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Examining health and health-related factors within a lifespan developmental framework is important for several reasons. First, health and development share many important characteristics—both are lifelong processes that involve gains (growth) and losses (decline), are multidimensional, and change as a function of adaptation to changing biological, psychological, social, environmental, and cultural conditions (Baltes, Staudinger, & Lindenberger, 1999; Whitman, 1999). Second, developmental processes influence health and illness behavior, the experience of illness, illness prevention and health promotion, and the assessment and treatment of disease (Penny, Bennett, & Herbert, 1994). An understanding of how these processes operate to affect health outcomes can help to optimize the effectiveness of interventions and determine when they are most appropriately offered (Peterson, 1996; Roberts, Maddux, & Wright, 1984). Third, a life-span developmental framework can aid in the understanding of health by identifying unique patterns of risk and protective factors that vary predictably by developmental stage (Baltes et al., 1999; Whitman, 1999). Finally, attention to developmental factors fosters an appreciation of how health-related experiences at earlier stages can affect health and health behaviors at later stages of the life-span. To date, little attention has been given to the ways in which development as a dynamic force shapes health and health behaviors (Peterson, 1996), although there are several notable exceptions (e.g., Schulenberg, Maggs, & Hurrelmann, 1997a). In fact, most models of health and illness ignore developmental factors, limiting their external validity beyond the age group for which they were developed (Whitman, 1999).
The goals of this research paper are (a) to elaborate on the utility of a life-span developmental approach to health; and (b) to discuss how biological, cognitive, and social development influences health and health behavior in each of five life stages—infancy, childhood, adolescence, midlife, and older adulthood. The fact that extrinsic factors such as social class and gender interact with these processes should be kept in mind throughout this discussion. Findings from empirical literature on physical activity and diabetes self-care are used to illustrate the role of these factors in each of the selected life stages.
The ways in which biological systems change with development influence an individual’s risk of morbidity and mortality across the life span (Kolberg, 1999). Kolberg (1999) classifies diseases and conditions according to their incidence across the life span: diseases of childhood, which decrease with age; diseases of aging, which increase with age; diseases of adulthood; diseases that are most frequent in infants and the elderly; and diseases that affect all age groups consistently.As an individual moves from infancy to older adulthood, biological systems change in ways that can either protect health or increase risk for morbidity and mortality (Kolberg, 1999). Biological development follows a sequential pattern: physical (and cognitive) abilities resemble an inverted U shape such that they are at their lowest levels of efficacy in very early and very late life (Schulz & Heckhausen, 1996); correspondingly, individuals are at greatest risk for medical problems in very early life and older adulthood (Kolberg, 1999). Some diseases (e.g., coronary artery disease or lung cancer) are most associated with older adulthood because of cumulative insult, or “wear and tear” (Kolberg, 1999), highlighting the need for considering the impact of risk factors and stressors across the life course.
Characterizing health status by age group, however, is a complex process (Whitman, 1999) because it depends to a great extent on external factors—for example, the health of midlife adults with low socioeconomic status (SES) tends to be inferior to that of high-SES older adults (House et al., 1990). In addition to the direct effects of age-related changes in biological systems on health status, the likelihood of illness at any given stage may also be an important determinant of health behaviors. For example, in late midlife and older adulthood, a greater propensity toward chronic illness may make the likely consequences of risky health behaviors seem particularly salient. Among adolescents and young adults, current good health may increase the likelihood of engaging in health-risk behaviors because the perceived threat of future illnesses is relatively remote.
Cognitive abilities such as intellectual functioning and feelings of control also vary over the course of the life span and have implications for making decisions about health-related behavior.At the beginning of the life span, increases in cognitive sophistication enable children to become better able to understand concepts of health and illness (Bibace & Walsh, 1980). At the end of the life span, decrements in mechanical (or fluid) intelligence and—to a lesser extent—pragmatic (or crystallized) intelligence have been found among the old and very old (Baltes, Lindenberger, & Staudinger, 1998; Lindenberger & Baltes, 1997); however, some older adults also exhibit high levels of wisdom, or knowledge about the meaning and conduct of life (Baltes et al., 1998). Heckhausen and Schulz (1995) describe shifts in the use of control strategies—either primary control (i.e., over the external world) or secondary control (i.e., cognitive or internally directed processes) in accordance with differing developmental needs over the life span. All such changes in cognitive processes may affect both the nature of health-related decisions and the extent to which individuals are able to make autonomous choices over the life course regarding their own health behavior.
The implications of developmental differences in cognitive factors, however, are rarely considered in theories that address health decision making. Theories that predict and explain health decision making in adults, for example, might not be appropriate for children and adolescents (Sturges & Rogers, 1996). Prohaska and Clark (1997) note that the Health Belief Model (HBM; Janz & Becker, 1984), one of the most widely used theories to predict health-related behavior, may not adequately predict behavior across age groups. This model assumes that perceived health threat is a strong motivator for engaging in preventive health behaviors; yet adolescents may be more motivated by social pressures than by personal health beliefs (Prohaska & Clark, 1997) or may use health behaviors as a way of accomplishing developmental tasks (Schulenberg, Maggs, Steinman, & Zucker, 2001). Developmental stages may also influence the relative importance of HBM components in predicting health outcomes (i.e., perceived susceptibility to and severity of a health threat and perceived benefits and barriers of taking action to reduce the threat) in midlife (Merluzzi & Nairn, 1999).
The components of Social Cognitive Theory (Bandura, 1986, 2001; N. M. Clark & Zimmerman, 1990), another widely used model to explain health behavior change, can also be affected by age and developmental stage. Selfefficacy—the belief of an individual that he or she can successfully perform a certain behavior and one of the central constructs of this theory—may be affected either positively (through experience) or negatively (by repeated failures) by age. Another SCT construct, outcome expectancy—that is, the belief that a behavior will lead to a positive result—may also vary with age, in part because health behaviors will not bring about the same positive results equally across the life span (Prohaska & Clark, 1997).
Several theories of health behavior include social factors. For example, the Theory of Planned Behavior (Ajzen, 1991; Montano, Kasprzyk, & Taplin, 1997) includes a component that assesses how an individual perceives important others to think about health and health behavior choices. SCT (Bandura, 1986, 2001) includes the role of others as behavioral models affecting health decision making. These social influences, however, vary by developmental period (Prohaska & Clark, 1997). For example, peer models may be particularly influential during adolescence. In addition, because the primary sources (e.g., friends, parents, spouses) of informational, tangible, and emotional social support are likely to vary predictably throughout the life span (Schulz & Rau, 1985), the way this support shapes health decisions is also likely to vary over the life course. Kahn and Antonucci (1980), for example, propose that an individual’s social network is a dynamic convoy that changes in structure and composition throughout the life course in response to changing situational factors of the individual. These changes are likely to affect the amount and type of influence that network members have on an individual’s health behaviors.
Structural Influences on Development and Health
Developmental influences on health operate concurrently with external factors that affect health and health behaviors both directly and indirectly. Murphy and Bennett (1994) suggest that health behavior may be best understood as “an interaction between individual features, the micro- and macro-social environment, and different stages in the life cycle.” SES is a prominent example of a structural variable that influences development, health, health behavior, and their interaction. Across the life span, health risks and conditions can be traced directly to poverty (e.g., violence in adolescence and young adulthood; mental health problems and lack of insurance in adulthood)—demonstrating that the health profiles of the poor across the life span are marked by risk and prevalence of disease greater at every point than those of their economically better-off counterparts (Bolig, Borkowski, & Brandenberger, 1999). Moreover, malnutrition early in life can affect the cognitive, behavioral, and social development of children, and prolonged exposure to poverty can affect the beliefs, attitudes, and cognitions of adolescents (Bolig et al., 1999). It should also be noted that economic poverty, particularly when combined with discrimination or racism from the society at large, may be associated with the development and maintenance of resources such as social networks and religiosity (McAdoo, 1995) that ultimately affect developmental trajectories, health, and health behavior choices.
SES may also affect the timing of health-related life transitions (e.g., earlier marriage and widowhood among those of low SES). This is exemplified in the weathering hypothesis (Geronimus, 1996), which explains high rates of teenage childbearing among the African American population as an adaptive response to impoverished circumstances that foster cumulative health risks in early adulthood (i.e., a weathering effect) that contribute to infant mortality. SES also determines the point in the life span at which the onset of chronic illness is likely to occur; this onset is more likely to take place in midlife for individuals of low SES than it is for their highSES counterparts (House et al., 1990).
