Traditional Epidemiological Studies Research Articles

Emphasis on awareness of early-onset colorectal cancer

The incidence and mortality rates of early-onset colorectal cancer (EOCRC) among people under 50 years old are showing an upward trend. Although traditional epidemiological studies have conducted relatively deep research and screened out environmental factors related to EOCRC, our understanding of the causes, mechanisms, and treatment of this disease is still far from sufficient. In this review, we clarify the current progress of EOCRC, with a particular focus on epidemiology, screening status, clinical symptoms, and prognosis. This provides new evidence for secondary prevention, including precision screening, and offers new ideas for improving the diagnosis and treatment of EOCRC.

Abstract PO2-25-11: Incidence of Breast Cancer in Louisiana Compared to the United States

Abstract Aside from skin cancer, breast cancer is the most common cancer in American women. More specifically, one in eight women will develop breast cancer during their lifetime. Breast cancer is classified into subtypes defined by immunohistochemistry (IHC) expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). ER+/PR+/HER2- tumors are the most common form of breast cancer and are typically associated with risk factors including older age, nulliparity, obesity following menopause, alcohol and tobacco use, sedentary lifestyle, and hormone therapy. ER-/PR-/HER2+ tumors comprise approximately 15-20% of breast cancers and are caused by overexpression of the HER2 gene. These tumors have similar risk factors to ER+/PR+/HER2- tumors, except for age. Women with HER2+ breast cancer are likely to be younger compared to ER+PR+/HER2-. Tumors lacking hormone receptors are classified as ER-/PR-/HER2-, otherwise known as triple-negative breast cancer (TNBC). TNBC represents 10%-20% of breast cancers and carries a poorer prognosis, shorter survival, and unresponsiveness to hormone therapy compared to other forms of breast cancer. TNBC has been associated with African American race, socioeconomically deprived population, younger age at diagnosis (most frequently in women ages 40-50), more advanced disease stage, higher grade, high mitotic indices, family history of breast cancer and BRCA1 mutations. The primary aim of this study is to compare incidence of ER+/PR+/HER2-, ER-/PR-/HER2+, and ER-/PR-/HER2- (TNBC) in Louisiana to the national population. The Louisiana Tumor Registry (LTR) was utilized to obtain state and national level data. The LTR is a participant of the National Cancer Institute’s Surveillance, Epidemiology and End Results Program, and the Centers for Disease Control and Prevention’s National Program of Cancer Registries. Our study evaluated women in Louisiana diagnosed with ER+/PR+/HER2-, ER-/PR-/HER2+, and ER-/PR-/HER2- from 2010-2019. The populations were subdivided by age at time of diagnosis. Data was subdivided into ages 0-49, and >50. Rates were calculated per 100,00 and age-adjusted to the 2000 United States Standard Population (19 age groups - Census P25-1130). A p-value of < 0.05 indicates a significantly different rate in Louisiana comparative to the United States (SEER). Our results are as follows. Unexpectedly, Louisiana has a significantly lower rate of ER+/PR+/HER2- cancer in women ages 0-49 and ages >50 compared to the United States. Based on epidemiological risk factors, Louisiana should have a much higher rate of ER+/PR+/HER2- comparative to the United States population. Louisiana has a significantly higher rate of ER-/PR-/HER2+ cancer in women ages >50 and ER-/PR-/HER2- (TNBC) in women ages 0-49 and ages >50 compared to the United States. These findings are discordant with traditional epidemiologic studies regarding breast cancer and require further investigation. Breast Cancer Incidence Rates1 by Age from 2010-2019 in Louisiana and the United States Table 1: Breast Cancer Incidence Rates in women ages 0-49 and ages >50 from 2010-2019 in Louisiana Compared to the United States. Citation Format: Avery Daily, Julie Cupp, Krystle Trosclair. Incidence of Breast Cancer in Louisiana Compared to the United States [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-25-11.

