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. Author manuscript; available in PMC: 2013 Jun 19.
Published in final edited form as: Clin Child Fam Psychol Rev. 2011 Jun;14(2):111–134. doi: 10.1007/s10567-011-0095-2

Creating Nurturing Environments: A Science-Based Framework for Promoting Child Health and Development within High-Poverty Neighborhoods

Kelli A Komro 1, Brian R Flay 2, Anthony Biglan 3; the Promise Neighborhoods Research Consortium4
PMCID: PMC3686471  NIHMSID: NIHMS469414  PMID: 21468644

Abstract

Living in poverty and living in areas of concentrated poverty pose multiple risks for child development and for overall health and wellbeing. Poverty is a major risk factor for several mental, emotional, and behavioral disorders, as well as for other developmental challenges and physical health problems. In this paper, the Promise Neighborhoods Research Consortium describes a science-based framework for the promotion of child health and development within distressed high-poverty neighborhoods. We lay out a model of child and adolescent developmental outcomes, and integrate knowledge of potent and malleable influences to define a comprehensive intervention framework to bring about a significant increase in the proportion of young people in high-poverty neighborhoods who will develop successfully. Based on a synthesis of research from diverse fields, we designed the Creating Nurturing Environments framework to guide community-wide efforts to improve child outcomes and reduce health and educational inequalities.

Keywords: child, adolescent, health, wellbeing, poverty, framework


Unemployment (U.S. Department of Labor, 2010), social inequalities (Braveman & Egerter, 2008), health disparities (Dow, Schoeni, Adler, & Stewart, 2010; National Center for Health Statistics, 2010), and rates of children living in poverty (from 19 to 21% between 2008 and 2009; DeNavas-Walt, Proctor, & Smith, 2009) are on the rise. Local, state, and federal governments are struggling with budget deficits (National Conference of State Legislatures, 2009), resulting in cuts to educational and social programs (Johnson, Oliff, & Williams, 2010). For example, communities around the country are (a) facing major cuts to K-12 education (eSchool News, April 9, 2010), (b) reducing summer educational opportunities (eSchool News), (c) closing parks and recreational facilities (Sichko, 2010; Young, 2009), and (d) reducing police personnel (Jackman, 2010; Muro & Hoene, 2009). At the same time, the scientific community has generated a significant amount of research demonstrating effective ways of preventing costly child mental, emotional, behavioral, and academic problems using cost-effective interventions that can be accessible to entire communities (National Research Council [NRC] & Institute of Medicine [IOM], 2009). Current economic and social conditions make this a critical time for the scientific community to work closely with policymakers and local communities to support implementation of effective, science-based, and efficient strategies to promote child health and development.

The absolute rate of poverty, particularly the rate of poverty among children, is higher in the U.S. than in other industrialized nations (Smeeding, Rainwater, & Burtless, 2001; Valletta, 2004). Rank, Yoon, and Hirschl (2003) have argued that this is a “structural failing” of the U.S., including a lack of sufficient jobs and the ineffectiveness of the social safety net. The overall poverty rate in the U.S. in 2009 was 14.3%; however, it was higher among female-headed households (29.9%), African Americans (25.8%), Hispanics (25.3%), children (20.7%), and those living in central cities (18.7%; DeNavas-Walt et al., 2009).

Living in poverty and living in areas of concentrated poverty pose multiple risks for child development and for overall health and wellbeing. Poverty is a major risk factor for several mental, emotional, and behavioral disorders, as well as other developmental challenges and physical health problems (NRC & IOM, 2009). High-poverty neighborhoods have substantially higher levels of depression (Cutrona, Wallace, & Wesner, 2006), obesity (Burdette & Hill, 2008), infant mortality, low birth weight, teenage childbearing, dropping out of school, child maltreatment, adolescent delinquency, injuries, homicide, suicide (Sampson, Morenoff, & Gannon-Rowley, 2002), and overall self-reported health problems (Do et al., 2008). In addition to the deleterious effects of concentrated poverty, higher levels of income inequality are associated with an increased risk for a wide range of negative health outcomes among infants, children, adolescents, and adults (Pickett & Wilkinson, 2008; Wilkinson & Pickett, 2009). Stratification of neighborhoods and schools by economic status also indicates a correlation with negative outcomes. Children attending schools with higher proportions of students from low-income families have lower educational performance and achievement, regardless of their own current poverty status (Aikens & Barbarin, 2008; Shumow, Vandell, & Posner, 1999), increasing the risk of poverty in adulthood (Rank & Hirschl, 2001).

Earning a high school diploma is key to success in many areas of life, including being able to continue education, increasing one’s chance for a good job and earnings, and maintaining overall health and wellbeing (Egerter, Braveman, Sadegh-Nobari, Grossman-Kahn, & Dekker, 2009). Better-educated people are more likely to be healthy and to live longer; and, if they have children, their children are healthier (Egerter et al., 2009). The interrelatedness of educational achievement and social, psychological, behavioral, and physical health and wellbeing points to the need for comprehensive efforts to prevent the many and varied deleterious consequences of poverty. Given the multitude of risks and limited opportunities to which they are exposed, children growing up in persistent poverty and within areas of concentrated poverty have considerable disadvantages in breaking out of the cycle of poverty (Ratcliffe & McKernan, 2010; Sampson, 2009; Silver, Mijanovich, Uyel, Kapadia, & Weitzman, 2011).

Advances in social and behavioral science over the past two decades have led to substantial progress in developing effective preventive and health-promoting interventions. The recent NRC and IOM report (2009) summarizes progress to date. The evidence summarized highlights the need for population-level, multicomponent, multilevel (e.g., family and community-wide strategies), and multiyear approaches to prevention and health promotion. The report also highlights the need to advance implementation science and the dissemination of evidence-based strategies into community practice. The report, as well as the President’s education and poverty reduction initiatives, inspired our thinking and motivated us to create a framework for action. The purpose of this paper is to present 1) a science-based framework that defines a key set of child and adolescent developmental outcomes and 2) a comprehensive intervention template to increase nurturing environments that could affect those key outcomes. The ultimate goal is to use the framework as a guide to promote effective and lasting improvements in social and physical environments that result in optimal child outcomes and break the cycle of intergenerational poverty.

Promise Neighborhoods and the Harlem Children’s Zone

President Obama proposed an ambitious effort, the Promise Neighborhoods Initiative, to address intergenerational poverty and to promote child educational and health outcomes. Its model is the Harlem Children’s Zone, a highly commendable effort to implement a continuum of school and community strategies to promote child success within distressed neighborhoods (Tough, 2008).

The Harlem Children’s Zone, Inc., is a non-profit, community-based organization that works to enhance the quality of life for children and families by providing support and services within a defined neighborhood in central Harlem. Harlem is a predominately African American neighborhood within New York City with a long history of marginalization, economic deprivation, high unemployment rates, high crime rates, high infant mortality rates, and short life expectancies. Since the 1990s, the introduction of the Upper Manhattan Empowerment Zone, which brought in millions of dollars in development funds and tax incentives, has helped to support a level of economic redevelopment. The Harlem Children’s Zone (HCZ), led by Geoffrey Canada, began as a 1-block pilot in 1990 and has expanded to serve children and families within 100 blocks in Harlem (Tough, 2008). HCZ’s ambitious goals are to end multigenerational poverty and to help each child succeed. Its core principals include creating a neighborhood-based, scalable approach to build community; providing a pipeline of support for children and families from before birth through young adulthood; creating a culture of success; and relying on continuous assessment of outcomes to modify strategies as needed (www.hcz.org).

The HCZ developed and implemented a network of programs and strategies, including 1) parenting classes for expectant and new parents, 2) a pre-kindergarten program, 3) charter schools, 4) afterschool programs, 5) an office to help students apply for and make the transition into college, 6) an employment and technology center, and 7) organization of tenant and block associations (Dobbie & Fryer, 2009; Tough, 2008). Charter schools were a main component of their efforts and included a variety of strategies to help children succeed, including 1) hiring and maintaining only high-quality teachers who obtained measurable academic success with their students measured with standardized test scores; 2) teacher and student incentives (e.g., money, trips); 3) social workers; 4) extended school days and years, plus afterschool tutoring; 5) medical services within the school; and 6) a nutritious food program (Dobbie & Fryer, 2009). Dobbie and Fryer published their evaluation of the HCZ charter schools, taking advantage of the fact that HCZ students gained entry into the charter schools through a lottery drawing. They therefore compared children who were interested in attending the HCZ schools, “won” the lottery, and attended the schools to those who lost the lottery and did not attend the schools. Among elementary school students, third graders (the first year that children in New York take standardized exams) showed significantly higher achievement in math and English Language Arts and students in the middle school had significantly higher achievement in math (Dobbie & Fryer, 2009). From their analysis of the results, within the context of the extant literature, Dobbie and Fryer concluded that the unique blend of school strategies and policies implemented in the HCZ charter schools could bring about the results from the HCZ initiatives. The effects of the community-based efforts were less clear given the lack of a rigorous research and evaluation design (Dobbie & Fryer, 2009). In an attempt to tease apart the effects of the HCZ school and community initiatives, Whitehurst and Croft (2010) compared test scores from the HCZ Promise Academy to other public charter schools in New York City that did not include wider community services and supports. From their analysis, in which they controlled for sociodemographic factors, they found that half or more of the public charter schools in Manhattan and the Bronx produced test scores on state assessments that were superior to those produced by the HCZ Promise Academy. They concluded that the community-based initiatives of the HCZ did not seem to increase achievement outcomes above school-based initiatives alone. However, their analysis did not consider other important outcomes, such as psychological, behavioral and health outcomes critical to a child's development and success.

The Obama administration’s Promise Neighborhoods initiative seeks to encourage efforts similar to the HCZ to make significant improvements in educational and developmental outcomes of children living in the most distressed communities. The U.S. Department of Education funded 21 neighborhoods for one-year planning grants that began in October 2010. Its goal is to release additional RFAs within a year to support implementation grants and additional planning grants. President Obama included $150 million in his FY 2012 budget proposal.

Promise Neighborhoods Research Consortium

Without significant involvement of the scientific community, efforts such as the Promise Neighborhoods will likely fall short of expectation. The HCZ, funded Promise Neighborhoods, and other communities working to improve the outcomes of children living within distressed neighborhoods will benefit from assistance in framing, selecting, and implementing evidence-based and efficient strategies. Without careful research and monitoring of outcomes, it will not be possible to determine if these efforts are working to achieve desired ends. Dissemination research will help to define barriers and solutions to widespread implementation of evidence-based strategies within community-based settings (Schoenwald, Kelleher, &Weisz, 2008; Weisz, Hawley, Pilkonis, Woody & Follette, 2000). Conducting dissemination research will also help to refine activities so they become increasingly effective and efficient over time.

Further progress to improve child outcomes requires a new framework to organize the scientific evidence, define the most important substantive priorities, and articulate the empirical methods needed to use existing knowledge to help achieve widespread benefit in the population. We created the PNRC for this purpose. The National Institute on Drug Abuse funded the PNRC in September 2009, under the American Recovery and Reinvestment Act (ARRA). The PNRC is a network of more than 30 nationally known researchers from a wide array of disciplines and fields, including behavioral and social sciences, education, epidemiology, evolutionary science, health behavior, human development, information technology, neuroscience, policy research, poverty research, prevention science, psychiatry, psychology, and public health. We have organized existing evidence and defined strategies for assisting high-poverty neighborhoods in improving development, health, and wellbeing among children and adolescents. We continue to monitor the scientific literature for the latest relevant research findings, and we are articulating methodological principles needed for integrating current knowledge into practice to ensure meaningful improvement in the lives of people living in high-poverty neighborhoods (Biglan et al., 2010; Flay et al., under review). We suggest a combination of design options to enhance causal inference and to allow for continuous quality improvement of complex multi-component interventions. We conclude that a standardized measurement system is also fundamental to the evaluation of complex multi-component interventions.

The PNRC consists of four workgroups: 1) networking, to link and develop relationships between scientists and high-poverty neighborhoods; 2) technology, to develop and maintain an interactive website (promiseneighborhoods.org) for information dissemination, data collection, and networking; 3) measurement, to develop comprehensive yet feasible data collection tools and strategies for neighborhoods; and 4) intervention, to provide a foundation for choosing, integrating, and implementing evidence-based strategies. The intervention workgroup has five teams: policies, programs, kernels (simple, evidence-based, behavior-influenced practices), and education intervention, plus a research team to advance science within high-poverty neighborhoods. Each workgroup and team includes senior and early career scientists and at least one neighborhood representative. In this paper, the PNRC provides an initial statement of a science-based framework for the promotion of child health and development within distressed, high-poverty neighborhoods. It lays out a model of optimal child and adolescent developmental outcomes and defines a comprehensive intervention framework to bring about a significant increase in the proportion of young people in high-poverty neighborhoods who will develop successfully.

Promise Neighborhoods Research Consortium’s Framework: “Creating Nurturing Environments”

We created a developmentally informed, science-based framework to guide comprehensive efforts to promote health and wellbeing among children living within high-poverty neighborhoods. The framework specifies developmental outcomes that are vital to health and successful development. For each stage of development—from the prenatal phase through infancy (age 2), early childhood (ages 3–5), childhood (ages 6–11), early adolescence (ages 12–14), and adolescence (15–19)—we defined a set of key measurable outcomes that provide the foundation for success in later development. Secondly, guided by the ecological systems theory of human development (Bronfenbrenner, 1979, 1981), a comprehensive theory of health behaviors (Flay & Petraitis, 1994; Flay, Snyder, & Petraitis, 2009), our collective expertise, and a thorough review of the literature within each domain of our model, we identified and categorized malleable influences that most affect key outcomes at each phase of development. Finally, within this framework, we identified evidence-based programs, curricula, policies, and practices shown to benefit families, schools, and neighborhoods to improve these influences on child outcomes specific to each developmental phase. This section describes the outcomes and influences within the framework. The following section describes how to use the framework within distressed neighborhoods to promote optimal child development, health, and wellbeing.

Figure 1 illustrates the overall framework, entitled Creating Nurturing Environments. This figure is a summary of key outcomes and influences that apply across developmental phases. However, we elaborate and provide further specification of these outcomes for each developmental phase, and provide measures of outcomes and influences at each phase. This detailed information is on our website, promiseneighborhoods.org. We define nurturing and environments broadly (Biglan, Flay, & Embry, under review). By nurturing, we mean any act, process, or condition that promotes and supports optimal developmental outcomes within a given environmental context. We define environments to include the social, economic, and physical conditions of a neighborhood or community. We intend the framework to be comprehensive and inclusive to guide the creation of social, economic, and physical conditions within communities that will promote and support optimal educational, social, behavioral, and physical health outcomes among youth. Our goal was to create a comprehensive and science-based framework while keeping it parsimonious, comprehensible, and usable. Although we understand the interrelatedness, interaction, and feedback loops within and between influences and multiple outcomes (Bronfenbrenner, 1979, 1981; Flay & Petraitis, 1994; Flay et al., 2009), for simplicity, we present the model with one-directional arrows only.

Figure 1.

Figure 1

A Framework for Creating Nurturing Environments

We defined key outcomes at each stage of development in terms of four central domains: cognitive development, social-emotional competence, the absence of psychological and behavioral problems, and physical health. These four categorical domains highlight the diversity of outcomes requiring monitoring and promotion from birth through late adolescence (NRC, IOM, & the Committee on Evaluation of Children's Health, 2004). The four domains are interrelated (NRC et al., 2004) and the most favorable outcomes within each domain are necessary for optimal development, health, and wellbeing throughout the lifecourse (Commission on Social Determinants of Health, 2008). Table 1 includes a summary of key constructs in each outcome domain by developmental phase.

Table 1.

Key outcomes by developmental phase

Outcome Domain
Developmental
phase
Cognitive Development Social & Emotional
Competence
Absence of Psychological
and Behavioral Problems
Physical Health

Prenatal- infancy (birth to age 2) language development; executive functioning social and emotional development; attachment self awareness develops; behavioral development birth weight; physical and motor skill development; injuries
Early childhood (3–5) language and early literacy development (e.g., picture naming, rhyming, letter naming); executive functioning self-regulation; emotional symptoms; social relations; prosocial behavior, skills, attitudes self-concept develops; behavioral development; attentional and hyperactivity difficulties; conduct problems physical development; injuries; asthma-like illness; diet; physical activity; height/weight percentiles; oral health
Childhood (6–11) reading proficiency; mathematics proficiency (at or above grade level); executive functioning Same as above, plus: gradual shift in control from parents to child; peers assume a more central role Same as above, plus: self- concept becomes more complex; disruptive and aggressive behavior; depressive symptoms Same as above, plus: strength and athletic skills improve

Early adolescence (12–14) Same as above, plus intellectual development, abstract thinking Same as above, plus: central role of peer group, identity formation Same as above, plus: violent behaviors; drug use; risky sexual behaviors Same as above, plus: more rapid physical growth and changes; puberty and reproductive maturity; self- inflicted injuries; type 2 diabetes; STDs; any pregnancy
Adolescence (15–19) Executive functioning; intellectual development; critical and rational thinking; high school graduation Same as above, plus: moral development; intimacy development Same as above injuries; self-inflicted injuries; diet; physical activity; BMI; type 2 diabetes; STDs; unplanned pregnancy, repeat pregnancy

Key Developmental Outcomes

Cognitive development

The broad definition of cognitive development is having age-appropriate language and numeracy skills, as well as basic cognitive skills and executive functioning. Acquiring a full, rich vocabulary is vital to young people’s language skills and successful development. Children with extensive vocabularies learn to read more easily and become better readers (Nation, 2009). Thus, language is a vital precursor for a child’s cognitive and social development (Cohen & Mendez, 2009). In fact, emergence of executive cognitive functions relies heavily upon language-processing abilities, a complex mediated process that allows for self-regulation, organization, and guidance of social behavior, future orientation, and abstraction. Executive functions are higher-order cognitive skills that develop throughout childhood and well into early adulthood (DeLuca et al., 2003). Examples of executive functions include working memory, attention, impulse control, goal-directed behavior, decision-making, problem solving, and sensitivity to consequences. Executive functions also operate to regulate emotional responses to the environment by interpreting social cues during interpersonal interactions, coping with stress situations, executing appropriate social responses, and inhibiting inappropriate emotional reactions (Giedd, 2004). Numeracy skills (including the ability to manipulate numbers) contribute to young people’s success throughout development. Adults who lack significant numeracy skills have poorer health, financial, and employment outcomes (Dieckmann, 2008; Parsons & Bynner, 1997). Numeracy skills begin with the ability to count and perform simple arithmetic. Children who have developed these skills appropriate for their age group are more likely to grasp and do well in elementary school arithmetic (Welsh, Nix, Blair, Bierman, & Nelson, 2010). Reading and mathematics proficiency and progression through school to high school graduation are readily available indicators of successful cognitive development.

