Childhood obesity's influence on socioeconomic disparities in young adolescents' mental health.

PURPOSE: We investigated whether socioeconomic inequalities in young adolescents' mental health are partially due to the unequal distribution of childhood obesity across socioeconomic positions (SEP), i.e. differential exposure, or due to the effect of obesity on mental health being more detrimental among certain SEPs, i.e. differential impact. METHODS: We studied 4660 participants of the Generation R study, a population-based study in the Netherlands. SEP was estimated by mother's education and household income at age five of the child. We estimated the contribution of the mediating and moderating effects of high body fat percentage to the disparity in mental health. This was done through a four-way decomposition using marginal structural models with inverse probability of treatment weighting. RESULTS: Comparing children with the least to most educated mothers and the lowest to highest household income, the total disparity in emotional problems was 0.98 points (95%CI:0.35-1.63) and 1.68 points (95%CI:1.13-2.19), respectively. Of these total disparities in emotional problems, 0.50 points (95%CI:0.15-0.85) and 0.24 points (95%CI:0.09-0.46) were due to the differential exposure to obesity. Obesity did not contribute to disparities in behavioural problems. CONCLUSION: Addressing the heightened obesity prevalence among children in low SEP families may reduce inequalities in emotional problems in early adolescence.

What maternal educational mobility tells us about the mother's parenting routines, offspring school achievement and intelligence.

BACKGROUND: Educational mobility at the macro-level is a common measure of social inequality. Nonetheless, the correlates of mobility of education at the individual level are less well studied. We evaluated whether educational mobility of the second generation (compared to the first generation level) predicts differences in parenting practices of the second generation and school achievement and intelligence in the third generation. METHODS: Data from a population-based cohort of children in the Netherlands (N = 3547; 49.4% boys) were analyzed. Maternal, grandparental education and family routines, a parenting practice, were reported by the mother. Child school achievement at the end of primary school (∼12 years, with the national Dutch academic test score) and child intelligence (∼6 and 13 years) were measured in a standardized manner. Also, a child genome-wide polygenic score of academic attainment was calculated. To estimate the effect of educational mobility, inverse probability-weighted linear models and Diagonal Reference Models (DRM) were used. RESULTS: Upward maternal educational mobility was associated with better offspring school achievement, higher intelligence, and more family routines if compared to offspring of mothers with no upward mobility. However, mothers did not implement the same level of family routines as similarly educated mothers and grandfathers who already had achieved this educational level. Likewise, children of mothers with upward educational mobility had lower school achievement and intelligence than children of similarly educated mothers with no mobility. Child's genetic potential for education followed a similar association pattern with higher potential in children of upward mobile mothers. CONCLUSION: Policymakers might overlook social inequalities when focused on parental socioeconomic status. Grandparental socioeconomic status, which independently predicts child school achievement, intelligence, and parental family routines, should also be assessed. The child's genetic endowment reflects the propensity for education across generations that partly underlies mobility and some of its effect on the offspring.

Social inequalities in child development: the role of differential exposure and susceptibility to stressful family conditions.

BACKGROUND: Stressful family conditions may contribute to inequalities in child development because they are more common among disadvantaged groups (ie, differential exposure) and/or because their negative effects are stronger among disadvantaged groups (ie, differential impact/susceptibility). We used counterfactual mediation analysis to investigate to what extent stressful family conditions contribute to inequalities in child development via differential exposure and susceptibility. METHODS: We used data from the Generation R Study, a population-based birth cohort in the Netherlands (n=6842). Mother's education was used as the exposure. Developmental outcomes, measured at age 13 years, were emotional and behavioural problems (Youth Self-Report), cognitive development (Wechsler Intelligence Scale for Children) and secondary education entry level. Financial and social stress at age 9 years were the putative mediators. RESULTS: Differential exposure to financial stress caused a 0.07 (95% CI -0.12 to -0.01) SD worse emotional and behavioural problem -score, a 0.05 (95% CI -0.08 to -0.02) SD lower intelligence score and a 0.05 (95% CI -0.05 to -0.01) SD lower secondary educational level, respectively, among children of less-educated mothers compared with children of more-educated mothers. This corresponds to a relative contribution of 54%, 9% and 6% of the total effect of mother's education on these outcomes, respectively. Estimates for differential exposure to social stress, and differential susceptibility to financial or social stress, were much less pronounced. CONCLUSION: Among children of less-educated mothers, higher exposure to financial stress in the family substantially contributes to inequalities in socioemotional development, but less so for cognitive development and educational attainment.