The causal effects of genetically predicted alcohol consumption on endometrial cancer risk from a Mendelian randomization study

Endometrial cancer (EC) is a common gynecological tumor in females with an increasing incidence over the past few decades. Alcohol consumption has been linked to the occurrence of various cancers; However, epidemiological studies have shown inconsistent associations between alcohol consumption and EC risk. In order to avoid the influence of potential confounding factors and reverse causality in traditional epidemiological studies, we used a method based on genetic principles-Mendelian randomization (MR) analysis to test whether there is a causal relationship between alcohol consumption and EC. MR analysis was conducted using publicly available summary-level data from genome-wide association studies (GWAS). Fifty-seven single nucleotide polymorphisms (SNPs) were extracted as instrumental variables for alcohol exposure from the GWAS and Sequencing Consortium of Alcohol and Nicotine GWAS summary data involving 941,287 participants of European ancestry. SNPs for EC were obtained from the Endometrial Cancer Association Consortium, the Endometrial Cancer Epidemiology Consortium, and the UK Biobank, involving 121,885 European participants. The inverse variance weighted (IVW) method was used as the primary method to estimate the causal effect, and the MR-Egger regression and weighted median method were used as supplementary methods. Sensitivity analyses were conducted using the Mendelian Randomization Pleiotropy RESidual Sum and Outlier global test, MR-Egger intercept test, and leave-one-out analysis to evaluate the impact of pleiotropy on causal estimates. An increase of 1 standard deviation of genetically predicted log-transformed alcoholic drinks per day was associated with a 43% reduction in EC risk [odds ratio (OR) = 0.57, 95% confidence interval (CI) 0.41–0.79, P < 0.001]. Subgroup analysis of EC revealed that alcohol consumption was a protective factor for endometrioid endometrial cancer (EEC) (OR = 0.56, 95% CI 0.38–0.83, P = 0.004) but not for non-endometrioid endometrial cancer (NEC) (OR = 1.36, 95% CI 0.40–4.66, P = 0.626). The MR-Egger regression and weighted median method yielded consistent causal effects with the IVW method. The consistent results of sensitivity analyses indicated the reliability of our causal estimates. Additionally, alcohol consumption was associated with decreased human chorionic gonadotropin (HCG) and insulin-like growth factor 1 (IGF1) levels. This MR study suggests that genetically predicted alcohol consumption is a protective factor for EC, particularly for EEC, and this protective effect may be mediated through the reduction of HCG and IGF1.

Environment-wide association study of elevated liver enzymes: results from the Korean National Environmental Health Survey 2018-2022.

Environmental exposure is characterized by low concentration, chronic, and complex exposure. Traditional epidemiological studies show limitations in reflecting these characteristics since they usually focus on a single or very limited number of exposure factors at a time. In this study, we adopted the methodology of environment-wide association study (EWAS) to figure out the association of human liver function with various environmentally hazardous substances. We analyzed 2,961 participants from the Korean National Environmental Health Survey Cycle 4 (2018-2020). Using generalized linear model (GLM) analysis, we analyzed the association of 72 variables with 3 liver function indices (aspartate aminotransferase [AST], alanine aminotransferase [ALT], and gamma glutamyl transferase [GGT]). Finally, we visualized our results with Manhattan plot. In GLM analysis, perfluorooctanesulfonate were positively associated with ALT (odds ratio [OR]: 2.2; 95% confidence interval [CI]: 1.39-3.46; p adjusted = 0.0147) and perfluorodecanoic acid showed positive association with GGT (OR: 2.73; 95% CI: 1.36-5.5; p adjusted = 0.0256). Plasma mercury showed positive association with GGT (OR: 1.45; 95% CI: 1.14-1.84; p adjusted = 0.0315). Using a plastic container while keeping food in the refrigerator was associated with elevated GGT compared to using a glass container (OR: 1.51; 95% CI: 1.16-1.95; p adjusted = 0.0153). 2-ethyl-5-oxohexyl phthalate, showed a negative trend with all 3 indices, with AST (OR: 0.54; 95% CI: 0.39-0.73; p adjusted = 0.00357), ALT (OR: 0.5; 95% CI: 0.34-0.75; p adjusted = 0.036), GGT (OR: 0.55; 95% CI: 0.4-0.76; p adjusted = 0.00697). Bisphenol S and frequent use of sunblock cream showed negative association with ALT (OR: 0.77; 95% CI: 0.66-0.89), and GGT (OR: 0.25; 95% CI: 0.11-0.55), respectively. We conducted an exploratory study on environmental exposure and human liver function. By using EWAS methodology, we identified 7 factors that could have potential association with liver function.

Family, twin and adoption studies of severe mental disorders in sub-Saharan Africa: a scoping review.

