3: 2.4 ± 2.1 AU, P = 0.013). CONCLUSIONS: We profiled a cluster of obesity-related metabolic perturbations (C-peptide, central adiposity, leptin, and leptin:adiponectin ratios) which may associate with more aggressive prostate cancer histology. Prostate 77:211-221, 2017. © 2016 Wiley Periodicals, Inc.

Clustering of risk-related modifiable behaviours and their association with overweight and obesity among a large sample of youth in the COMPASS study.

BACKGROUND: Canadian youth exhibit a number of risky behaviours, some of which are associated with overweight and obesity. The purpose of this study was to examine the prevalence of 15 modifiable risk behaviours in a large sample of Canadian youth, to identify underlying subgroups based on patterns of health behaviours, and to examine the association between identified subgroups and overweight/obesity. METHODS: Data from 18,587 grades 9-12 students in Year 1 (2012-13) of the COMPASS study and latent class analysis were used to identify patterns and clustering among 15 health behaviours (e.g., physical inactivity, sedentary behaviour, unhealthy eating, substance use). A logistic regression model examined the associations between these clusters and overweight/obesity status. RESULTS: Four distinct classes were identified: traditional school athletes, inactive screenagers, health conscious, and moderately active substance users. Each behavioural cluster demonstrated a distinct pattern of behaviours, some with a greater number of risk factors than others. Traditional school athletes (odds ratio (OR) 1.15, 95% CI 1.03-1.29), inactive screenagers (OR 1.33; 1.19-1.48), and moderately active substance users (OR 1.27; 1.14-1.43) were all significantly more likely to be overweight/obese compared to the health conscious group. CONCLUSIONS: Four distinct subpopulations of youth were identified based on their patterns of health and risk behaviours. The three clusters demonstrating poorer health behaviour were all at an increased risk of being overweight/obese compared to their somewhat healthier peers. Obesity-related public health interventions and health promotion efforts might be more effective if consideration is given to population segments with certain behavioural patterns, targeting subgroups at greatest risk of overweight or obesity.

Errors, Omissions, and Outliers in Hourly Vital Signs Measurements in Intensive Care.

OBJECTIVE: To empirically examine the prevalence of errors, omissions, and outliers in hourly vital signs recorded in the ICU. DESIGN: Retrospective analysis of vital signs measurements from a large-scale clinical data warehouse (Multiparameter Intelligent Monitoring in Intensive Care III). SETTING: Data were collected from the medical, surgical, cardiac, and cardiac surgery ICUs of a tertiary medical center in the United States. PATIENTS: We analyzed data from approximately 48,000 ICU stays including approximately 28 million vital signs measurements. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We used the vital sign day as our unit of measurement, defined as all the recordings from a single patient for a specific vital sign over a single 24-hour period. Approximately 30-40% of vital sign days included at least one gap of greater than 70 minutes between measurements. Between 3% and 10% of blood pressure measurements included logical inconsistencies. With the exception of pulse oximetry vital sign days, the readings in most vital sign days were normally distributed. We found that 15-38% of vital sign days contained at least one statistical outlier, of which 6-19% occurred simultaneously with outliers in other vital signs. CONCLUSIONS: We found a significant number of missing, erroneous, and outlying vital signs measurements in a large ICU database. Our results provide empirical evidence of the nonrepresentativeness of hourly vital signs. Additional studies should focus on determining optimal sampling frequencies for recording vital signs in the ICU.

Food safety knowledge of undergraduate students at a Canadian university: results of an online survey.

BACKGROUND: Foodborne diseases are an important public health issue, and young adults are an important demographic to target with food safety education. Our objective was to assess the food safety knowledge of undergraduate students at a Canadian university, to identify potential areas for such education. METHODS: In February 2015, we conducted an online survey of 485 undergraduate students at a university in Ontario, Canada. We assessed various food-related factors, including cooking frequency and prior food handling or preparation education. We then modeled the relationship between 'overall knowledge score' and the demographic and food skills/cooking experience predictors using multivariable log-binomial regression, to determine factors associated with relatively higher proportions of correct responses. RESULTS: Respondents were, on average, 20.5 years old, and the majority (64.8 %) lived off campus. Students cooked from basic ingredients infrequently, with 3 in 4 doing so a few times a year to never. Students averaged 6.2 correct answers to the 11 knowledge questions. Adjusting for other important covariates, older age and being a current food handler were associated with relatively higher knowledge, whereas working/volunteering in a hospital and infrequent cooking were associated with relatively lower knowledge. Males in the Faculty of Science had relatively higher knowledge than females in the Faculty of Science, both of whom had relatively higher knowledge than all students in other Faculties. Among students who had never taken a food preparation course, knowledge increased with self-reported cooking ability; however, among students who had taken such a course, knowledge was highest among those with low self-reported cooking ability. CONCLUSIONS: Consistent with other similar studies, students in Faculties outside of the Faculty of Science, younger students, and those who cook infrequently could benefit from food safety education. Supporting improved hand hygiene, in particular clarifying hand washing versus hand sanitizing messages, may also be important. Universities can play a role in such education, including as part of preparing students for work or volunteer placements, or as general support for student health and success.

