Child Health & Development: General Practice: The Integrative Approach Series

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Add Health is a national longitudinal study of more than 20, adolescents in grades 7—12 in who have been followed into young adulthood with three follow-up waves of interviews. Waves I and II occurred in —, when the sample was in adolescence, the majority of whom were aged 12—19; Wave III occurred in —, when the Add Health cohort was aged 18—26 and making their transition to adulthood. The recent Wave IV was completed in , when the cohort was aged 24—32 and settling into adulthood.

For more details on the design of Add Health, see Harris et al. An integrative approach begins with theory and study design. The purpose of Add Health, as mandated by Congress, was to explore how the social contexts of adolescent life influence the health and health behavior of young people. Theory suggested that the social environment becomes especially important during adolescence as young people begin to choose their environments and spend more time outside the family setting Furstenberg ; National Research Council The design of Add Health captured the theoretical sources of environmental influence by measuring key factors in the social contexts of adolescent life, including the family, peer, school, neighborhood, community, and romantic and sexual relationship.

Unique to Add Health as a social and behavioral study is that it captured the social, psychological, and behavioral domains at these multiple levels, and it included the biological domain in its original design. The following sections provide a few illustrations of this integrative design. Add Health measured social, demographic, economic, and cultural factors of the individual and his and her social environment, including the family, peer, romantic and sexual relationships, school, work, neighborhood, and government and policy contexts.

Reflecting a strength of population science, the Add Health design obtained independent measures of characteristics of friends and peer networks, family, school, neighborhood, and the larger community by including these clusters as part of the sampling design and not depending on self-reports of the characteristics of these contexts.

Add Health captured the emotional, mental, and cognitive dimensions of individuals, and these factors can also be measured at the family, peer, school, and neighborhood levels. Examples of factors in the psychological domain are personality, temperament, verbal aptitude, affect, learning disabilities, future expectations, positive orientation, self-esteem, and self-efficacy. Add Health focused on health and attainment behaviors, beginning in adolescence and incorporating adult behaviors as the cohort aged.

Coverage includes prosocial, healthy, and health-risk behaviors; educational achievement; and demographic behavior. Behavioral factors are also measured at multiple contextual levels of the family, school, peer network, and neighborhood. Because of the theoretical role that biology plays in health, the Add Health design included the biological domain from the start by embedding a genetic sample of over 3, pairs of adolescents with varying degrees of genetic resemblance, including identical and fraternal twins, full siblings, half siblings, cousins, and adolescents growing up in the same household with no biological relationship.

When only the environmental effect is measured, the genetic effect is included in the estimated environmental effect. The embedded genetic sample in Add Health, however, allows researchers to parse out environmental from genetic influence on health outcomes. In adolescence, we also included standard indicators of physical development and height and weight, from which we have been able to track body mass index and obesity into adulthood.

As the Add Health cohort aged, our design continued to incorporate the biological domain that was theoretically relevant to the developmental stage of the cohort, just as we did for factors in the social, psychological, and behavioral domains. At Wave III, when the cohort was aged 18—26, the ages of highest risk for sexually transmitted infections, we collected biospecimens to test for sexually transmitted infections STIs and HIV. To strengthen our genetic design, we collected buccal cell DNA for molecular analysis of genetic and gene-environment interaction effects in health and health behavior.

Reward Yourself

At Wave IV, we focused on the major health risks of the cohort at this time: Certain biological processes play roles in these diseases, and specific biomarkers can be used to characterize these processes Crimmins and Seeman Known methods offer feasible ways of measuring these biomarkers in large, nonclinical field settings such as Add Health, and we used these methods to greatly expand the biological domain at Wave IV to obtain objective measures of health status. For example, we obtained markers of metabolic function e. We expanded our DNA collection to the entire sample and collected information about prescription medications.

This integrative approach continues to capture the key theoretical social, behavioral, psychological, and biological processes represented in the major health issues for the ages of the Add Health cohort as they progress into adulthood. Moreover, the integrative approach in theory and design allows for the integration of data to improve measurement—two aspects we care a lot about in population research.

