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

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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. 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.

Integrative Approach to Child and Adolescent Mental Health

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.

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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. 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. Remaking the American Mainstream: Assimilation and Contemporary Immigration.

Harvard University Press; Lawrence Erlbaum Associates; Fertility, Biology, and Behavior: An Analysis of the Proximate Determinants. New York and London: Centers for Disease Control and Prevention. National Diabetes Fact Sheet: National Academies Press; Twenty-Five Years of Health Progress. Metropolitan Life Insurance Company; The Development of Population Statistics. Research Design Available online at http: Fundamentals of Genetic Epidemiology. Oxford University Press; Racial Trends and Their Consequences. Marmot M, Wilkinson RG, editors. Social Determinants of Health.

Health, United States, National Center for Health Statistics; The nervous system is derived from the ectoderm—the outermost tissue layer—of the embryo. The neuroectoderm appears in the third week of fetal development and forms the neural plate that is the source of the majority of neurons and glial cells in the mature human [ 1 ]. This is called the neural tube which later gives rise to the brain, the spinal cord, and the telencephalon, which eventually encompasses the two lateral ventricles, which in turn develops into the areas of the brain known as the basal ganglia and the limbic system [ 2 ].

Over time, cells cease division and begin to differentiate into neurons and glial cells, creating the main cellular components of the brain. The newly created neurons migrate to various parts of the brain to differentiate into the different brain structures. The fetal brain develops from neurons moving outward from early precursor cells [ 3 ]. At birth, the infant has many more neurons and synapses than it will use as an adult [ 4 ]. The strong bond and attachment of infants to their parents are crucial at a young age since their physical and social environments aid to strengthen the neurons that are used repeatedly.

Several clinical and animal studies have shown that providing a child in developmental stages an enriched physical or social environment can significantly improve learning and memory, encourage exploration, and decrease fearful responses to new and unfamiliar experiences [ 5 — 10 ]. It can also reduce the impact of genetic or environmental risk matters. Despite these experimental and clinical researches, it is hard to know the relationship between the particular mechanisms of brain development and mental activities.

Psyche is a function of the brain, and psychic phenomena and disorders may have neurobiological correlation. According to a longitudinal study, children as young as 18 months may suffer from mental illness as older children do. Risk factors and predictors of mental illness could be identified in the first 10 months of life, and the association of risks found in studies of older children seems to operate already from birth [ 11 ].

Even though there is plenty of research, it would be necessary to have further evidence between mental illness and risk factors of children at a young age. Ten to twenty percent of children and adolescents experience mental disorders worldwide [ 12 ]. Research has shown that most mental disorders begin at childhood and adolescence [ 13 , 14 ]. Developmental brain dysfunction, which can manifest as neuropsychiatric problems or impaired motor function, learning, language, or non-verbal communication are also characterized by abnormal behavioral or cognitive phenotypes originating either in utero or during early postnatal life.

The causes of mental disorders in children and adolescents are not currently known, but research suggests that a combination of factors that include heredity, biology, psychological trauma, and environmental stress might be involved [ 15 ]. A large cohort study of neurodevelopmental disorders showed a direct association of the severity of the physical condition with most classes of mental disorders. It also showed a strong overlap between physical and mental conditions and their impact on the severity of functional impairment in youth [ 16 ].

Specific patterns of comorbidity have important implications for the etiology. Prospective tracking of cross-disorder morbidity will be important to establishing more effective mechanisms for the prevention and intervention of mental disorders [ 16 ]. Genomic technology has shown great advances in gathering evidence that the current paradigm of psychiatric research needs to be updated. These studies provided converging evidence across a number of different levels, supporting the hypothesis that genetic risk factors are shared between disorders and challenging the validity of the classification systems currently used in research and clinical practice [ 17 ].

Through genomic technology, the growing list of genes that contribute to early onset developmental disorders is in its hundreds. That increasing number is further complicated by the observation that each patient can carry a unique combination of alleles of varying degree of effect that occurs de novo or inherited [ 18 ]. In the last 10 years, tremendous progress has been made in our comprehension of early onset developmental disorders [ 19 — 26 ]. To date, five main pathways have been identified as candidates for early onset neurodevelopmental disorders: Understanding the symptoms and course of action for each individual, as well as the biology ranging from genetic and environmental risk factors to the neural circuits involved, remains a substantial challenge for geneticists and neurobiologists [ 27 — 29 ].

Many mechanisms of human brain development remain hidden, but neuroscientists are beginning to uncover some of these complex steps through extensive studies [ 30 — 32 ]. Research finds that neurons migrate from their birthplace near the ventricular walls to their final destination in the brain. As they collect together, they form each of the various brain structures and acquire specific ways of transmitting nerve messages.

The result is the creation of a precise and elaborate adult network of billion neurons capable of directing a movement in the body, a perception, an emotion, or other brain functions. In , scientific and clinical research groups were formed to create an agenda for the fifth major revision of the Diagnostic and Statistical Manual of Mental Disorders DSM-5 [ 33 ]. These groups generated hundreds of white papers, monographs, and journal articles that provided the psychiatric field with a summary of the state of the science relevant to psychiatric diagnosis and faults within the current research in order to fortify knowledge in those fields.

The Task Force was also aided by 13 different work groups tasked with focusing on various disorder areas.