The traditional genetic epidemiological studies are necessary to improve accurate risk communication to service users and their families. This scoping review aimed to describe the volume and scope of existing research evidence on family, twin and adoption studies of severe mental disorders (SMDs) in SSA. This is with a view to identifying gaps in the literature and the adequacy of data for a systematic review and meta-analysis. Literature search was done for all original peer-reviewed research articles on the topic in SSA using PubMed and MEDLINE. Publications included were peer-reviewed original articles, irrespective of their quality, carried out in the region from the 1970s till 9th March, 2022, which were available in English or translated to English. Case reports, abstracts, and studies among populations living outside the region were excluded. A total of five studies that met the inclusion criteria across the 46 countries in the region were identified. Of the three thematic areas of focus, only family studies on SMDs had research work in SSA. These studies provided evidence of familial clustering of SMDs in SSA. There were no twin and adoption studies on SMDs in the region. However, the review noted the establishment of two twin registries in Guinea-Bissau and Nigeria. A huge gap exists in the area of twin and adoption studies on SMDs in SSA. The volume of research evidence on traditional family genetic studies of SMDs is grossly inadequate to consider a systematic review in SSA. We have suggested studies to remedy the situation.

1.J. Round table: Research Methods for Public Health Oriented Health Services Research – what works where and for what?

Abstract This workshop will present the different methodological approaches relevant to the field of public health. This includes approaches of health systems and health policy research, epidemiology, health technology assessment, health impact assessment, health systems performance and economic evaluations. Presentations will be hold by presidents and vice-presidents of the EUPHA Sections in the form of a panel, presenting the overview of each methodology and providing case examples. All organizers might invite special contributions from their members and students to share innovations of case examples from their counties. During the first half of the workshop the EUPHA Sections will provide input on traditional and innovative methods the following topics: 1. Health Policy and Systems Research (HPSR) applied to Primary Care. 2. The use of traditional and innovative epidemiological study designs for public health relevant inferences. 3. Overview of methods used for the quantification of health impacts, both following a risk assessment approach or an epidemiological approach. 4. Methodologies and techniques applied in Health Technology Assessment (HTA) and how their contribute to decision-making and evidence-informed policymaking. 5. Health Systems Performance Assessment (HSPA) and Economic evaluations. 6. Research methods from the public health policy and politics perspective. In the second half of the workshop we will discuss and share examples on innovation in research methods and seek to find an answer to the question: what is being done in the countries? Input from DGPH-FO, DNVF-IHRS, Charité WG HPSRI and from all participants will be welcome. Target audience: young and old professionals interested in updating their methods skills and sharing their own experiences on innovation in methods for a stronger public health research. Key messages • There are no better or worse research methods; they are just a tool, that when applied properly support evidence and action for a stronger public health. • As knowledge on research methods evolve, sharing knowledge amongst different fields is key to contribute to a stronger health system, better health policy decisions and a better health for all. Speakers/Panellists Lorena Dini Charité Univesitätsmedizin Berlin, Berlin, Germany Piedad Martin-Olmedo Escuela Andaluza de Salud Pública, Granada, Spain Stefania Boccia Italian Society of Hygiene, Preventive Medicine and Public Health, Rome, Italy Chiara de Waure University of Perugia, Perugia, Italy João Vasco Santos Faculty of Medicine, University of Porto, CINTESIS, Porto, Portugal

Genetically Predicted Smoking and Alcohol Consumption and Functional Outcome After Ischemic Stroke.

Smoking and alcohol consumption have been adversely associated with poststroke outcome in traditional epidemiologic studies. The present study explored the association of genetically predicted smoking and alcohol consumption on poststroke outcomes using the mendelian randomization (MR) framework. Instrumental variables for smoking initiation and alcohol consumption were selected from a genome-wide association study data of European ancestry individuals. Summary-level data for functional outcome after ischemic stroke were obtained from the Genetics of Ischemic Stroke Functional Outcome network study of European ancestry patients. The univariable and multivariable inverse-variance weighted MR methods were performed to obtain the causal estimates. The weighted median, MR-robust adjusted profile score, and MR-Egger regression approaches were adopted as sensitivity analyses. Q and I 2 statistics were used to evaluate heterogeneity in MR estimates across variants. Genetic predisposition to smoking initiation was associated with worse functional outcome after ischemic stroke in univariable inverse-variance weighted MR analysis (odds ratio [OR] 1.48; 95% CI 1.08-2.01, p = 0.013). This association remained significant when adjusting for genetically predicted alcohol consumption in multivariable MR analyses (OR 1.56; 95% CI 1.05-2.32, p = 0.027). Genetically predicted alcohol consumption was not associated with functional outcome after ischemic stroke (p > 0.05). Sensitivity analyses with other approaches and in analyses restricted to models without adjustment for baseline stroke severity produced similar results, and no evidence of heterogeneity in MR estimates between variants was detected (p > 0.05). Our results provide genetic support for a causal association of smoking with worse functional outcome after ischemic stroke and have important implications for poststroke recovery. Smoking cessation and avoidance should be promoted in patients with ischemic stroke.

