Purpose To estimate the prevalence of refractive errors in adult Chinese Americans, and evaluate factors associated with myopia and high myopia. Design A population-based, cross-sectional study. Methods Chinese Americans 50 years and older residing in Monterey Park, California, were recruited. Noncycloplegic automated refraction with supplemental subjective refraction was performed. Myopia, high myopia, hyperopia, and high hyperopia were defined as a spherical equivalent of < −0.5 diopter (D), < −5.0D, > +0.5D, and ≥ +3.0D, respectively. Astigmatism and high astigmatism were defined as a cylinder of > 0.5D and > 2.25D, respectively. Risk factor assessment was guided by a conceptual model. Results Data from 4144 participants were analyzed. The overall prevalence of myopia, high myopia, hyperopia, high hyperopia, astigmatism, and high astigmatism was 35.1% (95% confidence interval, 33.6%–36.6%), 7.4% (6.6%–8.3%), 40.2% (38.7%–41.8%), 2.7% (2.2%–3.3%), 45.6% (44.1%–47.2%), and 3.7% (3.1%–4.3%), respectively. The prevalence of myopia and high myopia was lower among older individuals (Ps < 0.05). Reversed age trends were observed for the other refractive errors (Ps < 0.05). There was no sex difference in the prevalence of refractive errors, except for a higher prevalence of hyperopia among females (P = 0.010). Age, acculturation, education, income, marital status, birth country, history of ocular disease, non-ocular comorbidities, and recent eye exam were associated with prevalence of myopia. All of these factors, except for acculturation, were also associated with high myopia. Conclusions Our data present the first population-based estimates of the prevalence of refractive errors among adult Chinese Americans. Compared with whites, Hispanics, and blacks, Chinese Americans have a higher burden of myopia, high myopia, and astigmatism.

The Healthy Communities Study is designed to assess relationships between characteristics of community programs and policies targeting childhood obesity and children’s BMI, diet, and physical activity. The study involved a complex data collection protocol implemented over a 2-year period (2013–2015) across a diverse sample of up to 125 communities, defined as public high school catchment areas. The protocol involved baseline assessment within each community that included in-person or telephone interviews regarding community programs and policies and in-home collection of BMI, nutritional, and physical activity outcomes from a sample of up to 81 children enrolled in kindergarten through eighth grade in public schools. The protocol also involved medical record reviews to establish a longitudinal trajectory of BMI for an estimated 70% of participating children. Staged sampling was used to collect less detailed measures of physical activity and nutrition across the entire sample of children, with a subset assessed using more costly, burdensome, and detailed measures. Data from the Healthy Community Study will be analyzed using both cross-sectional and longitudinal models that account for the complex design and correct for measurement error and bias using a likelihood-based Markov chain Monte Carlo methodology. This methods paper provides insights into the complex design features of the Healthy Communities Study and may serve as an example for future large-scale studies that assess the relationship between community-based programs and policies and health outcomes of community residents.

These data provide the first population-based estimates of MD in Chinese Americans and indicate that a high proportion of Chinese Americans might be at risk for MD and associated visual complications. Prevalence of MD in this cohort of Chinese Americans was higher than that observed in other East Asian populations and in people of other ethnicities.

The Healthy Communities Study (HCS) is examining how characteristics of community programs and policies targeting childhood obesity are related to childhood diet, physical activity, and obesity outcomes. The study involves selected districts and public schools in 130 communities; families recruited through schools; and data collected at the community, school, household, and child levels. Data collection took place in two waves—Wave 1 in Spring 2012 and Wave 2 from 2013 to 2015—with analysis to be completed by August 2016. This paper describes operational elements of the HCS, including recruitment activities, field operations, training of data collectors, human subjects protection, and quality assurance and quality control procedures. Experienced trainers oversaw and conducted all training, including training of: (1) district and school recruitment staff; (2) telephone interviewers for household screening and recruitment; (3) field data collectors for conducting household data collection; and (4) community liaisons for conducting key informant interviews, document abstraction, and community observations. The study team developed quality assurance and quality control procedures that were implemented for all aspects of the study. Planning and operationalizing a study of this complexity and magnitude, with multiple functional teams, required frequent communication and strong collaboration among all study partners to ensure timely and effective decision making.

No abstract