Social and emotional competence

This refers to a person’s ability to engage effectively in social interactions (with peers and adults), to perceive and interpret social cues accurately, and to regulate emotional responses (Denham et al., 2003). Of particular relevance to the PNRC model, abilities that fall within this domain manifest as self-regulation and prosocial behaviors, skills, and attitudes. Age-appropriate social and emotional regulatory functions underlie many aspects of child development (Bronson, 2000; Buckner, Mezzacappa, & Beardslee, 2009; NRC & IOM, 2000; Posner & Rothbart 2000). Self-regulation increases over time, allowing children to develop situational awareness and, in effect, to inhibit disadvantageous impulses, become aware of their emotions, and apply the requisite cognitive skills to exert effortful control over behavior in emotional situations, delay gratification, consider consequences, and identify a course of action that would benefit them and those around them. Children who do not fully develop this ability often exhibit aggression, anxiety, depression, frustration, anger, and other negative behaviors and moods (Denham et al., 2003). Very young children experience emotions and react to them long before they can verbalize their experiences or understand their own emotions. Learning to regulate these emotional experiences to support prosocial interactions is a primary developmental goal (Bronson, 2000; Kochanska, Murray, & Harlan, 2000; NRC & IOM, 2000). Self-regulatory abilities are more likely to develop fully within supportive environments (NRC & IOM, 2000). A nurturing environment and interventions designed to foster cognitive and emotional development have the potential to enhance self-regulation and, in effect, reduce maladjustment (Domitrovich, Cortes, & Greenberg, 2007).

Prosociality is a matter of wanting to help others, to contribute to one’s community, and to have respectful and caring relationships with others. Even in a hostile or dangerous environment, children who maintain a positive attitude toward social relationships with peers, adults, parents, and others are more resilient and able to cope with challenges (Wilson, O'Brien, & Sesma, 2009). Young people with a prosocial orientation have significantly fewer psychological and behavioral problems, do better in school, and contribute more to those around them (Hankins & Biglan, in preparation; Wilson & Csikszentmihalyi, 2007; Wilson et al., 2009). However, there is also evidence that prosocial young people experience more distress in stressful situations (Wilson & Csikszentmihalyi, 2007), presumably because they are not accustomed to coping with such situations.

Absence of psychological and behavioral problems

Very young children can manifest early predictors of future mental and behavioral disorders. For example, most two- and three-year-olds are distractible, but there is both a qualitative and a quantitative difference with how some children show rather extreme hyperactivity, opposition, or defiance (Willcutt, Doyle, Nigg, Faraone, & Pennington, 2005). Young children with speech-language impairments that persist into school-age years are at risk for psychological problems (Conti-Ramsden, & Botting, 2008; Snowling, Bishop, Stothard, Chipchase, & Kaplan, 2006). Early signs of aggression and problem behaviors present a risk factor for more severe mental and behavioral problems before and during adolescence (Loeber, 1982; World Health Organization, 2002). Three especially vital problems to monitor and prevent during childhood are 1) aggressive behavior with other children, 2) uncooperative behavior with teachers and adults, and 3) elevated levels of depressive symptoms (Bradshaw, Schaeffer, Petras, & Ialongo, 2010; Odgers et al., 2008). Children who behave aggressively with other children are more likely to have problems making friends and more likely to have serious behavior problems, including criminal activity, as adolescents and adults (Farrington, 2001).

Important psychological and behavioral problems to monitor during adolescence include 1) alcohol, tobacco, and other drug use, 2) violent and delinquent behaviors, 3) depression and suicide ideation, and 4) risky sexual behaviors (Centers for Disease Control and Prevention [CDCP], 2008). These behaviors put youth at risk for deleterious outcomes during adolescence and into adulthood (CDCP, 2008).

Physical health

Physical health includes health conditions, functioning, and health potential (NRC et al., 2004). Health potential is a child’s risk state and capacity to respond to challenges. Children in good physical health are in a better position to acquire knowledge (Council of Chief State School Officers, 1991). Health outcomes, problem behaviors, and competency indicators are interrelated (Kim, Guerra, & Williams, 2008). Through immunizations, we have made great progress in preventing serious health conditions among youth due to infectious diseases (CDCP, 1999). Yet young people living in poverty still suffer disproportionately from preventable health conditions, such as asthma, type 2 diabetes, dental morbidity, and injuries (Environmental Protection Agency [EPA], 2009; Heron, 2007; National Institutes of Health, 2008).

Childhood and adolescence should be times of great physical health and functioning, yet numbers of young people face poor health, with the rates of asthma and type 2 diabetes increasing (Akinbami, 2006; Nadeau & Dabelea, 2008). Both low-income and ethnic minority youth have increased risk for asthma and type 2 diabetes (EPA, 2009; NIH, 2008). Most reports of health disparities by race/ethnicity do not tease apart effects of poverty and lack of resources or biological differences across different ethnic backgrounds (Barr, 2008). What we do know is that toxins in the environment (pollution, high ozone levels, secondhand smoke, dust mites, molds, cockroaches, and pet dander) cause asthma attacks, these are preventable risk factors, and young people living in poverty are at increased risk from them (EPA, 2009). The major risk factor for developing type 2 diabetes is obesity (NIH, 2008), with poor diet and limited exercise causing an increase in youth obesity (Eyre, Kahn, Robertson, & ACS/ADA/AHA Collaborative Writing Committee, 2004).

Injuries are the leading cause of death during the first several decades of life (Heron, 2007). Major advances in the prevention of injuries have occurred with child safety seats and seat belt use (Du et al., 2010; Vick, 2010), yet the burden of injury remains high and requires continuing preventive efforts. African American youth, especially those living within distressed cities, have higher mortality rates due to homicide and unintentional injuries (excluding those related to motor vehicle crashes; Silver et al., 2011). Precocious and risky sexual activity puts youth at risk for sexually transmitted disease and early pregnancy. Significant racial disparities appear in the rates of STD and HIV prevalence (Hallfors, Iritani, Miller, & Bauer, 2007). Compared to their prevalence among Whites, HIV infections are seven times more common among African Americans and three times more common among Hispanics (Hall et al., 2008). Importantly, 80–90% of adolescent HIV infections result from sexual activities (CDC, 2008). In addition, adolescents who live in high-poverty neighborhoods are at increased risk for early pregnancy (Harding, 2003).

Summary

Our first step in creating a framework to promote optimal outcomes was to define key outcomes across developmental phases. At each phase of development and across developmental phases, outcomes are interconnected and have a similar set of causes. Outcomes within the cognitive, social/emotional, psychological/behavioral, and physical health domains often correlate at one point in time, and influence subsequent developmental outcomes within and across domains. In the next section, we outline six domains of malleable influences on these child and adolescent outcomes. We conceptualized three of the six chief domains as proximal (immediate) influences (including family, school, and peers) and three as distal (background) influences (those important conditions in a child’s neighborhood, including income and resources, social cohesion, and the physical environment). We define proximal or immediate influences as those within the immediate social environment, which have direct influences on outcomes. We define distal or background influences as predisposing factors, with effects fully or partially mediated through the proximal influences (Flay et al., 2009; Flay & Petraitis, 1994).

Proximal Influences

Family influences

Parents influence the lives of children in many ways, by creating the home environment, establishing parenting practices, modeling behaviors, and communicating values and norms. The ways in which parents interact with, and provide role models for, their children have a significant effect on children’s overall development and health.

Involvement in learning-related activities

Parents are key teachers for their children beginning while the children are still infants. Receiving stimulation and interaction during infancy and early childhood is vital to successful development (Barros, Matijasevich, Santos, & Halpern, 2009; Bonnier, 2008; Mustard, 2006). Cognitive, social-emotional, and physical development is essential for healthy development during the early years, which provide essential building blocks for success throughout childhood and into adulthood (Irwin, Siddiqi, & Hertzman, 2007). Young children develop best in warm, responsive environments with opportunities to explore, play, and learn how to speak and listen (Irwin et al., 2007). Family members provide most environmental stimuli for young children, so they are key to development (Irwin et al., 2007). As children enter the school system, they have better academic outcomes when their parents become involved in learning-related activities (such as homework), join parent organizations at school, and partake in extracurricular activities (Rutter & Maughan, 2002; Slavin, 1984, 1994; Spera, 2005). Parents can also encourage learning-related activities by communicating their goals and aspirations for their children along with their own values about education and achievement (Spera, 2005).

Involved monitoring

This is an important component of effective parenting. Monitoring means staying engaged with children in ways that enable the parents to know what the children are doing and to guide their behavior. It includes environmental strategies (i.e., not allowing a television, computer, or video game in the bedroom), verbal monitoring (i.e., stating rules), and tracking of the child (i.e., calling to see if the child is at a friend’s house; Dishion & McMahon, 1998). Involved monitoring also includes monitoring homework and school progress (Spera, 2005). Monitoring activities will change as the child ages. As children age and enter school, it becomes more important to monitor school attendance, grades, and activities away from home. As children become more involved with their peers, it becomes critical to monitor where they spend time and with whom they spend it (Crouter & Head, 2002; Dishion & McMahon, 1998). Involved monitoring has been associated with reduced alcohol and other drug use, conduct problems, juvenile delinquency, and risky sexual behavior, and with increased positive academic outcomes (Crouter & Head, 2002).

Non-harsh limit setting

Non-harsh limit setting is a type of parenting that uses moderate amounts of restrictiveness, expects appropriately mature behavior from children, sets reasonable limits, uses high levels of warmth, and is responsive and attentive to children’s needs (Parke & Buriel, 1998). Discipline, when used, is reasoned, consistent, and democratic, with mutual respect and give-and-take between the parent and child (Jackson, 2002; Simons-Morton & Hartos, 2002). Non-harsh limit setting is associated with many psychological and social advantages in adolescence, such as adolescent adjustment, school performance, and psychosocial maturity (Gray & Steinberg, 1999; Simons-Morton & Hartos, 2002), as well as lower rates of negative outcomes such as aggression, delinquency, school misconduct, violence, drug use (Simons-Morton & Hartos, 2002), and alcohol use (Jackson, Henriksen, & Foshee, 1998).

Reinforcing interactions

Parents influence child development and outcomes through reinforcing interactions and support of positive behaviors (Brooks, 2005; Dishion et al., 2008). A family intervention that was successful in increasing positive behavior support resulted in improvements in children's early problem behavior (Dishion et al., 2008). Positive behavior support includes positive reinforcement, proactive parenting, parent involvement, and verbal interaction. Among adolescents, positive daily conversations with parents can promote and enhance feelings of closeness with parents (Collins & Laursen, 2004). Parent-child relationship quality, measured by perceived quality of communication, trust, and alienation, predicted depressive symptoms in a longitudinal study of adolescents (Branje, Hale, Frijns, & Meeus, 2010).

Positive role modeling

Parents are important role models for their children. Children and adolescents learn through observation and modeling of behavior (Bandura, 1977, 1986). Parental role modeling includes modeling beliefs, attitudes, and overt behavior. By watching and interacting with their parents, children and adolescents learn what behaviors and beliefs the family accepts and values (Whitbeck, 1999). Children and adolescents exposed to family and community violence are more likely to have behavioral problems and engage in violent behavior (Linares et al., 2001; McMahon, Felix, Halpert, & Petropoulos, 2009). Additionally, children and adolescents exposed to parental substance use, including smoking, alcohol use, and other drug use, are more likely to engage in these behaviors (Richter & Richter, 2001). If their parents model healthful eating and exercise, children are more likely to eat healthful foods and exercise (Lindsay, Sussner, Kim, & Gortmaker, 2006).

Health maintenance, hygiene

Parents are important gatekeepers for health, hygiene, and the provision of healthy food. Providing access to medical care and teaching hygiene habits (e.g., proper dental care and overall hygiene) are key parenting practices. Youth with access to healthy foods in the home are more likely to eat fruits and vegetables (Pearson, Biddle, & Gorely, 2009). As noted above, parents are powerful role models for eating and exercise behaviors (Lindsay et al., 2006). Additionally, parents should encourage daily breakfast consumption, which can lead to a decreased risk of obesity and a better diet overall, and appears to improve memory and attention, leading to better academic outcomes (Rampersaud, Pereira, Girard, Adams, & Metzl, 2005). Another important area in which parents influence their child’s overall health is sleep. Adolescents typically do not get enough sleep; this is especially true during the school week (Carskadon, 1999; Strauch & Meier, 1988). Several negative outcomes, such as academic problems and increased risk for substance use and depression, result from inadequate sleep or widely varying patterns in sleep from the weekday to the weekend (Fredriksen, Rhodes, Reddy, & Way, 2004; O’Brien & Mindell, 2005; Pasch, Laska, Lytle, & Moe, 2010; Wolfson & Carskadon, 1998).

Involvement in positive activities

Parents can promote their children's involvement in positive, health-promoting activities. Positive activities include physical activities like sports, non-competitive organized physical activity, and other activities such as religious groups, music classes and lessons, and/or supervised afterschool clubs and programs (Duncan, Duncan, Strycker, & Chaumeton, 2002). When early adolescents engage in positive and healthy activities and entertainment, their prosocial skills and tendencies grow. Research on youth behavior tells us that involvement in structured, positive activities reduces youth negative behavior, such as substance use (Cooley, Henriksen, Nelson, & Thompson, 1995), misbehavior at school (Marsh, 1992), school dropout (Mahoney & Cairns, 1997), and delinquent activity (Landers & Landers, 1978). Participation in positive activities leads to better grades (Marsh, 1992), improved test scores (Gerber, 1996), and increased school attendance (Mahoney & Cairns, 1997).

Cumulative family risk

Maternal depression is associated with increased risk for most mental, emotional, and behavioral problems among youth (NRC & IOM, 2009). Several studies have highlighted the negative effects of cumulative family risk factors, including maternal depression, on child health and wellbeing across developmental phases. Cumulative family risk was associated with an increase in behavior problems among first grade students (Lima, Caughy, Nettles, & O’Campo, 2010). Lima et al. (2010) measured cumulative family risk by child-to-adult ratio, maternal education, marital status, current household smoking status, maternal depression, inter-partner violence, life stress, parental medical condition affecting parenting, harsh parenting, hostility, parental monitoring, parental affection, and parental eliciting behavior. Negative neighborhood social climate moderated the effect of family risk on behavior problems: more risk was associated with a larger increment in both psychological and behavioral problems for children living in high- versus low-risk neighborhoods. Eiden, Edwards, and Leonard (2007) examined the relations between parental alcohol diagnosis and parental warmth/sensitivity on kindergarteners’ problem behaviors. They found that paternal alcohol diagnosis led to lower maternal and paternal warmth/sensitivity, and that maternal warmth/sensitivity was longitudinally predictive of problem behaviors in kindergarten. Among adolescents and young adults, Forehand, Biggar, and Kotchick (1998) examined cumulative family risk on psychosocial adjustment. Measurement of family risk included parental divorce, interpersonal conflict, maternal physical health problems, maternal depressive mood, and mother-adolescent relationship difficulties. They found both concurrent and longitudinal associations between family risk and adolescent and young adult adjustment.

School influences

Effective schools can ensure that most young people develop the cognitive, social, and emotional regulation skills needed to succeed in life.

High quality early childhood education

High quality early childhood education improves the life prospects of poor children through improved IQs, school success, and reduced rates of delinquency during adolescence (Gorey, 2001; Pianta, Barnett, Burchinal, & Thornburg, 2009; Zoritch, Roberts, & Oakley, 2000). Characteristics of high-quality preschool programs include teacher credentials, teacher/preschooler ratios, and program intensity and duration (Gorey, 2001). Preschool programs are cost-effective: for every dollar invested in preschool programs, the benefits range from $3.78 to $17.07 per dollar (Heckman, Grunewald, & Reynolds, 2006). A review of the scientific evidence found that high-quality early education programs result in moderate improvements in academic achievement, school readiness, IQ test scores, and high school graduation rates, and in reductions in grade retention and the need for special education (Anderson et al., 2003). In addition to positive academic outcomes, early childhood programs increase social competence, employment, and home ownership, and decrease delinquency, teen pregnancy, teen arrests, and welfare use (Anderson et al., 2003).