Insomnia, sleep duration, and risk of anxiety: A two-sample Mendelian randomization study

BackgroundThe effect of insomnia and sleep duration on risk of anxiety has been assessed based on traditional epidemiological studies. However, the inconsistent conclusions do not establish causal associations. This study aimed to explore the causal associations of insomnia, short sleep, and long sleep with anxiety. MethodsWe used summary statistics from three large-scale genome-wide association studies (GWAS) of European ancestry to perform a two-sample Mendelian randomization (MR) study. MR analyses were mainly conducted with the inverse-variance-weighted (IVW) method. To evaluate the robustness of our findings, we performed the weighted-median approach, the MR-Egger method, and the MR-robust adjusted profile score (MR-RAPS) method for sensitivity analyses. ResultsThere was a statistically significant association of genetically predicted insomnia with anxiety using the IVW method (OR = 1.36, 95% CI = 1.23–1.51, P < 0.001). Genetically predicted short sleep was potentially associated with anxiety using IVW method (OR = 1.67, 95% CI = 1.08–2.60, P = 0.022). However, sensitivity analyses did not find the causal association of short sleep with anxiety (all P > 0.053). We did not observe a statistically significant causal association of genetically predicted long sleep with anxiety (OR = 0.91, 95% CI = 0.48–1.74, P = 0.775). ConclusionsWe found strong evidence that insomnia but not short sleep and long sleep has a causal effect on anxiety. The characteristics of insomnia should be incorporated into anxiety prevention and intervention strategies, which have important public health significance.

Educational attainment and offspring birth weight: A bidirectional Mendelian randomization study.

Background: The association between educational attainment (EA) and offspring birth weight (BW) has been reported by several traditional epidemiological studies. However, evidence for this association tends to be mixed and confounded. This study aimed to investigate the causal association between EA of parents and offspring BW. Methods: Here, we carried out a two-sample bidirectional Mendelian randomization (MR) analysis to examine the causal association between EA of males (n = 131,695) and females (n = 162,028) and offspring BW using genetic instruments. Summary statistics of EA associated single nucleotide polymorphisms (SNPs) were extracted from a GWAS incorporating 293,723 individuals of European descent performed by the Social Science Genetic Association Consortium (SSGAC), and the effects of these SNPs on offspring BW were estimated using a GWAS meta-analysis of 86,577 participants of European descent from 25 studies. Univariable MR analyses were conducted using the inverse-variance weighted (IVW) method and four other methods. Further sensitivity analyses were carried out to test the viability of the results. Multivariable MR was used to examine the confounders between the exposure and outcome. Results: The result shows evidence that the offspring BW is positively causally affected by female EA. Each one standard deviation (SD) increase in female EA was associated with 0.24 SD higher of offspring BW (95% confidence interval [CI], 0.10 to 0.37, p < 0.001 for the IVW method). Similarly, change in offspring BW was 0.21 SD (95% CI: 0.07 to 0.34, p = 2.82 × 10-3) per one SD higher in male EA. No causal effect of BW on EA was found by any of the five methods. The causal association between female EA and offspring BW maintained after adjusting for alcoholic drinks per week and BMI. The effect of male EA on offspring BW was attenuated when we adjusted for BMI and alcoholic drinks per week using multivariable MR analysis. Conclusion: Our study indicated that female EA is positively causally associated with offspring BW. The association between male EA and offspring BW may be confounded by alcoholic drinks per week and BMI.

The timing of adiposity and changes in the life course on the risk of cancer.

