Published online February 1, 2008
PEDIATRICS Vol. 121 No. 2 February 2008, pp. 337-344 (doi:10.1542/peds.2007-0447)
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ARTICLE

Influence of Multiple Social Risks on Children's Health

Kandyce Larson, PhDa,b, Shirley A. Russ, MD, MPHa,,c, James J. Crall, DDS, ScDa,d,e and Neal Halfon, MD, MPHa,b,f

a UCLA Center for Healthier Children, Families, and Communities, Los Angeles, California
b Department of Pediatrics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
c Department of Academic Primary Care Pediatrics, Cedars-Sinai Medical Center, Los Angeles, California
d National Oral Health Policy Center, Los Angeles, California
e UCLA School of Dentistry, Los Angeles, California
f Department of Health Services, School of Public Health; and Department of Public Policy, School of Public Affairs, University of California, Los Angeles, Los Angeles, California


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
OBJECTIVE. Social risk factors such as growing up in poverty, racial/ethnic minority status, and maternal depression have been associated with poorer health outcomes for children. This study examined the strength of association of 8 social risk factors, both individually and as part of a cumulative social risk index, on parent-reported child health status.

METHODS. We performed an analysis of cross-sectional data from the 2003 National Survey of Children's Health, a telephone survey of 102353 parents of children aged 0 to 17 years. In bivariate and multivariate logistic regression models, 8 social risk factors were tested as independent predictors of 4 parent-reported child health outcomes: global health status, dental health, socioemotional health, and overweight. These risk factors were combined into a categorical "social risk index" ranging from low risk (0 risk factors) to very high risk (≥6 risk factors), and risk gradients were examined using linear polynomial testing and multivariate logistic regression.

RESULTS. The percentage of children in poorer health increased with the number of social risk factors across all health outcomes. More than half of children had ≥2 risk factors, and 24% had ≥4. Low maternal mental health, black or Hispanic race/ethnicity, <200% of the federal poverty level, low household education, unsafe neighborhoods, and lack of health insurance increased the odds for less than very good child health in adjusted models.

CONCLUSIONS. Multiple social risk factors have a cumulative effect on parent-reported child health status across physical and socioemotional domains, demonstrating a very strong risk gradient effect. These findings emphasize the importance of addressing multiple levels of social risk to achieve improvements in child health.

Key Words: social environment • health outcomes • children • risk factors

Abbreviations: NSCH—National Survey of Children's Health • FPL—federal poverty level • OR—odds ratio • CI—confidence interval

Social factors are increasingly recognized as important determinants of children's health.1–7 Evidence supporting a role for social contributors comes from research that documents large disparities in the health status of children on the basis of stratifying factors such as social class and race/ethnicity.8–11 Although these 2 factors have been the primary focus of child health disparities research, evidence is accumulating that a wider range of social, economic, psychosocial, and community factors can also contribute to systematic differences in health.4 Risk factors including single-parent families,12–14 family conflict,15,16 maternal mental health and depression,17–19 lack of health insurance,20 and levels of community violence21–23 have been shown to predict the prevalence and severity of different child health conditions with some association that is independent from family income, education, or race/ethnicity. This empirical work has led to the development of new conceptual models of children's health that account for this broad range of child, family, and community influences on health and the cumulative toll that multiple co-occurring risk factors may take on health.4,24

The cumulative effects of multiple social risks on child health have been most closely studied in relation to socioemotional health and cognitive outcomes. The classic studies of Rutter in the Isle of Wight on family factors in children with psychosocial problems,25 Sameroff in Rochester,26,27 and Furstenberg in Philadelphia28 examining associations between multiple environmental risk variables and intelligence and socioemotional competencies suggest that the number of risk factors is more important than the nature of any 1 factor in determining outcomes.29 Associations between multiple social risks and physical health outcomes have been less well studied, so it is uncertain whether the same type of cumulative effect occurs. One recent analysis of National Health Interview Survey data showed that 3 social risks—poverty, low parent education, and not living in a 2-parent family—were associated with poorer parent-reported child health status, greater likelihood of the child's having a chronic condition, and greater risk for activity restriction in a cumulative manner.30

In this study, we analyzed data from a nationally representative sample of 102353 US children aged from birth to 17 years from the 2003 National Survey of Children's Health (NSCH). This database is particularly suited to a study of social risks in relation to child health outcomes because it includes rich data on a broad variety of social risks operating at multiple levels, together with data on a range of physical and socioemotional outcomes.31 Risk factors were chosen for inclusion in the study on the basis of the existence of previous research linking each risk individually with some aspect of child health. Risks were also chosen at the level of the child, family, and community following models from the Institute of Medicine4 and others that describe social environmental contributors to children's health.5,24 The study examined the hypothesis that multiple social risks will influence children's health in a cumulative manner across 4 health outcomes: global child health, dental health, socioemotional health, and overweight.


