Family wealth and adolescent physical health.

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Published in final edited form as: Health Psychol Rev. 2025 Jan 13;19(2):315–343. doi: 10.1080/17437199.2025.2451232 Family Wealth and Adolescent Physical Health Emily J Jones 1, * , Portia Miller 1 , Christina M Gibson-Davis 2 , Jamie L Hanson 1 , Elizabeth Votruba-Drzal 1 Author information Article notes Copyright and License information 1 University of Pittsburgh, 3420 Forbes Avenue, Pittsburgh, PA, 15260 2 Duke University, 228 Rubenstein Hall, Durham, NC, 27708 * Correspondences should be addressed to Emily J. Jones, 3420 Forbes Avenue, Pittsburgh, PA, 15260; emj63@pitt.edu Author contributions: Emily J. Jones drafted the initial manuscript; Emily J. Jones, Portia Miller, Christina M. Gibson-Davis, Jamie L. Hanson, and Elizabeth Votruba-Drzal conceptualized and designed the review and critically reviewed and revised the manuscript. All authors approved the final manuscript as submitted. Issue date 2025 Jun. PMC Copyright notice PMCID: PMC12116244  NIHMSID: NIHMS2053160  PMID: 39801320 The publisher's version of this article is available at Health Psychol Rev Abstract Widening inequalities in the distribution of wealth among families with children may have deleterious health consequences, especially for adolescent children. Marked by significant psychosocial and physiological changes, adolescence is a period when socioeconomic differences in chronic disease risk factors are observed. Family wealth could contribute to adolescents’ physical health. Yet, research on socioeconomic inequalities in adolescent health has overlooked the role of wealth, and has instead focused on differences in household income and parental educational attainment. Expanding our knowledge of whether and how family wealth impacts adolescents’ current and long-term health is of critical public health concern, especially now that wealth is more unequally distributed than income. This review discusses what is known about wealth-related inequalities in adolescent physical health and proposes four psychosocial mechanisms that may explain how wealth shapes adolescent physical health including 1) serving as a stress-buffer; 2) enabling parents to invest in opportunities to support adolescent healthy development; 3) increasing families’ access to social and cultural capital resources that may promote salutary health behaviors while mitigating experiences of social-class discrimination; 4) and supporting adolescents’ future expectations. We end with a discussion of existing questions and suggestions for future research to add to our understanding of wealth-related inequalities in adolescent physical health, which could be used to inform health equity interventions. Keywords: wealth, adolescence, physical health, socioeconomic inequalities, health disparities, health behaviors The unequal distribution of wealth, or a household’s assets net of debts, has widened over the past few decades among households with children in the United States (U.S) with wealth being more unevenly distributed than income [ 1 , 2 ] . In 2022, the wealthiest 1% of U.S. families held more than 34% of the nation’s wealth while families in the bottom 50% held less than 1%. This is in contrast to family income, where the top 1% of high-income households held less than 20% of the share of income while the bottom 50% of households held 15% (see Figure 1 ). Wealth inequalities among U.S. families with children are greater than among the general population and exhibit larger racial/ethnic disparities [ 1 , 3 ] . In fact, net worth poverty, which is a measure of wealth deprivation reflecting households with wealth less than one-fourth of the federal poverty line (adjusted for age and family composition), characterizes one-third of all U.S. family households. The number of net worth poor family households has continued to increase even as income poverty has decreased, especially among families of color. In 2019, 57% of Black families, 50% percent of Latine families, and 23% percent of white families in the U.S. were net worth poor [ 4 ] . Figure 1. Distribution of income and wealth among U.S. family households in 1989 and 2022. Open in a new tab Among U.S. family households, widening wealth inequalities have outpaced income inequalities. The left part of the figure depicts the change in the income distribution from 1989 to 2022, while the right part of the graph reflects the distribution of wealth in 1989 compared to 2022. The dark green part of the bar graph reflects the share of income or wealth held by the bottom 50% of family households, with the lightest green part of the bar graph reflecting the share of income or wealth held by the top 1% of family households. Importantly, inequalities in the distribution of wealth are not limited to the U.S. and research has shown that across the globe, wealth is more unequally distributed than income. [ 5 ] For example, in Norway, Sweden, Germany, and Austria, four countries that each have different government social and economic welfare structures and far less income inequality compared to the U.S., the top 5% of wealthy households hold between 40-44% of the country’s wealth. [ 6 ] Inequalities in the distribution of wealth can also be found in countries with emerging markets, including in countries in Latin and South America (e.g., Chile, Mexico, Argentina, Columbia), Southern Asia (e.g., Malaysia, Indonesia), the Middle East (e.g., Saudi Arabia, United Arab Emirates), and Africa (e.g., South Africa, Egypt). [ 5 ] For example, although 40% of households in African countries fall in the bottom two deciles in terms of global wealth, many of the wealthiest African households fall in the top decile and even top 1% of wealthiest households in the world. [ 5 ] Moderate to high levels of wealth inequality have also been observed in Denmark, Poland, Switzerland, the Netherlands, the United Kingdom, Canada, Australia, and India, among others. [ 5 - 7 ] Moreover, in the United Kingdom, Australia, and in most countries in the European Union except for Finland, family households with children have far less wealth compared to adult only households. [ 8 ] As such, wealth inequality and high levels of net worth poverty among families in the U.S. and abroad may be sources of financial precarity that could have collateral consequences for the health and well-being of families [ 9 ] . Although wealth may matter for all family members’ physical health [ 9 ] , it may be especially important to consider wealth-related health disparities among adolescent children in particular. Adolescence marks a period of growing autonomy and independence, and this newfound freedom means adolescent children increasingly make their own decisions about their health and health behaviors. In addition, adolescence is a sensitive period marked by significant physiological changes [ 10 ] including the onset of puberty and rapid development in brain regions involved in cognitive and affective regulation and stress physiology [ 11 ] . Chronic disease risk factors and signs of subclinical disease are evident as early as adolescence [ 12 - 14 ] , and are patterned by socioeconomic status (SES) [ 15 - 18 ] . Youth from lower SES households evidence a higher prevalence of obesity [ 15 ] , cardiometabolic risk [ 19 , 20 ] , and risky health behaviors (e.g., smoking, sedentary behavior, poor diet; Jackson et al., 2018) relative to their peers from higher SES households. Moreover, adolescent SES has been associated with sustained disease risk into adulthood [ 21 , 22 ] , perhaps in part because health behaviors adopted in adolescence may be maintained into adulthood [ 23 , 24 ] . Thus, family wealth (or the lack thereof) could contribute to adolescents’ physical health, setting adolescents on a path towards decreased or increased risk for morbidity and early mortality in adulthood [ 25 , 26 ] . Yet, family wealth has been mostly left out of the conversation on socioeconomic inequalities in adolescent health. For every 100 articles in PubMed on differences in adolescent health by more common SES measures like household income or parental educational attainment, there are fewer than five articles that consider differences in adolescent health by family wealth. The exclusion of wealth from SES estimates may in turn lead to an incomplete picture of a family’s socioeconomic circumstances [ 27 ] , especially as income and education are only modestly correlated with wealth (estimated r s = .48-.66) [ 1 ] . In fact, a recent study using Swedish administrative data found that wealth was distinct from parent educational attainment, income, or occupation, and should be considered a unique dimension of childhood SES. [ 27 ] Moreover, the researchers found that wealth was the primary driver of the intergenerational transmission of SES, even moderating the extent to which other aspects of SES (e.g., household income and education) were reproduced across generations [ 27 , 28 ] . Findings are even more compelling because these data are drawn from Sweden, a country with more extensive economic and social safety nets relative to the U.S. As such, we may be grossly underestimating current socioeconomic inequalities in adolescent health (especially in non-welfare states) if our studies fail to identify youth with health risk factors and subclinical disease who are living in families with average household incomes and parental educational attainment, but low levels of wealth. By ignoring wealth, we may also come to the wrong conclusion about what may be driving socioeconomic differences in adolescent physical health, which could undermine programs and policies aimed at reducing adolescent health inequalities. Policies are designed to act on specific dimensions of SES like income (e.g., cash transfers), education (e.g., Pell grants), or wealth (e.g., baby bonds, child savings accounts) and not based on SES more generally. Even though latent or composite SES variables can provide an overall sense of a family’s socioeconomic circumstances, they make it impossible to know which dimension(s) of SES to target in order to enhance adolescents’ physical health. Therefore, research is needed to pull apart the relative influence of each dimension of SES on adolescent health outcomes so that policymakers can more effectively develop targeted interventions. For example, if wealth explains unique variance in adolescent physical health that is not captured by differences in income or education alone, then programs aimed at increasing education or income will not fully remediate adolescent physical health inequities. We need to develop policies to address wealth as well. Moreover, as physical health in adolescence is thought to lay the foundation for longer-term health in adulthood (e.g., through the adoption of health behaviors and early signs of cardiometabolic risk and subclinical disease), interventions aimed at addressing wealth disparities in adolescent physical health may have the potential to reduce socioeconomic inequalities in adult morbidity and early mortality. [ 31 ] In the following review, we summarize the various ways that family wealth can be measured and discuss the existing literature on wealth-related inequalities in adolescent physical health. Next, we propose four psychosocial mechanisms that may explain how wealth shapes adolescent physical health. We conclude with a discussion of existing questions and future directions to further our understanding of wealth-related inequalities in adolescent physical health, which could be used to inform future health equity interventions. Expanding our knowledge of whether and how family wealth impacts adolescents’ current and long-term health is of crucial public health concern given the growing gap in wealth [ 32 ] , especially among families with children [ 1 , 8 ] . Please see Table 1 for constructs that are used throughout this review, including definitions and approaches to measurement. Table 1. Crucial constructs and measurement approaches referenced in the review Construct Definition and Measurement Approaches Wealth (net worth) A measure of a household’s total assets minus debts. Wealth can be measured continuously, categorically (e.g., net worth positive, negative, neutral), or based on percentiles or quintiles of a distribution. Net worth poverty A measure of wealth deprivation based on whether a household has wealth less than ¼ of the federal poverty line when adjusted for age and family composition. Cortisol A steroid hormone released from the adrenal cortex that is involved in various physiological processes including the body’s stress response, memory formation, and regulation of glucose, metabolism, and inflammation. Cortisol is commonly assessed in saliva and can be measured over the course of the day for several days to estimate diurnal cortisol production or measured in the minutes and hours following exposure to a laboratory stressor to assess cortisol stress reactivity. Systemic inflammation Elevated circulating levels of proinflammatory mediators that are present in the absence of acute infection. Circulating levels of C-reactive protein and interleukin-6 are commonly used as markers of systemic inflammation. Stimulated cytokine production The process by which cells release cytokines (i.e., proteins involved in cell signaling and immune processes) in response to injury or exposure to an antigen. Stimulated cytokine production can be measured in vitro by incubating whole blood with a viral or bacterial stimulus and examining the change in cytokines produced between stimulated and unstimulated wells. Glucocorticoid resistance The process by which cells become less sensitive to anti-inflammatory signaling from cortisol and other glucocorticoids. This is thought to be in part because of reduced functioning or expression of cells’ glucocorticoid receptors due to chronic exposure to high levels of glucocorticoids. Glucocorticoid resistance can be measured by examining the concentration of glucocorticoids needed to decrease the production of pro-inflammatory cytokines in response to an invitro viral or bacterial challenge. Eosinophil A type of leukocyte that has a variety of functions and is involved in the immune system’s response to infections, asthma, and allergic reactions Metabolic syndrome A cluster of biological risk factors linked to increased risk for cardiovascular disease, stroke, or diabetes. A person may have metabolic syndrome if they meet the criteria for three or more of the following five risk factors: clinically elevated blood glucose, high fasting triglycerides, high blood pressure, large waist circumference, and low HDL cholesterol. Cardiometabolic risk A composite measure of biological risk factors for cardiovascular disease and diabetes that may consist of continuous measures of adiposity, dyslipidemia, glucose, insulin, and resting blood pressure. Open in a new tab What is Family Wealth? Before discussing the literature on wealth and adolescent physical health, it is important to note that family wealth can be measured in multiple ways. Wealth reflects net worth, or the sum of a family’s assets net of debts. Measures of family wealth may assess levels of net worth continuously, [e.g., 33 , 34 ] by dividing families into their place in the wealth distribution by percentiles or quintiles, [e.g., 2 , 35 , 36 ] or by placing families into groups depending on whether they are net worth positive, neutral, or negative [e.g., 37 , 38 ] . Wealth deprivation, or net worth poverty, on the other hand, is based on whether a family’s net worth is less than one fourth of the federal poverty line when adjusted for the number of adults and children in the household. However, wealth portfolios can (and do) vary widely across families with the same net worth, such that a family with high levels of both assets and debts may have the same net worth as a family with few assets but no debts. Thus, researchers often measure individual components of wealth, and these wealth components may differentially relate to adolescent outcomes [ 39 , 40 ] . For example, assets can be categorized into liquid (e.g., assets that can readily accessed, such as savings accounts) and illiquid assets (e.g., assets that are harder to convert into cash, such as homes). Similarly, debts can be comprised of collateral (e.g., mortgages) or non-collateral debts (e.g., most credit cards), or be categorized into “good” (e.g., mortgage) versus “bad” debts (e.g., credit cards) [ 41 ] . Home ownership is also sometimes used as an approximation of family wealth in lieu of more detailed measures of net worth or individual assets or debts. However, using home ownership is problematic because home ownership varies widely across racial and ethnic groups, and across countries. In the U.S., only 40% of Black families own their homes as a consequence of historical and ongoing