Review and special article
Integrated perinatal health framework: A multiple determinants model with a life span approach

https://doi.org/10.1016/S0749-3797(03)00090-4Get rights and content

Abstract

Rationale

Despite great strides in improving prenatal care utilization among American women, key perinatal indicators have remained stagnant or worsened in the past decade, and the United States continues to rank near the bottom compared to other developed countries. A new approach is needed if we are to achieve improvements in perinatal health.

Objective

To propose a new framework that integrates a “life span” approach with a multiple determinants model.

Method

We recognize that (1) powerful influences on outcome occur long before pregnancy begins; (2) pregnancy outcome is shaped by social, psychological, behavioral, environmental, and biological forces; and (3) the demography of pregnancy has changed dramatically in the last few decades with more women delaying their first birth. Approaches that simultaneously consider the entire life span as well as multiple determinants may need to be adopted. We propose a framework that integrates these approaches and is supported by the research literature. The life span perspective focuses attention toward the preconceptional and interconceptional periods as targets for intervention in improving perinatal health. The multiple determinants model distinguishes among concepts of disease, health and functioning, and well-being for both women and their offspring.

Conclusion

Our intent is to influence how policymakers, public health professionals, clinicians, and researchers approach perinatal health.

Introduction

Current policy and practice approaches to improving the outcome of pregnancy and perinatal care are based, generally, on an individual-level epidemiologic model of addressing known risk factors. Some efforts have been made to incorporate multiple risk factors into programs of care, but these are still grounded in an intervention model that begins with pregnancy. This, in part, led to the enormous emphasis on early entry into prenatal care. The initial enthusiasm for prenatal care as an all-encompassing strategy, however, has faded as it became clear that the relationship is more complex.1 Despite great strides in improving prenatal care utilization among American women, there has not been a concurrent decline in indicators of adverse pregnancy outcome. Key perinatal indicators have remained stagnant or worsened in the past decade, and the United States continues to rank near the bottom for these indicators compared to rates in other developed counties.2 A new approach offers the opportunity to achieve improvements in perinatal health.

Presented here is our rationale for a perinatal framework that integrates a life span approach with a multiple determinants model. First, some of the most powerful influences on pregnancy outcome are related to influences on women’s health that occur long before pregnancy begins. For example, nutritional status may be strongly influenced by childhood practices.3, 4 To achieve sufficient folate in early pregnancy, nutrition may need to be ensured not just in the few weeks or months prior to pregnancy, but possibly years before childbearing begins. Similarly, although infection during pregnancy is a strong risk factor for preterm delivery,5, 6, 7, 8 the problem of infections may need to be addressed beginning in adolescence and between pregnancies to be effective in preventing adverse outcomes. While earlier frameworks have shown some recognition of the importance of the preconceptional period,9, 10, 11 most have limited the scope of their attention and have failed to place preconceptional forces in the context of women’s health across the life span. The focus has been on addressing factors in the few weeks to months prior to conception by targeting women who are planning their pregnancies. However, nearly one third of pregnancies in the United States are believed to be unintended (unwanted and/or mistimed).12 This underscores the importance of promoting a woman’s health regardless of her pregnancy plans. A “life span” approach to pregnancy outcome identifies the antecedents of poor perinatal outcome and links behaviors and risks across time, not solely during those periods in which a woman is pregnant.

Second, as in the case of chronic disease prevention programs, efforts to improve the outcome of pregnancy may need to adopt a “multiple determinants” model that integrates the social, psychological, behavioral, environmental, and biological forces that shape pregnancy. Such a model would provide a framework for showing the interrelationships among factors as well as the pathways by which factors might influence perinatal and women’s health. Again, the implications for practice and policy are that the integration of these various domains may be an essential step to improve perinatal health.

Third, the demography of pregnancy has changed dramatically in the last few decades,13, 14, 15 so that approaches that simultaneously consider the entire life span as well as multiple determinants may need to be adopted to achieve improvements in perinatal outcomes. While teen pregnancy and early childbearing have declined, the adolescent period remains important and retains the particular challenge of addressing issues of early sexual activity. But attention must now be given to the delayed childbearing occurring among older women, who have spent years in the workforce and enter pregnancy with a completely different set of biological and social issues than younger women. A framework for improving perinatal outcomes provides a structure that takes account of these differences.