   METHODS
TOP
 ABSTRACT
 METHODS
RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Sample
The NSCH was conducted in 2003–2004 by the National Center for Health Statistics as a module of the State and Local Area Integrated Telephone Survey. The NSCH was designed to address multiple aspects of child health and well-being, and a key strength of the survey was comprehensive assessment of the social and family contexts where children grow and develop.31 The NSCH used a stratified random-digit-dial sampling design to achieve a nationally representative sample of 102353 parents of children 0 to 17 years of age. A detailed telephone interview was conducted with the parent or guardian who knew the most about the child's health and health care experiences. Interviews of ~30 minutes were conducted in English and Spanish. The overall weighted response rate was 55.3%.

The sample for this study varies across each of the 4 health outcome measures. Certain health measures were not relevant and/or not asked for infants or very young children. Global health status was assessed for all children who were younger than 18 years, dental health status for children aged 1 to 17, socioemotional status for children aged 3 to 17, and overweight status for children aged 2 to 17. The final study sample is further restricted to include only individuals without missing data on the outcome under investigation and all study covariates. Cases that were excluded from the study because of missing data were examined for possible sources of bias. Excluded cases were more likely to be from low-income families, to be of black or Hispanic race/ethnicity, and to come from households in which the highest reported educational level was less than college.

For production of population-based estimates, data records for each interview were assigned a sampling weight. Additional details on the design and operation of NSCH are reported elsewhere.31 This study was granted exempt status by the UCLA institutional review board.

Measures
Child Health Outcomes
Global child health status was assessed by parent report and dichotomized as good/fair/poor versus excellent/very good. Parental ratings of child health status are regarded as an acceptable proxy measure of the child's actual health status and have been shown to be associated with health services use.32,33 A similar categorization of parent-reported dental health status was used, with condition of teeth indicated as good/fair/poor versus excellent/very good. Previous research has shown that actual disease of teeth is significantly associated with parents' perceptions of their child's oral health, at least for children aged 2 to 5 years.34 For children with special health care needs, however, there is evidence that caregivers underestimate their child's need for dental treatment.35

Parents were asked the following question about child socioemotional problems: "Overall, do you think that [child] has difficulties with 1 or more of the following areas: emotions, concentration, behavior, or being able to get along with other people?" The dichotomous socioemotional problem outcome variable is indicated by a response of yes.

Weight status of NSCH children was determined from calculations of BMI derived from parent-reported child height and weight. Children were identified as overweight when their BMI was in the 95th percentile or greater compared with children of the same age and gender. Percentiles were determined using Centers for Disease Control and Prevention growth charts.31

Social Risk Factors
Eight dichotomous social risk variables were included in this study. These risk factors represent influences at the level of the child, family, and community. Consistent with the Institute of Medicine categorization of social-environmental influences on children's health, we included both family demographic and family process variables in the study as social risk indicators.4 The cutoff points for dichotomization of risk factors were chosen on the basis of previous literature and sample size considerations.

"No education beyond high school" indicated that the highest educational level of any household member was a high school diploma or less. An indicator for "family income <200% of the federal poverty level" (FPL) was used to identify children in poor or near-poor families. This categorization was chosen because previous research showed that the risk for poor child health extended beyond the absolute poverty threshold.36–38 Any family structure type other than 2 parents was defined as "not a 2-parent household." Two-parent families were defined as 2 biological parents, adoptive parents, or step-families with a mother and a father. Children's race/ethnicity was categorized as black or Hispanic versus non-Hispanic white, multiracial, or other. Uninsured children were those who lacked health insurance of any type at the time of interview.

An indicator of family conflict was derived from 2 questions that asked parents to rate how often they "argue heatedly or shout" or "end up hitting or throwing things" in response to serious disagreements with household members. A response of sometimes/usually/always (versus rarely/never) to either question was used to indicate family conflict. Mother's mental health was self-reported and dichotomized into good/fair/poor (low maternal mental health) versus excellent/very good. Parent perception of an unsafe neighborhood was categorized as never/sometimes safe versus usually/always safe. Additional study variables that were used as statistical controls included child age in years, gender, and number of children in the household.