Race and ethnicity, due to their association with SES, discrimination, cultural practices, and health beliefs, are also important structural factors that influence the impact of development on health and health behaviors. For example, the relative importance of family and peers during adolescence in shaping health-related decisions may vary with differences in cultural beliefs such as familism. Race may also affect the timing of developmental stages in ways that have implications for health and health behaviors; for example, poorer health among midlife and older African American males is associated with earlier exit from the labor force relative to Whites (Bound, Schoenbaum, & Waidman, 1996). Race also influences the length of the life span itself—for example, White males and females have a longer life expectancy than their African American counterparts do (R. N. Anderson, 1999)—which may in turn have an impact on health attitudes and practices throughout the life course.
The remaining sections of this research paper are devoted to a stage-specific look at developmental and life span influences on health behavior. A rationale for selecting physical activity and diabetes self-management behaviors to illustrate how these influences operate at each stage is provided first.
Physical Activity Across the Life Span
Physical activity is an “independent risk factor or potential treatment for most of the major causes of morbidity and mortality in western societies” and has been associated with positive physical and mental health across the life span (Singh, 2000, p. 6). For example, physical activity is associated with lower blood pressure, reduced risk of heart disease and cancer, improved cognitive functioning and mood, maintenance of functional independence, higher self-esteem, lower levels of stress, and improved well-being (DiLorenzo, StuckyRopp, Vander Wal, & Gotham, 1998; National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, 1997). Physical activity is also an important component of self-management regimens for many prevalent chronic illnesses, including diabetes, heart disease, hypertension, arthritis, and stroke (Singh, 2000).
In addition to the general benefits of physical activity, there are unique reasons for exploring the determinants of physical activity during each of the developmental periods highlighted in this research paper. For example, several risk factors for chronic diseases (e.g., hypertension) are associated with health practices, such as sedentary behavior, that originate during childhood (DiLorenzo et al., 1998). In addition, lifelong physical activity patterns may be established early. For example, adolescents who engage in regular physical activity are more likely to be active in adulthood than are sedentary adolescents (Telama, Yang, Laakso, & Viikari, 1997). Among midlife and older adults, regular physical activity is considered an integral part of preventive gerontology (Hazzard, 1995). Examining the developmental factors that influence physical activity will assist in the identification of age- and stage-appropriate interventions to foster regular exercise habits across the life span.
Diabetes Across the Life Span
Diabetes is one of the most prevalent chronic health conditions that is diagnosed across the life span. More than 15 million Americans have been diagnosed with this condition, and it is estimated that 5.4 million remain undiagnosed (Centers for Disease Control and Prevention, 1998). In general, children and adolescents are affected by Type 1 diabetes, also known as insulin-dependent diabetes mellitus (IDDM). The vast majority of cases of diabetes diagnosed in adulthood are referred to as Type 2 or non–insulin-dependent diabetes (NIDDM). The prevalence of this condition increases with age, as does the prevalence of diabetes-related complications (Centers for Disease Control and Prevention, 1998).
Diabetes serves as a useful model for self-care, or selfmanagement behavior, because it requires the coordination of several behaviors on a daily basis, including diet, exercise, insulin administration, and blood glucose testing (Delamater, 1993). Adherence to a complex behavioral regimen is important for maintaining optimal blood glucose levels and decreasing the risk of complications, including heart disease, stroke, and kidney disease (The Diabetes Control and Complications Trial Research Group, 1993).
Normal developmental processes among children and adolescents may both affect and be affected by diabetes selfcare behaviors. For example, diabetes self-management behaviors (e.g., adherence to a strict diet) may interfere with normal striving for independence as children mature and the desire for independence may in turn interfere with regimen adherence. The need to adhere to a complex behavioral regimen presents unique challenges for people with diabetes in midlife and older adulthood, who may be managing other chronic health conditions and may lack appropriate education, support, and motivation to engage in appropriate selfcare behaviors (Glasgow et al., 1992). Throughout this research paper, examples from the empirical literature on diabetes self-management are used to illustrate the importance of considering a life-span developmental approach.
Infancy and Childhood
A great deal of attention has been afforded to the influence of developmental processes on health issues during the early stages of life, particularly infancy, childhood, and adolescence. From a life-span perspective, studying health behaviors during these periods is critical, as this may be the time at which the stage is set for health attitudes and behaviors that will persist into adulthood (O’Brien & Bush, 1997; Roberts et al., 1984). The following sections summarize the influence of biological, cognitive, and social developmental factors on health behaviors in childhood (Tinsley, 1992). Although several examples from the infancy period are used, the primary focus of this section is on children, who are able—at least to a limited extent—to perform health-related behaviors and make health-related decisions. The reciprocal effects of health behavior on developmental processes and tasks are also considered in this section.
Biological Development and the Health Behavior of Children
Biological development during infancy and childhood affects health behavior in several ways. First, as children move from infancy to preadolescence, the diseases, conditions, and injuries for which they are at highest risk change. For example, infants, especially newborns, may be at highest risk for infectious disease, and young adolescents are at greater risk for morbidity associated with sexual behavior or substance abuse (Kolberg, 1999; Millstein et al., 1992). The importance of specific preventive health behaviors, therefore, also changes along with these risk profiles. For example, the risk of sudden infant death syndrome (SIDS) in infancy requires appropriate preventive behaviors on the part of parents—for example, placing the infant on his or her back when sleeping (Whitman, White, O’Mara, & Goeke-Morey, 1999). Second, children’s motoric and physical maturation and growth allow them ever greater independence in interacting with the physical environment, making them more likely to encounter certain health hazards (Roberts et al., 1984)—for example, bike-related injuries, necessitating instruction in appropriate use of a bike helmet, or infant exploration that necessitates “baby-proofing” by parents (Kolberg, 1999).
Third, as children grow and mature, they become able to perform preventive and self-management behaviors on their own, such as wearing a seatbelt, brushing their teeth, or injecting insulin (Roberts et al., 1984). Fourth, favorable biological conditions during childhood make chronic illnesses such as diabetes relatively rare. Thus, for children with chronic illness, the nonnormative nature of its occurrence has implications for adjustment and regimen adherence. For example, Delamater (1993) reports that adherence with diabetic regimens may be compromised when children are with their peers, suggesting that the fear of appearing different inhibits the practice of self-management behaviors.
Cognitive Development and the Health Behavior of Children
Children’s beliefs about health and illness and their implications for preventive and self-care behaviors have been the focus of a sizable body of research. Children make health decisions very differently from the way adults do, given qualitative differences in reasoning and logical thinking skills (O’Brien & Bush, 1997). It is therefore essential to consider cognitive development when attempting to understand the determinants of health behavior in children and when designing effective ways to educate children about health and illness. In general, improvements over time in the ability to think, reason, and understand allow children to make increasingly thoughtful and independent decisions about their health-related behavior (Roberts et al., 1984). However, by the time children reach adolescence, the so-called egocentrism (Elkind, 1967) that is typical of this period—along with social pressures—may actually increase the likelihood of engaging in health risk behaviors or of nonadherence to medical regimens (but see Beyth-Marom & Fischhoff, 1997). Indeed, in spite of increased cognitive sophistication, compliance with diabetic regimens is more of a problem among older children and adolescents who are beginning to test limits and authority than it is among younger children (Delamater, 1993; Kreipe & Strauss, 1989).
Cognitive Development and Health: Theories and Models
Several theories and models offer insight into how cognitive development affects health behavior. Tinsley (1992) distinguishes between (a) developmental models that emphasize similarities in how children progress through stages in their conceptualizations of health and illness; and (b) individual differences models that consider personality, social, and cultural variables in explaining health behaviors in children. An example of each of these two types of models is described next.
Bibace and Walsh’s model (1980; Thompson & Gustafson, 1996) is one of the most frequently cited cognitive development models of health- and illness-related behavior for children. This model posits six stages—phenomenism, contagion, contamination, internalization, physiological, and psychophysiological—that closely parallel Piaget’s preoperational, concrete, and formal operational stages. These stages are characterized by increasing logic, complexity of thought, ability to think abstractly, and sophistication regarding the causes of health and the relationships between behavior and illness. For example, in the early stages, children conceive of the causes of illness as being spatially proximate to the body and may confuse symptoms and causes of disease. Later, children begin to realize a degree of control over causes or cures of illness by avoiding or performing certain behaviors. Roberts et al. (1984) discuss the implications of this stagebased model for guiding health behavior interventions. For example, programs designed to teach children about healthpromoting behaviors should be sensitive to cognitive developmental stages. Efforts that are too sophisticated may be confusing, and those that are too simplistic may be ignored or discounted, although individual differences certainly need to be considered.
