Abstract
Objective:
Subjective social status (SSS), perceived rank in the social ladder, is associated with weight, but determinants of SSS in youth remain unknown. We investigated relationships between youth SSS and income, food insecurity, parent SSS, and BMI change during an obesity intervention.
Methods:
Data came from a family-centered, community-based obesity intervention for low-income families. Parent and youth SSS were assessed using a validated, age-appropriate SSS scale. Food insecurity and socioeconomic factors were assessed in parents; child and parent weight-related data were measured at baseline and post-intervention.
Results:
Participants included 110 primarily Hispanic (97%), low-income youth and their parents. Food insecurity was reported in 66.4% of families. Youth SSS was positively associated with parent SSS (p=0.0014). In both parents and children, the association between income and SSS was moderated by food insecurity such that lower income was more strongly associated with lower SSS among food insecure households (p=0.0286 and p=0.0327, respectively). Youth SSS was not associated with youth BMI reduction.
Conclusions:
Youth SSS was not predictive of weight loss in this intervention. Intriguingly, the association between income and SSS was modified by food insecurity, suggesting that food insecurity shapes the contribution of socioeconomic factors to one’s perceived social status.
Keywords: socioeconomic status, obesity, Hispanics, education, family-based behavioral treatment program
Introduction
Socioeconomic status (SES), an objective measure of social rank based on education, income and occupation, is a significant predictor of health outcomes.[1, 2] However, methodological shortcomings in the use of traditional SES measures in youth are noted.[3–8] Shortcomings include traditional SES measures only reflecting the education, income, and occupational of a child’s parents at a single point in time and a failure to assess the child’s own perceived future trajectories and opportunities.[9] Research has demonstrated that subjective social status (SSS), a measure of one’s perceived relative social standing, is valuable for exploring social standing in adolescents and predicts health outcomes independently of SES.[3, 7]
Unlike traditional measures of SES, subjective measures of social status can account for earlier life circumstances, family history, perceived prospects for social mobility, and internalization of relative social standing and/or subordinate status.[10–12] SSS is associated with a wide range of physical and psychological health outcomes including diabetes[13], depression[13], and mental health[14, 15] in adults, and risk for cardiovascular disease in both adults and adolescents.[3, 13, 16] Thus, it is important to characterize factors that influence this construct among overweight Hispanic youth who face potential disparities in each of these health outcomes.
In adults, SSS is influenced by traditional measures of SES (i.e. education, income, and occupation) and psychosocial variables including depression, neighborhood satisfaction, and self-rated health.[17] Throughout child development, it has been posited that perceptions of one’s social rank may move from being primarily parent-based toward one’s own concept of social rank through experiential maturity and peer influence.[4] However, little is known about what factors influence youth determination of SSS.
Given that adult SSS is predicted by traditional measures of SES and psychosocial variables,[17] and a child’s perceived social rank may be influenced by parents’ perceived rank[4], we hypothesize parent SES and SSS will be positively associated with youth SSS. Given previous research[17] indicating that psychosocial factors predict SSS in adults, we further hypothesize that food insecurity is positively associated with youth SSS. Food insecurity has been associated with adverse physical and psychosocial development issues among youth[18, 19] and emotional distress among parents.[20] Additionally, food insecurity is often accompanied by obesity and is more prevalent in Hispanic households than in non-Hispanic white households.[21] Although many negative associations between food insecurity and health outcomes have been noted[22, 23], the relationship between SSS and food insecurity remains unclear.
In youth, SSS is associated with academic achievement[24], depression[24], and obesity[3]. Independent of SES, SSS has also been associated with weight status cross-sectionally[4] and longitudinally[6] in non-Hispanic black and white youth. Internalization of low perceived social status may be a psychosocial stressor that negatively alters health-related behaviors[25], such as eating and physical activity[26], which can impact obesity-related outcomes. Though both SES and SSS are associated with weight outcomes in free-living black and white youth, to our knowledge, no research has evaluated the relationship between SSS and BMI following an intervention, nor examined SSS among a Hispanic pediatric cohort with many Spanish-speaking parents.
The objective of this study was to explore the extent to which traditional SES factors and food insecurity predict SSS in youth, the concordance of parental and youth SSS, and whether SSS predicts BMI reduction in youth enrolled in a family-centered, community-based weight obesity prevention and treatment program delivered to a primarily Hispanic, low-income population. We hypothesized that low SES and food insecurity would be associated with low youth SSS and that higher youth SSS would be associated with greater BMI reduction at conclusion of the weight loss intervention.
Methods
Sample
Data were provided by participants in the Healthy Living Program (HeLP), a community-based obesity prevention and treatment program for children and their families referred by primary care providers. The program has been described previously.[27] HeLP served the majority Hispanic, low-income population cared for by safety-net clinics in a contiguous area of northern Denver and western counties in Colorado. Briefly, HeLP consisted of twelve, 2-hour sessions held twice per week indicating intensive program involvement for a total of 6 weeks, followed by monthly to bimonthly visits for up to 2 years offered by primary care providers trained in obesity counseling (24+ contact hours). HeLP included discussions about nutrition, parenting, and goal-setting combined with hands-on cooking classes and fitness sessions. In addition to targeting healthy weight, the curriculum was designed to build skills for cooking, shopping, and meal-planning to decrease food insecurity. Children aged 10 to 18 years with BMI >85th percentile[28], a sibling in this age range (if available), and one parent were invited to complete the surveys for this study during the enrollment period. At the first HeLP session, a trained research assistant requested a written consent or assent, as appropriate, of one parent who was the primary caregiver, the referred child aged 10–18 years with a BMI > 85th percentile[28], and one sibling in this age range (if available). Participants in this study were enrolled in HeLP from January 2014 through May 2016 (n=110 child-parent dyads) and were given questionnaires to assess SSS, our main variable of interest. Children who had a diagnosed developmental delay and/or were unable to complete the SSS survey were excluded. A parent completed additional surveys of food insecurity and demographics. During the first and last HeLP intervention sessions, each child was weighed, measured, and asked to complete surveys. All surveys were provided in either English or Spanish based on participant preference. The observational study of HeLP was approved by the Colorado Multiple Institutional Review Board (#13–3106). Families were reimbursed $30 for completing surveys at baseline and again at conclusion of the program, for a total of $60. No reimbursement for time or travel was provided. Small gifts to support program goals including measuring cups and jump ropes were given.
