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Average height (cm) trajectories of boys and girls predicted by the multilevel models according to maternal education categories (0–4, 5–8 and 9+ years of formal education).
Source publication
Matijasevich A, Howe LD, Tilling K, Santos IS, Barros AJD, Lawlor DA. Maternal education inequalities in height growth rates in early childhood: 2004 Pelotas birth cohort study. Paediatric and Perinatal Epidemiology 2012; 26 : 236–249.
Socio‐economic inequalities in attained height have been reported in many countries. The aim of this study was to...
Contexts in source publication
Context 1
... between observed and predicted measure- ments were very small in each period indicating good model fit (Table 2) and individual-level residuals were approximately normally distributed (Figures S1,S2). ...
Context 2
... predicted heights displayed in Table S4 were derived from the results of the multilevel linear spline model and were used to build Figure 1. That figure shows the average predicted growth trajectories for boys and girls according to each category of maternal education. ...
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Citations
... Studies have reported an association of father's socioeconomic status with growth of children (Bann et al. 2018;Lasker and Mascie-Taylor 1989;Rona et al. 1978;Whincup et al. 1988). More recently, researchers reported associations between growth and the level of a mother's education and occupation (Matijasevich et al. 2012). In India there are a number of programs and policies to encourage women's participation in education, jobs, and decision making from the household level to the greater societal level. ...
Aim: To assess the association of father’s education and occupation with children growth measured by height-for-age z-scores and BMI-for-age z-scores in a patriarchal culture where father’s social position is considered more important than mother’s social position. Sample and methods: The present cross-sectional study consists of 387 school-going girls aged 9-14 years residing in Matigara, Siliguri sub-division of Darjeeling district, West Bengal, India. Information on age, mother’s education, father’s education, ethnic affiliation, mother’s occupation, father’s occupation, house type, household monthly income and family size were recorded. Associations between variables were assessed using Spearman correlation, St. Nicolas house analysis (SNHA), and one-way analysis of variance (ANOVA) with box plots. Results: The hypothesis that in a patriarchy paternal socio-economic status (SES) influences children growth more than maternal SES was not supported. The observed correlation between mother education and measure of growth (BAZ and HAZ) was, 0.15 and 0.13, respectively. SNHA showed direct connection between HAZ of girls and mother education. Further, using ANOVA significant difference in the HAZ of adolescents was observed between least educated mothers and moderately educated mothers (F = 6.593; p < 0.01). No such difference between the maternal education levels was observed for BAZ. Conclusion: Maternal education is an important factor influencing children linear growth even in a patriarchy. The association was independent of nutrition. Common explanations are functional literacy, decision making, access to information and health infrastructure, and less domestic violence. Mother’s education may influence perceived future prospects of the daughters, and could be an important stimulus for growth.
... Regarding the influencing factors of HC trajectories, our results contribute to the evidence that higher maternal education and better birth outcomes were associated with a lower risk of being in the lower HC growth trajectory. Although the underlying pathways behind these associations remain unclear, together with other similar results [26][27][28], this evidence suggests that the socioeconomic inequalities in HC growth emerge early and continue to persist. Thus, further support for lower socioeconomic subpopulations from public health programs is needed. ...
The associations of early-life head circumference (HC) with child neurodevelopmental and mental health among generally healthy population remain unclear. We aimed to examine the associations of early-life HC trajectories with cognitive development and emotional and behavioral problems in adolescence and to identify the HC growth–sensitive period. We conducted a prospective, community-based birth cohort study in rural western China, and 745 adolescents aged 10–14 years were followed between June and December 2016. We assessed their HC eight times during the first 2 years of life and their adolescent cognitive, emotional, and behavioral outcomes using the Wechsler Intelligence Scale for Children-IV and Youth Self-Report-2001, respectively. We applied group-based trajectory modeling to identify the HC trajectories and conditional growth to derive the HC growth–sensitive periods. We identified five distinct HC trajectories characterized as Start below average-then decrease (7.8% of the sample), Start below average-then increase (6.8%), Start average-then decrease (33%), Consistently average (38%), and Consistently above average (14%). Infants in the trajectory of consistently above average had higher cognitive scores in adolescence compared to those from suboptimal trajectories, with adjusted mean differences ranging from 2.84 to 8.99 points. The conditional gains showed that the HC growth–sensitive period was between 0 and 18 months for child cognition. We found null associations between HC measures and adolescent emotional and behavioral problem scores.
