Comparison of individual-level and population-level risk factors for rhinoconjunctivitis, asthma, and eczema in the International Study of Asthma and Allergies in Childhood (ISAAC) Phase Three

ObjectiveThe purpose of this research is to identify how data science is applied in suicide prevention literature, describe the current landscape of this literature and highlight areas where data science may be useful for future injury prevention research.DesignWe conducted a literature review of injury prevention and data science in April 2020 and January 2021 in three databases.MethodsFor the included 99 articles, we extracted the following: (1) author(s) and year; (2) title; (3) study approach (4) reason for applying data science method; (5) data science method type; (6) study description; (7) data source and (8) focus on a disproportionately affected population.ResultsResults showed the literature on data science and suicide more than doubled from 2019 to 2020, with articles with individual-level approaches more prevalent than population-level approaches. Most population-level articles applied data science methods to describe (n=10) outcomes, while most individual-level articles identified risk factors (n=27). Machine learning was the most common data science method applied in the studies (n=48). A wide array of data sources was used for suicide research, with most articles (n=45) using social media and web-based behaviour data. Eleven studies demonstrated the value of applying data science to suicide prevention literature for disproportionately affected groups.ConclusionData science techniques proved to be effective tools in describing suicidal thoughts or behaviour, identifying individual risk factors and predicting outcomes. Future research should focus on identifying how data science can be applied in other injury-related topics.

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A unifying framework for depression: Bridging the major biological and psychosocial theories through stress

Clinical & Investigative Medicine ◽

10.25011/cim.v36i4.19951 ◽

2013 ◽

Vol 36 (4) ◽

pp. 170 ◽

Cited By ~ 21

Author(s):

Amrita Roy ◽

M Karen Campbell

Keyword(s):

Risk Factors ◽

Psychosocial Stress ◽

Structural Changes ◽

Population Level ◽

Brain Regions ◽

Multiple Systems ◽

Individual Level ◽

The Social ◽

Chronic Psychosocial Stress ◽

Social Causes

Several mechanisms for the development of depression have been proposed, and a comparative examination reveals considerable overlap. This paper begins by summarizing the conclusions drawn in the literature on the major biological theories: HPA-axis hyperactivity, the monoamine theory, the cytokine hypothesis/ macrophage theory, and structural changes to relevant brain regions and neurons. It then discusses the role of psychosocial stress as a bridge between the pathophysiology of depression and its predominantly psychosocial risk factors, touching upon theories offered in psychology and in population health. This paper further proposes a unifying framework which integrates the major theories. The multiple systems involved, and the directional complexity among them, likely help to explain the wide-ranging symptoms associated with depression, and the wide variety of comorbid medical conditions. They may also contribute to challenges in treatment, the diversity in symptoms and treatment outcomes among individuals, and the high rates of symptom persistence and relapse. The apparent bi-directionality of associations may suggest the existence of positive-feedback loops which aggravate symptoms; however, further bench research is required to confirm such phenomena. A better understanding of these interweaving associations is warranted. Additionally, given the significant influence of socioeconomic and psychosocial factors on the aetiology of depression, population-level interventions that address the social determinants of health are required. Current individual-level pharmacologic approaches are designed to treat pathophysiology once it is underway, and current individual-level non-pharmacologic interventions (such as talk therapy) are designed to moderate the relationship between psychosocial stress and pathophysiology. In contrast, a key strategy for primary prevention lies in population-level interventions that address the predominantly social causes of one of depression’s most notable risk factors: chronic psychosocial stress.

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Population level risk factors associated with childhood obesity

Obesity Abstracts ◽

10.1530/obabs.01.rfc2.6 ◽

2019 ◽

Author(s):

Claire Beynon ◽

Nora Pashyan ◽

Elizabeth Fisher ◽

Dougal Hargreaves ◽

Linda Bailey ◽

...