Multivariate longitudinal data analysis with mixed effects hidden Markov models.

Multiple longitudinal responses are often collected as a means to capture relevant features of the true outcome of interest, which is often hidden and not directly measurable. We outline an approach which models these multivariate longitudinal responses as generated from a hidden disease process. We propose a class of models which uses a hidden Markov model with separate but correlated random effects between multiple longitudinal responses. This approach was motivated by a smoking cessation clinical trial, where a bivariate longitudinal response involving both a continuous and a binomial response was collected for each participant to monitor smoking behavior. A Bayesian method using Markov chain Monte Carlo is used. Comparison of separate univariate response models to the bivariate response models was undertaken. Our methods are demonstrated on the smoking cessation clinical trial dataset, and properties of our approach are examined through extensive simulation studies.

The COMPASS study: a longitudinal hierarchical research platform for evaluating natural experiments related to changes in school-level programs, policies and built environment resources.

BACKGROUND: Few researchers have the data required to adequately understand how the school environment impacts youth health behaviour development over time. METHODS/DESIGN: COMPASS is a prospective cohort study designed to annually collect hierarchical longitudinal data from a sample of 90 secondary schools and the 50,000+ grade 9 to 12 students attending those schools. COMPASS uses a rigorous quasi-experimental design to evaluate how changes in school programs, policies, and/or built environment (BE) characteristics are related to changes in multiple youth health behaviours and outcomes over time. These data will allow for the quasi-experimental evaluation of natural experiments that will occur within schools over the course of COMPASS, providing a means for generating "practice based evidence" in school-based prevention programming. DISCUSSION: COMPASS is the first study with the infrastructure to robustly evaluate the impact that changes in multiple school-level programs, policies, and BE characteristics within or surrounding a school might have on multiple youth health behaviours or outcomes over time. COMPASS will provide valuable new insight for planning, tailoring and targeting of school-based prevention initiatives where they are most likely to have impact.

Classification of traumatic life events and substance use among persons admitted to inpatient psychiatry in Ontario, Canada.

BACKGROUND: Trauma is commonly overlooked or undiagnosed in clinical care settings. Undetected trauma has been associated with elevated substance use highlighting the need to prioritize identifying individuals with undetected trauma through common characteristics. OBJECTIVE: The purpose of this study is to identify classifications of traumatic life experiences and substance use among persons admitted to inpatient psychiatry in Ontario and to identify covariates associated with classification membership. STUDY DESIGN: A population-based retrospective cohort study was conducted using interRAI Mental Health (MH) assessment data. Individuals were included who experienced traumatic life events (N = 10,125), in Ontario, Canada between January 1, 2015, to December 31, 2019. RESULTS: Eight latent classes were identified that ranged from low (i.e., Class 1: Interpersonal Issues, Without Substance use) to high (i.e., Class 8: Widespread Trauma, Alcohol & Cannabis Addiction) complexity patterns of traumatic life events and substance use indicators. Classifications with similar trauma profiles were differentiated by patterns of substance use. For example, individuals in Class 2: Safety & Relationship Issues, Without Substance use and Class 3: Safety & Relationship Issues, Alcohol & Cannabis both had many estimates centered around the experience of victimization (e.g., victim of sexual assault, victim of physical assault, victim of emotional abuse). Multinomial logistic regression models highlighted additional factors associated with classifications such as homelessness, where those who were homeless were 2.09-4.02 times more likely to be in Class 6: Widespread Trauma & Substance Addiction. INTERPRETATION: Trauma exposures are complex and varied among persons in inpatient psychiatry and can be further differentiated by substance use patterns. These findings provide a population-based estimate of the trauma experiences of persons in inpatient settings in Ontario, Canada. Findings demonstrate the importance of using comprehensive assessment to support clinical decision making in relation to trauma and substance.

