An ecological systems approach to examining risk factors for early childhood overweight: findings from the UK Millennium Cohort Study

Participants

The MCS is a prospective study of UK children born in the new millennium. Families were invited to participate if they were eligible for Child Benefit (a universal benefit for families with children) and resident in England, Wales, Scotland, and Northern Ireland when the child was aged nine months.[11] The MCS employed a stratified clustered sampling design to over-represent children living in disadvantaged areas and from ethnic minority groups. Additional information on the sampling framework has been previously reported.[12] The original sample consisted of 18 819 children (18 553 families), born between September 2000 and January 2002, with a mean age of 9.2 months (SD 0.5) at the first contact (response 72%). Eighty percent (14 630/18 296) of the singleton infants participated in the second contact, which took place between September 2003 and January 2005, when the children were mean age 37.7 months (SD 2.5). Attrition was highest among families from Northern Ireland, in electoral wards in England defined as ‘ethnic’ (based on the 1991 Census, if at least 30% of residents were from an ethnic minority group), and ‘disadvantaged’ wards from all UK countries (above the upper quartile of the Child Poverty Index).[13] At both contacts, main respondents (over 99% were natural mothers) and their partners (of those interviewed, over 99% were natural fathers) were interviewed in the home. Data were obtained from the UK Data Archive, University of Essex. The MCS received ethical approval from the South West and London Multi-Centre Research Ethics Committees for the first and second contacts, respectively.[14]

Among the 14 630 singleton children, 13 188 had data available for analysis. Families were excluded if the main respondent was not female (185), the partner respondent was not male (132), there were two singleton cohort children from the same family (10), or the child had a missing height or weight (802) or a height-for-age, weight-for-age, or body mass index (BMI; weight/height²) -for-age z-score ≤ -5 or ≥ 5 (467). Some participants satisfied more than one exclusion criterion. Children were more likely to have missing or implausible BMI data if they were from an ethnic minority group, lower income family, or if their mother was a lone parent, had a lower academic qualification, or lower socioeconomic circumstances (p<.01).

Outcome measure

At the second contact, trained interviewers measured the children’s weight and height without shoes or outdoor clothing. The children were weighed using Tanita HD-305 scales (Tanita UK Ltd, Middlesex, UK), recorded to the nearest 0.1 kg, and height was measured using Leicester Height Measure Stadiometers (Seca Ltd, Birmingham, UK), recorded to the nearest 0.1 cm. Childhood overweight (including obesity) was defined by the International Obesity TaskForce cut-offs for BMI, which are age and sex specific.[15]

Potential risk factors

Potential risk factors were chosen based on prior evidence,[10, 16-19] including previous research on early childhood obesity in the MCS. Overall, 26 risk factors were examined across the following levels (Table 1): individual (6), family (13), community (5), area (2). All individual-, family-, and community-level risk factors were reported by parents, usually the mother. Area-level risk factors were derived from the child’s address at the first contact. Definitions of risk factors are presented in Table 1, while more detailed descriptions are published elsewhere.[17-19] Only those factors not previously defined are described here. Birthweight z-scores were calculated using the British 1990 growth reference[20], which are adjusted for gestational age and gender. Parental height and weight at the first contact was collected by self-report. Children were grouped as having neither parent overweight (BMI <25 kg/m²) or their father, mother, or both parents overweight (BMI ≥25 kg/m²). At the first contact, mothers were asked their smoking habits immediately before pregnancy, whether they changed during pregnancy, and if so, the month they changed. Maternal smoking during pregnancy was defined as the number of cigarettes smoked daily at three months gestation. Mothers also reported whether the cohort child was their first live born or not (parity). Ward type was based on the grouping of electoral wards (as established in 1998) as defined for the MCS sampling framework. Wards that were not ‘ethnic’ or ‘disadvantaged’ (previously defined) were considered ‘advantaged’. In Wales, Scotland, and Northern Ireland there was no ‘ethnic’ stratum.[12]

Statistical methods

All analyses were conducted using STATA statistical software, version 9.2 SE (Stata Corporation, Texas), with survey commands to account for the clustered sampling design and obtain robust standard errors. Weighted percentages were derived and regression analyses were conducted using survey and non-response weights to account for the clustered sampling and attrition between contacts. P values were calculated by an adjusted Wald test.

