Guns, Suicide, and Homicide: Individual-Level Versus Population-Level Studies

2014 ◽  
Vol 160 (2) ◽  
pp. 134-135 ◽  
Author(s):  
David Hemenway
Keyword(s):  
Population Level ◽  
Individual Level ◽  
Level Versus

scholarly journals Blood Pressure Trajectories Across the Life Course

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.

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

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.

Medication Adherence: Expanding the Conceptual Framework

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.

scholarly journals Urine Spot Samples Can Be Used to Estimate 24-Hour Urinary Sodium Excretion in Children

2018 ◽  
Vol 148 (12) ◽  
pp. 1946-1953 ◽  
Author(s):  
Magali Rios-Leyvraz ◽  
Pascal Bovet ◽  
René Tabin ◽  
Bernard Genin ◽  
Michel Russo ◽  
...  
Keyword(s):  
Sodium Excretion ◽  
Salt Intake ◽  
Sodium Intake ◽  
Population Level ◽  
Urinary Sodium Excretion ◽  
Cross Sectional Study ◽  
Urinary Sodium ◽  
Cross Sectional ◽  
High Sodium ◽  
Individual Level

ABSTRACT Background The gold standard to assess salt intake is 24-h urine collections. Use of a urine spot sample can be a simpler alternative, especially when the goal is to assess sodium intake at the population level. Several equations to estimate 24-h urinary sodium excretion from urine spot samples have been tested in adults, but not in children. Objective The objective of this study was to assess the ability of several equations and urine spot samples to estimate 24-h urinary sodium excretion in children. Methods A cross-sectional study of children between 6 and 16 y of age was conducted. Each child collected one 24-h urine sample and 3 timed urine spot samples, i.e., evening (last void before going to bed), overnight (first void in the morning), and morning (second void in the morning). Eight equations (i.e., Kawasaki, Tanaka, Remer, Mage, Brown with and without potassium, Toft, and Meng) were used to estimate 24-h urinary sodium excretion. The estimates from the different spot samples and equations were compared with the measured excretion through the use of several statistics. Results Among the 101 children recruited, 86 had a complete 24-h urine collection and were included in the analysis (mean age: 10.5 y). The mean measured 24-h urinary sodium excretion was 2.5 g (range: 0.8–6.4 g). The different spot samples and equations provided highly heterogeneous estimates of the 24-h urinary sodium excretion. The overnight spot samples with the Tanaka and Brown equations provided the most accurate estimates (mean bias: −0.20 to −0.12 g; correlation: 0.48–0.53; precision: 69.7–76.5%; sensitivity: 76.9–81.6%; specificity: 66.7%; and misclassification: 23.0–27.7%). The other equations, irrespective of the timing of the spot, provided less accurate estimates. Conclusions Urine spot samples, with selected equations, might provide accurate estimates of the 24-h sodium excretion in children at a population level. At an individual level, they could be used to identify children with high sodium excretion. This study was registered at clinicaltrials.gov as NCT02900261.

scholarly journals Migration, acculturation, and the maintenance of between-group cultural variation

2017 ◽  
Author(s):  
Alex Mesoudi
Keyword(s):  
Social Learning ◽  
Cultural Values ◽  
Cultural Evolution ◽  
Population Level ◽  
Empirical Literature ◽  
Cultural Variation ◽  
Individual Level ◽  
And Migration ◽  
The Individual ◽  
Social Learning Processes

AbstractHow do migration and acculturation (i.e. psychological or behavioral change resulting from migration) affect within- and between-group cultural variation? Here I answer this question by drawing analogies between genetic and cultural evolution. Population genetic models show that migration rapidly breaks down between-group genetic structure. In cultural evolution, however, migrants or their descendants can acculturate to local behaviors via social learning processes such as conformity, potentially preventing migration from eliminating between-group cultural variation. An analysis of the empirical literature on migration suggests that acculturation is common, with second and subsequent migrant generations shifting, sometimes substantially, towards the cultural values of the adopted society. Yet there is little understanding of the individual-level dynamics that underlie these population-level shifts. To explore this formally, I present models quantifying the effect of migration and acculturation on between-group cultural variation, for both neutral and costly cooperative traits. In the models, between-group cultural variation, measured using F statistics, is eliminated by migration and maintained by conformist acculturation. The extent of acculturation is determined by the strength of conformist bias and the number of demonstrators from whom individuals learn. Acculturation is countered by assortation, the tendency for individuals to preferentially interact with culturally-similar others. Unlike neutral traits, cooperative traits can additionally be maintained by payoff-biased social learning, but only in the presence of strong sanctioning institutions. Overall, the models show that surprisingly little conformist acculturation is required to maintain realistic amounts of between-group cultural diversity. While these models provide insight into the potential dynamics of acculturation and migration in cultural evolution, they also highlight the need for more empirical research into the individual-level learning biases that underlie migrant acculturation.