Conclusion: Early-life HC trajectories were associated with adolescent cognitive development. HC may serve as an inexpensive screening tool to monitor child development at risk during the first 18 months, particularly in resource-limited settings. What is Known:
• Postnatal head circumference (HC) has been shown to be associated with cognitive development in infants who were born premature and/or fetal growth restriction, while inconsistent associations were reported among generally healthy populations, especially in low- and middle- income countries, challenging its utility in public health practices.
What is New:
• Adolescents in the HC growth trajectory of consistently above average had higher cognitive scores compared to those with other suboptimal trajectories, while null findings were observed for adolescent emotional and behavioral health.
• HC may serve as an inexpensive screening tool to monitor child development at risk during the first 18 months of life, particularly in resource-limited settings.
... Because of potential influence of socioeconomic conditions on the variation in parental investment (Matijasevich et al., 2012;Sparks, 2011;Vázquez-Vázquez et al., 2013), we accounted for the random effects of socioeconomic status and parental education. However, in most models, the estimated variance in education of both parents was essentially zero, and thus, only the random effect of the socioeconomic status was included. ...
Namesaking (naming a child after a parent or other relative) can be viewed as a mechanism to increase perceived parent-child similarity and, consequently, parental investment. Male and, to a lesser extent, firstborn children are more frequently namesakes than female and later-born children, respectively. However, a direct link between namesaking and parental investment has not been examined. In the present study, 632 participants (98 men and 534 women) from Central Europe indicated their first name, sex, birth order, number of siblings, sexual orientation, socioeconomic status, paternal and maternal first names, as well as relationship quality with, and time and financial investment they received from, both parents during childhood. Mixed-effects models revealed associations between namesaking and parental investment. However, the effect of namesaking often appeared significant only in interaction with specific predictors, such as sex and primogeniture. It suggests instead that namesaking has an additive effect-it enhances the effect of biological factors on parental investment. In general, we found evidence for the bias in parental investment linked to name similarity among both parents, and support for the hypothesis that namesaking serves as a mechanism to increase paternity confidence and, thus, paternal investment. The effect of namesaking influences only certain types of parental investment-namely, those at the level of relationship quality. In addition, nonheterosexual orientation was the strongest negative predictor of paternal investment. Our study extends the research on parental investment by showing that cultural mechanisms, such as namesaking, can also exert some influence on parental rearing behavior.
... Because of potential influence of socioeconomic conditions on the variation in parental investment (Matijasevich et al., 2012;Sparks, 2011;Vázquez-Vázquez et al., 2013), we accounted for the random effects of socioeconomic status and parental education. However, in most models, the estimated variance in education of both parents was essentially zero, and thus, only the random effect of the socioeconomic status was included. ...
Namesaking (naming a child after a parent or other relative) can be viewed as a mechanism to increase perceived parent-child similarity and, consequently, parental investment. Male and, to a lesser extent, firstborn children are more frequently namesakes than female and later-born children, respectively. However, a direct link between namesaking and parental investment has not been examined. In the present study, 632 participants (98 men and 534 women) from Central Europe indicated their first name, sex, birth order, number of siblings, sexual orientation, socioeconomic status, paternal and maternal first names, as well as relationship quality with, and time and financial investment they received from, both parents during childhood. Mixed-effects models revealed associations between namesaking and parental investment. However, the effect of namesaking often appeared significant only in interaction with specific predictors, such as sex and primogeniture. It suggests instead that namesaking has an additive effect-it enhances the effect of biological factors on parental investment. In general, we found evidence for the bias in parental investment linked to name similarity among both parents, and support for the hypothesis that namesaking serves as a mechanism to increase paternity confidence and, thus, paternal investment. The effect of namesaking influences only certain types of parental investment-namely, those at the level of relationship quality. In addition, nonheterosexual orientation was the strongest negative predictor of paternal investment. Our study extends the research on parental investment by showing that cultural mechanisms, such as namesaking, can also exert some influence on parental rearing behavior.