The Children’s Health Belief Model (CHBM; Iannotti & Bush, 1993), adapted from the widely used Health Belief Model (HBM; Janz & Becker, 1984), examines how individual beliefs inform children’s health behavior choices. The HBM posits that the likelihood that an individual will perform a given health behavior depends on (a) the threat an individual perceives from a given health risk, (b) the perceived severity of this risk, (c) the benefits of taking action to counteract the threat relative to the barriers associated with this action, (d) the presence of a cue to action, and (e) the individual’s level of self-efficacy for taking action. Similarly, the CHBM considers several readiness factors: motivation, perceived vulnerability to the health threat, perceived severity of the threat, and perceived benefits and barriers to taking action to avoid the threat. Unlike the HBM, however, the CHBM posits that these readiness factors are affected by modifying factors that are influenced by developmental stage. These modifying factors are classified as cognitive-affective (e.g., health locus of control, knowledge), enabling (e.g., autonomy), and environmental (e.g., attitudes and motivations of the child’s caregiver).
Cognitive Development and Illness Self-Care Behaviors
In addition to general cognitive developmental theories and models of health behavior, research has also provided insight into how cognitive development affects self-management behaviors among chronically ill children. Changes in memory, perception of time, and an understanding of causality and consequences all influence children’s ability to carry out complex behavioral regimens and to understand and communicate with health care providers (Iannotti & Bush, 1993; Johnson, 1993). Cognitive development—in particular, social reasoning and the ability to regulate emotions—may also influence the types of coping strategies used by chronically ill children. For example, younger children may be less able to engage in cognitive distraction or emotion-focused coping than are older children (Thompson & Gustafson, 1996). Chronic illness may also have an indirect impact on cognitive development among children to the extent that it limits active exploration of the environment or results in school absences (Patterson, 1988).
The effect of cognitive development on self-management behaviors can be clearly illustrated in the case of childhood diabetes. Savinetti-Rose (1994) notes that children who have diabetes and who are in the early stages of cognitive development may not be able to conceive of a connection between their treatment regimen and their illness. She describes how more advanced cognitive development enables children with diabetes to better understand the rationale behind the treatment plan and also to take greater responsibility for carrying it out. For example, after a child is able to understand number concepts and seriation and when memory skills improve, he or she can better plan the timing of insulin doses, meals, and physical activity.
Social Development and the Health Behavior of Children
Two important social influences—parents and peers—on health behaviors during childhood are considered briefly in this section. Special attention is given to the way in which the relative importance of these social influences changes as a child develops. Also highlighted is the increasing autonomy a child experiences in health decision making and health behavior choices. Indeed, the increasing responsibility children assume for their own behavior is one of the most important effects of social development at this stage (Roberts et al., 1984).
The primary role of parents in shaping health behavior choices among children has been highlighted by a number of researchers (e.g., O’Brien & Bush, 1997; Tinsley, 1992). DiLorenzo et al. (1998) discuss the importance of socialization within the family and of parental modeling of health behaviors through “patterns of interaction, imposition of opportunities and restraints, and reinforcement of health-related activities” (p. 471).
Empirical evidence, however, for similarities in preventive health behaviors between parents and children has been mixed (O’Brien & Bush, 1997; Tinsley, 1992). DiLorenzo et al. (1998) examined the influence of parental beliefs, attitudes, and behaviors about physical activity on the exercise habits of fifth and sixth graders. Results of this longitudinal study demonstrate that parental influence may vary by age and gender, change over time, and operate in conjunction with other social, cognitive, and environmental variables. For boys, encouragement and modeling of physical activity by friends and family were important determinants of physical activity. For girls, both peer support and family support of physical activity were important, along with exercise knowledge and mother’s physical activity level.
Kimiecik, Horn, and Shurin (1996) also examined the impact of the family on children’s (ages 11–15) moderate-tovigorous physical activity. Results indicate that children’s beliefs about physical activity were strongly related to their perceptions of their parents’ beliefs (in terms of the value placed on physical activity and the child’s physical activity competence), although these perceptions were not related to actual physical activity levels. Despite the lack of relationship in this case between beliefs and behavior, this study highlights the congruence between children’s and parent’s beliefs regarding physical activity and the potential for parental attitudes to shape health behavior-related cognitions in children.
As children grow and develop, the role of peers in influencing health attitudes and behaviors increases (Tinsley, 1992). General research on peer influences suggests that this influence might vary a great deal depending on individual factors among children (e.g., self-esteem; Tinsley, 1992). In a qualitative analysis of the personal illness models of children with diabetes, Standiford, Turner, Allen, Drozda, and McCain (1997) found that both preadolescents (ages 10–12) and adolescents (ages 13–17) relied strongly on their families for help with diabetes treatment regimens, but that families were mentioned more often by the younger group. More respondents in the older group mentioned support from friends as being important.
As with cognitive development, there may also be a reciprocal effect of illness on social development. This effect may be especially salient in the case of peer relationships. Responses to illness by peers (Thompson & Gustafson, 1996), absences from school, or feelings of being different may impede friendships and make acceptance by peers more difficult (Miceli, Rowland, & Whitman, 1999). In general, chronic illness during childhood poses challenges to the normative transition to greater involvement with a peer group as childhood progresses.
Finally, it is important to keep in mind that developmental variations in the sources of influence on health behavior decision making are likely to be more complex and involve more factors than a simple peer-versus-parent model would suggest. For example, Tinsley, Holtgrave, Reise, Erdley, and Cupp (1995) found that habit and enjoyment (personal factors) were better predictors of preventive (e.g., seat belt use) and risky (e.g., cigarette use) health behaviors than was the perceived influence of parents, teachers, friends, and various media sources across elementary and high school students. They also discovered that personal factors played a larger role in the health behavior decisions of older compared to younger students (Tinsley et al., 1995).
Autonomy in Diabetes Self-Care
Another important transition for children is the gradual process of assuming responsibility for their own healthrelated decisions and behaviors. Autonomy in health decision making during childhood can be defined as “those behaviors indicating that the child cooperates in, takes the initiative for, has the capability for, or has responsibility for health promotion or treatment” (Iannotti & Bush, 1993, p. 64). The issue of when children are ready to make their own health decisions—and when they actually do so—has increased in importance over the last couple of decades, a development particularly evident in the increased attention to the selfmanagement of childhood chronic illness.
Issues associated with autonomy can be clearly illustrated in the case of diabetes self-care. For example, if too much responsibility is placed on children who are not cognitively ready, they may be inadvertently noncompliant because of knowledge absences or skill deficits (Johnson, 1993). This notion is supported by a study by Wysocki et al. (1996), who found that high levels of self-care autonomy for diabetes (defined by the ratio of diabetes self-management autonomy to intellectual, social-cognitive, and academic maturity) was associated with poorer treatment adherence, poorer diabetes control, lower levels of diabetes knowledge, and increased hospitalizations. These results, however, do not suggest that children are unable to engage in self-care; rather that the expectation for their self-care must be informed by developmental issues.
In fact, research suggests that relatively few self-care responsibilities are perceived as appropriate for preadolescent children by diabetes professionals. Wysocki, Meinhold, Cox, and Clark (1990) asked 229 health professionals to estimate the age at which children typically are able to master 38 diabetes-related skills. Recognizing and reporting hypoglycemia was thought to be appropriate for children at 6.5 years. On the other end of the age continuum, planning an exercise routine and taking into account insulin schedule and diet were thought to be inappropriate until age 14. An interesting result was that the estimates given varied greatly according to profession, with physicians tending to give the highest age estimates for each of the tasks.
This section has highlighted how biological, cognitive, and social development influences health-related behaviors during childhood. Adolescence is associated with a host of developmental transitions that are likely to have a strong impact on the behavioral choices—and ultimately the health status—of members of this age group. These factors are presented in the following section.