racial inequalities in housing and mortgage lending practices [ 42 , 43 ] . Thus, using home ownership as a proxy for wealth among this demographic subgroup ignores any wealth variation among the 60% of Black families that do not own homes [ 1 ] . Similarly, it is estimated that only 43.7% of Germans, 47.2% of Austrians, and 54.8% of French residents are homeowners, whereas 81.6% of Spanish, 72.0% of Greek, and 71% of Portuguese residents are homeowners. As such, home ownership may not hold the same weight across different countries and may not provide a full picture of household wealth in countries where most families do, or do not, own their own home. In fact, a 2019 study of 20 European countries found that home ownership was negatively correlated with wealth inequality, such that home ownership was far more common in countries where wealth was more equally distributed across households. [ 44 ] Thus, research is needed that goes beyond home equity to more comprehensively measure family net worth and net worth poverty in relation to adolescent physical health. Family wealth has also been approximated using the Family Affluence Scale, which has been widely used in adolescent health studies conducted outside of the U.S for over 25 years [ 45 - 47 ] . Several versions of the Family Affluence Scale exist and include questions about how many cars and computers a family owns, whether youth have their own bedroom, the number of bathrooms in the home, and how often families go on vacation. Although some of these items capture certain components of wealth (e.g., a vehicle is an asset), other questions do not capture wealth; they ask about consumption (e.g., number of computers, televisions, vacations). While it may be true that wealth can afford families these things (e.g., using savings to cover family vacations or to buy a larger home so that each child has their own room), these indices of consumption may also be procured using income [ 48 ] . In addition, none of these questions capture debt, which has risen dramatically in the past couple decades in many countries, including the U.S., Canada, Australia, and countries in the United Kingdom. [ 49 - 52 ] It is also unclear how well the Family Affluence Scale correlates with family assets net of debts, and the extent to which the growing ubiquity and increasing affordability of computers and other technological resources has impacted the ability of the Family Affluence Scale to discriminate between differences in material consumption among families today compared to when it was first developed [ 53 ] . Existing Research on Family Wealth and Adolescent Physical Health A small but growing number of studies have considered links between various components of family wealth and aspects of adolescents’ physical health. Though these studies vary in the degree to which they control for other SES indicators, studies have generally found an independent effect of wealth on adolescent physical health outcomes. For example, greater family liquid assets have been associated with less systemic inflammation among adolescents [ 54 ] and less proinflammatory cytokine production and fewer eosinophil counts in response to in-vitro bacterial challenge among youth with asthma [ 55 ] ; although other SES factors were not included as covariates. Lower levels of systemic inflammation and proinflammatory stimulated cytokine production are thought to reflect well-regulated inflammatory processes, which could potentially reduce the risk for inflammatory-mediated conditions such as cardiovascular disease [ 56 ] , while fewer eosinophil counts could suggest less severe symptoms and airway inflammation among youth with asthma [ 57 ] . Similarly, greater wealth, based on home equity, has been independently related to slower increases in adiposity among youth over time even when accounting for differences in maternal educational attainment and household income, which could reduce risk for obesity [ 58 ] . Lack of home ownership and having fewer family liquid assets, on the other hand, have both been associated with increased daily cortisol output among youth over a two-year period [ 59 ] (notably, these studies did not control for income or parent educational attainment). Cortisol is a hormone involved in various physiological regulatory processes in the body, including glucose modulation and downregulating the inflammatory response [ 60 , 61 ] . It is also involved in the physiological stress response and is the end product of the hypothalamic pituitary (HPA) axis cascade, with increases in peripheral levels of cortisol often observed 20-30 minutes following a stressor [ 62 ] . Consistently elevated levels of cortisol throughout the day are thought to be suggestive of physiological wear-and-tear and could increase risk for systemic inflammation, alterations in metabolic functioning, and future chronic health conditions [ 63 , 64 ] . Moreover, among adults, less childhood family wealth based on retrospective reports of parental home ownership, has been associated with increased risk of viral infections [ 65 , 66 ] and lower childhood SES using a composite score that includes childhood family home and vehicle ownership has also been related to greater systemic inflammation [ 67 , 68 ] . Viral infections and systemic inflammation may in turn give rise to elevated risk for morbidity and early mortality [ 69 , 70 ] . The protective health benefits of wealth have also been observed when considering the Family Affluence Scale, including positive associations between family affluence and adolescents’ diet, physical activity, and self-rated health, with less consistent associations for smoking and alcohol use behavior [ 45 , 53 , 71 ] . Nonetheless, the strength of certain associations between the Family Affluence Scale and adolescent physical health have weakened over the last decade, [ 72 ] with work suggesting no differences in adolescent cardiovascular health [ 73 ] and a variety of health behaviors [ 74 ] except for diet [ 75 , 76 ] , especially after adjusting for differences in parental occupation or educational attainment [ 71 , 72 , 74 ] . Attenuated associations between the Family Affluence Scale and adolescent health behaviors should not suggest that inequities in material consumption do not matter for adolescent physical health, but may instead reflect limitations in measurement as certain material resources (e.g., computers) have become more affordable to families across the socioeconomic spectrum. Importantly, the health benefits of family wealth may not generalize to youth residing in countries with emerging markets. Although greater family affluence has been related to better self-rated health in emerging markets like Ghana [ 77 ] , other work has shown that greater material wealth is related to increased risk for obesity among Mexican and Ghanian youth [ 78 , 79 ] , perhaps in part by increasing access to hyper-palatable foods that may be more expensive in emerging markets [ 80 ] . Given mixed findings depending on the country and measure of family wealth and adolescent physical health in question, further investigation of associations between family wealth and adolescent health is needed. Extant research on wealth-related inequalities in adolescent health also aligns with a larger literature on adult wealth and physical health [ 9 ] . Among adults, greater wealth has been cross-sectionally and prospectively linked to lower mortality risk [ 33 , 81 , 82 ] , and fewer chronic disease risk factors including obesity [ 83 ] , hypertension [ 37 , 84 ] , cardiometabolic risk [ 85 ] , metabolic syndrome [ 86 , 87 ] , and systemic inflammation [ 88 , 89 ] . Recent work has further linked net worth poverty to increased odds of poor self-rated health among adults [ 90 ] . Given that adult health may reflect the accumulation of health-relevant experiences and behaviors accumulated across the lifespan that may be shaped by family wealth earlier in life, it is likely that wealth-related socioeconomic inequalities in risk factors for chronic disease and early mortality observed in adulthood begin much earlier, including in adolescence. Pathways Underlying Links Between Family Wealth and Adolescent Physical Health Despite the heterogeneity in ways that family wealth has been measured and whether independent effects were tested by statistically adjusting for other SES indicators, the overarching pattern in countries with developed economies is that greater family wealth is associated with fewer biological and behavioral risk factors for disease among adolescents. There are numerous ways in which family wealth may shape adolescent health, including stress buffering processes, parental investments, manifestations of social class, and future expectations. Namely, increases in family wealth may be health-protective for youth in part because greater wealth may buffer families against certain financial and interpersonal stressors that could impact teen’s health and health behaviors [ 91 , 92 ] . Greater wealth may also promote adolescent health by enabling parents to invest in opportunities to support their adolescent child’s healthy development [ 93 ] . Wealth may also increase families’ access to social and cultural capital resources that may reinforce salutary health behaviors and support physical health [ 94 - 96 ] while simultaneously minimizing exposure to social class-based discrimination, which could have deleterious effects on physical health for youth from lower wealth households [ 97 ] . Family wealth may even influence adolescent’s expectations for the future and whether adolescents meet their expected goals, which could have downstream effects on their physical health [ 98 ] . In the following section, we discuss how these four mechanisms may serve as pathways through which inequalities in family wealth may contribute to differences in adolescents’ current and long-term physical health. Even though these mechanisms may be related to other measures of family SES like household income and parental educational attainment and occupation, we believe these pathways are particularly salient pathways through which family wealth (or the lack thereof) shapes adolescent physical health because: 1) wealth can buy opportunities for healthy development and social class acceptance that cannot be afforded by family income, parental education, or parent occupation alone, 2) wealth can buffer against financial stressors like the loss of income, and 3) wealth can be used to finance (and therefore it shapes) expectations for children’s futures, such as attending college or buying a home, which may indirectly benefit children’s long-term health via the intergenerational transmission of SES. See Figure 2 for conceptual model, which is adapted from work by Gibson-Davis and colleagues [ 1 , 2 ] . Figure 2. Conceptual Model of Potential Pathways Connecting Family Wealth to Adolescent Physical Health. Open in a new tab We theorize that family wealth may shape adolescent health through family stress-buffering processes, parental investment, expectations for the future, and manifestations of social class including differential access to social and cultural capital resources and exposure to social-class discrimination. The four psychosocial pathways may directly contribute to objective measures of adolescent physical health, or indirectly by shaping adolescent health behaviors. Wealth, Family Stress Processes, and Adolescent Physical Health The first pathway we consider is family stress processes. One of the clearest ways that family wealth may contribute to adolescent physical health is by influencing the extent to which youth are exposed to family financial and interpersonal stressors that exceed their coping resources [ 99 ] . Wealth may act as a stress buffer, enabling families with sufficient savings to effectively respond to unexpected financial hardships (e.g., loss of unemployment and subsequent income, medical crises) without needing to take on additional debt or completely disrupt family routines and relationships [ 92 , 100 - 104 ] . In contrast, insufficient wealth (or high levels of debt) may be a source of ongoing stress for families, which may negatively impact youth’s physical health by directly impacting teen’s experiences of psychological and financial stress, or indirectly via harsh parenting. Low wealth may be a source of chronic stress for adolescents that may impact their physical health by directly dysregulating their body’s physiological response to challenge (e.g., hyper- or blunted HPA axis or sympathetic-adreno-medullar (SAM) axis reactivity) [ 62 , 63 ] or indirectly impacting their health through changes in health behaviors (e.g., disrupting sleep, using substances to cope) [ 105 - 107 ] . For example, teens from families with less wealth may worry about their family’s financial circumstances and be more physiologically reactive to stressors [ 108 ] . In fact, both chronic psychosocial stress and perceived threat have been found to partly explain associations between fewer family liquid assets and greater stimulated pro-inflammatory cytokine production among youth with asthma [ 55 ] while less family chaos, which is related to family stress [ 109 ] , has been found to partly underlie links between family home ownership, greater family liquid assets, and lower daily cortisol production among youth [ 59 ] . In addition, adolescents who have experienced fewer stressful life events including financial crises are less likely to engage in risky health behaviors including underage alcohol, tobacco, and illicit drug use [ 110 ] while greater family-related perceived stress has been linked to greater cigarette and marijuana use among adolescents [ 105 ] . Differences in family wealth may also indirectly shape adolescent’s physical health through parenting. Greater family wealth has been associated with warm, responsive, and engaged parenting [ 111 ] , which may serve as a stress-buffer that may benefit adolescent’s physical health. Specifically, family wealth and warm and supportive parenting may provide youth with the tangible resources and emotional support needed to effectively respond to stressors if and when they arise [ 91 , 111 , 112 ] and promote adaptive health behaviors [ 113 ] including eating a diet high in fruits and vegetables [ 114 ] . Indeed, parental warmth may be one of the reasons why families with greater family wealth report better family communication, greater interpersonal support, and perceive fewer hardships following significant negative life events as suggested by a recent study of Norwegian adolescents and their parents [ 115 ] . In contrast, low levels of wealth and accumulating debt could be sources of ongoing stress for parents that may take a toll on their parenting, and in turn, negatively impact their teen’s health [ 50 , 116 , 117 ] . For example, parental financial strain may create an undercurrent of uncertainty, unpredictability, and financial precarity in the home, which may lead to less responsive or harsh parenting and increased parent-teen conflict [ 92 , 118 ] . Detached, harsh, and inconsistent parenting could be an added source of stress for teens that could negatively impact their health through alterations in stress physiology and the adoption of risky health behaviors as a means of coping [ 119 - 122 ] . Indeed, research finds that harsh parenting predicts reductions in adolescent’s self-rated health and increases in adolescent adiposity over time [ 120 ] . Moreover, harsh parenting may explain why mothers’ financial strain has been tied to poorer self-rated health among their daughters and more self-reported illnesses among their sons [ 123 ] . Wealth, Parental Investments, and Adolescent Physical Health The second way that greater family wealth may support adolescent physical health is by affording parents the ability to invest their money and time into activities, opportunities, and health-promotive resources for their adolescent children [ 93 , 124 ] . Investments of time and money may in turn benefit adolescents’ physical health by fostering salutary health behaviors and health practices. For example, many of the items included in the Family Affluence Scale reflect parents’ investments into their children. Items include investments in housing that allows teens to have their own bedroom, technology (e.g., computers, laptops), family vacations, which require both financial and time investments. Thus, positive associations between Family Affluence Scale scores and adolescent health summarized earlier in the review support the notion that parental investments may partly explain links between family wealth and adolescent health. In addition to these more general investments, specific health-relevant parental investments include investing in high-quality health care services regardless of premiums in countries with privatized healthcare [ 125 ] , housing