Excess body weight has been established as a risk factor for at least twelve cancer sites, though questions remain as to the timing of associations for adiposity and cancer riskthroughout the life course. We conducted a narrative review summarizing existing evidence to provide insights into the complex timing relationship between adiposity and risk of seven common obesity-related cancers. We considered five types of studies, including traditional epidemiologic studies examining adiposity at different time points, studies examining weight gain in specific life phases, studies examining weight loss over a period including from bariatric surgery, life course trajectory analysis, and Mendelian randomization studies. The results showed that lifetime excess body weight is associated with increased risk of cancers of endometrium, colorectum, liver, kidney, and pancreas. Early life obesity is one of the strongest risk factors for pancreatic cancer but less directly important than adult obesity for endometrial and kidney cancer. Interestingly, heavy weight during childhood, adolescence, and early adulthood is protective against pre- and postmenopausal breast cancer and possibly advanced prostate cancer. It is apparent that preventing weight gain later in adulthood would likely reduce risk of many cancers, including postmenopausal breast cancer, endometrial cancer, colorectal cancer (especially in men), liver cancer, kidney cancer, and probably advanced prostate cancer. Furthermore, weight loss even late in life may confer benefits for cancers of breast, endometrium, colorectum, and liver among patients with obesity, as mostly demonstrated by studies of bariatric surgery. Overall, maintaining a healthy weight throughout the life course will help prevent a large number of cancers.

Peking Union Health Application (PUHApp): Modern solution for effective epidemiological survey administration and health promotion

Large scale population-based epidemiological health surveys require effective administration. The diverse phenotype data sets also lead to challenge to quick and visual feedback of health check-up results or meeting the need of self-health management. With the rapid popularization of smartphone use, the smartphone-based applications bring about new inspirations for traditional epidemiological studies to fulfill various health and research needs. In 2015, we designed a software named Peking Union Health Application (PUHApp), which can be used noncommercially via smartphone or modern desktop web browser. PUHApp has been used by over 50 000 individuals to obtain their e-health reports. Diverse health data have been linked to this application. The module of self-health assessment and disease risk prediction modules enable individuals to estimate their physical fitness conveniently. By describing the concepts and usage of PUHApp, we aim to demonstrate its key role as modern solution for effective epidemiological survey administration and health promotion, and to provide practical cases that could be helpful for other researchers.

Using electronic medical record data to establish and monitor the distribution of refractive errors,

ObjectiveTo establish the baseline distribution of refractive errors and associated factors amongst a population that attended primary care optometry clinics. DesignRetrospective cross sectional cohort study of electronic medical records (EMR). MethodsElectronic medical record data was extracted from forty optometry clinics, representing a mix of urban and rural areas in Ireland. The analysis was confined to demographic and clinical data gathered over a sixty-month period between 2015 and 2019. Distribution rates were calculated using the absolute and relative frequencies of refractive error in the dataset, stratified for age and gender using the following definitions: high myopia ≤ -6.00 D, myopia ≤ -0.50 D, hyperopia ≥ +0.50 D, astigmatism ≤ -0.75 DC and anisometropia ≥ 1.00 D. Visual acuity data was used to explore vision impairment rates in the population. Further analysis was carried out on a gender and age-adjusted subset of the EMR data, to match the proportion of patients in each age grouping to the population distribution in the most recent (2016) Irish census. Results153,598 clinic records were eligible for analysis. Refractive errors ranged from -26.00 to +18.50 D. Myopia was present in 32.7%, of which high myopia represented 2.4%, hyperopia in 40.1%, astigmatism in 38.3% and anisometropia in 13.4% of participants. The clinic distribution of hyperopia, astigmatism and anisometropia peaked in older age groups, whilst the myopia burden was highest amongst people in their twenties. A higher proportion of females were myopic, whilst a higher proportion of males were hyperopic and astigmatic. Vision impairment (LogMAR > 0.3) was present in 2.4% of participants. In the gender and age- adjusted distribution model, myopia was the most common refractive state, affecting 38.8% of patients. ConclusionAlthough EMR data is not representative of the population as a whole, it is likely to provide a reasonable representation of the distribution of clinically significant (symptomatic) refractive errors. In the absence of any ongoing traditional epidemiological studies of refractive error in Ireland, this study establishes, for the first time, the distribution of refractive errors observed in clinical practice settings. This will serve as a baseline for future temporal trend analysis of the changing pattern of the distribution of refractive error in EMR data. This methodology could be deployed as a useful epidemiological resource in similar settings where primary eyecare coverage for the management of refractive error is well established.

