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Keywords:

  • familial;
  • obese;
  • overweight;
  • schoolchildren;
  • socio-economic;
  • Sydney Childhood Eye Study.

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Aim:  To examine associations between socio-economic, familial and perinatal factors with overweight/obesity in 6- and 12-year-old schoolchildren.

Methods:  Eligible year-1 (1765/2238, mean age 6.7 years) and year-7 students (2353/3144, mean age, 12.7 years) from a random cluster sample of 55 Sydney schools were examined during 2003–2005. Height, weight and body mass index were measured. Overweight or obesity was classified using International Obesity Task Force cut points. Information about each child's socio-demographic status, familial and perinatal information was sought in parental questionnaires.

Results:  After multivariate adjustment, lower parental education was significantly associated with prevalent overweight and obesity in 6-year-old children, odds ratio (OR) 1.52 (95% confidence interval (CI) 1.15–2.01) and OR 2.16 (CI 1.34–4.13), respectively. Smoking during pregnancy was associated with a higher likelihood of being obese among both 6- and 12-year-old children, OR 1.90 (CI 1.05–3.46) and OR 1.78 (CI 1.22–2.61). Population attributable risk estimates indicate that 14.9% and 10.1% of prevalent cases of obesity in 12-year-old children may be attributable to being: an only child or a heavy newborn, respectively.

Conclusions:  We show interdependent relationships between socio-economic, familial and perinatal factors and childhood weight status. Improved understanding of these pathways may help in developing childhood obesity prevention strategies.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

In Australia, at least one in five children and adolescents are overweight or obese, with rapid rises in prevalence apparently continuing.1 Similar trends are seen in other countries.2 Conversely, other studies have demonstrated that the prevalence of overweight and obesity have flattened, although levels of paediatric overweight in Australia still remained high.3 While it is important to clarify the determinants of paediatric adiposity in order to tackle this problem effectively, the influence of certain putative determinants remains inconclusive.4

Research to date identifies socio-economic status (SES) as a potentially important determining factor in obesity. In the Longitudinal Study of Australian Children,5 lower SES predicted a higher body mass index (BMI) among 4- to 5-year-old children. Although findings from the 2004 New South Wales (NSW) Schools Physical Activity and Nutrition Survey6 show an inverse association between overweight/obesity and SES, the association was not consistently statistically significant for all age groups. Hence, the association between SES and adiposity in children remains equivocal.4

The role of family provides another significant risk factor.7 The number of siblings has been suggested to be inversely related to prevalence of childhood obesity.4 In a recent Melbourne study of 2520 children, the association between family circumstance and weight status was assessed. Children without siblings and those with less educated mothers and fathers tended to have higher BMI z-scores and higher odds of overweight.4 Finally, based on the evidence on early life or perinatal risk factors, the relationships are complex, and more research is needed to understand their overall influence on development of overweight/obesity in children.8 Nevertheless, several epidemiological studies have demonstrated a positive relationship between birthweight and subsequent BMI in childhood.9,10 There is also strong evidence to support a link between maternal smoking during pregnancy and childhood adiposity.8,10–14

Very few Australian studies have analysed the association between multiple risk factors and the prevalence of overweight and obesity in children. This report describes the use of a large, population-based sample of schoolchildren to assess factors associated with the prevalence of overweight and obesity. The study factors assessed include: (i) SES; (ii) familial and (iii) perinatal or early life factors.

What is already known on this topic

  • 1
    Socio-economic, familial and perinatal/early-life influences have been identified as potential risk factors for childhood obesity.
  • 2
    The relationships between these risk factors and childhood adiposity are complex and more research is needed to understand their overall influence on development of overweight/obesity in children.
  • 3
    Low socio-economic status is a potential predictor of obesity.

