Seasonal birth patterns have been observed in virtually all human populations. While such patterns are known and well understood in many animal species, they are difficult to analyze in humans, since biological factors contributing to birth rates are confounded with cultural factors. Taken as a whole, the conclusion of the many studies on birth seasonality in humans is that while such seasonal variation is universal, the causes of variation are not universal. Most of the research that has attempted to explain observed seasonal patterns in specific populations has focused on only a few possible causal factors. In many cases factors such as diet, workload, and climate are shown to be correlated with fertility, but the mechanisms linking them with fertility remain unexplained. The proposed study will analyze seasonal birth patterns in an indigenous American population (the Anu of northwestern Venezuela). It will describe seasonal variation in proximate determinants of fertility, including characteristics of ovarian cycles and fetal loss. These data will be used in models of fecundability and fetal loss that together describe seasonality of fertility. The study includes analysis of 1346 urine samples that were collected twice weekly during the seasons of most and fewest conceptions. The samples will be assayed to determine levels of human chorionic gonadotropin (the hormone that indicates pregnancy) and of urinary metabolites of the hormones estradiol and progesterone; the assay data then will be used with interview data to determine proportion of cycles ovulatory, length of cycles, rates of conception, rates of fetal loss, and levels of progesterone, as an indicator of luteal sufficiency. Previous investigations of seasonality of fertility have been based largely on factors specific to the population being studied. The proposed study uses a model of seasonality of fertility that can be applied to any population. By combining existing models of fecundability and fetal loss, the impact of individual proximate determinants of fertility on seasonal fertility patterns can be more thoroughly analyzed than in previous studies. Seasonal data on more distal determinants, such as diet, workload, spouse absence, and nutritional status, can then be evaluated in terms of the information on the proximate determinants, shedding light on possible linking mechanisms and opening avenues for further research.
