Add Health Wave IV Documentation: Prescription Medication Use

Data on respondent use of prescription and select over-the-counter (aspirin-containing and non-steroidal anti-inflammatory) medications were collected during the Wave IV in-home interview. The process of collecting the prescription medication data, therapeutically classifying the prescription medications, and structuring a file of the therapeutic classifications for dissemination to users is described below. The questions concerning use of aspirin-containing and non-steroidal anti-inflammatory medications are detailed in the Section 6 codebook of the in-home interview

Non-Response in Wave IV of the National Longitudinal Study of Adolescent Health

Non-response is a potential threat to the accuracy of estimates obtained from sample surveys and can be particularly difficult to avoid in longitudinal studies. The objective of this report is to investigate non-response and consequent bias in estimates for Wave IV of the National Longitudinal Study of Adolescent Health (Add Health). The Survey Research Unit at the University of North Carolina at Chapel Hill previously analyzed the non-response rates for the first three waves of Add Health. As shown in Chantala, Kalsbeek and Andraca, 2005, the total bias in Waves I, II, and III for 13 measures of health and risk behaviors rarely exceed 1%, which is small relative to the 20% to 80% prevalence rates for most of these measures. Results are similar for Wave IV. In this paper, first, we outline the Wave IV sampling design and results of the field work. Second, we characterize the non-response rates overall and stratified by a number of demographic variables. Next, we use data on the health risk measures reported by Wave IV responders and non-responders during their Wave I In-home interview to estimate total and relative bias due to non-response in Wave IV. We conclude with a discussion of Wave IV bias due to non-response

Add Health Wave IV Documentation: Cardiovascular and Anthropometric Measures

During the Wave II and III in-home interviews, Add Health collected measures of respondent height and weight. To better understand the social, behavioral and biological linkages in health trajectories as the Add Health cohort ages through adulthood, the Wave IV study design included an expanded set of anthropometric measures as well as several new measures of cardiovascular health. The Wave IV cardiovascular and anthropometric measures were collected in the following order: • Blood pressure cuff size • Systolic blood pressure (SBP, mmHg) • Diastolic blood pressure (DBP, mmHg) • Pulse rate (PR, beats/min) • Height (cm) • Weight (kg) • Waist circumference (cm); In addition, the Add Health Wave IV data set includes the following constructed measures, derived from those listed above: • Blood pressure classification1 • Pulse pressure (mmHg) • Mean arterial pressure (mmHg) • Body mass index (BMI, kg/m2) • BMI classification; This document summarizes the rationale, measurement, equipment, protocol and data cleaning procedures for each of the cardiovascular and anthropometric measures collected at Wave IV. It also documents how constructed variables were derived from the cardiovascular and anthropometric measures collected in the field. Documentation of other Wave IV biological measures, including metabolic, inflammatory, immune and genetic measures, will be provided in separate reports

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 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: 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

Discordance in National Estimates of Hypertension Among Young Adults

In the U.S., where coronary heart disease (CHD) is the leading cause of mortality, CHD risk assessment is a priority and accurate blood pressure (BP) measurement is essential

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)

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

Blood spot–based measures of glucose homeostasis and diabetes prevalence in a nationally representative population of young US adults

We investigated under-studied, biomarker-based diabetes among young U.S. adults, traditionally characterized by low cardiovascular disease risk