Published online September 1, 2008
PEDIATRICS Vol. 122 No. 3 September 2008, pp. e529-e540 (doi:10.1542/peds.2008-0556)
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow E-mail this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My File Cabinet
Right arrow Download to citation manager
Right arrowRequest Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via CrossRef
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Gundersen, C.
Right arrow Articles by Eisenmann, J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Gundersen, C.
Right arrow Articles by Eisenmann, J.
Related Collections
Right arrow Nutrition & Metabolism
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Facebook   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

ARTICLE

Food Security, Maternal Stressors, and Overweight Among Low-Income US Children: Results From the National Health and Nutrition Examination Survey (1999–2002)

Craig Gundersen, PhDa, Brenda J. Lohman, PhDb, Steven Garasky, PhDb, Susan Stewart, PhDc and Joey Eisenmann, PhDd

a Department of Agricultural and Consumer Economics, University of Illinois, Urbana, Illinois
b Departments of Human Development and Family Studies
c Sociology, Iowa State University, Ames, Iowa
d Departments of Kinesiology and Pediatrics, Michigan State University, East Lansing, Michigan


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
OBJECTIVE. A high proportion of children in the United States are overweight, suffer from food insecurity, and live in households facing maternal stressors. The objective of this article was to identify the associations of food insecurity and maternal stressors with childhood overweight among low-income children. We hypothesized that maternal stressors may exacerbate the relationship between food insecurity and child obesity.

METHODS. The sample included 841 children (3–17 years old) and their mothers with incomes below 200% of the poverty line from the 1999–2002 National Health and Nutrition Examination Survey. Food insecurity was based on US Department of Agriculture protocol, maternal stressors were assessed from survey questions, and BMI was used to classify weight status. Probit regression models predicted the probability of a child being overweight or obese.

RESULTS. In most specifications, there was no direct association between food insecurity or maternal stressors and overweight for children of any age. Among 3- to 10-year-olds, the interaction of food insecurity and maternal stressors was significantly linked to the probability of being overweight; more specifically, an increase in maternal stressors amplified a food secure child's probability of being overweight or obese. This result is robust to alternative specifications. However, these results were not found among 11- and 17-year-old youth.

CONCLUSIONS. Younger children in food secure, low-income households in the United States who are experiencing higher levels of maternal stressors have a greater probability of being overweight than food insecure children. This finding was contrary to the hypothesis; 3 reasons for this are covered in the article. Those who create policies that address childhood obesity could consider the benefits to low-income children's well-being resulting from reducing their mothers' stressors. Because most children in the United States are food secure, these policies could have a profound impact on childhood overweight.

Key Words: food insecurity • childhood overweight • poverty • stressors • NHANES

Abbreviations: NHANES—National Health and Nutrition Examination Survey • NCHS—National Center for Health Statistics • CDC—Centers for Disease Control and Prevention • CPS—Current Population Survey • USDA—US Department of Agriculture • ADL—activities of daily living • CI—confidence interval

Approximately 17.1% of US children between the ages of 2 and 19 years are obese, and another 16.5% are overweight.1 This prevalence has increased threefold for children since 1970.2–4 Childhood obesity has negative physical, psychological, and social consequences that have current and future implications5–16 including reduced life expectancy.17 Because of these consequences, there are also varying estimates of the economic costs for the United States.18–20 Childhood obesity, therefore, is a critical public health issue today.18,21,22

On the other end of the nutrition spectrum, 1 in 5 children and >4 of 10 low-income children in the United States live in a food insecure household (ie, a household that does not have the financial means to access enough food to sustain active, healthy living for all members).23 Paradoxically, some studies have indicated a positive relationship between food insecurity and child obesity.24–27 However, other studies have found either no relationship28–33 or an inverse relationship.34–36

In addition to high levels of overweight and food insecurity, children in low-income families experience a myriad of adverse psychosocial conditions that result in high levels of stress.37 The stressors experienced by low-income families may originate from within individuals, family members (mothers, fathers, siblings, etc), neighborhoods, and communities. In turn, low-income families may have difficulty dealing with stressors, because they may not have adequate resources to cope with them. Household-production theories posit that families "produce" child health outcomes, such as obesity, through parental resources or lack thereof,38–40 as well as other factors, including stress, which threaten a family's adjustment.41,42 In this research, we assessed maternal mental, physical, financial, and family-structure stressors, all of which have been linked to increased physical and emotional health outcomes for children in low-income families.43–51 Of importance to this article is the growing body of evidence describing how and why stress can lead to obesity.52–54 For example, increased levels of cortisol during stressful conditions and the chronic hypersecretion of cortisol may lead to metabolic abnormalities and obesity.54 Stress may also contribute to poor eating habits55 and lower physical activity levels,55 which are both associated with overweight and obesity.56–59

In this article, we further examined the relationship between stress and childhood overweight by considering the stress that children face via their mother's stressors from mental, physical, financial, and family-structure issues. These stressors experienced by parents can be transmitted to children through several mechanisms (eg, diminished parenting, lack of time with children, or inability to shop for or cook nutritional foods), which then leads to higher stress levels among children and/or lower levels of well-being.47,60,61 Our overall aim was to examine the independent relationships and interactions between food insecurity, maternal stressors, and overweight in a nationally representative sample of low-income children. We conjectured that maternal stressors may exacerbate the relationship between food insecurity and child obesity.


   METHODS
TOP
 ABSTRACT
 METHODS
RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Participants
Participants were from the 1999–2002 National Health and Nutrition Examination Survey (NHANES). The NHANES is a program of studies conducted by the National Center for Health Statistics (NCHS), Centers for Disease Control (CDC) to assess the health and nutritional status of adults and children in the United States. The NHANES examines a nationally representative sample of ~5000 persons each year, approximately half of whom are children.62 Because food insecurity is rare among households above 200% of the poverty line,23 the sample was limited to households below this threshold.

