7 research outputs found

    Growth, socioeconomic position and later life outcomes in Guatemala, 1953–2017

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    It is well-established that early life environmental exposures and later life health and non-communicable disease (NCD) risk are related, however, life course evidence from low- and middle-income countries is currently limited. Guatemala, a middle-income country located in Central America, is both one of the most income inequal and most stunted countries in the world. It is also the site of the Universidad del Valle de Guatemala (UVG) Longitudinal Study of Child and Adolescent Development. The study followed the growth of over 40,000 urban school children of different socioeconomic position (SEP) groups between 1953-1999. Previous research, on subsamples of the study, has identified socioeconomic inequalities in both physical growth and cognitive ability but the later life health of UVG Study individuals is unknown, as are the broader patterns of growth and development of the entire sample. [Continues.]</div

    Life course associations of height, weight, fatness, grip strength, and all-cause mortality for high socioeconomic status Guatemalans

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    Objectives: The objective of this study was to investigate the association between physical growth in pre-adult life with five outcomes at age 64-76: weight, body mass index, estimated body fat percentage, hand grip strength and mortality. Methods: Super-Imposition by Translation and Rotation (SITAR) growth curves of 40,484 Guatemalan individuals aged 3-19 years were modelled for the parameters of size, timing and intensity (peak growth velocity, e.g. cm/year) of height, weight, body mass index, and grip strength. Associations between the SITAR parameters and old age outcomes were tested using linear and binary logistic regression for a follow-up sample of high socioeconomic status (SES) Guatemalans, of whom 50 were aged 64-76 years old at re-measurement and 45 died prior to the year 2017. Results: SITAR models explained 69-98% of the variance in each outcome, with height the most precise. Individuals in the follow-up sample who had a higher BMI before age 20 years had higher estimated body fat (B=1.4 CI -0.02-2.8) and BMI (B=1.2, CI 0.2-2.2) at the ages 64-76 years. Those who grew slower in height but faster in weight and BMI before age 20 years, had higher BMI and body fat later in life. Conclusions: These findings highlight the importance of a life course perspective on health and mortality risk. Childhood exposures leading to variation in pre-adult growth may be key to better understanding health and mortality risks in old age

    Four decades of socio-economic inequality and secular change in the physical growth of Guatemalans

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    OBJECTIVE: To investigate changes in socio-economic inequalities in growth in height, weight, BMI and grip strength in children born during 1955-1993 in Guatemala, a period of marked socio-economic-political change. DESIGN: We modelled longitudinal data on height, weight, BMI and hand grip strength using Super-Imposition by Translation and Rotation (SITAR). Internal Z-scores summarising growth size, timing and intensity (peak growth velocity, e.g. cm/year) were created to investigate inequalities by socio-economic position (SEP; measured by school attended). Interactions of SEP with date of birth were investigated to capture secular changes in inequalities. SETTING: Urban and peri-urban schools in the region of Guatemala City, Guatemala. PARTICIPANTS: Participants were 40 484 children and adolescents aged 3-19 years of Ladino and Maya ancestry (nobservations 157 067). RESULTS: The difference in height (SITAR size) between lowest and highest SEP decreased from -2·0 (95 % CI -2·2, -1·9) sd to -1·4 (95 % CI -1·5, -1·3) sd in males, and from -2·0 (95 % CI -2·1, -1·9) sd to -1·2 (95 % CI -1·3, -1·2) sd in females over the study period. Inequalities also reduced for weight, BMI and grip strength, due to greater secular increases in lowest-SEP groups. The puberty period was earlier and shorter in higher-SEP individuals (earlier SITAR timing and higher SITAR intensity). All SEP groups showed increases in BMI intensity over time. CONCLUSIONS: Inequality narrowed between the 1960s and 1990s. The lowest-SEP groups were still >1 sd shorter than the highest. Risks remain for reduced human capital and poorer population health for urban Guatemalans

    Differences and secular trends in childhood IQ trajectories in Guatemala City

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    This study documents differences in childhood IQ trajectories of Guatemala City children, aged 6-15 years and born 1961-1993, according to school attended, height-for-age Z-scores (HAZ) and over time (Flynn effect). IQ data come from the Universidad del Valle de Guatemala Longitudinal Study of Child and Adolescent Development. IQ was measured using standardised tests from the Otis-Lennon Mental Ability Test-series. A multilevel model was developed to describe 60 986 IQ observations (level 1), in 22 724 children (level 2), in five schools representing students of different socioeconomic status (SES) (level 3). Average IQ trajectories differed by school. The difference in average IQ at age 11 years between the students of high and low SES schools was 28.7 points. A one-unit increase in HAZ was associated with a 1.42 (0.72, 2.11) unit higher IQ if HAZ was </p

    Supplementary Information Files for Early childhood weight gain: latent patterns and body composition outcomes

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    Supplementary Information Files for Early childhood weight gain: latent patterns and body composition outcomesBackground: Despite early childhood weight gain being a key indicator of obesity risk, we do not have a good understanding of the different patterns that exist. Objectives: To identify and characterise distinct groups of children displaying similar early life weight trajectories. Methods: A growth mixture model captured heterogeneity in weight trajectories between 0-60 months in 1,390 children in the Avon Longitudinal Study of Parents and Children. Differences between the classes in characteristics and body size/composition at 9 years were investigated. Results: The best model had five classes. The “Normal” (45%) and “Normal after initial catch-down” (24%) classes were close to the 50th centile of a growth standard between 24-60 months. The “High-decreasing” (21%) and “Stable-high” (7%) classes peaked at the ~91st centile at 12-18 months, but while the former declined to the ~75th centile and comprised constitutionally big children, the latter did not. The “Rapidlyincreasing” (3%) class gained weight from below the 50th centile at 4 months to above the 91st centile at 60 months. By 9 years, their mean body mass index (BMI) placed them at the 98th centile. This class was characterised by the highest maternal BMI; highest parity; highest levels of gestational hypertension and diabetes; and the lowest socio-economic position. At 9 years, the “Rapidly-increasing” class was estimated to have 68.2% (48.3,88.1) more fat mass than the “Normal” class, but only 14.0% (9.1,18.9) more lean mass. Conclusions: Criteria used in growth monitoring practice are unlikely to consistently distinguish between the different patterns of weight gain reported here.<br
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