What this paper adds

  • 1
    Our data confirm the following as overweight/obesity risk factors: coming from single-child families, being a heavy newborn, maternal smoking during pregnancy and lower parental education.
  • 2
    Findings verify that overweight and obesity requires health promotion intervention programmes that adopt a multifaceted approach in order to tackle the complexities of childhood adiposity.
  • 3
    Our study identifies key modifiable risk factors that could be prioritised as key strategies for reducing childhood obesity.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

The Sydney Childhood Eye Study is a population-based survey of eye conditions in schoolchildren living within the Sydney Metropolitan Area, Australia. It was approved by the Human Research Ethics Committee, University of Sydney, the Department of Education and Training, and Catholic Education Office, New South Wales, Australia.15 We obtained informed written consent from at least one parent of each child as well as verbal assent from every child before the examinations. Study methods have been previously described for year-1 students from a stratified random cluster sample of 34 primary schools across Sydney (mean age 6.7 years, hereafter referred to as the 6-year-old cohort).15 Similar methods were used for a large cohort of older children, including use of the same instruments. Briefly, all year-7 students (mean age 12.7 years, hereafter referred to as the 12-year-old cohort) in a stratified random cluster sample of 21 high schools across Sydney, were eligible to participate. Stratification was based on socio-economic status data from the Australian Bureau of Statistics. This included a proportional mix of public, private or religious high schools. Data for the 6-year-old cohort were collected during 2003 and 2004 and for the 12-year-old cohort during 2004 and 2005.

The child's weight and body fat percentage (utilising leg–leg bioimpedance analysis) were measured with a Body Composition Analyser (Model TBF-300, Tanita, Kowloon, Hong Kong). Height was measured with shoes off using a free-standing SECA height rod (Model 220, Seca, Hamburg, Germany). Waist circumference was measured and defined as the narrowest part of the child's trunk.15 Weight in kilograms was measured using a professional weighing machine (Wedderburn Scales, Ingleburn, Australia) that was regularly calibrated. BMI was calculated as weight divided by the height squared (kg/m2). Overweight and obesity categories were defined using the International Obesity Taskforce age- and sex-specific cut points.16

Parents were asked to complete a comprehensive 193-item questionnaire. Socio-demographic information covering ethnicity, country of birth, education, occupation and parental age were included. Parents were asked to indicate the total number of children in the household and also asked to provide full details (age, sex, etc.) of all brothers and sisters (both biological and non-biological). Parents were also asked whether they or other people living in their home smoked inside the house. This defined the child's exposure to current passive smoking. The questionnaire also included a question on maternal smoking: ‘During the pregnancy, did the mother ever smoke cigarettes, cigars, pipes or other tobacco products?’ Information about the child's birth, such as birthweight, birth length and head circumference, gestational age, and mode of delivery, as well as maternal obstetric history, was sought. We asked parents to extract this information from their child's health record booklet (‘Blue Book’), as reported elsewhere.17 The distribution of birthweight in our sample is very close to published Australian figures for this birth cohort.18 We defined low birthweight as ≤2499 g and premature birth as <37 weeks gestation, in keeping with World Health Organization's definitions.19

The ethnicity of the child was determined only if both parents shared that ethnic origin. Otherwise, children were placed in a mixed ethnicity category. Ethnicity was classified on the basis of self-identification by the parents, combined with information about the place of birth of the child. Ethnic categories were consistent with the Australian Standard Classification of Cultural and Ethnic groups:20 (i) East Asian covered children whose parents originated from China, Malaysia, Singapore, Indonesia, Philippines, Japan, Korea, Myanmar, Thailand, Laos, Cambodia and Vietnam; (ii) South Asian included Indian, Sri Lankan and Pakistani; (iii) Middle Eastern or (iv) others/mixed (includes all other ethnicities). We defined parental education as the highest level of education completed by either parent. This ranged from never having attended school to having completed a higher degree such as a Masters or PhD. Socio-economic status was based on homeownership by the child's parents as well as their employment status and education level.

SAS software (SAS Institute, Cary, NC, USA) version 9.1 was used for analysis including t-tests, χ2 tests and logistic regression. We used mixed models and generalised estimating equations to adjust for cluster sampling effects. Multivariable logistic regression analysis was used to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs). Logistic regression models were constructed to assess significant associations with overweight and obesity among 6- and 12-year-old children defined using the age–sex specific International Obesity Task Force (IOTF) cut points. Population attributable risks (PARs) for overweight and obesity were calculated for factors with significant contributions, using the following equation: PAR =p× (OR − 1)/{p× (OR − 1) + 1}, where p is the prevalence and OR is the odds ratio. P-values of <0.05 indicate statistical significance.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Of 2238 eligible children aged 6 years (attending year 1), 1765 children were given parental permission to participate and underwent examination (78.9% response). Of these, 1741 had complete anthropometric data (77.8%). Similarly, of the 3144 eligible 12-year-old children (year 7), 2367 were given parental permission to participate and 2354 underwent examinations (74.9% response). Of these, 2353 participants had complete anthropometric data (74.8%). The overall prevalence of overweight and obesity was 12.9% and 5.9%, respectively, in the 6-year-old children, and 20.4% and 8.2%, respectively, in the 12-year-old children. The prevalence of obesity among 6-year-old boys and girls was 5.2% and 7.2%, respectively (P= 0.09). Among 12-year-old children, the prevalence of obesity among boys and girls was 10.6% and 10.0%, respectively (P= 0.09).