The publicly available NHANES has information on children and adults but does not allow one to ascertain whether a surveyed adult lives in the same household as a surveyed child. To obtain this information, we received permission to access confidential NHANES data that included household identifiers, which allowed us to match adults with children in the same household. However, the relationship between the household members remained unknown. Given this uncertainty, we further limited our sample to households with a female adult and at least 1 child in which at least 17 years separated the female adult and child. We investigated what proportion of our sample could be considered mothers and their children by examining another nationally representative data set (the Current Population Survey [CPS]), in which information on the relationship between household members is available. In the CPS, >88% of households with a woman and a child who were at least 17 years apart in age were composed of a mother and her child or children (analysis available on request). Henceforth, we refer to the female adult in the NHANES as the child's mother. The final NHANES analytical sample consisted of 841 children in 425 households. Approximately half of the children were non-Hispanic white, and one fourth were Hispanic of any race.

Measures
Classification of Weight Status
Height and weight were measured with an automated data-collection system by a trained technician in the NHANES mobile examination center. BMI (kg/m2) was calculated from the child's weight and height and mapped into a percentile by using age- and gender-specific reference values of the CDC growth charts for the United States.63 A child was then classified into 1 of 4 weight-status categories: (1) underweight (BMI < 5th percentile); (2) healthy weight (BMI = 5th–84th percentile); (3) overweight (BMI = 85th–94th percentile), and (4) obese (BMI > 95th percentile). To ensure that our referent group included healthy-weight children, we excluded underweight children (BMI < 5th percentile; n = 51).

Food Insecurity
We used the same methodology as the US Department of Agriculture (USDA) for our measures of food insecurity.23 Defined over a 12-month period, a series of 18 questions (the USDA Core Food Security Module [CFSM]) was posed to NHANES mothers.64 The full set of questions can be found in the Appendix. Two definitions of food insecurity were used. First, food insecurity was defined at the household level. A household with ≤2 affirmative responses was categorized as food secure, and a household with ≥3 affirmative responses was categorized as food insecure. Second, food insecurity was defined with respect to the children in the household via the 8 child-specific CFSM questions. Note that this measure is defined for all the children in the household, not just the child for whom overweight was being considered. Consistent with the USDA23 and Casey et al,25 children were defined as being in a food insecure household if ≥2 questions of the 8 child-specific questions were answered affirmatively.


View this table:
[in this window]
[in a new window]

  		APPENDIX Food Insecurity Questions on Core Food Security Module

 
Maternal Stressors
Stress is an often-used construct across different disciplines.65,66 Consistent with theoretical work on the "stress process,"65,67 we defined stressors as the external factors that may cause this response.65,67,68 Children may also experience "stressor pile-up" as a result of dealing with multiple stressors at once,69 which has been related to increased rates of children's psychopathology,70,71 problem behaviors,72–77 academic problems,70–72,77–79 and physical health problems.73,74 Therefore, we focused on a cumulative maternal stressor model rather than individual stressors. We assessed 4 indices of maternal stressors as described below. Finally, we created a total cumulative stressors index by summing the 4 indices.

Cumulative Mental Stressors Index
Using items from the Organization Composite International Diagnostic Interview, the following 3 measures were used to assess the mental stressors experienced by the child's mother.80 A value of 0 to 9 was assigned to the first indicator on the basis of the number of affirmative responses to questions assessing maternal depression. These questions were only asked of people who already passed through a screener demonstrating that they experienced at least some depression. Thus, a person without depression or with no symptoms of depression would receive a score of "0." The 9 questions were: Did the respondent have (1) a depressed mood, (2) markedly diminished interest in things, (3) significant appetite or weight change, (4) insomnia or hypersomnia, (5) psychomotor agitation or retardation, (6) fatigue or loss of energy, (7) feelings of worthlessness or guilt, (8) diminished ability to think or concentrate or indecisiveness, or (9) recurrent thoughts of death, suicidal ideation, plan, or attempt? The second measure received a value of 1 if the child's mother reported ever experiencing a panic attack. Finally, a score was assigned to the third measure on the basis of the number of affirmative responses to 6 questions that addressed symptoms of anxiety. These questions were only asked of people who already passed through a screener demonstrating that they experienced at least some anxiety. Thus, a person without anxiety or with no symptoms of anxiety would be assigned a value of "0." The questions were: Did the respondent often (1) feel restless or "keyed up," (2) feel more tired than usual, (3) feel more irritable, (4) have trouble sleeping, (5) have trouble keeping mind on topic, or (6) have tense, sore, or aching muscles? The cumulative mental stressor index was summed from all these measures and ranged from 0 to 16.

Cumulative Physical Stressor Index
Three measures were used to assess the physical stressors experienced by the child's mother. First, a value of 1 was assigned if she reported being in "fair" or "poor" health from a set of possible responses of "excellent," "very good," "good," "fair," or "poor." Second, a value of 1 was assigned if she reported any limitations that kept her from working; limitations that reduced the amount of work she could do; or physical, mental, or emotional limitations. Third, a value of 1 was assigned if the child's mother reported being unable to perform at least 1 activity of daily living (ADL). The cumulative physical stressor index ranged from 0 to 3.

Cumulative Financial Stressor Index
The following measures were used to define financial stressors experienced by the child's mother. The first 3 related to working. A value of 1 was assigned if the mother was unemployed or out of the labor force, worked <20 hours per week, or worked >60 hours per week. A value of 1 was assigned if she had no health insurance. Finally, a value of 1 was assigned if she was unable to work because of a disability. The cumulative financial stressor index summed across these 5 questions and ranged from 0 to 3, because the 3 work questions were mutually exclusive.

Cumulative Family Structure Stressor Index
To measure stressors related to family structure, a value of 1 was assigned to mothers who were not married. We delineate family structure as a unique stressor. Indeed, single mothers, especially those living in poverty, may be more likely to experience financial, mental, and physical health problems than mothers who are married.81,82 However, they may also be experiencing other stressors (eg, stigma, child care issues, lack of social support) not tapped by our other 3 indices.

Total Cumulative Stressor Index
To test an index of accumulated maternal stressors, we created a total cumulative stressor index by summing each of these 4 indices. The cumulative stressor index ranged from 0 to 23. This is consistent with, for example, refs 83–87. We also created 3 alternative specifications. These alternative specifications are (1) an index with weights inversely proportional to the number of possible responses within an index, (2) an index with weights inversely proportional to the average number of responses within an index, and (3) an index derived from a factor analysis defined over the 4 stress indices. For specification 3, the index was derived by using the factor command in Stata 10 for Windows88 (as described by, eg, van Bel et al89).