Statistical Analysis
All statistical analyses were performed using Stata 9.2 (Stata Corp, College Station, TX). Survey estimation procedures were applied with the Taylor-series linearization method used to adjust the SEs for the complex survey design. We first present descriptive statistics for the study sample. Social risk factors were analyzed independently and also combined into a categorical "social risk index" ranging from low risk (0 risk factors) to very high risk (≥6 risk factors).

Bivariate relationships between the categorical social risk index and the child health outcomes were examined using linear polynomial testing. Bivariate and multivariate logistic regression analyses were used to examine the associations between the individual social risks and the child health outcomes. Adjusted odds ratios (ORs) from the multivariate models incorporate controls for all of the social risk factors, plus child age, gender, and number of children in the household. Although considerable associations were noted between the social risk factors (eg, race/ethnicity and household education, family income and maternal mental health), collinearity diagnostics were within an acceptable range. In the final logistic regression models, child health outcomes were examined in relation to the categorical social risk index (0 as the reference category), controlling for child age, gender, and number of children in the household.


   RESULTS
TOP
 ABSTRACT
 METHODS
 RESULTS
DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Sample Characteristics
Descriptive statistics for the study analysis sample are shown in Table 1. A substantial proportion of children experienced social risk or vulnerability factors. Approximately 40% of children were in low-income families <200% FPL, and 32% lived in a household where no resident had an education beyond high school. Fifty-five percent of children had ≥2 social risk factors, whereas 24% had ≥4.


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  		TABLE 1 Sample Characteristics (N = 86 249)

 
Bivariate Analyses
Cumulative social risk gradients are depicted in Fig 1. The percentage of children in worse health increased with the number of social risk factors across all health outcomes (linear polynomial P < .05). The percentage of parents who reported less than very good child health status was 5% for those with 0 risk factors compared with 46% of those with ≥6 risk factors. The gradient for suboptimal condition of teeth went from 14% (0 risk factors) to 64% (≥6 risk factors). Substantial gradients are also shown for child socioemotional problems and overweight status.


Figure 1
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  		FIGURE 1 Percentage of children in worse health by number of social risk factors.

 
Bivariate associations between each risk indicator and the child health outcomes are reported in Table 2. Every social risk factor increased the odds for suboptimal health and suboptimal condition of teeth (P < .05). For these health outcomes, unadjusted ORs >2.0 were found for all risk indicators except family structure type and family conflict. Nearly all of the risk indicators were associated with socioemotional problems and overweight.


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  		TABLE 2 Effect Parameters for Logistic Regression Models Predicting Children's Health Outcomes

 
Multivariate Analyses
Most social risk factors remained significant independent predictors of children's health outcomes in multivariate logistic regression models, although with some attenuation in the magnitude of the associations (Table 2). Low maternal mental health (OR: 3.15; 95% confidence interval [CI]: 2.90–3.42), black or Hispanic race/ethnicity (OR: 2.05; 95% CI: 1.88–2.23), family income <200% FPL (OR: 1.87; 95% CI: 1.70–2.04), low household education (OR: 1.48; 95% CI: 1.36–1.62), unsafe neighborhoods, and lack of health insurance increased the odds for less than very good child health in adjusted models. Low maternal mental health (OR: 2.29; 95% CI: 2.14–2.44), family income <200% FPL (OR: 1.68; 95% CI: 1.56–1.80), black or Hispanic race/ethnicity (OR: 1.62; 95% CI: 1.51–1.73), no education beyond high school (OR: 1.47; 95% CI: 1.37–1.57), lack of health insurance (OR: 1.47; 95% CI: 1.32–1.64), unsafe neighborhoods, and family conflict increased the odds for less than very good condition of teeth.

For child socioemotional problems, low maternal mental health (OR: 2.07; 95% CI: 1.91–2.24), not residing in a 2-parent household (OR: 1.53; 95% CI: 1.41–1.67), and family conflict (OR: 1.47; 95% CI: 1.37–1.58) were strong independent correlates, along with residence in an unsafe neighborhood and family income <200% FPL. All of the risk factors except insurance status increased the odds for overweight, with a particularly strong effect for black or Hispanic race/ethnicity (OR: 1.71; 95% CI: 1.57–1.85) and family income and education.