High quality education

Quality teaching and curricula are vital to effective schools. Unqualified teachers, ineffective teaching practices, and low-quality curricula lead to academic failure (Ball, 2000; Darling-Hamond, 2000; Shulman, 1987). Teaching students the academic and social skills necessary to succeed in school and in life requires that schools address social and emotional concerns that could interfere with learning and classroom management (Adelman & Taylor, 1999). Perhaps the highest priority is to ensure that children learn to read, since those who do not learn to read by the end of third grade are unlikely ever to read effectively, even though reading is fundamental to most other learning (Juel, 1988; Shaywitz & Shaywitz, 1993). Solid evidence indicates that children can learn to read if they receive evidence-based reading instruction. Kame’enui et al. (1995, 1998) have stressed the need for a systematic, schoolwide approach to reading instruction. Continuous progress monitoring, in which educators adjust instruction in light of students’ progress, is also essential in every subject (Baker & Baker, 2008). In addition, a school is more effective when the staff shares a set of instructional goals, agrees on optimal instructional strategies for teaching, has strong support from the school and district leadership, and enjoys positive social relations (Bryk & Driscoll, 1988).

Positive school climate

The school environment has a very strong influence on the health, relationships, and academic success of students (Jia et al., 2009; Rowe & Stewart, 2009). Negative school environments include violence; bullying; limited academic and extracurricular activities; unfair discipline practices; and inadequate books, supplies, and other resources. Positive school environments show evidence of caring and supportive relationships among teachers and students, use of effective and collaborative teaching strategies, teacher commitment to student wellbeing, and parent involvement (Bowen & Bowen, 1999; Rumberger, 1995). Positive school environments help students feel connected to school, which is associated with improved academic achievement. Students who feel connected to school earn better grades, attend school more frequently, and are less likely to drop out compared to students who do not feel connected to school (CDCP, 2010a). A positive school environment and school connectedness also prevent adolescent risky behaviors, like alcohol and drug use, violence and gang involvement, and sexual risk-taking, and bring about fewer emotional problems (Battistich & Hom, 1997; CDCP, 2010b; McNeely, Nonnemaker, & Blum, 2002; Resnick et al., 1997; Whitlock, 2006).

In recent years, various systems have emerged to create schoolwide conditions that nurture positive social behavior and prevent behavioral problems. These systems manage student behavior positively and create conducive learning environments. The systems include 1) monitoring behavior and performance, 2) providing positive rewards and feedback for good behavior, 3) setting clear expectations, and 4) applying fair and consistent discipline and rules. These strategies encourage students to take responsibility for their behavior and motivate them to follow school rules so that discipline problems do not occur (Rutter & Maughan, 2002; Sugai & Horner, 2002, 2008).

Positive behavior management also makes students feel safe and connected at school (McNeely et al., 2002), and has been shown to improve academic performance (Blonigen et al., 2008). Punitive strategies that rely on excessive discipline and focus only on correcting bad behaviors are counterproductive. They increase behavior problems, coercive interactions among adults, and academic failure (Mayer, 1995; McEvoy & Welker, 2000; Skiba & Peterson, 1999, 2000).

School attendance

A strong link exists between poor school attendance and school dropout and academic failure. Students who attend school regularly use fewer drugs, alcohol, and tobacco; are less violent; and are less likely to have risky sex compared to students with high rates of absenteeism (Kirby, 2002; Rutter & Maughan, 2002; Suss, Tinkelman, Freeman, & Friedman, 1996). School attendance also aligns with student behaviors that are associated with good mental and physical health (Jessor, Turbin, & Costa, 1998).

Health education and prevention

Health education programs are an important component of quality education. Adolescents’ emotional, social, and physical health influences their academic success. Evidence-based health education programs can decrease substance use, risky sex, violence, physical inactivity, poor diet, and other health-risk behaviors that put student health at risk and lead to academic failure (Brown & Summerbell, 2009; NRC & IOM, 2009). Decreasing student health-risk behaviors leads to improved academic performance (NRC & IOM, 2009). School-based health education and prevention programs also protect adolescents against suicide, HIV/AIDS, sexually transmitted diseases, unwanted pregnancy, obesity, and diabetes (Joe, Joe, & Rowley, 2009; Needham, Crosnoe, & Muller, 2004).

Afterschool education and activities

Many young people have no supervision in the hours after school. Afterschool programs with an academic component provide adolescents with opportunities to develop academic, interpersonal, and other skills they will need to succeed in life (Durlak et al., 2007; Fashola, 1998; Lauer et al., 2006). Participation in afterschool activities improves homework completion, grades, standardized test scores, and school attendance (Cooper, Valentine, Nye, & Lindsay, 1999; Eccles, Templeton, & Larson, 2002; Jordan & Nettles, 2000; Kane, 2004). Afterschool programming provides adolescents with an opportunity to learn social, emotional, and communication skills needed to have successful relationships (Roth & Brooks-Gunn, 2000). Students who participate in afterschool activities have better relationships with their friends compared to those who do not participate in such activities (Ream & Rumberger, 2008). Participation in afterschool activities teaches teamwork, good sportsmanship, cooperation, problem-solving skills, and conflict-resolution skills (Fashola, 1998). Participation in afterschool programming also prevents health-risk behaviors, including drug and alcohol use, risky sex, violence and criminal activity (Eccles et al., 2002), pregnancy (Sabo, Miller, Farrell, Melnick, & Barnes, 1999), and obesity (Whitney, Cohen, Koralewicz, & Taylor, 2004). Compared to those who do not participate, adolescents who take part in extracurricular activities in school report fewer mental health concerns (Bohnert & Garber, 2007). Young people with no supervision during the afterschool hours have a greater risk of developing substance abuse (Richardson, Radziszewska, Dent, & Flay, 1993).

Peer influences

A healthy social environment for children is important for their overall wellbeing. As children move through elementary school, it becomes increasingly important for them to make and retain friends. Additionally, their friends have a great influence on decisions they make and behaviors they display. Therefore, the types of friends that children have can play a very important role in their wellbeing.

Prosocial peers, role models

Children who exhibit prosocial behavior (e.g., cooperative, helpful) are more likely to have friends, gain acceptance from peers, and encourage prosocial behaviors in each other. Children who frequently exhibit disruptive or aggressive behaviors are less likely to gain acceptance from prosocial children and tend to affiliate with other children who exhibit aggressive behaviors (Farmer et al., 2002). Even in communities in which violence occurs frequently, having prosocial peers can help these children avoid participating in violent and antisocial behaviors (Smith, Flay, Bell, & Weissberg, 2001). During early adolescence, social networks, including friends and peers, become much more important to youth (Larson & Richards, 1991). In middle school, youth begin to select friendships based on mutual interests, rather than on convenience (Csikszentmihalyi & Larson, 1984; Giordano, 2003). Research on adolescent behavior tells us that adolescents who ‘hang out’ with positive, prosocial youth are more likely to do better in school and participate in positive extracurricular activities (Wilson et al., 2009). Youth with prosocial friendships are less likely to engage in risky behavior, including dropping out of school, substance use, early and risky sexual activity, violence, and crime (Berndt & Keefe, 1995).

Prosocial friendships and social skill development will help youth become successful adults. Positive role models, or people they admire, also influence youth behavior. Research with adolescents indicates that youth benefit from relationships with positive adults they respect, such as parents, other relatives, adult friends, or professionals. This includes enhanced feelings of self-worth, higher grades, and less substance use (Hurd, Zimmerman, & Yange, 2009; Yancey, Siegel, & McDaniel, 2002).

Exposure to alcohol, tobacco and other drug use, violence, and crime

Community violence and youth exposure to violence have many negative consequences (Buka, Stichick, Birdthistle, & Earls, 2001). Reducing youth exposure to violence, drug use, and crime has a positive effect on adolescent youth development (Gardner, Roth, & Brooks-Gunn, 2008; Lerner et al., 2005; Roth, Brooks-Gunn, Murray, & Foster, 1998). Peer influences are also important. Adolescents’ estimates of the norms and expectations of their peers concerning drug use affect their use of alcohol, tobacco, and other drugs, as does the actual use by their peers (Hawkins, Catalano, & Miller, 1992). Therefore, a key component of effective preventive interventions is creating positive and health-promoting peer influences and norms, which has shown to be a significant mediator of program effects on behavior (Komro et al., 2001).

Social networking technologies

Regular use of the Internet is widespread among youth, although use rates among low-income (73%) and African American (77%) youth are lower than among higher income (90%), white (87%), and Hispanic (89%) youth (Lenhart, Madden, & Hitlin, 2005). Social networking sites are particularly popular among youth, who use them primarily to socialize and make plans with friends, and to make new friends (Pujazon-Zazik & Park, 2010). Online social interactions provide a venue to expand social skills during adolescence (Pujazon-Zazik & Park, 2010). However, potential risks accompany social networking sites, including promotion of risk-taking behaviors, cyberbullying, and exposure to sexual predators (Pujazon-Zazik & Park, 2010).

Distal Influences

Income and resources

Poverty harms people in many ways. It affects development; puts stresses on families, which results in increased conflict; affects parent and child health; and undermines cooperation among neighbors in high-poverty neighborhoods. Poor children are much more likely to grow up to be poor adults and to raise children with the same problems they had as children.

Neighborhood poverty

Families face special challenges when they live in neighborhoods with a high poverty rate, including 1) a high proportion of single-parent families, 2) racial segregation, and 3) families frequently moving in and out of the neighborhood (Sampson et al., 2002). Such neighborhoods have higher levels of child abuse, infant mortality, school dropout, crime, delinquency, and mental illness (Gephart, 1997; Leventhal & Brooks-Gunn, 2004; Sampson et al., 2002). In neighborhoods with high rates of poverty and frequent moving, it becomes harder for people to get to know and trust one another, making it more difficult to support each other, monitor each other’s children, and guide their young people in consistent ways (Sampson et al., 2002).

Family poverty

In the U.S., medium family income has a negative correlation and income inequality a positive correlation with preterm births, low birth rate, and infant mortality (Olson, Diekema, Elliott, & Renier, 2010). Family poverty puts stress on parents, making it more difficult for them to be attentive, warm, and caring with their children. Therefore, within families living in poverty, parents are less likely to help their children develop social skills (Gershoff, Aber, Raver, & Lennon, 2007). Poverty undermines the quality of the time parents can spend with their children, which results in less time spent on interacting and teaching their children (Gershoff et al., 2007). Children from low-income families are less likely to be prepared for school and more likely to fall behind in school (Duncan, Yeung, Brooks-Gunn, & Smith, 1998; West, Denton, & Germino-Hausken, 2000). Throughout children’s development, poverty reduces parents’ ability to invest in their children’s learning. Parents with low incomes find it difficult to buy books, attain quality childcare, or pay for afterschool programs. They even lower their expectations for their children’s education (Bradley, Corwyn, Burchinal, McAdoo, & Coll, 2001; Yoshikawa, Weisner, & Lowe, 2006). In this way, the effects of family poverty can stretch outside the home, affecting the quality of learning opportunities in childcare and after school. The longer children live in poverty, the more harmful its effect on their learning (Najman et al., 2009).

When their families are poor or experience job instability, children and adolescents have a higher number of psychological problems (such as depression) and behavioral problems, such as delinquency and substance use (Costello, Compton, Keeler, & Angold, 2003; Lipman, Offord, & Boyle, 1994). Economic stressors increase family conflict and reduce the quality of parenting, which in turn influences the development of problem behavior (Conger, Ge, Elder, Lorenz, & Simons, 1994).

Relative deprivation and inequality

Poverty is especially harmful in societies with great differences between the wealthiest and poorest people. Despite the fact that the United States is a wealthy country, the gap between rich and poor is higher in the U.S. than in most economically developed countries. Wilkinson and Pickett (2009) provide an overview of the relationship between economic inequality and various measures of health and wellbeing. Countries and U.S. states with greater inequality in wealth have higher levels of health and social problems. They have lower life expectancy, lower levels of trust, higher rates of mental illness and obesity, inferior school performance, more teenage births, more homicides, higher imprisonment rates, and less social mobility. In a subanalysis of income inequality specific to child wellbeing, they found similar relations (Pickett & Wilkinson, 2008). In an analysis of all 50 U.S. states, income inequality was associated with all indicators of child wellbeing and higher average income was associated with lower rates of teenage births and dropping out of school (Wilkinson & Pickett, 2009). As summarized above, income inequality showed a positive correlation with preterm births, low birth rate, and infant mortality in the U.S. (Olson et al., 2010).

Access to dental and health care

Low-income families are much less likely to have health insurance and access to dental care and healthcare, which results in many consequences, including 1) being unlikely to have a regular source of medical care; 2) unhealthy parents, which adds to their financial distress; 3) less prenatal care, resulting in unhealthy infants and increased infant mortality; 4) less health and dental care for children; and 5) poorer health outcomes among children (IOM, 2002). Many children without access to adequate healthcare suffer life-long effects from conditions such as iron deficiency anemia, asthma, attention deficit–hyperactivity disorder, and dental morbidity (IOM, 2002).

Social cohesion

Social cohesion involves people trusting and supporting each other in the neighborhood. It is a critical factor for neighborhoods striving to raise children successfully (Sampson et al., 2002).

Prosocial norms, informal social control

Laws and law enforcement are helpful to neighborhoods (Wagenaar, Toomey, & Erickson, 2005), but informal social norms are also important for maintaining neighborhood viability (Cialdini, 2007), even for such issues as public consumption of illegal drugs (Johnson, Ream, Dunlap, & Sifaneck, 2008). When neighbors are mindful of each other’s children, for example, boys tend to do better in school (Drukker, Feron, Mengelers, & Van Os, 2009). In a similar way, such mindfulness of each other’s children and discussion of rules reduces binge drinking and drug use among adolescents (Fulkerson, Pasch, Perry, & Komro, 2008). Informal policies, such as public reinforcement for prosocial behavior in schools, can reduce vandalism in and around the schools (Mayer, Butterworth, Nafpaktitis, & Sulzer-Azaroff, 1983). Communities can use a similar reinforcement strategy for adults not to sell alcohol or tobacco to minors, with positive results (Biglan et al., 1995, 1996).

Connectedness, social capital

A close relationship exists between having informal social norms and having a socially supportive neighborhood. Research shows that neighborhoods where people know and trust each other have reduced crime and juvenile delinquency (Sampson, Raudenbush, & Earls, 1997). In neighborhoods where people get to know each other and establish mutual respect and trust, people can agree on norms for behavior in the neighborhood, which encourages people to take action when young people violate those norms (Sampson et al., 1997; Veysey & Messner, 1999). This form of collective action to set limits and guide youth behavior is critical in preventing crime and other problem behavior (Sampson et al., 1997). It is easier for neighbors to cooperate in monitoring and guiding youth if the neighborhood has good common spaces for young people to play and where adults can be present (Sampson et al., 1997). Having recreational facilities, family support centers, libraries, and other places where people can gather in supportive ways is also important in ensuring that young people are guided in positive directions (Sampson et al., 2002).

Healthy community norms

Neighborhood norms about a healthy community can be created and have immense effects (Cubbin et al., 2008; Maddock et al., 2006; Sorensen et al., 2007). A focus on creating healthy community norms is vital since interventions focused only on individuals in poor neighborhoods often have weak effects (Maddock et al., 2006).

Social exclusion, discrimination

Social exclusion and discrimination break social cohesion. Certain racial, ethnic, income, and gender groups continue to receive differential treatment and face restricted access to available goods and services. Researchers have tried to understand discrimination both as social processes that affect identifiable groups and as social acts experienced by individual members of that group. Discriminatory policies and practices have limited the power, status, and wealth of particular subgroups, which contributes to patterns of social isolation and concentrated poverty (Wilson, 2009). As a result, residents in high-poverty neighborhoods tend to experience lower levels of physical and mental health, educational attainment, and employment than residents of other neighborhoods (Lamberty, Pachter & Crnic, 2000; Pachter & Coll, 2009).

Either a structural or cultural perspective has informed research on the implications of discrimination and social exclusion for the wellbeing of children and youth. For example, those concerned with structural inequalities argue that adverse educational and health outcomes may be due to differential access to material needs, such as adequate nutrition, quality housing, and schools, as well as increased exposure to environmental toxins and hazards (Williams, Neighbors, & Jackson, 2003). Others suggest that, in the absence of effective coping strategies, children and adults feel the stress associated with experiencing discrimination, which can lead to psychological and behavioral responses that undermine their optimal individual and collective development and wellbeing (Pachter & Coll, 2009; Harrell, Hall, & Taliaferro, 2003; Sellers, Copeland-Linder, Martin, & Lewis, 2006).

Physical environment

Many aspects of the physical environment harm young people's development. Physical design of the neighborhood affects social relations, crime, and the amount of physical activity. Decayed and abandoned buildings fuel more crime. Neighborhoods with easy access to alcohol have more drinking problems, injuries, and violence. Types of food available in the neighborhood affect people’s nutrition and health. Additionally, neighborhoods often have many physical toxins (e.g., air or soil pollution) that directly affect health and behavior.