Because the framework proposed here is based on a life course perspective that includes the preconceptional and interconceptional periods, these concepts are examined first. Figure 1 provides a schematic representation of the potential reproductive periods and paths within a woman’s life course. All women experience a preconceptional period beginning in childhood and ending either with menopause or the first pregnancy. Each cycle of pregnancy encompasses a prenatal, intrapartum, postpartum, and interconception period. Finally, the length of the interconceptional periods and number of cycles may vary for any given woman.

Each cycle also explicitly models pregnancy loss or termination. This is important to delineate, as sizable numbers of U.S. women will experience a loss or termination of pregnancy. The rate of clinically recognized loss is approximately 12% to 14% of recognized pregnancies.16, 17, 18, 19 It has been estimated that 43% of women will have had an induced abortion by 45 years of age.20

Four hypothetical paths are highlighted here (pictured in Figure 1) because each emphasizes a key issue with regard to reproductive trajectories. This should not be assumed to demarcate any of these paths as normative or optimal. Furthermore, while adolescent childbearing is clearly regarded as undesirable in the majority of American society, there may be cultural and ethnic differences in the meaning of reproduction timing. The first reproductive path describes the trajectory for a woman who becomes pregnant in her early twenties. The preconceptional period is abbreviated, but the interconception periods that follow may be lengthy or short. In the second path, childbearing is “delayed” and so, too, is the first reproductive cycle. In this case, the preconceptional period is lengthy, and future interconception periods will vary but be short if a woman continues childbearing. The third path portrays the experience of a woman who engages in late childbearing (i.e., late thirties through forties). The length of the preconceptional period is extended relative both to women in the first path (“early” childbearing) and the second path (“delayed” childbearing). As there is little time remaining in her reproductive years, the interconceptional period(s) will likely be brief. Finally, the fourth path is that of a woman who never becomes pregnant or gives birth.

As noted above, strategies to improve perinatal health have primarily focused on the prenatal, intrapartum, and immediate postpartum periods, and these strategies have failed to adequately address the impact of child, adolescent, and women’s health on maternal and infant outcomes. Regardless of the path taken, a woman will spend the bulk of her reproductive life span in either preconceptional or interconceptional periods. Figure 1 provides the underpinnings on which to build a perinatal health framework that considers all aspects of a woman’s life course in addressing perinatal health.

This framework marries a life course perspective, incorporating forces that influence the health of women through successive stages of their lives and their reproductive cycles with a multiple determinants model. Beginning in childhood/adolescence, attention focuses on the influences on health as women mature and on the forces that have implications for women’s health beyond their reproductive period. Childhood and adolescence may represent critical periods for women for a range of behaviors and exposures (e.g., family planning, protection against sexually transmitted infections, nutrition). Integral to the framework are the phases of the reproductive cycle described above.

The perinatal health framework presented is an adaptation of the Evans and Stoddart21 model of health determinants. While acknowledging the direct influence that biological, behavioral, environmental, and social factors have on health status, the Evans and Stoddart21 model more importantly provides a framework for understanding the interrelations between such factors. It distinguishes among concepts of disease, health and functioning, and well-being, providing a more comprehensive means of assessing health status than that encompassed by traditional health models. Organized in four hierarchical levels, Figure 2 provides a framework for assessing the multifactorial determinants of adverse perinatal and women’s health outcomes.

Here, the model has been constrained to the perinatal health arena, encompassing both the woman and her offspring. Following this presentation of the model, how various factors would be conceptualized is examined. The emphasis is on how factors relate to the preconceptional and interconceptional periods, and how multiple factors interact to influence the outcomes.

At the distal level, the framework brings focus to risk factors that place an individual or population at greater susceptibility to proximal risk factors. While having the potential to directly influence individual health status, distal factors are more relevant in terms of increasing or decreasing an individual’s predisposition toward developing compromising health conditions, engaging in high-risk behaviors, or being exposed to potential toxins. The primary categories of distal risk factors are genetic factors, the physical environment, and the social environment (Table 1).