... Median GA (Q1, Q3) was 40 weeks (39,40). Median maternal age (Q1, Q3) was 26 years (22,31), and mothers had a median (IQR) of 10 (8)(9)(10)(11)(12) years of education at the time of their infant's birth (table 1). For the six monthly anthropometric measurements prior to 6 months, each infant had at least two observations, and 72% had measures at all six time points. ...
Objectives
Infant anthropometric growth varies across socioeconomic factors, including maternal education and income, and may serve as an indicator of environmental influences in early life with long-term health consequences. Previous research has identified sociodemographic gradients in growth with a focus on the first year and beyond, but estimates are sparse for growth before 6 months. Thus, our objective was to examine the relationship between sociodemographic factors and infant growth patterns between birth and 5 months of age.
Design
Prospective cohort study.
Settings
Low-income to middle-income neighbourhoods in Santiago, Chile (1991–1996).
Participants
1412 participants from a randomised iron-deficiency anaemia preventive trial in healthy infants.
Main outcome measures
Longitudinal anthropometrics including monthly weight (kg), length (cm) and weight-for-length (WFL) values. For each measure, we estimated three individual-level growth parameters (size, timing and velocity) from SuperImposition by Translation and Rotation models. Size and timing changes represent vertical and horizontal growth curve shifts, respectively, and velocity change represents growth rate shifts. We estimated the linear association between growth parameters and gestational age, maternal age, education and socioeconomic position (SEP).
Results
Lower SEP was associated with a slower linear (length) velocity growth parameter (−0.22, 95% CI –0.31 to –0.13)—outcome units are per cent change in velocity from the average growth curve. Lower SEP was associated with later WFL growth timing as demonstrated through the tempo growth parameter for females (0.25, 95% CI 0.05 to 0.42)—outcome units are shifts in days from the average growth curve. We found no evidence of associations between SEP and the weight size, timing or velocity growth rate parameters.
Conclusion
Previous research on growth in older infants and children shows associations between lower SEP with slower length velocity. We found evidence supporting this association in the first 5 months of life, which may inform age-specific prevention efforts aimed at infant length growth.
... The offspring of better educated parents were generally taller, particularly in mid-childhood and from adolescence onwards, than those whose parents had lower education. Our findings for average height are in agreement with several population based studies showing a positive association between parents' education and offspring height 15,17,26,27 . In a Chinese study, childhood height was also related to grandparents' education, suggesting that socioeconomic conditions of current and previous generations may affect height 28 . ...
Genetic factors explain a major proportion of human height variation, but differences in mean stature have also been found between socio-economic categories suggesting a possible effect of environment. By utilizing a classical twin design which allows decomposing the variation of height into genetic and environmental components, we tested the hypothesis that environmental variation in height is greater in offspring of lower educated parents. Twin data from 29 cohorts including 65,978 complete twin pairs with information on height at ages 1 to 69 years and on parental education were pooled allowing the analyses at different ages and in three geographic-cultural regions (Europe, North America and Australia, and East Asia). Parental education mostly showed a positive association with offspring height, with significant associations in mid-childhood and from adolescence onwards. In variance decomposition modeling, the genetic and environmental variance components of height did not show a consistent relation to parental education. A random-effects meta-regression analysis of the aggregate-level data showed a trend towards greater shared environmental variation of height in low parental education families. In conclusion, in our very large dataset from twin cohorts around the globe, these results provide only weak evidence for the study hypothesis.
