A School–Family Partnership: Addressing Multiple Risk Factors to Improve School Readiness and Prevent Conduct Problems in Young Children

2010 ◽  
pp. 222-245
Keyword(s):  
Risk Factors ◽  
Young Children ◽  
School Readiness ◽  
Conduct Problems ◽  
Multiple Risk Factors ◽  
Family Partnership ◽  
Multiple Risk

Preschool-Aged Siblings of Adjudicated Youths: Multiple Risk Factors for Conduct Problems

2004 ◽  
Vol 15 (4) ◽  
pp. 387-406 ◽  
Author(s):  
Laurie Miller Brotman ◽  
Kathleen Kiely Gouley ◽  
Colleen O'Neal ◽  
Rachel G. Klein
Keyword(s):  
Risk Factors ◽  
Conduct Problems ◽  
Multiple Risk Factors ◽  
Multiple Risk

Managing Multiple Risk Factors

1998 ◽  
Author(s):  
Charlie M. Lolis ◽  
Keyword(s):  
Risk Factors ◽  
Multiple Risk Factors ◽  
Multiple Risk

The relative and interactive impact of multiple risk factors in schizophrenia spectrum disorders: a combined register-based and clinical twin study

2021 ◽  
pp. 1-11
Author(s):  
C. Lemvigh ◽  
R. Brouwer ◽  
R. Hilker ◽  
S. Anhøj ◽  
L. Baandrup ◽  
...  
Keyword(s):  
Risk Factors ◽  
Environmental Factors ◽  
Childhood Trauma ◽  
Cannabis Use ◽  
Paternal Age ◽  
Interactive Effects ◽  
Polygenic Risk Score ◽  
Multiple Risk Factors ◽  
Schizophrenia Spectrum ◽  
Multiple Risk

Abstract Background Research has yielded evidence for genetic and environmental factors influencing the risk of schizophrenia. Numerous environmental factors have been identified; however, the individual effects are small. The additive and interactive effects of multiple risk factors are not well elucidated. Twin pairs discordant for schizophrenia offer a unique opportunity to identify factors that differ between patients and unaffected co-twins, who are perfectly matched for age, sex and genetic background. Methods Register data were combined with clinical data for 216 twins including monozygotic (MZ) and dizygotic (DZ) proband pairs (one or both twins having a schizophrenia spectrum diagnosis) and MZ/DZ healthy control (HC) pairs. Logistic regression models were applied to predict (1) illness vulnerability (being a proband v. HC pair) and (2) illness status (being the patient v. unaffected co-twin). Risk factors included: A polygenic risk score (PRS) for schizophrenia, birth complications, birth weight, Apgar scores, paternal age, maternal smoking, season of birth, parental socioeconomic status, urbanicity, childhood trauma, estimated premorbid intelligence and cannabis. Results The PRS [odds ratio (OR) 1.6 (1.1–2.3)], childhood trauma [OR 4.5 (2.3–8.8)], and regular cannabis use [OR 8.3 (2.1–32.7)] independently predicted illness vulnerability as did an interaction between childhood trauma and cannabis use [OR 0.17 (0.03–0.9)]. Only regular cannabis use predicted having a schizophrenia spectrum diagnosis between patients and unaffected co-twins [OR 3.3 (1.1–10.4)]. Conclusion The findings suggest that several risk factors contribute to increasing schizophrenia spectrum vulnerability. Moreover, cannabis, a potentially completely avoidable environmental risk factor, seems to play a substantial role in schizophrenia pathology.

Association between second-hand smoking and acute coronary heart disease among Arab women with multiple risk factors

2015 ◽  
Vol 26 (1) ◽  
pp. 141-145 ◽  
Author(s):  
Khaled Awawdi ◽  
Hillel Steiner ◽  
Manfred S. Green ◽  
Shira Zelber-Sagi
Keyword(s):  
Risk Factors ◽  
Coronary Heart Disease ◽  
Heart Disease ◽  
Arab Women ◽  
Multiple Risk Factors ◽  
Multiple Risk ◽  
Second Hand Smoking

Multiple Risk Factors Before Pediatric Cardiac Transplantation Are Associated With Increased Graft Loss

2011 ◽  
Vol 33 (1) ◽  
pp. 49-54 ◽  
Author(s):  
Scott R. Auerbach ◽  
Marc E. Richmond ◽  
Jonathan M. Chen ◽  
Ralph S. Mosca ◽  
Jan M. Quaegebeur ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiac Transplantation ◽  
Graft Loss ◽  
Multiple Risk Factors ◽  
Multiple Risk

Abstract P672: Black White Disparity in Multiple Risk Factors is Increased in Older Young Adults

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Prachi Mehndiratta ◽  
Kathleen Ryan ◽  
Adeolu Morawo ◽  
Seemant Chaturvedi ◽  
Carolyn A Cronin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Young Adults ◽  
Stroke Risk ◽  
Reference Group ◽  
Population Based ◽  
Multiple Risk Factors ◽  
Stroke In Young Adults ◽  
Multiple Risk ◽  
The Relationship ◽  
Control Study

Background: Stroke in young adults constitutes 15-18% of all ischemic strokes. Vascular risk factors contribute to stroke risk in young adults particularly older young adults. Few studies have addressed Black White differences in risk, stratified by age. We evaluated the prevalence of risk factors in the younger young (less than 40 years) vs. the older young adults (40 and above). Methods: A population based case control study with 1034 cases and 1091 controls, ages 15-49 was used to investigate the relationship between risk factors (DM, HTN, Smoking and Obesity) and stroke. Groups were defined by the number of risk factors (RF) among cases and controls : no risk factors (ref group), one RF, two RF, three RF and four RF. Prevalence of risk factors was determined in the entire population and stratified by age, sex and race. Logistic regression was used to determine odds of stroke based on the number of risk factors compared to the reference group. Results: The percent of cases with three or more risk factors was compared in different subgroups: ages 15-39 vs. 40-49 was 8.4 vs. 21.6, women vs. men was 15.6 vs. 18.6 and White vs. Black was 12.3 vs. 22.7. Among cases 40 years and older, Blacks were 3 times more likely than Whites (5.9 vs. 2) to have four or more risk factors.Across all age, race and sex subgroups, the odds of having a stroke increased exponentially with an increase in the number of risk factors. Conclusion: Blacks are more likely to have multiple risk factors than Whites. This difference is accentuated in those 40 years and older. Targeting young adults with multiple risk factors for preventive interventions would address a root case of excess stroke risk especially among Blacks.

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