Decay: abandoned buildings, substandard housing

Much research shows that neighborhoods with greater physical disorder and decay (i.e., abandoned buildings, trash, and crumbling structures) have higher levels of social problems, including crime, higher levels of fear, lack of social cohesion, and more physical illness (Sampson et al., 2002). Evidence suggests that improving neighborhood conditions can increase social cohesion and mental health outcomes (Williams, Costa, Odunlami, & Mohammed, 2008). Simple street lighting can decrease crime, traffic crashes, and injuries (Beyer & Ker, 2009; Welsh & Farrington, 2006).

Neighborhood design, land use

Recent research on the design of neighborhoods shows that people benefit from living in neighborhoods made up of a mix of residential, commercial, and business activities, with housing that facilitates social interactions, and that makes walking from home to work and shopping easy (Bellair, 1997; Boarnet, Greenwald, & McMillan, 2008; Felner, Seitsinger, Brand, Burns, & Bolton, 2007; Frank, Andresen, & Schmid, 2004). Such neighborhoods encourage people to walk more, to get to know their neighbors, and to participate in neighborhood activities. These neighborhoods have lower levels of obesity and greater social contact and do better at guiding the prosocial behavior of young people (Biglan & Hinds, 2009). Changing community- and street-scale urban design and land use policies such as zoning can achieve significant increases in physical activity (Heath et al., 2006).

Access to alcohol, tobacco, other drugs, firearms

Easy access to health-compromising products poses a significant risk for child health and wellbeing. Tobacco availability and promotion is associated with all stages of smoking among children and adolescents, from experimentation through addiction (U.S. Department of Health and Human Services, 1994). A relationship is also evident between availability of alcohol and both alcohol use and alcohol-related problems among youth (Wagenaar & Perry, 1994). Neighborhoods with easy access to alcohol have more problem drinking, crime and violence, and alcohol-related injuries (Popova, Giesbrecht, Bekmuradov, & Patra, 2009). Reducing the number of alcohol outlets and the days and hours of sale can reduce all of these problems (Campbell et al., 2009; Popova et al., 2009). Reducing young people’s exposure to alcohol advertising also helps reduce problem drinking and alcohol-related problems (Anderson, de Bruijn, Angus, Gordon, & Hastings, 2009).

Easy access to firearms is a serious risk for youth living in high-poverty neighborhoods. In 2007, firearm-associated homicides accounted for greater than 80% of the deaths among African American male youth (Xu, Kochanek, & Tejada-Vera, 2009). In 1998, the firearm-homicide rate for black male teenagers was 63 out of every 100,000 (Fingerhut & Christoffel, 2002; Teplin, McClelland, Abram, & Mileusnic, 2005). The available evidence from time series, cross-sectional international and US studies indicates an association with increased firearm availability and an increased homicide rate (Hepburn & Hemenway, 2004). A 10-year time series analysis of data from the 50 states indicated a significant association between firearm availability and the rates of unintentional firearm deaths, suicides, and homicides among 5–14 year olds (Miller, Azrael, & Hemenway, 2002).

Access to nutritious foods

Consumption of fruits and vegetables is essential to healthy nutrition, chronic disease prevention, and weight control (World Cancer Research Fund, 1997). In urban areas, a higher density of fast food restaurants may contribute to racial differences in obesity rates (Powell, Chaloupka, & Bao, 2007). Residents of low income and minority neighborhoods most often encounter poor access to supermarkets and healthful food, and greater access to fast food restaurants and energy-dense foods (Powell et al., 2007). Increasing fruit and vegetable availability in low-access neighborhoods appears to improve dietary choices (Glanz & Yaroch, 2004). Research suggests that neighborhood residents with better access to supermarkets and limited access to convenience stores tend to have healthier diets and lower levels of obesity (Larson, Story, & Nelson, 2009). Larson et al. (2009) also examined the accessibility of restaurants and, although their results were somewhat less consistent, they found some evidence to suggest that residents with limited access to fast food restaurants have healthier diets and lower levels of obesity.

Exposure to poor quality food environments negatively affects adolescent eating patterns and weight (Davis & Carpenter, 2009). Home and school food environments influence fruit and vegetable consumption in children (French & Stables, 2003; Rasmussen et al., 2006). Eating fast food is associated with low or less frequent consumption of fruit and vegetables in children and adolescents (Rasmussen et al., 2006). Further, proximity of fast food restaurants to schools correlates with students consuming more soda and less fruits and vegetables, and having a greater likelihood of becoming overweight or obese (Davis & Carpenter, 2009). Policy interventions affecting the food environment could reduce adolescent obesity and improve overall health (Davis & Carpenter, 2009; French & Stables, 2003; Glanz & Yaroch, 2004; Rasmussen et al., 2006).

Exposure to toxins

Residents of high-poverty neighborhoods face a greater risk of exposure to physical toxicants. Physical toxins are detrimental to general health, behavior, cognitive capacity, and social capital. While most people know of lead (Pb) toxicity, many assume this is due only to lead paint. However, an additional problem is the lead in dust and water. Even low levels of lead exposure lower children’s IQs (Jusko et al., 2008), increase ADHD (Braun, Kahn, Froelich, Auinger, & Lamphear, 2006; Nigg et al., 2008), and increase conduct disorders (Braun et al., 2006). The effects intensify when people have other stressors in their lives (Fergusson, Swain-Campbell, & Horwood, 2004). Another airborne toxin is black carbon, a marker for motor vehicle exhaust. It is associated with decreased verbal and nonverbal intelligence and impaired memory (Suglia, Gryparis, Wright, Schwartz, & Wright, 2008).

The public is less aware of other already scientifically proven toxic influences. For example, omega-3 fatty acid deficiency and cytotoxic levels of omega-6 resulting from the consumption of fast foods, processed foods, and free-lunch programs, harm infant and child cognition and development into the eighth year of life (Helland, Smith, Saarem, Saugstad, & Drevon, 2003; Hibbeln et al., 2007; Tofail et al., 2006). It increases hyperactivity (Gale et al., 2008), aggression, and mental illnesses (Arora et al., 2008; Hibbeln, Nieminen, Blasbalg, Riggs, & Lands, 2006). These adverse fatty acid ratios also cause obesity (Dziedzic, Szemraj, Bartkowiak, & Walczewska, 2007) and worsen the negative impact of lead exposure (Arora et al., 2008).

Some toxins involve physical but not chemical mechanisms. For example, the chronic noise of many poor urban neighborhoods is associated with reductions in reading and math scores, even when studies control for poverty levels (Haines, Stansfeld, Head, & Job, 2002). Even the noise generated by the classroom itself affects literacy (Shield & Dockrell, 2008).

Some toxins involve only social mechanisms. Witnessing violence directly at home (Cummings, El-Sheikh, Kouros, & Buckhalt, 2009), in the neighborhood (Foster & Brooks-Gunn, 2009; Cooley-Strickland et al., 2009), in school (Embry, Flannery, Vazsonyi, Powell, & Atha, 1996; Linares et al., 2001; McMahon et al., 2009), or indirectly via media (Hopf, Huber, & Weiß, 2008; Huesmann, Lagerspetz, & Eron, 1984) contributes to children’s stress and aggressive behavior. Exposure to verbal coercion can also have this effect (Patterson, Dishion, & Bank, 1984; Patterson & Stouthamer-Loeber, 1984). Chronic exposure to these experiences appears to reset young people’s biology to render them prone to impulsivity, poor self-regulation, early sexual maturity, addictions, psychiatric disorders, and “gang-like behavior” (Embry, 2002; Embry, Lopez, & Minugh, 2005; Tsankova, Renthal, Kumar, & Nestler, 2007).

Media

Media exposure, including television, movies, rock music and videos, advertising, video games, and computers and the Internet, significantly affects child and adolescent outcomes. Media exposure can lead to increased violent and aggressive behavior, alcohol and tobacco use, and early onset of sexual activity (Villani, 2001). Among low-income preschool children, having a television in one’s bedroom puts one at risk of being overweight, with each additional hour of time spent watching television increasing that risk (Dennison, Erb, & Jenkins, 2002). Evidence also suggests that television viewing by infants is associated with delayed language and cognitive development (Christakis, 2009). Several researchers have found manufacturers to advertise addictive products more frequently in African American and Hispanic neighborhoods compared with non-Hispanic white neighborhoods (Altman, Schooler, & Basil, 1991; Hackbarth et al., 2001; Hackbarth, Silvestri, & Cosper, 1995; Mitchell & Greenberg, 1991; Pasch, Komro, Perry, Hearst, & Farbakhsh, 2009). Researchers have also found that outdoor advertising for unhealthy food and beverages prevails around schools and other youth-serving institutions (Kelly, Cretikos, Rogers, & King, 2008; Maher, Wilson, & Signal, 2005; Yancey et al., 2009).

Summary

The Creating Nurturing Environments framework provides a summary of potent and malleable influences on key child health and wellbeing indicators encompassing cognitive, social-emotional, psychological, behavioral, and physical health outcomes across developmental phases. We have provided a summary of evidence to support the importance of each construct and domain within the framework. Cognitive, social-emotional, psychological, behavioral, and health outcomes are interrelated and have an interacting set of key influences within the family, school, peer, and neighborhood environments. Negative health and developmental outcomes are concentrated among children living within high-poverty and disadvantaged neighborhoods (Dupéré & Perkins, 2007; Leventhal & Brooks-Gunn, 2000; NRC & IOM, 2009). Therefore, community-wide efforts—integrating strategies to improve the social and physical environments within families, schools, peer groups, and neighborhoods—are vital in promoting optimal child health and wellbeing. We designed this framework to guide comprehensive community efforts. It helps to highlight and promote cooperation and synergism among diverse actors within a community to integrate policies, programs, and practices more effectively to achieve community planning and action. Because all the factors we have reviewed interact (e.g., it is difficult for children to do well academically if they are in poor physical health), community sectors working on one problem have a direct interest in cooperating with and helping other sectors working in a different domain. Key implications of the Creating Nurturing Environments framework include the following:

  1. Cognitive, social-emotional, psychological, behavioral, and health outcomes have inherent interrelationships.

  2. The framework warrants a developmental perspective and multiyear efforts, given the significance and long-lasting effects of influences during earlier phases on later phases of development.

  3. The framework includes comprehensive multicomponent and multilevel strategies, considering the interrelatedness of outcomes and interactions among influences.

Application of the Creating Nurturing Environments Framework

In the final section of this paper, we provide recommendations regarding application of the Creating Nurturing Environments framework to improve child health and wellbeing and to reduce risks associated with poverty and with living in high-poverty neighborhoods. As we wrote earlier, the PNRC is a collaborative effort of neighborhood representatives, early career scientists, and senior scientists from a wide array of disciplines and fields. Developing this framework was one of the PNRC’s initial tasks. We then used the framework to guide our analysis and synthesis of the scientific literature to provide recommendations for evidence-based strategies that target key proximal and distal influences on child outcomes. We used the standards of evidence recommended by the Society for Prevention Research (Flay et al., 2005) to identify evidence-based strategies, including policies, programs, and practices that fit within the framework. We have placed our recommendations on our website (http://promiseneighborhoods.org/what-works/) as a tool for neighborhoods and fellow scientists. Implementation quality is key to the success of rolling out evidence-based strategies, with implementation process affected by program, provider, delivery system, support system, and community factors (Durlak & DuPre, 2008). Effective dissemination of evidence-based interventions will require capacity building, quality training, promotion of practitioner self-efficacy, workplace support, and supervision (Turner & Sanders, 2006; Wandersman et al., 2008). Each step of the dissemination process will require monitoring and continuous quality improvement to ensure desired outcomes.

The framework also guided our development of a comprehensive monitoring and measurement system. We assembled measures for the cognitive, social-emotional, psychological, behavioral, and health outcomes at each stage of development (from pregnancy through adolescence). In addition, we have assembled (and in some cases, developed) a comprehensive set of measures to assess the characteristics of families, schools, and neighborhoods as they relate to child outcomes. The measures include neighborhood-, school-, family-, and individual-level data from archival (pre-existing) sources, as well as surveys of enrolled students, parents, and teachers. Our website (http://promiseneighborhoods.org/measures/) provides details regarding these measures. We are now developing an infrastructure to support standardized collection of data and a summary of results for neighborhoods to use in achieving continuous quality improvement and to construct rigorous evaluations of each intervention component and an overall evaluation of multicomponent, community-wide initiatives (Biglan et al., 2010; Flay et al., under review).

We close with five principles to guide the application of the Creating Nurturing Environments framework:

  1. A focus on high-poverty neighborhoods makes sense, given significant health and educational inequalities that currently exist (Aikens & Barbarin, 2008; Burdette & Hill, 2008; Cohen, Farley, & Mason, 2003; Cutrona et al., 2006; NRC & IOM, 2009; Sampson et al., 2002; Shumow et al., 1999).

  2. The implementation of evidence-based strategies is necessary, but not sufficient. Ongoing measurement and monitoring is essential to determine the effectiveness of each component within specific neighborhood contexts (Biglan et al., 2010).

  3. It is important to integrate, coordinate, and sustain a comprehensive set of evidence-based strategies efficiently across developmental phases. This requires development and ongoing efforts for communication and cooperation across community organizations.

  4. Community-wide and non-stigmatizing approaches are fundamental in achieving high-levels of community support, participation, and population-level change.

  5. The framework highlights malleable proximal and distal influences to create healthful and nurturing environments. To begin, neighborhoods should focus on feasible changes to existing structures, functions, and environmental influences. The successful completion of feasible changes will then promote continued efforts and success.

Based on a synthesis of research from diverse fields, we designed the Creating Nurturing Environments framework to guide community-wide efforts to improve child outcomes and reduce health and educational inequalities. It is our sincere hope that this framework, along with the evidence-based strategy recommendations and measurement system provided on our website, will be valuable tools for the promotion of optimal success and wellbeing among children living within distressed communities. Integrating knowledge of potent and malleable influences and effective strategies into regular ongoing community-based practice, along with promotion and assistance in the use of scientific methods for continuous quality improvement and analysis of results, are key to determining what is and what is not working to improve the wellbeing of children within our communities. To make this happen, we encourage strong partnerships between the scientific community and neighborhood-based organizations.

Acknowledgments

A grant from the National Institute of Drug Abuse (DA028946) supported the authors during their work on this manuscript.