Perceived Social Status
At baseline, child and parental perceptions of social status were assessed using the youth and adult MacArthur SSS scales, respectively.[4] The MacArthur SSS scales assess one’s perceived social rank within American society as well as within their community (which for youth is defined as their school). Only children and parents who completed these questionnaires were included in our analyses. The youth version of the MacArthur SSS scale uses one picture of a 10-rung ladder that represents American society. Children are asked to choose the ladder rung that best represents their family’s place in American society. Higher scores indicate higher perceived family social status. Additionally, another picture of a 10-rung ladder represents the child’s school. Children are asked to choose the ladder rung that best represents their place on their school’s social ladder. The youth version of the MacArthur scale was developed and validated in a similar study population and two-month test-retest reliability demonstrated an intraclass correlation of 0.73 for the society ladder and 0.79 for the community (school) ladder.[4]
The adult SSS scales are similar and include one 10-rung ladder pictured to represent American society and the other 10-rung ladder pictured to represent the family’s community. Parental participants were asked to choose the location on each ladder that best represents their personal perception of current social standing taking into account the traditional measures that represent SES including income, education, and occupation. Higher scores indicate higher perceived social status.[29]
Objective SES
SES was measured through self-reported maternal education and household income. Maternal education included categories: ≤8th grade, <high school, high school, or some college and above. Gross monthly household income was self-reported using a dichotomous scale with income identified as below or above the US federal poverty level for a family of four at the time of study conception in 2013.[30] In our sample, 93.38% of families had a family of four or greater.
Food Insecurity
Food insecurity was assessed using the validated 2-item screen.[31] We chose this 2-item screener because it is becoming a standard-of-care in clinical settings and we believe the interpretation of the results will be more salient to clinicians who often refer youth to weight loss interventions. The items include: “Within the past 12 months, we worried whether our food would run out before we got money to buy more” and “Within the past 12 months, the food we bought just did not last and we did not have money to get more”. A 3-point scale was used as the response mechanism and respondents were considered food insecure if either ‘sometimes’ or ‘always’ was selected in response to either question.[31]
Health Measures and Demographics
Date of birth and sex were assessed in demographic questionnaires. Race and ethnicity were reported as two separate variables. Because 97% of our sample self-identified as Hispanic and overwhelmingly selected “other” as a race, we report race categories as white and “other.” Parent and child height and weight were measured at baseline and post-intervention by trained research assistants following a written protocol using a LifeSource™ UC-321 Precision Scale and a Charder HM200P Portstad Stadiometer. CDC guidelines were used to determine child and adult weight classification categories.
Statistical Analyses
Normality assumptions were evaluated and met for all dependent variables. Mean and standard deviations are presented for continuous variables and two-sample t-tests and ANOVA were performed to test the significance of mean differences between groups. Categorical variables were summarized as count and percent and a Chi-Square test was conducted for comparison between sex and race. Spearman correlation coefficients were assessed between SSS, SES, and food insecurity measures. The Wilcoxon rank sum test and Kruskal-Wallis test were performed to compare the medians between independent groups for non-normally distributed independent variables. Multiple logistic regression models were used to model the association between weight change and SSS scores, adjusting for child age and sex. Multivariable general linear models were used to model the relationship between SSS and SES, adjusting for maternal education. Interaction terms explored the effect of food insecurity on the strength of the relationship between SES and SSS. We hypothesized a stronger relationship between objective and perceived social status for those with food insecurity, since running out of money for food may make living with low-income especially salient in a child’s consciousness and increase the impact of poverty on SSS. Generalized linear mixed models were applied for all models accounting for clustering of siblings in the study. All the covariates in multivariable models were predefined with clinical and social relevance regardless of statistical significance. A p-value < 0.05 was considered statistically significant and all analyses were performed using SAS V9.4.
Results
Sample Characteristics
Table 1 includes characteristics of youth (n=110) and their parents. Details are included for the overall sample as well as stratified by child sex and race. Mean age of child participants was 12.6 (± 1.8) years and 40% of child participants were female. Additionally, 97% of child participants identified as Hispanic.
Table 1.