Genetic Predisposition to Diabetes and Abdominal Aortic Aneurysm: A Two Stage Mendelian Randomisation Study

Observational studies demonstrate an inverse association between type II diabetes and abdominal aortic aneurysm (AAA) for reasons that are unclear. The aim of this study was to clarify the causal association between type II diabetes predisposition and AAA using Mendelian randomisation. Effect estimates for single nucleotide polymorphisms (SNPs) associated with diabetes were obtained from the DIAbetes Meta-ANalysis of Trans-Ethnic association studies (DIAMANTE) consortium to construct a genetic instrumental variable. Corresponding effect estimates for associations of these SNPs with AAA were obtained from the International Aneurysm Consortium comprising six separate AAA genomewide association studies (4 972 cases and 99 858 controls). Mendelian randomisation estimates were calculated using inverse variance, weighted median, and MR-Egger methods, and compared against recently published observational estimates. A genetic risk score was constructed from 206 SNPs associated with diabetes. All three Mendelian randomisation models showed no effect of genetic liability to diabetes and risk of AAA (inverse variance: odds ratio 1.04 per unit higher log odds, 95% 0.98 - 1.11, p= .19; MR-Egger slope p= .33; weighted median p= .50). Results were similar after excluding the TCF7L2 locus (inverse variance p= .075). Findings from the Mendelian randomisation analysis differed from previous observational reports of an inverse association (pdif < .001). Lifelong genetic predisposition to diabetes does not appear to protect against AAA. These findings differ from traditional epidemiological studies showing an inverse association between diabetes and AAA, for reasons that remain unclear.

Monitoring the safety of COVID-19 vaccines in pregnancy in the US

ABSTRACT Pregnant persons are at increased risk of severe illness from COVID-19. The first COVID-19 vaccines in the U.S. were authorized for emergency use in December 2020 and pregnant persons were eligible and could get vaccinated despite scarce safety data in this population. To monitor the safety of COVID-19 vaccination during pregnancy, four surveillance systems are used by the Centers for Disease Control and Prevention (CDC). The Vaccine Adverse Event Reporting System is a national, passive system that captures reports of potential adverse events. V-safe is a novel, active system that uses text messaging and web-based surveys to provide health check-ins after vaccination; and enrolls eligible v-safe participants in the v-safe pregnancy registry. The Vaccine Safety Datalink is a collaboration between the CDC and nine integrated health care organizations which performs near-real time surveillance and traditional epidemiologic studies on pregnant vaccine recipients. The CDC is committed to timely and comprehensive monitoring of COVID-19 vaccine safety in pregnancy.

Network Analysis in Systems Epidemiology.

Traditional epidemiological studies have identified a number of risk factors for various diseases using regression-based methods that examine the association between an exposure and an outcome (i.e., one-to-one correspondences). One of the major limitations of this approach is the “black-box” aspect of the analysis, in the sense that this approach cannot fully explain complex relationships such as biological pathways. With high-throughput data in current epidemiology, comprehensive analyses are needed. The network approach can help to integrate multi-omics data, visualize their interactions or relationships, and make inferences in the context of biological mechanisms. This review aims to introduce network analysis for systems epidemiology, its procedures, and how to interpret its findings.

Body mass index and risk of dying from a bloodstream infection: A Mendelian randomization study.

In observational studies of the general population, higher body mass index (BMI) has been associated with increased incidence of and mortality from bloodstream infection (BSI) and sepsis. On the other hand, higher BMI has been observed to be apparently protective among patients with infection and sepsis. We aimed to evaluate the causal association of BMI with risk of and mortality from BSI. We used a population-based cohort in Norway followed from 1995 to 2017 (the Trøndelag Health Study [HUNT]), and carried out linear and nonlinear Mendelian randomization analyses. Among 55,908 participants, the mean age at enrollment was 48.3 years, 26,324 (47.1%) were men, and mean BMI was 26.3 kg/m2. During a median 21 years of follow-up, 2,547 (4.6%) participants experienced a BSI, and 451 (0.8%) died from BSI. Compared with a genetically predicted BMI of 25 kg/m2, a genetically predicted BMI of 30 kg/m2 was associated with a hazard ratio for BSI incidence of 1.78 (95% CI: 1.40 to 2.27; p < 0.001) and for BSI mortality of 2.56 (95% CI: 1.31 to 4.99; p = 0.006) in the general population, and a hazard ratio for BSI mortality of 2.34 (95% CI: 1.11 to 4.94; p = 0.025) in an inverse-probability-weighted analysis of patients with BSI. Limitations of this study include a risk of pleiotropic effects that may affect causal inference, and that only participants of European ancestry were considered. Supportive of a causal relationship, genetically predicted BMI was positively associated with BSI incidence and mortality in this cohort. Our findings contradict the "obesity paradox," where previous traditional epidemiological studies have found increased BMI to be apparently protective in terms of mortality for patients with BSI or sepsis.