Trajectories of socioeconomic inequality in early child development: a cohort analysis.

BACKGROUND: Addressing socioeconomic inequalities in early child development (ECD) is key to reducing the intergenerational transmission of health inequalities. Yet, little is known about how socioeconomic inequalities in ECD develop over the course of childhood. Our study aimed to describe how inequalities in ECD by maternal education develop from infancy to middle childhood. METHODS: We used data from Generation R, a prospective population-based cohort study in The Netherlands. Language skills were measured at ages 1, 1.5, 2, 3, and 4 years, using the Minnesota Child Development Inventory. Socioemotional (i.e. internalizing and externalizing) problems were measured at ages 1.5, 3, 5 and 9 years using the Child Behavior Checklist. We estimated inequalities in language skills and socioemotional problems across the above-mentioned ages, using linear mixed models with standardized scores at each wave. We used maternal education as indicator of socioeconomic position. RESULTS: Children of less educated mothers had more reported internalizing (B = 0.72, 95%CI = 0.51;0.95) and externalizing (B = 0.25, 95%CI = 0.10;0.40) problems at age 1.5 years, but better (caregiver reported) language skills at 1 year (B = 0.50, 95%CI = 0.36;0.64) than children of high educated mothers. Inequalities in internalizing and externalizing problems decreased over time. Inequalities in language scores reversed at age 2, and by the time children were 4 years old, children of less educated mothers had substantially lower language skills than children of high educated mothers (B = -0.38, 95%CI = -0.61;-0.15). CONCLUSIONS: Trajectories of socioeconomic inequality in ECD differ by developmental domain: whereas inequalities in socioemotional development decreased over time, inequalities increased for language development. Children of less educated mothers are at a language disadvantage even before entering primary education, providing further evidence that early interventions are needed.

Role of neighbourhood social characteristics in children's use of mental health services between ages 9 and 13 years: a population-based cohort study in the Netherlands.

OBJECTIVES: This study aims to investigate the association of neighbourhood socioeconomic status (SES) and social cohesion (SC) within the neighbourhood with mental health service use in children, independent of individual-level characteristics and mental health problems. DESIGN, SETTING AND PARTICIPANTS: A longitudinal analysis was done using data from the Generation R Study, a prospective, population-based cohort of children born in Rotterdam, the Netherlands. These data were linked to the Neighbourhood Profile, containing registry and survey data on residents of Rotterdam. Data of 3403 children (mean age: 13.6 years, SD: 0.4) were used to study the associations between neighbourhood SES, SC (SC belonging and SC relations) and mental health service use, adjusted for mental health problems and sociodemographic characteristics. OUTCOME MEASURES: Mental health service use was reported by the accompanying parent at the research centre using the question: 'Did your child visit a psychologist or psychiatrist between 9 and 13 years old?'. RESULTS: Mental health services were used by 524 (15.4%) children between ages 9 and 13 years. No significant differences in mental health service use between neighbourhoods were identified (median OR: 1.07 (p=0.50)). The neighbourhood social characteristics were associated with mental health service use, but only when adjusted for each other. Children living in neighbourhoods with a low SES (OR 0.57 (95% CI 0.32 to 1.00)) or high SC belonging (OR 0.79 (95% CI 0.64 to 0.96)) were less likely to use services compared with children in a high SES or low SC belonging neighbourhood. SC relations was not associated with mental health service use. CONCLUSIONS: Our findings indicate that children living in high SES neighbourhoods or in neighbourhoods where people feel less sense of belonging are more likely to use mental health services. As these associations were only present when studied jointly, more research is warranted on the complex associations of neighbourhood factors with children's mental health service use.

