Mammographic over-screening: Evaluation based on probabilistic linkage of records databases from the breast cancer information system (SISMAMA)

The Brazilian Ministry of Health recommends biennial mammographic screening for women aged between 50 and 69 years. Since screening is opportunistic in the country, the actual periodicity varies. This study sought to test a methodology for estimating over-screening due to excessive periodicity, defined as a smaller than recommended interval between exams, and its association with socio-demographic characteristics. A cohort of women who underwent mammography in 2010, and whose result was normal, was assembled through probabilistic linkage SISMAMA records based on a set of personal identifiers. We used data from women living in the micro health region of Juiz de Fora/Lima Duarte/Bom Jardim, Minas Gerais State, Brazil, who were followed in the System until the end of 2012. The rate of over-screening was 150/1,000 women/year (95%CI: 144.9-155.9), affecting 21% of women. Over-screening increased by 24% during Pink October campaigns (adjusted HR = 1.24; 95%CI: 1.15-1.35). The shorter the time passed since the last mammogram, the greater the odds of over-screening. Compared with women who had never had a mammogram prior to 2010, women who had had one in the previous 2 years were two times more likely to be over-screened (adjusted HR = 2.01; 95%CI: 1.74-2.31) whilst those who had had a mammogram ≤ 1 year previously were three times more likely to be over-screened (adjusted HR = 3.27; 95%CI: 2.87-3.73). Over-screening was substantial in this population, excessively exposing women to the risks of screening with no additional benefits and overestimating mammogram coverage. The methodology proved to be successful and should be applied to representative populations in order to guide breast cancer control policies

Inequities in access to mammographic screening in Brazil

Our objectives with this study were to describe the spatial distribution of mammographic screening coverage across small geographical areas (micro-regions) in Brazil, and to analyze whether the observed differences were associated with spatial inequities in socioeconomic conditions, provision of health care, and healthcare services utilization. We performed an area-based ecological study on mammographic screening coverage in the period of 2010-2011 regarding socioeconomic and healthcare variables. The units of analysis were the 438 health micro-regions in Brazil. Spatial regression models were used to study these relationships. There was marked variability in mammographic coverage across micro-regions (median = 21.6%; interquartile range: 8.1%-37.9%). Multivariable analyses identified high household income inequality, low number of radiologists/100,000 inhabitants, low number of mammography machines/10,000 inhabitants, and low number of mammograms performed by each machine as independent correlates of poor mammographic coverage at the micro-region level. There was evidence of strong spatial dependence of these associations, with changes in one micro-region affecting neighboring micro-regions, and also of geographical heterogeneities. There were substantial inequities in access to mammographic screening across micro-regions in Brazil, in 2010-2011, with coverage being higher in those with smaller wealth inequities and better access to health care

Eating behavior trajectories in the first 10 years of life and their relationship with BMI

BACKGROUND: Child eating behaviors are highly heterogeneous and their longitudinal impact on childhood weight is unclear. The objective of this study was to characterize eating behaviors during the first 10 years of life and evaluate associations with BMI at age 11 years. METHOD: Data were parental reports of eating behaviors from 15 months to age 10 years (n = 12,048) and standardized body mass index (zBMI) at age 11 years (n = 4884) from the Avon Longitudinal Study of Parents and Children. Latent class growth analysis was used to derive latent classes of over-, under-, and fussy-eating. Linear regression models for zBMI at 11 years on each set of classes were fitted to assess associations with eating behavior trajectories. RESULTS: We identified four classes of overeating; "low stable" (70%), "low transient" (15%), "late increasing" (11%), and "early increasing" (6%). The "early increasing" class was associated with higher zBMI (boys: β = 0.83, 95% CI: 0.65, 1.02; girls: β = 1.1; 0.92, 1.28) compared with "low stable." Six classes were found for undereating; "low stable" (25%), "low transient" (37%), "low decreasing" (21%), "high transient" (11%), "high decreasing" (4%), and "high stable" (2%). The latter was associated with lower zBMI (boys: β = -0.79; -1.15, -0.42; girls: β = -0.76; -1.06, -0.45). Six classes were found for fussy eating; "low stable" (23%), "low transient" (15%), "low increasing" (28%), "high decreasing" (14%), "low increasing" (13%), and "high stable" (8%). The "high stable" class was associated with lower zBMI (boys: β = -0.49; -0.68-0.30; girls: β = -0.35; -0.52, -0.18). CONCLUSIONS: Early increasing overeating during childhood is associated with higher zBMI at age 11. High persistent levels of undereating and fussy eating are associated with lower zBMI. Longitudinal trajectories of eating behaviors may help identify children potentially at risk of adverse weight outcomes