Keyword(s):

Risk Factors ◽

Childhood Obesity ◽

Population Level ◽

Factors Associated

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Dementia Prevention at the Population Level: Modifiable Risk Factors

American Journal of Geriatric Psychiatry ◽

10.1016/j.jagp.2021.02.007 ◽

2021 ◽

Vol 29 (4) ◽

pp. S9-S10

Author(s):

Kristine Yaffe

Keyword(s):

Risk Factors ◽

Population Level ◽

Modifiable Risk Factors ◽

Dementia Prevention

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Blood Pressure Trajectories Across the Life Course

American Journal of Hypertension ◽

10.1093/ajh/hpab009 ◽

2021 ◽

Vol 34 (3) ◽

pp. 234-241

Author(s):

Norrina B Allen ◽

Sadiya S Khan

Keyword(s):

Blood Pressure ◽

Measurement Errors ◽

Clinical Care ◽

Population Level ◽

Cumulative Exposure ◽

Older Adulthood ◽

Individual Level ◽

The Life Course ◽

Level Group ◽

Improve Health

Abstract High blood pressure (BP) is a strong modifiable risk factor for cardiovascular disease (CVD). Longitudinal BP patterns themselves may reflect the burden of risk and vascular damage due to prolonged cumulative exposure to high BP levels. Current studies have begun to characterize BP patterns as a trajectory over an individual’s lifetime. These BP trajectories take into account the absolute BP levels as well as the slope of BP changes throughout the lifetime thus incorporating longitudinal BP patterns into a single metric. Methodologic issues that need to be considered when examining BP trajectories include individual-level vs. population-level group-based modeling, use of distinct but complementary BP metrics (systolic, diastolic, mean arterial, mid, and pulse pressure), and potential for measurement errors related to varied settings, devices, and number of readings utilized. There appear to be very specific developmental periods during which divergent BP trajectories may emerge, specifically adolescence, the pregnancy period, and older adulthood. Lifetime BP trajectories are impacted by both individual-level and community-level factors and have been associated with incident hypertension, multimorbidity (CVD, renal disease, cognitive impairment), and overall life expectancy. Key unanswered questions remain around the additive predictive value of BP trajectories, intergenerational contributions to BP patterns (in utero BP exposure), and potential genetic drivers of BP patterns. The next phase in understanding BP trajectories needs to focus on how best to incorporate this knowledge into clinical care to reduce the burden of hypertensive-related outcomes and improve health equity.

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Examining the Effects of the Sacramento Dockless E-Bike Share on Bicycling and Driving

Sustainability ◽

10.3390/su13010368 ◽

2021 ◽

Vol 13 (1) ◽

pp. 368

Author(s):

Dillon T. Fitch ◽

Hossain Mohiuddin ◽

Susan L. Handy

Keyword(s):

Travel Behavior ◽

Regression Models ◽

Population Level ◽

Panel Survey ◽

Multilevel Regression ◽

Combine Data ◽

Cross Sectional ◽

Individual Level ◽

Before And After ◽

Bike Share

One way cities are looking to promote bicycling is by providing publicly or privately operated bike-share services, which enable individuals to rent bicycles for one-way trips. Although many studies have examined the use of bike-share services, little is known about how these services influence individual-level travel behavior more generally. In this study, we examine the behavior of users and non-users of a dockless, electric-assisted bike-share service in the Sacramento region of California. This service, operated by Jump until suspended due to the coronavirus pandemic, was one of the largest of its kind in the U.S., and spanned three California cities: Sacramento, West Sacramento, and Davis. We combine data from a repeat cross-sectional before-and-after survey of residents and a longitudinal panel survey of bike-share users with the goal of examining how the service influenced individual-level bicycling and driving. Results from multilevel regression models suggest that the effect of bike-share on average bicycling and driving at the population level is likely small. However, our results indicate that people who have used-bike share are likely to have increased their bicycling because of bike-share.