This section focuses on the effects of biological development (i.e., physiological changes associated with puberty), cognitive development (i.e., increasing cognitive sophistication and egocentric beliefs), and social development (i.e., the increasing importance of peers) on health behaviors during adolescence. As noted earlier, environmental, contextual, and structural factors may influence adolescent health behaviors directly and may also shape the way in which developmental factors affect health behavior choices ( Brooks-Gunn, 1993; Cowell & Marks, 1997; Lerner, Ostrom, & Freel, 1999; Schulenberg, Maggs, & Hurrelmann, 1997a). Such factors include—but are not limited to—gender, race-ethnicity, social class, culture, religion, social environment, and access to health care services. Thus, the reader is cautioned that the developmental influences as described in subsequent sections are only main effects that must eventually be embedded in a much broader context that includes both structural and demographic factors. Consequently, developmental variables inevitably explain only a limited amount of the variance in health behavior choices among adolescents. Nonetheless, understanding the potential effects on health behavior of the “fundamental and nearly universal transitions” that characterize adolescence is an essential starting point when planning interventions to affect adolescent health (Maggs, Schulenberg, & Hurrelmann, 1997).
Health behaviors take on particular importance in adolescence for two primary reasons. First, several of the leading causes of morbidity and mortality in this age group are related to behavior (Cowell & Marks, 1997). Second, adolescence marks an important period of transition from parental control to self-determination of behavior (BrooksGunn, 1993). Although a number of factors suggest that this developmental period should be characterized by optimal health (e.g., increased strength and stamina, a lack of vulnerability to the major health threats of adulthood), many adolescents face significant health risks, particularly those related to accidents (e.g., motor vehicle injuries) and lifestyle choices (e.g., sexually transmitted diseases, substance abuse; Gondoli, 1999). Moreover, these health risks may be increasing with subsequent cohorts of adolescents, lending urgency to the study of adolescent health behaviors and their determinants (Lerner et al., 1999).
Because adolescence is a time of biological, cognitive, emotional, and social transitions (Cowell & Marks, 1997; Gondoli, 1999), it provides a unique context for examining health behavior choices. Although adolescence is most frequently associated with problem health behaviors (e.g., tobacco and alcohol use; Petersen, 1988), this developmental period may have both positive and negative effects on health-related behaviors (Schulenberg et al., 1997b). For example, health risk behaviors may play a constructive role in negotiating developmental transitions (e.g., binge drinking may ease the transition to the college social environment by increasing acceptance by peer groups), while at the same time posing serious health risks (Maggs et al., 1997; Schulenberg et al., 1997b). The impact of adolescent development on preventive health behaviors has received limited attention in the empirical literature, despite the potential for establishing positive lifelong habits at this stage (Maggs et al., 1997). Among adolescents with a chronic illness, health behaviors take on special importance because they face the usual developmental risks for suboptimal health, as well as additional risks related to illness selfmanagement.
Biological Development and the Health Behavior of Adolescents
Puberty has been defined as “a series of hormonal and somatic changes that adolescents experience as they attain reproductive capacity” (Gondoli, 1999, p. 149); it includes development of the adrenal glands, gonads, and secondary sex characteristics (Cowell & Marks, 1997). Although there is a great deal of individual variation in the timing of these changes, they generally take place between 8 and 13 years of age in girls and between 9.5 and 13.5 years of age in boys (Gondoli, 1999).
Gondoli (1999) has identified three themes emerging from research on puberty and health. First, puberty affects how adolescents perceive themselves and how they are perceived by others. These perceptions in turn may affect health behavior. Among adolescent girls, for example, the increase in body fat associated with puberty may increase their susceptibility to eating disorders (Brooks-Gunn, 1993). Second, the timing of puberty appears to carry a great deal of significance when it comes to health behavior decisions. For example, early or precocious puberty appears to be associated with greater prevalence of risk behaviors such as alcohol and tobacco use in both genders; moreover, in girls, off-time puberty—whether precocious or delayed—might pose a greater risk for low self-esteem (Silbereisen & Kracke, 1999), which might ultimately influence health behavior. Third, the social context in which puberty occurs determines in large part its effects on behavioral choices.
In addition to affecting health risk behaviors, pubertal status may also affect the practice of preventive health behaviors. Lindquist, Reynolds, and Goran (1999) found independent effects of pubertal development and age on physical activity among children ages 6–13 years. Specifically, they found that although older children were more likely than were younger children to participate in organized sports, children in a higher stage of pubertal development were less likely to do so than were children with less advanced development. They conclude that the social, psychological, and behavioral consequences of pubertal development have a negative impact on physical activity levels, and that the apparent effect of age in previous studies on decreases in physical activity may actually be due to physical maturation. Goran, Gower, Nagy, and Johnson (1998) found evidence for a sharp reduction in girls’ physical activity preceding pubertal changes that may be related to biological development or to behavioral or environmental changes accompanying puberty.
Hartman-Stein and Reuter (1988) have discussed the potential effects of pubertal status on diabetes self-care behaviors. After puberty, for example, in an effort to maintain or lose weight, adolescent girls with diabetes may be more likely to develop disordered eating patterns that jeopardize blood glucose control. In addition, there may be a reciprocal effect of self-care behaviors on pubertal markers; for example, poor diabetic control in adolescent girls may lead to missed or light menstrual periods.
Cognitive Development and the Health Behavior of Adolescents
Increasing cognitive sophistication among adolescents has important implications for health decision making. Most adolescents have entered the formal operations stage of cognitive development, marked by the ability to engage in abstract thought and to understand the psychological and physiological causes of illness (Schulz & Rau, 1985). In addition, by adolescence, the knowledge base regarding health and illness is much larger than that in childhood (Cowell & Marks, 1997). One result of these changes may be a heightened belief by adolescents in their ability to affect symptoms and health outcomes (Patterson, 1988).
Brooks-Gunn (1993) highlights three additional cognitive processes that may influence adolescent health behavior: perceptions of costs and benefits, perceptions of risk, and understanding of future consequences of health-related actions. The costs and benefits of health-related actions may be evaluated by adolescents differently from the way those in other age groups evaluate them; for example, among adolescents, the social benefits of engaging in a particular risk behavior such as smoking may be more likely to outweigh the known negative consequences.
Although teenagers may be increasingly able to understand concepts of probability and risk, other factors associated with adolescence may foster risk-taking behaviors. For example, perceptions of good health and lack of experience with poor health may lead to feelings of invulnerability. Indeed, one manifestation of so-called adolescent egocentrism is said to be belief in a “personal fable” in which adolescents imagine themselves to be invincible (Elkind, 1967). Such feelings are often assumed to contribute to a propensity for risk behaviors, although it has been argued that there is little empirical evidence to support this notion (Gondoli, 1999). Moreover, later scholars have suggested that the creation of personal fables is adaptive and contributes to resilience and coping (Lapsley, 1993); hence, the influence of such fables might be expected to ultimately have positive influences on health behaviors. Therefore, the precise ways in which adolescent perceptions of invulnerability affect health behavior choices remain unclear.
Otherfactorsthatfosterhealth-riskbehaviorinadolescents may include lack of experience with the consequences of risk, lack of information, or denial (Brooks-Gunn, 1993). Researchers have also suggested that adolescent’s risk perceptions reflect their behavioral experiences, instead of the other wayaround.Forexample,Halpern-Felsheretal.(2001)found that adolescents and young adults who had engaged in particular health risk behaviors (e.g., related to sexual activity and alcohol use) judged the risks of negative outcomes from those behaviors as less likely than did nonengagers. Such findings have implications for attempts to modify behavior-specific risk perceptions among adolescents and may underscore the importance of preventing initiation of risk behaviors in late childhood or early adolescence.
Finally, the ability of adolescents to consider long-term consequences of health-related actions (Brooks-Gunn, 1993) may have special relevance when it comes to decision making about preventive health behaviors with long-term benefits, such as diet or physical activity. However, the extent to which adolescents consider the proximal versus long-term benefits when it comes to making decisions about these behaviors has not been well established.
Explaining Physical Activity Patterns in Adolescence
In general, levels of physical activity decline between childhood and adolescence (National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, 1997), challenging health researchers and professionals to identify the developmental and contextual factors that contribute to this decrease. Much of the research on the determinants of physical activity among adolescents considers cognitive and social-cognitive factors in tandem, along with demographic and social-structural factors. Variables such as SES, ethnicity, gender, and the physical environment all predict patterns of activity in this age group; for example, female adolescents and those of lower SES engage in less activity—as do adolescents living in highcrime areas (Gordon-Larsen, McMurray, & Popkin, 2000); these factors and their interaction with psychosocial factors therefore are an important focus of current research in this area.
Garcia, Pender, Antonakos, and Ronis (1998) conducted a study that explores changes in cognitive and social factors related to physical activity during the transition to adolescence. Their sample (n 132) was tracked from elementary to junior high school. Results indicate that when girls reached junior high school, they were less likely to report that the benefits of exercise outweighed the barriers, and they had fewer physically active role models than they had at younger ages. Boys making the transition had less self-efficacy for physical activity and were less likely to perceive social expectations that they would be active compared to when they were in elementary school. Both boys and girls were less likely to report social support for exercise from family and friends following the transition to junior high school. In other words, positive beliefs about physical activity declined for both boys and girls.