Characteristics of Parents and Children Enrolled in the Healthy Living Program, Mean (SD) or percentages
| Total Sample N=110 | By Child Sex | By Child Race | |||||
|---|---|---|---|---|---|---|---|
| Girls N=44 | Boys N=66 | p-value | White N=22 | Other N=88 | p-value | ||
| Demographics | |||||||
| Child age in years | 12.6 (1.8) | 12.7 (2.0) | 12.5 (1.7) | 0.5001 | 12.8 (2.1) | 12.5 (1.7) | 0.4845 |
| Child sex (% Female) | 40% | 45.4% | 38.6% | 0.5593 | |||
| Child ethnicity (% Hispanic) | 96.6% | 95.4% | 96.9% | 0.9999 | 81.8% | 100% | 0.0014 |
| Objective Socioeconomic factors | |||||||
| Maternal Education (%) | 0.6098 | 0.7197 | |||||
| <= 8th Grade | 17.9% | 23.8% | 14.1% | 9.1% | 20.2% | ||
| < High School | 23.6% | 23.8% | 23.4% | 31.8% | 21.4% | ||
| High School | 28.3% | 26.2% | 29.7% | 22.7% | 29.8% | ||
| College | 30.2% | 26.2% | 32.8% | 36.4% | 28.6% | ||
| Household Income (%) | 0.4357 | 0.9351 | |||||
| under $1962 per month | 59.8% | 52.8% | 64.2% | 11 (61.1%) | 44 (59.5%) | ||
| between $1962–2943 per month | 32.6% | 36.1% | 30.4% | 6 (33.3%) | 24 (32.4%) | ||
| over $2943 per month | 7.6% | 11.1% | 5.4% | 1 (5.6%) | 6 (8.1%) | ||
| Subjective Social Status (SSS) | |||||||
| Parental SSS, Society Parental SSS, Community Youth SSS, Society Youth, SSS, School |
4.6 (1.7) 5.1 (1.9) 5.8 (1.9) 6.8 (2.1) |
4.5 (1.7) 5.0 (1.7) 5.8 (1.7) 7.0 (2.1) |
4.6 (1.8) 5.1 (2.0) 5.8 (2.0) 6.7 (2.2) |
0.8392 0.7191 0.9949 0.6300 |
4.5 (1.3) 5.2 (1.7) 5.9 (2.0) 5.8 (2.8) |
4.6 (1.8) 5.0 (1.9) 5.7 (1.9) 7.0 (2.0) |
0.8751 0.8096 0.7906 0.1011 |
| Food Insecurity | 66.4% | 54.6% | 74.2% | 0.0322 | 72.7% | 64.8% | 0.4800 |
| Use of Services | |||||||
| WIC Program | 17.3% | 13.6% | 19.7% | 0.4101 | 9.1% | 19.3% | 0.3534 |
| Food Stamps/SNAP-ED | 29.1% | 27.3% | 30.3% | 0.7317 | 22.7% | 30.7% | 0.4625 |
| Food Banks | 8.2% | 13.6% | 4.6% | 0.1523 | 9.1% | 8.0% | 0.9999 |
| Parent Weight Status | |||||||
| Female BMI Classification, N=101 | 0.5398 | 0.1795 | |||||
| %Healthy Weight | 12.2% | 15.2% | 10.2% | 23.5% | 9.2% | ||
| %Overweight | 26.8% | 33.3% | 22.4% | 17.7% | 29.2% | ||
| %Class 1 Obesity | 30.5% | 24.2% | 34.7% | 17.7% | 33.9% | ||
| %Class 2 or 3 Obesity | 30.5% | 27.3% | 32.7% | 41.1% | 27.7% | ||
| Male BMI Classification, N=9 | 0.9999 | 0.4444 | |||||
| %Healthy Weight | -- | -- | -- | -- | -- | ||
| %Overweight | 44.4% | 50% | 40% | 0% | 57.1% | ||
| % Class 1 Obesity | 55.6% | 50% | 60% | 100% | 42.9% | ||
| %Class 2 or 3
Obesity |
-- | -- | -- | -- | -- | ||
| Child Weight Status | |||||||
| Child BMI z-score | 1.7 (0.8) | 1.6 (0.8) | 1.7 (0.8) | 0.3300 | 1.5 (1.1) | 1.7 (1.5) | 0.3086 |
| Child BMI percentile-for-sex-and-age | 0.0830 | 0.5015 | |||||
| %5th-<85th Normal Weight | 19.1% | 22.7% | 16.7% | 27.3% | 17.1% | ||
| %85th-<95th Overweight | 17.3% | 25.0% | 12.1% | 13.6% | 18.2% | ||
| %95th-99th Obesity | 50.9% | 36.4% | 60.6% | 40.9% | 53.4% | ||
| %>99th Severe Obesity | 12.7% | 15.9% | 10.6% | 18.2% | 11.3% | ||
Mean and standard deviation or percentages are presented. Two-sample t-tests were used to compare the mean differences between comparison groups. Categorical variables (e.g. maternal education) were summarized as count and percent and Chi-Square test was conducted for comparison between sex and race. Significance of P-value<0.05 is shown in bold.
The majority of mothers in the sample completed high school or less (69.8%). On average, family members living at home included 2.2 (± 0.8) adults and 2.7 (± 1.0) children, with 89% of homes having at least two adults (data not shown). The majority of participants had a household income under $1,962 per month (59.8%). The mean societal SSS for parents was 4.6 (± 1.7) and 5.8 (± 1.9) for children on a scale of 1–10 with 1 representing the lowest possible SSS and 10 representing the highest possible SSS of their family relative to other families in American society, respectively. Mean parent community SSS was 5.1 (± 1.9), while mean youth community (school) SSS was 6.8 (± 2.1) on an identical 1–10 scale with 1 representing the lowest possible SSS and 10 representing the highest possible SSS. For adults, community SSS was based on their perception of status in the community in which the adult participants lived whereas for children, community SSS was based on the child’s perception of status at their school. Sixty-six percent of all families reported food insecurity and 29% indicated use of food stamps/SNAP-ED. Food bank use was reported in 8% of families and 17% of families used Women, Infants, and Children (WIC) services.