These results suggest a cumulative influence of multiple risk factors on children's health. In logistic regression models that control for child age, gender, and number of children in the household, there was a 17-fold increase in the odds for less than very good health and an almost 11-fold increase in the odds for less than very good teeth for children with ≥6 versus no social risks. The respective figure for child socioemotional well-being and overweight status was ~4.


   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
CONCLUSIONS
 REFERENCES
 
A large proportion of the study sample exhibited social risks, with more than half having ≥2 risks and 24% having ≥4, underscoring the challenges faced by children growing up in America. For individual social risks, modest associations with poorer health outcomes were obtained across all domains, and these associations largely persisted in multivariate models. When risks were combined into a social risk index, large cumulative effects were observed, with a 17-fold increase in odds for poorer child health status for children with ≥6 risks compared with those with no risks and a near 11-fold increase in odds for poorer oral health. These findings support the hypothesis that the cumulative impact of multiple risks is much greater than the effect of any 1 risk acting alone. These findings are broadly consistent with those of Sameroff and others25–28 on the importance of total number of risks for child cognitive and socioemotional outcomes and extends the concept of cumulative risk to physical health outcomes including global health status, dental health, and overweight.

To date, few studies have addressed associations between multiple social risks and child physical health outcomes. Bauman et al30 reported that 3 social risks—poverty, low parental education, and single-parent household—were associated with poorer parent-reported child health in a cumulative manner. Stevens20 reported that greater numbers of risk factors (race/ethnicity, maternal education and family poverty, child health insurance coverage, and maternal mental health) were associated with poorer health status and being at higher risk for developmental delays with a risk gradient effect in a sample of children who were younger than 3 years. Our findings are broadly consistent with these studies and also show that a wider range of factors operating at the child, family, and community levels contribute to child health risk. These results highlight the importance of incorporating multiple levels of risk into child health development models.

Considering the overall patterns of risk, family income, race/ethnicity, and maternal mental health had strong independent associations with physical well-being, considerably more than health insurance status. Family structure, family conflict, and neighborhood safety were more important for child socioemotional health but not inconsequential for physical well-being. Income disparities in children's health were reduced by statistically controlling for related social risks, but a substantial direct association of this form of material disadvantage remained for all health outcomes. For socioemotional health, both minority race/ethnicity and uninsured status actually seemed to be associated with fewer reported problems, potentially reflecting underrecognition, as described in other studies of black and Hispanic youth,39,40 rather than a true protective effect. Differential parent recognition of children's mental health problems may help to explain why social gradients in socioemotional health were less pronounced than those for global child health status and condition of teeth.

Poor maternal mental health showed consistent associations with each child health outcome included in this study. Previous studies demonstrated a relationship between maternal depression and poorer child socioemotional health;18,41 however, relationships with child physical health outcomes have been less comprehensively studied. The considerable association between maternal mental health and condition of child's teeth found in this study is particularly intriguing. Although low income and racial/ethnic minority status are known to be associated with poorer child oral health,42,43 far less is known about the relationship between oral health and other social risks. These findings suggest a need for increasing attention to maternal mental health as part of a larger strategy to combat social risks and their negative impact.

This study does not address the mechanism whereby multiple social risks might influence child health, but 1 candidate explanation emerges from empirical studies that demonstrate how cumulative risks can induce high levels of toxic stress, leading to greater susceptibility to poorer health outcomes.44–47 Each risk factor might also influence health in unique ways (eg, restricted diet and nutrition for children with limited family income, disrupted health routines for families with psychosocial difficulties, inadequate preventive care for children who lack health insurance) with diverse health insults exerting a cumulative negative toll on the health status of children with multiple risks. Although the social risk factors included in this study were associated with one another, it is noteworthy that most retained an independent association with health in mutually adjusted models. This suggests that each factor represents a unique source of health vulnerability, even considering that certain risks, such as poor maternal mental health, may mediate some of the influence of the other risks.