Confounders
Several demographic characteristics were included as covariates because they are often related to children's weight status, food insecurity status, and maternal stressors. Child-specific covariates included age (years), race/ethnicity (Hispanic of any race, non-Hispanic black, and non-Hispanic white), household income divided by the poverty line, and gender. Maternal-specific covariates included whether a high school degree or General Equivalency Diploma is held by the mother, and mother's BMI and age. For parsimony, we did not include these coefficients in the tables. Complete results are available on request.

Statistical Analyses
Descriptive statistics were calculated for sociodemographic characteristics, maternal stressors, and child weight measures and weighted with the sample weights supplied for the 4-year sample in the NHANES. Probit maximum-likelihood models90 were estimated to assess associations with a child's probability of being at risk of overweight or overweight. Specifically, the following models that controlled for other factors were estimated:

  • Model 1: food insecurity;
  • Model 2: food insecurity and the 4 maternal stressor indices;
  • Model 3: food insecurity, the 4 maternal stressor indices, and the interaction of these indices with food insecurity;
  • Model 4: food insecurity and a total cumulative maternal stressor index; and
  • Model 5: food insecurity, the total cumulative maternal stressor index, and the interaction of this index with food insecurity.

These models were estimated for food insecurity defined at the household level and for all the children in the household. Because multiple children in the sample could be in the same household, the confidence intervals (CIs) were adjusted for clustering at the household level.91 On the basis of previous studies,92–94 these models were not weighted because some of the covariates in our models were used in the establishment of the sample weights. We repeat our results from the baseline cumulative stressor model along with the alternative specifications of the cumulative indices described above. Because the effect of food insecurity and stress may differ by age, the models were further estimated for 2 age groupings (3–10 and 11–17 years of age) on the basis of youth physical and psychosocial development.

To convey the combined influence of the variables in the interactive model and the total cumulative maternal stressor index, the odds of being overweight or obese were estimated at different levels of total cumulative maternal stress for children in food insecure and food secure households. The values of all other variables were assessed at their sample means. All analyses were conducted by using Stata 10 for Windows.88


   RESULTS
TOP
 ABSTRACT
 METHODS
 RESULTS
DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Descriptive characteristics for the sample are provided in Table 1. Thirty-seven percent of the children were either overweight or obese. Approximately one fourth and one fifth of the children were food insecure when food insecurity was reported at the household and child level, respectively. A range of stressors was reported by mothers. Many of the covariates reflected the characteristics of a low-income sample. In addition, 52.4% of the children were the sole child interviewed in the household, 28.6% of the children were 1 of 2 children interviewed, 13.4% were 1 of 3 children interviewed, and the remaining 5.5% were 1 of >3 children interviewed (results not shown).


View this table:
[in this window]
[in a new window]

  		TABLE 1 Descriptive Statistics

 
Tables 2 and 3 report the results from the multivariate probit regression analyses. The columns in the tables correspond with the models described in "Statistical Analyses" (eg, column 1 is model 1). Food insecurity measured at the household level was not significantly related to the weight status of the child (Table 2, model 1). Similarly, none of the maternal stressor indices were significant when tested as independent main effects or when they were interacted with food insecurity (models 2 and 3). Akin to model 2, the cumulative stress index was statistically insignificant in model 4. In model 5, a significant interaction was found between the cumulative stressor index and food insecurity at the household level. In other words, the positive effect of stress on childhood overweight is reduced when the household is food insecure and is enhanced when the household is food secure.


View this table:
[in this window]
[in a new window]

  		TABLE 2 Coefficients From Probit Regression Models for Child Overweight or Obesity Status as a Function of Household Food Insecurity and Indices of Maternal Stressors

 

View this table:
[in this window]
[in a new window]

  		TABLE 3 Coefficients From Probit Regression Models for Child Overweight or Obesity Status as a Function of Child Food Insecurity and Indices of Maternal Stressors

 
When food insecurity was measured at the child level (Table 3), in models 1, 2, and 4, the results are similar to those for the respective models when food insecurity was measured at the household level. In model 3, however, food insecurity at the child level has a positive and statistically significant association with the weight status of the child. In addition, the family structure stressor interacted with food insecurity at the child-level was negative and statistically significant. In other words, children in food secure households experiencing family-structure stress (ie, an unmarried mother) are more likely to be overweight or at risk of overweight than children in food insecure households experiencing this type of stress. In model 5, the associations of the cumulative stress index and its interaction with food insecurity showed a trend for being statistically insignificant (.06 and .05, respectively). Although these are statistically insignificant (but jointly significant), the trend results do support the pattern of results in model 5 of Table 3, when food insecurity was measured at the household level. This is our main consistent pattern of results overall for the 2 measures of food insecurity. Moreover, as seen below in the results from the alternative indices and for the analysis for which the sample was split according to age, the effects of total cumulative maternal stress are statistically significant in many instances for both measures of food insecurity.

Figure 1 illustrates the relationships between food security, maternal stressors, and childhood overweight. The child's probability of being overweight or obese is estimated for children in (1) food secure and (2) food-insecure households with total cumulative stressor index values of 0, 3 (the mean value), and 6. These simulations use the results from model 5 in Tables 2 and 3. Figure 1 left is for the household food insecurity measure, and Fig 1 right is for the child food insecurity measure. For children in households with values of 0 for the total cumulative stressor index, children in food secure households as defined at the household level had a 33.0% probability of being overweight, whereas children in food insecure households had a 34.8% probability. However, at the mean value of the total cumulative stressor index the probabilities began to diverge, with children in food secure households having a 38.9% probability of being overweight or obese, whereas the probability for children in food insecure households was 33.0%. Finally, when a 1-SD increase above the mean (ie, 6) in the index was tested, a larger divergence was shown. Children in food-secure households had a 43.7% greater probability of being overweight or obese relative to children in food insecure households. The patterns of results were similar when food insecurity was measured at the child level. The probabilities for 0, 3, and 6 stressors were 32.4%, 36.7%, and 41.2% for food secure households and 41.4%, 38.6%, and 35.9% for food insecure households, respectively.


Figure 1
View larger version (10K):
[in this window]
[in a new window]

  		FIGURE 1 Probability of at risk of overweight or overweight based on maternal stress according to food-insecurity status. Left, Household food-insecurity measure; right, child food-insecurity measure.