in neighborhoods with opportunities for healthy child development, and camps and extracurricular activities (e.g., club sports teams) that may support adolescents’ physical well-being [ 126 , 127 ] . For example, wealth may enable families to afford a down payment on housing in socioeconomically-advantaged neighborhoods with an abundance of health-promoting resources. These neighborhood resources may include recreational and green spaces, grocery stores with healthy food options, and high-quality schools that have physical fitness classes, school nurses, after-school activities, and sports teams. Neighborhood socioeconomic advantage has been associated with lower body mass index [ 128 ] , cortisol levels [ 128 ] , and systolic blood pressure and heart rate relative among adolescents [ 129 ] . These neighborhoods are also typically lower in noise and air pollution, as well as other toxins that can have negative effects on adolescents’ health and health behaviors [ 130 , 131 ] including disrupting sleep [ 132 ] , contributing to airway inflammation [ 133 ] , and potentially interfering with metabolic processes [ 134 ] . In addition to investing in housing in well-resourced neighborhoods, wealth may also allow parents to financially outsource other tasks so that they have more time to spend with their adolescent children and to invest in psychosocial, leisure, and educational opportunities that could have collateral benefits to their teen’s short- and long-term physical health. For example, wealth may enable parents to be more involved in their adolescent’s lives and cultivate salutary health behaviors and habits at home. Parental time investment in the form of routine family dinners during middle and high school have been cross-sectionally and longitudinally associated with greater vegetable and fruit consumption in adolescence and young adulthood [ 135 , 136 ] . Additionally, adolescent boys who engage in regular physical activities with their fathers are more likely to adopt regular exercise habits and participate in sports [ 137 ] , which could have benefits for their cardiorespiratory fitness. Furthermore, parents’ general awareness of, and involvement in, their adolescent’s daily activities have been linked to less marijuana and alcohol use [ 138 ] , lower odds of initiating smoking [ 138 , 139 ] and less in-vitro glucocorticoid resistance [ 140 ] , which may suggest better inflammatory regulation [ 141 ] . In contrast, low levels of wealth may impede on parents’ time investments if parents need to pick up extra shifts or jobs to pay down existing debt, precluding them from spending as much time with their teens or affording opportunities that extend beyond caring for their teen’s essential needs [ 117 , 142 , 143 ] . Indeed, less contact with parents in adolescence is related to greater somatic concerns (e.g., migraine, nausea, fatigue) in adulthood [ 144 ] . Moreover, parents with lower levels of wealth may not be able to invest in and access preventative and curative health care services and medications for their teens due to time restrictions (e.g., flexibility in work schedules, paid time off) or insufficient savings to cover the cost of co-payments and premiums in countries where healthcare is privatized. In fact, families with less wealth in the U.S. may even be turned away from services because of their Medicaid status, ultimately precluding youth in these families from receiving the care that they need unless their parents take on medical debt in order to access such services by paying out-of-pocket [ 125 ] . Unfortunately, universal healthcare does not seem to fully absolve the time and financial barriers to quality healthcare services that youth from low wealth families face, as social class-based healthcare discrimination and utilization has been reported in welfare states including Belgium, Sweden, and Finland [ 145 - 147 ] . Wealth, Manifestations of Social Class, and Adolescent Physical Health Manifestations of social class may be a third pathway underlying links between family wealth and adolescent physical health. More specifically, greater wealth may increase adolescents’ access to social and cultural capital resources that may be beneficial for their current and long-term health [ 94 - 96 ] , while lower levels of wealth may increase adolescents’ experiences of social class-based discrimination, which could have negative implications for their health [ 97 ] . Social capital refers to relational and material resources and opportunities that may be available to families through their social networks and communities, and may serve as social safety nets in times of need [ 148 ] . Cultural capital, on the other hand, can be thought of as learned behaviors, values, norms, and knowledge that people acquire through their interactions with others [ 149 ] . For youth and their families, health-relevant social capital resources afforded to wealthier families may include people in their networks who are medical professionals or who understand the healthcare system to help them identify and gain access to different types of medical interventions when health concerns arise. Healthcare capital can include knowing which specialists to contact or knowing what questions to ask healthcare or insurance providers so that their teens receive the care that they need. Health-related social capital can also encompass access to people in a family’s network who have knowledge about opportunities for healthy development, including extracurricular activities, camps, and sports teams to promote salutary behaviors. Greater social capital, in turn, has been related to healthier diets, greater physical activity, and less adiposity among adolescents [ 150 - 152 ] . Moreover, interventions that focus on cultivating social capital within low-income communities show promising benefits for physical health, perhaps by way of increasing health literacy [ 153 ] . Cultural capital may also be important for adolescents’ physical health by encouraging the adoption of healthful behaviors [ 96 ] . For example, wealthier families may have cultural norms and knowledge around healthy living (e.g., food literacy, sleep hygiene, regular exercise), the importance of preventative health care services (e.g., vaccine uptake), and how to identify early signs of illness in their children (e.g., wheezing as a sign of asthma, frequent urination and thirst as a sign of type 1 diabetes; Abel, 2008). Greater cultural capital, in turn, has been tied to higher fruit and vegetable intake, regularly eating breakfast and dinner, lower intake of sugar-sweetened soft drinks and sweets [ 155 ] and less smoking and healthier weight management among youth [ 96 ] . In contrast, adolescents from low wealth families may have less access to health-relevant social and cultural capital resources [ 156 ] , which may contribute to poorer perceived health [ 157 ] and negative changes in health status over time [ 158 ] . Moreover, families with less wealth may also have a general distrust of the healthcare system given that low SES families report barriers to accessing health care, receiving poorer care, and having their concerns dismissed by healthcare professionals relative to more affluent families [ 145 , 147 , 159 ] . Nevertheless, it is not clear if differential access to social and cultural capital resources is attributed solely to wealth or other socioeconomic factors, like parental educational attainment and occupation. For example, parents with more years of education may draw on their educational background to decipher healthcare information and understand health behavior research that they can then leverage to support their teen’s healthy development [ 160 ] . Similarly, parents may be able to use relationships from their places of employment to connect their adolescents to health-relevant opportunities, like referrals to healthcare specialists or exclusive sports teams. As such, wealth may afford access to social and cultural capital that benefit adolescent’s physical health, but whether this pathway is unique to wealth over and above other socioeconomic factors warrants investigation. For youth living in households with less wealth, social class may also manifest in experiences of social class-based discrimination, which could negatively impact their physical health and health behaviors [ 161 , 162 ] . Although there is less research focused on class-based discrimination specifically, a robust literature links discrimination more broadly to a variety of negative physical health outcomes including heightened physiological stress reactivity among adolescents and adults alike [ 163 , 164 ] . In addition, social class-based discrimination may be related to subjective social status, which is how adolescents view themselves in relation to others in their schools, local communities, and the broader society [ 165 ] . Subjective social status may vary as a function of family wealth as suggested by work showing that less family wealth based on the Family Affluence scale and teens’ perceptions of their family’s wealth is related to lower subjective social status among Scottish and Norwegian youth. [ 115 , 166 ] While higher subjective social status may foster a sense of belonging, safety, and security among youth from wealthier families, youth from families with less wealth may perceive themselves as lower in the social hierarchy, which may lead to feelings of exclusion and isolation and potentially exacerbate physiological stress [ 167 - 169 ] . Meta-analytic evidence from 44 studies has found that lower subjective social status among adolescents is related to poorer subjective and objective measures of physical health [ 97 ] . Among youth, lower subjective social status has been further linked to higher resting diastolic blood pressure and disrupted sleep [ 170 ] and greater cortisol reactivity to stressors arising from individual evaluation of social status [ 171 ] . Although subjective social status may be related to other measures of family SES, research has found that, at least among adults, subjective social status is more strongly correlated with wealth compared to education or occupation, and that subjective social status mediates the association between net worth and self-rated health among British adults [ 172 ] . Wealth, Expectations for the Future, and Adolescent Physical Health A fourth pathway through which wealth may shape adolescent’s current and long-term physical health is by contributing to youth’s expectations for the future [ 103 ] . Adolescents may hold a range of expectations about their futures, with some expectations that are explicitly linked to their physical health (e.g., living a long and healthy life) and others may seem more distally or indirectly related to health (e.g., attending college, buying a home). Indeed, both educational attainment and home ownership have been shown to have benefits for physical health, perhaps in part because education can facilitate the acquisition of knowledge and reasoning skills that can be used when making health decisions, and home ownership can provide people with more control over their housing conditions compared to renting. [ 173 , 174 ] Wealth may shape adolescents’ future expectations, such that adolescents from wealthy families may feel that certain expectations are within reach, like going to a private university or owning a home, because that is what they have been taught to expect (e.g., through discussions with their parents) [ 175 ] . Wealth may further influence the extent to which these expected goals are realized, especially those goals that require a large financial investment like buying a home [ 176 - 178 ] , which cannot be covered by income alone. In fact, Canadian, Swedish, German, and British young adults have higher rates of homeownership if their parents are homeowners. [ 179 - 181 ] For many youth and their parents, the most salient aspiration for the near future may be attending college. Even before matriculating, cross-sectional research finds that adolescents who aspire to go to college are more likely to engage in regular physical activity, maintain a healthy diet and oral hygiene, and abstain from alcohol, tobacco, and marijuana [ 182 , 183 ] . Youth may abstain from certain risky health behaviors, like drinking alcohol and using marijuana, to ensure that they do not compromise their chances of getting into college by getting in trouble or having these health behaviors negatively impact their academic performance. Then again, personality characteristics, including being high in conscientiousness, could explain these associations [ 184 , 185 ] . Socioeconomic factors like family income and parents’ educational attainment and occupation may contribute to educational expectations; [ 186 ] however, wealth may determine the extent to which these expectations are realized. [ 187 ] For example, parents who went to college or who work in a specific field may expect their child to follow in their footsteps. Yet, research finds that whether youth matriculate and ultimately graduate from college may be more heavily determined by their family’s wealth [ 187 ] . Specifically, youth from wealthier families may know there are savings set aside to use towards college tuition, which may increase the likelihood that these youth will meet their expected goals. In fact, having college savings is associated with whether youth enroll in college [ 188 ] , with family wealth being a stronger correlate of college attendance than family income [ 1 , 189 , 190 ] . Moreover, the gap between aspiring and actually going to college is significantly wider for the 41% of youth who do not have college savings accounts as compared to 12% of children who do [ 177 ] . Nonetheless, many youth from low wealth families still aspire to, and ultimately enroll, in college. Yet, the effort required to meet their educational goals could come at an unintended cost to their physical health (e.g., sacrificing sleep, physical activity, or maintaining a healthy diet to work to save money for college). Research on skin-deep resilience and socioeconomic mobility has found that thriving academically and graduating from college may come with physiological tradeoffs as indicated by a higher prevalence of metabolic syndrome and other biological risk factors for disease among youth and young adults from socioeconomically disadvantaged backgrounds, especially those who also belong to racial or ethnic minority groups [ 98 , 191 , 192 ] . Potential tradeoffs to physical health should not dissuade youth from low-wealth households from pursuing their educational aspirations; rather, these findings should motivate institutions to make changes to better support teens’ educational endeavors while simultaneously supporting their physical health and well-being. Beyond educational aspirations, differences in family wealth could also contribute to adolescents’ health through aspirations for the more distal future, including how long they expect to live. Research on SES more broadly (rather than wealth specifically) has found that youth growing up in low SES environments are less likely to believe that they will live to see the age of 35 relative to their peers living in more advantaged circumstances [ 193 ] . Life expectancy may in turn impact the extent to which youth engage in health-relevant behaviors including seeking out preventative health care services and engaging in health-promoting behaviors. Research has found that youth who expect to live to see 35 years of age are less likely to smoke cigarettes [ 182 ] and engage in unprotected sex [ 194 ] , whereas youth who do not expect to reach age 35 have a greater risk of substance use behaviors and 2-3 times the risk of death in young adulthood relative to their peers who expect to live longer [ 195 ] . Greater family wealth may also allow for more future-oriented thinking more broadly while less wealth may contribute to a scarcity mindset insofar that financial precarity may force adolescents and their families to focus on current socioeconomic and psychosocial challenges and thus have less bandwidth to attend to future possibilities [ 196 , 197 ] that may be relevant to their health [ 198 ] . Having a future orientation has been associated with less substance use among youth [ 199 ] while having a “nothing to lose” attitude about the future has been tied to selling drugs and using weapons, which could put adolescents’ physical health at risk [ 200 ] . Discussion Given the unequal distribution of wealth among families across the globe and the share of youth who may be experiencing wealth deprivation, research on socioeconomic inequalities in adolescent physical health would benefit from a greater focus on the role of wealth. Although understudied, extant research on associations between family wealth and adolescent physical health suggests that, at least in countries