scholarly journals Electroencephalographic Evidence for Individual Neural Inertia in Mice That Decreases With Time

2022 ◽  
Vol 15 ◽  
Author(s):  
Andrzej Z. Wasilczuk ◽  
Qing Cheng Meng ◽  
Andrew R. McKinstry-Wu
Keyword(s):  
Stochastic Model ◽  
Path Dependence ◽  
Inbred Mice ◽  
Population Level ◽  
Supervised Machine Learning ◽  
State Transitions ◽  
Intrinsic Resistance ◽  
Linear Discriminant ◽  
Individual Level ◽  
Increased Risk

Previous studies have demonstrated that the brain has an intrinsic resistance to changes in arousal state. This resistance is most easily measured at the population level in the setting of general anesthesia and has been termed neural inertia. To date, no study has attempted to determine neural inertia in individuals. We hypothesize that individuals with markedly increased or decreased neural inertia might be at increased risk for complications related to state transitions, from awareness under anesthesia, to delayed emergence or confusion/impairment after emergence. Hence, an improved theoretical and practical understanding of neural inertia may have the potential to identify individuals at increased risk for these complications. This study was designed to explicitly measure neural inertia in individuals and empirically test the stochastic model of neural inertia using spectral analysis of the murine EEG. EEG was measured after induction of and emergence from isoflurane administered near the EC50 dose for loss of righting in genetically inbred mice on a timescale that minimizes pharmacokinetic confounds. Neural inertia was assessed by employing classifiers constructed using linear discriminant or supervised machine learning methods to determine if features of EEG spectra reliably demonstrate path dependence at steady-state anesthesia. We also report the existence of neural inertia at the individual level, as well as the population level, and that neural inertia decreases over time, providing direct empirical evidence supporting the predictions of the stochastic model of neural inertia.

scholarly journals Modelling the HIV-Associated TB Epidemic and the Impact of Interventions Aimed at Epidemic Control

2019 ◽  
pp. 25-55
Author(s):  
P. J. Dodd ◽  
C. Pretorius ◽  
B. G. Williams
Keyword(s):  
Natural History ◽  
Mathematical Models ◽  
Population Level ◽  
Explicit Representation ◽  
Epidemic Control ◽  
Future Directions ◽  
Individual Level ◽  
Tuberculosis Epidemiology ◽  
History Of ◽  
The Impact

Abstract In this chapter, we focus on mathematical models of tuberculosis epidemiology (TB) that include interactions with HIV and an explicit representation of transmission. We review the natural history of TB and illustrate how its features are simplified and incorporated in mathematical models. We then review the ways HIV influences the natural history of TB, the interventions that have been considered in models, and the way these individual-level effects are represented in models. We then go on to consider population-level effects, reviewing the TB/HIV modelling literature. We first review studies whose focus was on purely epidemiological modelling, and then studies whose focus was on modelling the impact of interventions. We conclude with a summary of the uses and achievements of TB/HIV modelling and some suggested future directions.

scholarly journals General intelligence disentangled via a generality metric for natural and artificial intelligence

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
José Hernández-Orallo ◽  
Bao Sheng Loe ◽  
Lucy Cheke ◽  
Fernando Martínez-Plumed ◽  
Seán Ó hÉigeartaigh
Keyword(s):  
Task Difficulty ◽  
Population Level ◽  
Limited Resources ◽  
General Intelligence ◽  
Individual Level ◽  
Cognitive Efficiency ◽  
Comprehensive Performance ◽  
Individual Measure ◽  
Level Of Difficulty ◽  
The Individual

