scholarly journals Biomarkers for aging identified in cross-sectional studies tend to be non-causative

2019 ◽  
Author(s):  
Paul G. Nelson ◽  
Daniel E. L. Promislow ◽  
Joanna Masel
Keyword(s):  
Longitudinal Studies ◽  
Mortality Rates ◽  
Cross Sectional ◽  
Causal Factors ◽  
Physiological Conditions ◽  
Biomarkers Of Aging ◽  
Cohort Selection ◽  
The Status ◽  
Cross Sectional Studies ◽  
Sectional Analysis

AbstractBiomarkers are important tools for diagnosis, prognosis, and identification of the causal factors of physiological conditions. Biomarkers are typically identified by correlating biological measurements with the status of a condition in a sample of subjects. Cross-sectional studies sample subjects at a single timepoint, while longitudinal studies follow a cohort through time. Identifying biomarkers of aging is subject to unique challenges. Individuals who age faster have intrinsically higher mortality rates and so are preferentially lost over time, in a phenomenon known as cohort selection. In this paper, we use simulations to show that cohort selection biases cross-sectional analysis away from identifying causal loci of aging, to the point where cross-sectional studies are less likely to identify loci that cause aging than if loci had been chosen at random. We go on to show this bias can be corrected by incorporating correlates of mortality identified from longitudinal studies, allowing cross sectional studies to effectively identify the causal factors of aging.

scholarly journals Biomarkers for Aging Identified in Cross-sectional Studies Tend to Be Non-causative

2019 ◽  
Vol 75 (3) ◽  
pp. 466-472 ◽  
Author(s):  
Paul G Nelson ◽  
Daniel E L Promislow ◽  
Joanna Masel
Keyword(s):  
Longitudinal Studies ◽  
Mortality Rates ◽  
Cross Sectional ◽  
Causal Factors ◽  
Physiological Conditions ◽  
Biomarkers Of Aging ◽  
Cohort Selection ◽  
The Status ◽  
Cross Sectional Studies ◽  
Sectional Analysis

Abstract Biomarkers are important tools for diagnosis, prognosis, and identification of the causal factors of physiological conditions. Biomarkers are typically identified by correlating biological measurements with the status of a condition in a sample of subjects. Cross-sectional studies sample subjects at a single timepoint, whereas longitudinal studies follow a cohort through time. Identifying biomarkers of aging is subject to unique challenges. Individuals who age faster have intrinsically higher mortality rates and so are preferentially lost over time, in a phenomenon known as cohort selection. In this article, we use simulations to show that cohort selection biases cross-sectional analysis away from identifying causal loci of aging, to the point where cross-sectional studies are less likely to identify loci that cause aging than if loci had been chosen at random. We go on to show this bias can be corrected by incorporating correlates of mortality identified from longitudinal studies, allowing cross-sectional studies to effectively identify the causal factors of aging.

Cross-Sectional and Longitudinal Studies

2021 ◽  
pp. 72-76
Author(s):  
Andrew Bell
Keyword(s):  
Longitudinal Studies ◽  
Repeated Measures ◽  
Survival Duration ◽  
Data Sets ◽  
Cross Sectional ◽  
Comparison Time ◽  
Cross Sectional Studies ◽  
Sectional Analysis ◽  
Unit Of Observation ◽  
Over Time

This chapter focuses on cross-sectional and longitudinal studies. cross-sectional studies involve the analysis of usually quantitative data collected at a single snapshot in time. The unit of observation might be people or countries, and those are measured only once, all at approximately the same time. In contrast, longitudinal studies (also referred to as repeated measures studies) involve analysis on multiple occasions over time, where the same individuals (or countries) — the panel — are measured on each occasion. As such, the unit of observation is occasions, and there are multiple occasions/measures of each individual. A subcategory of longitudinal studies is event-history/survival/duration analysis, where the dependent variable is binary and the focus is on causes of changes between the two states of the outcome. Note that in comparison, time series analysis typically involves fewer individuals (often only one) and a larger number of time points. A third type of study, situated in between longitudinal and cross-sectional studies, is repeated cross-sectional analysis, which involves the analysis of multiple cross-sectional data sets over time, and different individuals are measured in each wave of the survey. Here, the unit of observation is individuals, and there are multiple individuals measured in each survey wave.

scholarly journals The impact of the COVID-19 pandemic on socio-economic and sustainability

2021 ◽  
Author(s):  
Xueli Wei ◽  
Lijing Li ◽  
Fan Zhang
Keyword(s):  
World Economy ◽  
Social Economy ◽  
Secondary Data ◽  
Well Being ◽  
Cross Sectional ◽  
The Social ◽  
The World ◽  
The Status ◽  
Sectional Analysis ◽  
The Impact