... The average height of Chinese children has increased in the past two decades [4], possibly related to the improvement of individual factors, such as protein intake [5], family income [6,7] and maternal education level [8,9]. These improvements of individual factors resulted from China's economic and social development through increased food supply, better housing conditions, and improved health care services [10]. ...
... We observed a significant association between child height and the 'education' segment of the urbanization component. Some studies have documented a positive impact of parental education on child height [8,9]. However, less is known about the effect of community mean education relating to child height. ...
... Regarding influence factors at the individual level, gender [25], family income [6,7], protein intake [5] maternal education [8,9], and maternal height [26] were previously demonstrated to be associated with child height. These findings were consistent with our findings. ...
Background
Recent economic development in China has been accompanied by well-documented health inequalities between regions. The impact of individual factors on child height has been widely studied, but the influence of community-level factors has not yet been fully studied.
Methods
The cross-sectional data of 1606 Chinese children aged 5–18 years from the China Health and Nutrition Survey 2011 were used. Multilevel analysis was used to examine the association of community factors (using urbanization index) with child height. Child height was measured following standardized procedures, and height-for-age Z scores were calculated as outcome variables. Datasets were presented at two levels: community variable (Level-2) was an urbanization index which is a composite score summarizing 12 community-level contextual factors. Individual variables (Level-1) were child gender, ethnicity, percentage of energy intake from protein, maternal height, maternal education level, and family income.
Results
Urbanization index was associated with child height. Among the 12 community-level factors, ‘education’ were positively associated with child height. Additionally, stratified analyses by age showed that ‘population density’ and ‘housing’ were positively significantly associated with the height of elder children (13–18 years). At the individual level, male sex, higher maternal height, higher maternal education levels, higher family income, and higher percentage of energy intake from protein, were significantly positively associated with child height.
Conclusions
Our findings point to the role of contextual factors that generate differences between regions in shaping the distribution of child physical health outcomes. Our study suggests that public health programs and policies for child’s physical development may need to combine individual-centered strategies and also approaches aimed at changing residential environments.
... It takes time to overcome that initial disadvantage. Moreover, the chronic exposure during early childhood to risk factors that negatively affect height development remains higher for children born to low-income households than for those born in wealthier ones, which further reinforces socioeconomic inequalities in height-for-age [26][27][28][29][30][31][32]. Several studies confirm that in Belgium as well, children born in poor households on average have poorer health and lag in development compared to children from wealthier households [33][34][35][36][37][38]. ...
Introduction:
Poverty is a well-known risk factor for a child's health and development. This paper aimed to establish whether poverty negatively affected both intra-uterine growth and early childhood growth, i.e., whether children facing poverty were at a double disadvantage.
Methods:
For this study, we made use of routinely collected data on child development throughout early childhood from the 2006-2009 birth cohorts in Kind & Gezin's Ikaros database collected during 2,605,975 consultations with 273,935 children from birth to 730 days old. Indicators for child development at birth were gestational age and height-at-birth. A standardized height-for-age indicator captured height development throughout early childhood. A multidimensional indicator measured the risk of poverty. For the analysis of development at birth, we used linear and logistic regression; for the analysis of height development during early childhood, we estimated linear and logistic growth curve models.
Results:
The risk of poverty negatively affected both gestational age and height-at-birth. Throughout early childhood, we observed a negative relation between the risk of poverty and height-for-age indicators. However, the effect varied throughout childhood. Children at risk of poverty (over)compensated for their smaller stature at birth, and between ages 6 and 18 months, approximately, the negative effects of risk of poverty decreased substantially or disappeared. However, towards the end of the period studied, children born in households at risk of poverty started to lag again in height development.
Conclusion:
This study found that the risk of poverty indeed negatively affected a child's growth, both in utero and in early childhood. However, the results suggest that developmental lags later in childhood were not merely an extension of such lags at birth.