Table 1 shows the study characteristics of the 6- and 12-year-old children sample. The mean BMI for 6- and 12-year-old children was 16.2 and 20.4 kg/m2, respectively. Body fat percentage was 16.1% and 20.8% in 6- and 12-year-old children, respectively. Mean waist circumference in the 6- and 12-year-old children sample was 55.1 and 67.1 cm, respectively (Table 1). In the 6- and 12-year-old groups, 49.1% and 40.6% of parents reported gaining a university education. Exposure to passive smoking was reported among 21.6% and 23.3% of the 6- and 12-year-old children sample. Additionally, around 11.3% and 9.5% of 6- and 12-year-old children were from only-child families (Table 1).

Table 1.  Characteristics of the 6- and 12-year-old schoolchildren included in the study
Characteristics6-year-old children (n= 1741)12-year-old children (n = 2353)
  1. Data are mean (standard deviation) or proportions unless otherwise stated. †Includes hypertension, diabetes, high fever, rubella and mumps.

Age, years6.7 (0.4)12.7 (0.4)
Sex, male881 (50.6)1190 (50.6)
Height, cm120.6 (5.7)156.1 (7.9)
Weight, kg23.7 (4.5)50.2 (12.9)
Body mass index, kg/m216.2 (2.1)20.4 (4.2)
Body fat percentage, %16.120.8
Waist circumference, cm55.1 (5.1)67.1 (9.0)
Ethnicity, %  
 White1109 (63.7)1406 (59.8)
 East Asian299 (17.2)352 (15.0)
 South Asian40 (2.3)129 (5.5)
 Middle Eastern83 (4.8)166 (7.1)
 Others/mixed210 (12.1)300 (12.8)
Parental education  
 University771 (49.1)837 (40.6)
 Less than university801 (51.0)1224 (59.4)
Maternal smoking in pregnancy  
 No1421 (88.3)1804 (85.0)
 Yes189 (11.7)319 (15.0)
Maternal illness in pregnancy  
 No1515 (87.0)2104 (89.4)
 Yes226 (13.0)249 (10.6)
Maternal age at birth  
 <20 years40 (2.6)81 (4.0)
 20–24 years167 (10.8)332 (16.4)
 ≥25 years1343 (86.7)1615 (79.6)
Number of siblings  
 Only child196 (11.3)223 (9.5)
 1 other sibling181 (10.4)178 (7.6)
 2 or more siblings1364 (78.4)1952 (83.0)
Passive smoking  
 No1265 (78.4)1687 (76.7)
 Yes349 (21.6)512 (23.3)
First-born child  
 No797 (45.8)1131 (48.1)
 Yes944 (54.2)1222 (51.9)
Birthweight  
 Low (≤2499 g)92 (6.2)114 (6.2)
 Normal (2500–4000 g)1208 (81.6)1534 (83.5)
 High (≥4001 g)180 (12.2)190 (10.3)
Birth by Caesarean section  
 No1034 (77.2)1381 (79.1)
 Yes305 (22.8)365 (20.9)
Duration of breastfeeding  
 ≥3 months997 (62.4)1211 (58.8)
 <3 months601 (37.6)847 (41.2)

Table 2 shows selected socio-economic and familial factors found to be associated with overweight and obesity among 6- and 12-year-old schoolchildren. Among 6-year-old children, after adjusting for age, sex and ethnicity, maternal and paternal education was significantly associated with the prevalence of overweight. Other socio-economic factors such as homeownership and parental employment were not significant covariates (data not shown). Current exposure to passive smoking and being an only child increased the likelihood of being obese by twofold and threefold, respectively (Table 2). Being an only child was significantly associated with obesity in 12-year-old children, OR 2.64 (CI 1.43–4.88). Parental employment and homeownership were not associated with overweight/obesity in this older age group (data not shown).