Reference List

  1. Adelman HS, Taylor L. Mental health in schools and system restructuring. Clinical Psychology Review. 1999;19:137–163. doi: 10.1016/s0272-7358(98)00071-3. [DOI] [PubMed] [Google Scholar]
  2. Aikens NL, Barbarin O. Socioeconomic differences in reading trajectories: The contribution of family, neighborhood, and school contexts. Journal of Educational Psychology. 2008;100:235–251. [Google Scholar]
  3. Akinbami LJ. The state of childhood asthma, United States, 1980–2005. Advance Data from Vital and Health Statistics. 2006;381:1–24. [PubMed] [Google Scholar]
  4. Altman DG, Schooler C, Basil MD. Alcohol and cigarette advertising on billboards. Health Education Research. 1991;6:487–490. [Google Scholar]
  5. Anderson LM, Shinn C, Fullilove MT, Scrinshaw SC, Fielding JE, Normand J, et al. The effectiveness of early childhood development programs: A systemic review. American Journal of Preventive Medicine. 2003;24(3 Suppl):32–46. doi: 10.1016/s0749-3797(02)00655-4. [DOI] [PubMed] [Google Scholar]
  6. Anderson P, de Bruijn A, Angus K, Gordon R, Hastings G. Impact of alcohol advertising and media exposure on adolescent alcohol use: A systematic review of longitudinal studies. Alcohol and Alcoholism. 2009;44:229–243. doi: 10.1093/alcalc/agn115. [DOI] [PubMed] [Google Scholar]
  7. Arora M, Ettinger AS, Peterson KE, Schwartz J, Hu H, Hernandez-Avila M, et al. Maternal dietary intake of polyunsaturated fatty acids modifies the relationship between lead levels in bone and breast milk. Journal of Nutrition. 2008;138:73–79. doi: 10.1093/jn/138.1.73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Baker SK, Baker DL. English language learners and response to intervention: Improving quality of instruction in general and special education. In: Grigorenko EL, editor. Educating individuals with disabilities: IDEIA 2004 and beyond. New York, NY: Springer; 2008. pp. 249–272. [Google Scholar]
  9. Ball DL. Bridging practices: Intertwining content and pedagogy in teaching and learning to teach. Journal of Teacher Education. 2000;51:241–247. [Google Scholar]
  10. Bandura A. Social learning theory. Englewood Cliffs, NJ: Prentice Hall; 1977. [Google Scholar]
  11. Bandura A. Social foundations of thought and action: a social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall; 1986. [Google Scholar]
  12. Barr DA. Health disparities in the United States: Social class, race, ethnicity, and health. Baltimore, MD US: Johns Hopkins University Press; 2008. [Google Scholar]
  13. Barros AJD, Matijasevich A, Santos IS, Halpern R. Child development in a birth cohort: effect of child stimulation is stronger in less educated mothers. International Journal of Epidemiology. 2009;39:285–294. doi: 10.1093/ije/dyp272. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Battistich V, Hom A. The relationship between students' sense of their school as a community and their involvement in problem behaviors. American Journal of Public Health. 1997;87:1997–2001. doi: 10.2105/ajph.87.12.1997. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Bellair PE. Social interaction and community crime: examining the importance of neighbor networks. Criminology. 1997;35:677–703. [Google Scholar]
  16. Berndt TJ, Keefe K. Friends' influence on adolescents' adjustment to school. Child Development. 1995;66:1312–1329. [PubMed] [Google Scholar]
  17. Beyer FR, Ker K. Street lighting for prevention of road traffic injuries. Injury Prevention. 2009;15:282. doi: 10.1002/14651858.CD004728.pub2. [DOI] [PubMed] [Google Scholar]
  18. Biglan A, Hinds E. Evolving prosocial and sustainable neighborhoods and communities. Annual Review of Clinical Psychology. 2009;5:169–196. doi: 10.1146/annurev.clinpsy.032408.153526. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Biglan A, Ary DV, Koehn V, Levings D, Smith S, Wright Z, et al. Mobilizing positive reinforcement in communities to reduce youth access to tobacco. American Journal of Community Psychology. 1996;24:625–638. doi: 10.1007/BF02509717. [DOI] [PubMed] [Google Scholar]
  20. Biglan A, Flay BR, Embry DD. Nurturing environments and the next generation of prevention research and practice. Under review [Google Scholar]
  21. Biglan A, Flay BR, Komro KA, Embry DD, Aldridge WA, II, Prinz RJ, et al. The evaluation and research infrastructure for comprehensive prevention. 2010 Available at http://promiseneighborhoods.org/journal/
  22. Biglan A, Henderson J, Humphreys D, Yasui M, Whisman R, Black C, et al. Mobilising positive reinforcement to reduce youth access to tobacco. Tobacco Control. 1995;4:42–48. [Google Scholar]
  23. Blonigen B, Harbaugh W, Singell L, Horner RH, Irvin LK, Smolkowski K. Application of economic analysis to School-Wide Positive Behavior Support (SWPBS) programs. Journal of Positive Behavior Interventions. 2008;10:5–19. [Google Scholar]
  24. Boarnet MG, Greenwald M, McMillan TE. Walking, urban design, and health: toward a cost-benefit analysis framework. Journal of Planning Education and Research. 2008;27:341–358. [Google Scholar]
  25. Bohnert AM, Garber J. Prospective relations between organized activity participation and psychopathology during adolescence. Journal of Abnormal Child Psychology. 2007;35:1021–1033. doi: 10.1007/s10802-007-9152-1. [DOI] [PubMed] [Google Scholar]
  26. Bonnier C. Evaluation of early stimulation programs for enhancing brain development. Acta Paediatrica. 2008;97:853–858. doi: 10.1111/j.1651-2227.2008.00834.x. [DOI] [PubMed] [Google Scholar]
  27. Bowen NK, Bowen GL. Effects of crime and violence in neighborhoods and schools on the school behavior and performance of adolescents. Journal of Adolescent Research. 1999;14:319–342. [Google Scholar]
  28. Bradley RH, Corwyn RF, Burchinal M, McAdoo HP, Coll CG. The home environment of children in the United States Part 2: Relations with behavioral development through age 13. Child Development. 2001;72:1868–1886. doi: 10.1111/1467-8624.t01-1-00383. [DOI] [PubMed] [Google Scholar]
  29. Bradshaw CP, Schaeffer CM, Petras H, Ialongo N. Predicting negative life outcomes from early aggressive-disruptive behavior trajectories: gender differences in maladaptation across life domains. Journal of Youth and Adolescence. 2010;39:953–966. doi: 10.1007/s10964-009-9442-8. [DOI] [PubMed] [Google Scholar]
  30. Branje SJT, Hale WW, III, Frijns T, Meeus WHJ. Longitudinal associations between perceived parent-child relationship quality and depressive symptoms in adolescence. Journal of Abnormal Child Psychology. 2010;38:751–763. doi: 10.1007/s10802-010-9401-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Braun JM, Kahn RS, Froelich T, Auinger P, Lamphear BP. Exposures to environmental toxicants and attention deficit hyperactivity disorder in U.S. children. Environmental Health Perspectives. 2006;114:1904–1909. doi: 10.1289/ehp.9478. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Braveman P, Egerter S. Overcoming obstacles to health. 2008 Feb; Report from the Robert Wood Johnson Foundation to the Commission to Build a Healthier America. Available at http://www.rwjf.org/files/research/obstaclestohealth.pdf.
  33. Bronfenbrenner U. The ecology of human development: Experiments by nature and design. Cambridge, MA: Harvard University Press; 1979. [Google Scholar]
  34. Bronfenbrenner U. On making human beings human. New York: Sage; 1981. [Google Scholar]
  35. Bronson MB. Recognizing and supporting the development of self-regulation in young children. Young Children. 2000;55:32–37. [Google Scholar]
  36. Brooks RB. The power of parenting. In: Goldstein S, Brooks RB, editors. Handbook of resilience in children. New York: Kluwer/Plenum; 2005. pp. 297–314. [Google Scholar]
  37. Brown T, Summerbell C. Systemic review of school-based interventions that focus on changing dietary intake and physical activity levels to prevent childhood obesity: an update to the obesity guidance produced by the National Institute for Health and Clinical Excellence. Obesity Reviews. 2009;10:110–141. doi: 10.1111/j.1467-789X.2008.00515.x. [DOI] [PubMed] [Google Scholar]
  38. Bryk A, Driscoll M. The high school as community: Contextual influences and consequences for students and teachers. Madison: University of Wisconsin, National Center on Effective Secondary Schools; 1988. [Google Scholar]
  39. Buckner JC, Mezzacappa E, Beardslee WR. Self-regulation and its relations to adaptive functioning in low-income youths. American Journal of Orthopsychiatry. 2009;79:19–30. doi: 10.1037/a0014796. [DOI] [PubMed] [Google Scholar]
  40. Buka SW, Stichick TL, Birdthistle I, Earls FJ. Youth exposure to violence: Prevalence, risks, and consequences. American Journal of Orthopsychiatry. 2001;71:298–310. doi: 10.1037/0002-9432.71.3.298. [DOI] [PubMed] [Google Scholar]
  41. Burdette AM, Hill TD. An examination of processes linking perceived neighborhood disorder and obesity. Social Science & Medicine. 2008;67:38–46. doi: 10.1016/j.socscimed.2008.03.029. [DOI] [PubMed] [Google Scholar]
  42. Campbell CA, Hahn RA, Elder R, Brewer R, Chattopadhyay S, Fielding J, et al. The effectiveness of limiting alcohol outlet density as a means of reducing excessive alcohol consumption and alcohol-related harms. American Journal of Preventive Medicine. 2009;37:556–569. doi: 10.1016/j.amepre.2009.09.028. [DOI] [PubMed] [Google Scholar]
  43. Carskadon MA. When worlds collide - adolescent need for sleep versus societal demands. Phi Delta Kappan. 1999;8:348–353. [Google Scholar]
  44. Centers for Disease Control and Prevention. Achievements in Public Health, 1990–1999: Impact of vaccines universally recommended for children-United States, 1990–1998. MMWR. 1999;48:243–248. Available at http://www.cdc.gov/mmwr/preview/mmwrhtml/00056803.htm. [PubMed] [Google Scholar]
  45. Centers for Disease Control and Prevention. Youth Risk Behavior Survey. Atlanta, GA: U.S. Department of Health and Human Services; 2008. pp. 1991–2007. [Google Scholar]
  46. Centers for Disease Control and Prevention. Student health and academic achievement. 2010a Available at http://www.cdc.gov/healthyyouth/health_and_academics/index.htm.
  47. Centers for Disease Control and Prevention. Strategies for increasing protective factors among youth. 2010b Available at http://www.cdc.gov/HealthyYouth/AdolescentHealth/connectedness.htm.
  48. Christakis DA. The effects of infant media usage: What do we know and what should we learn? Acta Paediatrica. 2009;98:8–16. doi: 10.1111/j.1651-2227.2008.01027.x. [DOI] [PubMed] [Google Scholar]
  49. Cialdini RB. Descriptive social norms as underappreciated sources of social control. Psychometrika. 2007;72:263–268. [Google Scholar]
  50. Cohen DA, Farley TA, Mason K. Why is poverty unhealthy? Social and physical mediators. Social Science & Medicine. 2003;57:1631–1641. doi: 10.1016/s0277-9536(03)00015-7. [DOI] [PubMed] [Google Scholar]
  51. Cohen JS, Mendez JL. Emotion regulation, language ability, and the stability of preschool children's peer play behavior. Early Education and Development. 2009;20:1016–1037. [Google Scholar]
  52. Collins WA, Laursen B. Parent-adolescent relationships and influences. In: Lerner R, Steinberg L, editors. Handbook of adolescent psychology. New York: Wiley; 2004. [Google Scholar]
  53. Commission on Social Determinants of Health. Closing the gap in a generation: Health equity through action on the social determinants of health. Final Report of the Commission on Social Determinants of Health. Geneva, Switzerland: World Health Organization; 2008. [Google Scholar]
  54. Conger RD, Ge X, Elder GH, Lorenz FO, Simons RL. Economic stress,coercive family process, and developmental problems of adolescents. Child Development. 1994;65:541–561. [PubMed] [Google Scholar]
  55. Conti-Ramsden G, Botting N. Emotional health in adolescents with and without a history of Specific Language Impairment (SLI) Journal of Child Psychology and Psychiatry. 2008;49:516–525. doi: 10.1111/j.1469-7610.2007.01858.x. [DOI] [PubMed] [Google Scholar]
  56. Cooley V, Henriksen L, Nelson C, Thompson J. A study to determine the effect of extracurricular participation on student alcohol and drug use in secondary schools. Journal of Alcohol and Drug Education. 1995;40:71–87. [Google Scholar]
  57. Cooley-Strickland M, Quille T, Griffin R, Stuart E, Bradshaw C, Furr-Holden D. Community violence and youth: affect, behavior, substance use, and academics. Clinical Child and Family Psychology Review. 2009;12:127–156. doi: 10.1007/s10567-009-0051-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Cooper H, Valentine JC, Nye B, Lindsay J. Relationships between five after-school activities and academic achievement. Journal of Educational Psychology. 1999;91:369–378. [Google Scholar]
  59. Costello EJ, Compton SN, Keeler G, Angold A. Relationships between poverty and psychopathology: A natural experiment. Journal of the American Medical Association. 2003;290:2023–2029. doi: 10.1001/jama.290.15.2023. [DOI] [PubMed] [Google Scholar]
  60. Council of Chief State School Officers. Beyond the health room. Washington, DC: Council of Chief State School Officers, Resource Center on Educational Equity; 1991. [Google Scholar]
  61. Crouter AC, Head MR. Parental monitoring and knowledge of children. In: Bornstein MH, editor. Handbook of parenting. 2nd ed. Mahwah, NJ: Erlbaum; 2002. pp. 461–483. [Google Scholar]
  62. Csikszentmihalyi M, Larson R. Being adolescent: Conflict and growth in the teenage years. New York: Basic Books; 1984. [Google Scholar]
  63. Cubbin C, Marchi K, Lin M, Bell T, Marshall H, Miller C, et al. Is neighborhood deprivation independently associated with maternal and infant health? Evidence from Florida and Washington. Maternal & Child Health Journal. 2008;12:61–74. doi: 10.1007/s10995-007-0225-0. [DOI] [PubMed] [Google Scholar]
  64. Cummings EM, El-Sheikh M, Kouros C, Buckhalt J. Children and violence: the role of children's regulation in the marital aggression-child adjustment link. Clinical Child and Family Psychology Review. 2009;12:3–15. doi: 10.1007/s10567-009-0042-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Cutrona CE, Wallace G, Wesner KA. Neighborhood characteristics and depression: an examination of stress processes. Current Directions in Psychological Science. 2006;15:188–192. doi: 10.1111/j.1467-8721.2006.00433.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Darling-Hamond L. Teacher quality and student academic achievement: A review of state policy evidence. Education Policy Archives. 2000;8:1–44. [Google Scholar]
  67. Davis B, Carpenter C. Proximity of fast-food restaurants to schools and adolescent obesity. American Journal of Public Health. 2009;99:505–510. doi: 10.2105/AJPH.2008.137638. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. DeLuca CR, Wood SJ, Anderson V, Buchanan JA, Proffitt TM, Mahony K, et al. Normative data from the CANTAB. I: development of executive function over the lifespan. Journal of Clinical and Experimental Neuropsychology. 2003;25:242–254. doi: 10.1076/jcen.25.2.242.13639. [DOI] [PubMed] [Google Scholar]
  69. DeNavas-Walt CP, Proctor BD, Smith JC. Income, poverty, and health insurance coverage in the United States 2008. Vol. 60. Washington, DC: US Census Bureau; 2009. p. 236. Current Population Reports, Available at http://www.census.gov/prod/2009pubs/p60-236.pdf. [Google Scholar]
  70. Denham SA, Blair KA, DeMulder E, Levitas J, Sawyer K, Auerbach-Major S, et al. Preschool emotional competence: Pathway to social competence. Child Development. 2003;74:238–256. doi: 10.1111/1467-8624.00533. [DOI] [PubMed] [Google Scholar]
  71. Dennison BA, Erb A, Jenkins PL. Television viewing and television in bedroom associated with overweight risk among low-income preschool children. Pediatrics. 2002;109:1028–1035. doi: 10.1542/peds.109.6.1028. [DOI] [PubMed] [Google Scholar]
  72. Dishion TJ, McMahon RJ. Parental monitoring and the prevention of child and adolescent problem behavior: a conceptual and empirical formulation. Clinical Child & Family Psychology Review. 1998;1:61–75. doi: 10.1023/a:1021800432380. [DOI] [PubMed] [Google Scholar]
  73. Dishion TJ, Shaw DS, Connell A, Gardner F, Weaver C, Wilson M. The Family Check-Up with high-risk indigent families: Outcomes of positive parenting and problem behavior from age 2 through 5. Child Development. 2008;79:1395–1414. doi: 10.1111/j.1467-8624.2008.01195.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Do DP, Finch BK, Basurto-Davila R, Bird C, Escarce J, Lurie N. Does place explain racial health disparities? Quantifying the contribution of residential context to the Black/White health gap in the United States. Social Science & Medicine. 2008;67:1258–1268. doi: 10.1016/j.socscimed.2008.06.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Dobbie W, Fryer RG., Jr . Are high-quality schools enough to close the achievement gap? Evidence from a bold social experiment in Harlem. Boston, MA: Harvard; 2009. [Google Scholar]
  76. Domitrovich C, Cortes R, Greenberg M. Improving young children's social and emotional competence: a randomized trial of the preschool •PATHS• curriculum. The Journal of Primary Prevention. 2007;28:67–91. doi: 10.1007/s10935-007-0081-0. [DOI] [PubMed] [Google Scholar]