DATA ON HEALTH

Despite the great advances in neuroscience and genetic research during the last 20 years, there are still too few reliable genetic or other biomarkers that can reliably guide the diagnosis of psychiatric disorders. As a diagnostic tool, the DSM considers different disorders as distinct entities. However, from the diagnostic perspective, such disorders do not classify neatly within their boundaries as the DSM would want it. As an alternative tool for diagnosis and research into psychiatric disorders, the U. This new project strives to create an experimental classification system that can provide a first step toward precision medicine for mental disorders [ 34 ].

The RDoC stems from the Research Diagnostic Criteria RDC , created in the s in response to the problems in diagnosis that the field of psychiatry experienced as it emerged from the shadow psychological domination [ 35 ].

The RDoC framework strives to free researchers and investigators from the rigid classification system of the DSM and pursue research questions in psychopathology that take advantage of burgeoning knowledge of complex behaviors and how these relate to specific aspects of brain activity [ 38 ]. It provides a set of guidelines for evaluating the strength of hypotheses relating clinical symptoms or impairments to dimensions of behavioral functioning and neural systems. The future of the RDoC is undetermined but will depend on how well the diagnostic system can direct clinicians to concise and effective treatment or prevention strategies for each individual patient [ 38 ].

The RDoC approach to clinical research of child and adolescent psychopathology contributes to the understanding of development as an aspect of the heterogeneity within DSM disorders and commonalities across seemingly disparate disorders. Incorporating the RDoC as a diagnostic tool in this area of clinical research promises to be fruitful avenue of research into the root causes and manifestations of mental illness, eventually leading to more precise and patient-specific treatments [ 39 ].

Behavioral and emotional mental disorders with a high prevalence frequently commence in childhood or adolescence. With some respect, the fetal origins of adult disease models explain the associations between undernutrition of the fetus and an increased risk of cardiovascular disease, diabetes, and metabolic syndrome in later life [ 40 ]. This model has been expanded to include events beginning prior to conception as well as early postnatal life [ 41 ]. Three main classes of prenatal exposure were investigated in the late s for a range of general health outcomes: Recent human epidemiological and animal studies indicate that stressful experiences in utero or during early life may increase the risk of neurological and psychiatric disorders, arguably via altered epigenetic regulation.

Altered epigenetic regulation may potentially influence fetal endocrine programming and brain development across several generations, resulting in the added attention paid to possible transgenerational effects of stress. Based on existing evidence, it would be possible that prenatal stress, as an epigenetic factor, may become one of the most powerful influences on mental health in later life [ 43 ].

Epidemiological studies suggested that gestational exposures to environmental factors such as stress are strongly associated with an increased incidence of neurodevelopmental disorders, including attention-deficit hyperactivity disorder ADHD , schizophrenia, autism spectrum disorders ASD , and depression [ 44 — 47 ].

There is growing evidence from human studies showing that early exposures to lifestyle factors and maternal mental health are predictive of child behavioral, emotional, and learning outcomes. Already a number of successful programs have been developed, such as nurse visitation in the perinatal period [ 48 ].

An Integrative Approach to Health

Recent emerging evidence shows that current interventions aiming to prevent postnatal depression in women are beneficial and effective not only for women with depression but also for those suffering from anxiety and high stress disorders [ 49 — 51 ]. Fetal programming refers to the way in which environmental events alter the course of fetal development, resulting in lasting modifications in the structure and function of biological systems.

Programming refers to the influence of a specific environmental factor at a specific point in development. There are exposures during pregnancy such as maternal mental health, lifestyle factors, and potential teratogenic and neurotoxic exposures on child outcomes. Outcomes of interest are common child and adolescent mental disorders such as hyperactive, behavioral, and emotional disorders.

The preconception and perinatal periods offer opportunities for the prevention of harmful fetal exposures. Therefore, it is imperative that during the perinatal period maternal mental health prevention efforts should be most strongly advocated and developed. Interventions developed with evidence-based advisement for the perinatal period could later be instituted into the public health system and grow toward universal and targeted interventions. In the course of time, such interventions are likely to have lifelong effects on mental and physical health [ 52 ].

Data from human and laboratory animals provide compelling evidence that stress-relevant neurocircuitry and immunity form an integrated system that evolved to protect organisms from a wide range of environmental threats [ 53 ]. In particular, the fetal inflammatory response to intrauterine infection seems to contribute to neonatal brain injury and subsequent neurological disability [ 54 ]. The preconception and perinatal periods are important because deleterious fetal exposures can be prevented during those periods. Therefore, future mental health prevention efforts must be focused on the critical period as well as prevention models should be developed focusing on the perinatal period.

Interventions based on evidence-based recommendations for the perinatal period may occur as the form of public health, interventions that are universal and more targeted. If successful, such interventions can have enduring, lifelong effects on mental health. The quality of the fetal environment can be compromised in several ways. Indirect stresses such as endocrine, metabolic, or immune responses of toxins like nicotine or alcohol produces vascular restrictions, thereby impeding oxygen and nutritional supply to the fetus. Direct transfer of maternal glucocorticoids or other agents across the placenta are the other stresses.

These stresses include neuro-immune factors that are now being recognized as playing important roles in the etiology of neurological and neuropsychiatric disorders, including immunological processes that target the developing brain and prenatal mental infection. Recent data have elucidated the mechanisms by which the innate and adaptive immune systems interact with neurotransmitters and neuronal circuits to influence the risk for depression.

Responses of stress mediated via activation of the inflammasome to secrete inflammatory cytokines, heightened serotonin metabolism, and reduced neurotransmitter availability together with hypothalamic-pituitary-adrenal axis hyperactivity.

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