... Although the emergence of socioeconomic inequalities in BMI across childhood has so far mainly been addressed with a focus on weight, our findings shed light on the potential importance of height in the early development of such disparities. Socioeconomic patterning of height in childhood was also observed by Howe [42]. This trend has not, however, been observed in all studies [43,44]. ...
Background/objectives:
Studies in high-income countries show that despite the positive association of weight with socioeconomic position at birth, an inverse socioeconomic gradient in overweight (OW) appears later in childhood. The objectives were to understand the natural history of socioeconomic inequalities in weight, height and body mass index (BMI), by investigating their associations with maternal educational level between birth and 5 years, separately in boys and girls.
Subjects/methods:
A published work of growth modelling between birth and 5 years allowed us to calculate predicted weight, height and BMI at 1 month, 6 months, 1, 3 and 5 years for 1735 children from the French EDEN mother-child cohort. Associations between maternal education and predicted measures of body size were analysed with marginal linear and logistic models, stratified by sex.
Results:
In girls, despite a positive association between maternal education and birthweight, an inverse socioeconomic gradient was observed as early as 1 month for BMI. Girls whose mothers had low education levels were shorter on the whole than their counterparts with better-educated mothers, despite their similar weights. In boys, no socioeconomic gradient in BMI was observed at any age, including birth, but positive associations were found as early as 1 month for both weight and height.
Conclusions:
The emergence of an inverse socioeconomic gradient in BMI and OW apparently results from a complex pattern of socioeconomic inequalities in weight and height from 1 month onwards. The very start of life thus appears to be an important window of opportunity for addressing socioeconomic inequalities in growth.
... We parameterised the relationship between BMI z-score and age using linear splines and 3 knot points at 3, 12 and 34 months to describe periods of approximately linear growth based on the data [17]. Although a linear spline model is an approximation of the true growth function, its coefficients are easily interpretable and have been shown to produce good model fit in this and several other cohorts [30][31][32][33][34][35]. The multilevel model included three levels: (i) the age at measurement; (ii) the individual child; and (iii) the hospital or polyclinic site where the child was examined. ...
Objective:
To examine associations of parental socioeconomic position with early-life offspring body mass index (BMI) trajectories in a middle-income country.
Subjects:
Overall, 12,385 Belarusian children born 1996-97 and enrolled in a randomised breastfeeding promotion trial at birth, with 3-14 measurements of BMI from birth to 7 years.
Methods:
Cohort analysis in which exposures were parental education (common secondary or less; advanced secondary or partial university; completed university) and occupation (manual; non-manual) at birth, and the outcome was BMI z-score trajectories estimated using multilevel linear spline models, controlling for trial arm, location, parental BMI, maternal smoking status and number of older siblings.
Results:
Infants born to university-educated mothers were heavier at birth than those born to secondary school-educated mothers [by 0.13 BMI z-score units (95% confidence interval, CI: 0.07, 0.19) for girls and 0.11 (95% CI: 0.05, 0.17) for boys; equivalent for an infant of average birth length to 43 and 38 g, respectively]. Between the ages of 3-7 years children of the most educated mothers had larger BMI increases than children of the least educated mothers. At age 7 years, after controlling for trial arm and location, children of university-educated mothers had higher BMIs than those born to secondary school-educated mothers by 0.11 z-score (95% CI: 0.03, 0.19) among girls and 0.18 (95% CI: 0.1, 0.27) among boys, equivalent to differences in BMI for a child of average height of 0.19 and 0.26 kg/m2, respectively. After further controlling for parental BMI, these differences attenuated to 0.08 z-score (95% CI: 0, 0.16) and 0.16 z-score (95% CI: 0.07, 0.24), respectively, but changed very little after additional adjustment for number of older siblings and mother's smoking status. Associations were similar when based on paternal educational attainment and highest household occupation.
Conclusions:
In Belarus, consistent with some middle-income countries, higher socioeconomic position was associated with greater BMI trajectories from age 3 onwards.
