Methodologic and statistical approaches to studying human fertility and environmental exposure - Mini-Monograph

Environmental Health Perspectives, Jan, 2004 by Candace Tingen, Joseph B. Stanford, David B. Dunson

Although there has been growing concern about the effects of environmental exposures on human fertility, standard epidemiologic study designs may not collect sufficient data to identify subtle effects while properly adjusting for confounding. In particular, results from conventional time to pregnancy studies can be driven by the many sources of bias inherent in these studies. By prospectively collecting detailed records of menstrual bleeding, occurrences of intercourse, and a marker of ovulation day in each menstrual cycle, precise information on exposure effects can be obtained, adjusting for many of the primary sources of bias. This article provides an overview of the different types of study designs, focusing on the data required, the practical advantages and disadvantages of each design, and the statistical methods required to take full advantage of the available data. We conclude that detailed prospective studies allowing inferences on day-specific probabilities of conception should be considered as the gold standard for studying the effects of environmental exposures on fertility. Key words: conception, fecundability, menstrual cycle, ovulation, reproductive epidemiology, statistical methods, study design, time to pregnancy.

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There is increasing concern about the effects of environmental exposures on human fertility (Baird and Strassmann 2000). At least 10% of couples in the United States have had difficulty achieving pregnancy (Chandra and Stephen 1998). Investigators are worried that fertility may be declining, and there is corresponding concern in the general public (Carlsen et al. 1992; Pearce et al. 1999; Swan et al. 2000; United Nations 1997). The increased public focus on fertility problems has resulted partly from the increasing numbers of women who delay attempting pregnancy until their midddle to late 30s, ages at which a substantial proportion of couples will flail to conceive within a year and hence be categorized as clinically infertile (Dunson et al. In press). Many of these couples will resort to assisted reproduction techniques, which pose potential concerns about safety and impact on perinatal and child health (Mitchell 2002). Despite broad interest in the scientific community and in the general public, surprisingly little is known about key factors related to human fertility and fecundity, such as age, environmental exposures, sexual behavior, and lifestyle (Joffe 2003; Olsen and Rachootin 2003). In this article we first review broadly the factors known to affect fertility. We then discuss methodologic and statistical issues involved in studying fecundity, with an emphasis on the advantages, necessary design elements, and statistical methods for detailed prospective preconception cohort studies. We also comment on the need to integrate the study of human fecundity with the study of other aspects of human reproduction and development.

Throughout the article, we use the term "fecundity" to refer to a couple's probability of pregnancy with regular intercourse without the use of contraception. In other words fecundity is the inherent capacity to conceive. Depending on the context, fecundity can be assessed for women, for men, or for couples. The related term from demography, "fecundability," is the specific probability of conception within a single menstrual cycle with noncontracepted intercourse. We use the term "fertility" to refer to the ability of a couple to achieve a pregnancy that survives to birth.

Factors Affecting Fertility

Age and environmental exposures. It is generally accepted that female fecundity declines with age (Sauer 1998). However, limited data are available on the rate of decline (Schwartz and Mayaux 1982; Stovall et al. 1991; van Noord-Zaadstra et al. 1991) and on factors contributing to the decline (Abdalla et al. 1997; Rosenwaks et al. 1995). Even less is known about aging effects on male fecundity, with the available data pertaining mostly to declines in the elderly years (Kidd et al. 2001). A recent study reported that female fecundity starts to decline in the late 20s and male fecundity in the late 30s, controlling for timing of intercourse (Dunson et al. 2002), but more data are needed to validate this result and investigate causes. In particular, little is known about the impact of environmental exposures on the variability in fecundity among young couples and in the rate of decline with age. Some studies have reported lower fecundity associated with environmental factors, such as parental consumption of contaminated fish (Buck et al. 2000) and exposure to lead (Apostoli et al. 2000; Sallmen et al. 1995), pesticides (Curtis et al. 1999; Larsen et al. 1998; Thonneau et al. 1999), organic and chemical solvents (Sallmen et al. 1998; Wennborg et al. 2001), and cigarette smoking (Weinberg et al. 1989). However, in studies to date, exposure has been assessed only retrospectively, and these results were based mostly on small sample sizes.

Sexual behavior. One of the main difficulties in studying human fertility is the large behavioral component. There is a tremendous interplay between behavior and biology, both of which need to be considered when assessing etiologic end points. The ages at which couples attempt conception vary substantially between different socioeconomic and ethnic groups (Morabia and Costanza 1998; O'Connell and Rogers 1982; Pearce et al. 1999; Taffel 1977). Over the last several decades there has been a steady increase in the age of the mother at first birth (Morabia and Costanza 1998; Pearce et al. 1999; Ventura et al. 2000, 2001), largely due to women delaying childbirth while focusing on careers. Such trends may be more prevalent among couples in certain demographic groups, making it important to carefully adjust for age and behavior in analyses of environmental effects. In particular, including only age as a covariate in a time to pregnancy (TTP) model may not adequately adjust for differences between groups in the timing and frequency of intercourse. Fertility data analysis is also biased by the "survival" effect, where more fertile couples conceive early in their reproductive years, resulting in an age-dependent increase in the proportion of subfertile couples among the couples attempting pregnancy.