Prevalence and predictors of 6-month exclusive breastfeeding among Canadian women: a national survey

<p>Abstract</p> <p>Background</p> <p>In spite of the evidence supporting the importance of breastfeeding during the first year of life, data on breastfeeding practices remain limited in Canada. The study aimed to examine the prevalence and predictors of 6-month exclusive breastfeeding among Canadian women.</p> <p>Methods</p> <p>The analysis was based on the Maternity Experience Survey targeting women aged ≥ 15 years who had singleton live births between February 2006 - May 2006 in the Canadian provinces and November 2005 - February 2006 in the territories. The main outcome was exclusive breastfeeding based on the World Health Organization definition. Socioeconomic, demographic, maternal, pregnancy and delivery related variables were considered for a multivariate logistic regression using stepwise modeling. Bootstrapping was performed to account for the complex sampling design.</p> <p>Results</p> <p>The sample size in this study was 5,615 weighted to represent 66,810 Canadian women. While ever breastfeeding was 90.3%, the 6-month exclusive breastfeeding rate was 13.8%. Based on the regression model, having higher years of education, residing in the Northern territories and Western provinces, living with a partner, having had previous pregnancies, having lower pre-pregnancy body mass index and giving birth at older age were associated with increased likelihood of 6-month exclusive breastfeeding. Moreover, smoking during pregnancy, Caesarean birth, infant's admission to the intensive care unit and maternal employment status before 6 months of infant's age were negatively associated with exclusive breastfeeding. Mothers choosing to deliver at home were more likely to remain exclusively breastfeeding for 6 months (Odds Ratio: 5.29, 95% Confidence Interval: 2.95-9.46).</p> <p>Conclusions</p> <p>The 6-month exclusive breastfeeding rate is low in Canada. The study results constitute the basis for designing interventions that aim to bridge the gap between the current practices of breastfeeding and the World Health Organization recommendation.</p

Characteristics associated with pediatric growth measurement collection in electronic medical records: a retrospective observational study

Abstract Background Complete growth measurements are an essential part of pediatric care providing a proxy for a child’s overall health. This study describes the frequency of well-child visits, documented growth measurements, and clinic and provider factors associated with measurement. Methods Retrospective cross-sectional study utilizing electronic medical records (EMRs) from primary care clinics between 2015 and 2017 in Manitoba, Canada. This study assessed the presence of recorded height, weight and head circumference among children (0–24 months) who visited one of 212 providers participating in the Manitoba Primary Care Research Network. Descriptive and multivariable logistic regression analyses assessed clinic, provider, and patient factors associated with children having complete growth measurements. Results Our sample included 4369 children. The most frequent growth measure recorded was weight (79.2% n = 3460) followed by height (70.8% n = 3093) and head circumference (51.4% n = 2246). 67.5% of children (n = 2947) had at least one complete growth measurement recorded (i.e. weight, height and head circumference) and 13.7% (n = 599) had complete growth measurements at all well-child intervals attended. Pediatricians had 2.7 higher odds of documenting complete growth measures within well-child intervals compared to family physicians (95% CI 1.8–3.8). Additionally, urban located clinics (OR 1.7, 95% CI 1.2–2.5), Canadian trained providers (OR 2.3, 95% CI 1.4–3.7), small practice size (OR 1.6, 95% CI 1.2–2.2) and salaried providers (OR 3.4, 95% CI 2.2–5.2) had higher odds of documented growth measures. Conclusions Growth measurements are recorded in EMRs but documentation is variable based on clinic and provider factors. Pediatric growth measures at primary care appointments can improve primary prevention and surveillance of child health outcomes

Using Growth velocity to predict child mortality

Background: Growth assessment based on the WHO child growth velocity standards can potentially be used to predict adverse health outcomes. Nevertheless, there are very few studies on growth velocity to predict mortality. Objectives: We aimed to determine the ability of various growth velocity measures to predict child death within 3 mo and to compare it with those of attained growth measures. Design: Data from 5657 children <5 y old who were enrolled in a cohort study in the Democratic Republic of Congo were used. Children were measured up to 6 times in 3-mo intervals, and 246 (4.3%) children died during the study period. Generalized estimating equation (GEE) models informed the mortality risk within 3 mo for weight and length velocity z scores and 3-mo changes in midupper arm circumference (MUAC). We used receiver operating characteristic (ROC) curves to present balance in sensitivity and specificity to predict child death. Results: GEE models showed that children had an exponential increase in the risk of dying with decreasing growth velocity in all 4 indexes (1.2- to 2.4-fold for every unit decrease). A length and weight velocity z score of <−3 was associated with an 11.8- and a 7.9-fold increase, respectively, in the RR of death in the subsequent 3-mo period (95% CIs: 3.9, 35.5, and 3.9, 16.2, respectively). Weight and length velocity z scores had better predictive abilities [area under the ROC curves (AUCs) of 0.67 and 0.69] than did weight-for-age (AUC: 0.57) and length-for-age (AUC: 0.52) z scores. Among wasted children (weight-for-height z score <−2), the AUC of weight velocity z scores was 0.87. Absolute MUAC performed best among the attained indexes (AUC: 0.63), but longitudinal assessment of MUAC-based indexes did not increase the predictive value. Conclusion: Although repeated growth measures are slightly more complex to implement, their superiority in mortality-predictive abilities suggests that these could be used more for identifying children at increased risk of death