Comparative Circulation Dynamics of the Five Main HIV Types in China.

The HIV epidemic in China accounts for 3% of the global HIV incidence. We compared the patterns and determinants of interprovincial spread of the five most prevalent circulating types. HIV pol sequences sampled across China were used to identify relevant transmission networks of the five most relevant HIV-1 types (B and circulating recombinant forms [CRFs] CRF01_AE, CRF07_BC, CRF08_BC, and CRF55_01B) in China. From these, the dispersal history across provinces was inferred. A generalized linear model (GLM) was used to test the association between migration rates among provinces and several measures of human mobility. A total of 10,707 sequences were collected between 2004 and 2017 across 26 provinces, among which 1,962 are newly reported here. A mean of 18 (minimum and maximum, 1 and 54) independent transmission networks involving up to 17 provinces were identified. Discrete phylogeographic analysis largely recapitulates the documented spread of the HIV types, which in turn, mirrors within-China population migration flows to a large extent. In line with the different spatiotemporal spread dynamics, the identified drivers thereof were also heterogeneous but are consistent with a central role of human mobility. The comparative analysis of the dispersal dynamics of the five main HIV types circulating in China suggests a key role of large population centers and developed transportation infrastructures as hubs of HIV dispersal. This advocates for coordinated public health efforts in addition to local targeted interventions.IMPORTANCE While traditional epidemiological studies are of great interest in describing the dynamics of epidemics, they struggle to fully capture the geospatial dynamics and factors driving the dispersal of pathogens like HIV as they have difficulties capturing linkages between infections. To overcome this, we used a discrete phylogeographic approach coupled to a generalized linear model extension to characterize the dynamics and drivers of the across-province spread of the five main HIV types circulating in China. Our results indicate that large urbanized areas with dense populations and developed transportation infrastructures are facilitators of HIV dispersal throughout China and highlight the need to consider harmonized country-wide public policies to control local HIV epidemics.

Exploring Effects of Sociodemographic Inequities in Greenness Accessibility on theDevelopment of Allergic-related Respiratory Diseases in Children, Ontario

Greenness, linked with fresh air and active living environment, is thought to associate with various health benefits. The normalized difference vegetation index (NDVI), which has been the most widely used proxy for measuring green space in traditional epidemiological studies, does not effectively reflect access to greenness nor the attributes of the space. Therefore, it may not capture the relevant complex exposure pathways that impact human health, e.g. the development of childhood asthma.Given these issues, we have initiated a research project, funded by the Canadian Institute of Health Research (CIHR), to 1) create a matrix that measures greenness accessibility by the travel time of each residential location to its nearest greenness, including park and forest/natural space; and 2) to determine the associations between greenness accessibility and the risks of developing asthma, allergic rhinitis, bronchitis, and bronchiolitis in children. Accessibility of greenness will be measured by travel time regarding road types and condition, land use, and other geographic variables (e.g. altitude, slopes, rivers/lakes), as well as season, weather, air quality, travel modes, holidays, and the day of the week as proxies for people’s potential activities, which may provide a more precise daily-varying exposure measure of access. Additionally, we will compare our proposed matrix of greenness accessibility to the traditional NDVI in charactering the inequity of greenness exposure at both individual and community levels. Finally, we will assess if better greenness accessibility is associated with reduced risk of childhood asthma and other respiratory conditions. The study will include about one million healthy Ontario infants who were born between April 1st, 2006 and March 31st, 2014. Analysis will be stratified by and/or adjusted for individual and contextual covariates. Our study offers a novel matrix on greenness accessibility and also a comprehensive measure of the impact of exposure to greenness on young children's health.

Study design, size, and adequate exposure data as the crucial aspects in cancer risk assessment and implementation of the precautionary principle.

