31 research outputs found

    Substance abuse prevention infrastructure: a survey-based study of the organizational structure and function of the D.A.R.E. program

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    BACKGROUND: The only national drug abuse prevention delivery system that supports the rapid diffusion of new prevention strategies and includes uniform training and credentialing of instructors who are monitored for quality implementation of prevention programming is the Drug Abuse Resistance Education network (D.A.R.E.) linking community law enforcement to schools. Analysis of the organizational structure and function of D.A.R.E. provides an understanding of the essential parameters of this successful delivery system that can be used in the development of other types of national infrastructures for community-based prevention services. Information regarding organizational structure and function around funding issues, training, quality control and community relationships was gathered through telephone surveys with 50 state D.A.R.E. coordinators (including two major cities), focus groups with local D.A.R.E. officers and mentors, and interviews with national D.A.R.E. office staff. RESULTS: The surveys helped identify several strengths inherent in the D.A.R.E. program necessary for building a prevention infrastructure, including a well-defined organizational focus (D.A.R.E. America), uniform training and means for rapid dissemination (through its organized training structure), continuing education mechanisms (through the state and national conference and website), mechanisms for program monitoring and fidelity of implementation (formal and informal), branding and, for several states, predictable and consistent financing. Weaknesses of the program as currently structured include unstable funding and the failure to incorporate components for the continual upgrading of curricula reflecting research evidence and "principles of prevention". CONCLUSION: The D.A.R.E. organization and service delivery network provides a framework for the rapid dissemination of evidence-based prevention strategies. The major strength of D.A.R.E. is its natural affiliation to local law enforcement agencies through state coordinators. Through these affiliations, it has been possible for D.A.R.E. to become established nationally within a few years and internationally within a decade. Understanding how this structure developed and currently functions provides insights into how other such delivery systems could be developed

    The National Longitudinal Study of Adolescent to Adult Health (Add Health) Sibling Pairs Genome-Wide Data

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    Here we provide a detailed description of the genome-wide information available on the National Longitudinal Study of Adolescent to Adult Health (Add Health) sibling pair subsample (Harris et al., 2012). A total of 2020 samples were genotyped (including duplicates) arising from 1946 Add Health individuals from the sibling pairs subsample. After various steps for quality control (QC) and quality assurance (QA), we have high quality genome-wide data available on 1,888 individuals. In this report, we first highlight theQC and QA steps that were taken to prune the data of poorly performing samples and genetic markers. We further estimate the pairwise biological relationships using genome-wide data and compare those estimates to the assumed relationships in Add Health. Additionally, using genome-wide data from knownregional reference populations from Europe, West Africa, North and South America, Japan and China, weestimate the relative genetic ancestry of the respondents. Finally, rather than conducting a traditional cross-sectional genome-wide association study (GWAS) of body mass index (BMI), we opted to utilize the extensivepublicly available genome-wide information to conduct a weighted genome-wide association study (GWAS) of longitudinal BMI while accounting for both family and ethnic variation

    Living Arrangements in Young Adulthood: Results from Wave IV of the National Longitudinal Study of Adolescent Health

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    "Over the past few decades, there has been a lengthening of the transition period from adolescence to adulthood in the United States. Milestones commonly associated with entering adulthood – such as finishing school, landing a job, marrying, buying a home, and starting a family – are occurring at later ages. Increasingly, young adults are depending on their families to support them – both financially and emotionally – as they take on adult roles.1,2 Economic times are also harder for this generation than previous ones. Even before the start of the latest recession, employment prospects and associated wages were on the decline for young adults in North America, especially for men.3 Living arrangements in young adulthood have shifted as a result of these new social and economic realities. The traditional paradigm – a married couple living with children in a home that they own – no longer “fits” for a substantial proportion of the young adult population. This brief provides a portrait of the living arrangements of young adults in the U.S. in 2008, before the start of the latest recession. Using data from the National Longitudinal Study of Adolescent Health (Add Health), we examine three important household characteristics: living arrangements, home ownership, and household composition. We explore patterns in these characteristics by gender, age, race/ethnicity, marital status, educational level, and personal income. We address the following questions: Where are young adults in their late twenties and early thirties living? Do they own their place of residence? Who lives with them? Although we cannot yet examine the effect of the most recent recession on the Add Health cohort, this brief lays the groundwork for future post-recession analyses.

