Big Mother or Small Baby: Which Predicts Hypertension?

Abstract

According to the Barker hypothesis, intrauterine growth restriction and premature delivery adversely affect cardiovascular health in adult life. The association of childhood hypertension as a cardiovascular risk factor and birth weight has been understudied. In a prospective cohort study, the authors evaluated the effect of birth weight, gestational age, maternal prepregnancy body mass index (BMI), and child BMI z score at the time of enrollment on the systolic and diastolic blood pressure (BP) z score in 3024 (1373 women) consecutive outpatient clinic patients aged 2.05 to 18.58 years. The latest National Health and Nutrition Examination Survey (NHANES III) was used to calculate the age‐dependent z scores. The median z scores of BMI (+0.48, range −6.96–6.64), systolic BP (+0.41, range −4.50–6.73), and diastolic BP (+0.34, range −3.15–+6.73) were all significantly greater than the NHANES III reference population. Systolic BP z score did not correlate with birth weight or gestational age, but did correlate with maternal prepregnancy BMI (r=.090, P<.0001) and BMI z score (r=.209, P<.0001). Diastolic BP z score positively correlated with birth weight (0.037, P=.044), gestational age (r=.052, P=.005), BMI z score(r=.106, P<.0001), and maternal prepregnancy BMI (r=.062, P=.0007). In contrast to what would be expected from the Barker hypothesis, the authors found no negative correlation between BP z score and birth weight or gestational age. This study suggests that a high BMI, a big mom, and a high birth weight are more important risk factors for hypertension during childhood than low birth weight or gestational age. J Clin Hypertens (Greenwich). 2011;13:35–41. ©2010 Wiley Periodicals, Inc.

Applying the WHO instead of CDC growth charts may double obesity rates

“…Kulaga et al studied a Polish cohort using both the CDC and the WHO as well as a local growth chart and also found significant differences [16]. Presumably, the population of Canada with its high prevalence of obesity is different [8]. We are unaware of similar studies among G8 countries.…”

“…Parts of the study have been published elsewhere [8]. Median age was 11.8 years (range 5.09 -20.85 years, 1993 females = 45.6%), median height for the entire group of patients was 149.9 cm (range 78.0 -164.5 cm), median weight was 43.5 kg (range 10.9 -170.0 kg) and median BMI was 19.05 kg/m 2 (range 10.71 -62.69 kg/m 2 ).…”

“…We did not adjust for ethnicity, which is an important determinant of growth [19]. However, the population in South Western Ontario is largely Caucasian [8]. Further, the healthy weight study was not designed for the analysis of this question.…”

Cystatin C adaptation in the first month of life

“…To obtain the value (X) of a given physical measurement at a particular z-score or percentile, we used the following equation: X=M (1+LSZ)**(1/L), where L, M, and S are the values corresponding to the age in months of the child, and Z is the z-score that corresponds to the percentile. An example can be found in a recent study on the effects of preconception age of mothers on the body mass index percentiles of their offspring [26]. For the current issue, the aim is to collate cystatin C values of healthy infants less than 2 years of age obtained in pooled samples from multiple centers with standardized cystatin C measurements.…”

The independent associations of HbA1c, C-reactive protein and birth weight with cardiovascular disease, diabetes mellitus and chronic kidney disease in a remote Indigenous Australian community: a prospective cohort study

“…Several studies [215][216][217][218][219][220] suggest there is an increase in blood pressure as birth weight decreases, but there are recent studies suggesting there is either a positive or no association [221][222][223][224][225][226][227]. Several meta-analyses and systematic literature reviews have attempted to explain these differences and the three primary trends appear to be due to differences in populations, differences of analysis classifications and differences in adjusting for confounding variables [210,228,229].…”