with developed economies, wealth is health protective. Adolescents living in wealthier households generally engage in more salutary health behaviors and evidence fewer biological risk factors for disease relative to their peers living in households with less wealth [ 45 , 53 - 55 , 58 , 59 ] . These wealth-related differences in health may accumulate across decades and extend into adulthood to lower risk for morbidity and early mortality [ 65 - 68 ] . Greater wealth may support adolescents’ current and long-term physical health by 1) serving as a stress-buffer, protecting youth and their families from financial strain and interpersonal conflict following stressful life events; 2) enabling parents to invest in opportunities for healthy adolescent development including buying a home in a well-resourced neighborhood with access to healthy foods and recreational activities to promote salutary health behaviors, while decreasing exposure to pollutants that could negatively affect their health; 3) increasing families’ access to social and cultural capital resources including navigating the healthcare system and identifying extracurricular activities, camps, and other health-relevant opportunities for teens; and 4) cultivating, and financially aiding, adolescents’ expectations for the future. In contrast, less wealth may have deleterious consequences for adolescents’ physical health by 1) being a source of ongoing financial, interpersonal, and physiological strain; 2) precluding parents from being able to financially invest as much in health-relevant activities and opportunities including access to high-quality health care services and living in safe neighborhoods; 3) increasing teens’ risk for experiencing social-class based discrimination, and 4) serving as a financial barrier to adolescent’s future expectations, which may make it more challenging for these youth to achieve their expected goals without tradeoffs to their physical health. Nonetheless, our current understanding of how family wealth relates to adolescent health is incomplete and warrants further investigation. To elucidate the various ways in which wealth contributes to socioeconomic inequalities in adolescent physical health and for whom, we end this review with a discussion of existing empirical questions and racial, ethnic, and international considerations when studying associations between family wealth and adolescent physical health. Empirical Gaps in Our Understanding of How Family Wealth Shapes Adolescent Physical Health and the Extent to Which These Pathways are Specific to Family Wealth Rather Than Other SES Indicators Studies have shown positive associations between various components of family wealth and adolescent physical health, which suggest that programs to support families in acquiring and building assets or paying down debts have the potential to benefit the health of adolescents. Nevertheless, before policy recommendations can be made, additional research is needed to tease apart the relative strength of the associations between adolescent physical health when taking into account. other dimensions of SES, such as household income and parental educational attainment. Most of the existing literature on wealth and adolescent health has looked at the main effects of wealth (or one component of wealth) on adolescent physical health, with one notable exception. Using two decades of data from the Panel Study of Income Dynamics, Boen and colleagues [ 58 ] found that family wealth was negatively, and cumulatively, related to BMI and obesity risk among U.S. youth even when accounting for differences in household income, maternal educational attainment, and health insurance status. Replicating these findings in other samples of youth in the U.S. and internationally and with a broader range of measures of physical health, beyond BMI, will be crucial for informing programs aimed at combatting wealth-specific inequalities in adolescent physical health. At the same time, longitudinal research is needed to glean how changes in wealth relate to corresponding changes in adolescent physical health by conducting observational and intervention studies that follow youth and their families over time. Although there are several studies that have looked at changes in adolescent’s health trajectories as a function of wealth [ 58 , 59 ] , wealth is typically measured once even though it can vary over time as families acquire assets (e.g., come into an inheritance) and take on or pay off debts (e.g., educational loans, mortgage). Observational studies would allow for the establishment of temporal precedence, elucidating how increases and decreases in family wealth contribute to adolescent physical health, as well as how long it takes to observe measurable changes in health following a change in net worth. Experimental studies with random assignment could then be used to test the extent to which programs aimed at increasing wealth through debt forgiveness or savings programs (e.g., Child Development Accounts), for example, lead to measurable improvements in adolescents’ physical health like they have adolescents’ post-secondary enrollment. [ 177 ] In addition to research that addresses questions related to the independent effects of wealth on adolescent physical health and how changes in wealth correspond to changes in adolescent physical health, mechanistic research is needed to empirically test the pathways through which wealth shapes adolescent physical health. Although there are theoretical reasons for how wealth comes to be associated with adolescent physical health, very few studies have tested the extent to which the association between family wealth and adolescent physical health is explained by the four psychosocial pathways reviewed here and whether these pathways are specific to wealth, versus other indicators of family SES. There have been a few studies focused on indirect effects of wealth on adolescent academic and psychological outcomes through certain parental investments, family stress processes, and future expectations [ 201 - 203 ] , although not all these studies adjusted for other family SES factors like income and parent educational attainment. In addition, there are no studies that have considered these pathways in relation to parameters of adolescent physical health except for Boen and colleagues, who found support for family stress processes and parental educational investments, but not other forms of investment, as mechanisms linking family wealth to BMI. [ 58 ] We also do not know of any studies that have focused on manifestations of social class as a candidate mediator. Nonetheless, there is reason to believe that the effects of wealth on adolescent health may operate through one or more of the pathways we have discussed here given that there is relatively strong evidence linking family wealth to each of these four mediators even when accounting for other aspects of family SES (‘a to b’ paths) as well as empirical support linking each of these four mediators to adolescent health behaviors and physical health outcomes (‘b to c’ paths). Figure 3 provides a visual summary of our review of wealth’s associations with adolescent physical health (both directly and through health behaviors) by way of parental investments, family stress processes, future expectations, and manifestations of social class. Thicker arrows reflect ‘a to b’ and ‘b to c’ paths that have received more empirical support while thinner arrows reflect pathways that may benefit from further empirical investigation. Once indirect effects have been established, future research could then test whether increased wealth (e.g., through government programs or interventions) leads to improvements in adolescents’ physical health by enhancing parental investments, future expectations, and access to social and cultural capital resources for families while decreasing family stress and experiences of social-class discrimination. Figure 3. Conceptual model illustrating the level of empirical support for associations between family wealth, four candidate mediators, and adolescent physical health. Open in a new tab Arrow thickness reflects the level of empirical support for associations between family wealth and adolescent physical health and health behaviors, family wealth and each of the four mediators, and between the four mediators and adolescent physical health and health behaviors. Note that for indirect effects, most research has focused on the individual paths (e.g., wealth → parental investment; manifestations of social class → adolescent health behaviors) rather than the full mediation pathway (wealth → parental investment → adolescent health behaviors) In addition to mechanistic work, research is also needed to clarify whether there are certain sensitive periods in adolescence when wealth may be especially important for physical health [ 204 ] and whether there is a wealth gradient of adolescent health [ 205 , 206 ] or a threshold effect whereby a certain amount of wealth (or the lack thereof) may meaningfully affect certain aspects of youth’s health. Research on adults has generally found support for a socioeconomic gradient of physical health such that every additional increase in income and educational attainment is linearly associated with a relative increase in life expectancy and a relative decrease in chronic disease risk [ 205 , 207 ] . This income and educational gradient of health has also been observed in adolescent samples [ 206 ] but it is not clear if this socioeconomic gradient generalizes to measures of family wealth specifically. Moreover, there is no research that we are aware of that has considered the role of wealth deprivation on adolescent physical health. However, research on other aspects of youth development has found that net worth poverty is associated with greater problem behaviors, which could have indirect effects on youth’s physical health [ 40 ] . Because wealth can be measured in a variety of ways, it also remains unclear whether net worth (assets minus debts) is most salient for adolescent physical health or if the composition of this wealth is what really matters, as suggested by work on wealth and academic achievement [ 39 ] . For instance, different types of assets (e.g., home equity, stocks, savings) and whether these assets are liquid or illiquid may be important for adolescents’ physical health, but how and in what ways is unknown. It is also unclear whether wealth deprivation that is driven by high levels of debt has differential effects on adolescent physical health relative to wealth deprivation that is due to little to no assets, which has been observed in a study focused on net worth poverty and adolescent problem behaviors [ 40 ] . Research is also needed to determine whether associations between the four psychosocial mechanisms and adolescent health discussed here are linear or nonlinear, especially when considering future expectations. For example, it is possible that greater wealth may relate to better adolescent health through expectations for the future up to a certain point, but that unreasonably high expectations (or a disconnect between parent and teen’s expectations for the future) could have negative health consequences. Among older adolescents transitioning to college, one study found that those who felt they were not meeting their own expectations or the expectations of their parents, reported poorer college adjustment and less self-worth [ 208 ] , which could have negative downstream consequences on health behaviors including disordered eating, smoking, and alcohol and marijuana use [ 209 ] . It also remains unclear whether family stress-buffering processes, parental investments, manifestations of social class, and expectations for the future are equally important contributors to the wealth-adolescent physical health relationship. Some studies focused on adolescent psychological outcomes have attempted to compare these pathways. Simons and colleagues [ 210 ] found that family stress, but not parental investments, explained associations between family economic pressure and externalizing behaviors among Black youth. However, this study, like many other studies, did not directly measure wealth and relied on one type of parental investment, which may not capture the various ways in which parents invest in their children. It is also unclear if findings would generalize to adolescents’ physical health. Thus, future research could compare multiple pathways to one another using more than one measure of each construct or latent variables to inform how and on what to intervene to potentially mitigate wealth-related inequalities in adolescent physical health. Racial, Ethnic, and Nativity Differences in the Association Between Family Wealth and Adolescent Health When discussing the distribution of wealth and candidate psychosocial mechanisms that may connect wealth to adolescent physical health, it is imperative to consider race, ethnicity, and other sociodemographic factors including nativity. In the U.S. and abroad, there are racial and ethnic inequalities in both the distribution of wealth and in adolescent physical health. Among U.S. family households, the median wealth of white households in 2022 was $87,538, which was 5 and 41 times greater than the median wealth of Latine ($17,218) and Black households ($2,121), respectively. This staggering racial and ethnic gap in wealth may reflect a constellation of factors including current and historical forms of structural racism in the built environment that have limited Black and Latine families from building intergenerational wealth. Historically, racist housing practices like redlining and blockbusting [ 211 , 212 ] , as well as modern-day discriminatory practices in business lending [ 213 ] , hiring [ 214 ] , and higher education [ 215 ] , have undermined the acquisition of assets, while predatory lending and usury outfits (e.g., payday loans) have contributed to the accumulation of debt among Black and Latine families [ 216 , 217 ] . Racial and ethnic inequalities in wealth are also evident in other countries, with British ethnic minority groups holding fewer liquid assets and home equity and owing more debts relative to their British white and Indian peers [ 211 ] . Moreover, research conducted in Germany, Israel, and Canada, finds that wealth varies by nativity status, with immigrant households having significantly less wealth relative to native and second-generation households [ 212 - 214 ] . At the same time, adolescents from certain racial and ethnic minority groups evidence poorer physical health relative to their majority peers. In the U.S., 26% of Latine and 22% of Black adolescents are obese compared to just 14% of white adolescents [ 218 ] . Latine and Black youth also have a higher incidence of pediatric type II diabetes compared to their white peers, with 15% of Latine youth showing signs of non-alcoholic fatty liver disease relative to 10% of white youth [ 218 ] and Black youth being diagnosed with pediatric hypertension twice as often as their white peers [ 219 ] . Racial and ethnic inequalities in adolescent health are also evident outside the U.S. In Australia, the incidence of type II diabetes was 31 per 100,000 person years for Indigenous youth compared to just 1.4 per 100,000 person-years for non-Indigenous youth in 2012 [ 220 ] and in the U.K., South Asian youth have greater insulin resistance and higher body fat percentage and central adiposity relative to their white counterparts [ 221 ] . Research has also shown that body fat percentage, sedentary behavior, poor diet, and health insurance coverage and quality of care may also vary as a function of nativity status, level of acculturation, and country of origin, among immigrant youth and youth who are the children of immigrants [ 222 - 226 ] . However, what remains unclear is if associations between family wealth and adolescent physical health vary by race and ethnicity. In other words, it is not clear whether wealth benefits the physical health of racial and ethnic minority youth to the same degree as their majority peers, and through the same pathways. The minorities’ diminished returns to health framework suggests that racial and ethnic minority youth may not reap the same physical health benefits of wealth that are afforded to majority youth in part because minority youth may face more racial and ethnic discrimination and segregation, experience more risk factors and adversity (e.g., crime, pollution), and have less access to high-quality resources (e.g., health care) compared to their majority peers. [ 164 , 227 - 232 ] For example, empirical research has shown that the protective effect of higher parental educational attainment on adolescent BMI is attenuated among Black compared to white youth [ 233 ] and that the benefits of higher household income for minimizing adolescent nicotine use are