 
Table 4 contains the results from the 3 alternative specifications (detailed above) of the total cumulative stressor index. Column 1 repeats the results from model 5 of Tables 2 and 3. Indeed, the statistically significant interaction between food insecurity and total cumulative stressors holds across all 3 model specifications when food security is defined at the household level (columns 2–4). Once again, increases in maternal stressors amplified a food secure child's probability of being overweight or obese. As noted earlier, this interaction was barely statistically insignificant when food insecurity was measured at the child level. However, the interaction between food insecurity at the child level and total cumulative stressors is statistically significant in 2 of 3 of the alternative specifications (columns 2 and 4). Thus, in general, across household and child definitions of food insecurity, the positive effect of stress on childhood overweight is reduced when the household is food insecure and increased when the household is food secure.


View this table:
[in this window]
[in a new window]

  		TABLE 4 Coefficients from Probit Regression Models for Child Overweight or Obesity Status as a Function of Food Insecurity and Child Food Insecurity and Cumulative Stressor Index; Alternative Specifications

 
Table 5 repeats the analyses of model 5 in Tables 2 and 3 when the sample is broken down into 2 age categories (ages 3–10 and 11–17 years). For young children (column 1), the association between the interaction of total cumulative stressors and food insecurity is negative but insignificant, albeit with low P values (.07 for household food insecurity and .08 for child food insecurity). However, supporting the results from Table 2, the alternative indices did show statistically significant effects for the interaction between cumulative stressors and food insecurity (for each measure) for children between the ages of 3 and 10 years (results not tabulated but available on request). For children over the age of 10 years, the interaction of total cumulative stressors and food insecurity and child weight were all statistically insignificant.


View this table:
[in this window]
[in a new window]

  		TABLE 5 Coefficients From Probit Regression Models for Child Overweight or Obesity Status as a Function of Food Insecurity and Child Food Insecurity and Cumulative Stressor Index, Split According to Age Groups

 

   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
CONCLUSIONS
 REFERENCES
 
We found that food insecurity and maternal stressors were, in most of our specifications, not independently associated with a child's probability of being overweight or obese. However, when these factors were considered jointly, children in food secure households suffering from maternal stressors were more likely to be overweight or obese than children in food insecure households with mothers suffering from similar stressor levels. In other words, increases in maternal stressors increased the probability of being overweight or obese for children in food secure households but decreased these odds for children in food insecure households. Insofar as the majority of low-income children in the United States live in food secure households, our findings indicate that maternal stressors (via its interaction with food insecurity) may be an important factor for children in the United States that are overweight or obese. Our findings are particularly relevant for children between the ages of 3 and 10. We conjecture that the interaction between food insecurity and maternal stress is particularly salient for younger children more so than it is for adolescents, because they lack the resources to recover from diminished parenting of mothers who are stressed. For example, adolescents may turn to outside sources (eg, schools, friends, work) for instrumental (eg, money or food) or expressive (eg, social support) resources that may mediate the relationship between maternal stressors and food insecurity on their propensity to be overweight or obese. Future research should address a family-stress model that accounts for these meditational family processes at varying developmental stages to understand the age differences we found among these associations.

Our findings are contrary to our hypothesis insofar as maternal stressors did not exacerbate the relationship between food insecurity and child overweight. Some possible reasons for not finding this expected association are as follows. First, children in food secure households may consume greater energy and possess a positive energy balance compared with children in food insecure households. Although children in both household types may have wanted to eat in response to maternal stressors, only children in food secure households may be able to do so. Second, children in food secure households may have a greater ability to consume more "comfort foods," which are often unhealthy, in response to the stressors they experience. Third, the difference in the direction of the relationships in food secure and food insecure children may be related to the influence of stress in conjunction with energy availability. More specifically, higher stress levels coupled with sufficient (or excess) energy intake may produce metabolic disturbances that lead to obesity. In contrast, food insecure children who are experiencing undernourishment may be facing the catabolic effects of cortisol in muscle,95 thus resulting in a lower BMI.

Maternal stressors are just 1 set of stressors that low-income children face, along with individual, household, and community-level stressors. Our findings show that when it comes to overweight and obesity, low-income children are indeed influenced by stress emanating from their mother. In particular, we found that the cumulative stress experienced by the child's mother is an important determinant of child overweight. Thus, although it is important to examine stressors coming from individuals, households, and communities, it is also important to examine stressors coming from children's main caregivers.

This study also contributes to the often-discussed relationship between food insecurity and childhood weight. The results from the specifications in this article are consistent with the findings of no association between food insecurity and childhood overweight.28–33 In a limited number of our specifications, however, we did find a positive relationship between food insecurity and child obesity consistent with the results discussed in refs 24–27, but only when the interaction with maternal stress was considered. One contribution our work makes with respect to this literature is that we controlled for a set of variables (the stressors) that previous work had not considered.

Five limitations of this study and subsequent directions for future research warrant mention. First, because of confidentiality restrictions, we were unable to obtain the exact relationship between the woman and the child in a household. However, on the basis of the analyses of CPS data noted earlier, we are confident that the vast majority of the female adults are the children's mothers. Second, we tested 4 indices of maternal stressors; other maternal stressors may yield different results. Third, we were unable to examine associations with food insecurity specifically for the focal child in question. Because the availability of food to eat may vary among the children in a household, analyses testing the relationships between food insecurity for a particular child and that child's overweight status are needed.24 Fourth, for some of our indices there are not many variables that can be used from the NHANES. Those who wish to perform additional work on this topic may wish to use other data sets with richer sets of these variables. Fifth, we concentrated on low-income children in this study, because food insecurity is rare among those at >200% of the poverty line. Stressors, however, may also affect children above this threshold; others who perform additional work in this area may wish to examine how stress affects children in middle- and upper-income families.


   CONCLUSIONS
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
REFERENCES
 
There have been numerous recent recommendations to improve policies and programs to address childhood overweight.96–104 Our research demonstrates that another set of policies and programs may also help reduce childhood overweight, especially for children between the ages of 3 and 10 years. Namely, these policies would entail reducing maternal stressors. Consider, for example, that a number of the mothers in this study suffer from at least 1 symptom of depression and anxiety. By providing these women with relevant medical care and counseling, these symptoms may be alleviated with the further indirect benefit of reducing childhood overweight. Similarly, other efforts to reduce other maternal stressors for low-income families may further benefit the health of the children in these households by reducing the number of stressors to which these children are exposed. Although our cumulative stress analyses give policy makers additional impetus to assist low-income families, it should be noted that these analyses provide less guidance as to which of the specific stressors examined here should be eliminated. Nevertheless, the potential benefits to be generated as a result of reducing childhood overweight and obesity should be considered as programs and policies are developed and modified in an effort to help low-income families meet their physical, financial, and familial needs.