Table 2.  Association between selected socio-economic and familial factors with the prevalence of overweight and obesity, adjusted for age, sex and ethnicity in 6- and 12-year-old children
FactorPrevalence among 6-year-old childrenPrevalence among 12-year-old children
Overweight n (%)OR (95% CI)Obesity n (%)OR (95% CI)Overweight n (%)OR (95% CI)Obesity n (%)OR (95% CI)
  1. OR, odds ratio; 95% CI, 95% confidence interval.

Maternal education        
 University48 (9.1)1.0 (reference)16 (3.2)1.0 (reference)86 (16.0)1.0 (reference)32 (6.6)1.0 (reference)
 Less than university148 (15.6)1.76 (1.18–2.63)65 (7.5)1.85 (1.18–2.91)323 (24.2)1.60 (1.30–1.97)132 (11.6)1.34 (0.91–1.98)
Paternal education        
 University58 (10.4)1.0 (reference)18 (3.5)1.0 (reference)112 (18.4)1.0 (reference)41 (7.6)1.0 (reference)
 Less than university128 (14.5)1.42 (1.06–1.90)59 (7.3)1.88 (0.98–3.60)277 (23.5)1.30 (1.57–1.76)107 (10.6)0.99 (0.70–1.40)
Parental education        
 University80 (10.8)1.0 (reference)24 (3.5)1.0 (reference)146 (18.2)1.0 (reference)56 (8.1)1.0 (reference)
 Less than university117 (15.8)1.51 (1.15–1.99)57 (8.4)2.06 (1.23–3.46)274 (24.8)1.40 (1.13–1.74)110 (11.7)1.06 (0.72–1.55)
Number of siblings        
 Only child23 (14.2)1.39 (0.90–2.15)18 (11.5)3.29 (1.78–6.11)42 (27.1)1.41 (0.99–2.01)22 (16.3)2.64 (1.43–4.88)
 1 other sibling93 (13.7)1.18 (0.83–1.69)33 (5.3)1.30 (0.73–2.31)147 (19.9)0.90 (0.75–1.07)63 (9.6)1.28 (0.97–1.70)
 2 or more siblings79 (12.8)1.0 (reference)28 (5.0)1.0 (reference)238 (22.5)1.0 (reference)86 (9.5)1.0 (reference)
Passive smoking        
 No154 (12.8)1.0 (reference)52 (4.7)1.0 (reference)312 (19.9)1.0 (reference)117 (8.5)1.0 (reference)
 Yes51 (16.0)1.24 (0.86–1.81)31 (10.4)2.04 (1.22–3.40)127 (28.6)1.49 (1.21–1.84)65 (17.0)1.62 (1.01–2.59)

Table 3 shows perinatal factors associated with overweight and obesity among 6- and 12-year-old children. Among 6-year-old children, the only statistically significant factor associated with overweight was having a high birthweight, OR 1.86 (CI 1.20–2.87). However, we need to highlight that there were a small number of children who were low birthweight, and therefore we may not have had sufficient power to assess the association with overweight or obesity. Being breastfed for less than 3 months was marginally non-significant, OR 1.33 (CI 0.96–1.85). Six-year-old children whose mothers smoked during pregnancy had an 85% increased odds of being obese, and birth by Caesarean section was also a predictor. In the 12-year-old children sample, smoking during pregnancy and admission to a neonatal intensive care unit during infancy increased the likelihood of being overweight by 65% and 60%, respectively. Being born to a mother aged less than 20 years and/or being born as a heavy baby significantly increased the likelihood of being an obese 12-year-old by 97% and 95%, respectively (Table 3).

Table 3.  Association between selected perinatal factors with the prevalence of overweight and obesity adjusted for age, sex and ethnicity in 6- and 12-year-old children
FactorPrevalence among 6-year-old childrenPrevalence among 12-year-old children
Overweight n (%)OR (95% CI)Obesity n (%)OR (95% CI)Overweight n (%)OR (95% CI)Obesity n (%)OR (95% CI)
  • Includes hypertension, diabetes, high fever, rubella and mumps. OR, odds ratio; 95% CI, 95% confidence interval; NICU, neonatal intensive care unit.

