The consequences of early childhood growth failure over the life course:

This paper examines the impact over the life course of early childhood growth failure as measured by achieved height at 36 months. It uses data collected on individuals who participated in a nutritional supplementation trial between 1969 and 1977 in rural Guatemala and who were subsequently reinterviewed between 2002 and 2004. It finds that individuals who did not suffer growth failure in the first three years of life complete more schooling, score higher on tests of cognitive skill in adulthood, have better outcomes in the marriage market, earn higher wages and are more likely to be employed in higher-paying skilled labor and white-collar jobs, are less likely to live in poor households, and, for women, fewer pregnancies and smaller risk of miscarriages and stillbirths. Growth failure has adverse impacts on body size and several dimensions of physical fitness in adulthood but does not have marked effects on risk indicators of cardiovascular and related chronic diseases. These results provide a powerful rationale for investments that reduce early-life growth failure.Chronic disease, early life growth failure, fertility, Human capital, Poverty, Undernutrition, Wages,

Dietary patterns and cardio-metabolic risk in a population of Guatemalan young adults

Abstract Background Latin America is facing an increasing burden of nutrition-related non-communicable disease. Little is known about dietary patterns in Guatemalan adults and how dietary patterns are associated with cardio-metabolic disease (CMD) risk. Methods This analysis is based on data from a 2002–04 follow-up study of the INCAP Nutrition Supplementation Trial Longitudinal Cohort. Diet data were collected using a validated, semi-quantitative food frequency questionnaire. We derived dietary patterns using principal components analysis. CMD risk was assessed by anthropometry (body mass index, waist circumference), biochemistry (fasting blood glucose and lipids), and clinical (blood pressure) measures. We used sex-stratified multivariable log binomial models to test associations between dietary pattern tertile and CMD risk factors. The sample included 1428 participants (681 men and 747 women) ages 25–43 years. Results We derived three dietary patterns (traditional, meat-based modern, and starch-based modern), collectively explaining 24.2% of variance in the diet. Dietary patterns were not associated with most CMD risk factors; however, higher starch-based modern tertiles were associated with increased prevalence of low highdensity lipoprotein cholesterol (HDL-c) in men (Prevalence Ratio (PR) 1.17, 95% Confidence Interval (CI) 1.01, 1.20 for tertile 2; PR 1.20, 95% CI 1.00, 1.44 for tertile 3; p trend 0.04). Higher traditional tertiles were associated with increased prevalence of abdominal obesity in women (PR 1.24, 95% CI 1.07, 1.43 for tertile 2; PR 1.19, 95% CI 1.02, 1.39 for tertile 3; p trend 0.02) but marginally significant reduced prevalence of low HDL-c in men (PR 0.88, 95% CI 0.76, 1.00 for tertile 2; PR 0.85, 95% CI 0.72, 1.00 for tertile 3; p trend 0.05). Conclusion Our findings suggest the presence of two ‘modern' dietary patterns in Guatemala – one of which was associated with increased prevalence of low HDL-c in men. The association between the traditional dietary pattern and some CMD risk factors may vary by sex.https://deepblue.lib.umich.edu/bitstream/2027.42/137709/1/40795_2017_Article_188.pd

Nutrition status of children in Latin America.

The prevalence of overweight and obesity is rapidly increasing among Latin American children, posing challenges for current healthcare systems and increasing the risk for a wide range of diseases. To understand the factors contributing to childhood obesity in Latin America, this paper reviews the current nutrition status and physical activity situation, the disparities between and within countries and the potential challenges for ensuring adequate nutrition and physical activity. Across the region, children face a dual burden of undernutrition and excess weight. While efforts to address undernutrition have made marked improvements, childhood obesity is on the rise as a result of diets that favour energy-dense, nutrient-poor foods and the adoption of a sedentary lifestyle. Over the last decade, changes in socioeconomic conditions, urbanization, retail foods and public transportation have all contributed to childhood obesity in the region. Additional research and research capacity are needed to address this growing epidemic, particularly with respect to designing, implementing and evaluating the impact of evidence-based obesity prevention interventions

Implementation tells us more beyond pooled estimates: Secondary analysis of a multicountry mHealth trial to reduce blood pressure