   ACKNOWLEDGMENTS
 
This research was supported by the USDA, Cooperative State Research, Education, and Extension Service grant 2007-35215-17871.

We thank Negasi Beyene for assistance in preparing and enabling access to the NHANES data.


   FOOTNOTES
 
Accepted Jun 3, 2008.

Address correspondence to Craig Gundersen, PhD, Department of Agricultural and Consumer Economics, University of Illinois, 324 Mumford Hall, 1301 West Gregory Dr, Urbana, IL 61801-3605. E-mail: cggunder{at}illinois.edu

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


What's Known on This Subject

Evidence on the connection between food insecurity and childhood overweight is mixed. Some clinical work has examined stress and obesity, but to our knowledge, there has been no previous work on the connection between maternal stress and childhood overweight.

 

What This Study Adds

In general, we found no relationship between food insecurity and childhood overweight. We found that children in food secure households (the majority of low-income children in the United States) with mothers experiencing stress are more likely to be overweight.

 


   REFERENCES
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 

  1. Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CC, Flegal KM. Prevalence of overweight and obesity in the United States, 1999–2004. JAMA. 2006;295 (13):1549 –1555[Abstract/Free Full Text]
  2. Anderson P, Butcher KE. Childhood obesity: trends and potential causes. Future Child. 2006;16 (1):19 –45[CrossRef][Web of Science][Medline]
  3. Kumanyika S, Grier S. Targeting interventions for ethnic minority and low-income populations. Future Child. 2006;16 (1):187 –207[CrossRef][Web of Science][Medline]
  4. Wang Y, Zhang Q. Are American children and adolescents of low socioeconomic status at increased risk of obesity? Changes in the association between overweight and family income between 1971 and 2002. Am J Clin Nutr. 2006;84 (4):707 –716[Abstract/Free Full Text]
  5. Gunnell D, Frankel S, Nanchahal K, Peters T, Davey Smith G. Childhood obesity and adult cardiovascular mortality: a 57-y follow-up study based on the Boyd Orr cohort. Am J Clin Nutr. 1998;67 (6):1111 –1118[Abstract]
  6. Mahoney L, Burns T, Stanford W, et al. Coronary risk factors measured in childhood and young adult life are associated with coronary artery calcification in young adults: the Muscatine Study. J Am Coll Cardiol. 1996;27 (2):277 –284[Abstract]
  7. Nieto F, Szklo M, Comstock G. Childhood weight and growth rate as predictors of adult mortality. Am J Epidemiol. 1992;136 (2):201 –213[Abstract/Free Full Text]
  8. Power C, Lake JK, Cole TJ. Measurement and long-term health risks of child and adolescent fatness. Int J Obes Relat Metab Disord. 1997;21 (7):507 –526[CrossRef][Web of Science][Medline]
  9. Schwimmer J, Burwinkle T, Varni, J. Health-related quality of life of severely obese children and adolescents. JAMA. 2003;289 (14):1813 –1819[Abstract/Free Full Text]
  10. Serdula M, Ivery D, Coates R, Freedman D, Williamson D, Byers, T. Do obese children become obese adults? A review of the literature. Prev Med. 1993;22 (2):167 –177[CrossRef][Web of Science][Medline]
  11. Smoak C, Burke G, Webber L, Harsha D, Srinivasan S, Berenson G. Relation of obesity to clustering of cardiovascular disease risk factors in children and young adults: the Bogalusa Heart Study. Am J Epidemiol. 1987;125 (3):364 –372[Abstract/Free Full Text]
  12. Williams D, Going S, Lohman T, et al. Body fatness and risk for elevated blood pressure, total cholesterol, and serum lipoprotein ratios in children and adolescents. Am J Public Health. 1992;82 (3):358 –363[Abstract/Free Full Text]
  13. Carroll CL, Stoltz P, Raykov N, Smith SR, Zucker AR. Children overweight increases hospital admission rates for asthma. Pediatrics. 2007;120 (4):734 –740[Abstract/Free Full Text]
  14. Bender BG, Fuhlbrigge A, Walders N, Zhang L. Overweight, race, and psychological distress in the children asthma management program. Pediatrics. 2007;120 (4):805 –813[Abstract/Free Full Text]
  15. Pinto NM, Marino BS, Wernovsky G, et al. Obesity is a common comorbidity in children with congenital and acquired heart disease. Pediatrics. 2007;120 (5). Available at: www.pediatrics.org/cgi/content/full/120/5/e1157
  16. Nguyen S, McCulloch C, Brakeman P, Portale A, Hsu C. Being overweight modifies the association between cardiovascular risk factors and microalbuminuria in adolescents. Pediatrics. 2008;121 (1):37 –45[Abstract/Free Full Text]
  17. Fontaine K, Redden D, Wang C, Westfall A, Allison D. Years of life lost due to obesity. JAMA. 2003;289 (2):187 –193[Abstract/Free Full Text]
  18. Marder WD, Chang S. Childhood Obesity: Costs, Treatment Patterns, Disparities in Care, and Prevalent Medical Conditions. Stamford, CT: Thomson Medstat Research Brief; 2006
  19. Wang G, Dietz WH. Economic burden of obesity in youths aged 6 to 17 years: 1979–1999 [published correction appears in Pediatrics. 2002;109():195]. Pediatrics. 2002;109 (5). Available at: www.pediatrics.org/cgi/content/full/109/5/e81
  20. Skinner AC, Mayer ML, Flower K, Weinberger M. Health status and health care expenditures in a nationally representative sample: how do overweight and healthy-weight children compare? Pediatrics. 2008;121 (2). Available at: www.pediatrics.org/cgi/content/full/121/2/e269
  21. Hedley A, Ogden C, Johnson C, Carroll M, Curtin L, Flegal K. Prevalence of overweight and obesity among US children, adolescents, and adults, 1999–2002. JAMA. 2004;291 (23):2847 –2850[Abstract/Free Full Text]
  22. Koplan J, Liverman C, Kraak V, eds. Preventing Childhood Obesity: Health in the Balance. Washington, DC: National Academies Press; 2005