Table 1 shows prevalence estimates of hypertension and diabetes based on preliminary data collected in Wave IV of Add Health, when the sample was 24—32 years old. By combining self-reports with objective biological measures and pharmacologic data, we obtain a more valid estimate of prevalence. Young Adults Aged 24— Estimates are based on preliminary unweighted Wave IV data N ranges from to 15, Self-reports of hypertension indicate that When we combine this report with medication use for high blood pressure, prevalence rises slightly to When we combine these survey measures with objective biological measures from blood pressure BP readings and use standard BP cutoffs recommended by the American Heart Association, the prevalence of stage 2 hypertension rises to We see similar gains in measuring all cases with diabetes.

Based on self-reports and medication use for diabetes, 3. Combining the survey data with objective biological measures of diabetes risk from glucose and glycosylated hemoglobin HbA1c assays on a blood drop from a finger stick, the percentage with diabetes doubles to 6. Self-reports severely underestimate the prevalence of these serious and growing health conditions within the young adult population. Moreover, these health conditions lead to future chronic illness and disease, and with an integrative design, we have the ability to identify the social, psychological, behavioral, and biological precursors that make up predisease pathways.

Recent analyses of the causes of deaths in the United States indicate that the single greatest opportunity to improve health and reduce premature deaths lies in personal behavior McGinnis and Foege ; Mokdad et al. I now return to health during adolescence and young adulthood and focus on these particular behaviors—smoking, physical inactivity, and obesity—among young people because of their significant consequences for adult health and premature death.

Earlier, I argued that greater involvement in health-risk behavior during the prolongation of the transition to adulthood, and the creeping of health problems into the young ages, have consequences for adulthood health in two ways. First, there is substantial evidence that health tracks across the life course Halfon and Hochstein Recall the worsening trends in health status, behavior, and health care during the transition to adulthood that I summarized earlier from our health disparities research Harris et al.

Health patterns during the transition to adulthood may set health trajectories into adulthood. Second, health during the transition to adulthood has important consequences for key social and economic outcomes, including marriage, fertility, education, occupation, and income. Health in young adulthood may increasingly become an important marker of social stratification. Below, I show some hints of these two important consequences.

The next set of figures presents evidence of how health tracks across the life course. Figure 5 extends the trajectory of obesity that I showed earlier for the adolescent and young adulthood ages by adding the next point in adulthood at ages 24—32 for males and females in Add Health. These aggregate patterns are the result of both individual stability and increasing rates of entry into obesity. Figure 6 shows the cohort trajectory for levels of no bouts of physical activity from adolescence into adulthood by sex.

Physical activity is measured using a standard physical activity behavior recall Anderson et al. Lack of exercise, or no physical activity, is defined by self-reports of no bouts of moderate to vigorous physical activity 5—8 metabolic equivalents per week. Physical activity levels improve slightly in adulthood, and the sex gap narrows somewhat but remains significant. More importantly, the relatively high levels of no exercise are set coming out of adolescence.

Figure 7 presents the trends for regular smoking. Again, we see that the prevalence of smoking levels off in adulthood, but the levels are set and the significant sex disparity emerges in the transition from adolescence into young adulthood. Two important findings come out of these data. First, the largest increase in poor health—as indicated by obesity, smoking, and lack of physical activity—occurred during the transition from adolescence into young adulthood. As young people settle into adulthood, levels of poor health behavior stabilize, with the exception of obesity, but that level is set coming out of adolescence, a vulnerable time for health in early life.

Second, disparities by sex grow with age, and there is evidence of widening disparities in these health behaviors across age for other population characteristics, such as race, ethnicity, and socioeconomic status Harris et al. I have provided evidence that adolescence and the transition to adulthood can set health trajectories into adulthood, but do these patterns matter for general health and disease risk given that young people are generally healthy, with low prevalence of disease or chronic illness?

I now turn to whether health trajectories from adolescence into young adulthood are related to health outcomes in adulthood to further explore how health tracks across the life course. In Figure 8 , I examine the relationship between the obesity trajectory from adolescence into young adulthood and markers of future disease in adulthood to begin to map predisease pathways.

Markers of future disease are measured in Wave IV, when the Add Health sample was 24—32 years old, by indicators of 1 diabetes, 2 hypertension, 3 high cholesterol, and 4 sleep problems. Diabetes is indicated by whether the respondent self-reported diabetes diagnosis, is taking medication for diabetes, had a random glucose assay result of or greater, or had a glycosylated hemoglobin HbA1c assay result of 6. Hypertension is measured by self-report of hypertension diagnosis, using medication for hypertension, having a systolic blood pressure SBP reading greater than or equal to , or having a diastolic blood pressure DBP reading of or greater i.