Allison, Dwyer, and Makin (1999) examined the impact of self-efficacy, perceived barriers, and life strain on the physical activity of 1,041 students in Grades 9 and 11. Results indicated that one component of self-efficacy (i.e., confidence despite external barriers) was positively associated with physical activity participation. Life strain and perceived barriers were not strongly related to physical activity. These findings suggest that efficacy-enhancing strategies may present one way to offset a decline in physical activity as children mature.
Cognitive Development and Diabetes Self-Care in Adolescence
Cognitive changes during adolescence are likely to affect diabetes self-care behaviors in several ways. During early adolescence, children in the concrete operational stage may be unable to consider the potential future complications resulting from noncompliance and may focus instead on more immediate concerns (e.g., inconvenience of blood glucose monitoring, embarrassment of eating a snack during class; Kreipe & Strauss, 1989). By middle adolescence—with the advent of formal operational thinking and an increasing sense of personal control—children may be better able to understand the role of self-care behaviors in preventing long-term complications (Hartman-Stein & Reuter, 1988). Despite this new level of cognitive sophistication, adherence to strict behavioral regimens may be compromised by the fact that adolescents at this stage are striving for independence, identity, and autonomy and are testing limits and authority (Kreipe & Strauss, 1989). Kriepe and Strauss (1989) suggest that at this stage, treatment options should be structured to maximize the adolescent’s sense of control and independence. For example, adolescents could be offered the option of using an insulin pump in an effort to avoid regular insulin injections that may interrupt valued social activities.
A study by Ingersoll, Orr, Herrold, and Golden (1986) provides evidence that cognitive development affects diabetes self-care behavior. Among adolescents aged 12–21, Ingersoll et al. (1986) found that those who practiced anticipatory glucose control (i.e., adjusting an insulin dose according to anticipated changes in exercise and diet) had a level of conceptual maturity higher than the conceptual maturity level of those who did not.These results suggest that health care professionals should consider the extent to which an adolescent is able to make the complex decisions involved in diabetes management; they should then work with parents to ensure that the degree of autonomy given to an adolescent to manage his or her treatment plan is developmentally appropriate.
Social Development and the Health Behavior of Adolescents
The increased importance of peer influence is an accepted hallmark of adolescence (Brooks-Gunn, 1993). Adolescents have larger networks of peers than do children, as well as more stable, intimate, and supportive friendships that occupy more time and have more influence over attitudes and behaviors (Brown, Dolcini, & Leventhal, 1997; Petersen, 1988). Despite the central role of peers, research has also demonstrated the ongoing influence of parents on health behavior choices. For example, Lau, Quadrel, and Hartman (1990) found in a longitudinal study that although peers had a strong effect on the extent to which adolescents experienced changes in health behaviors such as drinking and exercise during the first 3 years of college, the effect of parental influence (particularly via modeling) on these behaviors also remained strong throughout the study period.
Several transformations in peer relationships during the adolescent years may have an impact on health behaviors. These transformations include (a) the development of emotionally supportive friendships, (b) the initiation of romantic relationships, and (c) the emergence of peer crowds (Brown et al., 1997; Gondoli, 1999). Each of these changes may have either a positive or negative influence on health behavior. For example, research has demonstrated both positive and negative associations between the intimacy and level of support from friendships and the practice of health risk (Brown et al., 1997). For example, becoming part of a romantic relationship may increase the probability that an adolescent will engage in sexual risk-taking, but such relationships may also be associated with decreases in risk behaviors more common in same-sex cliques (e.g., alcohol use; Brown et al., 1997). The relationship between peer crowd membership and health behaviors is complex, because peers are often defined (both by researchers and by youth themselves) in terms of the types of health behaviors in which their members engage (e.g., druggies, jocks). Thus, individual differences in the practice of health behaviors may channel youth into certain peer crowds, and peer crowd norms may reinforce positive and negative health behaviors (Brown et al., 1997).
Social Development and Diabetes Self-Care
Adolescent social transitions—in particular, the increase in the importance and influence of peer relationships—are commonly seen as a barrier to effective diabetes selfmanagement. Compared to children, adolescents have been shown to have poorer adherence to diabetic regimens, and older adolescents may be less adherent than younger adolescents (Kovacs, Goldston, Obrosky, & Iyengar, 1992; La Greca et al., 1995). Attaining optimal adherence and metabolic control has been called “more problematic” for adolescents than for any other age group (La Greca et al., 1995). Researchers have noted that adolescents with diabetes experience conflicts between the drive to attain independence and gain peer acceptance on one hand and adherence to their diabetes regimen on the other (Anderson, Wolf, Burkhart, Cornell, & Bacon, 1989; Hartman-Stein & Reuter, 1988). Moreover, barriers to adherence are present at precisely a time when parents and providers begin to expect adolescents to assume a greater degree of independence and autonomy in their self-care (Anderson et al., 1989; Wysocki et al., 1996).
The influence of peer relationships on diabetes self-care behavior, however, is not uniformly negative. As demonstrated by LaGreca et al. (1995), the friendships of adolescents with diabetes can be an important source of support by providing assistance with insulin administration, blood glucose monitoring, following a meal plan, exercising, and “feeling good about diabetes.” Although family members provided more tangible support such as preparing meals and helping with blood glucose monitoring, friends offered companionship and emotional support and encouraged physical activity. LaGreca’s (1995) study underscores the value of considering the important role of friends in addition to family members in the design of educational interventions for adolescents with diabetes.
Compared to early and late in the life span (i.e., infancy, childhood, adolescence, older adulthood), relatively little is known about health and development during midlife (Lachman & James, 1997; Merluzzi & Nairn, 1999; Willis & Reid, 1999). In fact, the middle years are often depicted as little more than a “staging area on the way to old age” (Baruch & BrooksGunn, 1984, p. 1). Several factors, however, will result in increased emphasis on midlife in the scholarly literature in the decades ahead; such factors include the movement of the largest cohorts in U.S. history through this developmental period and an accompanying increase in the median age of the U.S. population (Willis & Reid, 1999).
A life-span perspective on health during midlife is important because this transition is influenced by the health behavior choices and patterns of young adulthood and sets the stage for older adulthood. As stated by Willis and Reid (1999), “optimal physical and psychological development in late life will depend largely on the experiences of baby boomers during middle age” (p. xv). Despite the fact that midlife is a period of relatively good health for most people, the frequency of chronic illnesses, persistent symptoms, disability, and mortality rates accelerate during this period (Merrill & Verbrugge, 1999). Thus, middle age represents a shift in how people view their health—in part due to their increased sense of vulnerability to health threats (Hooker & Kaus, 1994; Merluzzi & Nairn, 1999). It should be noted, however, that perceptions of health in middle age are embedded in existing social structures that present both opportunities and constraints (Elder, 1998), including social class, education, gender, and race (Moen & Wethington, 1999).
Although chronological age is an imperfect proxy for marking developmental periods, it provides a starting point for purposes of discussion. Despite the popular view that midlife begins at age 35 (Moen & Wethington, 1999), other conceptualizations of this period have been more refined. For example, Merluzzi and Narin (1999) describe early adulthood as the period from age 22–34 years; early middle age as between 35 and 44 years of age, and late middle age as between 45 and 64 years of age. Age 45 has been viewed as marking the beginning of the period of midlife in the U.S. census as well as by researchers (Merrill & Verbrugge, 1999). Rather than rely on chronological age, several markers of midlife boundaries have been examined in research on this period, including transitions in employment (e.g., career peaking and early retirement; Moen & Wethington, 1999) and parenting (i.e., the period when children move into school age, adolescence, and early adulthood; Brooks-Gunn & Kirsh, 1984).
In midlife, there are few markers of physical change as dramatic as those that occur in childhood and adolescence (e.g., walking, puberty) or in old age (e.g., rapid decline in health, death; Merrill & Verbrugge, 1999). Most physical changes are very gradual, and individual differences greatly affect the rate of physiological change.