The majority of parents were classified as having at least class 1 obesity, and 31% of female parents had class 2 or 3 obesity. The majority of children had overweight/obesity (17% with overweight, 51% with non-severe obesity and 13% with severe obesity). When stratified by sex, obesity and severe obesity were more prevalent in boys (71%) than girls (52%). Obesity and severe obesity were also less prevalent in whites (59%) than in all other races (65%).
Table 2 includes data on weight changes from baseline (week 1) to week 6 of the weight loss intervention among the total sample of youth (n=110) and among youth with overweight or obesity (n=89). Among youth with overweight or obesity, we observed a significant decrease in BMI percent of 95th percentile change from week 1 to week 6 (p = 0.0271) but not BMI (p = 0.1067). Among the total sample, which included the siblings with normal weight, we did not observe a significant decrease in BMI percent of 95th percentile change or BMI from week 1 to week 6.
Table 2.
Weight Changes from Baseline to Week 6 among Youth participating in the Healthy Living Program Intervention
| Pre (Week 1) | Post (Week 6) | Mean Difference | P-value | |
|---|---|---|---|---|
| Total Sample (n=110) | ||||
| BMI | 26.83 (5.3) | 26.77 (5.3) | −0.08 | 0.7220 |
| BMI Percent of 95th Percentile | 107.45 (20.8) | 106.47 (20.6) | −0.82 | 0.4210 |
| Youth with Overweight and Obesity (n=89) | ||||
| BMI | 28.34 (4.4) | 28.03 (4.8) | −0.30 | 0.1067 |
| BMI Percent of 95th Percentile | 113.64 (16.7) | 11.68 (17.9) | −1.75 | 0.0271 |
Mean and standard deviation are presented. Significance of P-value<0.05 is shown in bold.
Associations of Parent and Child SSS, SES, and Food Insecurity
Spearman correlation coefficients among variables of SSS, SES, and food insecurity are reported in Table 3. Child SSS society was significantly correlated with child SSS school, parent SSS society, parent SSS community, and monthly income (p < 0.05) and was nearly significantly correlated with maternal education and food insecurity (p < 0.10). The child SSS school was significantly correlated with monthly income (p = 0.0190) and was nearly significantly correlated with parent SSS community and food insecurity (p < 0.10). Parent SSS society was significantly correlated with parent SSS community and maternal education (p < 0.05) and was nearly significantly correlated with monthly income (p = 0.0691). Parent SSS community was significantly correlated with monthly income and maternal education (p = 0.0056 and p = 0.0001, respectively). Food insecurity was significantly correlated with monthly income and maternal education (p = 0.0252 and p = 0.0448, respectively).
Table 3.
Spearman Correlation Coefficients among Variables of Subjective Social Status, Socioeconomic Status, and Food Insecurity
| Child SSS Society | Child SSS School | Parent SSS Society | Parent SSS Community | Monthly Income | Maternal Education | Food Insecurity | |
|---|---|---|---|---|---|---|---|
| Child SSS Society | - | ||||||
| Child SSS School | 0.31 | - | |||||
| 0.0023 | |||||||
| Parent SSS Society | 0.35 | 0.11 | - | ||||
| 0.0006 | 0.2800 | ||||||
| Parent SSS Community | 0.47 | 0.17 | 0.73 | - | |||
| <.0001 | 0.0962 | <0.0001 | |||||
| Monthly Income | 0.30 | 0.26 | 0.20 | 0.30 | - | ||
| 0.0057 | 0.0190 | 0.0691 | 0.0056 | ||||
| Maternal Education | 0.17 | 0.05 | 0.28 | 0.38 | 0.20 | - | |
| 0.0927 | 0.6426 | 0.0041 | 0.0001 | 0.0628 | |||
| Food Insecurity | −0.18 | −0.18 | −0.02 | −0.13 | −0.23 | 0.20 | - |
| 0.0732 | 0.0793 | 0.8275 | 0.1805 | 0.0252 | 0.0448 |
Significance of P-value<0.05 is shown in bold.
Results of multiple linear regression modeling the associations of parent SSS on youth SSS (Model 1) and SES and food insecurity on youth SSS (Model 2) are reported in Table 4. In Model 1, youth societal SSS was significantly associated with parent societal SSS (β = 0.49; p = 0.0014). There were no significant relationships between parent society SSS or community SSS with child school SSS.
Table 4.