Pumping elephantThe COVID-19 pandemic has adversely affected the lives of people around the world in millions of ways . Due to this severe epidemic, all countries in the world have been affected by all aspects, mainly economic. It is widely discussed that the COVID-19 outbreak has affected the world economy. When considering this dimension, this study aims to examine the impact of the COVID-19 pandemic on the world economy, socio-economics, and sustainability. In addition, the research focuses on multiple aspects of social well-being during the pandemic, such as employment, poverty, the status of women, food security, and global trade. To this end, the study used time series and cross-sectional analysis of the data. The second-hand data used in this study comes from the websites of major international organizations. From the analysis of secondary data, the conclusion of this article is that the impact of the pandemic is huge. The main finding of the thesis is that the social economy is affected by the pandemic, causing huge losses in terms of economic well-being and social capital.

scholarly journals The Fundamentals of Longitudinal Research: An Overview

2001 ◽  
Vol 28 (2) ◽  
pp. 169 ◽  
Author(s):  
Fernando Rajulton
Keyword(s):  
Longitudinal Data ◽  
Longitudinal Studies ◽  
Historical Development ◽  
Longitudinal Research ◽  
Special Issue ◽  
Cross Sectional ◽  
Complicating Factors ◽  
Cross Sectional Studies

This paper outlines briefly the historical development of ideas related to longitudinal studies and their advantages over cross-sectional studies. Then it points out a few complicating factors that arise with the analysis of longitudinal data and highlights some of the approaches adopted to manage those complicating factors and illustrated in the papers included in this Special Issue. The overall aim is to promote a better understanding of the information that longitudinal data provide and of the suitable techniques needed to analyze such data.

Interunit and Intraunit Reliability of the RT3 Triaxial Accelerometer

2008 ◽  
Vol 5 (4) ◽  
pp. 527-538 ◽  
Author(s):  
Joanne B. Krasnoff ◽  
Michael A. Kohn ◽  
Frankie K.K. Choy ◽  
Julie Doyle ◽  
Kirsten Johansen ◽  
...  
Keyword(s):  
Physical Activity ◽  
Longitudinal Studies ◽  
Data Interpretation ◽  
Triaxial Accelerometer ◽  
Good Reliability ◽  
Cross Sectional ◽  
Coefficients Of Variation ◽  
Cross Sectional Studies ◽  
A Performance

Background:Interest in the quantification of physical activity is on the rise. Tri-axial accelerometry has frequently been used; however, research on the reliability of these devices is limited. We examine the interunit and intraunit reliability of 22 RT3 triaxial accelerometers using a performance-documented laboratory agitator.Methods:The RT3 units were tested while moving in 2 directions (antero-posterior, medio-lateral) and speeds (150 and 275 RPM) on a shaker with simultaneous documented performance output for three 24-hour periods.Results:Minimal shaker variance was recorded for all trials (coefficients of variation [CVs] < 0.52%). Our data demonstrate good reliability within RT3s (CVs < 1.81%) but poor reliability among the 22 units (CVs range = 9.5% to 34.7%).Conclusions:In longitudinal studies, each subject should use the same RT3 unit at each assessment. The use of multiple RT3 units in cross-sectional studies is not recommended because data interpretation would be compromised by the high between-unit variability.

Usability and acceptability of balance exergames in older adults: A scoping review

2016 ◽  
Vol 22 (4) ◽  
pp. 911-931 ◽  
Author(s):  
Ather Nawaz ◽  
Nina Skjæret ◽  
Jorunn Lægdheim Helbostad ◽  
Beatrix Vereijken ◽  
Elisabeth Boulton ◽  
...  
Keyword(s):  
Older Adults ◽  
Video Games ◽  
Muscle Strength ◽  
Longitudinal Studies ◽  
Scoping Review ◽  
Postural Balance ◽  
Serious Games ◽  
Cross Sectional ◽  
Developmental Approach ◽  
Cross Sectional Studies

Serious games (exergames) have the potential to be effective for postural balance and increasing muscle strength. Several games have been developed to increase physical fitness and balance among older adults. However, it is unclear to which degree usability and acceptability of exergames for older adults have been evaluated. The aim of this study was to summarize usability evaluation and acceptability of studies in older adults. We conducted a scoping review on studies focusing on usability of exergames for older adults. The result shows that older adults consider usability and acceptability of exercise video games good. The review shows that longitudinal studies mainly use off-the-shelf exergame and evaluated game effectiveness and acceptability, whereas cross-sectional studies focus on interactional experience. Studies varied in their approaches to measure usability and acceptability of exergames for older adults. There is a need for a systematic developmental approach to involve older adults in development of exergames for longitudinal studies.