weaker among Black and Latine versus white youth [ 234 ] . In line with the proximity to disadvantage theory, it is also possible that the detrimental effects of net worth poverty on adolescent physical health may be stronger among minority versus majority youth, partly because racial and ethnic minority youth may be more likely that their majority peers to be cut off from salutary resources (e.g., in their neighborhoods, schools, or extended family) that could compensate for net worth poverty. [ 228 ] Although no empirical studies to date have investigated whether links between net worth poverty and adolescent health are stronger among racial and ethnic minority youth, research has shown that associations between income poverty and childhood asthma are stronger among Black compared to white youth [ 235 ] . As such, policies and programs aimed at reducing wealth-related inequalities in adolescent physical health should consider the additional structural, social, environmental, and interpersonal barriers that racial and ethnic minority and immigrant youth and their families face in acquiring wealth and maintaining their physical health. In the same way that race and ethnicity may moderate associations between wealth and adolescent physical health, it is also possible that there are additional or different psychosocial pathways through which wealth shapes the physical health of adolescents from racial, ethnic, and other minority groups beyond the pathways proposed here. For example, racial and ethnic minority and immigrant families may invest in their children in ways beyond the neighborhood and time investments discussed, from instilling cultural values to promoting a sense of collectivism to support adolescent physical health and well-being. Similarly, there may be certain protective factors that may mitigate the extent to which low levels of wealth increase risk for physical health problems among youth from minoritized backgrounds. For example, family connectedness has been shown to buffer the extent to which lower Family Affluence scores are related to health complaints among immigrant youth living in Italy. [ 236 ] In addition, recent work on the Hispanic Health Paradox (which refers to Latine adults in the U.S. having lower rates of cardiovascular disease despite having more socioeconomic risk factors for the disease) suggests that the Spanish language may buffer Latine families against physiological stress by altering appraisals of stress, which could in turn lower their risk for chronic diseases [ 237 ] . Thus, the wealth to adolescent physical health literature would benefit from viewing the association between family wealth, psychosocial factors, and adolescent physical health from an intersectional lens. International Considerations When Examining Family Wealth and Adolescent Health Associations Research on associations between family wealth and adolescent physical health must also attend to the country or countries where the work is being conducted. Family wealth is measured as assets minus debts but has been approximated by home ownership or the Family Affluence Scale. Yet, the extent to which these different measures are correlated with one another and with adolescent physical health, both within and between countries, is unclear. For example, in countries where most families own their home, home ownership may be a poorer indicator of family wealth, while scores on the Family Affluence Scale may not be able to pick up on meaningful differences between families in countries where material resources, like computers and laptops, are more affordable. One solution is to create a survey that comprehensively assesses various types of assets and debts that families may have in order to calculate a family’s net worth based on their assets net of debts. However, researchers need to be thoughtful about the types of assets and debts that they include depending on the country context. In the U.S., for example, privatized healthcare and the rising cost of post-secondary education have led to higher levels of medical and educational debt than might be seen in countries with universal healthcare and government subsidized post-secondary education. Additionally, common types of liquid assets in the U.S. and other industrialized countries like stocks and bonds, may not be as common in other countries with emerging economies. For example, in 2014, financial assets comprised 71% of total assets in the U.S. and Canada compared to 46% of assets in Europe, 30% in Latin America, and 15% in India. Another solution could be to statistically account for area-level wealth using multi-level models when examining wealth-related inequalities in adolescent physical health across countries or contexts with different degrees of wealth inequality and economic or social infrastructures. For example, using the Family Affluence Scale, Schmengler and colleagues showed that family affluence was positively associated with engagement in physical activity among youth across 32 countries, with stronger effects among youth from countries with more educational upward mobility. [ 76 ] To inform our understanding of how differences in family net worth, and the composition of wealth, may contribute to adolescent health inequalities within and between countries, future research could include 1) accounting for country- and contextual-level factors that may contribute to links between individual-level family wealth and adolescent physical health, and 2) developing scales that comprehensively assess a wide range of family assets and debts that are ubiquitous across families as well as specific to where families live in order. Conclusion Wealth is unequally distributed across family households throughout the world and may partly drive socioeconomic inequalities in adolescent physical health, which are likely to grow in the coming decades. Among U.S. families, the share of wealth held by the top 1% of family households has grown from 31% to 34% from 1989 to 2022, while the share of wealth held by the bottom 50% of family households has remained less than 1% over the past three decades (see Figure 1 ). Although the U.S. ranks the highest in the unequal distribution of wealth, wealth disparities are still evident across the globe, in both established and emerging economies alike, and even in countries where income is more evenly distributed across residents. [ 5 , 6 ] Moreover, wealth is more unequally distributed across family households with children compared to other types of households, with the median net worth of family households lagging behind the net worth of adult only and senior households across the globe. [ 8 ] Therefore, to better understand, and ultimately address, socioeconomic inequalities in adolescent health and reach all youth who may be at-risk for future health concerns, we need to pay closer attention to the innumerable ways in which wealth uniquely shapes adolescents’ physical health and health trajectories, over and above more common measures of family SES like household income and parental educational attainment and occupational class. Inequalities in wealth may contribute to disparities in exposure to family stress, parental investments, manifestations of social class, and expectations for the future, which in turn may influence adolescents’ physical health. Along with programs aimed at building intergenerational wealth and addressing structural barriers contributing to inequalities in wealth, these four psychosocial pathways could serve as potential points of intervention to promote health equity and support the physical health of adolescents, both now and in the long-term. Acknowledgments: This work was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development under Grant 1R01HD110423-01 (MPIs: Portia Miller, PhD. & Christina M. Gibson-Davis, PhD; Co-Is: Jamie L. Hanson & Elizabeth Votruba-Drzal). We also want to acknowledge the Study of Teen Experiences that Promote Success (STEPS) research team. Footnotes Disclosure statement : The authors declare no conflicts of interest and have nothing to disclose. References 1. Gibson-Davis C, & Hill HD (2021). Childhood wealth inequality in the United States: Implications for social stratification and well-being. RSF: The Russell Sage Foundation Journal of the Social Sciences, 7(3), 1–26. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 2. Gibson-Davis CM, & Percheski C (2018). Children and the elderly: Wealth inequality among America’s dependents. Demography, 55(3), 1009–1032. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 3. Bhutta N, Chang AC, & Dettling LJ (2020). Disparities in wealth by race and ethnicity in the 2019 Survey of Consumer Finances. [ Google Scholar ] 4. Gibson-Davis C, Keister LA, & Gennetian LA (2021). Net Worth Poverty in Child Households by Race and Ethnicity, 1989–2019. Journal of Marriage and Family, 83(3), 667–682. 10.1111/jomf.12742 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 5. Davies JB, Lluberas R, & Shorrocks AF (2017). Estimating the Level and Distribution of Global Wealth, 2000–2014. Review of Income and Wealth, 63(4), 731–759. 10.1111/roiw.12318 [ DOI ] [ Google Scholar ] 6. Pfeffer FT, & Waitkus N (2021). The Wealth Inequality of Nations. American Sociological Review, 86(4), 567–602. 10.1177/00031224211027800 [ DOI ] [ Google Scholar ] 7. Skopek N, Buchholz S, & Blossfeld H-P (2014). National patterns of income and wealth inequality. International Journal of Comparative Sociology, 55(6), 463–488. 10.1177/0020715214565674 [ DOI ] [ Google Scholar ] 8. Pfeffer & Waitkus. (2021). Comparing Child Wealth Inequality Across Countries. RSF: The Russell Sage Foundation Journal of the Social Sciences, 7(3), 28. 10.7758/rsf.2021.7.3.02 [ DOI ] [ Google Scholar ] 9. Pollack CE, Chideya S, Cubbin C, Williams B, Dekker M, & Braveman P (2007). Should Health Studies Measure Wealth?: A Systematic Review. American Journal of Preventive Medicine, 33(3), 250–264. 10.1016/j.amepre.2007.04.033 [ DOI ] [ PubMed ] [ Google Scholar ] 10. Spear L. (2010). The behavioral neuroscience of adolescence. WW Norton & Company. [ Google Scholar ] 11. Lupien SJ, McEwen BS, Gunnar MR, & Heim C (2009). Effects of stress throughout the lifespan on the brain, behaviour and cognition. Nature Reviews Neuroscience, 10(6), 434–445. 10.1038/nrn2639 [ DOI ] [ PubMed ] [ Google Scholar ] 12. Braveman P, & Barclay C (2009). Health disparities beginning in childhood: A life-course perspective. Pediatrics, 124(Supplement 3), S163–S175. [ DOI ] [ PubMed ] [ Google Scholar ] 13. May AL, Kuklina EV, & Yoon PW (2012). Prevalence of Cardiovascular Disease Risk Factors Among US Adolescents, 1999–2008. Pediatrics, 129(6), 1035–1041. 10.1542/peds.2011-1082 [ DOI ] [ PubMed ] [ Google Scholar ] 14. Strong JP, Malcom GT, McMahan CA, Tracy RE, Newman WP III, Herderick EE, Cornhill JF, & for the Pathobiological Determinants of Atherosclerosis in Youth Research Group. (1999). Prevalence and Extent of Atherosclerosis in Adolescents and Young AdultsImplications for Prevention From the Pathobiological Determinants of Atherosclerosis in Youth Study. JAMA, 281(8), 727–735. 10.1001/jama.281.8.727 [ DOI ] [ PubMed ] [ Google Scholar ] 15. Frederick CB, Snellman K, & Putnam RD (2014). Increasing socioeconomic disparities in adolescent obesity. Proceedings of the National Academy of Sciences, 111(4), 1338–1342. 10.1073/pnas.1321355110 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 16. Hanson MD, & Chen E (2007). Socioeconomic status and health behaviors in adolescence: A review of the literature. Journal of Behavioral Medicine, 30(3), 263. [ DOI ] [ PubMed ] [ Google Scholar ] 17. Jackson SL, Yang EC, & Zhang Z (2018). Income Disparities and Cardiovascular Risk Factors Among Adolescents. Pediatrics, 142(5), e20181089. 10.1542/peds.2018-1089 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 18. Power C, & Matthews S (1997). Origins of health inequalities in a national population sample. The Lancet, 350(9091), 1584–1589. 10.1016/S0140-6736(97)07474-6 [ DOI ] [ PubMed ] [ Google Scholar ] 19. Goodman E, McEwen BS, Huang B, Dolan LM, & Adler NE (2005). Social inequalities in biomarkers of cardiovascular risk in adolescence. Psychosomatic Medicine, 67(1), 9–15. [ DOI ] [ PubMed ] [ Google Scholar ] 20. Howe LD, Galobardes B, Sattar N, Hingorani AD, Deanfield J, Ness AR, Davey-Smith G, & Lawlor DA (2010). Are there socioeconomic inequalities in cardiovascular risk factors in childhood, and are they mediated by adiposity? Findings from a prospective cohort study. International Journal of Obesity, 34(7), Article 7. 10.1038/ijo.2010.52 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 21. Doom JR, Mason SM, Suglia SF, & Clark CJ (2017). Pathways between childhood/adolescent adversity, adolescent socioeconomic status, and long-term cardiovascular disease risk in young adulthood. Social Science & Medicine, 188, 166–175. 10.1016/j.socscimed.2017.06.044 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 22. Poulton R, Caspi A, Milne BJ, Thomson WM, Taylor A, Sears MR, & Moffitt TE (2002). Association between children’s experience of socioeconomic disadvantage and adult health: A life-course study. The Lancet, 360(9346), 1640–1645. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 23. Ames ME, Leadbeater BJ, & MacDonald SWS (2018). Health behavior changes in adolescence and young adulthood: Implications for cardiometabolic risk. Health Psychology, 37(2), 103–113. 10.1037/hea0000560 [ DOI ] [ PubMed ] [ Google Scholar ] 24. Frech A. (2012). Healthy Behavior Trajectories between Adolescence and Young Adulthood. Advances in Life Course Research, 17(2), 59–68. 10.1016/j.alcr.2012.01.003 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 25. Cohen S, Janicki-Deverts D, Chen E, & Matthews KA (2010). Childhood socioeconomic status and adult health. Annals of the New York Academy of Sciences, 1186(1), 37–55. 10.1111/j.1749-6632.2009.05334.x [ DOI ] [ PubMed ] [ Google Scholar ] 26. Miller GE, & Chen E (2013). The biological residue of childhood poverty. Child Development Perspectives, 7(2), 67–73. 10.1111/cdep.12021 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 27. Hällsten M, & Thaning M (2022). Wealth as One of the “Big Four” SES Dimensions in Intergenerational Transmissions. Social Forces, 100(4), 1533–1560. 10.1093/sf/soab080 [ DOI ] [ Google Scholar ] 28. Hällsten M, & Pfeffer FT (2017). Grand Advantage: Family Wealth and Grandchildren’s Educational Achievement in Sweden. American Sociological Review, 82(2), 328–360. 10.1177/0003122417695791 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 29. Braveman PA, Cubbin C, Egerter S, Chideya S, Marchi KS, Metzler M, & Posner S (2005). Socioeconomic Status in Health ResearchOne Size Does Not Fit All. JAMA, 294(22), 2879–2888. 10.1001/jama.294.22.2879 [ DOI ] [ PubMed ] [ Google Scholar ] 30. Duncan GJ, & Magnuson KA (2002). Off With Hollingshead: Socioeconomic Resources, Parenting, and Child Development. In Socioeconomic Status, Parenting, and Child Development. Routledge. [ Google Scholar ] 31. Sawyer SM, Afifi RA, Bearinger LH, Blakemore S-J, Dick B, Ezeh AC, & Patton GC (2012). Adolescence: A foundation for future health. The Lancet, 379(9826), 1630–1640. [ DOI ] [ PubMed ] [ Google Scholar ] 32. Saez E, & Zucman G (2016). Wealth Inequality in the United States since 1913: Evidence from Capitalized Income Tax Data *. The Quarterly Journal of Economics, 131(2), 519–578. 10.1093/qje/qjw004 [ DOI ] [ Google Scholar ] 33. Duncan GJ, Daly MC, McDonough P, & Williams DR (2002). Optimal Indicators of Socioeconomic Status for Health Research. American Journal of Public Health, 92(7), 1151–1157. 10.2105/AJPH.92.7.1151 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 34. Schoenbaum M, & Waidmann T (1997). Race, Socioeconomic Status, and Health: Accounting for Race Differences in Health. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 52B(Special), 61–73. 10.1093/geronb/52B.Special_Issue.61 [ DOI ] [ PubMed ] [ Google Scholar ] 35. Pfeffer FT & Killewald A (2015). How rigid is the wealth structure and why? Inter-and multi-generational associations in family wealth (PSR Reports No.15-845). University of Michigan Institute for Social Research. [ Google Scholar ] 36. Semyonov M, Lewin-Epstein N, & Maskileyson D (2013). Where wealth matters more for health: The wealth–health gradient in 16 countries. Social Science & Medicine, 81, 10–17. 10.1016/j.socscimed.2013.01.010 [ DOI ] [ PubMed ] [ Google Scholar ] 37. Spikes T, Murden R, McKinnon II, Bromfield S, Van Dyke ME, Moore RH, Rahbari-Oskoui FF, Quyummi A, Vaccarino V, & Lewis TT (2022). Association of Net Worth and Ambulatory Blood Pressure in Early Middle-aged African American Women. JAMA Network Open, 5(2), e220331. 