  77. Dow WH, Schoeni RF, Adler NE, Stewart JC. Evaluating the evidence base: Policies and interventions to address socioeconomic status gradients in health. Annals of the New York Academy of Sciences. 2010;1186:240–251. doi: 10.1111/j.1749-6632.2009.05386.x. [DOI] [PubMed] [Google Scholar]
  78. Drukker M, Feron FJM, Mengelers R, Van Os J. Neighborhood socioeconomic and social factors and school achievement in boys and girls. The Journal of Early Adolescence. 2009;29:285–306. [Google Scholar]
  79. Du W, Finch CF, Hayen A, Bilston L, Brown J, Hatfield J. Relative benefits of population-level interventions targeting restraint-use in child car passengers. Pediatrics. 2010;125:304–312. doi: 10.1542/peds.2009-1171. [DOI] [PubMed] [Google Scholar]
  80. Duncan GJ, Yeung WJ, Brooks-Gunn J, Smith JR. How much does childhood poverty affect the life chances of children? American Sociological Review. 1998;63:406–423. [Google Scholar]
  81. Duncan SC, Duncan T, Strycker LA, Chaumeton NR. Relations between youth antisocial and prosocial activities. Journal of Behavioral Medicine. 2002;25:425–438. doi: 10.1023/a:1020466906928. [DOI] [PubMed] [Google Scholar]
  82. Dupéré V, Perkins DD. Community types and mental health: a multilevel study of local environmental stress and coping. American Journal of Community Psychology. 2007;39:107–119. doi: 10.1007/s10464-007-9099-y. [DOI] [PubMed] [Google Scholar]
  83. Durlak JA, DuPre EP. Implementation matters: A review of research on the influence of implementation on program outcomes and the factors affecting implementation. American Journal of Community Psychology. 2008;41:327–350. doi: 10.1007/s10464-008-9165-0. [DOI] [PubMed] [Google Scholar]
  84. Durlak JA, Taylor RD, Kawashima K, Pachan MK, DuPre EP, Celio CI, et al. Effects of positive youth development programs on school, family, and community systems. American Journal of Community Psychology. 2007;39:269–286. doi: 10.1007/s10464-007-9112-5. [DOI] [PubMed] [Google Scholar]
  85. Dziedzic B, Szemraj J, Bartkowiak J, Walczewska A. Various dietary fats differentially change the gene expression of neuropeptides involved in body weight regulation in rats. Journal of Neuroendocrinology. 2007;19:364–373. doi: 10.1111/j.1365-2826.2007.01541.x. [DOI] [PubMed] [Google Scholar]
  86. Eccles JS, Templeton J, Larson R. Extracurricular and other after-school activities for youth. Review of Research in Education. 2002;26:113–180. [Google Scholar]
  87. Egerter S, Braveman P, Sadegh-Nobari T, Grossman-Kahn R, Dekker M. Education matters for health. Robert Wood Johnson Foundation Commission to Build a Healthier America. Issue Brief 6: Education and Health. 2009 www.commissionhealth.org.
  88. Eiden RD, Edwards EP, Leonard KE. A conceptual model for the development of externalizing behavior problems among kindergarten children of alcoholic families: Role of parenting and children's self-regulation. Developmental Psychology. 2007;43:1187–1201. doi: 10.1037/0012-1649.43.5.1187. [DOI] [PMC free article] [PubMed] [Google Scholar]
  89. Embry DD. The good behavior game: A best practice candidate as a universal behavioral vaccine. Clinical Child and Family Psychology Review. 2002;5:273–297. doi: 10.1023/a:1020977107086. [DOI] [PubMed] [Google Scholar]
  90. Embry DD, Flannery DJ, Vazsonyi AT, Powell KE, Atha H. PeaceBuilders: A theoretically driven, school-based model for early violence prevention. American Journal of Preventive Medicine. 1996;12:91. [PubMed] [Google Scholar]
  91. Embry DD, Lopez D, Minugh PA. Stop the methamphetamine epidemic. Arizona Medical Association Journal. 2005;16:30–34. [Google Scholar]
  92. Environmental Protection Agency. [Last accessed February 16];EPA Asthma Fact Sheet. 2009 2010 at www.epa.gov/asthma/pdfs/asthma_fact_sheet_en.pdf.
  93. eSchoolNews: Technology News for Today’s K-20 Educator. Survey: school budget cuts even worse next year. 2010 Apr 9; Available at http://www.eschoolnews.com/2010/04/09/survey-school-budget-cuts-even-worse-next-year/
  94. Eyre H, Kahn R, Robertson RM ACS/ADA/AHA Collaborative Writing Committee. ACS/ADA/AHA Scientific statement preventing cancer, cardiovascular disease, and diabetes: A common agenda for the American Cancer Society, the American Diabetes Association, and the American Heart Association. Circulation. 2004;109:3244–3255. doi: 10.1161/01.CIR.0000133321.00456.00. [DOI] [PubMed] [Google Scholar]
  95. Farmer TW, Leung MC, Pearl R, Rodkin PC, Cadwallader TW, Van Acker R. Deviant of diverse peer groups? The peer affiliations of aggressive elementary students. Journal of Educational Psychology. 2002;94:611–620. [Google Scholar]
  96. Farrington DP. Predicting adult official and self-reported violence. In: Pinard GF, Pagani L, editors. Clinical assessment of dangerousness: Empirical contributions. New York: Cambridge University Press; 2001. pp. 66–88. [Google Scholar]
  97. Fashola OS. Review of extended-day and after-school programs and their effectiveness. Center for Research on the Education of Students Placed At Risk Report 24. US Department of Education. 1998 Available at www.csos.jhu.edu/crespar/techReports/Report24.pdf.
  98. Felner RD, Seitsinger AN, Brand S, Burns A, Bolton N. Creating small learning communities: Lessons from the project on high-performing learning communities about “what works” in creating productive, developmentally enhancing, learning contexts. Educational Psychologist. 2007;42:209–221. [Google Scholar]
  99. Fergusson D, Swain-Campbell N, Horwood J. How does childhood economic disadvantage lead to crime? Journal of Child Psychology & Psychiatry. 2004;45:956–966. doi: 10.1111/j.1469-7610.2004.t01-1-00288.x. [DOI] [PubMed] [Google Scholar]
  100. Fingerhut LA, Christoffel . The Future of Children (Special Issue: Children, Youth, & Gun Violence) Vol. 12. Princeton, NJ: Princeton University and The Brookings Institution; 2002. Firearm-related death and injury among children and adolescents. Available at http://futureofchildren.org/publications/journals/article/index.xml?journalid=42&articleid=163&sectionid=1048. [PubMed] [Google Scholar]
  101. Flay BR, Petraitis JM. The Theory of Triadic Influence: A new theory of health behavior with implications for preventive interventions. Advances in Medical Sociology. 1994;4:19–44. [Google Scholar]
  102. Flay BR, Biglan A, Boruch RF, Castro FG, Gottfredson D, Kellam S, et al. Standards of evidence: Criteria for efficacy, effectiveness, and dissemination. Prevention Science. 2005;6:151–175. doi: 10.1007/s11121-005-5553-y. [DOI] [PubMed] [Google Scholar]
  103. Flay BR, Biglan A, Komro KA, Wagenaar AC, Embry DD. The Promise Neighborhoods Research Consortium. Designs for evaluating comprehensive community interventions in neighborhoods and communities. Under review [Google Scholar]
  104. Flay BR, Snyder F, Petraitis J. The Theory of Triadic Influence. In: DiClemente RJ, Kegler MC, Crosby RA, editors. Emerging theories in health promotion practice and research. Second ed. New York: Jossey-Bass; 2009. pp. 451–510. [Google Scholar]
  105. Forehand R, Biggar H, Kotchick BA. Cumulative risk across family stressors: Short- and long-term effects for adolescents. Journal of Abnormal Child Psychology. 1998;26:119–128. doi: 10.1023/a:1022669805492. [DOI] [PubMed] [Google Scholar]
  106. Foster H, Brooks-Gunn J. Toward a stress process model of children's exposure to physical family and community violence. Clinical Child and Family Psychology Review. 2009;12:71–94. doi: 10.1007/s10567-009-0049-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  107. Frank LD, Andresen MA, Schmid TL. Obesity relationships with community design, physical activity, and time spent in cars. American Journal of Preventive Medicine. 2004;27:87–96. doi: 10.1016/j.amepre.2004.04.011. [DOI] [PubMed] [Google Scholar]
  108. Fredriksen K, Rhodes J, Reddy R, Way N. Sleepless in Chicago: tracking the effects of adolescent sleep loss during the middle school years. Child Development. 2004;75:84–95. doi: 10.1111/j.1467-8624.2004.00655.x. [DOI] [PubMed] [Google Scholar]
  109. French SA, Stables G. Environmental interventions to promote vegetable and fruit consumption among youth in school settings. Preventive Medicine. 2003;37:593–610. doi: 10.1016/j.ypmed.2003.09.007. [DOI] [PubMed] [Google Scholar]
  110. Fulkerson JA, Pasch KE, Perry CL, Komro K. Relationships between alcohol-related informal social control, parental monitoring, and adolescent problem behaviors among racially diverse urban youth. Journal of Community Health. 2008;33:425–433. doi: 10.1007/s10900-008-9117-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  111. Gale CR, Robinson SM, Godfrey KM, Law CM, Schlotz W, O'Callaghan FJ. Oily fish intake during pregnancy - association with lower hyperactivity but not with higher full-scale IQ in offspring. Journal of Child Psychology & Psychiatry. 2008;49:1061–1068. doi: 10.1111/j.1469-7610.2008.01908.x. [DOI] [PubMed] [Google Scholar]
  112. Gardner M, Roth J, Brooks-Gunn J. Adolescents’ participation in organized activities and developmental success two and eight years after high school: Do sponsorship, duration, and intensity matter? Developmental Psychology. 2008;44:813–840. doi: 10.1037/0012-1649.44.3.814. [DOI] [PubMed] [Google Scholar]
  113. Gephart MA. Neighborhoods and communities as contexts for development. In: Brooks-Gunn J, Duncan GJ, Aber JL, editors. Neighborhood poverty, Volume I: Contexts and consequences for children. New York: Sage; 1997. pp. 1–43. [Google Scholar]
  114. Gerber S. Extracurricular activities and academic achievement. Journal of Research and Development in Education. 1996;30:50. [Google Scholar]
  115. Gershoff ET, Aber JL, Raver CC, Lennon MC. Income is not enough: Incorporating material hardship into models of income associations with parenting and child development. Child Development. 2007;78:70–95. doi: 10.1111/j.1467-8624.2007.00986.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  116. Giedd JN. Structural magnetic resonance imaging of the adolescent brain. In: Dahl RE, Spear LP, editors. Adolescent brain development: Vulnerabilities and opportunities. New York: New York Academy of Sciences; 2004. pp. 77–85. [DOI] [PubMed] [Google Scholar]
  117. Giordano P. Relationships in adolescence. Annual Review of Sociology. 2003;29:257–281. [Google Scholar]
  118. Glanz K, Yaroch AL. Strategies for increasing fruit and vegetable intake in grocery stores and communities: policy, pricing and environmental change. Preventive Medicine. 2004;39(S2):75–80. doi: 10.1016/j.ypmed.2004.01.004. [DOI] [PubMed] [Google Scholar]
  119. Gorey KM. Early childhood education: A meta-analytic affirmation of the short- and long-term benefits of educational opportunity. School Psychology Quarterly. 2001;16:9–30. [Google Scholar]
  120. Gray MR, Steinberg L. Unpacking authoritative parenting: reassessing a multidimensional construct. Journal of Marriage and the Family. 1999;61:574–586. [Google Scholar]
  121. Hackbarth DP, Schnopp-Wyatt D, Katz D, Williams J, Silvestri B, Pfleger M. Collaborative research and action to control the geographic placement of outdoor advertising of alcohol and tobacco products in Chicago. Public Health Reports. 2001;116:558–567. doi: 10.1016/S0033-3549(04)50088-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  122. Hackbarth DP, Silvestri B, Cosper W. Tobacco and alcohol billboards in 50 Chicago neighborhoods: market-segmentation to sell dangerous products to the poor. Journal of Public Health Policy. 1995;16:213–230. [PubMed] [Google Scholar]
  123. Haines MM, Stansfeld SA, Head J, Job RFS. Multilevel modeling of aircraft noise on performance tests in schools around Heathrow Airport London. Journal of Epidemiology and Community Health. 2002;56:139–144. doi: 10.1136/jech.56.2.139. [DOI] [PMC free article] [PubMed] [Google Scholar]
  124. Hall HI, Song R, Rhodes P, Prejean J, An Q, Lee LM, et al. Estimation of HIV incidence in the United States. JAMA: Journal of the American Medical Association. 2008;300:520–529. doi: 10.1001/jama.300.5.520. [DOI] [PMC free article] [PubMed] [Google Scholar]
  125. Hallfors DD, Iritani BJ, Miller WC, Bauer DJ. Sexual and drug behavior patterns and HIV and STD racial disparities: The need for new directions. American Journal of Public Health. 2007;97:125–132. doi: 10.2105/AJPH.2005.075747. [DOI] [PMC free article] [PubMed] [Google Scholar]
  126. Hankins FM, Biglan A. The relationship of prosociality to psychological and behavioral problems among early adolescents. In preparation. [Google Scholar]
  127. Harding DJ. Counterfactual models of neighborhood effects: The effect of neighborhood poverty on dropping out and teenage pregnancy. American Journal of Sociology. 2003;109:676–719. [Google Scholar]
  128. Harrell JP, Hall S, Taliaferro J. Physiological responses to racism and discrimination: an assessment of the evidence. American Journal of Public Health. 2003;93:243–248. doi: 10.2105/ajph.93.2.243. [DOI] [PMC free article] [PubMed] [Google Scholar]
  129. Hawkins JD, Catalano RF, Miller JY. Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: Implications for substance abuse prevention. Psychological Bulletin. 1992;112:64–105. doi: 10.1037/0033-2909.112.1.64. [DOI] [PubMed] [Google Scholar]
  130. Heath GW, Brownson RC, Kruger J, Miles R, Powell KE, Ramsey LT. The effectiveness of urban design and land use and transport policies and practices to increase physical activity: a systematic review. Journal of Physical Activity & Health. 2006;3:S55–S76. doi: 10.1123/jpah.3.s1.s55. [DOI] [PubMed] [Google Scholar]
  131. Heckman J, Grunewald R, Reynolds A. The dollars and cents of investing early: cost-benefit analysis in early care and education. Zero to Three. 2006;26:10–17. [Google Scholar]
  132. Helland IB, Smith L, Saarem K, Saugstad OD, Drevon CA. Maternal supplementation with very-long-chain n-3 fatty acids during pregnancy and lactation augments children's IQ at 4 years of age. Pediatrics. 2003;111:e39–e44. doi: 10.1542/peds.111.1.e39. [DOI] [PubMed] [Google Scholar]
  133. Hepburn LM, Hemenway D. Firearm availability and homicide: a review of the literature. Aggression and Violent behavior. 2004;9:417–440. [Google Scholar]
  134. Heron M. Deaths: leading causes for 2004. National Vital Statistics Reports. 2007;56:1–96. [PubMed] [Google Scholar]
  135. Hibbeln JR, Davis JM, Steer C, Emmett P, Rogers I, Williams C, et al. Maternal seafood consumption in pregnancy and neurodevelopmental outcomes in childhood (ALSPAC study): An observational cohort study. Lancet. 2007;369:578–585. doi: 10.1016/S0140-6736(07)60277-3. [DOI] [PubMed] [Google Scholar]
  136. Hibbeln JR, Nieminen LRG, Blasbalg TL, Riggs JA, Lands WEM. Healthy intakes of n-3 and n-6 fatty acids: estimations considering worldwide diversity. American Journal of Clinical Nutrition. 2006;83:1483S–1394S. doi: 10.1093/ajcn/83.6.1483S. [DOI] [PubMed] [Google Scholar]
  137. Hopf WH, Huber GL, Weiß RH. Media violence and youth violence: A 2-year longitudinal study. Journal of Media Psychology: Theories, Methods, and Applications. 2008;20:79–96. [Google Scholar]
  138. Huesmann LR, Lagerspetz K, Eron LD. Intervening variables in the TV violence-coaggression relation: Evidence from two countries. Developmental Psychology. 1984;20:746–775. [Google Scholar]
  139. Hurd N, Zimmerman M, Yange X. Negative adult influences and the protective effects of role models: a study with urban adolescents. Journal of Youth & Adolescence. 2009;38:777–789. doi: 10.1007/s10964-008-9296-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  140. Institute of Medicine. Health insurance is a family matter. 2002 Available at http://books.nap.edu/openbook.php?record_id=10503&page=1.
  141. Irwin LG, Siddiqi A, Hertzman C. Early child development: A powerful equalizer. Final Report to the World Health Organization’s Commission on the Social Determinants of Health. Vancouver, BC, Canada: Early Child Development Knowledge Network; 2007. [Google Scholar]
  142. Jackman T. Police chiefs feel pinch of budget cuts. Washington Post, Section A. 2010 Sep; Available at http://www.washingtonpost.com/wp-dyn/content/article/2010/09/29/AR2010092907702.html?referrer=emailarticle.
  143. Jackson C. Perceived legitimacy of parental authority and tobacco and alcohol use during early adolescence. Journal of Adolescent Health. 2002;31:425–432. doi: 10.1016/s1054-139x(02)00398-1. [DOI] [PubMed] [Google Scholar]
  144. Jackson C, Henriksen L, Foshee VA. The Authoritative Parenting Index: predicting health risk behaviors among children and adolescents. Health Education behavior. 1998;25:319–337. doi: 10.1177/109019819802500307. [DOI] [PubMed] [Google Scholar]
  145. Jessor R, Turbin MS, Costa FM. Protective factors in adolescent health behavior. Journal of Personality and Social Psychology. 1998;75:788–800. doi: 10.1037//0022-3514.75.3.788. [DOI] [PubMed] [Google Scholar]
  146. Jia Y, Way N, Ling G, Yoshikawa H, Chen X, Hughes D, et al. The influence of student perceptions of school climate on socioemotional and academic adjustment: A comparison of Chinese and American adolescents. Child Development. 2009;80:1514–1530. doi: 10.1111/j.1467-8624.2009.01348.x. [DOI] [PubMed] [Google Scholar]