As summarized by Merrill and Verbrugge (1999), signs of physiological change include alterations in physical appearance (e.g., wrinkles, age spots, gray hair), losing height and gaining weight, decreased muscle strength, loss of bone density, lower basal metabolic rate, weaker immune response, diminished sense of smell and taste, gradual hearing loss, decline in eyesight, and poorer sleep habits. The extent to which these age-related processes—particularly weight gain and changes in appearance—provide an incentive to engage in health-promoting behaviors and limit health-damaging behaviors has not been explored to any great extent in the literature. Extensive research evidence, however, supports the link between health habits and chronic illnesses and conditions, and it suggests that engaging in health-promoting behaviors can prevent or delay disease and some of the aging changes that occur in midlife (Merrill & Verbrugge, 1999).
In keeping with the general framework established for this research paper, this section highlights how specific aspects of biological (i.e., menopause), cognitive (i.e., personal control, self-efficacy), and social (i.e., social support) development affect health and self-management behaviors during the middle years.
Biological Development and the Health Behavior of Adults in Midlife
Menopause is thought to represent a major cultural, psychological, and physiological milestone for women during the middle years (Avis, 1999), and it represents one of the few distinct health events of midlife. In fact, most of the health-related research among women at midlife focuses on experiences of menopause and the management of its symptoms (Woods & Mitchell, 1997). Although there is wide variability among women in the age of menopause, the median age of last menstrual period is between 50 and 52 years of age (Brambilla & McKinlay, 1989), and 80% of women experience their last menstrual period between 45 and 55 (Avis, 1999). The hormonal changes associated with menopause affect the musculoskeletal, cardiovascular, and urogenital systems, precipitating increases in heart disease, hypertension, osteoporosis, urinary incontinence, autoimmune disease, and diabetes (Avis, 1999). Although menopause represents a significant life event, few empirical studies have examined the impact of this milestone on health behaviors.
Menopause and Physical Activity
One qualitative study of 17 women in middle age lends insight into how menopause might influence women’s decisions about health behaviors such as physical activity. Jones (1997) discovered that women perceive menopause as a marker or symbol of more general life-stage developmental issues and respond with lifestyle adjustments, including changes in physical activity (i.e., exercising more regularly and vigorously) and diet (i.e., eating more low-fat foods, introducing or increasing calcium supplements). The women who participated in the study all reported engaging in high levels of exercise and being healthy eaters before menopause; these behaviors increased or became more disciplined with the onset of negative health-related changes associated with menopause (Jones, 1997). Additional research is needed to reveal the specific ways in which attitudes and beliefs about physical activity are affected by this important transition (see Avis & McKinlay, 1995; Pinto, Marcus, & Clark, 1996; Scharff, Homan, Kreuter, & Brennan, 1999).
Menopause and Diabetes Self-Care
More research attention is also needed to determine how the physical transitions experienced in midlife may affect diabetes self-management behavior. According to the HBM, individuals are more likely to engage in preventive and selfmanagement behaviors if they perceive a significant health threat. Perceived threat derives from perceptions of the severity of the health condition and of susceptibility to negative health outcomes attributed to behavior. Thus, to the extent that menopause heightens perceptions of threat, women in midlife may engage in high levels of regimen adherence.
Although empirical evidence of the possible impact of menopause on self-management behaviors is limited, a small body of research addresses the impact of menopause on a variety of diabetes-related and psychosocial outcomes. In a review of the literature, Javanovic (1997, 1998) concludes that menopause decreases the insulin requirement in women with Type 1 diabetes, increases the risk of depression and cardiovascular disease, and increases percentage of body fat, resulting in increased insulin resistance in women with Type 2 diabetes. In her discussion of diabetes among women, Poirier and Coburn (2000) suggest that menopause results in extreme swings in blood glucose levels, which can complicate self-management efforts. She also describes how women with diabetes may not be able to distinguish between episodes of hypoglycemia and hot flashes. Additional research is needed to determine how changes related to menopause affect the experience of diabetes, diabetes-related outcomes, and— ultimately—self-management behaviors.
Cognitive Development and the Health Behavior of Adults in Midlife
As discussed by Merluzzi and Nairn (1999), one of the overarching themes in the transition from perceived invulnerability and risk taking in the early part of the life span to substantial vulnerability to health threats toward the end is a sense of personal control. The middle years have been described as a time of “settling down” (Levinson, 1977), marked by the perception of increased control and feelings of security and stability that are greater than those at other developmental periods (Lachman, Lewkowicz, Marcus, & Peng, 1994; Wallston & Smith, 1994). Thus, the role played by cognitive phenomena—including perceptions of control— in the health behavior decisions of adults at midlife is of particular interest.
Although several conceptualizations of control have been advanced in the literature, self-efficacy is one of the most frequently used measures of this construct. Self-efficacy is defined as the belief that an individual can successfully engage in a particular behavior (Bandura, 1997). This construct is used often in the empirical literature on the determinants and effects of health behaviors, such as physical activity and disease self-management.
Self-Efficacy and Physical Activity in Midlife
In an empirical study of factors associated with physical activity in 653 women across the life span, Scharff et al. (1999) discovered that women in midlife reported having higher levels of self-efficacy for physical activity than did older women; however, women in midlife also reported much lower levels of self-efficacy than did younger women. In fact, the authors report that women in midlife (aged 40–49) were more than twice as likely as the younger women (18–39 years of age) to be unsure of their ability to meet their physical activity goals (Scharff et al., 1999). In terms of their current levels of physical activity, older women were the least likely to be physically active.
Other findings from this study are also of interest. Family characteristics associated with midlife—particularly having children at home—were consistently related to patterns of physical activity. For example, women at midlife with children at home reported significantly higher levels of physical activities of daily living (e.g., house and yard work) than did women without children at home (Scharff et al., 1999). This study represents one of the few examples of research that acknowledges the possible impact of developmental milestones (e.g., menarche, having children, menopause, career choices) on self-efficacy related to the initiation and maintenance of physical activity in women.
Self-Efficacy and Diabetes Self-Care in Midlife
The role of personal control and self-efficacy in diabetes self management has been the focus of a great deal of empirical research across life stages. Adherence to challenging medical regimens like those required for the successful selfmanagement of diabetes is thought to be more consistent and longer lasting among people with strong beliefs in their abilities to affect their health (O’Leary, 1985). In a recent study of 296 adults with diabetes (with a mean age of 52 years), Watkins et al. (2000) discovered that perceived control of diabetes was asignificantpredictorofdiabetes-specifichealthbehaviors,including following a diet and engaging in regular exercise.
In terms of our understanding of how personal control affects diabetes self-management at midlife, additional research is needed to answer such questions as (a) Does the overall increase in general perceptions of control in midlife translate into higher levels of self-efficacy for self management behaviors; (b) Are levels of control and selfefficacy for managing illness relatively stable over the life span, or are they affected significantly by the developmental context; and (c) How might control and self-efficacy work differently for people who are diagnosed with diabetes in midlife compared to those who have lived with the disease since adolescence? Such research could help to identify strategies used to maintain high levels of control and self-efficacy for self-management tasks across the life span, including adopting age-related performance standards, engaging in social comparison with same-age peers, and optimizing skills in selected areas such as health beliefs and physical-capacity change over time (Merluzzi & Nairn, 1999).
Social Development and the Health Behavior of Adults in Midlife
Two aspects of the social environment take on particular importance at midlife—social support and social roles (Antonucci & Akiyama, 1997). Avast empirical literature examines the impact of social support on a variety of mental and physical health outcomes, including morbidity and mortality (for a review, see Berkman & Glass, 2000). A smaller body of literature examines the impact of social support on self-management behaviors during adulthood (for a review, see Gallant, in press). For example, family members and friends may facilitate or impede health and self-management behaviors by offering information, advice, and encouragement, and by providing emotional and tangible support (Lewis & Rook, 1999).
Although the general social support literature is very compellinginitsquantityandoverallquality,itrarelyincorporates specific discussion of the unique developmental context of the middle years (for an exception, see Connell & D’Augelli, 1988). Kahn and Antonucci (1980) argue that there are four major reasons for considering the changing nature of social support over an individual’s life: (a) role entries and exits create changing needs and circumstances for support; (b) the forms and amount of support appropriate for a given time and place depend on these changing life stations; (c) individual differences among adults in the need and desire for social support must be understood via reference to earlier life experiences; and (d) age, period cohort, and history effects may be discerned by a reference to individual experiences.
In addition to the changing patterns of social support over the life span, the pattern and types of social roles held during adulthood—particularly work and family—are critical to an understanding of health behavior choices during midlife (Moen & Wethington, 1999). Studies of the interplay of social support, role trajectories, and health in midlife that reflect a developmental perspective, however, are uncommon (Moen & Wethington, 1999).
