Annual incidence rates of hip symptoms and three hip OA outcomes from a U.S. population-based cohort study: the Johnston County Osteoarthritis Project.

Objective: Estimate annual incidence rates (IRs) of hip symptoms and three osteoarthritis (OA) outcomes (radiographic, symptomatic, and severe radiographic) overall and by race, sociodemographic characteristics, and hip OA risk factors.

Design: Analyze baseline (1991-1997) and first follow-up (1999-2003) data (n = 1446) from the Johnston County Osteoarthritis Project, a population-based, prospective study of adults ≥45 years in North Carolina. Hip symptoms were pain, aching, and/or stiffness on most days, or groin pain.

Annual Incidence of Knee Symptoms and Four Knee Osteoarthritis Outcomes in the Johnston County Osteoarthritis Project.

Objective: To estimate annual incidence rates (IRs) of knee symptoms and 4 knee osteoarthritis (OA) outcomes (radiographic, symptomatic, severe radiographic, and severe symptomatic), overall and stratified by sociodemographic characteristics and knee OA risk factors.

Methods: We analyzed baseline (1991-1997) and first followup (1999-2003) data (n = 1,518) from the Johnston County Osteoarthritis Project. Participants were African American and white adults, ages ≥45 years, living in Johnston County, North Carolina, US.

Genetic association analysis under complex survey sampling: the Hispanic Community Health Study/Study of Latinos.

The cohort design allows investigators to explore the genetic basis of a variety of diseases and traits in a single study while avoiding major weaknesses of the case-control design. Most cohort studies employ multistage cluster sampling with unequal probabilities to conveniently select participants with desired characteristics, and participants from different clusters might be genetically related. Analysis that ignores the complex sampling design can yield biased estimation of the genetic association and inflation of the type I error.

Local Dependence in Latent Class Analysis of Rare and Sensitive Events.

For survey methodologists, latent class analysis (LCA) is a powerful tool for assessing the measurement error in survey questions, evaluating survey methods, and estimating the bias in estimates of population prevalence. LCA can be used when gold standard measurements are not available and applied to essentially any set of indicators that meet certain criteria for identifiability. LCA offers quality inference, provided the key threat to model validity-namely, local dependence-can be appropriately addressed either in the study design or in the model-building process.

Meeting physical activity guidelines and the risk of incident knee osteoarthritis: a population-based prospective cohort study.

Objective: Knee osteoarthritis (OA) is a leading cause of disability and joint pain. Although other risk factors of knee OA have been identified, how physical activity affects incident knee OA remains unclear.

Methods: Using data from the first (1999-2004) and second (2005-2010) followup periods of the Johnston County Osteoarthritis Project study, we tested the association between meeting physical activity guidelines and incident knee outcomes among 1,522 adults ages ≥45 years.