  147. Joe S, Joe E, Rowley LL. Consequences of physical health and mental illness risks for academic achievement in grades K-12. Review of Research in Education. 2009;33:283–309. [Google Scholar]
  148. Johnson BD, Ream GL, Dunlap E, Sifaneck SJ. Civic norms and etiquettes regarding marijuana use in public settings in New York City. Substance Use & Misuse. 2008;43:895–918. doi: 10.1080/10826080701801477. [DOI] [PMC free article] [PubMed] [Google Scholar]
  149. Johnson N, Oliff P, Williams E. An update on state budget cuts: At least 46 states have imposed cuts that hurt vulnerable residents and the economy. Washington, DC: Center on Budget and Policy Priorities; 2010. http://www.cbpp.org/cms/?fa=view&id=1214. [Google Scholar]
  150. Jordan WJ, Nettles SM. How students invest their time outside of school: Effects on school-related outcomes. Social Psychology of Education. 2000;3:217–243. [Google Scholar]
  151. Juel C. Learning to read and write: A longitudinal study of 54 children from first through fourth grades. Journal of Educational Psychology. 1988;80:437–447. [Google Scholar]
  152. Jusko TA, Henderson CR, Lanphear BP, Cory-Slechta DA, Parsons PJ, Canfield RL. Blood lead concentrations < 10 microg/dL and child intelligence at 6 years of age. Environmental Health Perspectives. 2008;116:243–248. doi: 10.1289/ehp.10424. [DOI] [PMC free article] [PubMed] [Google Scholar]
  153. Kame'enui EJ, Simmons DC, Baker SK, Chard DJ, Dickson SV, Gunn BK . Effective strategies for accommodating diverse learners. In: Kame'enui EJ, Carnine DW, editors. Effective strategies for accommodating diverse learners. Alexandria, VA: ASCD; 1995. [Google Scholar]
  154. Kame’enui EJ, Simmons DC, Baker SK, Chard DJ, Dickson SV, Gunn BK, et al. Effective strategies for teaching beginning reading. In: Kame'enui EJ, Carnine DW, editors. Effective strategies that accommodate diverse learners. Columbus, OH: Merrill; 1998. pp. 45–70. [Google Scholar]
  155. Kane T. The impact of after school programs: interpreting the results of four recent evaluations. 2004 Working paper of the William T. Grant Foundation. Available at www.wtgrantfoundation.org/usr_doc/After-school_paper.pdf.
  156. Kelly B, Cretikos M, Rogers K, King L. The commercial food landscape: outdoor food advertising around primary schools in Australia. Australian and New Zealand Journal of Public Health. 2008;32:522–528. doi: 10.1111/j.1753-6405.2008.00303.x. [DOI] [PubMed] [Google Scholar]
  157. Kim TE, Guerra NG, Williams KR. Preventing youth problem behaviors and enhancing physical health by promoting core competencies. Journal of Adolescent Health. 2008;43:401–107. doi: 10.1016/j.jadohealth.2008.02.012. [DOI] [PubMed] [Google Scholar]
  158. Kirby D. The impact of schools and school programs upon adolescent sexual behavior. Journal of Sex Research. 2002;39:27–33. doi: 10.1080/00224490209552116. [DOI] [PubMed] [Google Scholar]
  159. Kochanska G, Murray KT, Harlan ET. Effortful control in early childhood: Continuity and change, antecedents, and implications for social development. Developmental Psychology. 2000;36:220–232. [PubMed] [Google Scholar]
  160. Komro KA, Perry CL, Williams CL, Stigler MH, Farbakhsh K, Veblen-Mortenson S. How did Project Northland reduce alcohol use among young adolescents? Analysis of mediating variables. Health Education Research. 2001;16:59–70. doi: 10.1093/her/16.1.59. [DOI] [PubMed] [Google Scholar]
  161. Lamberty G, Pachter LM, Crnic K. Role of Partnerships: Second Annual Meeting of Child Health Services Researchers. Rockville, MD: Agency for Healthcare Research and Quality; 2000. Social stratification: implications for understanding racial, ethnic and class disparities in child health and development. Available at: http://www.ahrq.gov/research/chsr2soc.htm. [Google Scholar]
  162. Landers D, Landers D. Socialization via interscholastic athletics: Its effects on delinquency. Sociology of Education. 1978;51:299–303. [Google Scholar]
  163. Larson NI, Story MT, Nelson MC. Neighborhood environments: Disparities in access to healthy foods in the U.S. Journal of Preventive Medicine. 2009;36:74–81. doi: 10.1016/j.amepre.2008.09.025. [DOI] [PubMed] [Google Scholar]
  164. Larson R, Richards MH. Daily companionship in late childhood and early adolescence: Changing developmental contexts. Child Development. 1991;62:284–300. doi: 10.1111/j.1467-8624.1991.tb01531.x. [DOI] [PubMed] [Google Scholar]
  165. Lauer PA, Akiba M, Wilderson SB, Apthorp HS, Snow D, Martin-Glenn M. The effectiveness of out-of-school time strategies in assisting low-achieving students in reading and mathematics: A research synthesis. Aurora, CO: Mid-Continent Research for Education and Learning; 2004. [Google Scholar]
  166. Lenhart A, Madden M, Hitlin P. Teens and technology: youth are leading the transition to a fully wired and mobile nation. Washington, DC: Pew Internet & American Life Project; 2005. Available at http://www.pewinternet.org/pdfs/PIP_Teens_Tech_July2005web.pdf. [Google Scholar]
  167. Lerner RM, Lerner JV, Almerigi JB, Theokas C, Phelps E, Gestsdottir S, et al. Positive youth development, participation in community youth development programs, and community contributions of fifth-grade adolescents: Findings from the first wave of the 4-H study of positive youth development. Journal of Early Adolescence. 2005;25:17–71. [Google Scholar]
  168. Leventhal T, Brooks-Gunn J. A randomized study of neighborhood effects on low-income children's educational outcomes. Developmental Psychology. 2004;40:488–507. doi: 10.1037/0012-1649.40.4.488. [DOI] [PubMed] [Google Scholar]
  169. Leventhal T, Brooks-Gunn J. The neighborhoods they live in: The effects of neighborhood residence on child and adolescent outcomes. Psychological Bulletin. 2000;126:309–337. doi: 10.1037/0033-2909.126.2.309. [DOI] [PubMed] [Google Scholar]
  170. Lima J, Caughy M, Nettles SM, O'Campo PJ. Effects of cumulative risk on behavioral and psychological well-being in first grade: Moderation by neighborhood context. Social Science & Medicine. 2010;71:1447–1454. doi: 10.1016/j.socscimed.2010.06.022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  171. Linares LO, Hereen T, Bronfman E, Zuckerman B, Augustyn M, Tronick E. A mediational model for the impact of exposure to community violence on early child behavior problems. Child Development. 2001;72:639–652. doi: 10.1111/1467-8624.00302. [DOI] [PubMed] [Google Scholar]
  172. Lindsay AC, Sussner KM, Kim J, Gortmaker S. The role of parents in preventing childhood obesity. The Future of Children. 2006;16:169–186. doi: 10.1353/foc.2006.0006. [DOI] [PubMed] [Google Scholar]
  173. Lipman EL, Offord DR, Boyle MH. Relation between economic disadvantage and psychosocial morbidity in children. Canadian Medical Association Journal. 1994;151:431–437. [PMC free article] [PubMed] [Google Scholar]
  174. Loeber R. The stability of antisocial and delinquent child behavior: A review. Child Development. 1982;53:1431–1446. [PubMed] [Google Scholar]
  175. Maddock J, Takeuchi L, Nett B, Tanaka C, Irvin L, Matsuoka C, et al. Evaluation of a statewide program to reduce chronic disease: The Healthy Hawaii Initiative, 2000–2004. Evaluation and Program Planning. 2006;29:293–300. [Google Scholar]
  176. Maher A, Wilson N, Signal L. Advertising and availability of 'obesogenic' foods around New Zealand secondary schools: a pilot study. The New Zealand Medical Journal. 2005;118:U1556. [PubMed] [Google Scholar]
  177. Mahoney J, Cairns R. Do extracurricular activities protect against early school dropout? Developmental Psychology. 1997;33:241–253. doi: 10.1037//0012-1649.33.2.241. [DOI] [PubMed] [Google Scholar]
  178. Marsh H. Extracurricular activities: Beneficial extension of the traditional curriculum or subversion of academic goals? Journal of Educational Psychology. 1992;84:553–562. [Google Scholar]
  179. Mayer GR. Preventing antisocial behavior in the schools. Journal of Applied Behavior Analysis. 1995;28:467–478. doi: 10.1901/jaba.1995.28-467. [DOI] [PMC free article] [PubMed] [Google Scholar]
  180. Mayer GR, Butterworth TW, Nafpaktitis M, Sulzer-Azaroff B. Preventing school vandalism and improving discipline: A three-year study. Journal of Applied Behavior Analysis. 1983;16:355–369. doi: 10.1901/jaba.1983.16-355. [DOI] [PMC free article] [PubMed] [Google Scholar]
  181. McEvoy AA, Welker R. Antisocial behavior, academic failure, and school climate: A critical review. Journal of Emotional and Behavioral Disorders. 2000;8:130–140. [Google Scholar]
  182. McMahon SD, Felix ED, Halpert JA, Petropoulos LAN. Community violence exposure and aggression among urban adolescents: testing a cognitive mediator model. Journal of Community Psychology. 2009;37:895–910. [Google Scholar]
  183. McNeely CA, Nonnemaker JM, Blum RW. Promoting school connectedness: Evidence from the national longitudinal study of adolescent health. Journal of School Health. 2002;72:138–146. doi: 10.1111/j.1746-1561.2002.tb06533.x. [DOI] [PubMed] [Google Scholar]
  184. Miller M, Azrael D, Hemenway D. Firearm availability and unintentional firearm deaths, suicide, and homicide among 5–14 year olds. Journal of Trauma. 2002;52:267–275. doi: 10.1097/00005373-200202000-00011. [DOI] [PubMed] [Google Scholar]
  185. Mitchell O, Greenberg M. Outdoor advertising of addictive products. New Jersey Medicine: The Journal of The Medical Society of New Jersey. 1991;88:331–333. [PubMed] [Google Scholar]
  186. Muro M, Hoene CW. Fiscal challenges facing cities: Implications for recovery. 2009 Available at http://www.nlc.org/ASSETS/…/LocalFiscalBrief_11-17_FINAL.pdf.
  187. Mustard JF. Experience-based brain development: Scientific underpinnings of the importance of early child development in a global world. Paediatrics and Child Health. 2006;11:571–572. doi: 10.1093/pch/11.9.571. [DOI] [PMC free article] [PubMed] [Google Scholar]
  188. Nadeau K, Dabelea D. Epidemiology of type 2 diabetes in children and adolescents. Endocrine Research. 2008;33:35–58. doi: 10.1080/07435800802080138. [DOI] [PubMed] [Google Scholar]
  189. Najman JM, Hayatbakhsh MR, Heron MA, Bor W, O'Callaghan MJ, Williams GM. Impact of episodic and chronic poverty on child cognitive development. Journal of Pediatrics. 2009;154:284–289. doi: 10.1016/j.jpeds.2008.08.052. [DOI] [PubMed] [Google Scholar]
  190. Nation K. Reading comprehension and vocabulary: What's the connection? In: Wagner RK, Schatschneider C, Phythian-Sence C, editors. Beyond decoding: The behavioral and biological foundations of reading comprehension. New York: Guilford; 2009. pp. 176–194. [Google Scholar]
  191. National Center for Health Statistics. Health, United States, 2009, with Special Feature on Medical Technology. 2010:2010–1232. http://www.cdc.gov/nchs/data/hus/hus09.pdf. [PubMed]
  192. National Conference of State Legislatures. Projected revenue growth in fiscal year 2010. 2009 Oct; Available at http://www.ncsl.org/documents/fiscal/ProjectedRevenueGrowth_October2009.pdf.
  193. National Institutes of Health. Research results for the public: Type 2 Diabetes. 2008 Available at www.nih.gov/about/researchresultsforthepublic/Type2Diabetes.pdf.
  194. National Research Council & Institute of Medicine. From neurons to neighborhoods: the science of early childhood development. Committee on Integrating the Science of Early Childhood Development; 2000. Available at http://www.nap.edu/openbook.php?record_id=9824&page=1. [Google Scholar]
  195. National Research Council & Institute of Medicine. Preventing mental, emotional, and behavioral disorders among young people: progress and possibilities. Committee on Prevention of Mental Disorders and Substance Abuse Among Children, Youth, and Young Adults: Research Advances and Promising Interventions. Washington, DC: The National Academies Press; 2009. [PubMed] [Google Scholar]
  196. National Research Council, Institute of Medicine, & Committee on Evaluation of Children's Health. Children's health, the nation's wealth: Assessing and improving child health. Washington, DC: National Academies Press; 2004. [Google Scholar]
  197. Needham BL, Crosnoe R, Muller RC. Academic failure in secondary school: The inter-related role of health problems and educational context. Social Problems. 2004;51:569–586. doi: 10.1525/sp.2004.51.4.569. [DOI] [PMC free article] [PubMed] [Google Scholar]
  198. Nigg JT, Knottnerus GM, Martel MM, Nikolas M, Cavanagh K, Karmaus W, et al. Low blood lead levels associated with clinically diagnosed attention-deficit/hyperactivity disorder and mediated by weak cognitive control. Biological Psychiatry. 2008;63:325–331. doi: 10.1016/j.biopsych.2007.07.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  199. O'Brien EM, Mindell JA. Sleep and risk-taking behavior in adolescents. Behavioral Sleep Medicine. 2005;3:113–133. doi: 10.1207/s15402010bsm0303_1. [DOI] [PubMed] [Google Scholar]
  200. Odgers CL, Moffitt TE, Broadbent JM, Dickson N, Hancox RJ, Harrington H, et al. Female and male antisocial trajectories: From childhood origins to adult outcomes. Development and Psychopathology. 2008;20:673–716. doi: 10.1017/S0954579408000333. [DOI] [PubMed] [Google Scholar]
  201. Olson ME, Diekema D, Elliott BA, Renier CM. Impact of income and income inequality on infant health outcomes in the United States. Pediatrics. 2010;126:1165–1176. doi: 10.1542/peds.2009-3378. [DOI] [PubMed] [Google Scholar]
  202. Pachter LM, Coll CG. Racism and child health: a review of the literature and future directions. Journal of Developmental and Behavioral Pediatrics. 2009;30:255–263. doi: 10.1097/DBP.0b013e3181a7ed5a. [DOI] [PMC free article] [PubMed] [Google Scholar]
  203. Parke RD, Buriel R. Socialization in the family: Ethnic and ecological perspectives. In: Damon W, Eisenberg N, editors. Handbook of child psychology. 5th ed. Vol. 3. New York: Wiley; 1998. pp. 463–552. [Google Scholar]
  204. Parsons S, Bynner J. Numeracy and employment. Education & Training. 1997;39:43–51. [Google Scholar]
  205. Pasch KE, Komro KA, Perry CL, Hearst MO, Farbakhsh K. Does outdoor alcohol advertising around elementary schools vary by the ethnicity of students in the school? Ethnicity & Health. 2009;14:225–236. doi: 10.1080/13557850802307809. [DOI] [PMC free article] [PubMed] [Google Scholar]
  206. Pasch KE, Laska MN, Lytle LA, Moe SG. Adolescent sleep, risk behaviors, and depressive symptoms: Are they linked? American Journal of Health Behavior. 2010;34:237–248. doi: 10.5993/ajhb.34.2.11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  207. Patterson GR, Stouthamer-Loeber M. The correlation of family management practices and delinquency. Child Development. 1984;55:1299–1307. [PubMed] [Google Scholar]
  208. Patterson GR, Dishion TJ, Bank L. Family interaction: A process model of deviancy training. Aggressive behavior. 1984;10:253–267. [Google Scholar]
  209. Pearson N, Biddle SJ, Gorely T. Family correlates of fruit and vegetable consumption in children and adolescents: a systematic review. Public Health Nutrition. 2009;12:267–283. doi: 10.1017/S1368980008002589. [DOI] [PubMed] [Google Scholar]
  210. Pianta RC, Barnett WS, Burchinal MR, Thornburg KR. The effects of preschool education: What we know, how public policy is or is not aligned with the evidence base, and what we need to know. Psychological Science in the Public Interest. 2009;10:49–88. doi: 10.1177/1529100610381908. [DOI] [PubMed] [Google Scholar]
  211. Pickett KE, Wilkinson RG. People like us: ethnic group density effects on health. Ethnicity & Health. 2008;13:321–334. doi: 10.1080/13557850701882928. [DOI] [PubMed] [Google Scholar]
  212. Popova S, Giesbrecht N, Bekmuradov D, Patra J. Hours and days of sale and density of alcohol outlets: Impacts on alcohol consumption and damage: a systematic review. Alcohol and Alcoholism. 2009;44:500–516. doi: 10.1093/alcalc/agp054. [DOI] [PubMed] [Google Scholar]
  213. Posner MI, Rothbart MK. Developing mechanisms of self-regulation. Development and Psychopathology. 2000;12:427–441. doi: 10.1017/s0954579400003096. [DOI] [PubMed] [Google Scholar]
  214. Powell LM, Chaloupka FJ, Bao Y. The availability of fast food and full-service restaurants in the United States: Associations with neighborhood characteristics. American Journal of Preventive Medicine. 2007;33:S240–S245. doi: 10.1016/j.amepre.2007.07.005. [DOI] [PubMed] [Google Scholar]
  215. Pujazon-Zazik M, Park MJ. To tweet, or not to tweet: gender differences and potential positive and negative health outcomes of adolescents' social internet use. American Journal of Men's Health. 2010;4:77–85. doi: 10.1177/1557988309360819. [DOI] [PubMed] [Google Scholar]
  216. Rampersaud GC, Pereira MA, Girard BL, Adams J, Metzl JD. Breakfast habits, nutritional status, body weight, and academic performance in children and adolescents. Journal of the American Dietetic Association. 2005;105:743–760. doi: 10.1016/j.jada.2005.02.007. [DOI] [PubMed] [Google Scholar]
  217. Rank MR, Hirschl TA. The occurrence of poverty across the life cycle: Evidence from the PSID. Journal of Policy Analysis and Management. 2001;20:737–755. [Google Scholar]
  218. Rank MR, Yoon HS, Hirschl TA. American poverty as a structural failing: evidence and arguments. Journal of Sociology & Social Welfare. 2003;30:3–29. [Google Scholar]
