Obesity and its related non-communicable diseases (NCDs), such as type 2 diabetes, heart disease and cancer, impose huge burdens on society, particularly the healthcare system. Until recently, public health and policy were primarily focused on secondary prevention and treatment of NCDs. However, epidemiological and experimental evidence indicates that early-life exposures influence the risk of childhood obesity and related diseases later in life, and has now focused attention on the health of both mother and child. During pregnancy and the early neonatal period, individuals respond to their environment by establishing anatomical, physiological and biochemical trajectories that shape their future health. This period of developmental plasticity provides an early window of opportunity to mitigate the environmental insults that may increase an individual’s sensitivity to, or risk of, developing obesity or related diseases later in life. Although much investigation has already occurred in the area of Developmental Origins of Health and Disease research, the science itself is still in its infancy. It remains for researchers to tackle the important outstanding questions and translate their knowledge into workable solutions for the public good. The challenge, however, is to decide which areas to focus on. With these opportunities and challenges in mind, the 2014 Gravida Summit convened to examine how its early-life research program can determine which areas of research into mechanisms, biomarkers and interventions could contribute to the international research strategy to fight childhood obesity and its related diseases.

Some studies have found a significant relationship between birth weight (BW) and the risk of coronary heart disease (CHD) in adulthood, but results were inconsistent. The purpose of this study was to characterize the association between BW and the risk of CHD in adults. Among 144 papers detected by our search, 27 papers provided data on the relationship between BW and CHD, of which 23 papers considered BW as a continuous variable, and 14 articles considered BW as a categorical variable for this meta-analysis. Based on 23 papers, the mean weighted estimate for the association between BW and the combined outcome of non-fatal and fatal CHD was 0.83 [95% confidence interval (CI), 0.80–0.86] per kilogram of BW (P<0.0001). Low birth weight (LBW<2500 g) was associated with increased risk of CHD [odds ratio (OR), 1.19; 95% confidence interval (CI), 1.11–1.27] compared with subjects with BW⩾2500 g. LBW, as compared with normal BW (2500–4000 g), was associated with increased risk of CHD (OR, 1.16; 95% CI, 1.08–1.25). High birth weight (HBW⩾4000 g) was associated with decreased risk of CHD (OR, 0.89; 95% CI, 0.81–0.98) compared with subjects with BW<4000 g. In addition, there was an indication (not quite significant) that HBW was associated with a lower risk of CHD (OR, 0.89; 95% CI, 0.79–1.01), as compared with normal BW. No significant evidence of publication bias was present. These results suggest that LBW is significantly associated with increased risk of CHD and a 1 kg higher BW is associated with a 10–20% lower risk of CHD.

The importance of skeletal muscle for metabolic health and obesity prevention is gradually gaining recognition. As a result, interventions are being developed to increase or maintain muscle mass and metabolic function in adult and elderly populations. These interventions include exercise, hormonal and nutritional therapies. Nonetheless, growing evidence suggests that maternal malnutrition and obesity during pregnancy and lactation impede skeletal muscle development and growth in the offspring, with long-term functional consequences lasting into adult life. Here we review the role of skeletal muscle in health and obesity, providing an insight into how this tissue develops and discuss evidence that maternal obesity affects its development, growth and function into adult life. Such evidence warrants the need to develop early life interventions to optimise skeletal muscle development and growth in the offspring and thereby maximise metabolic health into adult life.

We implemented six confounding adjustment methods: (1) covariate-adjusted regression, (2) propensity score (PS) regression, (3) PS stratification, (4) PS matching with two calipers, (5) inverse probability weighting and (6) doubly robust estimation to examine the associations between the body mass index (BMI) z-score at 3 years and two separate dichotomous exposure measures: exclusive breastfeeding v. formula only (n=437) and cesarean section v. vaginal delivery (n=1236). Data were drawn from a prospective pre-birth cohort study, Project Viva. The goal is to demonstrate the necessity and usefulness, and approaches for multiple confounding adjustment methods to analyze observational data. Unadjusted (univariate) and covariate-adjusted linear regression associations of breastfeeding with BMI z-score were −0.33 (95% CI −0.53, −0.13) and −0.24 (−0.46, −0.02), respectively. The other approaches resulted in smaller n (204–276) because of poor overlap of covariates, but CIs were of similar width except for inverse probability weighting (75% wider) and PS matching with a wider caliper (76% wider). Point estimates ranged widely, however, from −0.01 to −0.38. For cesarean section, because of better covariate overlap, the covariate-adjusted regression estimate (0.20) was remarkably robust to all adjustment methods, and the widths of the 95% CIs differed less than in the breastfeeding example. Choice of covariate adjustment method can matter. Lack of overlap in covariate structure between exposed and unexposed participants in observational studies can lead to erroneous covariate-adjusted estimates and confidence intervals. We recommend inspecting covariate overlap and using multiple confounding adjustment methods. Similar results bring reassurance. Contradictory results suggest issues with either the data or the analytic method.