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Geographical variation and clustering are found in atrial fibrillation beyond socioeconomic differences: a Danish cohort study, 1987–2015

International Journal of Health Geographics ◽

10.1186/s12942-021-00264-2 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Kirstine Wodschow ◽

Kristine Bihrmann ◽

Mogens Lytken Larsen ◽

Gunnar Gislason ◽

Annette Kjær Ersbøll

Keyword(s):

Risk Factors ◽

Atrial Fibrillation ◽

Cohort Study ◽

Incidence Rate ◽

Socioeconomic Position ◽

Geographical Variation ◽

Incidence Rates ◽

Socioeconomic Differences ◽

Individual Level ◽

Geographical Variations

Abstract Background The prevalence and incidence rate of atrial fibrillation (AF) increase worldwide and AF is a risk factor for more adverse cardiovascular diseases including stroke. Approximately 44% of AF cases cannot be explained by common individual risk factors and risk might therefore also be related to the environment. By studying geographical variation and clustering in risk of incident AF adjusted for socioeconomic position at an individual level, potential neighbourhood risk factors could be revealed. Methods Initially, yearly AF incidence rates 1987–2015 were estimated overall and stratified by income in a register-based cohort study. To examine geographical variation and clustering in AF, we used both spatial scan statistics and a hierarchical Bayesian Poisson regression analysis of AF incidence rates with random effect of municipalities (n = 98) in Denmark in 2011–2015. Results The 1987–2015 cohort included 5,453,639 individuals whereof 369,800 were diagnosed with an incident AF. AF incidence rate increased from 174 to 576 per 100,000 person-years from 1987 to 2015. Inequality in AF incidence rate ratio between highest and lowest income groups increased from 23% in 1987 to 38% in 2015. We found clustering and geographical variation in AF incidence rates, with incidence rates at municipality level being up to 34% higher than the country mean after adjusting for socioeconomic position. Conclusions Geographical variations and clustering in AF incidence rates exist. Compared to previous studies from Alberta, Canada and the United States, we show that geographical variations exist in a country with free access to healthcare and even when accounting for socioeconomic differences at an individual level. An increasing social inequality in AF was seen from 1987 to 2015. Therefore, when planning prevention strategies, attention to individuals with low income should be given. Further studies focusing on identification of neighbourhood risk factors for AF are needed.

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Medication Adherence: Expanding the Conceptual Framework

American Journal of Hypertension ◽

10.1093/ajh/hpab046 ◽

2021 ◽

Author(s):

Marie Krousel-Wood ◽

Leslie S Craig ◽

Erin Peacock ◽

Emily Zlotnick ◽

Samantha O’Connell ◽

...

Keyword(s):

Older Adults ◽

Medication Adherence ◽

Conceptual Framework ◽

Clinical Outcomes ◽

Implicit Attitudes ◽

Explanatory Power ◽

Population Level ◽

Time Preferences ◽

Adherence Behavior ◽

Individual Level

Abstract Interventions targeting traditional barriers to antihypertensive medication adherence (AHMA) have been developed and evaluated, with evidence of modest improvements in adherence. Translation of these interventions into population-level improvements in adherence and clinical outcomes among older adults remains suboptimal. From the Cohort Study of Medication Adherence among Older adults (CoSMO), we evaluated traditional barriers to AHMA among older adults with established hypertension (N=1544; mean age=76.2 years, 59.5% women, 27.9% Black, 24.1% and 38.9% low adherence by proportion of days covered (i.e., PDC<0.80) and the 4-item Krousel-Wood Medication Adherence Scale (i.e., K-Wood-MAS-4≥1), respectively), finding that they explained 6.4% and 14.8% of variance in pharmacy refill and self-reported adherence, respectively. Persistent low adherence rates, coupled with low explanatory power of traditional barriers, suggest that other factors warrant attention. Prior research has investigated explicit attitudes toward medications as a driver of adherence; the roles of implicit attitudes and time preferences (e.g., immediate versus delayed gratification) as mechanisms underlying adherence behavior are emerging. Similarly, while associations of individual-level social determinants of health (SDOH) and medication adherence are well-reported, there is growing evidence about structural SDOH and specific pathways of effect. Building on published conceptual models and recent evidence, we propose an expanded conceptual framework that incorporates implicit attitudes, time preferences and structural SDOH, as emerging determinants that may explain additional variation in objectively and subjectively measured adherence. This model provides guidance for design, implementation and assessment of interventions targeting sustained improvement in implementation medication adherence and clinical outcomes among older women and men with hypertension.

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