Traditional approaches and study design in cancer epidemiology have not been very successful in identifying and evaluating adequately the potential risk and/or protective factors associated with the disease. The main reasons for the failure are often due the small study sample size, and inadequate exposure information. In this paper, issues and approaches relevant to these two challenges are discussed. Multicentre study is proposed as a way to increase study size and to mitigate criticism about meta-analysis of independent studies. A multicentre study of large cohort or case-control studies also offer an exciting opportunity to study the contribution of epigenetic events that may be associated with lifestyle and environmental risk factors for human health. Optimizing methods for exposure assessment and how to reduce exposure to misclassification represent a difficult component in epidemiological studies. A potentially useful approach for improving exposure estimation is to rely on biomarkers of exposures. An example is provided to demonstrate how biomarkers of exposures could provide valuable information in addition to exposure measurements in traditional epidemiological studies. Finally, it is argued that risk assessment and the precautionary principle should not be viewed as conflicting paradigms but, rather, as a complementary approach for developing appropriate policies to address risks posed by exposure to carcinogens and a wide spectrum of other health hazards.

Abstract IA22: Insights from adopting a data commons approach: The California Teachers Study

Abstract Background: Cancer epidemiology studies offer unique value to the cancer research enterprise. With large populations and detailed data, including repeat measurements, collected over many years, cancer epidemiology studies contribute immensely to the understanding of real-world cancer risks and outcomes. To accelerate research, discovery, and translation, and to reduce the overall burden of cancer, the NCI has embraced the vision, as outlined by the Cancer Moonshot Blue Ribbon Panel, of creating a national cancer data ecosystem that enables “all participants across the cancer research and care continuum to contribute, access, combine, and analyze diverse data.” The cancer data ecosystem will integrate data from many domains using an overall infrastructure that leverages the elasticity, scalability, and security of cloud computing. The first components of the ecosystem are based on genomics and imaging. Other areas, including biomarkers, animal models, clinical trials, EHRs, and observational studies, will follow. Including data from the dozens of ongoing cancer epidemiology studies, and especially the prospective cancer epidemiology cohorts, that exist today would greatly enhance the cancer data ecosystem. However, many of these existing studies began before cloud computing existed and do not use cloud computing to store, manage, analyze, and share their data. Cancer epidemiology studies today must decide how to transition from their legacy data approaches to the types of cloud-first approach the national cancer data ecosystem requires. Methods: The California Teachers Study (CTS) is a large and prospective cancer epidemiology cohort that began in 1995-1996. In 2014, the CTS decided to adopt cloud computing to improve the quality, speed, and visibility of its data collection, management, analysis, and sharing. Since 2015, in partnership with the San Diego Supercomputer Center and funded by award U01-CA199277, the CTS has installed a new, innovative, and secure yet flexible infrastructure that includes a data warehouse, data marts, and shared workspace. Results: The CTS infrastructure contains the technical, security, data, and process features necessary to participate in the national cancer data ecosystem. Our novel solution serves as a prototype that other cancer epidemiology studies—and other observational studies and cohorts in general—can emulate. In designing, developing, and deploying this CTS solution, our team encountered a number of challenges that are likely not unique to the CTS and that other observational studies and cohorts are likely to encounter as they modernize their data and infrastructure. This presentation will discuss lessons learned in three key areas that the CTS encountered during our data-modernization process. First, although cancer epidemiology has always been multidisciplinary, the transition to a cancer data ecosystem creates opportunities for even broader collaborations with new partners, both public and private. Second, a central benefit of the national cancer data ecosystem is to process data via standardized pipelines. This should incentivize cancer epidemiology studies to prioritize standardization of common cancer epidemiologic data activities. Third, the cancer data ecosystem creates opportunities for new entities, and not just traditional NIH-funded cancer epidemiology studies, to meaningfully contribute to the observational research landscape. Although competition for funding and relevance seems likely to increase, the overall effects on the cancer research enterprise could be positive. Conclusion: Observational studies, and especially cancer epidemiology studies, will be a vital component of the national cancer data ecosystem, but existing cancer epidemiology studies will need to drastically and rapidly modernize their core data processes and infrastructure before that can occur. As an early adopter of cloud computing and the key foundational principles of the cancer data ecosystem, the CTS has developed a fully functioning and successful example of how existing cancer epidemiology studies can modernize their infrastructure in ways that preserve their unique strengths and further increase their immense potential and value. Citation Format: Jim Lacey. Insights from adopting a data commons approach: The California Teachers Study [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr IA22.