Canonical correlation analysis of infant's size at birth and maternal factors: a study in rural northwest Bangladesh.
This analysis was conducted to explore the association between 5 birth size measurements (weight, length and head, chest and mid-upper arm [MUAC] circumferences) as dependent variables and 10 maternal factors as independent variables using canonical correlation analysis (CCA). CCA considers simultaneously sets of dependent and independent variables and, thus, generates a substantially reduced type 1 error. Data were from women delivering a singleton live birth (n = 14,506) while participating in a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural Bangladesh. The first canonical correlation was 0.42 (P<0.001), demonstrating a moderate positive correlation mainly between the 5 birth size measurements and 5 maternal factors (preterm delivery, early pregnancy MUAC, infant sex, age and parity). A significant interaction between infant sex and preterm delivery on birth size was also revealed from the score plot. Thirteen percent of birth size variability was explained by the composite score of the maternal factors (Redundancy, RY/X = 0.131). Given an ability to accommodate numerous relationships and reduce complexities of multiple comparisons, CCA identified the 5 maternal variables able to predict birth size in this rural Bangladesh setting. CCA may offer an efficient, practical and inclusive approach to assessing the association between two sets of variables, addressing the innate complexity of interactions.
Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh; International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh.
Alamgir
A
Kabir
Center for Human Nutrition, Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States of America.
Rebecca D
RD
Merrill
The JiVitA Maternal and Child Health and Nutrition Research Project, Gaibandha, Bangladesh.
Abu Ahmed
AA
Shamim
Center for Human Nutrition, Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States of America.
Rolf D W
RD
Klemn
Center for Human Nutrition, Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States of America.
Alain B
AB
Labrique
Center for Human Nutrition, Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States of America.
Parul
P
Christian
Center for Human Nutrition, Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States of America.
Keith P
KP
West
Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh.
Mohammed
M
Nasser
D001459:Bangladesh; D001724:Birth Weight; D005260:Female; D006801:Humans; D007231:Infant, Newborn; D008297:Male; D009035:Mothers / Q000706:statistics & numerical data*; D011247:Pregnancy; D047928:Premature Birth / Q000503:physiopathology; D012044:Regression Analysis; D012424:Rural Population / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors; D013223:Statistics as Topic; D055815:Young Adult