10.1001/jamanetworkopen.2022.0331 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 38. Wu S, Wang X, Wu Q, & Harris KM (2018). Household Financial Assets Inequity and Health Disparities Among Young Adults: Evidence from the National Longitudinal Study of Adolescent to Adult Health. Journal of Health Disparities Research and Practice, 11(1), 122–135. [ PMC free article ] [ PubMed ] [ Google Scholar ] 39. Conwell JA, & Ye LZ (2021). All Wealth Is Not Created Equal: Race, Parental Net Worth, and Children’s Achievement. RSF: The Russell Sage Foundation Journal of the Social Sciences, 7(3), 101–121. [ Google Scholar ] 40. Gibson-Davis C, Keister LA, Gennetian LA, & Lowell W (2022). Net worth poverty and child development. Socius, 8, 23780231221111672. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 41. Xiao JJ, & Yao R (2022). Good debt, bad debt: Family debt portfolios and financial burdens. International Journal of Bank Marketing, 40(4), 659–678. 10.1108/IJBM-06-2021-0243 [ DOI ] [ Google Scholar ] 42. Jr WAD, & Mullen AK (2022). From Here to Equality, Second Edition: Reparations for Black Americans in the Twenty-First Century. UNC Press Books. [ Google Scholar ] 43. Rugh JS, & Massey DS (2010). Racial Segregation and the American Foreclosure Crisis. American Sociological Review, 75(5), 629–651. 10.1177/0003122410380868 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 44. Kaas L, Kocharkov G, & Preugschat E (2019). Wealth Inequality and Homeownership in Europe. Annals of Economics and Statistics, 136, 27–54. 10.15609/annaeconstat2009.136.0027 [ DOI ] [ Google Scholar ] 45. Currie C, Molcho M, Boyce W, Holstein B, Torsheim T, & Richter M (2008). Researching health inequalities in adolescents: The development of the Health Behaviour in School-Aged Children (HBSC) family affluence scale. Social Science & Medicine, 66(6), 1429–1436. [ DOI ] [ PubMed ] [ Google Scholar ] 46. Boyce W, Torsheim T, Currie C, & Zambon A (2006). The Family Affluence Scale as a Measure of National Wealth: Validation of an Adolescent Self-Report Measure. Social Indicators Research, 78(3), 473–487. 10.1007/s11205-005-1607-6 [ DOI ] [ Google Scholar ] 47. Torsheim T, Currie C, Boyce W, Kalnins I, Overpeck M, & Haugland S (2004). Material deprivation and self-rated health: A multilevel study of adolescents from 22 European and North American countries. Social Science & Medicine, 59(1), 1–12. 10.1016/j.socscimed.2003.09.032 [ DOI ] [ PubMed ] [ Google Scholar ] 48. Corell M, Chen Y, Friberg P, Petzold M, & Löfstedt P (2021). Does the family affluence scale reflect actual parental earned income, level of education and occupational status? A validation study using register data in Sweden. BMC Public Health, 21(1), 1995. 10.1186/s12889-021-11968-2 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 49. scheme=AGLSTERMS. AglsAgent; authorName=Macfarlane I (2003, April 3). Do Australian Households Borrow Too Much? ∣ Speeches (Australia). Reserve Bank of Australia. https://www.rba.gov.au/speeches/2003/sp-gov-030403.html [ Google Scholar ] 50. Dunn LF, & Mirzaie IA (2016). Consumer debt stress, changes in household debt, and the great recession. Economic Inquiry, 54(1), 201–214. [ Google Scholar ] 51. Montgomerie J. (2006). Giving Credit where it’s Due: Public Policy and Household Debt in the United States, the United Kingdom and Canada. Policy and Society, 25(3), 109–141. 10.1016/S1449-4035(06)70085-6 [ DOI ] [ Google Scholar ] 52. Daneshkhu S. (2002). Consumer debt rising and worsening, warns Bank FINANCIAL STABILITY REVIEW ALARM OVER HOUSEBUYERS’ BORROWING AND SPIRALLING DEBT AMONG VULNERABLE GROUPS. The Financial Times, 3–3. [ Google Scholar ] 53. Currie C, Alemán Díaz AY, Bosáková L, & de Looze M (2024). The international Family Affluence Scale (FAS): Charting 25 years of indicator development, evidence produced, and policy impact on adolescent health inequalities. SSM - Population Health, 25, 101599. 10.1016/j.ssmph.2023.101599 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 54. Chen E, Lee WK, Cavey L, & Ho A (2013). Role Models and the Psychological Characteristics That Buffer Low-Socioeconomic-Status Youth From Cardiovascular Risk. Child Development, 84(4), 1241–1252. 10.1111/cdev.12037 [ DOI ] [ PubMed ] [ Google Scholar ] 55. Chen E, Hanson MD, Paterson LQ, Griffin MJ, Walker HA, & Miller GE (2006). Socioeconomic status and inflammatory processes in childhood asthma: The role of psychological stress. Journal of Allergy and Clinical Immunology, 117(5), 1014–1020. 10.1016/j.jaci.2006.01.036 [ DOI ] [ PubMed ] [ Google Scholar ] 56. Libby P (2006). Inflammation and cardiovascular disease mechanisms. The American Journal of Clinical Nutrition, 83(2), 456S–460S. [ DOI ] [ PubMed ] [ Google Scholar ] 57. Green RH, Brightling CE, McKenna S, Hargadon B, Parker D, Bradding P, Wardlaw AJ, & Pavord ID (2002). Asthma exacerbations and sputum eosinophil counts: A randomised controlled trial. The Lancet, 360(9347), 1715–1721. 10.1016/S0140-6736(02)11679-5 [ DOI ] [ PubMed ] [ Google Scholar ] 58. Boen Keister, & Graetz. (2021). Household Wealth and Child Body Mass Index: Patterns and Mechanisms. RSF: The Russell Sage Foundation Journal of the Social Sciences, 7(3), 80. 10.7758/rsf.2021.7.3.04 [ DOI ] [ Google Scholar ] 59. Chen E, Cohen S, & Miller GE (2010). How Low Socioeconomic Status Affects 2-Year Hormonal Trajectories in Children. Psychological Science, 21(1), 31–37. 10.1177/0956797609355566 [ DOI ] [ PubMed ] [ Google Scholar ] 60. Padgett DA, & Glaser R (2003). How stress influences the immune response. Trends in Immunology, 24(8), 444–448. 10.1016/S1471-4906(03)00173-X [ DOI ] [ PubMed ] [ Google Scholar ] 61. Plat L, Byrne MM, Sturis J, Polonsky KS, Mockel J, Fery F, & Van Cauter E (1996). Effects of morning cortisol elevation on insulin secretion and glucose regulation in humans. American Journal of Physiology-Endocrinology and Metabolism, 270(1), E36–E42. 10.1152/ajpendo.1996.270.1.E36 [ DOI ] [ PubMed ] [ Google Scholar ] 62. Chrousos GP (2009). Stress and disorders of the stress system. Nature Reviews Endocrinology, 5(7), 374–381. 10.1038/nrendo.2009.106 [ DOI ] [ PubMed ] [ Google Scholar ] 63. Miller GE, Chen E, & Zhou ES (2007). If it goes up, must it come down? Chronic stress and the hypothalamic-pituitary-adrenocortical axis in humans. [ DOI ] [ PubMed ] [ Google Scholar ] 64. Pervanidou P, & Chrousos GP (2012). Metabolic consequences of stress during childhood and adolescence. Metabolism, 61(5), 611–619. 10.1016/j.metabol.2011.10.005 [ DOI ] [ PubMed ] [ Google Scholar ] 65. Cohen S, Doyle WJ, Turner RB, Alper CM, & Skoner DP (2004). Childhood Socioeconomic Status and Host Resistance to Infectious Illness in Adulthood. Psychosomatic Medicine, 66(4), 553–558. 10.1097/01.psy.0000126200.05189.d3 [ DOI ] [ PubMed ] [ Google Scholar ] 66. Cohen S, Janicki-Deverts D, Turner RB, Marsland AL, Casselbrant ML, Li-Korotky H-S, Epel ES, & Doyle WJ (2013). Childhood socioeconomic status, telomere length, and susceptibility to upper respiratory infection. Brain, Behavior, and Immunity, 34, 31–38. 10.1016/j.bbi.2013.06.009 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 67. Carroll JE, Cohen S, & Marsland AL (2011). Early childhood socioeconomic status is associated with circulating interleukin-6 among mid-life adults. Brain, Behavior, and Immunity, 25(7), 1468–1474. 10.1016/j.bbi.2011.05.016 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 68. Packard CJ, Bezlyak V, McLean JS, Batty GD, Ford I, Burns H, Cavanagh J, Deans KA, Henderson M, McGinty A, Millar K, Sattar N, Shiels PG, Velupillai YN, & Tannahill C (2011). Early life socioeconomic adversity is associated in adult life with chronic inflammation, carotid atherosclerosis, poorer lung function and decreased cognitive performance: A cross-sectional, population-based study. BMC Public Health, 11(1), 42. 10.1186/1471-2458-11-42 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 69. Hansen CL, Chaves SS, Demont C, & Viboud C (2022). Mortality associated with influenza and respiratory syncytial virus in the US, 1999-2018. JAMA Network Open, 5(2), e220527–e220527. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 70. Koskela R-S, Mutanen P, Sorsa J-A, & Klockars M (2005). Respiratory disease and cardiovascular morbidity. Occupational and Environmental Medicine, 62(9), 650–655. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 71. Richter M, Vereecken CA, Boyce W, Maes L, Gabhainn SN, & Currie CE (2009). Parental occupation, family affluence and adolescent health behaviour in 28 countries. International Journal of Public Health, 54(4), 203–212. 10.1007/s00038-009-8018-4 [ DOI ] [ PubMed ] [ Google Scholar ] 72. Dierckens M, Richter M, Moor I, Elgar FJ, Clays E, Deforche B, & De Clercq B (2022). Trends in material and non-material inequalities in adolescent health and health behaviours: A 12-year study in 23 European countries. Preventive Medicine, 157, 107018. 10.1016/j.ypmed.2022.107018 [ DOI ] [ PubMed ] [ Google Scholar ] 73. Henriksson P, Henriksson H, Labayen I, Huybrechts I, Gracia-Marco L, Ortega FB, España-Romero V, Manios Y, González-Gross M, Marcos A, Moreno LA, Gutiérrez Á, Ruiz JR, Moreno LA, Gottrand F, De Henauw S, González-Gross M, Gilbert C, Kafatos A, … Navarro P (2018). Correlates of ideal cardiovascular health in European adolescents: The HELENA study. Nutrition, Metabolism and Cardiovascular Diseases, 28(2), 187–194. 10.1016/j.numecd.2017.10.018 [ DOI ] [ PubMed ] [ Google Scholar ] 74. Belardinelli P, Torbica A, & Fattore G (2022). Longitudinal associations between different measures of socioeconomic status and health behavior among adolescents. Data from a wealthy Italian region. Preventive Medicine, 160, 107092. 10.1016/j.ypmed.2022.107092 [ DOI ] [ PubMed ] [ Google Scholar ] 75. Zaborskis A, Grincaitė M, Kavaliauskienė A, & Tesler R (2021). Family structure and affluence in adolescent eating behaviour: A cross-national study in forty-one countries. Public Health Nutrition, 24(9), 2521–2532. 10.1017/S1368980020003584 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 76. Schmengler H, Peeters M, Stevens GWJM, Kunst AE, Delaruelle K, Dierckens M, Charrier L, Weinberg D, Oldehinkel AJ, & Vollebergh WAM (2022). Socioeconomic inequalities in adolescent health behaviours across 32 different countries – The role of country-level social mobility. Social Science & Medicine, 310, 115289. 10.1016/j.socscimed.2022.115289 [ DOI ] [ PubMed ] [ Google Scholar ] 77. Doku D, Koivusilta L, & Rimpelä A (2010). Indicators for Measuring Material Affluence of Adolescents in Health Inequality Research in Developing Countries. Child Indicators Research, 3(2), 243–260. 10.1007/s12187-009-9045-7 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 78. Azupogo F, Abizari A-R, Aurino E, Gelli A, Osendarp SJ, Bras H, Feskens EJM, & Brouwer ID (2020). Malnutrition, hypertension risk, and correlates: An analysis of the 2014 ghana demographic and health survey data for 15–19 years adolescent boys and girls. Nutrients, 12(9), 2737. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 79. Ullmann SH, Buttenheim AM, Goldman N, Pebley AR, & Wong R (2011). Socioeconomic differences in obesity among Mexican adolescents. International Journal of Pediatric Obesity, 6(2Part2), e373–e380. 10.3109/17477166.2010.498520 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 80. Islam MR, Rahman SM, Rahman MM, Pervin J, Rahman A, & Ekström E-C (2022). Gender and socio-economic stratification of ultra-processed and deep-fried food consumption among rural adolescents: A cross-sectional study from Bangladesh. Plos One, 17(7), e0272275. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 81. Makaroun LK, Brown RT, Diaz-Ramirez LG, Ahalt C, Boscardin WJ, Lang-Brown S, & Lee S (2017). Wealth-Associated Disparities in Death and Disability in the United States and England. JAMA Internal Medicine, 177(12), 1745–1753. 10.1001/jamainternmed.2017.3903 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 82. Pool LR, Burgard SA, Needham BL, Elliott MR, Langa KM, & Mendes de Leon CF (2018). Association of a Negative Wealth Shock With All-Cause Mortality in Middle-aged and Older Adults in the United States. JAMA, 319(13), 1341–1350. 10.1001/jama.2018.2055 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 83. Hajat A, Kaufman JS, Rose KM, Siddiqi A, & Thomas JC (2010). Do the wealthy have a health advantage? Cardiovascular disease risk factors and wealth. Social Science & Medicine, 71(11), 1935–1942. 10.1016/j.socscimed.2010.09.027 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 84. Sweet E, Nandi A, Adam EK, & McDade TW (2013). The high price of debt: Household financial debt and its impact on mental and physical health. Social Science & Medicine, 91, 94–100. 10.1016/j.socscimed.2013.05.009 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 85. Shartle K, Yang YC, Richman LS, Belsky DW, Aiello AE, & Harris KM (2022). Social Relationships, Wealth, and Cardiometabolic Risk: Evidence from a National Longitudinal Study of U.S. Older Adults. Journal of Aging and Health, 34(6–8), 1048–1061. 10.1177/08982643221087807 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 86. Kane JB, Harris KM, Morgan SP, & Guilkey DK (2018). Pathways of Health and Human Capital from Adolescence into Young Adulthood. Social Forces, 96(3), 949–976. 10.1093/sf/sox079 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 87. Perel P, Langenberg C, Ferrie J, Moser K, Brunner E, & Marmot M (2006). Household wealth and the metabolic syndrome in the Whitehall II study. Diabetes Care, 29(12), 2694–2700. [ DOI ] [ PubMed ] [ Google Scholar ] 88. Hamilton OS, & Steptoe A (2023). Socioeconomic determinants of inflammation and neuroendocrine activity: A longitudinal analysis of compositional and contextual effects. Brain, Behavior, and Immunity, 107, 276–285. [ DOI ] [ PubMed ] [ Google Scholar ] 89. Koster A, Bosma H, Penninx BWJH, Newman AB, Harris TB, van Eijk J. Th. M., Kempen GIJM, Simonsick EM, Johnson KC, Rooks RN, Ayonayon HN, Rubin SM, Kritchevsky SB, & for the Health ABC Study. (2006). Association of Inflammatory Markers With Socioeconomic Status. The Journals of Gerontology: Series A, 61(3), 284–290. 10.1093/gerona/61.3.284 [ DOI ] [ PubMed ] [ Google Scholar ] 90. Gibson-Davis C, Boen CE, Keister LA, & Lowell W (2023). Net worth poverty and adult health. Social Science & Medicine, 318, 115614. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 91. Chen E, Brody GH, & Miller GE (2017). Childhood close family relationships and health. American Psychologist, 72(6), 555. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 92. Conger RD, Conger KJ, & Martin MJ (2010). Socioeconomic Status, Family Processes,and Individual Development. Journal of Marriage and Family, 72(3), 685–704. 10.1111/j.1741-3737.2010.00725.x [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 93. Conger RD, & Donnellan MB (2007). An interactionist perspective on the socioeconomic context of human development. Annu. Rev. Psychol, 58, 175–199. [ DOI ] [ PubMed ] [ Google Scholar ] 94. Lin N (2000). Inequality in social capital. Contemporary Sociology, 29(6), 785–795. [ Google Scholar ] 95. Vyncke V, De Clercq B, Stevens V, Costongs C, Barbareschi G, Jónsson SH, Curvo SD, Kebza V, Currie C, & Maes L (2013). Does neighbourhood social capital aid in levelling the social gradient in the health and well-being of children and adolescents? A literature review. BMC Public Health, 13(1), 65. 10.1186/1471-2458-13-65 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 96. Hashemi N, Sebar B, & Harris N (2018). The relationship between cultural capital and lifestyle health behaviours in young people: A systematic review. Public Health, 164, 57–67. 10.1016/j.puhe.2018.07.020 [ DOI ] [ PubMed ] [ Google Scholar ] 97. Quon EC, & McGrath JJ (2014). Subjective socioeconomic status and adolescent health: A meta-analysis. Health Psychology, 33(5), 433–447. 10.1037/a0033716 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 98. Chen E, Brody GH, & Miller GE (2022). What Are the Health Consequences of Upward Mobility? Annual Review of Psychology, 73(1), null. 10.1146/annurev-psych-033020-122814 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 99. Folkman S, Lazarus RS, Dunkel-Schetter C, DeLongis A, & Gruen RJ (1986). Dynamics of a stressful encounter: Cognitive appraisal, coping, and encounter outcomes. Journal of Personality and Social Psychology, 50(5), 992. [ DOI ] [ PubMed ] [ Google Scholar ] 100. Conger RD, Conger KJ, Elder GH, Lorenz FO, Simons RL, & Whitbeck LB (1993). Family economic stress and adjustment of early adolescent girls. Developmental Psychology, 29(2), 206–219. 