Social Factors and Physical Activity in Midlife
It is generally assumed that both general and exercisespecific social support factors are positively associated with physical activity. Eyler et al. (1999) conducted one of the few empirical studies to examine the relationship between social support and physical activity levels of women in midlife and older adulthood. Using a national sample of minority women aged 40 and older, results indicate that women with low levels of social support for physical activity were more likely to be sedentary than were women with high levels of such support. The authors suggest that interventions designed to increase physical activity should incorporate the social networks of potential participants to increase the likelihood that women will initiate and maintain an exercise program (Eyler et al., 1999). The authors did not specifically address issues of midlife, however, despite having a large sample size (n 2,912) that would lend itself to comparisons in study outcomes across the life span and contribute to the discussion of how social roles associated with midlife might increase or inhibit physical activity.
Social Factors and Diabetes Self-Care in Midlife
Because diabetes is a psychologically and behaviorally demanding illness, psychosocial factors are particularly relevant to the process of self-management (Delamater et al., 2001). In fact, the psychosocial impact of diabetes has been recognized as a predictor of mortality in people with diabetes that is stronger than many clinical and physiological variables (Davis, Hess, & Hiss, 1988).
In general, the empirical research suggests that higher levels of social support—especially diabetes-related support from spouses and other family members—is associated with better regimen adherence, including diet, exercise, and weight management (Glasgow & Toobert, 1988; Wilson et al., 1986). This research, typically conducted with samples of adults spanning a large age range and based on crosssectional designs, provides a snapshot of the relationships among social factors and diabetes self-management behaviors. Additional research, however, is needed to determine how the key social roles of midlife (e.g., parent, spouse, employee) affect the relationship between social support and self-management behavior during this period.
Although a great deal of attention has been afforded to the general area of health and aging, a relatively small subset of this work overtly incorporates a life-span developmental perspective. Because a life-span view of development is dynamic and marked by the continuous interplay between growth and decline, research guided by this perspective is more likely to include a focus on positive (rather than only negative) age-related changes and gains (rather than only losses; Baltes & Baltes, 1990; Lachman, Ziff, & Spiro, 1994). In addition, a life-span developmental perspective emphasizes intra-individual variability; thus, this view recognizes that people—even in later life—have the potential to improve their adaptive capacity and to experience unique developmental trajectories (Baltes, Reese, & Nesselroade, 1988).
In light of this potential, it is apparent that older adults should be a major focus of the growing body of research on the determinants of health behavior and interventions to shape this behavior (Schulz & Martire, 1999). A selected review of the health behavior literature, however, suggests that older adults are not well represented (Connell, 1999). Specifically, only 15% of articles published in two leading health behavior journals (i.e., Health Education and Behavior, formerly entitled Health Education Quarterly; and Health Education Research: Theory and Practice) over a 10-year period included older adults in the sample. In the majority of the articles that included older adults, age was not examined in the data analysis, and the context of older adulthood was not considered in the discussion of findings. A similar finding is reported by Peterson (1996), who found that less than one quarter of the studies published in the journal Health Psychology over a 3-year period dealt with older adults. Of the few studies that included adults in more than one period (e.g., midlife and older adulthood), the influence of development was rarely addressed (Peterson, 1996). Thus, despite the vast literature on issues related to health and aging, much remains to be learned about the health behaviors of older adults, particularly from a life-span developmental perspective.
The final section of this research paper focuses on how specific aspects of biological (i.e., functional capacity), cognitive (i.e., personal control, self-efficacy), and social (i.e., social support, social roles) development affect health and selfmanagement behaviors during older adulthood. As with other periods of the life span, the importance of structural factors such as gender, class, race, and ethnicity should be considered throughout this discussion because they are likely to have both independent effects on the health behaviors of older adults (Markides, 1989) and interactive effects with development-related factors discussed here.
Biological Development and the Health Behavior of Older Adults
Normal aging has been described as the time-dependent, irreversible changes that lead to progressive loss of functional capacity (i.e., respiratory function) after the point of maturity (Moody, 1998). Age-related physical changes include sensory declines, loss of muscle mass and bone density, increased risk of fractures, wrinkled skin, and short-term memory lapses. About 80% of people over the age of 65 have one or more chronic conditions. Three quarters of all deaths of people over the age of 65 are due to heart disease, cancer, and stroke (National Center for Health Statistics, 1996).
Despite the health declines that are typically associated with aging, older adults may be more likely than their younger counterparts to engage in positive health behaviors.
For example, results from the National Health Interview Survey suggest that older adults are more likely than younger adults to report never having smoked cigarettes, abstaining from alcohol, drinking in moderation, eating breakfast regularly, and obtaining general medical exams (Thornberry, Wilson, & Golden, 1986). Older adults, however, are much less likely than are young and middle-aged adults to be physically active (Healthy People, 2000, 1991; U.S. Department of Health and Human Services, 1996).
Biological Aging and Physical Activity
The bidirectional relationship between physical activity and the declines in functioning associated with aging has not been fully explored. Although it has been established that physical activity is an important avenue for delaying the negative health consequences of aging (e.g., risk of physical decline, chronic disease, and mortality) and promoting a variety of positive psychological and physical outcomes among older adults (for a review, see McAuley & Katula, 1999), little is known about how physiological changes associated with aging affect attitudes and beliefs about physical activity.
Just as during midlife, negative age-related health changes in older adulthood may affect health behaviors such as physical activity in a variety of ways. For example, the onset of illness or a perceived decline in physical ability may provide incentive for people who have engaged in physical activity throughout their adult years to maintain and even increase their patterns of exercise. Alternatively, some adults may feel resentful when confronted with the need to adapt their lifelong exercise routines to their gradually diminishing physical capacity. Age-associated health changes can also mean that individuals who have never engaged in regular exercise may find this period a particularly daunting time to begin a routine of regular physical activity.
Becauseexerciseisacornerstoneofmanyself-management regimens,olderadultswhoarediagnosedwithachronicillness may be motivated to increase their level of physical activity, even if they had been sedentary earlier in life. This motivation may be bolstered by advice from a health care professional to initiate or maintain physical activity (Russell & Roter, 1993). Additional research is needed to assess how attitudes and beliefsaboutphysicalactivitymayevolveasaresultofbiological changes—both normal and pathological—associated with older adulthood.
Cognitive Development and the Health Behavior of Older Adults
Perceptions of control may be particularly important for the health of older adults (Mirowsky, 1995; Rodin, 1986). Empirical evidence, however, suggests that older adults report a decrease in objective and subjective control (Bandura, 1997), and this loss is related to functional impairment, cardiovascular disease, cancer, deterioration of the immune system, and mortality (as summarized in Bergeman & Wallace, 1999). As described in an earlier section, the concept of selfefficacy (i.e., belief that an individual can successfully engage in a particular behavior) is one aspect of perceived control that has demonstrated a strong association with health behavior.
Self-Efficacy and Physical Activity in Older Adulthood
Of the considerable literature that has identified self-efficacy as an important predictor of exercise behavior and vice versa (McAuley, 1992; O’Leary, 1985), several empirical studies have included or focused exclusively on older adults (D. O. Clark, 1996). For example, Resnick (2001) found that among a sample of 175 older adults in a retirement community, selfefficacy for exercise significantly predicted moderate exercise. In another empirical study, McAuley, Lox, and Duncan (1993) examined the extent to which physical activity facilitates self-efficacy over time. Results from a sample of 44 older adults who completed a 20-week exercise program indicated that self-efficacy was the only significant predictor of exercise behavior at 9 months postintervention. Among 225 community-dwelling older adults aged 65–92, Conn (1997) demonstrated that self-efficacy was a strong predictor of physical activity. Finally, in a study of 327 women aged 70–98 years living in Vancouver, British Columbia, selfefficacy for physical activity later in life was found to be associated with recollections of specific childhood physical activity competencies from decades earlier (Cousins, 1997). This study is important because it is one of the few that examines how health-related experiences at earlier stages can affect specific health behaviors at later stages.
Kaplan and his colleagues have conducted several studies to examine the physical and psychosocial responses to physical activity in older adults with chronic obstructive pulmonary disorder (Kaplan, Reis, Prewitt, & Eakin, 1994; Ries, Kaplan, Limberg, & Prewitt, 1995; Toshima, Kaplan, & Ries, 1990). In one such study, Toshima et al. (1990) report that an 8-week exercise training intervention conducted with 119 older adults resulted in higher levels of self-efficacy for exercise and exercise tolerance compared to a comparison group. Thus, the available evidence suggests that enhancing selfefficacy may be one important means of increasing exercise levels among older adults.