  23. Nord M, Andrews M, Carlson S. Household Food Security in the United States, 2005. Washington, DC: US Department of Agriculture; 2006. Economic Research Report 29
  24. Casey P, Szeto K, Lensing S, Bogle M, Weber J. Children in food-insufficient, low-income families: prevalence, health and nutrition status. Arch Pediatr Adolesc Med. 2001;155 (4):508 –514[Abstract/Free Full Text]
  25. Casey PH, Simpson PM, Gossett JM, et al. The association of child and household food insecurity with childhood overweight status. Pediatrics. 2006;118 (5). Available at: www.pediatrics.org/cgi/content/full/118/5/e1406
  26. Dubois L, Farmer A, Girard M, Porcherie M. Family food insufficiency is related to overweight among preschoolers. Soc Sci Med. 2006;63 (6):1503 –1516[CrossRef][Web of Science][Medline]
  27. Jyoti DF, Frongillo EA, Jones SJ. Food insecurity affects school children's academic performance, weight gain, and social skills. J Nutr. 2005;135 (12):2831 –2839[Abstract/Free Full Text]
  28. Alaimo K, Olson CM, Frongillo EA Jr. Low family income and food insufficiency in relation to overweight in US children: is there a paradox? Arch Pediatr Adolesc Med. 2001;155 (10):1161 –1167[Abstract/Free Full Text]
  29. Gundersen C, Lohman BJ, Eisenmann JC, Garasky S, Stewart SD. Child-specific food insecurity and overweight are not associated in a sample of 10- to 15-year-old low-income youth. J Nutr. 2008;138 (2):371 –378[Abstract/Free Full Text]
  30. Kaiser L, Melgar-Quiñonez H, Lamp C, Johns M, Sutherlin J, Harwood J. Food security and nutritional outcomes of preschool-age Mexican-American children. J Am Diet Assoc. 2002;102 (7):924 –929[CrossRef][Web of Science][Medline]
  31. Martin KS, Ferris AM. Food insecurity and gender are risk factors for obesity. J Nutr Educ Behav. 2007;39 (1):31 –36[CrossRef][Web of Science][Medline]
  32. Bronte-Tinkew J, Zaslow M, Capps R, Horowitz A, McNamara M. Food insecurity works through depression, parenting, and infant feeding to influence overweight and health in toddlers. J Nutr. 2007;137 (9):2160 –2165[Abstract/Free Full Text]
  33. Bhargava A, Jolliffe D, Howard LL. Socioeconomic, behavioral and environmental factors predicted body weights and household food insecurity scores in the Early Childhood Longitudinal Study: kindergarten. Br J Nutr. 2008;100 (2):438 –444[Web of Science][Medline]
  34. Jimenez-Cruz A, Bacardi-Gascon M, Spindler AA. Obesity and hunger among Mexican-Indian migrant children on the US–Mexico border. Int J Obes Relat Metab Disord. 2003;27 (6):740 –747[CrossRef][Web of Science][Medline]
  35. Matheson D, Varady J, Varady A, Killen J. Household food security and nutritional status of Hispanic children in the fifth grade. Am J Clin Nutr. 2002;76 (1):210 –217[Abstract/Free Full Text]
  36. Rose D, Bodor J. Household food insecurity and overweight status in young school children: results from the early childhood longitudinal study. Pediatrics. 2006;117 (2):464 –473[Abstract/Free Full Text]
  37. Finkelstein DM, Kubzansky LD, Capitman J, Goodman E. Socioeconomic differences in adolescent stress: the role of psychological resources. J Adolesc Health. 2007;40 (2):127 –134[CrossRef][Web of Science][Medline]
  38. Becker G. A theory of the allocation of time. Econ J. 1965;75 (299):493 –515[CrossRef]
  39. Becker G. A Treatise on the Family. Cambridge, MA: Harvard University Press; 1981
  40. Foster EM. How economists think about family resources and child development. Child Dev. 2002;73 (6):1904 –1914[CrossRef][Web of Science][Medline]
  41. McCubbin H, Patterson J. Systematic Assessment of Family Stress, Resources, and Coping: Tools for Research, Education, and Clinical Intervention. St Paul, MN: Department of Family Social Science; 1981
  42. McCubbin H, Thompson E, Thompson A, Fromer J. Stress, Coping, and Health in Families: Sense of Coherence and Resiliency. Thousand Oaks, CA: Sage Publications; 1999
  43. Friedemann M. Family economic stress and unemployment: child's peer behavior and parent's depression. Child Study J. 1986;16 (2):125 –142
  44. Gutman LM, McLoyd VC, Tokoyawa T. Financial strain, neighborhood stress, parenting behaviors, and adolescent adjustment in urban African American families. J Res Adolesc. 2005;15 (4):425 –449[CrossRef][Web of Science]
  45. Jaffee KD, Liu GC, Canty-Mitchell J, Qi RA, Austin J, Swigonski N. Race, urban community stressors, and behavioral and emotional problems of children with special health care needs. Psychiatr Serv. 2005;56 (1):63 –69[Abstract/Free Full Text]
  46. Parke RD, Coltrane S, Duffy S, et al. Economic stress, parenting, and child adjustment in Mexican American and European American Families. Child Dev. 2004;75 (6):1632 –1656[CrossRef][Web of Science][Medline]
  47. Sleskova M, Salonna F, Geckova AM, et al. Does parental unemployment affect adolescents' health? J Adolesc Health. 2006;38 (5):527 –535[CrossRef][Web of Science][Medline]
  48. Wadsworth ME, Compas BE. Coping with family conflict and economic strain: the adolescent perspective. J Res Adolesc. 2002;12 (2):243 –274[CrossRef][Web of Science]
  49. Haas JS, Lee LB, Kaplan CP, Sonneborn D, Phillips KA, Liang S. The association of race, socioeconomic status, and health insurance status with the prevalence of overweight among children and adolescents. Am J Public Health. 2003;93 (12):2105 –2110[Abstract/Free Full Text]
  50. Amato PR. The consequences of divorce for parents and children. J Marriage Fam. 2000;62 (4):1269 –1287[CrossRef][Web of Science]
  51. Seltzer JA. Families formed outside of marriage. J Marriage Fam. 2000;62 (4):1247 –1268[CrossRef][Web of Science]