10.1037/0012-1649.29.2.206 [ DOI ] [ Google Scholar ] 101. Conger RD, Ge X, Elder GH Jr, Lorenz FO, & Simons RL (1994). Economic stress, coercive family process, and developmental problems of adolescents. Child Development, 65(2), 541–561. [ PubMed ] [ Google Scholar ] 102. Rodems R, & Pfeffer FT (2021). Avoiding material hardship: The buffer function of wealth. Journal of European Social Policy, 31(5), 517–532. [ Google Scholar ] 103. Sherraden M (1991). Assets and the poor: A new American welfare policy. ME Sharpe. Inc., Armonk, New York. [ Google Scholar ] 104. Yeung WJ, & Hofferth SL (1998). Family adaptations to income and job loss in the US. Journal of Family and Economic Issues, 19, 255–283. [ Google Scholar ] 105. Low NC, Dugas E, O’Loughlin E, Rodriguez D, Contreras G, Chaiton M, & O’Loughlin J (2012). Common stressful life events and difficulties are associated with mental health symptoms and substance use in young adolescents. BMC Psychiatry, 12(1), 116. 10.1186/1471-244X-12-116 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 106. Peltz JS, Rogge RD, & O’Connor TG (2019). Adolescent sleep quality mediates family chaos and adolescent mental health: A daily diary-based study. Journal of Family Psychology, 33(3), 259–269. 10.1037/fam0000491 [ DOI ] [ PubMed ] [ Google Scholar ] 107. Simantov E, Schoen C, & Klein JD (2000). Health-Compromising Behaviors: Why Do Adolescents Smoke or Drink? ARCH PEDIATR ADOLESC MED, 154. [ DOI ] [ PubMed ] [ Google Scholar ] 108. Chen E, Langer DA, Raphaelson YE, & Matthews KA (2004). Socioeconomic Status and Health in Adolescents: The Role of Stress Interpretations. Child Development, 75(4), 1039–1052. 10.1111/j.1467-8624.2004.00724.x [ DOI ] [ PubMed ] [ Google Scholar ] 109. Dumas JE, Nissley J, Nordstrom A, Smith EP, Prinz RJ, & Levine DW (2005). Home Chaos: Sociodemographic, Parenting, Interactional, and Child Correlates. Journal of Clinical Child & Adolescent Psychology, 34(1), 93–104. 10.1207/s15374424jccp3401_9 [ DOI ] [ PubMed ] [ Google Scholar ] 110. He K, Kramer E, Houser RF, Chomitz VR, & Hacker KA (2004). Defining and understanding healthy lifestyles choices for adolescents. Journal of Adolescent Health, 35(1), 26–33. 10.1016/j.jadohealth.2003.09.004 [ DOI ] [ PubMed ] [ Google Scholar ] 111. Kotchick BA, & Forehand R (2002). Putting parenting in perspective: A discussion of the contextual factors that shape parenting practices. Journal of Child and Family Studies, 11, 255–269. [ Google Scholar ] 112. Lippold MA, Davis KD, McHale SM, Buxton OM, & Almeida DM (2016). Daily stressor reactivity during adolescence: The buffering role of parental warmth. Health Psychology, 35(9), 1027–1035. 10.1037/hea0000352 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 113. Davids EL, Roman NV, & Leach L (2017). The link between parenting approaches and health behavior: A systematic review. Journal of Human Behavior in the Social Environment, 27(6), 589–608. 10.1080/10911359.2017.1311816 [ DOI ] [ Google Scholar ] 114. Ghazy Elsayed HA, Lissner L, Mehlig K, Thumann BF, Hebestreit A, Pala V, Veidebaum T, Solea T, Moreno L, Molnár D, Wisnuwardani RW, Lauria F, Hunsberger M, & on behalf of the IDEFICS and I.Family consortia. (2020). Relationship between perception of emotional home atmosphere and fruit and vegetable consumption in European adolescents: Results from the I.Family survey. Public Health Nutrition, 23(1), 53–62. 10.1017/S1368980019002234 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 115. Ramdahl ME, Jensen SS, Borgund E, Samdal O, & Torsheim T (2018). Family wealth and parent–child relationships. Journal of Child and Family Studies, 27, 1534–1543. [ Google Scholar ] 116. Brown S, Taylor K, & Price SW (2005). Debt and distress: Evaluating the psychological cost of credit. Journal of Economic Psychology, 26(5), 642–663. [ Google Scholar ] 117. Drentea P, & Lavrakas PJ (2000). Over the limit: The association among health, race and debt. Social Science & Medicine, 50(4), 517–529. [ DOI ] [ PubMed ] [ Google Scholar ] 118. Chen E, & Miller GE (2013). Socioeconomic Status and Health: Mediating and Moderating Factors. Annual Review of Clinical Psychology, 9(1), 723–749. 10.1146/annurev-clinpsy-050212-185634 [ DOI ] [ PubMed ] [ Google Scholar ] 119. McLoyd VC (1998). Socioeconomic disadvantage and child development. American Psychologist, 53(2), 185. [ DOI ] [ PubMed ] [ Google Scholar ] 120. Schofield TJ, Conger RD, Gonzales JE, & Merrick MT (2016). Harsh parenting, physical health, and the protective role of positive parent-adolescent relationships. Social Science & Medicine (1982), 157, 18–26. 10.1016/j.socscimed.2016.03.027 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 121. Streit C, & Davis AN (2022). The longitudinal links between parenting stress, harsh parenting, and adolescents’ social behaviors in Latinx families. Journal of Latinx Psychology, 10(2), 128. [ Google Scholar ] 122. Wadsworth ME, & Berger LE (2006). Adolescents coping with poverty-related family stress: Prospective predictors of coping and psychological symptoms. Journal of Youth and Adolescence, 35, 54–67. [ Google Scholar ] 123. Sleskova M, Salonna F, Geckova AM, Nagyova I, Stewart RE, van Dijk JP, & Groothoff JW (2006). Does parental unemployment affect adolescents’ health? Journal of Adolescent Health, 38(5), 527–535. 10.1016/j.jadohealth.2005.03.021 [ DOI ] [ PubMed ] [ Google Scholar ] 124. Duncan GJ, Magnuson K, & Votruba-Drzal E (2017). Moving beyond correlations in assessing the consequences of poverty. Annual Review of Psychology, 68, 413–434. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 125. Dickman SL, Himmelstein DU, & Woolhandler S (2017). Inequality and the health-care system in the USA. The Lancet, 389(10077), 1431–1441. 10.1016/S0140-6736(17)30398-7 [ DOI ] [ PubMed ] [ Google Scholar ] 126. Evans GW, & Wachs TD (2010). Chaos and its influence on children’s development. Washington, DC: American Psychological Association, 6(2–3), 66–80. [ Google Scholar ] 127. Wachs TD, & Evans GW (2010). Chaos in context. [ Google Scholar ] 128. Chen E, & Paterson LQ (2006). Neighborhood, family, and subjective socioeconomic status: How do they relate to adolescent health? Health Psychology, 25(6), 704–714. 10.1037/0278-6133.25.6.704 [ DOI ] [ PubMed ] [ Google Scholar ] 129. McGrath JJ, Matthews KA, & Brady SS (2006). Individual versus neighborhood socioeconomic status and race as predictors of adolescent ambulatory blood pressure and heart rate. Social Science & Medicine, 63(6), 1442–1453. 10.1016/j.socscimed.2006.03.019 [ DOI ] [ PubMed ] [ Google Scholar ] 130. Aris IM, Rifas-Shiman SL, Jimenez MP, Li L-J, Hivert M-F, Oken E, & James P (2021). Neighborhood Child Opportunity Index and Adolescent Cardiometabolic Risk. Pediatrics, 147(2), e2020018903. 10.1542/peds.2020-018903 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 131. Brook RD, Rajagopalan S, Pope CA, Brook JR, Bhatnagar A, Diez-Roux AV, Holguin F, Hong Y, Luepker RV, Mittleman MA, Peters A, Siscovick D, Smith SC, Whitsel L, & Kaufman JD (2010). Particulate Matter Air Pollution and Cardiovascular Disease. Circulation, 121(21), 2331–2378. 10.1161/CIR.0b013e3181dbece1 [ DOI ] [ PubMed ] [ Google Scholar ] 132. Mayne SL, Mitchell JA, Virudachalam S, Fiks AG, & Williamson AA (2021). Neighborhood Environments and Sleep Among Children and Adolescents: A Systematic Review. Sleep Medicine Reviews, 57, 101465. 10.1016/j.smrv.2021.101465 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 133. Patel MM, Chillrud SN, Deepti KC, Ross JM, & Kinney PL (2013). Traffic-related air pollutants and exhaled markers of airway inflammation and oxidative stress in New York City adolescents. Environmental Research, 121, 71–78. 10.1016/j.envres.2012.10.012 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 134. Chen Z, Newgard CB, Kim JS, IIkayeva O, Alderete TL, Thomas DC, Berhane K, Breton C, Chatzi L, Bastain TM, McConnell R, Avol E, Lurmann F, Muehlbauer MJ, Hauser ER, & Gilliland FD (2019). Near-roadway air pollution exposure and altered fatty acid oxidation among adolescents and young adults – The interplay with obesity. Environment International, 130, 104935. 10.1016/j.envint.2019.104935 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 135. Larson NI, Story MT, & Nelson MC (2009). Neighborhood Environments: Disparities in Access to Healthy Foods in the U.S. American Journal of Preventive Medicine, 36(1), 74–81.e10. 10.1016/j.amepre.2008.09.025 [ DOI ] [ PubMed ] [ Google Scholar ] 136. Neumark-Sztainer D, Larson NI, Fulkerson JA, Eisenberg ME, & Story M (2010). Family meals and adolescents: What have we learned from Project EAT (Eating Among Teens)? Public Health Nutrition, 13(7), 1113–1121. 10.1017/S1368980010000169 [ DOI ] [ PubMed ] [ Google Scholar ] 137. Sukys S, Majauskienė D, Cesnaitiene VJ, & Karanauskiene D (2014). Do Parents’ Exercise Habits Predict 13–18-Year-Old Adolescents’ Involvement in Sport? Journal of Sports Science & Medicine, 13(3), 522–528. [ PMC free article ] [ PubMed ] [ Google Scholar ] 138. DiClemente RJ, Wingood GM, Crosby R, Sionean C, Cobb BK, Harrington K, Davies S, Hook EW III, & Oh MK (2001). Parental Monitoring: Association With Adolescents’ Risk Behaviors. Pediatrics, 107(6), 1363–1368. 10.1542/peds.107.6.1363 [ DOI ] [ PubMed ] [ Google Scholar ] 139. Mahabee-Gittens EM, Xiao Y, Gordon JS, & Khoury JC (2013). The dynamic role of parental influences in preventing adolescent smoking initiation. Addictive Behaviors, 38(4), 1905–1911. 10.1016/j.addbeh.2013.01.002 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 140. Human LJ, Chan M, DeLongis A, Roy L, Miller GE, & Chen E (2014). Parental Accuracy Regarding Adolescent Daily Experiences: Relationships With Adolescent Psychological Adjustment and Inflammatory Regulation. Psychosomatic Medicine, 76(8), 603. 10.1097/PSY.0000000000000105 [ DOI ] [ PubMed ] [ Google Scholar ] 141. Cohen S, Janicki-Deverts D, Doyle WJ, Miller GE, Frank E, Rabin BS, & Turner RB (2012). Chronic stress, glucocorticoid receptor resistance, inflammation, and disease risk. Proceedings of the National Academy of Sciences, 109(16), 5995–5999. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 142. Berger LM, & Houle JN (2016). Parental debt and children’s socioemotional well-being. Pediatrics, 137(2). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 143. Berger LM, & Houle JN (2019). Rising household debt and children’s socioemotional well-being trajectories. Demography, 56(4), 1273–1301. [ DOI ] [ PubMed ] [ Google Scholar ] 144. Landstedt E, Hammarström A, & Winefield H (2015). How well do parental and peer relationships in adolescence predict health in adulthood? Scandinavian Journal of Public Health, 43(5), 460–468. 10.1177/1403494815576360 [ DOI ] [ PubMed ] [ Google Scholar ] 145. Ces S, & Baeten R (2020). Inequalities in access to healthcare in Belgium. [ Google Scholar ] 146. Wamala S, Merlo J, Bostrom G, & Hogstedt C (2007). Perceived discrimination, socioeconomic disadvantage and refraining from seeking medical treatment in Sweden. Journal of Epidemiology & Community Health, 61(5), 409–415. 10.1136/jech.2006.049999 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 147. Wahlbeck K, Manderbacka K, Vuorenkoski L, Kuusio H, Luoma ML, & Widström E (2008). Quality and Equality of Access to Healthcare Services: HealthQUEST country report for Finland. [ Google Scholar ] 148. Portes A. (1998). Social Capital: Its Origins and Applications in Modern Sociology. Annual Review of Sociology, 24(1), 1–24. 10.1146/annurev.soc.24.1.1 [ DOI ] [ Google Scholar ] 149. Swartz D. (2012). Culture and power: The sociology of Pierre Bourdieu. University of Chicago Press. [ Google Scholar ] 150. Kerri M, Kerr PDS, Cheater F, & Morgan A (2013). The role and impact of social capital on the health and wellbeing of children and adolescents: A systematic review. Glasgow: Glasgow Centre for Population Health. Glasgow Caledonian University. [ Google Scholar ] 151. Morgan A, & Haglund BJA (2009). Social capital does matter for adolescent health: Evidence from the English HBSC study. Health Promotion International, 24(4), 363–372. 10.1093/heapro/dap028 [ DOI ] [ PubMed ] [ Google Scholar ] 152. Richmond TK, Milliren C, Walls CE, & Kawachi I (2014). School Social Capital and Body Mass Index in the National Longitudinal Study of Adolescent Health. Journal of School Health, 84(12), 759–768. 10.1111/josh.12213 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 153. Domínguez S, & Arford T (2010). It is all about who you know: Social capital and health in low-income communities. Health Sociology Review, 19(1), 114–129. 10.5172/hesr.2010.19.1.114 [ DOI ] [ Google Scholar ] 154. Abel T. (2008). Cultural capital and social inequality in health. Journal of Epidemiology and Community Health, 62, e13. 10.1136/jech.2007.066159 [ DOI ] [ PubMed ] [ Google Scholar ] 155. Fismen A-S, Samdal O, & Torsheim T (2012). Family affluence and cultural capital as indicators of social inequalities in adolescent’s eating behaviours: A population-based survey. BMC Public Health, 12(1), 1036. 10.1186/1471-2458-12-1036 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 156. Raymond-Flesch M, Auerswald C, McGlone L, Comfort M, & Minnis A (2017). Building social capital to promote adolescent wellbeing: A qualitative study with teens in a Latino agricultural community. BMC Public Health, 17(1), 177. 10.1186/s12889-017-4110-5 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 157. Boyce WF, Davies D, Gallupe O, & Shelley D (2008). Adolescent Risk Taking, Neighborhood Social Capital, and Health. Journal of Adolescent Health, 43(3), 246–252. 10.1016/j.jadohealth.2008.01.014 [ DOI ] [ PubMed ] [ Google Scholar ] 158. Nieuwenhuis J. (2020). Neighborhood social capital and adolescents’ individual health development. Social Science & Medicine, 265, 113417. 10.1016/j.socscimed.2020.113417 [ DOI ] [ PubMed ] [ Google Scholar ] 159. Newacheck PW, Hung YY, Jane Park M, Brindis CD, & Irwin CE Jr (2003). Disparities in adolescent health and health care: Does socioeconomic status matter? Health Services Research, 38(5), 1235–1252. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 160. Friis K, Lasgaard M, Rowlands G, Osborne RH, & Maindal HT (2016). Health Literacy Mediates the Relationship Between Educational Attainment and Health Behavior: A Danish Population-Based Study. Journal of Health Communication, 21(sup2), 54–60. 10.1080/10810730.2016.1201175 [ DOI ] [ PubMed ] [ Google Scholar ] 161. Ahuja M, Haeny AM, Sartor CE, & Bucholz KK (2022). Perceived racial and social class discrimination and cannabis involvement among Black youth and young adults. Drug and Alcohol Dependence, 232, 109304. 10.1016/j.drugalcdep.2022.109304 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 162. Leventhal AM, Cho J, Andrabi N, & Barrington-Trimis J (2018). Association of Reported Concern About Increasing Societal Discrimination With Adverse Behavioral Health Outcomes in Late Adolescence. JAMA Pediatrics, 172(10), 924–933. 10.1001/jamapediatrics.2018.2022 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 163. Denise EJ (2012). Multiple Forms of Perceived Discrimination and Health among Adolescents and Young Adults. Journal of Health and Social Behavior, 53(2), 199–214. 10.1177/0022146512444289 [ DOI ] [ PubMed ] [ Google Scholar ] 164. Pascoe EA, & Richman LS (2009). Perceived Discrimination and Health: A Meta-Analytic Review. Psychological Bulletin, 135(4), 531–554. 10.1037/a0016059 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 165. Adler N, & Stewart J (2007). The MacArthur scale of subjective social status. San Francisco: MacArthur Research Network on SES & Health. [ Google Scholar ] 166. Sweeting H, & Hunt K (2014). Adolescent socio-economic and school-based social status, health and well-being. Social Science & Medicine, 121, 39–47. 10.1016/j.socscimed.2014.09.037 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 167. Anderson C, Kraus MW, Galinsky AD, & Keltner D (2012). The Local-Ladder Effect: Social Status and Subjective Well-Being. Psychological Science, 23(7), 764–771. 10.1177/0956797611434537 [ DOI ] [ PubMed ] [ Google Scholar ] 168. Destin M, Richman S, Varner F, & Mandara J (2012). “Feeling” hierarchy: The pathway from subjective social status to achievement. Journal of Adolescence, 35(6), 1571–1579. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 169. Kraus MW, Tan JJX, & Tannenbaum MB (2013). The Social Ladder: A Rank-Based Perspective on Social Class. Psychological Inquiry, 24(2), 81–96. 10.1080/1047840X.2013.778803 [ DOI ] [ Google Scholar ] 170. Huynh VW, & Chiang JJ (2018). Subjective Social Status and Adolescent Health: The Role of Stress and Sleep. Youth & Society, 50(7), 926–946. 10.1177/0044118X16646028 [ DOI ] [ Google Scholar ] 171. Rahal D, Chiang JJ, Bower JE, Irwin MR, Venkatraman J, & Fuligni AJ (2020). Subjective social status and stress responsivity in late adolescence. Stress, 23(1), 50–59. 10.1080/10253890.2019.1626369 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 172. Demakakos P, Nazroo J, Breeze E, & Marmot M (2008). Socioeconomic status and health: The role of subjective social status. Social Science & Medicine, 67(2), 330–340. 