Suicidal Ideation and Attempts Among Youth With Physical-Mental Comorbidity in Canada: Proposal for an Epidemiological Study.

BACKGROUND: Evidence suggests that having a chronic physical illness (CPI; eg, asthma, diabetes, and epilepsy) is an independent risk factor for suicidality (ie, suicidal ideation or attempts) among youth. Less is known about the mechanisms linking CPI and suicidality. Some evidence suggests that mental illness (eg, depression and anxiety) or neurodevelopmental disorder (eg, attention-deficit/hyperactivity disorder) mediates or moderates the CPI-suicidality association. Missing from the knowledge base is information on the association between having co-occurring CPI and mental illness or neurodevelopmental disorder (MIND) on youth suicidality. OBJECTIVE: This study uses epidemiological data from the 2019 Canadian Health Survey of Children and Youth (CHSCY) to study the intersection of CPI, MIND, and suicidality in youth. We will estimate prevalence, identify predictors, and investigate psychosocial and service use outcomes for youth with CPI-MIND comorbidity versus other morbidity groups (ie, healthy, CPI only, and MIND only). METHODS: Conducted by Statistics Canada, the CHSCY collected data from 47,850 children (aged 1-17 years) and their primary caregiving parent. Measures of youth CPI, MIND, family environment, and sociodemographics are available using youth and parent informants. Information on psychiatric services use is available via parent report and linkage to national administrative health data found in the National Ambulatory Care Reporting System and the Discharge Abstract Database, which allow the investigation of hospital-based mental health services (eg, emergency department visits, hospitalizations, and length of stay in hospital). Questions about suicidality were restricted to youths aged 15-17 years (n=6950), which form our analytic sample. Weighted regression-based analyses will account for the complex survey design. RESULTS: Our study began in November 2023, funded by the American Foundation for Suicide Prevention (SRG-0-008-22). Access to the linked CHSCY microdata file was granted in May 2024. Initial examination of CHSCY data shows that approximately 20% (1390/6950) of youth have CPI, 7% (490/6950) have MIND, 7% (490/6950) seriously considered suicide in the past year, and 3% (210/6950) had attempted suicide anytime during their life. CONCLUSIONS: Findings will provide estimates of suicidality among youth with CPI-MIND comorbidity, which will inform intervention planning to prevent loss of life in this vulnerable population. Modeling correlates of suicidality will advance understanding of the relative and joint effects of factors at multiple levels-information needed to target prevention efforts and services. Understanding patterns of psychiatric service use is vital to understanding access and barriers to services. This will inform whether use matches need, identifying opportunities to advise policy makers about upstream resources to prevent suicidality. Importantly, findings will provide robust baseline of information on the link between CPI-MIND comorbidity and suicidality in youth, which can be used by future studies to address questions related to the impact of the COVID-19 pandemic and associated countermeasures in this vulnerable population of youth. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/57103.

Revealing the Mysteries of Population Mobility Amid the COVID-19 Pandemic in Canada: Comparative Analysis With Internet of Things-Based Thermostat Data and Google Mobility Insights.