Cholesterol is measured by self-report only. Individual obesity trajectories from adolescence when the Add Health cohort was aged 13—19 in Wave II to young adulthood when they were aged 18—26 at Wave III are categorized into three groups: Add Health data diabetes, hypertension, cholesterol, and sleep problems based on preliminary Wave IV data. The results in Figure 8 generally show an increasing percentage that have diabetes, hypertension, high cholesterol, and sleep problems, with increasing time obese in adolescence and young adulthood.

Poor metabolic function, represented by high cholesterol and diabetes, is generally uncommon for young people aged 24—32, but those who are obese as they enter adulthood, and especially those who begin their obesity trajectory in adolescence, face much higher risks of these metabolic disorders in early adulthood. The increase in hypertension is particularly dramatic among those in obese trajectories, doubling the percentage of 9. The impact of obesity on quality of life and general health is furthermore seen by the increase in severe sleep problems with longer obese trajectories.

An Integrative Approach to Health

Evidence indicates that cigarette smoking and sleep problems characterize predisease pathways for cardiovascular disease risk Young et al. Indeed, I find that smoking during adolescence and the transition to adulthood and sleep problems in adulthood are associated with hypertension in adulthood.

These descriptive relationships between health trajectories in adolescence and the transition to adulthood and markers of future disease at such an early age in adulthood forebode profound implications for future morbidity and chronic illness throughout adulthood, as well as substantial medical care costs for the individual and society as a whole. Finally, I end with some hints of how health trajectories from adolescence into young adulthood are associated with demographic outcomes and markers of social stratification in adulthood.

Table 2 provides descriptive data on the relationships among the three behavioral trajectories of obesity, physical activity, and regular smoking from adolescence to young adulthood, with indicators of socioeconomic status and income at Wave IV in adulthood. In this table, I contrast trajectories of good or improving health 3 not obese, physically active, and not a regular smoker with poor health always obese, never physically active, and always a regular smoker throughout adolescence and young adulthood.

Social stratification measures are binary indicators of ever attended college, finished college, ever married, and home ownership, all measured at Wave IV. Income measures are presented as household income respondent income and income of everyone in the household who contributes to the household budget , personal earnings of those employed , and household assets total value of respondent assets and assets of everyone in the household who contributes to the household budget. The overall findings show a strong and significant relationship between longitudinal poor health trajectories in adolescence and through the transition to young adulthood and social and economic outcomes in adulthood.

For example, compared with those who were not obese, young people who were obese during adolescence and the transition to adulthood were significantly less likely to attend college Never engaging in physical activity from adolescence and into adulthood was also associated with a lower likelihood of attending college, finishing college, and owning a home, as well as lower average household income, personal earnings, and total assets compared with those who were physically active in adolescence and young adulthood.

Adolescent to young adulthood trajectories of regular smoking show the same negative relationship with college attendance, college completion, and income indicators in adulthood, but have a slightly positive association with ever married and home ownership compared with the trajectory for not being a regular smoker.

The overall consistency and strength of these descriptive results suggest the importance of health among the young as a marker for social stratification early in the adult life course. I have tried to make the case for using an integrative approach to health, broadly defined as social, emotional, mental, and physical well-being; for studying health among the young as an important marker for future health and well-being across the life course; and for understanding health disparities among the young as both causes and consequences of social stratification.

I want to encourage population scientists to embrace an integrative approach in their research because population scientists bring strengths to this approach that other disciplines do not. Population training and research is inherently transdisciplinary, so these barriers are less of a problem in our field. We bring strengths in study design, measurement, data collection, and analytic tools that are required to achieve an integrative approach. Population scientists are ideally positioned to show that behavioral and social processes have broader significance and are fundamental to a comprehensive understanding of disease etiology as well as the promotion of health and well-being.

Incorporating the biological dimensions of health improves our understanding of the social and behavioral dimensions of health and lends credibility to our findings that biomedical scientists cannot ignore. But an integrative approach involves more than sticking biological measures in with social, psychological, and behavioral measures in our models; it is more than collecting biomarker data just because we can.

