Newborn Body Fatness and Autonomic Function: Identification of Infants at Risk of Later Cardiovascular Disease
Authors: Dissanayake Hasthi , McMullan Rowena , Phang Melinda , Gordon Adrienne , Hyatt Jon , Rains‐Greenow Camille , Celermajer David , Polson Jaimie , Skilton Michael 
Published: November 2023

Birth weight is associated with hypertension across the lifespan and adult cardiovascular disease, such that those at both ends of the spectrum are at increased risk. This may at least partially be driven by modification to autonomic control, a mechanistic contributor to hypertension. Nonetheless, birth weight is a relatively crude surrogate of fetal growth, and it may be that quantification of body composition in newborns, such as percent body fat, may more accurately identify the “at risk” infant. Accordingly, we sought to determine whether newborns with a high or low body fat have altered autonomic control, and whether this is independent of birth weight.

Body fat percent was assessed by air displacement plethysmography (PEAPOD) in term newborns (<24h postnatal) from RPA Hospital, Sydney, Australia. Blood pressure waveform (Finapres) and 3‐lead ECG were recorded at rest for 15 minutes, within 2 weeks of birth. Infants were categorised according to body fat percentile, gender and gestation‐specific percentile groups: 1. High body fat percent (>90th percentile); 2. Low body fat percent (≤10th percentile); control (25–75th percentile). Markers of autonomic function, specifically heart rate variability and systolic blood pressure variability, were analysed using frequency and time domain methods. Spontaneous baroreflex was calculated using the sequence method.

Newborns with high (n=26) or low (n=27) body fat percent had lower heart rate variability compared to Controls (n=40)(Total power, P<0.001 and P=0.01 respectively). This appeared to be most marked in those with a high body fat percent, in whom all frequency components and time domain parameters tested were significantly lower than controls (Table 1). These differences were independent of birth weight (Total power, P=0.001, P=0.008). Baroreflex gain was not significantly different between groups (all P=0.10). However, infants with low body fat percent (n=14) had significantly lower baroreflex effectiveness index than controls (n=20)(P=0.02), whereas this did not reach statistical significance for the high percent body fat group (n=10) (P=0.09 vs control). No significant differences were found in individual frequency components or time domain measures of blood pressure variability between groups (all P=0.20).

Collectively, our results show newborns with either a low or high percent body fat have altered markers of autonomic function, consistent with decreased autonomic modulation of the heart, but not the blood vessels. This suggests that altered cardiac autonomic control may potentially be a mechanistic link that drives increased risk of hypertension and cardiovascular disease in people who were born with either a low or high proportion of body fatness.

Support or Funding Information

Skilton MR is funded by a National Heart Foundation of Australia Future Leader Fellowship (100419). Dissanayake HUW is funded by a Australian Postgraduate Award (APA) scholarship (SC0042).

Heart Rate Variability

Control
<10th Percentile
P value
>90th Percentile
P value

Frequency analysis
(n=40)
(n=27)
(<10th vs control)
(n=26)
(>90th vs control)

Total Power ms2
1872.4 ± 163.4
1210.8 ± 176.5
*0.018
763.0 ± 82.2
*p<0.01

VLF ms2
1057.0 ± 100.1
566.2 ± 94.8
*0.001
457.4 ± 46.4
*p<0.01

LF ms2
494.0 ± 65.0
367.0 ± 54.7
0.14
213.3 ± 35.1
*p<0.01

HF ms2
305.7 ± 44.1
278.1 ± 83.0
0.77
91.1 ± 12.6
*p<0.01

Time domain

SDNN
44.3 ± 2.1
36.2 ± 2.4
*0.013
31.3 ± 1.6
*p<0.01

SD delta NN
22.4 ± 1.8
20.2 ± 2.9
0.521
13.5 ± 1.0
*p<0.01

RMSSD
22.4 ± 1.8
19.7 ± 2.8
0.435
13.5 ± 1.0
*p<0.01

Values are mean ± SEM

Indicated groups vs control group, according to independent T‐Test.

VLF, very low frequency power; LF, low frequency power; HF, high frequency power; SDNN, mean SD of all normal RR intervals; SD delta NN, SD change in RR intervals; RMSSD, square root of the mean squared differences of successive NN intervals.