Objective: Signal detection analysis, a form of recursive partitioning, was used to identify combinations of sociodemographic and acculturation factors that predict trying to lose weight in a community-based sample of 957 overweight and obese Mexican-American adults (ages 18-69 years).
Design: Data were pooled from the 2004 and 2006 Behavioral Risk Factor Surveillance System conducted in a low-income, semi-rural community in California.
Results: Overall, 59 % of the population reported trying to lose weight. The proportion of adults who were trying to lose weight was highly variable across the seven mutually exclusive groups identified by signal detection (range 30-79 %). Significant predictors of trying to lose weight included BMI, gender, age and income. Women who were very overweight (BMI > 28.5 kg/m2) were most likely to be trying to lose weight (79 %), followed by very overweight higher-income men and moderately overweight (BMI = 25.0-28.5 kg/m2) higher-income women (72 % and 70 %, respectively). Moderately overweight men, aged 28-69 years, were the least likely to be trying to lose weight (30 %), followed by moderately overweight lower-income women (47 %) and very overweight lower-income men (49 %). The latter group is of particular concern since they have characteristics associated with medical complications of obesity (low education and poor access to medical care).
Conclusions: Our findings highlight opportunities and challenges for public health professionals working with overweight Mexican-American adults - particularly lower-income adults who were born in Mexico - who are not trying to lose weight and are therefore at high risk for obesity-related co-morbidities.