Pregnancy-related changes in behavior and cardiac activity in primiparous pigs.

ABSTRACT

Pregnancy in mammals is a time of considerable physical, physiological and behavioral change necessary for the continuance of the gestation. Gestating pigs are often used in behavior and welfare studies; yet, there are little published data describing how pregnancy affects normal behavior and cardiac activity patterns. The objective of this work was to describe the longitudinal dynamics of cardiac activity and behavior during pregnancy in primiparous pigs (gilts). The behavior and cardiac activity of nine gilts were recorded on eight occasions at certain fixed time points during their pregnancy 1-2 weeks before oestrus and mating (week -1), 14 days postmating (week 2), and days 30 (week 4), 44 (week 6), 65 (week 9), 79 (week 11), 93 (week 13) and 107 (week 15) of pregnancy. Temporal changes in behavior patterns were present in all gilts over the course of gestation. Pretest levels of general activity progressively declined between weeks -1 and 15, as indicated by a decrease in the proportion of observations spent rooting (p<0.001), walking (p<0.001) and standing (p<0.001). There was a corresponding increase in inactivity (p<0.001), and the proportion of time spent sleeping, as opposed to lying alert, increased also (p<0.001). Apart from RR-min and its corresponding HR-max indices, all time-domain parameters were influenced by the stage of gestation. Specifically, mean HR increased (p<0.001), whereas the root-mean-square of successive differences (RMSSD) and standard deviation (S.D.) decreased (p<0.001). Pregnancy further impacted the frequency domain measures of heart rate variability. From week -1 to 15, the absolute magnitude of Total power (p<0.001) decreased, HF power decreased (p<0.001) and LF power increased (p=0.004). In conclusion, pregnancy induced widespread changes in behavior and in sympathovagal regulation of cardiac activity in pigs that were reflected in both the time and frequency domain indices of heart rate variability analysis.