  52. Björntorp P. Do stress reactions cause abdominal obesity and comorbidities? Obes Rev. 2001;2 (2):73 –86[CrossRef][Medline]
  53. Räikkönen K, Keltikangas-Jarvinen L, Adlercreutz H, Hautanen A. Psychosocial stress and the insulin resistance syndrome. Metabolism. 1996;45 (12):1533 –1538[CrossRef][Web of Science][Medline]
  54. Rosmond R, Bjorntorp P. Psychosocial and socio-economic factors in women and their relationship to obesity and regional body fat distribution. Int J Obes Relat Metab Disord. 1999;23 (2):138 –145[CrossRef][Web of Science][Medline]
  55. Jenkins SK, Rew L, Sternglanz RW. Eating behaviors among school-aged children associated with perceptions of stress. Issues Compr Pediatr Nurs. 2005;28 (3):175 –191[CrossRef][Medline]
  56. Hill JO, Trowbridge FL. Childhood obesity: future directions and research priorities. Pediatrics. 1998;101 (3 pt 2):570 –574[Abstract/Free Full Text]
  57. Ness A, Leary S, Mattocks C, et al. Objectively measured physical activity and fat mass in a large cohort of children. PLoS Med. 2007;4 (3):e97[CrossRef][Medline]
  58. Nicklas TA, Yang SJ, Baranowski T, Zakeri I, Berenson G. Eating patterns and obesity in children. The Bogalusa Heart Study. Am J Prev Med. 2003;25 (1):9 –16[CrossRef][Web of Science][Medline]
  59. Niemeier HM, Raynor HA, Lloyd-Richardson EE, Rogers ML, Wing RR. Fast food consumption and breakfast skipping: predictors of weight gain from adolescence to adulthood in a nationally representative sample. J Adolesc Health. 2006;39 (6):842 –849[CrossRef][Web of Science][Medline]
  60. Robila M, Krishnakumar A. Economic pressure and children's psychological functioning. J Child Fam Stud. 2006;15 (4):433 –441[CrossRef]
  61. Whitbeck LB, Simons RL, Conger RD, Wickrama KAS, Ackely KA, Edler GH Jr. The effects of parents' working conditions and family economic hardship on parenting behaviors and children's self-efficacy. Soc Psychol Q. 1997;60 :291 –303[CrossRef][Web of Science]
  62. Centers for Disease Control and Prevention, National Center for Health Statistics. National Health and Nutrition Examination Survey Data. Hyattsville, MD: US Department of Health and Human Services, Centers for Disease Control and Prevention; 1999–2002
  63. Ogden C, Kuczmarski R, Flegal K, et al. Centers for Disease Control and Prevention 2000 growth charts for the United States: improvements to the 1977 National Center for Health Statistics version. Pediatrics. 2002;109 (1):45 –60[Abstract/Free Full Text]
  64. Hamilton W, Cook J, Thompson W, et al. Household Food Security in the United States in 1995: Summary Report of the Food Security Measurement Project. Washington, DC: US Department of Agriculture; 1997
  65. Chrousos G, Gold P. The concepts of stress and stress system disorders: overview of physical and behavioral homeostasis. JAMA. 1992;267 (9):1244 –1252[Abstract/Free Full Text]
  66. Monat A, Lazarus R. Stress and coping: some current issues and controversies. In: Monat A, Lazarus R, eds. Stress and Coping: An Anthology. New York, NY: Columbia University Press; 1991
  67. Pearlin L, Lieberman MA, Menaghan EJ, Mullan JT. The stress process. J Health Soc Behav. 1981;22 (4):337 –356[CrossRef][Web of Science][Medline]
  68. Aneshensel C. Social stress: theory and research. Annu Rev Sociol. 1992;18 (1):15 –38[CrossRef][Web of Science]
  69. White JM, Klein DM. Family Theories. 2nd ed. Thousand Oaks, CA: Sage; 2002
  70. Rutter M. Child psychiatry: looking 30 years ahead. J Child Psychol Psychiatry. 1986;27 (6):803 –840[CrossRef][Web of Science][Medline]
  71. Sameroff AJ. Principles of development and psychopathology. In: Sameroff AJ, Emde RN, eds. Relationship Disturbances in Early Childhood: A Developmental Approach. New York, NY: Basic Books, Inc; 1992:17–32
  72. Fergusson DM, Lynskey MT. Adolescent resiliency to family adversity. J Child Psychol Psychiatry. 1996;37 (3):281 –292[Web of Science][Medline]
  73. Friedman RJ, Chase-Lansdale PL. Chronic adversities. In: Rutter M, Taylor E, eds. Child and Adolescent Psychiatry. 4th ed. Boston, MA: Blackwell Science; 2002:261–276
  74. Garmezy N, Masten AS. Chronic adversities. In: Rutter M, Taylor E, Hersov L, eds. Child and Adolescent Psychiatry. 2nd ed. Boston, MA: Blackwell Science Ltd; 1994:152–176
  75. Jones DJ, Forehand R, Brody G, Armistead L. Psychosocial adjustment of African American children in single-mother families: a test of three risk models. J Marriage Fam. 2002;64 (1):105 –115[CrossRef][Web of Science]
  76. Kolvin I, Miller FJW, Fleeting M, Kolvin PA. Risk/protective factors for offending with particular reference to deprivation. In: Rutter M, ed. Studies of Psychosocial Risk: The Power of Longitudinal Data. Cambridge, United Kingdom: Cambridge University Press; 1988:77–95
  77. Liaw R, Brooks-Gunn J. Cumulative familial risks and low-birthweight children's cognitive and behavioral development. J Clin Child Psychol. 1994;23 (4):360 –372[CrossRef][Web of Science]
  78. Sameroff AJ, Seifer R, Baldwin A, Baldwin C. Stability of intelligence from preschool to adolescence: the influence of social and family risk factors. Child Dev. 1993;64 (1):80 –97[CrossRef][Web of Science][Medline]
  79. Sameroff AJ, Seifer R, Barocas R, Zac M, Greenspan S. Intelligence quotient scores of 4-year-old children: social environmental risk factors. Pediatrics. 1987;79 (3):343 –350[Abstract/Free Full Text]
  80. World Health Organization. Composite International Diagnostic Interview (CIDI): Core Version 2.1 Interviewer's Manual. Geneva, Switzerland: World Health Organization; 1997
  81. Burgos NM, Lennon MC, Bravo M, Gutzman J. Depressive symptomatology in single women heads of households in Puerto Rico: a comparative analysis. Women Health. 1995;23 (3):1 –18[Web of Science][Medline]