Multiple Linear Regression results for the association of Youth Subjective Social Status (SSS) with Parent SSS (Model 1) and Youth SSS with Socioeconomic Status and Food Insecurity (Model 2)
| Total Sample (n=110) | Youth Society SSS | Youth School SSS | Parent Society SSS | Parent Community SSS | ||||
|---|---|---|---|---|---|---|---|---|
| Independent Variables | β (SE) | P-value | β (SE) | P-value | β (SE) | P-value | β (SE) | P-value |
| Model 1* | ||||||||
| Parent Society SSS | 0.49 (0.15) | 0.0014 | 0.20 (0.18) | 0.2762 | - | - | - | - |
| Parent Community SSS | 0.01 (0.14) | 0.9569 | 0.01 (0.14) | 0.9334 | - | - | - | - |
| Model 2** | ||||||||
| Monthly Income <$1962 | 0.46 (0.78) | 0.5619 | −.033 (0.87) | 0.7088 | 0.66 (0.63) | 0.2987 | 0.31 (0.74) | 0.6747 |
| Maternal education, less than 8th grade | −0.75 (0.61) | 0.2222 | −0.41 (0.68) | 0.5521 | −1.48 (0.49) | 0.0032 | −1.24 (0.58) | 0.0350 |
| Food Insecurity | 0.35 (0.62) | 0.5807 | −0.75 (0.69) | 0.2818 | −0.04 (0.53) | 0.9441 | 0.24 (0.62) | 0.7016 |
| Monthly Income <$1962 and Food Insecurity | −2.05 (0.94) | 0.0327 | −0.53 (1.05) | 0.6143 | −1.73 (0.77) | 0.0286 | −1.13 (0.90) | 0.2163 |
Multiple Linear Regression model included independent variables, Parent Community SSS and Parent Society SSS
Multiple Linear Regression model included independent variables, monthly income <$1962, maternal education, food insecurity, and an interaction between monthly income <$1962 and food insecurity
Significance of P-value<0.05 is shown in bold.
In Model 2, maternal education ≤8th grade was significantly associated with lower parental SSS both in society (β = −1.48; p = 0.0032) and in their community (β = −1.24; p = 0.0350). The association between household income and SSS in society was moderated by food insecurity of parent-child dyads such that lower household income was more strongly associated with lower parental (β = −1.73; p = 0.0286) and youth (β = −2.05; p = 0.0327) SSS in society among households with food insecurity. Additionally, 18 families (36 children) had siblings enrolled in the study (36/110=32.7%). Thus, we ran all models accounting for clustering of siblings in the dataset and though parameter estimates were changed slightly, no difference was observed in the conclusion of our reported findings.
Table 5 includes odds ratio estimates for the association of youth SSS and BMI reduction following the HeLP. Youth SSS was not associated with change in child BMI relative to the 95th percentile or BMI z-score during the weight loss intervention.
Table 5.
Odds Ratio Estimates for the association of Baseline Youth Subjective Social Status (SSS) and Weight Loss Outcomes Following the Healthy Living Program Intervention*
| Total Sample (N=110) | Change in Child BMI Percent of 95th Percentile | Child BMI Z-score Change | ||||
|---|---|---|---|---|---|---|
| Independent Variables | Point Estimate | 95% CI | P-value | Point Estimate | 95% CI | P-value |
| Youth Society SSS | 1.28 | 0.90–1.8 | 0.1680 | 1.35 | 0.93–1.95 | 0.1101 |
| Youth School SSS | 1.09 | 0.84–1.40 | 0.5343 | 1.11 | 0.86–1.44 | 0.4363 |
Multiple logistic regression models were employed to model the association between weight change and SSS scores while adjusting for child age and sex.
Discussion
We characterized sociodemographic factors that inform the construct of SSS and assessed the extent to which youth SSS predicts weight loss following participation in a family- and community-based pediatric weight loss intervention. In our cohort of low-income, primarily Hispanic youth with overweight/obesity (OW/OB), we observed that parental perception of their position on the social ladder in society was related to their child’s perception of their family rank in the societal milieu. In both parents and children, the association between household income and SSS was moderated by food insecurity, indicating that lower household income was more strongly associated with lower SSS among families with food insecurity. Contrary to our hypothesis, youth SSS was not predictive of child weight loss outcomes, perhaps because of the intervention’s heavy focus on skill-building to ameliorate food insecurity.
The adult participants consisted of low-income, primarily Hispanic parents of youth with OW/OB who participated in the intervention. Additionally, almost 90% of parents had OW/OB. The average parent SSS was 4.6 and 5.1 in relation to society and their community, respectively, lower than non-Hispanic white women (SSS mean=6.8) and African American adults (societal SSS=6.2 and community SSS =7.6) in other studies.[29, 32] Differences in SSS by race have previously been reported[17], but our sample was consistent with another study of low-income Hispanic adults who appear to report the lowest perceived social rank among racial/ethnic groups in the United States.[14]
In our low-SES adult cohort, parents’ view of themselves in society was only significantly correlated with maternal education, whereas parents’ view of themselves within their community was significantly correlated with monthly income and maternal education, but not food insecurity. In adjusted models, however, household income was not associated with SSS (either society or community among participants who did not report being food insecure). This is congruent with findings from other adult populations.[29, 33] The use of services including food banks, WIC, and food stamps/SNAP-ED was also not predictive of parent SSS (data not shown). However, SSS was positively associated with maternal education such that SSS was higher among those with a college degree compared to those with a high school education or less. The association between household income and parent SSS in society was moderated by food insecurity, such that lower household income was more strongly associated with lower reported parental SSS in society among families with food insecurity. A previous study in socioeconomically diverse non-Hispanic black and white adults demonstrated that SSS was associated with traditional measures of SES (i.e. income and education), but that only men (but not women) perceived employment status as important in defining their position in the social hierarchy.[17] Several psychosocial variables including self-rated health, neighborhood satisfaction, and depressive symptomology have also been related to adult SSS[17], but we are not aware of any studies that have considered the relationship of food insecurity or services utilized (i.e. food banks, WIC, and food stamps/SNAP-ED). Additionally, we are not aware of any studies characterizing predictors of the SSS construct among low-income, Hispanic adults. Our data suggests that among low-income Hispanic adults whose children have OW/OB, low levels of education and the experience of both poverty and food insecurity can negatively impact SSS.