Health-care costs of underweight, overweight and obesity: Australian population-based study.

AIM: Child health varies with body mass index (BMI), but it is unknown by what age or how much this attracts additional population health-care costs. We aimed to determine the (1) cross-sectional relationships between BMI and costs across the first decade of life and (2) in longitudinal analyses, whether costs increase with duration of underweight or obesity. PARTICIPANTS: Baby (n = 4230) and Kindergarten (n = 4543) cohorts in the nationally representative Longitudinal Study of Australian Children. OUTCOME: Medicare Benefits Scheme (including all general practitioner plus a large proportion of paediatrician visits) plus prescription medication costs to federal government from birth to sixth (Baby cohort) and fourth to tenth (Kindergarten cohort) birthdays. PREDICTOR: biennial BMI measurements over the same period. RESULTS: Among Australian children under 10 years of age, 5-6% were underweight, 11-18% overweight and 5-6% obese. Excess costs with low and high BMI became evident from age 4-5 years, with normal weight accruing the least, obesity the most, and underweight and overweight intermediate costs. Relative to overall between-child variation, these excess costs per child were very modest, with a maximum of $94 per year at age 4-5 years. Nonetheless, this projects to a substantial cost to government of approximately $13 million per annum for all Australian children aged less than 10 years. CONCLUSIONS: Substantial excess population costs provide further economic justification for promoting healthy body weight. However, obese children's low individual excess health-care costs mean that effective treatments are likely to increase short-term costs to the public health purse during childhood.

Trajectories and outcomes among children with special health care needs.

BACKGROUND AND OBJECTIVE: Outcomes for children with special health care needs (SHCN) can vary by their patterns and persistence over time. We aimed to empirically establish typical SHCN trajectories throughout childhood and their predictive relationships with child and parent outcomes. METHODS: The 2 cohorts of the nationally representative Longitudinal Study of Australian Children were recruited in 2004 at ages 0 to 1 (n = 5107, B cohort) and 4 to 5 years (n = 4983, K cohort). The parent-reported Children With SHCN Screener (Short Form) was completed at each of 4 biennial waves. Wave 4 outcomes were parent-reported behavior and health-related quality of life, teacher-reported learning, and directly assessed cognition. Both parents self-reported mental distress. We derived intracohort trajectories by using latent class analysis in Mplus. We compared mean outcome scores across trajectories by using linear regression, adjusting for socioeconomic position. RESULTS: Four distinct SHCN trajectories were replicated in both cohorts: persistent (B 6.8%, K 8.7%), emerging (B 4.1%, K 11.5%), transient (B 7.9%, K 4.2%), and none (B 81.3%, K 75.6%). Every outcome was adversely affected except fathers' mental health. From infancy to age 6 to 7 years, the persistent and emerging groups had similarly poor outcomes. From age 4 and 5 to 10 and 11 years, outcomes were incrementally poorer on moving from none to transient to emerging and to persistent SHCN. Effect sizes were largest for behavior, learning, and psychosocial outcomes. CONCLUSIONS: Adverse outcomes are shaped more by cumulative burden than point prevalence of SHCNs. In addition to providing care according to a child's need at any given time, prioritizing care toward persistent SHCNs may have the biggest benefits for children and parents.

Television viewing through ages 2-5 years and bullying involvement in early elementary school.