Background: The uptake of an intervention aimed at improving health-related lifestyles may be influenced by the participant’s stage of readiness to change behaviors. Objective: We conducted secondary analysis of the Grupo de Investigación en Salud Móvil en América Latina (GISMAL) trial according to levels of uptake of intervention (dose-response) to explore outcomes by country, in order to verify the consistency of the trial’s pooled results, and by each participant’s stage of readiness to change a given lifestyle at baseline. The rationale for this secondary analysis is motivated by the original design of the GISMAL study that was independently powered for the primary outcome—blood pressure—for each country. Methods: We conducted a secondary analysis of a mobile health (mHealth) multicountry trial conducted in Argentina, Guatemala, and Peru. The intervention consisted of monthly motivational phone calls by a trained nutritionist and weekly tailored text messages (short message service), over a 12-month period, aimed to enact change on 4 health-related behaviors: salt added to foods when cooking, consumption of high-fat and high-sugar foods, consumption of fruits or vegetables, and practice of physical activity. Results were stratified by country and by participants’ stage of readiness to change (precontemplation or contemplation; preparation or action; or maintenance) at baseline. Exposure (intervention uptake) was the level of intervention (<50%, 50%-74%, and ≥75%) received by the participant in terms of phone calls. Linear regressions were performed to model the outcomes of interest, presented as standardized mean values of the following: blood pressure, body weight, body mass index, waist circumference, physical activity, and the 4 health-related behaviors. Results: For each outcome of interest, considering the intervention uptake, the magnitude and direction of the intervention effect differed by country and by participants’ stage of readiness to change at baseline. Among those in the high intervention uptake category, reductions in systolic blood pressure were only achieved in Peru, whereas fruit and vegetable consumption also showed reductions among those who were at the maintenance stage at baseline in Argentina and Guatemala. Conclusions: Designing interventions oriented toward improving health-related lifestyle behaviors may benefit from recognizing baseline readiness to change and issues in implementation uptake. Trial Registration: ClinicalTrials.gov NCT01295216; http://clinicaltrials.gov/ct2/show/NCT01295216 (Archived by WebCite at http://www.webcitation.org/72tMF0B7B)

Body fat measurement by bioelectrical impedance and air displacement plethysmography: a cross-validation study to design bioelectrical impedance equations in Mexican adults

<p>Abstract</p> <p>Background</p> <p>The study of body composition in specific populations by techniques such as bio-impedance analysis (BIA) requires validation based on standard reference methods. The aim of this study was to develop and cross-validate a predictive equation for bioelectrical impedance using air displacement plethysmography (ADP) as standard method to measure body composition in Mexican adult men and women.</p> <p>Methods</p> <p>This study included 155 male and female subjects from northern Mexico, 20–50 years of age, from low, middle, and upper income levels. Body composition was measured by ADP. Body weight (BW, kg) and height (Ht, cm) were obtained by standard anthropometric techniques. Resistance, R (ohms) and reactance, Xc (ohms) were also measured. A random-split method was used to obtain two samples: one was used to derive the equation by the "all possible regressions" procedure and was cross-validated in the other sample to test predicted versus measured values of fat-free mass (FFM).</p> <p>Results and Discussion</p> <p>The final model was: FFM (kg) = 0.7374 * (Ht²/R) + 0.1763 * (BW) - 0.1773 * (Age) + 0.1198 * (Xc) - 2.4658. R²was 0.97; the square root of the mean square error (SRMSE) was 1.99 kg, and the pure error (PE) was 2.96. There was no difference between FFM predicted by the new equation (48.57 ± 10.9 kg) and that measured by ADP (48.43 ± 11.3 kg). The new equation did not differ from the line of identity, had a high R²and a low SRMSE, and showed no significant bias (0.87 ± 2.84 kg).</p> <p>Conclusion</p> <p>The new bioelectrical impedance equation based on the two-compartment model (2C) was accurate, precise, and free of bias. This equation can be used to assess body composition and nutritional status in populations similar in anthropometric and physical characteristics to this sample.</p

Confusion and Conflict in Assessing the Physical Activity Status of Middle-Aged Men