Recent studies have shown that a low birth weight is a risk factor for increased systemic blood pressure (BP) in adulthood. Further, systemic BP and arterial stiffness (AS) are reported to be increased in adolescents born prematurely. The purpose of this study was to characterize systemic BP and AS in young adults born preterm. Systemic BP was measured using an automated oscillometric device. AS was assessed by measuring the right carotid–radial pulse wave velocity (PWV) using a validated non-invasive automated method. Systemic BP, pulse pressure, and PWV [mean (confidence intervals)] were compared between 16 adults (age 21 years) born preterm (age at birth 32 weeks of gestation) with a birth weight (1710 g) appropriate for their gestational age and 15 adults (21 years) born at term (40 weeks of gestation) with a birth weight (3430 g) appropriate for their gestational age. Adults born preterm had a significantly higher systolic BP [122 mmHg (114–144) v. 112 (106–127)], mean BP [89 mmHg (86–98) v. 84 (81–91)], diastolic BP [69 mmHg (66–76) v. 65 (62–78)], pulse pressure [54 mmHg (47–72) v. 47 (42–60)], and PWV [7 m/s (6.3–8.6) v. 6.4 (5.8–8)] than did those born at term. Our findings suggest that young adults with a low birth weight due to preterm birth have increased systemic BP and AS. Accordingly, preterm birth may predispose individuals to cardiovascular diseases in adulthood due to increased AS.

Investigators have suggested a link between birth weight and both hand and lumbar spine osteoarthritis (OA). In this study, we sought to extend these observations by investigating relationships between growth in early life, and clinical and radiological diagnoses of OA at the hand, knee and hip, among participants from the Hertfordshire Cohort Study. Data were available for 222 men and 222 women. Clinical OA was defined based on American College of Rheumatology criteria. Radiographs were taken of the knees and hips, and graded for the presence of osteophytes and overall Kellgren and Lawrence (KL) score. Lower weight at year one was associated with higher rates of clinical hand OA (OR 1.396, 95% CI 1.05, 1.85, P=0.021). Individuals with lower birth weights were more likely to have hip osteophytes (OR 1.512, 95% CI 1.14, 2.00, P=0.004) and this remained robust after adjustment for confounders. Furthermore, a low weight at one year was also associated with a higher osteophyte number in the lateral compartment of the knee, after adjustment for confounders (OR 1.388, 95% CI 1.01, 1.91, P=0.043). We have found further evidence of a relationship between early life factors and adult OA. These findings accord with previous studies.

Evidence suggests that breastfeeding during infancy lowers the risk of metabolic syndrome (MS) and its attendant risk factors in adult life. To investigate the influence of feeding type on the risk factors of MS, we assessed insulin sensitivity and lipid and apolipoprotein metabolism in preterm infants. Blood samples were collected from preterm infants at the time of discharge. Infants were separated into two groups: a breast milk (BM) group receiving ⩾90% of their intake from BM, and a mixed-fed (MF) group receiving ⩾50% of their intake from formula. The following indices were then compared between the two groups. Blood glucose and serum insulin levels were used to calculate the quantitative insulin sensitivity check index (QUICKI). We also measured serum total cholesterol (TC), low-density lipoprotein cholesterol (LDLc), high-density lipoprotein cholesterol (HDLc), apolipoprotein-A1 (apoA1) and apolipoprotein-B (apoB) levels, and the ratios of TC/HDLc, LDLc/HDLc and apoB/apoA1. The mean gestational age was 32.9 weeks at birth, and blood samples were collected at a mean corrected age of 37.4 weeks. There were 22 infants in the BM group and 19 in the MF group. QUICKI was significantly higher in the BM group. TC, HDLc and apoA1 were not significantly different between the groups, but LDLc and apoB levels were significantly higher in the BM group. The TC/HDLc, LDLc/HDLc and apoB/apoA1 ratios were significantly higher in the BM group. In preterm infants, the type of feeding exposure in the early postnatal period may influence glucose, lipid and apolipoprotein metabolism, and affect markers of MS.