BACKGROUND: High television exposure time at young age has been described as a potential risk factor for developing behavioral problems. However, less is known about the effects of preschool television on subsequent bullying involvement. We examined the association between television viewing time through ages 2-5 and bullying involvement in the first grades of elementary school. We hypothesized that high television exposure increases the risk of bullying involvement. METHOD: TV viewing time was assessed repeatedly in early childhood using parental report. To combine these repeated assessments we used latent class analysis. Four exposure classes were identified and labeled "low", "mid-low", "mid-high" and "high". Bullying involvement was assessed by teacher questionnaire (n=3423, mean age 6.8 years). Additionally, peer/self-report of bullying involvement was obtained using a peer nomination procedure (n=1176, mean age 7.6 years). We examined child risk of being a bully, victim or a bully-victim (compared to being uninvolved in bullying). RESULTS: High television exposure class was associated with elevated risks of bullying and victimization. Also, in both teacher- and child-reported data, children in the high television exposure class were more likely to be a bully-victim (OR=2.11, 95% CI: 1.42-3.13 and OR=3.68, 95% CI: 1.75-7.74 respectively). However, all univariate effect estimates attenuated and were no longer statistically significant once adjusted for maternal and child covariates. CONCLUSIONS: The association between television viewing time through ages 2-5 and bullying involvement in early elementary school is confounded by maternal and child socio-demographic characteristics.

Family and neighbourhood socioeconomic inequalities in childhood trajectories of BMI and overweight: longitudinal study of Australian children.

BACKGROUND: Socioeconomic inequalities in longitudinal patterning of childhood overweight could cause marked differentials in total burden by adulthood. This study aims to determine timing and strength of the association between socioeconomic status (SES) and children's body mass index (BMI) in the pre- and primary school years, and to examine socioeconomic differences in overweight trajectories across childhood. METHODS: Participants were 4949 children from the Longitudinal Study of Australian Children. BMI was measured at four biennial waves starting at age 4-5 years in 2004. Developmental trajectories of childhood overweight were identified with latent class analyses. Composite variables of family and neighbourhood SES were used. RESULTS: Socioeconomic differences in mean BMI z-scores already present at age 4-5 more than doubled by age 10-11 years, reflecting decreasing mean BMI among advantaged rather than increasing means among disadvantaged children. Latent class analysis identified children with 'stable normal weight' (68%), and with 'persistent' (15%), 'late-onset' (14%), and 'resolving' overweight (3%). Risks of persistent and late-onset childhood overweight were highest among low SES families (e.g. most disadvantaged quintile: OR(persistent) = 2.51, 95%CI: 1.83-3.43), and only partly explained by birth weight and parental overweight. Relationships with neighbourhood SES were weaker and attenuated fully on adjustment for family SES. No socioeconomic gradient was observed for resolving overweight. CONCLUSIONS: Childhood has become the critical period when socioeconomic inequalities in overweight emerge and strengthen. Although targeting disadvantaged children with early overweight must be a top priority, the presence of childhood overweight even among less-disadvantaged families suggests only whole-society approaches will eliminate overweight-associated morbidity.

Maternal educational level and preschool children's consumption of high-calorie snacks and sugar-containing beverages: mediation by the family food environment.

OBJECTIVE: To examine the associations between maternal educational level and preschoolers' consumption of high-calorie snacks and sugar-containing beverages, and to assess the mediating effects of variables relating to the family food environment. METHODS: We analyzed data from 2814 native Dutch preschoolers enrolled in a birth cohort study in Rotterdam (the Netherlands), between 2002 and 2006. Logistic regression models were used to calculate odds ratios of snacking ≥ 2 times/day and consuming sugar-containing beverages ≥ 3 glasses/day for children of mothers with low, mid-low, and mid-high educational levels (reference group: high educational level), before and after adjustment for mediators. RESULTS: Children of low and mid-low educated mothers were significantly more likely to consume excessive amounts of high-calorie snacks and sugar-containing beverages compared with children of high educated mothers, with the highest odds in children of low educated mothers (OR: 2.44; 95% CI: 1.84, 3.23 and OR: 2.46; 95% CI: 1.87, 3.24 respectively). Parental feeding practices, parental consumption of sugar-containing beverages, and children's television time partly explained these associations. CONCLUSION: Maternal educational level is inversely related to preschoolers' consumption of high-calorie snacks and sugar-containing beverages. Targeting the family food environment may be an effective way of reducing educational inequalities in children's unhealthy dietary behaviors.