AbstractSuccess in all sorts of situations is the most classical interpretation of general intelligence. Under limited resources, however, the capability of an agent must necessarily be limited too, and generality needs to be understood as comprehensive performance up to a level of difficulty. The degree of generality then refers to the way an agent’s capability is distributed as a function of task difficulty. This dissects the notion of general intelligence into two non-populational measures, generality and capability, which we apply to individuals and groups of humans, other animals and AI systems, on several cognitive and perceptual tests. Our results indicate that generality and capability can decouple at the individual level: very specialised agents can show high capability and vice versa. The metrics also decouple at the population level, and we rarely see diminishing returns in generality for those groups of high capability. We relate the individual measure of generality to traditional notions of general intelligence and cognitive efficiency in humans, collectives, non-human animals and machines. The choice of the difficulty function now plays a prominent role in this new conception of generality, which brings a quantitative tool for shedding light on long-standing questions about the evolution of general intelligence and the evaluation of progress in Artificial General Intelligence.

scholarly journals Ecology and Prediction of Compensatory Growth: From Theory to Application in Forestry

2021 ◽  
Vol 12 ◽  
Author(s):  
Chao Li ◽  
Hugh Barclay ◽  
Bernard Roitberg ◽  
Robert Lalonde
Keyword(s):  
Compensatory Growth ◽  
Population Level ◽  
Human Society ◽  
Common Phenomenon ◽  
Partial Mortality ◽  
Individual Level ◽  
State Dependent ◽  
Dependent Model ◽  
Accelerated Growth ◽  
The Individual

Compensatory growth has been observed in forests, and it also appears as a common phenomenon in biology. Though it sometimes takes different names, the essential meanings are the same, describing the accelerated growth of organisms when recovering from a period of unfavorable conditions such as tissue damage at the individual level and partial mortality at the population level. Diverse patterns of compensatory growth have been reported in the literature, ranging from under-, to compensation-induced-equality, and to over-compensation. In this review and synthesis, we provide examples of analogous compensatory growth from different fields, clarify different meanings of it, summarize its current understanding and modeling efforts, and argue that it is possible to develop a state-dependent model under the conceptual framework of compensatory growth, aimed at explaining and predicting diverse observations according to different disturbances and environmental conditions. When properly applied, compensatory growth can benefit different industries and human society in various forms.

scholarly journals Opposite outcomes of coinfection at individual and population scales

2018 ◽  
Vol 115 (29) ◽  
pp. 7545-7550 ◽  
Author(s):  
Erin E. Gorsich ◽  
Rampal S. Etienne ◽  
Jan Medlock ◽  
Brianna R. Beechler ◽  
Johannie M. Spaan ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Negative Impact ◽  
Scale Up ◽  
Population Level ◽  
Clear Understanding ◽  
African Buffalo ◽  
Global Public Health ◽  
Individual Level ◽  
Secondary Infections ◽  
The Individual

Coinfecting parasites and pathogens remain a leading challenge for global public health due to their consequences for individual-level infection risk and disease progression. However, a clear understanding of the population-level consequences of coinfection is lacking. Here, we constructed a model that includes three individual-level effects of coinfection: mortality, fecundity, and transmission. We used the model to investigate how these individual-level consequences of coinfection scale up to produce population-level infection patterns. To parameterize this model, we conducted a 4-y cohort study in African buffalo to estimate the individual-level effects of coinfection with two bacterial pathogens, bovine tuberculosis (bTB) and brucellosis, across a range of demographic and environmental contexts. At the individual level, our empirical results identified bTB as a risk factor for acquiring brucellosis, but we found no association between brucellosis and the risk of acquiring bTB. Both infections were associated with reductions in survival and neither infection was associated with reductions in fecundity. The model reproduced coinfection patterns in the data and predicted opposite impacts of coinfection at individual and population scales: Whereas bTB facilitated brucellosis infection at the individual level, our model predicted the presence of brucellosis to have a strong negative impact on bTB at the population level. In modeled populations where brucellosis was present, the endemic prevalence and basic reproduction number (R0) of bTB were lower than in populations without brucellosis. Therefore, these results provide a data-driven example of competition between coinfecting pathogens that occurs when one pathogen facilitates secondary infections at the individual level.

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