Introduction: birth size is affected by diverse maternal, environmental, social, and economic factors. Aim: analyze the relationships between birth size—shown by the indicators small for gestational age (SGA) and large for gestational age (LGA)—and maternal, social, and environmental factors in the Argentine province of Jujuy, located in the Andean foothills. Methods: data was obtained from 49,185 mother-newborn pairs recorded in the Jujuy Perinatal Information System (SIP) between 2009 and 2014, including the following: newborn and maternal weight, length/height, and body mass index (BMI); gestational age and maternal age; mother’s educational level, nutritional status, marital status and birth interval; planned pregnancy; geographic-linguistic origin of surnames; altitudinal place of birth; and unsatisfied basic needs (UBN). The dataset was split into two groups, SGA and LGA, and compared with adequate for gestational age (AGA). Bivariate analysis (ANOVA) and general lineal modeling (GLM) with multinomial distribution were employed. Results: for SGA newborns, risk factors were altitude (1.43 [1.12–1.82]), preterm birth (5.33 [4.17–6.82]), older maternal age (1.59 [1.24–2.05]), and primiparous mothers (1.88 [1.06–3.34]). For LGA newborns, the risk factors were female sex (2.72 [5.51–2.95]), overweight (1.33 [1.22–2.46]) and obesity (1.85 [1.66–2.07]). Conclusions: the distribution of birth size and the factors related to its variability in Jujuy are found to be strongly conditioned by provincial terrain and the clinal variation due to its Andean location.

Objective To analyze variability in newborn (NB) anthropometry among Jujenean NBs as a function of geographic altitude (500 m to ≈4000 masl), maternal anthropometry and other maternal characteristics within the maternal capital framework. Materials and methods Data obtained from 41,371 mother/child pairs recorded in the Jujuy Perinatal Information System (SIP) between 2009 and 2014, including: NB and maternal weight, length/height and BMI; gestational age (corrected); maternal age, educational level, nutritional status, and marital status; birth interval; and planned pregnancy. Based on the declared place of residence, the prevalence of unsatisfied basic needs (% UBN) was determined and the data was split into two altitudinal groups: highlands (HL, >2500 masl) and lowlands (LL, <2500 masl). ANOVA, Chi‐squared and Pearson tests were applied as needed. Statistical associations between the response variables—NB weight, length and BMI—and maternal and environmental variables were tested using a Generalized Additive Mixed Model (GAMM). Results All NB and maternal anthropometric variables were lower in HL compared to LL; they also presented negative correlations with altitude, except NB length. Apart from gestational age and birth interval, HL and LL presented statistically significant differences in all study variables. GAMM results showed that maternal anthropometry was the main influence on NB weight and length. Discussion Of all the maternal capital features examined, only maternal anthropometric variables were found to protect offspring against the negative impact of HL environments.