Change in weight‐for‐length status during the first three months: Relationships to birth weight and implications for metabolic risk

Abstract

Weight-for-length during the early postnatal period is a critical predictor of subsequent body composition and metabolic risk. This study was designed to analyze change in weight-for-length status according to birth weight in early infancy. Data were collected for 267 infants enrolled in the Jackson County Women, Infants, and Children (WIC) program. Postnatal measurements were collected at a clinic visit between birth and 12 weeks of age (mean = 5.7 weeks). Changes in WHO z-scores (weight, length, weight-for-length) between birth and the clinic visit were calculated. Infants were classified as exclusively breastfed or as formula-fed. Ethnicity was coded as Hispanic or non-Hispanic. Infants were classified based on birth weight z-score as lower (<-1 SD) or higher (> +1 SD). Multiple regression models tested birth weight, demographic factors, and feeding as predictors of z-score change measures. Demographic factors and feeding were also tested as moderators of the effects of birth weight. Lower birth weight infants displayed an increase in weight-for-length z-score between birth and the clinic visit. Change in weight-for-length was associated with significant increase in weight z-score but not in length z-score. Higher birth weight predicted decrease in weight and length z-scores but did not predict change in weight-for-length. Hispanic ethnicity predicted decrease in length z-score and increase in weight-for-length z-score but did not moderate effects of birth weight. Increase in weight-for-length among lower birth weight infants and persistence of high weight-for-length among higher birth weight infants may reflect phenotypic adjustments that are maladaptive in adverse dietary environments.

Connecting the Dots in Childhood Obesity Disparities: a Review of Growth Patterns from Birth to Pre-Adolescence

“…However, results were mixed [29, 36, 39, 42, 49], especially with regard to specific race/ethnic groups [28, 30, 45]. Race/ethnicity and SES were less consistently associated with categorical definitions of rapid infant weight gain [28, 30, 33, 35].…”

“…From birth to 12 months, minority race/ethnicity was associated with faster linear growth [25, 39, 42, 44, 45], with heterogeneity across specific race/ethnic group [45]. Evidence was equivocal for low SES, which was associated with faster [47] or similar [29, 41] linear growth in the first year (Appendix Table S3). Associations between low SES or minority race/ethnicity and faster linear growth were more common after the first three months of life [41, 45] and in periods spanning beyond one year [47, 48, 55], in some cases greatly reducing or overcoming social differences in stature by the end of the study period [46, 47, 49].…”

“…In the first year of life, relative weight change was unrelated to lower SES (Table 2) [29] and inconsistently associated with race/ethnicity [25, 29, 42]. Beyond 12 months, lower SES [34, 38, 48] but not race [38] was associated with faster relative weight change beyond 12 months though with variation in timing [49] and by sex and ethnic subgroup [48, 55].…”

Síndrome metabólica e associação com nível socioeconômico em escolares

“…In a meta-analysis, involving the MC of newborns with the prevalence of metabolic syndrome, it was confirmed that there is a risk of 2.53 chances of developing into adults born with LBW, since genetic mechanisms influencing factors and MC birth determine environmental changes that culminate in the MS and consequent CVD [22][23][24] .…”

“…In the studied sample, decreased concentrations of HDL-C occurred in 18.8% of the school in CSEB, a result that is higher than that of the cross-sectional study done among children and adolescent who were born in Sāo Paulo State, which totaled 13.8% 37 . The presence of MS was diagnosed in 8.7% and all of CSEB and studies indicate the prevalence of those affected to be between 4.1% and 17.2% of investigated [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26] . The relationship between CSE and MS is close because economic disadvantages are predictive for its occurrence among children and adolescents 6,7,13 .…”