Maternal smoking in pregnancy
 No173 (12.8)1.0 (reference)67 (5.4)1.0 (reference)340 (20.4)1.0 (reference)131 (9.0)1.0 (reference)
 Yes31 (17.9)1.40 (0.95–2.06)16 (10.1)1.85 (1.04–3.29)84 (30.4)1.65 (1.34–2.02)41 (17.6)1.61 (1.06–2.45)
Maternal illness in pregnancy
 No185 (13.0)1.0 (reference)80 (6.0)1.0 (reference)433 (22.4)1.0 (reference)162 (9.7)1.0 (reference)
 Yes35 (16.6)1.36 (0.92–2.00)13 (6.9)1.14 (0.57–2.25)46 (21.3)0.93 (0.60–1.43)30 (15.0)1.65 (1.11–2.45)
Maternal age at birth (years)
 <2010 (26.3)1.60 (0.68–3.73)2 (6.7)0.57 (0.10–3.19)21 (32.3)1.29 (0.65–2.55)16 (26.7)1.97 (1.02–3.82)
 20–2427 (17.9)1.0 (reference)15 (10.8)1.0 (reference)77 (25.9)1.0 (reference)33 (13.0)1.0 (reference)
 ≥25155 (12.1)0.69 (0.43–1.09)61 (5.2)0.60 (0.32–1.15)302 (20.2)0.79 (0.62–1.00)113 (8.6)0.77 (0.50–1.16)
First-born child
 No103 (13.6)1.0 (reference)35 (5.1)1.0 (reference)217 (21.0)1.0 (reference)95 (10.4)1.0 (reference)
 Yes117 (13.3)1.01 (0.79–1.30)58 (7.1)1.44 (0.84–2.44)262 (23.4)1.15 (0.95–1.40)97 (10.62)0.99 (0.78–1.26)
Caesarean birth
 No136 (13.8)1.0 (reference)47 (5.3)1.0 (reference)264 (21.0)1.0 (reference)119 (10.7)1.0 (reference)
 Yes39 (14.0)1.14 (0.77–1.69)25 (9.4)2.32 (1.34–4.00)78 (23.5)1.18 (0.89–1.57)32 (11.2)1.11 (0.70–1.77)
Birth weight
 Low (≤2499 g)11 (12.1)1.00 (0.58–1.74)1 (1.2)0.19 (0.02–1.56)18 (16.2)0.69 (0.41–1.18)3 (3.1)0.30 (0.08–1.09)
 Normal (2500–4000 g)141 (12.4)1.0 (reference)64 (6.0)1.0 (reference)296 (21.0)1.0 (reference)116 (9.4)1.0 (reference)
 High (≥4001 g)34 (20.0)1.86 (1.20–2.87)9 (6.2)1.23 (0.65–2.31)43 (26.2)1.26 (0.83–1.91)26 (17.7)1.95 (1.26–3.02)
Admission to NICU
 No164 (13.2)1.0 (reference)73 (6.3)1.0 (reference)343 (21.7)1.0 (reference)140 (10.2)1.0 (reference)
 Yes14 (15.6)1.28 (0.68–2.42)2 (2.6)0.43 (0.12–1.60)35 (31.3)1.60 (1.02–2.52)11 (12.5)1.31 (0.56–3.07)
Duration of breastfeeding
 ≥3 months117 (12.3)1.0 (reference)44 (5.0)1.0 (reference)186 (19.8)1.0 (reference)79 (8.0)1.0 (reference)
 <3 months85 (15.2)1.33 (0.96–1.85)38 (7.4)1.33 (0.85–2.07)224 (24.3)1.29 (1.06–1.58)77 (11.7)1.37 (0.86–2.17)

Parental education less than university level and high birthweight remained independently associated with overweight in 6-year-old children after multivariate adjustment (Table 4). The influence of parental education could potentially be attributed to around 51.9% of obese cases among 6-year-old children (Table 4). Being an only child also increased the risk of obesity by ∼2-fold, compared with having two or more siblings.

Table 4.  Multivariate model of modifiable factors found associated with overweight and obesity in 6- and 12-year-old children
 Prevalence (%)Multivariate-adjusted OR (95% CI)PAR
  • Model also included age, sex and ethnicity (i.e. un-modifiable factors).

