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

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

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

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

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

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

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

Add Health Wave IV Documentation: Lipids

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)

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

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

Depression, Stressful Life Events, and the Impact of Variation in the Serotonin Transporter: Findings from the National Longitudinal Study of Adolescent to Adult Health (Add Health)

BackgroundThe low transcriptionally efficient short-allele of the 5HTTLPR serotonin transporter polymorphism has been implicated to moderate the relationship between the experience of stressful life events (SLEs) and depression. Despite numerous attempts at replicating this observation, results remain inconclusive.MethodsWe examined this relationship in young-adult Non-Hispanic white males and females between the ages of 22 and 26 (n = 4724) participating in the National Longitudinal Study of Adolescent to Adult Health (Add Health) with follow-up information every six years since 1995.ResultsLinear and logistic regression models, corrected for multiple testing, indicated that carriers of one or more of the S-alleles were more sensitive to stress than those with two L-alleles and at a higher risk for depression. This relationship behaved in a dose-response manner such that the risk for depression was greatest among those who reported experiencing higher numbers of SLEs. In post-hoc analyses we were not able to replicate an interaction effect for suicide ideation but did find suggestive evidence that the effects of SLEs and 5HTTLPR on suicide ideation differed for males and females. There were no effects of childhood maltreatment.DiscussionOur results provide partial support for the original hypothesis that 5-HTTLPR genotype interacts with the experience of stressful life events in the etiology of depression during young adulthood. However, even with this large sample, and a carefully constructed a priori analysis plan, the results were still not definitive. For the purposes of replication, characterizing the 5HTTLPR in other large data sets with extensive environmental and depression measures is needed

Add Health Wave IV Documentation: Cardiovascular Measures Appendix I: Baroreflex Sensitivity and Hemodynamic Recovery

This is an appendix to Add Health Wave IV Documentation: Cardiovascular and Anthropometric Measures (Entzel et al., 2009). Please refer to that user guide for complete descriptions of the cardiovascular data collection procedures and measures disseminated by the study at that time. In addition to the measures described there, this appendix introduces three more constructed measures that are included in the Add Health Wave IV public use data: Baroreflex sensitivity Pulse rate recovery Systolic blood pressure recovery. The rationale for their estimation and description of their quality control are provided below

Social, Behavioral, and Genetic Linkages from Adolescence Into Adulthood

The influence of genetic factors on health and behavior is conditioned by social, cultural, institutional, and physical environments in which individuals live, work, and play. We encourage studies supporting multilevel integrative approaches to understanding these contributions to health, and describe the Add Health study as an exemplar