BACKGROUND: Physical activity (including exercise) is prescribed for health and there are various recommendations that can be used to gauge physical activity status. The objective of the current study was to determine whether twelve commonly-used physical activity recommendations similarly classified middle-aged men as sufficiently active for general health. METHODS AND FINDINGS: We examined the commonality in the classification of physical activity status between twelve variations of physical activity recommendations for general health in ninety men aged 45-64 years. Physical activity was assessed using synchronised accelerometry and heart rate. Using different guidelines but the same raw data, the proportion of men defined as active ranged from to 11% to 98% for individual recommendations (median 73%, IQR 30% to 87%). There was very poor absolute agreement between the recommendations, with an intraclass correlation coefficient (A,1) of 0.24 (95% CI, 0.15 to 0.34). Only 8% of men met all 12 recommendations and would therefore be unanimously classified as active and only one man failed to meet every recommendation and would therefore be unanimously classified as not sufficiently active. The wide variability in physical activity classification was explained by ostensibly subtle differences between the 12 recommendations for thresholds related to activity volume (time or energy), distribution (e.g., number of days of the week), moderate intensity cut-point (e.g., 3 vs. 4 metabolic equivalents or METs), and duration (including bout length). CONCLUSIONS: Physical activity status varies enormously depending on the physical activity recommendation that is applied and even ostensibly small differences have a major impact. Approximately nine out of every ten men in the present study could be variably described as either active or not sufficiently active. Either the effective dose or prescription that underlies each physical activity recommendation is different or each recommendation is seeking the same prescriptive outcome but with variable success

Implementation tells us more beyond pooled estimates: Secondary analysis of a multicountry mhealth trial to reduce blood pressure

Background: The uptake of an intervention aimed at improving health-related lifestyles may be influenced by the participant’s stage of readiness to change behaviors. Objective: We conducted secondary analysis of the Grupo de Investigación en Salud Móvil en América Latina (GISMAL) trial according to levels of uptake of intervention (dose-response) to explore outcomes by country, in order to verify the consistency of the trial’s pooled results, and by each participant’s stage of readiness to change a given lifestyle at baseline. The rationale for this secondary analysis is motivated by the original design of the GISMAL study that was independently powered for the primary outcome—blood pressure—for each country. Methods: We conducted a secondary analysis of a mobile health (mHealth) multicountry trial conducted in Argentina, Guatemala, and Peru. The intervention consisted of monthly motivational phone calls by a trained nutritionist and weekly tailored text messages (short message service), over a 12-month period, aimed to enact change on 4 health-related behaviors: salt added to foods when cooking, consumption of high-fat and high-sugar foods, consumption of fruits or vegetables, and practice of physical activity. Results were stratified by country and by participants’ stage of readiness to change (precontemplation or contemplation; preparation or action; or maintenance) at baseline. Exposure (intervention uptake) was the level of intervention (<50%, 50%-74%, and ≥75%) received by the participant in terms of phone calls. Linear regressions were performed to model the outcomes of interest, presented as standardized mean values of the following: blood pressure, body weight, body mass index, waist circumference, physical activity, and the 4 health-related behaviors. Results: For each outcome of interest, considering the intervention uptake, the magnitude and direction of the intervention effect differed by country and by participants’ stage of readiness to change at baseline. Among those in the high intervention uptake category, reductions in systolic blood pressure were only achieved in Peru, whereas fruit and vegetable consumption also showed reductions among those who were at the maintenance stage at baseline in Argentina and Guatemala. Conclusions: Designing interventions oriented toward improving health-related lifestyle behaviors may benefit from recognizing baseline readiness to change and issues in implementation uptake.Fil: Carrillo-Larco, Rodrigo M.. Universidad Peruana Cayetano Heredia; Perú. Imperial College London; Reino UnidoFil: Jiwani, Safia S.. Universidad Peruana Cayetano Heredia; PerúFil: Diez Canseco, Francisco. Universidad Peruana Cayetano Heredia; PerúFil: Kanter, Rebecca. Institute of Nutrition of Central America and Panama; Guatemala. Universidad de Chile; ChileFil: Beratarrechea, Andrea Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Institute for Clinical Effectiveness and Health Policy; ArgentinaFil: Irazola, Vilma. Institute for Clinical Effectiveness and Health Policy; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Ramirez Zea, Manuel. Institute of Nutrition of Central America and Panama; GuatemalaFil: Rubinstein, Adolfo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaFil: Martinez, Homero. Nutrition International; Canadá. Hospital Infantil de Mexico Federico Gomez; MéxicoFil: Miranda, J. Jaime. Cronicas Centro de Excelencia En Enfermedades Crónicas; Perú. Universidad Peruana Cayetano Heredia; PerúFil: Alasino, Adrían. Funprecal; ArgentinaFil: Budiel Moscoso, Berneth Nuris. Universidad Peruana Cayetano Heredia; PerúFil: Carrara, Carolina. Instituto Universitario del Hospital Italiano de Buenos Aires; ArgentinaFil: Espinoza Surichaqui, Jackelyn. Universidad Peruana Cayetano Heredia; PerúFil: Giardini, Gimena. Instituto Universitario del Hospital Italiano de Buenos Aires; ArgentinaFil: Guevara, Jesica. Institute of Nutrition of Central America And Panama Guatemala; GuatemalaFil: Morales Juárez, Analí. Institute of Nutrition of Central America And Panama Guatemala; GuatemalaFil: Lázaro Cuesta, Lorena. Funprecal; ArgentinaFil: Lewitan, Dalia. Institute For Clinical Effectiveness And Health Policy; ArgentinaFil: Palomares Estrada, Lita. Universidad Peruana Cayetano Heredia; PerúFil: Martínez Ramírez, Carla. Universidad Peruana Cayetano Heredia; PerúFil: de la Cruz, Gloria Robles. Universidad Peruana Cayetano Heredia; PerúFil: Salguero, Julissa. Institute Of Nutrition Of Central America And Panama Guatemala; GuatemalaFil: Saravia Drago, Juan Carlos. Universidad Peruana Cayetano Heredia; PerúFil: Urtasún, María. Institute For Clinical Effectiveness And Health Policy; ArgentinaFil: Zavala Loayza, José Alfredo. Universidad Peruana Cayetano Heredia; Per