Prevalence of bullying and victimization among children in early elementary school: do family and school neighbourhood socioeconomic status matter?

BACKGROUND: Bullying and victimization are widespread phenomena in childhood and can have a serious impact on well-being. Children from families with a low socioeconomic background have an increased risk of this behaviour, but it is unknown whether socioeconomic status (SES) of school neighbourhoods is also related to bullying behaviour. Furthermore, as previous bullying research mainly focused on older children and adolescents, it remains unclear to what extent bullying and victimization affects the lives of younger children. The aim of this study is to examine the prevalence and socioeconomic disparities in bullying behaviour among young elementary school children. METHODS: The study was part of a population-based survey in the Netherlands. Teacher reports of bullying behaviour and indicators of SES of families and schools were available for 6379 children aged 5-6 years. RESULTS: One-third of the children were involved in bullying, most of them as bullies (17%) or bully-victims (13%), and less as pure victims (4%). All indicators of low family SES and poor school neighbourhood SES were associated with an increased risk of being a bully or bully-victim. Parental educational level was the only indicator of SES related with victimization. The influence of school neighbourhood SES on bullying attenuated to statistical non-significance once adjusted for family SES. CONCLUSIONS: Bullying and victimization are already common problems in early elementary school. Children from socioeconomically disadvantaged families, rather than children visiting schools in disadvantaged neighbourhoods, have a particularly high risk of involvement in bullying. These findings suggest the need of timely bullying preventions and interventions that should have a special focus on children of families with a low socioeconomic background. Future studies are necessary to evaluate the effectiveness of such programs.

Children of low socioeconomic status show accelerated linear growth in early childhood; results from the Generation R Study.

OBJECTIVES: People of low socioeconomic status are shorter than those of high socioeconomic status. The first two years of life being critical for height development, we hypothesized that a low socioeconomic status is associated with a slower linear growth in early childhood. We studied maternal educational level (high, mid-high, mid-low, and low) as a measure of socioeconomic status and its association with repeatedly measured height in children aged 0-2 years, and also examined to what extent known determinants of postnatal growth contribute to this association. METHODS: This study was based on data from 2972 mothers with a Dutch ethnicity, and their children participating in The Generation R Study, a population-based cohort study in Rotterdam, The Netherlands (participation rate 61%). All children were born between April 2002 and January 2006. Height was measured at 2 months (mid-90% range 1.0-3.9), 6 months (mid-90% range 5.6-11.4), 14 months (mid-90% range 13.7-17.9) and 25 months of age (mid-90% range 23.6-29.6). RESULTS: At 2 months, children in the lowest educational subgroup were shorter than those in the highest (difference: -0.87 cm; 95% CI: -1.16, -0.58). Between 1 and 18 months, they grew faster than their counterparts. By 14 months, children in the lowest educational subgroup were taller than those in the highest (difference at 14 months: 0.40 cm; 95% CI: 0.08,0.72). Adjustment for other determinants of postnatal growth did not explain the taller height. On the contrary, the differences became even larger (difference at 14 months: 0.61 cm; 95% CI: 0.26,0.95; and at 25 months: 1.00 cm; 95% CI: 0.57,1.43) CONCLUSIONS: Compared with children of high socioeconomic status, those of low socioeconomic status show an accelerated linear growth until the 18th month of life, leading to an overcompensation of their initial height deficit. The long-term consequences of these findings remain unclear and require further study.

Mother's educational level and fetal growth: the genesis of health inequalities.