Despite evidence that engaging in exercise increases levels of self-efficacy and that self-efficacy for exercise predicts exercise behavior, few studies have examined the extent to which the decline in physical activity that is commonly associated with older adulthood is related to more global decreases in perceived control. Obviously, a longitudinal design is best suited to address this issue. Similarly, we know little about how increasing physical activity levels via interventions may offset age-related declines in control.
In an ongoing study, Connell and colleagues are assessing the impact of a telephone-based physical activity intervention on psychosocial and physical outcomes among women who are providing full-time care to a spouse with a dementing illness. A primary goal of the study is to examine whether women who set and achieve realistic goals for increasing physical activity also experience a heightened sense of selfefficacy in several key domains (e.g., physical activity and self-care) and demonstrate subsequent improvement in indicators of physical and psychological health. Positive findings in this regard would suggest a potentially valuable means of enhancing control among a vulnerable older population.
Additional research is also needed to examine how the developmental context of older adulthood affects the four types of influence on efficacy expectations—primary experience, secondary experience, verbal persuasion, and physiological states (Bandura, 1986). Older adults may have less direct experience with physical activity as a function of their birth cohort; less secondary experience because there are fewer opportunities to observe exercise behavior in general and among peers; and fewer sources of verbal persuasion to exercise among the media, supportive others, and health care professionals (D. O. Clark, 1996). Physiological states may play a particularly important role in shaping efficacy expectations among older adults. Older adults are more likely than younger and middle-aged adults to experience poorer overall health; more past failures at behavior change; and— regarding physical activity—difficulty with balance, a fear of falling, and complications from comorbidities (D. O. Clark, 1996). Future research should address the specific mechanisms whereby self-efficacy affects exercise behavior and exercise affects self-efficacy among older adults; how the conceptualization and measurement of self-efficacy are shaped by the context of older adulthood; and how contextual variables such as SES, gender, and race affect self-efficacy expectations.
Self-Efficacy and Diabetes Self-Care in Older Adulthood
Although research has demonstrated that self-efficacy is a predictor of diabetes self-management among adults, older adults have not been included in much of this work.An exception is the development and evaluation of a self-management training program designed specifically for people 60 years of age and over with Type 2 diabetes (Glasgow et al., 1992). Results indicate that the program was effective in improving dietary intake and glucose testing and resulting in weight loss among the participants in the intervention group. Contrary to expectations, however, behavior change was not attributed to increases in diabetes-specific self-efficacy. The authors contend that this surprising finding may be attributed to ceiling effects, given that levels of self-efficacy were high at baseline (Glasgow et al., 1992).
Although this study makes an important contribution to the literature because it describes one of the few published interventions designed exclusively for older adults with diabetes, the authors provide little information about how the program was tailored to the needs of the target audience, whether the process (e.g., self-efficacy) and outcome (e.g., self-care behaviors, glycosylated hemoglobin, quality of life) measures used in the study were appropriate for use with older adults, and how the developmental context of older adulthood may have affected the study findings.
To best examine changes in the relationship between selfefficacy and self-care behavior over the life span, longitudinal research is needed. A case could be made that as people age, they become more experienced at illness self-management, resulting in increasing levels of self-efficacy. Alternatively, it is equally possible that the challenges of older adulthood could erode self-efficacy for illness management. The reciprocal and dynamic nature of these relationships needs to be acknowledged and investigated in future research.
Social Development and the Health Behavior of Older Adults
Social factors are central to the maintenance of health and functioning in older adulthood. For some older adults, aging is associated with good health and fulfillment, whereas for others, aging brings chronic illness, disability, and disengagement (Riley & Bond, 1987). As stated by Riley and Bond (1987), such differences in how people age are influenced not only by biology, but also by the social environments in which they grow old—by the work they do, the people with whom they interact, and the community in which they live. Social factors also influence individuals’ perceptions of health and illness and their behavioral responses (Riley & Bond, 1987).
A small body of research examines the impact of life transitions during older adulthood on health behaviors and selfcare practices. Many of these life transitions have a direct effect on the quality and quantity of social support available to older adults. For example, dietary changes among older adults may be a result of the loss of a spouse rather than an age-associated change (Prohaska & Clark, 1997). In an empirical study by Rosenbloom and Whittington (1993), married older adults were compared to same-aged adults who were recently widowed. Compared to those whose spouses were still living, widows reported a loss of appetite, a high level of unintentional weight loss, and a lack of enjoyment for eating meals.
Assuming the role of caregiver for an ill spouse is another common life transition among older adults. The responsibilities of caregiving may limit opportunities to engage in positive health behaviors and may promote reliance on negative health behaviors. In an empirical study, Gallant and Connell (1997) discovered that almost half of a sample of 233 spouse caregivers reported being less physically active than they were before they began providing care to their spouse. In addition, almost half of the women in the sample reported gaining weight since caregiving began. The caregivers’attributed these negative health behaviors in part to their changing relationship with their husbands. Specifically, many study participants reported that their patterns of exercise and meal preparation had changed dramatically because they could no longer count on the positive social influence that their husband had provided (e.g., serving as an exercise buddy, having someone with whom to prepare and enjoy healthy meals). Thus, periods of life transition (e.g., widowhood, caregiving, retirement, change in residence) may be viewed as an ideal time to promote and support positive changes in health behaviors, including physical activity (King, 2001).
Social Development and Diabetes Self-Care in Older Adulthood
The social context of older adulthood also affects selfmanagement behaviors of people with chronic illnesses. Continuing with the example of diabetes self-management, Connell, Fisher, and Houston (1992) examined the relationships among both general and diabetes-specific measures of social support and self-care in a sample of 191 older adults with Type 2 diabetes. For men, results from this study support the contention that social support specific to one’s diabetes regimen increases self-care behavior. For women, neither diabetes-specific nor general support was related to self-care behavior. Men and women did not differ, however, in the amount of assistance with their diabetes regimen that they receive or desire from their family and friends (e.g., help with following a meal plan). These findings point to the complexity of the relationship between support and self-management behaviors and the importance of considering multiple conceptualizations of support, demographic, and other contextual factors (e.g., gender).
In a related study, Connell (1991) reported that a sample of older adults with diabetes perceived high levels of emotional support related to their diabetes self-care— encouragement, reassurance, and someone to listen to their problems and concerns. In terms of tangible support, however, the majority of older adults reported that they did not want a lot of help from their family and friends related to the self-management. More older adults reported receiving help than reported wanting help with their regimen. Providing support that is not desired, even when offered with good intentions, may be perceived as nagging or as interference (Connell, 1991). As suggested in other research, the characteristics of and the relationship between potential support providers and recipients may determine whether support has a beneficial impact on self-management behavior. Additional research that considers the developmental context of older adulthood is needed to deepen current understanding of the changing role of support over the life span and how it affects both health behaviors and diabetes self-care.
Directions for Future Research
The goal of this research paper was to adopt a life-span developmental perspective to guide a discussion of the determinants of health behaviors during five stages—infancy, childhood, adolescence, midlife, and older adulthood. Obviously, the published literature relevant to this topic is voluminous and presented quite a challenge in terms of selecting the best possible examples to illustrate the major themes of the paper. Despite the impressive quantity and overall high quality of the available research, a great deal of additional work needs to be completed to better address how biological, cognitive, and social development influences health behavior across the life span.
The vast majority of relevant studies are based on crosssectional designs, which present implicit difficulties when the goal is to assess change over time and the dynamic and reciprocal influences of development on health behaviors. For example, little is known about the effect of health behaviors at one life stage on health behaviors at subsequent stages—in part because of the relatively few longitudinal studies that have been conducted in this area. Additional research is also critical to increase our understanding of the developmental context of health behaviors during midlife. Although great strides have been made in recent research (e.g., Willis & Reid, 1999), much remains to be done.
Discussion of how best to adapt existing health behavior theories (e.g., health belief model, social cognitive theory, theory of planned behavior) to better address research questionsbasedonalife-spandevelopmentalperspectiveisneeded. Similarly, a careful analysis of whether commonly used conceptualizations of relevant concepts (e.g., self-efficacy, personal control, social support) are appropriate for various life stages would be of great value to those conducting research in this area. Finally, in order to better account for the complexity of the determinants of health behavior and to acknowledge the broader context in which health decisions are made, there is a critical need to examine the interaction between developmental phenomena and such extrinsic factors as SES, race, culture, and gender.
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