BACKGROUND: The COVID-19 pandemic necessitated public health policies to limit human mobility and curb infection spread. Human mobility, which is often underestimated, plays a pivotal role in health outcomes, impacting both infectious and chronic diseases. Collecting precise mobility data is vital for understanding human behavior and informing public health strategies. Google's GPS-based location tracking, which is compiled in Google Mobility Reports, became the gold standard for monitoring outdoor mobility during the pandemic. However, indoor mobility remains underexplored. OBJECTIVE: This study investigates in-home mobility data from ecobee's smart thermostats in Canada (February 2020 to February 2021) and compares it directly with Google's residential mobility data. By assessing the suitability of smart thermostat data, we aim to shed light on indoor mobility patterns, contributing valuable insights to public health research and strategies. METHODS: Motion sensor data were acquired from the ecobee "Donate Your Data" initiative via Google's BigQuery cloud platform. Concurrently, residential mobility data were sourced from the Google Mobility Report. This study centered on 4 Canadian provinces-Ontario, Quebec, Alberta, and British Columbia-during the period from February 15, 2020, to February 14, 2021. Data processing, analysis, and visualization were conducted on the Microsoft Azure platform using Python (Python Software Foundation) and R programming languages (R Foundation for Statistical Computing). Our investigation involved assessing changes in mobility relative to the baseline in both data sets, with the strength of this relationship assessed using Pearson and Spearman correlation coefficients. We scrutinized daily, weekly, and monthly variations in mobility patterns across the data sets and performed anomaly detection for further insights. RESULTS: The results revealed noteworthy week-to-week and month-to-month shifts in population mobility within the chosen provinces, aligning with pandemic-driven policy adjustments. Notably, the ecobee data exhibited a robust correlation with Google's data set. Examination of Google's daily patterns detected more pronounced mobility fluctuations during weekdays, a trend not mirrored in the ecobee data. Anomaly detection successfully identified substantial mobility deviations coinciding with policy modifications and cultural events. CONCLUSIONS: This study's findings illustrate the substantial influence of the Canadian stay-at-home and work-from-home policies on population mobility. This impact was discernible through both Google's out-of-house residential mobility data and ecobee's in-house smart thermostat data. As such, we deduce that smart thermostats represent a valid tool for facilitating intelligent monitoring of population mobility in response to policy-driven shifts.

Exploring the differential impacts of social isolation, loneliness, and their combination on the memory of an aging population: A 6-year longitudinal study of the CLSA.

Memory plays a crucial role in cognitive health. Social isolation (SI) and loneliness (LON) are recognized risk factors for global cognition, although their combined effects on memory have been understudied in the literature. This study used three waves of data over six years from the Canadian Longitudinal Study on Aging to examine whether SI and LON are individually and jointly associated with memory in community-dwelling middle-aged and older adults (n = 14,208). LON was assessed with the question: "In the last week, how often did you feel lonely?". SI was measured using an index based on marital/cohabiting status, retirement status, social activity participation, and social network contacts. Memory was evaluated with combined z-scores from two administrations of the Rey Auditory Verbal Learning Test (immediate-recall, delayed-recall). We conducted our analyses using all available data across the three timepoints and retained participants with missing covariate data. Linear mixed models were used to regress combined memory scores onto SI and LON, adjusting for sociodemographic, health, functional ability, and lifestyle variables. Experiencing both SI and LON had the greatest inverse effect on memory (least-squares mean: -0.80 [95 % confidence-interval: -1.22, -0.39]), followed by LON alone (-0.73 [-1.13, -0.34]), then SI alone (-0.69 [-1.09, -0.29]), and lastly by being neither lonely nor isolated (-0.65 [-1.05, -0.25]). Sensitivity analyses confirmed this hierarchy of effects. Policies developed to enhance memory in middle-aged and older adults might achieve greater benefits when targeting the alleviation of both SI and LON rather than one or the other individually.

Use of online food delivery services among adults in five countries from the International Food Policy Study 2018-2021.

Aim: Online food delivery services (OFDS) are popular for purchasing meals prepared outside home, increasing access to energy-dense and nutrient-poor foods. This adversely impacts dietary choices and health outcomes. Our study examined trends in OFDS use in Australia, Canada, Mexico, the United Kingdom (UK), and the United States (US) from 2018 to 2021. Methods: Repeated annual cross-sectional data was sourced from the International Food Policy Study for five countries among adults over 18 years (N = 83,337). Weighted estimates for trends in i) the proportion of the respondent's purchasing meals per week using OFDS, and ii) average number (and standard deviation (SD)) of meals purchased per week using OFDS were assessed. Logistic regression models were fitted. Findings: OFDS use increased among adults between 2018-2021 (Australia: 17 % of respondents purchased at least one meal in the last 7 days using OFDS in 2018 to 25 % in 2021, Canada: 12 % to 19 %, Mexico: 28 % to 38 %, UK: 19 % to 28 %, and US: 17 % to 21 %). Average number of meals purchased per week outside home remained consistent for all countries over time (e.g., in Australia, 2.70 (SD 0.06) meals in 2018 and 2.63 (SD 0.06) in 2021). However, average number of meals purchased using OFDS nearly doubled between 2018 and 2021 (e.g., in Australia, 0.45 (SD 0.03) meals in 2018 to 0.81 (SD 0.04) in 2021). Conclusion: OFDS use is increasing and are substituting the conventional forms of purchasing meals outside home. Nutritional quality of foods sold, marketing practices and purchasing patterns on OFDS deserve further attention.