BACKGROUND: Women of low socio-economic status (SES) give birth to lighter babies. It is unknown from which moment during pregnancy socio-economic differences in fetal weight can be observed, whether low SES equally affects different fetal-growth components, or what the effect of low SES is after taking into account mediating factors. METHODS: In 3545 pregnant women participating in the Generation R Study, we studied the association of maternal educational level (high, mid-high, mid-low and low) as a measure of SES with fetal weight, head circumference, abdominal circumference and femur length. We did this before and after adjusting for potential mediators, including maternal height, pre-pregnancy body mass index and smoking. RESULTS: In fetuses of low-educated women relative to those of high-educated women, fetal growth was slower, leading to a lower fetal weight that was observable from late pregnancy onwards. In these fetuses, growth of the head [-0.16 mm/week; 95% confidence interval (CI): -0.25 to -0.07; P = 0.0004], abdomen (-0.10 mm/week; 95% CI: -0.21 to 0.01; P = 0.08) and femur (-0.03 mm/week; 95% CI: -0.05 to -0.006; P = 0.01) were all slower; from mid-pregnancy onwards, head circumference was smaller, and from late pregnancy onwards, femur length was also smaller. The negative effect of low education was greatest for head circumference (difference in standard deviation score in late pregnancy: -0.26; 95% CI: -0.36 to -0.15; P < 0.0001). This effect persevered even after adjustment for the potential mediators (adjusted difference: -0.14; 95% CI: -0.25 to -0.03; P = 0.01). CONCLUSIONS: Low maternal education is associated with a slower fetal growth and this effect appears stronger for growth of the head than for other body parts.

Explaining educational inequalities in birthweight: the Generation R Study.

Although low socio-economic status has consistently been associated with lower birthweight, little is known about the factors whereby socio-economic disadvantage influences birthweight. We therefore examined explanatory mechanisms that may underlie the association between the educational level of pregnant women, as an indicator of socio-economic status, and birthweight. The study was embedded within a population-based cohort study in the Netherlands. Information on maternal education, offspring's birthweight and several determinants of birthweight was available for 3546 pregnant women of Dutch origin. Infants of the lowest educated women had a statistically significantly lower birthweight than infants of the highest educated women [difference adjusted for gender and gestational age: -123 g (95% CI -167, -79)]. Parity, age of the pregnant women, hypertension, parental height and parental birthweight, marital status, pregnancy planning, financial concerns, number of people in household, weight gain and smoking habits individually explained part of the differences in birthweight, while adjustment for working hours and body mass index resulted in increases in birthweight differences between the educational levels. After full adjustment, the difference in birthweight between lowest and highest education was reduced by 66%. Our study confirmed remarkable educational inequalities in birthweight, a large part of which was explained by pregnancy characteristics, anthropometrics, the psychosocial and material situation, and lifestyle-related factors. Altering smoking habits may be an option to reduce educational differences in birthweight, as many lower-educated women tend to continue smoking during pregnancy. In order to tackle inequalities in birthweight, it is important that interventions are accessible for pregnant women in lower socio-economic strata.

Socioeconomic inequalities in infant temperament: the generation R study.

BACKGROUND: A low socioeconomic status (SES) has consistently been associated with behavioural problems during childhood. The studies of SES and behaviour in infants used temperament as a behavioural measure. However, these studies in younger children yielded inconsistent findings. Furthermore, they generally did not examine explanatory mechanisms underlying the association between SES and temperament. We investigated the association between SES and temperament in infancy. METHODS: The study was embedded in the Generation R study, a population-based cohort in The Netherlands. Maternal and paternal education, family income, and maternal occupational status were used as indicators of SES. At the age of 6 months, 4,055 mothers filled out six scales of the Infant Behaviour Questionnaire-Revised. RESULTS: Lower SES was associated with more difficult infant temperament as measured by five of the six temperament dimensions (e.g. Fear: unadjusted z-score difference between lowest and highest education: 0.57 (95%CI: 0.43, 0.71)). Only the direction of the association between SES and Sadness was reversed. The effect of SES on Distress to Limitations, Recovery from Distress, and Duration of Orienting scores was largely explained by family stress and maternal psychological well-being. These covariates could not explain the higher levels of Activity and Fear nor the lower Sadness scores of infants from low SES groups. CONCLUSIONS: SES inequalities in temperament were already present in six months old infants and could partially be explained by family stress and maternal psychological well-being. The results imply that socioeconomic inequalities in mental health in adults may have their origin early in life.