  • ‡Passive smoking was significant in the age, sex and ethnicity adjusted model; however, this covariate did not remain significant in the multivariate model, hence, this was not included in the final model and in this table.

  • §

    §Lower parental education, smoking during pregnancy and duration of breastfeeding were significant in age, sex and ethnicity adjusted models; however, these covariates did not remain significant in the multivariate model, and hence, were not included in the final model and in this table.

  • ¶Maternal illness, maternal age at birth and passive smoking were both significant in age, sex and ethnicity adjusted models; however, these covariates did not remain significant in the multivariate model, hence, were not included in this table. OR, odds ratio; 95% CI, 95% confidence intervals; PAR, population attributable risk proportions; NICU, neonatal intensive care unit.

6-year-old study sample   
 Factors associated with overweight   
  Lower parental education49.91.52 (1.15–2.01)0.206
  High birth weight (≥4001 g)12.11.85 (1.17–2.93)0.093
 Factors associated with obesity   
  Lower parental education49.92.16 (1.34–4.13)0.519
  Smoking during pregnancy11.31.90 (1.05–3.46)0.092
  Caesarean birth22.82.33 (1.36–3.97)0.233
  Only child11.72.63 (1.23–5.63)0.160
12-year-old study sample   
 Factors associated with overweight§   
  Passive smoking22.11.36 (1.04–1.77)0.074
  Admission to NICU6.61.54 (1.01–2.53)0.039
 Factors associated with obesity   
  Smoking during pregnancy13.81.78 (1.22–2.61)0.097
  High birth weight (≥4001 g)10.02.12 (1.42–3.16)0.101
  Only child8.03.19 (1.87–5.43)0.149

Exposure to current passive smoking remained independently associated with the prevalence of overweight after adjusting for multiple factors among 12-year-old children (Table 4). PAR proportions indicate that approximately 14.9% of prevalent cases of obesity among 12-year-old children could be attributable to being a single child. Maternal smoking during pregnancy and high birthweight were also factors that were independently associated with the prevalence of obesity in 12-year-old children, after adjusting for multiple confounders (Table 4).

Given that being an only child was significantly associated with the prevalence of obesity among 6- and 12-year-old children, we explored the education and economic status of only-child families compared with other families. We found that in the 6-year-old children sample, one-child families had a higher frequency of homeownership compared with families with more than one child, 56.8% and 43.2%, respectively (P= 0.02). Significant differences were not observed in relation to other indicators of economic status. In 12-year-old children, the frequency of at least one parent attaining university level qualification was 81.6% and 18.4% among children who come from families with more than one child and those that come from one-child families, respectively (P= 0.001). However, there was a higher frequency of homeownership among one-child families compared with families with more than one child, 72.2% and 27.8%, respectively (P= 0.01).

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

There are very few large Australian studies that have analysed the association between multiple risk factors and the prevalence of overweight and obesity in childhood. In this large population-derived study of 6- and 12-year-old schoolchildren, a range of independent risk factors for overweight/obesity was identified in multiple logistic regression analysis. These key risk factors included: lower level of parental education, high birthweight, and current exposure to passive smoking, maternal smoking during pregnancy, and being an only child.

In our study, the level of parental education was inversely associated with prevalence of overweight and obesity in 6-year-old schoolchildren. The mechanisms underlying this link are unknown;21 however, differences in cultural and social norms between parents of high and low education might be a possible explanation.22 Specifically, better educated parents may be more aware of the weight status of their child, as well as the importance of physical activity and healthy eating, and as a result may provide more healthy opportunities and model healthier behaviours.4 Moreover, tertiary educated parents may be more able to afford a healthy diet and provide financial support for children's sporting activity interests.4 Finally, less educated parents are more likely to live in low-income neighbourhoods that are known to be more obesogenic, e.g. having a greater density of fast food outlets.4 Given that childhood socio-economic conditions have a long-lasting impact on risk of developing obesity in adulthood,23 our findings warrant further longitudinal studies to determine the mechanisms underlying the association between low level of parental education and weight status.