Our child cohort in the HeLP intervention was comprised of low-income, primarily Hispanic youth with OW/OB (80.9%) who were referred by their primary care provider. In youth, the mean society SSS was 5.8 and the mean school SSS was 6.8, which is consistent with previous research in youth[4, 6], but higher than what their parents reported. Higher scores in the children relative to their parents may be because subjective measures of social status have the ability to account for perceived prospects for social mobility.[10–12] Thus, though these children lived in low-income households, they may have perceived themselves to be on a different trajectory than their parents. Regardless, in both correlational models and adjusted models, youth society SSS was positively related to parent society SSS, such that parents who reported a higher society SSS were more likely to have a child who reported a higher society SSS. This may be due to the wording of the youth society SSS question, which asks children to choose the ladder rung that best represents their family’s place in American society, not their own as the school SSS does. Thus, the children were likely reporting on their perception of their collective family’s social standing, but may not have internalized this as their own personal social standing. This hypothesis is supported by our findings that youth school SSS was not significantly associated with parent society or community SSS, nor was it related to any measure of SES alone, including income, education, food insecurity, or services the family utilized (i.e. food banks, WIC, and food stamps/SNAP-ED; data not shown). This differs from previous research in non-Hispanic black and white adolescents, which observed statistically significant, yet weak, correlations between youth SSS and parent socioeconomic factors.[4] This may be due to differences in the low-income status of our cohort or a difference due to race/ethnicity, as previous reports indicate differences in how SSS is determined by race.[17] However, consistent with this relationship in parents, we observed an association between household income and youth society SSS that was moderated by food insecurity. This suggests that food insecurity has important effects on the SSS of youth in the lowest income households.
SSS has been associated with weight status cross-sectionally[4] and longitudinally[6] in non-Hispanic black and white youth. Additionally, when compared with SES, SSS is a stronger predictor of weight status in non-Hispanic black and white youth[4, 6], however, this relationship has not been assessed in Hispanics. The examination of the relationship between SSS and weight loss following an intervention is reasonable, as internalization of low perceived social status may be a stressor that negatively alters health-related behaviors[25], such as eating and physical activity[26], which can hinder a person’s ability to lose weight during a weight loss intervention. In fact, recent work from our research group demonstrated Hispanic young adults experimentally randomized to a scenario simulating a low social status position consumed 130 additional calories at one meal and showed a significant increase in percent of daily calorie needs and saturated fat consumed.[34] This relationship has been confirmed in other populations as well[35, 36], suggesting that low SSS may impact eating behavior. Contrary to our hypothesis, we did not see a significant relationship between youth SSS variables and changes in child BMI percentile or child BMI z-score. This may be for a variety of reasons including: (1) we did not have the power to detect such changes with a sample size of 110, (2) SSS has no bearing on a person’s desire or physiological capacity to lose weight, or (3) the intervention provided skills to overcome food insecurity and social support for lifestyle change among those with low baseline SSS and SES. In order to target health disparities, weight management programs should seek effectiveness among low SSS/SES populations. However, widely disseminated childhood obesity programs have shown significantly worse outcomes among lower SES participants.[37, 38] If the association between obesity and SSS is causal, our results suggest that the relationship may be explained more by the role of SSS in weight gain rather than its role in prevention of effective treatment. Further research is needed to investigate the extent to which SSS plays a role in weight loss, especially in populations facing obesity-related health disparities.
Our study has limitations which must be considered. Our cohort was comprised of low-income, primarily Hispanic families participating in a family- and community-based pediatric weight loss intervention, so the population was biased by treatment-seeking. Additionally, the findings from this study may not be generalizable to other racial/ethnic or sociodemographic populations. Although we accounted for traditional measures of SES (income, education), measures related to SES (food insecurity, use of food banks, WIC, and food stamps/SNAP-ED), and parental SSS in our various models, there are a variety of psychosocial influences that significantly predict adult SSS that we did not assess.[17] These include depressive symptomology, neighborhood dissatisfaction, and self-rated health.[17] Further research should examine the extent to which additional psychosocial variables influence SSS in youth.
This study has important implications. Traditional measures of SES have been used pervasively for studying health disparities over the life course, but methodological shortcomings in the use of traditional SES measures in youth are important to note.[3–8] Youth may not be privy to information regarding parental or household income and may not accurately report parental education or occupation. Additionally, traditional SES fails to capture the child’s own perceived future trajectories and opportunities.[9] Thus, we encourage researchers to capture both measures of SES and SSS whenever possible. Given the easily obtained single ladder questions that can reflect both family and youth SSS, it is highly feasible to include in future research.
Our study demonstrated that a parent’s perception of their position on the societal social ladder was associated with the child’s perception of their family’s position on the social rank ladder. Additionally, in both parents and children, the association between household income and SSS was moderated by food insecurity, suggesting that food insecurity is an important influence on perceived social status. Youth SSS was not predictive of child BMI outcomes among low-income Hispanic youth participating in this weight loss intervention.
Study Importance Questions.
What is already known about this subject?
Subjective social status (SSS), a measure of one’s perceived relative social standing and internalization of subordinate status, may be a better measure for exploring social standing in adolescents than objective measures of socioeconomic status (SES).
In adults, the factors that predict SSS include traditional measures of SES (i.e. education, income, and occupation) and psychosocial variables including depression, neighborhood satisfaction, and self-rated health. Characterization of the factors that influence the construct of SSS in youth is needed.