    Changes in Statin Adherence Following an Acute Myocardial Infarction Among Older Adults: Patient Predictors and the Association With Follow‐Up With Primary Care Providers and/or Cardiologists

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    BACKGROUND: Hospitalizations for acute myocardial infarctions (AMIs) are associated with changes in statin adherence. It is unclear to what extent adherence changes, which patients are likely to change, and how post-discharge follow-up is associated with statin adherence change. METHODS AND RESULTS: This retrospective study used Medicare data for all fee-for-service beneficiaries 66 years and older with an AMI hospitalization in 2008-2010 and statin use before their index AMI. Multivariable multinomial logistic regression models (odds ratio [OR] and 99% confidence interval [CI]) were applied to assess associations between both patient characteristics and follow-up with a primary care provider and/or cardiologist with the outcome of statin adherence change (increase or decrease) from the 6-month pre- to 6-month post-AMI periods. Of 113 296 patients, 64.0% had no change in adherence, while 19.7% had increased and 16.3% had decreased adherence after AMI hospitalization. Black and Hispanic patients were more likely to have either increased or decreased adherence than white patients. Patients who required coronary artery bypass graft surgery (OR, 1.34; 99% CI, 1.21-1.49) or percutaneous transluminal coronary angioplasty/stent procedure (OR, 1.25; 99% CI, 1.17-1.32) during their index hospitalization were more likely to have increased adherence. Follow-up with a primary care provider was only mildly associated with increased adherence (OR, 1.08; 99% CI, 1.00-1.16), while follow-up with a cardiologist (OR, 1.15; 99% CI, 1.05-1.25) or both provider types (OR, 1.21; 99% CI, 1.12-1.30) had stronger associations with increased adherence. CONCLUSIONS: Post-AMI changes in statin adherence varied by patient characteristics, and improved adherence was associated with post-discharge follow-up care, particularly with a cardiologist or both a primary care provider and a cardiologist

    Add Health Wave IV Documentation: Measures of Inflammation and Immune Function

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    During Wave IV, Add Health collected biological specimens from a large, nationally representative sample of young adults. Given the size of the Wave IV sample, its geographic distribution, and in-home setting of the respondent interviews, biological specimen collection involved practical, relatively non-invasive, cost-efficient and innovative methods. These methods included collection of capillary whole blood via finger prick by trained and certified field interviewers, its in situ desiccation, then shipment, assay and archival of dried blood spots. The collection of capillary whole blood followed the collection of cardiovascular and anthropometric measures (Entzel et al, 2009) and saliva (Smolen et al, 2012). It preceded the collection of data on respondent use of prescription and select over-the-counter medications (Tabor et al, 2010). Further details on the design of Add Health Waves I-IV, are available elsewhere (Harris, 2011). Included in the Add Health Wave IV data are two measures of inflammation and immune function based on assay of the dried blood spots: • High Sensitivity C-Reactive Protein (hsCRP, mg/L) and • Epstein Barr Viral Capsid Antigen IgG (EBV, AU/ml) To facilitate analysis and interpretation of hsCRP and EBV, the restricted-use Add Health Wave IV data also include two data quality flags and 11constructed measures: • CRP_FLAG • EBV_FLAG • Classification of hsCRP (Pearson et al, 2003) • Count of Common Subclinical Symptoms (Vaidya et al, 2006) • Count of Common Infectious or Inflammatory Diseases • NSAID/Salicylate Medication Use in the Past 24 Hours • NSAID/Salicylate Medication Use in the Past 4 Weeks • Cox-2 Inhibitor Medication Use in the Past 4 Weeks • Inhaled Corticosteroid Medication Use in the Past 4 Weeks • Corticotropin/Glucocorticoid Medication Use in the Past 4 Weeks • Anti-rheumatic/Anti-psoriatic Medication Use in the Past 4 Weeks • Immunosuppressive Medication Use in the Past 4 Weeks • Anti-inflammatory Medication Use. This document summarizes the rationale, equipment, protocol, assay, internal quality control, data cleaning, external quality control, and classification procedures for each measure listed above. Measures of glucose homeostasis and candidate genes are documented elsewhere 3 (Whitsel et al, 2012; Smolen et al, 2012). Documentation of lipids will be provided in a separate report

    Add Health Wave IV Documentation: Candidate Genes

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    During Wave IV, Add Health collected biological specimens from a large, nationally representative sample of young adults. Given the size of the Wave IV sample, its geographic distribution, and in-home setting of the respondent interviews, biological specimen collection involved practical, relatively non-invasive, cost-efficient and innovative methods. These methods included collection of saliva by trained and certified field interviewers, salivary buccal cell lysis and DNA stabilization in the field, then shipment to a central lab for DNA extraction, genotyping, and archiving. The collection of saliva followed the interview and collection of cardiovascular and anthropometric measures (Entzel et al. 2009). It preceded the collection of capillary whole blood (Whitsel et al. 2012) and data on respondent use of prescription and select over-the-counter medications (Tabor et al. 2010). Further details on the design of Add Health Waves I-IV are available elsewhere (Harris 2012; Harris et al. in press)