Family circumstance also predicts a child's weight status.24 Indeed, in our study, we show that being an only child increased the likelihood of being obese by approximately twofold and threefold in the 6- and 12-year-old child samples, respectively. This is in agreement with findings from Hesketh et al.4 indicating that children with siblings were less likely to be overweight than children without siblings. This can be explained by circumstances specific to only-child families compared with those with several children. For example, it has been shown that children without siblings tend to have fewer opportunities to engage in physical activity and have higher food and fat intakes, as such, increasing their risk of overweight.24 We also observed significant differences in the education and economic status of only child versus other families. Specifically, among both 6- and 12-year-old children, the frequency of homeownership was higher among families with only one child compared with those with two or more children. Future research into the dynamics of single-child families is needed, particularly as the identification of behaviours that could mediate these relationships with obesity would enhance the ability of intervention strategies to improve outcomes for children in such family situations.4

Our study demonstrates that mothers who smoked during pregnancy were 90% and 78% more likely to have obese 6- and 12-year-old children, respectively. These data support findings from recent studies demonstrating links between maternal smoking during pregnancy and childhood adiposity.8,10–14 It is postulated that smoking affects childhood obesity through intrauterine exposure.13 Specifically, a neonate may be undernourished because of exposure to smoking during gestation; this in turn may lead to increased nutrient absorption and greater risk of post-natal obesity.13 Second, hormones such as leptin may mediate associations of smoking with offspring size.13 In humans, maternal smoking throughout pregnancy was observed to be associated with lower cord blood leptin.25 Finally, the significance of maternal smoking during pregnancy is not limited to its harmful effect on mother and foetus. Smoking clusters with other adverse lifestyle choices such as sedentary behaviours, higher fat consumption and greater alcohol intake,26 and its presence during pregnancy is unlikely to be an isolated marker of risk. Our study provides an important public health message, given that there appears to be a continuing increase in smoking among young women that could in turn contribute to the escalating increases in rates of obesity and its related adverse health outcomes in the future.13

High birthweight was another perinatal factor that increased the likelihood of 6- and 12-year-old children being overweight or obese. This observation of higher birthweight being linked to increased body mass later in childhood concurs with the hypothesis that in utero determinants of birthweight, such as the altered maternal–foetal glucose metabolism during gestational diabetes, may also program the foetus for an elevated risk of subsequent weight gain.9 In our study cohort, however, gestational diabetes was not significantly associated either overweight/obesity among 6- and 12-year-old children (data not shown), although this negative finding could have resulted from low study power.

While the above associations were epidemiologically significant, they are unlikely to be the major determinants of obesity and overweight in childhood populations. Overweight and obesity in childhood is likely to be because of a complex interplay of several factors. Inherited characteristics in particular, which we did not measure, aspects of lifestyle such as diet and activity, and psychosocial factors are all likely to be important.27 The Australian Child and Adolescent Obesity Research Network recently identified high priority questions related to modifiable environmental risk/protective factors that remained to be addressed through longitudinal research including prenatal and early childhood patterns of growth and nutrition.28 Our study has identified several modifiable risk factors that could be prioritised as key strategies for reducing childhood obesity. Specifically, in 6-year-old children, over 20% and 50% of overweight and obese cases, respectively, could be attributed to lower parental education. Among the 12-year-old children, around 15% disease burden of obesity may be attributable to coming from an only-child family.

The strengths of this study are its population-derived design and uniform acquisition of data. However, this study has a number of limitations. The present study was primarily a survey of eye disease in Australian children, not obesity. The parental questionnaire therefore did not target obesity as a major study outcome, and we did not collect information on some variables that may be relevant to obesity development such as parental BMI and the exclusivity of breastfeeding. Finally, this study is limited by its cross-sectional design, which does not allow causality to be inferred from the observed associations. A follow-up study is currently underway.

In conclusion, our study suggests that children of less educated parents and/or of mothers who smoked during pregnancy have a higher likelihood of being overweight or obese. Additionally, children who were heavy as newborns and/or who came from single-child families are also at increased risk of being heavier during childhood. These data have identified potential pathways that could be foci of obesity preventions efforts in addition to other, well-established mechanisms. Our findings reinforce the idea that prevention of childhood overweight and obesity requires health promotion intervention programmes that adopt a multifaceted approach in order to tackle the complexities of childhood adiposity.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

The Sydney Myopia Study (Sydney Childhood Eye Study) was supported by the Australian National Health & Medical Research Council (Grant nos. 253732 and 457351); the Westmead Millennium Institute, University of Sydney and the Vision Co-operative Research Centre, University of New South Wales, Sydney, Australia.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
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