Alcoholism and Personality

2002 ◽  
Vol 36 (1) ◽  
pp. 46-51 ◽  
Author(s):  
Roger T Mulder
Keyword(s):  
High Risk ◽  
Alcohol Dependence ◽  
Longitudinal Studies ◽  
Antisocial Behaviour ◽  
Negative Emotionality ◽  
Personality Measures ◽  
Novelty Seeking ◽  
Cross Sectional ◽  
Personality Variables ◽  
Cross Sectional Studies

Objective: The search for an alcoholic personality has been pursued with varying enthusiasm throughout the 20th century. This paper reviews the methodological issues, research designs and current theories relating alcoholism and personality. Method: A selected literature search using computerised databases was ordered via the four major research design strategies: cross sectional studies, high-risk studies, longitudinal studies and genetic epidemiology studies. Results: Cross sectional studies have suggested that two broad bands of personality, impulsivity/novelty seeking and neuroticism/negative emotionality, are associated with alcoholism. Although high-risk studies have repeatedly shown that sons of male alcoholics are at increased risk of alcoholism, whether this risk is related to personality variables is unclear. Many authors believe that the presence of antisocial personality disorder is a confounder and that this may explain some of the contradictory findings. Longitudinal studies have consistently reported that antisocial behaviour and hyperactivity are related to later alcoholism. Negative emotionality seems to be less important and may largely be a consequence of the alcoholism itself. Genetic epidemiological studies suggest that personality measures play a modest but significant role in the genetic influence of alcoholism. The strongest relationships are with conduct disorder and antisocial behaviour. The postulated alcoholic subtypes (Type I, Type II or Type A/B) based on age of onset and personality style have been challenged by recent research. The most vulnerable to alcoholism may be those with both high impulsivity/high novelty seeking and high neuroticism/negative emotionality. Conclusion: Antisocial behaviour and hyperactivity are the most consistent behaviours associated with alcoholism. These behaviours are not specific for alcoholism and are associated with many other psychiatric conditions. Personality variables by themselves explain only a small proportion of the risk for alcohol dependence. There is no alcoholic personality nor are there personality measures which are specific to vulnerability to later alcohol dependence. Attempting to link alcoholism with theoretical, poorly validated models of personality is premature.

scholarly journals Associations of AT(N) biomarkers with neuropsychiatric symptoms in preclinical Alzheimer’s disease and cognitively unimpaired individuals

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Kok Pin Ng ◽  
Hui Chiew ◽  
Pedro Rosa-Neto ◽  
Nagaendran Kandiah ◽  
Zahinoor Ismail ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Longitudinal Studies ◽  
Neuropsychiatric Symptoms ◽  
Amyloid Β ◽  
Cross Sectional ◽  
Preclinical Ad ◽  
Cross Sectional Studies

AbstractThe development of in vivo biomarkers of Alzheimer’s disease (AD) has advanced the diagnosis of AD from a clinical syndrome to a biological construct. The preclinical stage of AD continuum is defined by the identification of AD biomarkers crossing the pathological threshold in cognitively unimpaired individuals. While neuropsychiatric symptoms (NPS) are non-cognitive symptoms that are increasingly recognized as early manifestations of AD, the associations of NPS with AD pathophysiology in preclinical AD remain unclear. Here, we review the associations between NPS and AD biomarkers amyloid-β (Aβ), tau and neurodegeneration in preclinical AD and cognitively-unimpaired individuals in 19 eligible English-language publications (8 cross-sectional studies, 10 longitudinal, 1 both cross-sectional and longitudinal). The cross-sectional studies have consistently shown that NPS, particularly depressive and anxiety symptoms, are associated with higher Aβ. The longitudinal studies have suggested that greater NPS are associated with higher Aβ and cognitive decline in cognitively unimpaired subjects over time. However, most of the studies have either cross-sectionally or longitudinally shown no association between NPS and tau pathology. For the association of NPS and neurodegeneration, two studies have shown that the cerebrospinal fluid total-tau is linked to longitudinal increase in NPS and that the NPS may predict longitudinal metabolic decline in preclinical AD, respectively. However, evidence for the association between atrophy and NPS in preclinical AD is less consistent. Therefore, future longitudinal studies with well-designed methodologies and NPS measurements are required not only to determine the relationship among AT(N) biomarkers, NPS and cognitive decline, but also to elucidate the contribution of comorbid pathology to preclinical AD.

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