10.1016/j.socscimed.2008.03.038 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 173. Zajacova A, & Lawrence EM (2024). The Relationship Between Education and Health: Reducing Disparities Through a Contextual Approach. Annual Review of Public Health, 39(1), 273–289. 10.1146/annurev-publhealth-031816-044628 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 174. Mawhorter S, Crimmins EM, & Ailshire JA (2023). Housing and cardiometabolic risk among older renters and homeowners. Housing Studies, 38(7), 1342–1364. 10.1080/02673037.2021.1941792 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 175. Song H, & Petracchi HE (2020). The effects of college savings on college enrollment and the mediating role of parental expectations and discussions about college among students from low-income households. Children and Youth Services Review, 108, 104553. 10.1016/j.childyouth.2019.104553 [ DOI ] [ Google Scholar ] 176. Castleman BL, & Page LC (2014). A Trickle or a Torrent? Understanding the Extent of Summer “Melt” Among College-Intending High School Graduates. Social Science Quarterly, 95(1), 202–220. 10.1111/ssqu.12032 [ DOI ] [ Google Scholar ] 177. Elliott III W. (2009). Children’s college aspirations and expectations: The potential role of children’s development accounts (CDAs). Children and Youth Services Review, 31(2), 274–283. [ Google Scholar ] 178. Wang X, & Squires G (2023). Intergenerational transfer, parental support and housing: A literature review. Property Management, ahead-of-print(ahead-of-print). 10.1108/PM-04-2023-0037 [ DOI ] [ Google Scholar ] 179. Öst CE (2012). Parental Wealth and First-time Homeownership: A Cohort Study of Family Background and Young Adults’ Housing Situation in Sweden. Urban Studies, 49(10), 2137–2152. 10.1177/0042098011427185 [ DOI ] [ Google Scholar ] 180. Bayrakdar S, Coulter R, Lersch P, & Vidal S (2019). Family formation, parental background and young adults’ first entry into homeownership in Britain and Germany. Housing Studies, 34(6), 974–996. 10.1080/02673037.2018.1509949 [ DOI ] [ Google Scholar ] 181. Mirdamadi M, & Khalid A (n.d.). Parents and children in the Canadian housing market: Does parental property ownership increase the likelihood of homeownership for their adult children? [ Google Scholar ] 182. McDade TW, Chyu L, Duncan GJ, Hoyt LT, Doane LD, & Adam EK (2011). Adolescents’ expectations for the future predict health behaviors in early adulthood. Social Science & Medicine, 73(3), 391–398. 10.1016/j.socscimed.2011.06.005 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 183. Whitehead R, Currie D, Inchley J, & Currie C (2015). Educational expectations and adolescent health behaviour: An evolutionary approach. International Journal of Public Health, 60(5), 599–608. 10.1007/s00038-015-0692-9 [ DOI ] [ PubMed ] [ Google Scholar ] 184. Bogg T, & Roberts BW (2004). Conscientiousness and health-related behaviors: A meta-analysis of the leading behavioral contributors to mortality. Psychological Bulletin, 130(6), 887. [ DOI ] [ PubMed ] [ Google Scholar ] 185. Trapmann S, Hell B, Hirn J-OW, & Schuler H (2007). Meta-analysis of the relationship between the Big Five and academic success at university. Zeitschrift Für Psychologie/Journal of Psychology, 215(2), 132–151. [ Google Scholar ] 186. Parents’ Roles in Shaping Early Adolescents’ Occupational Aspirations—Jodl—2001—Child Development—Wiley Online Library. (n.d.). Retrieved July 2, 2024, from https://srcd.onlinelibrary.wiley.com/doi/abs/10.1111/1467-8624.00345 [ DOI ] [ PubMed ] [ Google Scholar ] 187. Zhan M, & Sherraden M (2011). Assets and liabilities, educational expectations, and children’s college degree attainment. Children and Youth Services Review, 33(6), 846–854. 10.1016/j.childyouth.2010.12.006 [ DOI ] [ Google Scholar ] 188. Elliott W, & Beverly SG (2011). The role of savings and wealth in reducing ‘wilt’ between expectations and college attendance. Journal of Children and Poverty, 17(2), 165–185. 10.1080/10796126.2011.538375 [ DOI ] [ Google Scholar ] 189. Jez SJ (2014). The Differential Impact of Wealth Versus Income in the College-Going Process. Research in Higher Education, 55(7), 710–734. [ Google Scholar ] 190. Pfeffer FT (2018). Growing wealth gaps in education. Demography, 55(3), 1033–1068. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 191. Gaydosh L, Schorpp KM, Chen E, Miller GE, & Harris KM (2018). College completion predicts lower depression but higher metabolic syndrome among disadvantaged minorities in young adulthood. Proceedings of the National Academy of Sciences, 115(1), 109–114. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 192. Miller GE, Chen E, Yu T, & Brody GH (2020). Youth Who Achieve Upward Socioeconomic Mobility Display Lower Psychological Distress But Higher Metabolic Syndrome Rates as Adults: Prospective Evidence From Add Health and MIDUS. Journal of the American Heart Association, 9(9), e015698. 10.1161/JAHA.119.015698 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 193. Swisher RR, & Warner TD (2013). If They Grow up: Exploring the Neighborhood Context of Adolescent and Young Adult Survival Expectations. Journal of Research on Adolescence, 23(4), 678–694. 10.1111/jora.12027 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 194. Borowsky IW, Ireland M, & Resnick MD (2009). Health Status and Behavioral Outcomes for Youth Who Anticipate a High Likelihood of Early Death. Pediatrics, 124(1), e81–e88. 10.1542/peds.2008-3425 [ DOI ] [ PubMed ] [ Google Scholar ] 195. Nguyen QC, Villaveces A, Marshall SW, Hussey JM, Halpern CT, & Poole C (2012). Adolescent Expectations of Early Death Predict Adult Risk Behaviors. PLOS ONE, 7(8), e41905. 10.1371/journal.pone.0041905 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 196. de Bruijn E-J, & Antonides G (2022). Poverty and economic decision making: A review of scarcity theory. Theory and Decision, 92(1), 5–37. 10.1007/s11238-021-09802-7 [ DOI ] [ Google Scholar ] 197. Shah AK, Mullainathan S, & Shafir E (2012). Some Consequences of Having Too Little. Science, 338(6107), 682–685. 10.1126/science.1222426 [ DOI ] [ PubMed ] [ Google Scholar ] 198. Griskevicius V, Tybur JM, Delton AW, & Robertson TE (2011). The Influence of Mortality and Socioeconomic Status on Risk and Delayed Rewards: A Life History Theory Approach. Journal of Personality and Social Psychology, 100(6), 1015–1026. 10.1037/a0022403 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 199. Keough KA, Zimbardo PG, & Boyd JN (1999). Who’s Smoking, Drinking, and Using Drugs? Time Perspective as a Predictor of Substance Use. Basic and Applied Social Psychology, 21(2), 149–164. 10.1207/S15324834BA210207 [ DOI ] [ Google Scholar ] 200. Harris KM, Duncan GJ, & Boisjoly J (2002). Evaluating the Role of “Nothing to Lose” Attitudes on Risky Behavior in Adolescence*. Social Forces, 80(3), 1005–1039. 10.1353/sof.2002.0008 [ DOI ] [ Google Scholar ] 201. Chen J-H, Zheng H, Drake B, & Jonson-Reid M (2023). Explaining adolescent problematic behavior: An application of the family stress model and the Family Investment Model. Journal of Child and Family Studies, 1–12. [ Google Scholar ] 202. Diemer MA, Marchand AD, & Mistry RS (2020). Charting How Wealth Shapes Educational Pathways from Childhood to Early Adulthood: A Developmental Process Model. Journal of Youth and Adolescence, 49(5), 1073–1091. 10.1007/s10964-019-01162-4 [ DOI ] [ PubMed ] [ Google Scholar ] 203. Simons LG, & Steele ME (2020). The Negative Impact of Economic Hardship on Adolescent Academic Engagement: An Examination Parental Investment and Family Stress Processes. Journal of Youth and Adolescence, 49(5), 973–990. 10.1007/s10964-020-01210-4 [ DOI ] [ PubMed ] [ Google Scholar ] 204. Sisk LM, & Gee DG (2022). Stress and adolescence: Vulnerability and opportunity during a sensitive window of development. Current Opinion in Psychology, 44, 286–292. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 205. Adler NE, Boyce T, Chesney MA, Cohen S, Folkman S, Kahn RL, & Syme SL (1994). Socioeconomic status and health: The challenge of the gradient. American Psychologist, 49(1), 15–24. 10.1037/0003-066X.49.1.15 [ DOI ] [ PubMed ] [ Google Scholar ] 206. Goodman E (1999). The role of socioeconomic status gradients in explaining differences in US adolescents’ health. American Journal of Public Health, 89(10), 1522–1528. 10.2105/AJPH.89.10.1522 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 207. Chetty R, Stepner M, Abraham S, Lin S, Scuderi B, Turner N, Bergeron A, & Cutler D (2016). The association between income and life expectancy in the United States, 2001-2014. Jama, 315(16), 1750–1766. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 208. Agliata AK, & Renk K (2008). College Students’ Adjustment: The Role of Parent–College Student Expectation Discrepancies and Communication Reciprocity. Journal of Youth and Adolescence, 37(8), 967–982. 10.1007/s10964-007-9200-8 [ DOI ] [ Google Scholar ] 209. Mcgee R, & Williams S (2000). Does low self-esteem predict health compromising behaviours among adolescents? Journal of Adolescence, 23(5), 569–582. 10.1006/jado.2000.0344 [ DOI ] [ PubMed ] [ Google Scholar ] 210. Simons LG, Wickrama K. a. S., Lee TK, Landers-Potts M, Cutrona C, & Conger RD (2016). Testing Family Stress and Family Investment Explanations for Conduct Problems Among African American Adolescents. Journal of Marriage and Family, 78(2), 498–515. 10.1111/jomf.12278 [ DOI ] [ Google Scholar ] 211. Hartley DA, & Rose J (2023). Blockbusting and the challenges faced by Black families in building wealth through housing in the postwar United States. Federal Reserve Bank of Chicago. 10.21033/wp-2023-02 [ DOI ] [ Google Scholar ] 212. Lynch EE, Malcoe LH, Laurent SE, Richardson J, Mitchell BC, & Meier HC (2021). The legacy of structural racism: Associations between historic redlining, current mortgage lending, and health. SSM-Population Health, 14, 100793. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 213. Mijid N, & Bernasek A (2013). Decomposing Racial and Ethnic Differences in Small Business Lending: Evidence of Discrimination. Review of Social Economy, 71(4), 443–473. 10.1080/00346764.2012.761751 [ DOI ] [ Google Scholar ] 214. Quillian L, & Midtbøen AH (2021). Comparative Perspectives on Racial Discrimination in Hiring: The Rise of Field Experiments. Annual Review of Sociology, 47(1), 391–415. 10.1146/annurev-soc-090420-035144 [ DOI ] [ Google Scholar ] 215. Barber PH, Hayes TB, Johnson TL, Márquez-Magaña L, & 10, 234 signatories. (2020). Systemic racism in higher education. Science, 369(6510), 1440–1441. [ DOI ] [ PubMed ] [ Google Scholar ] 216. Charron-Chénier R. (2020). Predatory Inclusion in Consumer Credit: Explaining Black and White Disparities in Payday Loan Use. Sociological Forum, 35(2), 370–392. 10.1111/socf.12586 [ DOI ] [ Google Scholar ] 217. Gallmeyer A, & Roberts WT (2009). Payday lenders and economically distressed communities: A spatial analysis of financial predation. The Social Science Journal, 46(3), 521–538. 10.1016/j.soscij.2009.02.008 [ DOI ] [ Google Scholar ] 218. Katz SF, Rodriguez F, & Knowles JW (2021). Health disparities in cardiometabolic risk among Black and Hispanic youth in the United States. American Journal of Preventive Cardiology, 6, 100175. 10.1016/j.ajpc.2021.100175 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 219. Hanevold CD (2023). Racial-ethnic disparities in childhood hypertension. Pediatric Nephrology, 38(3), 619–623. 10.1007/s00467-022-05707-x [ DOI ] [ PubMed ] [ Google Scholar ] 220. Haynes A, Kalic R, Cooper M, Hewitt JK, & Davis EA (2016). Increasing incidence of type 2 diabetes in Indigenous and non-Indigenous children in Western Australia, 1990–2012. Medical Journal of Australia, 204(8), 303–303. 10.5694/mja15.00958 [ DOI ] [ PubMed ] [ Google Scholar ] 221. Ehtisham S, Crabtree N, Clark P, Shaw N, & Barrett T (2005). Ethnic Differences in Insulin Resistance and Body Composition in United Kingdom Adolescents. The Journal of Clinical Endocrinology & Metabolism, 90(7), 3963–3969. 10.1210/jc.2004-2001 [ DOI ] [ PubMed ] [ Google Scholar ] 222. Schaefer SE, Salazar M, Bruhn C, Saviano D, Boushey C, & Van Loan MD (2009). Influence of Race, Acculturation, and Socioeconomic Status on Tendency Toward Overweight in Asian-American and Mexican-American Early Adolescent Females. Journal of Immigrant and Minority Health, 11(3), 188–197. 10.1007/s10903-008-9150-6 [ DOI ] [ PubMed ] [ Google Scholar ] 223. Unger JB, Reynolds K, Shakib S, Spruijt-Metz D, Sun P, & Johnson CA (2004). Acculturation, Physical Activity, and Fast-Food Consumption Among Asian-American and Hispanic Adolescents. Journal of Community Health, 29(6), 467–481. 10.1007/s10900-004-3395-3 [ DOI ] [ PubMed ] [ Google Scholar ] 224. Popkin BM, & Udry JR (1998). Adolescent Obesity Increases Significantly in Second and Third Generation U.S. Immigrants: The National Longitudinal Study of Adolescent Health1,2. The Journal of Nutrition, 128(4), 701–706. 10.1093/jn/128.4.701 [ DOI ] [ PubMed ] [ Google Scholar ] 225. Barnett RC, Davidson H, & Marshall NL (1991). Physical symptoms and the interplay of work and family roles. Health Psychology : Official Journal of the Division of Health Psychology, American Psychological Association, 10(2), 94–101. 10.1037/0278-6133.10.2.94 [ DOI ] [ PubMed ] [ Google Scholar ] 226. Perreira KM, & Ornelas IJ (2011). The Physical and Psychological Well-Being of Immigrant Children. The Future of Children, 21(1), 195–218. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 227. Farmer MM, & Ferraro KF (2005). Are racial disparities in health conditional on socioeconomic status? Social Science & Medicine, 60(1), 191–204. 10.1016/j.socscimed.2004.04.026 [ DOI ] [ PubMed ] [ Google Scholar ] 228. Henry DA, Votruba-Drzal E, & Miller P (2019). Chapter One - Child development at the intersection of race and SES: An overview. In Henry DA, Votruba-Drzal E, & Miller P (Eds.), Advances in Child Development and Behavior (Vol. 57, pp. 1–25). JAI. 10.1016/bs.acdb.2019.05.002 [ DOI ] [ PubMed ] [ Google Scholar ] 229. De Freitas DF, Fernandes-Jesus M, Ferreira PD, Coimbra S, Teixeira PM, De Moura A, Gato J, Marques SC, & Fontaine AM (2018). Psychological correlates of perceived ethnic discrimination in Europe: A meta-analysis. Psychology of Violence, 8(6), 712–725. 10.1037/vio0000215 [ DOI ] [ Google Scholar ] 230. Assari S. (2020). Family Socioeconomic Status and Exposure to Childhood Trauma: Racial Differences. Children, 7(6), Article 6. 10.3390/children7060057 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 231. Assari S, Cobb S, Saqib M, & Bazargan M (2020). Diminished returns of educational attainment on heart disease among Black Americans. The Open Cardiovascular Medicine Journal, 14, 5. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 232. Assari S. (2017). Unequal Gain of Equal Resources across Racial Groups. International Journal of Health Policy and Management, 7(1), 1–9. 10.15171/ijhpm.2017.90 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 233. Assari S, Boyce S, Bazargan M, Mincy R, & Caldwell CH (2019). Unequal Protective Effects of Parental Educational Attainment on the Body Mass Index of Black and White Youth. International Journal of Environmental Research and Public Health, 16(19), Article 19. 10.3390/ijerph16193641 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 234. Assari S, Najand B, & Sheikhattari P (2024). Household income and subsequent youth tobacco initiation: Minorities’ Diminished Returns. Journal of Medicine, Surgery, and Public Health, 2, 100063. 10.1016/j.glmedi.2024.100063 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 235. Assari S, & Moghani Lankarani M (2018). Poverty Status and Childhood Asthma in White and Black Families: National Survey of Children’s Health. Healthcare, 6(2), Article 2. 10.3390/healthcare6020062 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 236. Borraccino A, Berchialla P, Dalmasso P, Sciannameo V, Vieno A, Lazzeri G, Charrier L, & Lemma P (2020). Connectedness as a protective factor in immigrant youth: Results from the Health Behaviours in School-aged Children (HBSC) Italian study. International Journal of Public Health, 65(3), 303–312. 10.1007/s00038-020-01355-w [ DOI ] [ PubMed ] [ Google Scholar ] 237. Llabre MM (2021). Insight Into the Hispanic Paradox: The Language Hypothesis. Perspectives on Psychological Science, 16(6), 1324–1336. 10.1177/1745691620968765 [ DOI ] [ PubMed ] [ Google Scholar ] ACTIONS View on publisher site PDF (683.9 KB) Cite Collections Permalink RESOURCES Similar articles Cited by other articles Links to NCBI Databases Follow NCBI NCBI on X (formerly known as Twitter) NCBI on Facebook NCBI on LinkedIn NCBI on GitHub NCBI RSS feed Connect with NLM NLM on X (formerly known as Twitter) NLM on Facebook NLM on YouTube National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894 Web Policies FOIA HHS Vulnerability Disclosure Help Accessibility Careers NLM NIH HHS USA.gov Back to Top

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