SSS has also been associated with weight status cross-sectionally and longitudinally in non-Hispanic black and white youth.
What does your study add?
Youth SSS was positively associated with parent SSS, suggesting that parents’ perceptions of their social standing may influence their child’s perception of their social standing.
In both parents and children, the association between income and SSS was modified by food insecurity, suggesting that food insecurity shapes the contribution of socioeconomic factors to one’s perceived social status.
Youth SSS was not predictive of youth weight loss among low-income Hispanic youth in this family-based weight management program.
Acknowledgements
We thank Commerce City Parks and Recreation, Thornton Parks and Recreation, and Cooking Matters Colorado™ for their partnership in delivering HeLP, and KidsFirst Health Care, Salud Family Health Center, Denver Health Montbello Family Health Center, Clinica Family Health Services, Rocky Mountain Youth Clinic, and Mountainland Pediatrics for their assistance with recruiting families.
Funding: This project was funded by Colorado Health Foundation Grant #5510 (PI-Haemer) and K23 NIDDK K23DK104090 (PI-Haemer) and T32 DK07658 (Cardel). Dr. Cardel is supported by the National Institutes of Health National Heart, Lung, and Blood Institute (R25HL126146, R01HL120960, and K01HL141535) and the National Center For Advancing Translational Sciences of the National Institutes of Health (UL1TR001427). This paper is also supported by the Colorado Clinical and Translational Science Institute (UL1RR025780). The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the Colorado Health Foundation or the National Institutes of Health.
Footnotes
Disclosure: The authors declared no conflict of interest.
Contributor Information
DR. Michelle I. Cardel, University of Florida, Department of Health Outcomes and Biomedical Informatics, PO Box 100147, Gainesville, FL 32610, 352-273-8811, mcardel@ufl.edu.
Suhong Tong, University of Colorado Denver, Department of Biostatistics and Informatics, Building 500, Room N2227A, Anschutz Medical Campus, Aurora, CO 80045 Suhong.tong@ucdenver.edu.
Greg Pavela, University of Alabama at Birmingham, Department of Health Behavior, School of Public Health, 227K RPHB, 1665 University Boulevard, Birmingham, AL 35294, pavela@uab.edu.
DR. Emily Dhurandhar, Texas Tech University, Department of Kinesiology and Sport Management, Box 43011, Lubbock, TX 79409, 806-834-6556, Emily.dhurandhar@ttu.edu.
Darci Miller, University of Florida, Department of Health Outcomes and Biomedical Informatics, PO Box 100147, Gainesville, FL 32610, 352-294-5980, dmiller5@ufl.edu.
Richard Boles, University of Colorado Denver, Department of Pediatrics, Section of Nutrition, 12631 East 17th Avenue, Mailstop F561, Aurora, Colorado 80045, 303-724-3312, Richard.boles@UCDenver.edu.
Matthew Haemer, University of Colorado Denver, Department of Pediatrics, Section of Nutrition, 12631 East 17th Avenue, Mailstop F561, Aurora, Colorado 80045, 303-724-3312, Matthew.Haemer@UCDenver.edu.
References
- 1.Marmot MG, et al. , Health inequalities among British civil servants: the Whitehall II study. Lancet, 1991. 337(8754): p. 1387–93. [DOI] [PubMed] [Google Scholar]
- 2.Marmot MG and Shipley MJ, Do socioeconomic differences in mortality persist after retirement? 25 year follow up of civil servants from the first Whitehall study. Bmj, 1996. 313(7066): p. 1177–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Goodman E, et al. , Impact of Objective and Subjective Social Status on Obesity in a Biracial Cohort of Adolescents. Obesity Research, 2003. 11(8): p. 1018–1026. [DOI] [PubMed] [Google Scholar]
- 4.Goodman E, et al. , Adolescents’ Perceptions of Social Status: Development and Evaluation of a New Indicator. Pediatrics, 2001. 108(2): p. e31. [DOI] [PubMed] [Google Scholar]
- 5.Goodman E, et al. , Perceived Socioeconomic Status: A New Type of Identity That Influences Adolescents’ Self-Rated Health. Journal of Adolescent Health, 2007. 41(5): p. 479–487. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Goodman E, et al. , Developmental Trajectories of Subjective Social Status. Pediatrics, 2015. 136(3): p. e633–e640. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Goodman E, et al. , Social disadvantage and adolescent stress. Journal of Adolescent Health, 2005. 37(6): p. 484–492. [DOI] [PubMed] [Google Scholar]
- 8.Slopen N, et al. , Socioeconomic and Other Social Stressors and Biomarkers of Cardiometabolic Risk in Youth: A Systematic Review of Less Studied Risk Factors. PLoS ONE, 2013. 8(5): p. e64418. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Hollingshead A, Four factor index of social status. 1975, New Haven, CT: Yale University Press. [Google Scholar]
- 10.Goodman E, et al. , Adolescents’ perceptions of social status: Development and evaluation of a new indicator. Pediatrics, 2001. 108(2). [DOI] [PubMed] [Google Scholar]
- 11.Goodman E, The role of socioeconomic status gradients in explaining differences in US adolescents’ health. American Journal of Public Health, 1999. 89(10): p. 1522–1528. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Goodman E, et al. , Perceived socioeconomic status: A new type of identity that influences adolescents’ self-rated health. Journal of Adolescent Health, 2007. 41(5): p. 479–487. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Singh-Manoux A, Adler NE, and Marmot MG, Subjective social status: its determinants and its association with measures of ill-health in the Whitehall II study. Social Science & Medicine, 2003. 56(6): p. 1321–1333. [DOI] [PubMed] [Google Scholar]