    Add Health Wave IV Documentation: Measures of Glucose Homeostasis

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    During Wave IV, Add Health collected biological specimens from a large, nationally representative sample of young adults. Given the size of the Wave IV sample, its geographic distribution, and in-home setting of the respondent interviews, biological specimen collection involved practical, relatively non-invasive, cost-efficient and innovative methods. These methods included collection of capillary whole blood via finger prick by trained and certified field interviewers, its in situ desiccation, then shipment, assay and archival of dried blood spots. The collection of capillary whole blood followed the collection of cardiovascular and anthropometric measures (Entzel et al., 2009) and saliva (in preparation). It preceded the collection of data on respondent use of prescription and select over-the-counter medications (Tabor et al., 2010). Further details on the design of Add Health Waves I-IV, are available elsewhere (Harris, 2011). Included in the Add Health Wave IV data are two measures of glucose homeostasis based on assay of the dried blood spots: • Glucose (mg/dl) and • Hemoglobin A1c (HbA1c, %). To facilitate analysis and interpretation of HbA1c, the restricted-use Add Health Wave IV data also include a trichotomous flag distinguishing the original (0) from two types (1,2) of inter-converted assay results (see Section 4.2.3.3): • Convert (0,1,2) Moreover, the restricted-use Add Health Wave IV data include six constructed measures: • Fasting duration (h) • Classification of fasting glucose (ADA, 2011) • Classification of non-fasting glucose (ADA, 2011) • Classification of HbA1c (ADA, 2011) • Anti-diabetic medication use • Joint classification of glucose, HbA1c, self-reported history of diabetes, and anti-diabetic medication use. This document summarizes the rationale, equipment, protocol, assay, internal quality control, data cleaning, external quality control, and classification procedures for each measure listed above. Documentation of other (metabolic; inflammatory; immune; genetic) measures based on assay of the dried blood spots and genotyping of DNA extracted from salivary buccal cells will be provided in separate reports

    Genotype, Childhood Maltreatment, and Their Interaction in the Etiology of Adult Antisocial Behaviors

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    BACKGROUND: Maltreatment by an adult or caregiver during childhood is a prevalent and important predictor of antisocial behaviors in adulthood. A functional promoter polymorphism in the monoamine oxidase A (MAOA) gene has been implicated as a moderating factor in the relationship between childhood maltreatment and antisocial behaviors. Although there have been numerous attempts at replicating this observation, results remain inconclusive. METHODS: We examined this gene-environment interaction hypothesis in a sample of 3356 white and 960 black men (aged 24-34) participating in the National Longitudinal Study of Adolescent Health. RESULTS: Primary analysis indicated that childhood maltreatment was a significant risk factor for later behaviors that violate rules and the rights of others (p .05). Power analyses indicated that these results were not due to insufficient statistical power. CONCLUSIONS: We could not confirm the hypothesis that MAOA genotype moderates the relationship between childhood maltreatment and adult antisocial behaviors

    Add Health Wave IV Documentation: Lipids

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    During Wave IV, Add Health collected biological specimens from a large, nationally representative sample of young adults. Given the size of the Wave IV sample, its geographic distribution, and in-home setting of the respondent interviews, biological specimen collection involved practical, relatively non-invasive, cost-efficient and innovative methods. These methods included collection of capillary whole blood via finger prick by trained and certified field interviewers, its in situ desiccation, then shipment, assay and archival of dried blood spots. The collection of capillary whole blood followed the collection of cardiovascular and anthropometric measures (Entzel et al. 2009) and saliva (Smolen et al. 2013). It preceded the collection of data on respondent use of prescription and select over-the-counter medications (Tabor et al. 2010). Further details on the design of Add Health Waves I-IV, are available elsewhere (Harris 2012; Harris et al. in press). Included in the Add Health Wave IV restricted use and public use data are thirteen constructed measures designed to facilitate analysis and interpretation of lipids results: • Total cholesterol decile • High-density lipoprotein cholesterol decile • Triglycerides decile • Total cholesterol measurement method • High-density lipoprotein cholesterol measurement method • Triglycerides measurement method • Low-density lipoprotein cholesterol decile • Non-high-density lipoprotein cholesterol decile • Total to high-density lipoprotein cholesterol ratio decile • Fasting duration • Fasted for nine hours or more • Antihyperlipidemic medication use • Hyperlipidemia. This document summarizes the rationale, equipment, protocol, assay, internal quality control, data cleaning, external quality control, and classification procedures for each measure listed above. Measures of glucose homeostasis, inflammation, immune function, and candidate genes are documented elsewhere (Whitsel et al. 2012a, 2012b; Smolen et al. 2013)
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