American Journal of Health Promotion

To determine the prevalence of major depressive disorder (MDD) by smoking status, and the temporal relationship between smoking and MDD, and explore other smoking-related variables that may be associated with MDD.

Cross-sectional study.

Public primary care clinics.

Researchers studied 338 women (76% African-Americans) who were randomly selected while attending appointments in two public primary care clinics.

Data pertaining to smoking-related variables and MDD diagnosis were obtained using the Diagnostic Interview Schedule for the Diagnostic Statistical Manual of Mental Disorders IV (DSM-IV).

The prevalence of a lifetime history of MDD was significantly higher for current smokers (56.6%) than among former smokers (37.5%) or never-smokers (30.3%; p < .001). Most ever-smokers (81.3%) began smoking and were nicotine-dependent (63.6%) prior to their first episode of MDD. Using logistic regression, after controlling for demographic and smoking-related variables, age of smoking onset was the strongest variable associated with MDD among ever-smokers. Specifically, the odds of having an MDD decreased by 8.2% for each year delay in smoking initiation.

These results suggest that smoking initiation precedes MDD and that smoking is associated with a high prevalence of MDD among low-income women attending primary care clinics. Further, the younger women start smoking the more likely they are to have MDD.

The purpose of this research was to use a three-phase ethnographic approach to examine the range of factors that affect people's decisions about physical activity and diet.

We used open-ended data collection strategies, analyzed inductively, to inform the development of a family intervention.

The study was conducted in a small low-income town in Colorado.

Families with young children were selected to include social, economic, and ethnic diversity. Twenty-nine of 31 invited families participated (94%).

The measures consisted of 21 open-ended interviews in the first phase; 12 semistructured interviews in the second phase, and six home visits in the third phase. The Atlas.ti program²⁵ was used for data analysis.

Significant barriers to regular exercise and good dietary habits were grouped as social/structural (e.g., working parents, costs of exercise) and cultural (e.g., perception that fast food is normal). Behavioral facilitators include disease in the family and community opportunities for exercise. Results revealed family values and dynamics that other methods would have missed.

These data suggest that families are embedded in a multicomponent “web” of factors that influence diet and physical activity. It is feasible and desirable to use ethnographic methods to discern the interactions of these factors that make each household unique. These results argue for dynamic intervention designs that operate from a broad contextual perspective.