  219. Rasmussen M, Krolner R, Klepp KI, Lytle L, Brug J, Bere E, et al. Determinants of fruit and vegetable consumption among children and adolescents: a review of the literature. Part I: quantitative studies. International Journal of Behavioral Nutrition and Physical Activity. 2006;3:22. doi: 10.1186/1479-5868-3-22. Available at http://www.ijbnpa.org/content/3/1/22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  220. Ratcliffe C, McKernan S-M. Childhood poverty persistence: Facts and consequences, Brief 14. Washington, DC: The Urban Institute; 2010. [Google Scholar]
  221. Ream RK, Rumberger RW. Student engagement, peer social capital, and school dropout among Mexican American and non-Latino white students. Sociology of Education. 2008;81:109–139. [Google Scholar]
  222. Resnick MD, Bearman PS, Blum RW, Bauman KE, Harris KM, Jones J, et al. Protecting adolescents from harm: Findings from the National Longitudinal Study on Adolescent Health. Journal of the American Medical Association. 1997;278:823–832. doi: 10.1001/jama.278.10.823. [DOI] [PubMed] [Google Scholar]
  223. Richardson JL, Radziszewska B, Dent CW, Flay BR. Relationship between after-school care of adolescents and substance use, risk-taking, depressed mood, and academic-achievement. Pediatrics. 1993;92:32–38. [PubMed] [Google Scholar]
  224. Richter L, Richter DM. Exposure to parental tobacco and alcohol use: effects on children's health and development. American Journal of Orthopsychiatry. 2001;71:182–203. doi: 10.1037/0002-9432.71.2.182. [DOI] [PubMed] [Google Scholar]
  225. Roth J, Brooks-Gunn J. What do adolescents need for healthy development? Implications for youth policy. Ann Arbor, MI: Society for Research in Child Development; 2000. Social Policy Report. [Google Scholar]
  226. Roth J, Brooks-Gunn J, Murray L, Foster W. Promoting healthy adolescents: Synthesis of youth development program evaluations. Journal of Research on Adolescence. 1998;8:423–459. [Google Scholar]
  227. Rowe F, Stewart S. Promoting connectedness through whole-school approaches: a qualitative study. Health Education. 2009;109:396–413. [Google Scholar]
  228. Rumberger RW. Dropping out of middle school: A multilevel analysis of students and schools. American Educational Research Journal. 1995;32:583–625. [Google Scholar]
  229. Rutter M, Maughan B. School effectiveness findings 1979–2002. Journal of School Psychology. 2002;40:451–475. [Google Scholar]
  230. Sabo DF, Miller KE, Farrell MP, Melnick MJ, Barnes GM. High school athletic participation, sexual behavior, and adolescent pregnancy: a regional study. Journal of Adolescent Health. 1999;25:207–216. doi: 10.1016/s1054-139x(99)00070-1. [DOI] [PubMed] [Google Scholar]
  231. Sampson RJ. Racial stratification and the durable tangle of neighborhood inequality. Annals of the American Academy of Political and Social Science. 2009;621:260–280. [Google Scholar]
  232. Sampson RJ, Morenoff JD, Gannon-Rowley T. Assessing “neighborhood effects”: Social processes and new directions in research. Annual Review of Sociology. 2002;28:443–478. [Google Scholar]
  233. Sampson RJ, Raudenbush SW, Earls F. Neighborhoods and violent crime: A multilevel study of collective efficacy. Science. 1997;277:918–924. doi: 10.1126/science.277.5328.918. [DOI] [PubMed] [Google Scholar]
  234. Schoenwald SK, Kelleher K, Weisz JR. Building bridges to evidence-based practice: The MacArthur Foundation Child System and Treatment Enhancement Projects (Child STEPs) Administration and Policy in Mental Health and Mental Health Services Research. 2008;35:66–72. doi: 10.1007/s10488-007-0160-9. [DOI] [PubMed] [Google Scholar]
  235. Sellers RM, Copeland-Linder N, Martin PP, Lewis RL. Racial identity matters: the relationship between racial discrimination and psychological functioning in African American adolescents. Journal of Research on Adolescence. 2006;16:187–216. [Google Scholar]
  236. Shaywitz SE, Shaywitz BA. Learning disabilities and attention deficits in the school setting. In: Meltzer LJ, editor. Strategy assessment and instruction for students with learning disabilities: From theory to practice. Austin, TX US: PRO-ED; 1993. pp. 221–245. [Google Scholar]
  237. Shield BM, Dockrell JE. The effects of environmental and classroom noise on the academic attainments of primary school children. The Journal of the Acoustical Society of America. 2008;123:133–144. doi: 10.1121/1.2812596. [DOI] [PubMed] [Google Scholar]
  238. Shulman LS. Knowledge and teaching: Foundations of the new reform. Harvard Educational Review. 1987;57:1–22. [Google Scholar]
  239. Shumow L, Vandell DL, Posner J. Risk and resilience in the urban neighborhood: Predictors of academic performance among low-income elementary school children. Merrill-Palmer Quarterly: Journal of Developmental Psychology. 1999;45:309–331. [Google Scholar]
  240. Sichko A. Eight area state parks to close: no budget, no funding. The Business Review. 2010 May; Available at http://albany.bizjournals.com/albany/stories/2010/05/17/daily4.html.
  241. Silver D, Mijanovich T, Uyei T, Kapadia F, Weitzman BC. Lifting boats not closing gaps: Child health outcomes in distressed cities 1992–2002. American Journal of Public Health. 2011;101:278–284. doi: 10.2105/AJPH.2010.194761. [DOI] [PMC free article] [PubMed] [Google Scholar]
  242. Simons-Morton B, Hartos J. Application of the Authoritative Parenting Model to adolescent health behavior. In: DiClemente RJ, Crosby RA, Kegler MC, editors. Emerging theories in health promotion practice and research. San Francisco: Jossey-Bass; 2002. pp. 100–125. [Google Scholar]
  243. Skiba RJ, Peterson RL. The dark side of zero tolerance: Can punishment lead to safe schools? Phi Delta Kappan. 1999;80:372–376. [Google Scholar]
  244. Skiba RJ, Peterson RL. School discipline at a crossroads: From zero tolerance to early response. Exceptional Children. 2000;66:335–396. [Google Scholar]
  245. Slavin RE. Students motivating students to excel: Cooperative incentives, cooperative tasks, and student achievement. The Elementary School Journal. 1984;85:53–63. [Google Scholar]
  246. Slavin RE. Quality, appropriateness, incentive, and time: A model of instructional effectiveness. International Journal of Educational Research. 1994;21:141–157. [Google Scholar]
  247. Smeeding TM, Rainwater L, Burtless G. United States poverty in a cross-national context. In: Danziger SH, Haveman RH, editors. Understanding poverty. New York: Sage; Cambridge, MA: Harvard University Press; 2001. pp. 162–189. [Google Scholar]
  248. Smith P, Flay BR, Bell CC, Weissberg RP. The protective influence of parents and peers in violence avoidance among African-American youth. Maternal & Child Health Journal. 2001;5:245. doi: 10.1023/a:1013080822309. [DOI] [PubMed] [Google Scholar]
  249. Snowling AJ, Bishop DVM, Stothard SE, Chipchase B, Kaplan C. Psychosocial outcomes at 15 years of children with a preschool history or speech-language impairment. Journal of Child Psychology and Psychiatry. 2006;47:759–765. doi: 10.1111/j.1469-7610.2006.01631.x. [DOI] [PubMed] [Google Scholar]
  250. Sorensen G, Stoddard AM, Dubowitz T, Barbeau EM, Bigby J, Emmons KM, et al. The influence of social context on changes in fruit and vegetable consumption: results of the Healthy Directions Studies. American Journal of Public Health. 2007;97:1216–1227. doi: 10.2105/AJPH.2006.088120. [DOI] [PMC free article] [PubMed] [Google Scholar]
  251. Spera C. A review of the relationship among parenting practices, parenting styles, and adolescent school achievement. Educational Psychology Review. 2005;17:125–146. [Google Scholar]
  252. Strauch I, Meier B. Sleep need in adolescents: a longitudinal approach. Sleep. 1988;11:378–386. doi: 10.1093/sleep/11.4.378. [DOI] [PubMed] [Google Scholar]
  253. Sugai G, Horner RH. Introduction to the special series on positive behavior supports in schools. Journal of Emotional and Behavioral Disorders. 2002;10:130–135. [Google Scholar]
  254. Sugai G, Horner R. What we know and need to know about preventing problem behavior in schools. Exceptionality. 2008;16:67–77. [Google Scholar]
  255. Suglia SF, Gryparis A, Wright RO, Schwartz J, Wright RJ. Association of black carbon with cognition among children in a prospective birth cohort study. American Journal of Epidemiology. 2008;167:280–286. doi: 10.1093/aje/kwm308. [DOI] [PubMed] [Google Scholar]
  256. Suss AL, Tinkelman BK, Freeman K, Friedman SB. School attendance, health-risk behaviors, and self-esteem in adolescents applying for working papers. Bulletin of the New York Academy of Medicine. 1996;73:255–266. [PMC free article] [PubMed] [Google Scholar]
  257. Teplin LA, McClelland GM, Abram KM, Mileusnic D. Early violent death among delinquent youth: A prospective longitudinal study. Pediatrics. 2005;115:1586–1593. doi: 10.1542/peds.2004-1459. [DOI] [PMC free article] [PubMed] [Google Scholar]
  258. Tofail F, Kabir I, Hamadani JD, Chowdhury F, Yesmin S, Mehreen F, et al. Supplementation of fish-oil and soy-oil during pregnancy and psychomotor development of infants. Journal of Health, Population, and Nutrition. 2006;24:48–56. [PubMed] [Google Scholar]
  259. Tough P. Whatever it takes: Geoffrey Canada's quest to change Harlem and America. New York: Houghton Mifflin; 2008. [Google Scholar]
  260. Tsankova N, Renthal W, Kumar A, Nestler EJ. Epigenetic regulation in psychiatric disorders. Nature Reviews Neuroscience. 2007;8:355–367. doi: 10.1038/nrn2132. [DOI] [PubMed] [Google Scholar]
  261. Turner KMT, Sanders MR. Dissemination of evidence-based parenting and family support strategies: learning from the Triple P--Positive Parenting Program system approach. Aggression and Violent Behavior. 2006;11:176–193. [Google Scholar]
  262. U.S. Department of Health and Human Services. Preventing tobacco use among young people: A report of the Surgeon General. Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 1994. [Google Scholar]
  263. U.S. Department of Labor. Issues in Labor Statistics. 2010 Jun; Available at http://www.bls.gov/opub/ils/pdf/opbils82.pdf.
  264. Valletta RG. The ins and outs of poverty in advanced economies: poverty dynamics in Canada, Germany, Great Britain, and the United States. San Francisco, CA: Federal Reserve Bank of San Francisco; 2004. Rep. No. Working Paper 2004–18. [Google Scholar]
  265. Veysey BM, Messner SF. Further testing of social disorganization theory: An elaboration of Sampson and Groves's 'Community structure and crime'. Journal of Research in Crime and Delinquency. 1999;36:156–174. [Google Scholar]
  266. Vick JW. Securing the safety of our most precious cargo: SAFE KIDS. The American Journal of Maternal-Child Nursing. 2010;35:52–57. doi: 10.1097/01.NMC.0000366811.59832.ba. [DOI] [PubMed] [Google Scholar]
  267. Villani S. Impact of media on children and adolescents: a 10-year review of the research. Journal of the American Academy of Child and Adolescent Psychiatry. 2001;40:392–401. doi: 10.1097/00004583-200104000-00007. [DOI] [PubMed] [Google Scholar]
  268. Wagenaar AC, Toomey TL, Erickson DJ. Complying with the minimum drinking age: Effects of enforcement and training interventions. Alcoholism: Clinical & Experimental Research. 2005;29:255–262. doi: 10.1097/01.alc.0000153540.97325.3a. [DOI] [PubMed] [Google Scholar]
  269. Wagenaar AC, Perry CL. Community strategies for the reduction of youth drinking: Theory and application. Journal of Research on Adolescence. 1994;4:319–345. [Google Scholar]
  270. Wandersman A, Duffy J, Flaspohler P, Noonan R, Lubell K, Stillman L, et al. Bridging the gap between prevention research and practice: The Interactive Systems Framework for dissemination and implementation. American Journal of Community Psychology. 2008;41:171–181. doi: 10.1007/s10464-008-9174-z. [DOI] [PubMed] [Google Scholar]
  271. Weisz JR, Hawley KM, Pilkonis PA, Woody SR, Follette WC. Stressing the (other) three Rs in the search for empirically supported treatments: Review procedures, research quality, relevance to practice and the public interest. Clinical Psychology: Science and Practice. 2000;7:243–258. [Google Scholar]
  272. Welsh BC, Farrington DP. CCTV and street lighting: comparative effects on crime. In: Perry AE, McDougall C, Farrington DP, editors. Reducing crime: The effectiveness of criminal justice interventions. New York: Wiley; 2006. pp. 95–113. [Google Scholar]
  273. Welsh JA, Nix RL, Blair C, Bierman KL, Nelson KE. The development of cognitive skills and gains in academic school readiness for children from low-income families. Journal of Educational Psychology. 2010;102:43–53. doi: 10.1037/a0016738. [DOI] [PMC free article] [PubMed] [Google Scholar]
  274. West J, Denton K, Germino-Hausken E. America’s Kindergarteners. Washington, DC: National Center for Education Statistics, U.S. Department of Education; 2000. NCES 2000–070. [Google Scholar]
  275. Whitbeck LB. Primary socialization theory: it all begins with the family. Substance Use and Misuse. 1999;34:1025–1032. doi: 10.3109/10826089909039394. [DOI] [PubMed] [Google Scholar]
  276. Whitehurst GJ, Croft M. hThe Harlem Children's Zone, Promise Neighborhoods, and the broader, bolder approach to education. Washington, DC: Brown Center on Education Policy at Brookings Institute; 2010. [Google Scholar]
  277. Whitlock JL. Youth perceptions of life at school: contextual correlates of school connectedness in adolescence. Applied Developmental Science. 2006;10:13–29. [Google Scholar]
  278. Whitney LE, Cohen DA, Koralewicz LM, Taylor SN. After school activities, overweight, and obesity among inner city youth. Journal of Adolescence. 2004;27:181–189. doi: 10.1016/j.adolescence.2003.10.010. [DOI] [PubMed] [Google Scholar]
  279. Wilkinson R, Pickett K. The spirit level: why greater equality makes societies stronger. London: Bloomsbury Press; 2009. [Google Scholar]
  280. Willcutt EG, Doyle AE, Nigg JT, Faraone SV, Pennington BF. Validity of the executive function theory of attention-deficit/hyperactivity disorder: A meta-analytic review. Biological Psychiatry. 2005;57:1336–1346. doi: 10.1016/j.biopsych.2005.02.006. [DOI] [PubMed] [Google Scholar]
  281. Williams DR, Costa MV, Odunlami AO, Mohammed SA. Moving upstream: How interventions that address the social determinants of health can improve health and reduce disparities. Journal of Public Health Management and Practice. 2008;14:S8–S17. doi: 10.1097/01.PHH.0000338382.36695.42. [DOI] [PMC free article] [PubMed] [Google Scholar]
  282. Williams DR, Neighbors HW, Jackson JS. Racial/ethnic discrimination and health: Findings from community studies. American Journal of Public Health. 2003;93:200–208. doi: 10.2105/ajph.93.2.200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  283. Wilson DS, Csikszentmihalyi M. Health and the ecology of altruism. In: Post SG, editor. The science of altruism and health. Oxford: Oxford University Press; 2007. pp. 314–331. [Google Scholar]
  284. Wilson DS, O'Brien DT, Sesma A. Human prosociality from an evolutionary perspective: Variation and correlations at a city-wide scale. Evolution and Human behavior. 2009;30:190–200. [Google Scholar]
  285. Wilson WJ. The political and economic forces shaping concentrated poverty. Political Science Quarterly. 2009;123:556–572. [Google Scholar]
  286. Wolfson AR, Carskadon MA. Sleep schedules and daytime functioning in adolescents. Child Development. 1998;69:875–887. [PubMed] [Google Scholar]
  287. World Cancer Research Fund American Institute for Cancer Research. Food, nutrition and the prevention of cancer: A global perspective. Washington, DC: American Institute for Cancer Research; 1997. [DOI] [PubMed] [Google Scholar]
  288. World Health Organization. The World Health Report 2002: Reducing risks, promoting healthy life. Geneva, Switzerland: Author; 2002. [Google Scholar]
  289. Xu J, Kochanek KD, Tejada-Vera B. National vital statistics reports. Vol. 58. Hyattsville, MD: National Center for Health Statistics; 2009. Deaths: Preliminary data for 2007. [Google Scholar]
  290. Yancey A, Seigel JM, McDaniel KL. Role models, ethnic identity, and health-risk behaviors in urban adolescents. Archives of Pediatric and Adolescent Medicine. 2002;156:55–61. doi: 10.1001/archpedi.156.1.55. [DOI] [PubMed] [Google Scholar]
  291. Yancey AK, Cole BL, Brown RO, Williams JD, Hillier A, Kline RS, et al. A cross-sectional prevalence study of ethnically targeted and general audience outdoor obesity-related advertising. Milbank Quarterly. 2009;87:155–184. doi: 10.1111/j.1468-0009.2009.00551.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  292. Yoshikawa H, Weisner TS, Lowe E, editors. Making it work: Low-wage employment, family life, and child development. New York: Russell Sage; 2006. [Google Scholar]
  293. Young S. Schwarzenegger would close 220 state parks to cut deficit. The Huffington Post. 2009 May; Available at http://www.huffingtonpost.com/2009/05/29/schwarzenegger-would-clos_n_208941.html.
  294. Zoritch B, Roberts I, Oakley A. Day care for pre-school children. Cochrane Database of Systematic Reviews. 2000;3 doi: 10.1002/14651858.CD000564. Art. No. CD000564. [DOI] [PubMed] [Google Scholar]

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