Heart failure--related mortality and hospitalization in the year following admission to a long-term care facility: the geriatric outcomes and longitudinal decline in heart failure (GOLD-HF) study.

BACKGROUND: Heart failure (HF) is common in long-term care facilities (LTCs). This study compared mortality and hospitalization rates and examined predictors of these outcomes among new LTC residents with and without HF. METHODS AND RESULTS: This prospective cohort study followed 546 newly admitted residents from 42 LTCs for up to 1 year. Health information was collected from participant and caregiver interviews, physicians' records, diagnostic procedures, and hospitalization records. Multivariate logistic regression modeling determined predictors of hospitalization among residents, and Cox proportional hazards regression determined predictors for time to mortality. HF prevalence was 21.4%. The sample was predominantly (>70%) female, and individuals with HF were significantly older with higher prevalence of reduced left ventricular ejection fraction. Overall annual mortality and hospitalization rates were 24% and 27%, respectively. Among residents with HF, 42% died and 31% were hospitalized within 1 year. Among residents with HF, use of major tranquilizers was the strongest predictor of sooner mortality; use of anticoagulants and major tranquilizers also increased mortality risk, whereas higher baseline function was associated with longer time to mortality. History of peripheral vascular disease was the strongest predictor of hospitalizations among residents with HF, and use of antiplatelet agents and history of any smoking exposure increased this risk. CONCLUSIONS: Among LTC residents, HF is associated with high mortality and hospitalization rates. Many factors contribute to mortality and hospitalizations among residents with HF, and comprehensive HF management programs are needed to improve outcomes.

Breast Cancer and Bone Mineral Density in a U.S. Cohort of Middle-Aged Women: Associations with Phosphate Toxicity.

Breast cancer is associated with phosphate toxicity, the toxic effect from dysregulated phosphate metabolism that can stimulate tumorigenesis. Phosphate toxicity and dysregulated phosphate metabolism are also associated with bone mineral abnormalities, including excessive bone mineral loss and deposition. Based on shared associations with dysregulated phosphate metabolism and phosphate toxicity, a hypothesis proposed in the present mixed methods-grounded theory study posits that middle-aged women with incidence of breast cancer had a greater magnitude of changes in bone mineral density over time compared with women who remained cancer-free. To test this hypothesis, a mixed-effects model was used to analyze the associations of breast cancer incidence with spinal bone mineral density changes in the U.S. Study of Women's Health Across the Nation. Compared with women in the cohort who remained cancer-free, women who self-reported breast cancer had higher bone mineral density at baseline, but had more rapid losses in bone mineral density during follow-up visits. These findings agree with the hypothesis that a greater magnitude of changes in bone mineral density over time is associated with breast cancer in a cohort of middle-aged women. The findings also have implications for studies investigating dysregulated phosphate metabolism and phosphate toxicity as causative factors of bone metastasis in metastatic breast cancer. Additionally, the authors previously found increased breast cancer risk associated with high dietary phosphate intake in the same cohort of middle-aged women, and more studies should investigate a low-phosphorus diet to reduce bone mineral abnormalities and tumorigenesis in breast cancer patients.

High Dietary Phosphorus Is Associated with Increased Breast Cancer Risk in a U.S. Cohort of Middle-Aged Women.

Research has shown that high amounts of dietary phosphorus that are twice the amount of the U.S. dietary reference intake of 700 mg for adults are associated with all-cause mortality, phosphate toxicity, and tumorigenesis. The present nested case-control study measured the relative risk of self-reported breast cancer associated with dietary phosphate intake over 10 annual visits in a cohort of middle-aged U.S. women from the Study of Women's Health Across the Nation. Analyzing data from food frequency questionnaires, the highest level of daily dietary phosphorus intake, >1800 mg of phosphorus, was approximately equivalent to the dietary phosphorus levels in menus promoted by the United States Department of Agriculture. After adjusting for participants' energy intake, this level of dietary phosphorus was associated with a 2.3-fold increased risk of breast cancer incidence compared to the reference dietary phosphorus level of 800 to 1000 mg, which is based on recommendations from the U.S. National Kidney Foundation, (RR: 2.30, 95% CI: 0.94-5.61, p = 0.07). Despite the lack of statistical significance, likely due to the small sample size of the cohort, the present nested case-control study's clinically significant effect size, dose-response, temporality, specificity, biological plausibility, consistency, coherence, and analogy with other research findings meet the criteria for inferred causality in observational studies, warranting further investigations. Furthermore, these findings suggest that a low-phosphate diet should be tested on patients with breast cancer.