What are the clinical implications of these findings? First, they suggest that clinical strategies that either ignore the presence of social risks or address only individual risks are unlikely to be successful. Current approaches to well-child care in the United States lack both a systematic approach to the identification of numbers of risks and effective strategies to target children with multiple risks for additional preventive or treatment services. There is a growing realization that our existing system of well-child care is not matching services to child and family needs and needs to be reconceptualized.48 All too often, important psychosocial risks remain unrecognized and unaddressed.49 In addition to lack of tools to identify systematically both patterns and degrees of risk, primary care providers lack the resources, relationships, and case management capacity to connect families to appropriate services.50

Well-child care that is sufficiently flexible to provide more intense services for families with greatest biological, psychological, and social risks might prove more effective than the existing "one size fits all" approach.51,52 Kemper53,54 and Fleegler et al49 suggested that by routinely using a standardized psychosocial risk assessment, child health providers could improve identification of risks, like those that were compiled for this study. A brief social risk assessment could be performed at or even before birth, and children with the greatest number of risks could be offered enhanced or supplemented well-child care. This might include longer or more frequent visits, as well as encouraging access to comprehensive community-based interventions designed to reduce the impact of common psychosocial risks, such as home visiting programs for new mothers.55 Children with multiple risks might also benefit from evidence-based supplements to traditional well-child care, such as the Healthy Steps program for developmental monitoring,56 and coordinated referral programs, such as the Help Me Grow program in Connecticut.57

The sizable cumulative toll that multiple social risks may take on child health points toward a need for comprehensive childhood programs and service systems that address a variety of family needs with diverse forms of assistance, such as parenting support, education, financial planning, health care, and mental health and domestic violence services. As advocates for children at the community level, pediatricians can establish formal linkages with other child service providers aimed at improving the entire system of community supports and services;58 however, services alone are not enough. The vulnerabilities resulting from low social class, minority status (a probable proxy for various forms of discrimination), single parenthood, being uninsured, poor maternal mental health, family conflict, and community violence must be addressed through coordinated national policy action aimed at reducing developmental risk. That social gradients in children's health are variable in magnitude across different countries with differing child and family policy schemes suggests that they are amenable to change.3,59 Pediatricians would be well positioned to advocate for social policy change aimed at reducing social risks and their negative impact through the provision of adequate family income, adequate time for parenting, and generous supportive services.60

The strengths of this study include the very large sample size and the nationally representative nature of the study sample. The NSCH provided detailed information on the social and environmental contexts in which children live, allowing us to construct a social risk index composed of risks that operate at multiple ecological levels and to test it against a range of child health outcomes.

The study has several limitations. First, the data were collected by telephone survey of parents or other caregivers. Most of the indicators obtained, therefore, reflect parent perceptions of their child's health and of family and community characteristics. Some parents, such as mothers with poorer mental health, might overestimate health problems in their children.61 Maternal psychological distress has been associated with more pessimistic assessments on the problem-focused Child Behavior Checklist; however, related problems such as maternal substance abuse have been demonstrated to result in more optimistic assessments.62 We consider it unlikely that the observed associations between poorer maternal mental health and reported child health outcomes can be entirely explained by parental bias but acknowledge that additional research is required to confirm these findings. Similarly, some parents may give socially desirable rather than objective responses to survey questions. Finally, inferences about causality are limited by the cross-sectional nature of the study: it can be argued, for example, that poorer maternal mental health or greater family conflict may result from the effects of having a child with poorer health status.


   CONCLUSIONS
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
REFERENCES
 
Social risk factors threaten children's health in a cumulative manner across physical health, oral health, and mental health domains. Attention to social risk factors is an important part of child health optimization. Early identification of children with multiple social risks would allow targeting of enhanced well-child preventive care services, tailored to the child's family and community context.63 The high proportion of the childhood population with multiple social risks speaks to a need for ongoing advocacy efforts to improve the circumstances in which America's youngest citizens are growing up. These findings suggest that there are multiple avenues through which children's health status might be improved. Programs and policies that address multiple domains of social risk offer the best hope for achieving improvements in child health.


   ACKNOWLEDGMENTS
 
This research was supported in part by funding from the Maternal and Child Health Bureau of the Health Resources and Services Administration Interdisciplinary Maternal and Child Health Training Program (2 T76M600014:11; Dr Halfon) and National Oral Health Policy Center (5 U44MC03661; Dr Crall).

We thank Louba Benassaya and Nicole Garro, who assisted with data analysis and manuscript preparation.


   FOOTNOTES
 
Accepted Jul 25, 2007.

Address correspondence to Kandyce Larson, PhD, UCLA Center for Healthier Children, Families, and Communities, 1100 Glendon Ave, Suite 850, Los Angeles, CA 90024. E-mail: kandyce{at}ucla.edu

The authors have indicated they have no financial relationships relevant to this article to disclose.


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 CONCLUSIONS
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PEDIATRICS (ISSN 1098-4275). ©2008 by the American Academy of Pediatrics

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