Early life growth trajectories and future risk for overweight.

OBJECTIVE: Standard approaches have found that rapid growth during the first 2 years of life is a risk factor for overweight in later childhood. Our objective was to test whether growth velocity, independent of concurrent size, was associated with overweight using a nonlinear random-effects model that allows for enhanced specifications and estimations. METHODS: Longitudinal data from a birth cohort in Mexico (n=586) were used to estimate growth trajectories over 0-24 months for body mass index (BMI), length and weight using the SuperImposition by Translation and Rotation (SITAR) models. The SITAR models use a nonlinear random-effects model to estimate an average growth curve for BMI, length and weight and each participant's deviation from this curve on three dimensions-size, velocity and timing of peak velocity. We used logistic regression to estimate the association between overweight status at 7-9 years and size, velocity and timing of BMI, length and weight trajectories during 0-24 months. We tested whether any association between velocity and overweight varied by relative size during 0-24 months or birth weight. RESULTS: SITAR models explained the majority of the variance in BMI (73%), height (86%) and weight (85%) between 0-24 months. When analyzed individually, relative BMI/length/weight (size) and BMI/length/weight velocity during 0-24 months were each associated with increased odds of overweight in late childhood. Associations for timing of peak velocity varied by anthropometric measure. However, in the mutually adjusted models, only relative BMI/length/weight (size) remained statistically significant. We found no evidence that any association between velocity and overweight varied by size during 0-24 months or birth weight. CONCLUSIONS: After mutual adjustment, size during 0-24 months of life (as opposed to birth size), but not velocity or timing of peak velocity, was most consistently associated with overweight in later childhood.

Estimating the potential impacts of intervention from observational data: methods for estimating causal attributable risk in a cross-sectional analysis of depressive symptoms in Latin America.

BACKGROUND: The field of epidemiology struggles both with enhancing causal inference in observational studies and providing useful information for policy makers and public health workers focusing on interventions. Population intervention models, analogous to population attributable fractions, estimate the causal impact of interventions in a population, and are one option for understanding the relative importance of various risk factors. With population intervention parameters, risk factors are effectively standardised, allowing one to compare their values directly and determine which potential intervention may have the greatest impact on the outcome. METHODS: The difference between total effects and population intervention parameters was examined using naïve, G-computation and inverse probability of treatment weighting approaches. The differences between these parameters and the intuitions they provide were explored using data from a 2003 cross-sectional study in rural Mexico. RESULTS: The assumptions, specific analytic steps, limitations and interpretations of the total effects and population intervention parameters are discussed, and code is provided in Stata. CONCLUSION: Population intervention parameters are a valuable and straightforward approach in epidemiological studies for making causal inference from the data while also supplying information that is relevant for researchers, public health practitioners and policy makers.

Social and economic correlates of depressive symptoms and perceived stress in South African adults.

OBJECTIVES: Adults in South Africa demonstrate rates of mental illness at or above levels elsewhere in the developing world. Yet there is a research gap regarding the social context surrounding mental health in this region. The objective of this analysis was to characterize the prevalence and correlates of depressive symptoms and perceived stress among a heterogeneous South African population. METHODS: Low-income adults (n = 257) in Capetown, Port Elizabeth and Durban were interviewed regarding demographics, income, subjective social status, life events and decision-making. The Center for Epidemiologic Studies Depression Scale (CES-D) and Cohen's Perceived Stress Scale (PSS) were used. RESULTS: CES-D scores were 18.8 (SD 11.7), with 50.4% of men and 64.5% of women exceeding the cut-off at which professional care is recommended (p = 0.03). PSS scores were 18.6 (SD 6.7), with a mean of 17.5 among men and 19.6 among women (p = 0.02). In multivariate regressions, increased CES-D scores were associated with more household members (p<0.1), lower educational attainment (p = 0.07), less income stability (p<0.07), lower subjective social status (p<0.01) and independent decision-making (p = 0.04). Increased PSS scores were associated with female gender (p<0.05), multiracial race (p<0.02), more household members (p<0.1), lower subjective social status (p<0.02) and recent birth or catastrophe (p<0.01). CONCLUSIONS: Depressive symptoms and perceived stress are public health concerns in this sample, with more symptoms among those with fewer resources. The prevention of mental illness is critical, especially in vulnerable populations.

Blood pressure and socioeconomic status in low-income women in Mexico: a reverse gradient?

OBJECTIVES: In the developed world, there is a well-established inverse association between socioeconomic status (SES) and blood pressure. In the developing world, however, these relationships are not as clear, particularly in middle-income countries undergoing epidemiological and nutritional transition. METHODS: A house-to-house cross-sectional survey was conducted in low-income regions of rural Mexico in 2003. A sample of women (n = 9362) aged 18-65 years (mean 35.2, SD 10.4) was assessed. Measurements of systolic blood pressure (SBP) and body mass index (BMI) were obtained using standardised techniques and equipment. Interviews were conducted to collect information about SES, both objective (education, income, housing and assets, occupation) and subjective (perceived social status). RESULTS: Household income, housing and assets were positively and strongly associated with age-adjusted SBP; the associations were attenuated somewhat with the inclusion of BMI. SBP was also positively associated with perceived social status within one's community. In contrast, age and BMI-adjusted SBP was negatively associated with educational achievement. There was a significant education by BMI interaction; at equivalent values for BMI, women who had received at least some secondary education had lower SBP than those who had received less education. CONCLUSIONS: In contrast to traditional assumptions about the associations between SES and health, women in low-income rural populations who are at the upper end of the income spectrum within their community were found to be more likely to have higher SBP, as were those who perceived that they had higher status in the community. These results challenge standard assumptions about the association of SES and health.