  82. Jayakody R, Stauffer D. Mental health problems among single mothers: implications for work and welfare reform. J Soc Issues. 2000;56 (4):617 –634[CrossRef][Web of Science]
  83. Rudolph K, Hammen C. Age and gender as determinants of stress exposure, generation, and reactions in youngsters: a transactional perspective. Child Dev. 1999;70 (3):660 –677[CrossRef][Web of Science][Medline]
  84. Williamson DE, Birmaher B, Anderson BP, Al-Shabbout M, Ryan ND. Stressful life events in depressed adolescents: the role of dependent events during the depressive episode. J Am Acad Child Adolesc Psychiatry. 1995;34 (5):591 –598[CrossRef][Web of Science][Medline]
  85. Murry V, Bown A, Brody G, Cutrona C, Simons R. Racial discrimination as a moderator of the links among stress, maternal psychological functioning, and family relationships. J Marriage Fam. 2001;63 (4):915 –926[CrossRef][Web of Science]
  86. Evans G, English K. The environment of poverty: multiple stressor exposure, psychophysiological stress, and socioemotional adjustment [published correction appears in Child Dev. 2002;73(5):1]. Child Dev. 2002;73 (4):1238 –1248[CrossRef][Web of Science][Medline]
  87. Conger R, Elder G, Lorenz F, et al. Linking economic hardship to marital quality and instability. J Marriage Fam. 1990;52 (3):643 –656[CrossRef][Web of Science]
  88. Stata Corp. Stata Corp Statistical Software. Release 9. College Station, TX: Stata Corp; 2007
  89. Van Bell G, Fisher L, Heagerty P, Lumley T. Biostatistics: A Methodology for the Health Sciences. 2nd ed. New York, NY: Wiley; 2004
  90. Wooldridge J. Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: MIT Press; 2002
  91. Cochrane W. Sampling Techniques. 3rd ed. New York, NY: Wiley; 1977
  92. Korn E, Graubard B. Epidemiologic studies utilizing surveys: accounting for the sampling design. Am J Public Health. 1991;81 (9):1166 –1173[Abstract/Free Full Text]
  93. Dumouchel W, Duncan G. Using sample survey weights in multiple regression analyses of stratified samples. J Am Stat Assoc. 1983;78 (383):535 –543[CrossRef][Web of Science]
  94. Winship C, Radbill L. Sampling weights and regression analysis. Soc Methods Res. 1994;23 (2):230 –257[CrossRef]
  95. Simmons PS, Miles JM, Gerich JE, Haymond MW. Increased proteolysis: an effect of increases in plasma cortisol within the physiologic range. J Clin Invest. 1984;73 (2):412 –420[Web of Science][Medline]
  96. McKay CM, Bell-Ellison BA, Wallace K, Ferron JM. A multilevel study of the associations between economic and social context, stage of adolescence, and physical activity and body mass index. Pediatrics. 2007;119 (suppl 1):S84 –S91[Abstract/Free Full Text]
  97. Kant AK, Miner P. Physician advice about being overweight: association with self-reported weight loss, dietary, and physical activity behaviors of US adolescents in the National Health and Nutrition Examination Survey, 1999–2002. Pediatrics. 2007;119 (1). Available at: www.pediatrics.org/cgi/content/full/119/1/e142
  98. Foster GD, Sherman S, Borradaile KE, et al. A policy-based school intervention to prevent overweight and obesity. Pediatrics. 2008;121(4). Available at: www.pediatrics.org/cgi/content/full/121/4/e794
  99. Davis MM, Gance-Cleveland B, Hassink S, Johnson R, Paradis G, Resnicow K. Recommendations for prevention of childhood obesity. Pediatrics. 2007;120 (suppl 4):S229 –S253[Abstract/Free Full Text]
  100. Barlow SE. Expert Committee. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics. 2007;120 (suppl 4):S164 –S192[Abstract/Free Full Text]
  101. Stock S, Miranda C, Evans S, Plessis S, Ridley J, Yeh S, Chanoine JP. Healthy buddies: a novel, peer-led health promotion program for the prevention of obesity and eating disorders in children in elementary school. Pediatrics. 2007;120 (4). Available at: www.pediatrics.org/cgi/content/full/120/4/e1059
  102. von Hippel PT, Power B, Downey DB, Rowland NJ. The effect of school on overweight in childhood: gain in body mass index during the school year and during summer vacation. Am J Public Health. 2007;97 (4):696 –702[Abstract/Free Full Text]
  103. Spear BA, Barlow SE, Ervin C, et al. Recommendations for treatment of child and adolescent overweight and obesity. Pediatrics. 2007;120 (suppl 4):S254 –S288[Abstract/Free Full Text]
  104. Gable S, Chang Y, Krull J. Television watching and frequency of family meals are predictive of overweight onset and persistence in a national sample of school-aged children. J Am Diet Assoc. 2007;107 (1):53 –61[CrossRef][Web of Science][Medline]
PEDIATRICS (ISSN 1098-4275). ©2008 by the American Academy of Pediatrics

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Facebook Facebook   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?


This article has been cited by other articles:


Home page
 J. Nutr.Home page
C. Gundersen, S. Garasky, and B. J. Lohman
Food Insecurity Is Not Associated with Childhood Obesity as Assessed Using Multiple Measures of Obesity
J. Nutr., June 1, 2009; 139(6): 1173 - 1178.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow E-mail this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My File Cabinet
Right arrow Download to citation manager
Right arrowRequest Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via CrossRef
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Gundersen, C.
Right arrow Articles by Eisenmann, J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Gundersen, C.
Right arrow Articles by Eisenmann, J.
Related Collections
Right arrow Nutrition & Metabolism
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Facebook   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?