Parental childhood growth and offspring birthweight : Pooled analyses from four birth cohorts in low and middle income countries

Funding Information Bill and Melinda Gates Foundation. Grant Number: OPP1020058 Wellcome Trust 089257/Z/09/Z Contract grant sponsor: the National Heart, Lung and Blood Institute at National Institutes of Health. Grant Number: HHSN 268200900028C to the Center of Excellence – INCAP/ Guatemala; and Grand Challenges Canada (Grant number: 0072‐03 to the Grantee, The Trustees of the University of Pennsylvania)Peer reviewedPublisher PD

Size at Birth, Weight Gain in Infancy and Childhood, and Adult Diabetes Risk in Five Low-or Middle-Income Country Birth Cohorts

OBJECTIVEdWe examined associations of birth weight and weight gain in infancy and early childhood with type 2 diabetes (DM) risk in five cohorts from low-and middle-income countries. RESEARCH DESIGN AND METHODSdParticipants were 6,511 young adults from Brazil, Guatemala, India, the Philippines, and South Africa. Exposures were weight at birth, at 24 and 48 months, and adult weight, and conditional weight gain (CWG, deviation from expected weight gain) between these ages. Outcomes were adult fasting glucose, impaired fasting glucose or DM (IFG/DM), and insulin resistance homeostasis model assessment (IR-HOMA, three cohorts). RESULTSdBirth weight was inversely associated with adult glucose and risk of IFG/DM (odds ratio 0.91[95% CI 0.84-0.99] per SD). Weight at 24 and 48 months and CWG 0-24 and 24-48 months were unrelated to glucose and IFG/DM; however, CWG 48 months-adulthood was positively related to IFG/DM (1.32 [1.22-1.43] per SD). After adjusting for adult waist circumference, birth weight, weight at 24 and 48 months and CWG 0-24 months were inversely associated with glucose and IFG/DM. Birth weight was unrelated to IR-HOMA, whereas greater CWG at 0-24 and 24-48 months and 48 months-adulthood predicted higher IR-HOMA (all P , 0.001). After adjusting for adult waist circumference, birth weight was inversely related to IR-HOMA. CONCLUSIONSdLower birth weight and accelerated weight gain after 48 months are risk factors for adult glucose intolerance. Accelerated weight gain between 0 and 24 months did not predict glucose intolerance but did predict higher insulin resistance. 35:72-79, 2012 Diabetes Car