At the proximal level of the framework, risk factors that have a direct impact on individual health status are represented by two categories, behavioral and biomedical responses (Table 2). This distinction between the behavioral and biomedical characteristics of proximal risk factors highlights the relationships between high-risk or protective behaviors and a woman’s health status, as well the influences of the physiological and biological characteristics of specific health conditions. Psychological factors are included in behavioral as well as biological responses. Both behavioral and biomedical responses provide important targets for intervention.

The interaction between distal and proximal risk factors determines an individual’s overall health status. It is the interrelationship between a woman’s health status directly prior to conception and the changes and demands of pregnancy that is one of the primary influences on perinatal health outcomes. Three of the four groups of outcomes from Evans and Stoddart21 are included here: (1) diseases and complications; (2) health and functioning; and (3) well-being (Table 3).

Distal determinants (Table 1) range from biological to social. At the extreme end of the continuum is the genetic environment. The physical environment falls somewhere between the biological and social ends of the continuum of distal determinants. At the far end of the continuum is the social environment. The distal determinants are the foundation for Figure 2. They exert influence throughout a woman’s reproductive life, and may be addressed irrespective of the cycles and paths delineated in Figure 1. The emphasis of prior frameworks on the perinatal period may have led us to overlook these distal factors, as they are unlikely to be resolved by perinatal interventions alone.

The criteria for selection of the risk factors for the proximal determinants (Table 2) in this framework include consideration of the existing body of scientific knowledge on the factors that influence perinatal health as well as the feasibility of achieving changes in those factors in the U.S. population. First, only factors for which there was scientific evidence of an effect on perinatal outcomes were selected. Second, consistent with the life course perspective, factors were chosen if effective intervention was unlikely to achieve change unless the woman’s health during the preconceptional/interconceptional periods was addressed. Third, emphasis was put on those factors that could potentially be addressed directly without requiring major changes in the preceding level of the framework (distal determinants), particularly the social and genetic environment. While the social environment may have a strong influence on these factors, there may be strategies that address these proximal factors taking account of context but that can be effective without fundamental changes in the social environment. Finally, only factors for which we had an infrastructure and experience in addressing in the pregnant population were included, as these were viewed as more feasible to address.

It should be readily apparent that these risk factors for proximal determinants co-exist (i.e., chronic disease and receipt of assisted reproductive technology [ART] services). It is important to consider the implications of the multivariate nature of the model. Efforts to assess the impact of addressing proximal factors (such as attributable risk estimation) must account for the overlap. Furthermore, interventions to address these factors must address multiple factors simultaneously. It might be necessary to develop a range of strategies to address a particular factor, and the choice of interventions will differ depending on the co-occurrence of other factors.

Figure 2 includes a “processes” level in the framework that connects the framework to the life course of the woman described in Figure 1. The transition from the preconceptional/interconceptional state to the event of conception and the pregnancy state is explicitly identified.

Section snippets

Outcomes

This framework includes three groups of outcomes (Table 3), each differentiating between mother and infant (including fetus): (1) diseases and complications; (2) health and functioning; and (3) well-being. Short-term diseases have been explicitly separated from long-term diseases and complications, as these groupings are consistent with the way in which perinatal outcomes are grouped for monitoring and research purposes. The intent is to call attention to a broader array of outcomes than is

Conclusion

This proposed model focuses attention on risk factors that influence perinatal outcomes but that occurred prior to and between pregnancies. We argue in favor of creating a system of health care that integrates the multiple determinants of perinatal outcome across the early life span of women. This review concludes that improvements in perinatal outcomes, among both women and their infants, have plateaued for two major reasons. First, interventions are focused primarily on the most proximal of

Acknowledgements

Financial support was provided by the Maternal and Child Health Bureau (MCHB) (cooperative agreement U93 MC 00101), Health Resources and Services Administration, U.S. Department of Health and Human Services. We acknowledge especially the contributions of Ann Koontz at the MCHB. Holly Grason, director of the Johns Hopkins University (JHU) Women’s and Children’s Health Policy Center (WCHPC), was particularly instrumental in the development and writing of this paper. The input of many colleagues

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