Abstrak: By using data from wave 2 (in 1996) and wave 3 (in 2000-2001) of the US-based National Longitudinal Study of Adolescent Health, we investigated the association between young women's body weight and depression during the transition to adulthood. Respondents (n = 5,243) were 13-18 years of age during wave 2 and 19-25 years of age during wave 3. We used Center for Epidemiologic Studies Depression Scale scores to classify young women as never depressed, consistently depressed, experiencing depression onset, or experiencing depression recovery from wave 2 to wave 3. Results from adjusted multinomial logistic regression models indicated that respondents who experienced significant weight gain were at risk of depression onset. Normal weight (adjusted odds ratio = 2.10, 95% confidence interval: 1.14, 3.84) and overweight (adjusted odds ratio = 1.86, 95% confidence interval: 1.15, 2.99) adolescent girls who were obese by young adulthood, as well as young women who were consistently obese during adolescence and young adulthood (adjusted odds ratio = 1.97, 95% confidence interval: 1.19, 3.26), had roughly twice the odds of depression onset as did young women who were never overweight. We concluded that weight gain and obesity are risk factors for depression onset during the transition to adulthood. Policies prioritizing healthy weight maintenance may help improve young women's mental health as they begin their adult lives.

Abstrak: This study took place in eastern Massachusetts and included respondents from the Harvard Study of Moods and Cycles Cohort 1, enrolled between 1995 and 1997, and the Harvard Study of Moods and Cycles Cohort 2, enrolled between 2005 and 2009. In prospectively assessing rates of new-onset depression in 2 populations of late-reproductive-aged women with no Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) lifetime history of depression, we were surprised to find far lower rates of depression in the population with greater racial diversity and lower socioeconomic status, contrary to what had been reported in the scientific literature. To better understand why these disparate results occurred, we assessed confounding and outcome misclassification as potential explanations for the discrepancy. After determining that these were unlikely explanations for the findings, we explored 2 potential sources of selection bias: one induced by self-referral of healthy participants into the study and the other induced by the design of the study itself. We concluded that both types of selection bias were likely to have occurred in this study and could account for the observed difference in rates.