Unadjusted logistic regression analyses were conducted to examine the relationships between individual-, family-, community-, and area-level factors and early childhood overweight (Table 1). Factors significant at the p≤.05 level were included in the adjusted models in a stepped approach. Model 1 included individual-level risk factors only. In Models 2-4, family-, community-, and area-level risk factors were added sequentially. Only one interaction was examined, specified a priori, between ‘child’s gender’ and ‘which parent overweight’. The interaction was not significant in the unadjusted analyses and not included in the adjusted models.

Unadjusted analyses

Adjusted analyses

Results from the stepped analysis are presented in Table 3. After mutual adjustment for individual-level factors (Model 1), early childhood overweight was directly associated with birthweight, Black ethnicity, early introduction of solid foods, and television use for at least three hours daily. Protective factors for early childhood overweight were Indian ethnicity and breastfeeding. All relationships, except television viewing, were maintained after adjustment for family- (Model 2), community- (Model 3), and area-level (Model 4) factors.

After mutual adjustment for individual- and family-level factors (Model 2), early childhood overweight was directly associated with lone motherhood, smoking during pregnancy (1-19 cigarettes daily), parental overweight, prepregnancy overweight, and maternal employment (21+ hours/week). These relationships were maintained after adjustment for community- (Model 3) and area-level (Model 4) factors.

The relationship between early childhood overweight and access to a garden was not maintained after it was added in Model 3 or after adjustment for area-level factors (Model 4). After area-level factors were added in Model 4, early childhood overweight was only associated with residence in Wales.

Forward and backward stepwise logistic regression analyses were conducted to check the validity of the model from the stepped analysis. All significant factors from the fully adjusted stepped model were retained in the final forward and backward models, demonstrating agreement between the three approaches (data not shown).

Implications for policy and practice

Our results provide additional evidence that obesity prevention needs to begin in early life. When an ecological systems approach was applied to examining overweight in young children, individual- and family-level risk factors were found to be more influential than community- and area-level factors. Our findings suggest that obesity prevention should focus on supporting parents, particularly in promoting maternal health behaviours during pregnancy and postpartum. There are a limited number of interventions on preventing early childhood obesity and most have targeted dietary, physical activity, and sedentary behaviours during the preschool years.[4-6] Wen and colleagues are conducting a randomised controlled trial of home visits over the first two years of life with the aim of preventing overweight in preschool children.[37] Whilst this novel study addresses gaps in the evidence base, additional interventions focusing on early factors are needed.

Since parental overweight is one of the strongest predictors of early childhood overweight as well as overweight across the life course,[28] supporting parents to maintain a healthy weight is an important component of obesity prevention. The US has a target to reduce the number of overweight adults[38] and addressing adult obesity is a component of the UK Government’s obesity strategy.[9, 39] Furthermore, maternal overweight prepregnancy is increasing in the US[40] and UK.[41] The recently published cross-Government obesity strategy for England proposes that obesity prevention will be integrated into routine health visits to identify at-risk families.[39] During the first antenatal visit, health professionals will give advice to overweight mothers on healthy weight gain during pregnancy. Furthermore, health visits during infancy will focus on promoting a healthy weight in early life.

An ecological systems approach to tackling obesity requires action across government departments. This is well illustrated by action on infant feeding. It has been suggested that improving breastfeeding rates could significantly reduce the number of cases of childhood obesity.[42] There is international support to increase breastfeeding rates,[38, 43] with the aim for mothers to exclusively breastfeed for six months.[44] The WHO Child Growth Standard promotes breastfeeding by monitoring infant growth with a chart developed from exclusively breastfed infants.[45] The cross-Government obesity strategy for England endorses the adoption of the WHO Child Growth Standard as well as an information campaign to promote breastfeeding.[39] Legislation has been proposed in England[46] and enacted elsewhere[47, 48] to protect breastfeeding in public places and/or at work. In the UK, government efforts to increase paid parental leave[49] and promote work/life balance[50] may help support infant feeding recommendations.[44]

Most risk factors for early childhood overweight, including parental overweight and maternal smoking during pregnancy, are modifiable or would allow at-risk groups, such as lone mothers or overweight women early in pregnancy, to be identified. Improving modifiable risk factors could reduce childhood obesity at the population level.[42, 51] Since the short- and long-term consequences of obesity are a significant burden to society,[9] even a small decrease in the prevalence of obesity at the population level is worth achieving. However, modifying health behaviours requires action at many different levels. Policies at the community- and regional-levels can help create an environment that supports healthy behaviours for parents and their children.