- 14.Franzini L and Fernandez-Esquer ME, The association of subjective social status and health in low-income Mexican-origin individuals in Texas. Social Science & Medicine, 2006. 63(3): p. 788–804. [DOI] [PubMed] [Google Scholar]
- 15.Leung B, et al. , Comparing three measures of health status (perceived health with Likert-type scale, EQ-5D, and number of chronic conditions) in Chinese and white Canadians. Med Care, 2007. 45(7): p. 610–7. [DOI] [PubMed] [Google Scholar]
- 16.Miyakawa M, et al. , Subjective social status: its determinants and association with health in the Swedish working population (the SLOSH study). The European Journal of Public Health, 2012. 22(4): p. 593–597. [DOI] [PubMed] [Google Scholar]
- 17.Shaked D, et al. , Indicators of subjective social status: Differential associations across race and sex. SSM - Population Health. [DOI] [PMC free article] [PubMed]
- 18.Alaimo K, Olson CM, and Frongillo EA Jr., Food insufficiency and American school-aged children’s cognitive, academic, and psychosocial development. Pediatrics, 2001. 108(1): p. 44–53. [PubMed] [Google Scholar]
- 19.Rose-Jacobs R, et al. , Household food insecurity: associations with at-risk infant and toddler development. Pediatrics, 2008. 121(1): p. 65–72. [DOI] [PubMed] [Google Scholar]
- 20.Ashiabi GS and O’Neal KK, Food insecurity and adjustment problems in a national sample of adolescents. Journal of Children and Poverty, 2007. 13(2): p. 111–132. [Google Scholar]
- 21.Hernandez DC, Reesor LM, and Murillo R, Food insecurity and adult overweight/obesity: Gender and race/ethnic disparities. Appetite, 2017. 117: p. 373–378. [DOI] [PubMed] [Google Scholar]
- 22.Lee AM, Scharf RJ, and DeBoer MD, Association between kindergarten and first-grade food insecurity and weight status in U.S. children. Nutrition, 2018. 51-52: p. 1–5. [DOI] [PubMed] [Google Scholar]
- 23.Dhurandhar EJ, The food-insecurity obesity paradox: A resource scarcity hypothesis. Physiology & Behavior, 2016. 162: p. 88–92. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Destin M, et al. , “Feeling” hierarchy: the pathway from subjective social status to achievement. J Adolesc, 2012. 35(6): p. 1571–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Demakakos P, et al. , Socioeconomic status and health: the role of subjective social status. Social science & medicine (1982), 2008. 67(2): p. 330–340. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Cardel MI, et al. , The effects of experimentally manipulated social status on acute eating behavior: A randomized, crossover pilot study. Physiology & Behavior, 2016. 162: p. 93–101. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Fisher JO and Birch LL, Parents’ restrictive feeding practices are associated with young girls’ negative self-evaluation of eating. J Am Diet Assoc, 2000. 100: p. 1341–1346. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Kuczmarski RJ, et al. , 2000. CDC Growth Charts for the United States: methods and development. Vital Health Stat 11, 2002(246): p. 1–190. [PubMed] [Google Scholar]
- 29.Adler NE, et al. , Relationship of subjective and objective social status with psychological and physiological functioning: preliminary data in healthy white women. Health Psychol, 2000. 19(6): p. 586–92. [DOI] [PubMed] [Google Scholar]
- 30.Services U.S.D.o.H.a.H. 2013. Poverty Guidelines. 2013; Available from: https://aspe.hhs.gov/prior-hhs-poverty-guidelines-and-federal-register-references.
- 31.Hager ER, et al. , Development and Validity of a 2-Item Screen to Identify Families at Risk for Food Insecurity. Pediatrics, 2010. 126(1): p. e26–e32. [DOI] [PubMed] [Google Scholar]
- 32.Subramanyam MA, et al. , Subjective social status and psychosocial and metabolic risk factors for cardiovascular disease among African Americans in the Jackson Heart Study. Soc Sci Med, 2012. 74(8): p. 1146–54. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Subramanyam MA, et al. , Subjective social status and psychosocial and metabolic risk factors for cardiovascular disease among African Americans in the Jackson Heart Study. Social Science & Medicine, 2012. 74(8): p. 1146–1154. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Cardel M, et al. , The effects of experimentally manipulated social status on acute eating behavior: A randomized, crossover pilot study. Physiology & behavior, 2016. 162: p. 93–101. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Bratanova B, et al. , Poverty, inequality, and increased consumption of high calorie food: Experimental evidence for a causal link. Appetite, 2016. 100: p. 162–171. [DOI] [PubMed] [Google Scholar]
- 36.Cheon BK and Hong Y-Y, Mere experience of low subjective socioeconomic status stimulates appetite and food intake. Proceedings of the National Academy of Sciences, 2016. [DOI] [PMC free article] [PubMed]
- 37.Butte NF, et al. , Efficacy of a Community- Versus Primary Care-Centered Program for Childhood Obesity: TX CORD RCT. Obesity (Silver Spring), 2017. 25(9): p. 1584–1593. [DOI] [PubMed] [Google Scholar]
- 38.Fagg J, et al. , From trial to population: a study of a family-based community intervention for childhood overweight implemented at scale. Int J Obes (Lond), 2014. 38(10): p. 1343–9. [DOI] [PMC free article] [PubMed] [Google Scholar]