Examining the Association Between Household Enrollment in the Pantawid Pamilyang Pilipino Program (4Ps) and Wasting and Stunting Status Among Children Experiencing Poverty in the Philippines: A Cross-Sectional Study.

This study assessed whether enrollment in a national conditional cash transfer program was associated with wasting and stunting among children experiencing extreme poverty in the Philippines. Data were drawn from cross-sectional surveys collected from 10 regional areas in the Philippines between April 2018 and May 2019. A total of 2945 children aged between six months and 12 years comprised the analytical sample. Multilevel logistic regression was conducted to estimate the association between enrollment in Pantawid Pamilyang Pilipino Program (4Ps) and stunting and wasting, controlling for sociodemographic factors and clustering by region. There was no meaningful association between household enrollment in 4Ps and the wasting status of children, but enrollment in 4Ps was associated with lower odds of stunting and differed by geography type. Findings suggest that the current design of 4Ps may not address sudden shocks that contribute to wasting, but may address the underlying socioeconomic risk factors associated with stunting.

Examining the use of decision trees in population health surveillance research: an application to youth mental health survey data in the COMPASS study. / Utilisation des arbres décisionnels dans la recherche en surveillance de la santé de la population : application aux données d'enquête sur la santé mentale des jeunes de l'étude COMPASS.

INTRODUCTION: In population health surveillance research, survey data are commonly analyzed using regression methods; however, these methods have limited ability to examine complex relationships. In contrast, decision tree models are ideally suited for segmenting populations and examining complex interactions among factors, and their use within health research is growing. This article provides a methodological overview of decision trees and their application to youth mental health survey data. METHODS: The performance of two popular decision tree techniques, the classification and regression tree (CART) and conditional inference tree (CTREE) techniques, is compared to traditional linear and logistic regression models through an application to youth mental health outcomes in the COMPASS study. Data were collected from 74 501 students across 136 schools in Canada. Anxiety, depression and psychosocial well-being outcomes were measured along with 23 sociodemographic and health behaviour predictors. Model performance was assessed using measures of prediction accuracy, parsimony and relative variable importance. RESULTS: Decision tree and regression models consistently identified the same sets of most important predictors for each outcome, indicating a general level of agreement between methods. Tree models had lower prediction accuracy but were more parsimonious and placed greater relative importance on key differentiating factors. CONCLUSION: Decision trees provide a means of identifying high-risk subgroups to whom prevention and intervention efforts can be targeted, making them a useful tool to address research questions that cannot be answered by traditional regression methods.

Forecasting daily COVID-19 cases with gradient boosted regression trees and other methods: evidence from U.S. cities.

Introduction: There is a vast literature on the performance of different short-term forecasting models for country specific COVID-19 cases, but much less research with respect to city level cases. This paper employs daily case counts for 25 Metropolitan Statistical Areas (MSAs) in the U.S. to evaluate the efficacy of a variety of statistical forecasting models with respect to 7 and 28-day ahead predictions. Methods: This study employed Gradient Boosted Regression Trees (GBRT), Linear Mixed Effects (LME), Susceptible, Infectious, or Recovered (SIR), and Seasonal Autoregressive Integrated Moving Average (SARIMA) models to generate daily forecasts of COVID-19 cases from November 2020 to March 2021. Results: Consistent with other research that have employed Machine Learning (ML) based methods, we find that Median Absolute Percentage Error (MAPE) values for both 7-day ahead and 28-day ahead predictions from GBRTs are lower than corresponding values from SIR, Linear Mixed Effects (LME), and Seasonal Autoregressive Integrated Moving Average (SARIMA) specifications for the majority of MSAs during November-December 2020 and January 2021. GBRT and SARIMA models do not offer high-quality predictions for February 2021. However, SARIMA generated MAPE values for 28-day ahead predictions are slightly lower than corresponding GBRT estimates for March 2021. Discussion: The results of this research demonstrate that basic ML models can lead to relatively accurate forecasts at the local level, which is important for resource allocation decisions and epidemiological surveillance by policymakers.