An integrative approach brings together biological sciences with social and behavioral sciences in its theory and design, data collection, measurement, and analysis. Many demographers have written about and conduct research that brings biology into our models of social and behavioral phenomena, and there are two monographs on the collection of biological data in social surveys National Research Council , In this article, I have tried to articulate this integration as a research process and to advocate for this integration in the study of health among the young.

Research from Add Health suggests that an especially critical time that sets health trajectories into adulthood occurs during the transition from adolescence into young adulthood, when young people exercise more control over the selection of their social environments and make behavioral choices regarding their health.

With an integrative foundation in theory and design, we will better understand the social, psychological, behavioral, and biological origins and tracking of predisease pathways that offer the promise of reducing future disease and chronic illness, as well as social and economic inequalities. The empirical examples I have used in this article primarily focus on individual health trajectories over time and highlight the biological measures expanded in Wave IV of Add Health.

Other empirical evidence from Add Health illustrates the theoretical importance of the social contexts for health trajectories that are facilitated in an integrative design. Research has documented associations with obesity for peer networks e. Health-risk behavior is associated with peers e. Moreover, exploration of the genetic data in Add Health uncovered a gene-environment interaction of the dopamine transporter gene, DAT1, with the proportion of the high school population who had had sex by age 16 in relation to the number of lifetime sex partners Guo, Tong, and Cai Such evidence of the role that peer, school, and neighborhood contexts play in health and health behavior early in the life course emphasizes the need to track health trajectories as young people move into and through adulthood in order to understand the enduring influence of social context as a key element of the integrative approach to health.

Add Health is not the only study with an integrative approach, and it is not the only study that allows population scholars to bridge biomedical and social sciences in their research. I mentioned just a few of the rich and innovative studies breaking ground in this area at the beginning of this article. The antecedents of predisease pathways likely begin before adolescence, in childhood, at birth, in the womb, and in the health behavior and genetic profiles of parents.

To the extent that social, behavioral, psychological, and biological data can be collected retrospectively or during these critical life stages, these rich data sources will further the development and knowledge to be gained from an integrative approach for understanding health trajectories of children. Inter- and intragenerational data from the biological and extended family of origin e.

These and other exciting research opportunities are becoming available, and I expect population scholars will become the leaders in this new scientific frontier. Think big, but start small and build. Putting the pieces together in an integrative approach from theory to design to data and analysis will contribute more to science than the sum of its parts; it will advance knowledge about the world around us and change the future for health research, politics, and policy.

This research uses data from Add Health, a program project designed by J. Richard Udry, Peter S. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. I do not elaborate on this trend here because it is has been so widely documented in population science over the past 40 years. Blood spots were collected for assay of lipids in Add Health Wave IV, but these results were not available at the time this article was prepared.

An improving health trajectory includes those who have poor health in adolescence but better health by young adulthood e.

This trajectory is relatively uncommon. National Center for Biotechnology Information , U. Journal List Demography v. Author information Copyright and License information Disclaimer. This article has been cited by other articles in PMC. Abstract In this article, I make the case for using an integrative approach to health, broadly defined as social, emotional, mental, and physical well-being; for studying health among the young as an important marker for future health and well-being across the life course; and for understanding health disparities among the young as both causes and consequences of social stratification.

Open in a separate window. Office of Budget, National Institutes of Health. Total Number of Deaths, by Age: United States, Source: Social Add Health measured social, demographic, economic, and cultural factors of the individual and his and her social environment, including the family, peer, romantic and sexual relationships, school, work, neighborhood, and government and policy contexts.

Psychological Add Health captured the emotional, mental, and cognitive dimensions of individuals, and these factors can also be measured at the family, peer, school, and neighborhood levels. Behavioral Add Health focused on health and attainment behaviors, beginning in adolescence and incorporating adult behaviors as the cohort aged.

Biological Because of the theoretical role that biology plays in health, the Add Health design included the biological domain from the start by embedding a genetic sample of over 3, pairs of adolescents with varying degrees of genetic resemblance, including identical and fraternal twins, full siblings, half siblings, cousins, and adolescents growing up in the same household with no biological relationship.

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