Length of urban residence and obesity among within-country rural-to-urban Andean migrants.

OBJECTIVE: To evaluate the association between length of residence in an urban area and obesity among Peruvian rural-to-urban migrants. DESIGN: Cross-sectional database analysis of the migrant group from the PERU MIGRANT Study (2007). Exposure was length of urban residence, analysed as both a continuous (10-year units) and a categorical variable. Four skinfold site measurements (biceps, triceps, subscapular and suprailiac) were used to calculate body fat percentage and obesity (body fat percentage >25% males, >33% females). We used Poisson generalized linear models to estimate adjusted prevalence ratios and 95 % confidence intervals. Multicollinearity between age and length of urban residence was assessed using conditional numbers and correlation tests. SETTING: A peri-urban shantytown in the south of Lima, Peru. SUBJECTS: Rural-to-urban migrants (n 526) living in Lima. RESULTS: Multivariable analyses showed that for each 10-year unit increase in residence in an urban area, rural-to-urban migrants had, on average, a 12 % (95 % CI 6, 18 %) higher prevalence of obesity. This association was also present when length of urban residence was analysed in categories. Sensitivity analyses, conducted with non-migrant groups, showed no evidence of an association between 10-year age units and obesity in rural (P=0·159) or urban populations (P=0·078). High correlation and a large conditional number between age and length of urban residence were found, suggesting a strong collinearity between both variables. CONCLUSIONS: Longer lengths of urban residence are related to increased obesity in rural-to-urban migrant populations; therefore, interventions to prevent obesity in urban areas may benefit from targeting migrant groups

Análisis espacial de la anemia gestacional en el Perú, 2015.

Objectives. To establish regional prevalences of anemia in pregnant women receiving care at public clinics in Peru in 2015 and identify high-prevalence district conglomerates. Materials and Methods. An ecological study was carried out on data from pregnant women with anemia registered on the Nutritional Status Information System (SIEN) who received care in 7703 public clinics in 2015. Regional and district prevalences of gestational anemia were calculated. District conglomerates with a high prevalence of gestational anemia were identified using the Moran Index. Results. Information was gathered from 311,521 pregnant women distributed in 1638 districts in Peru. The national prevalence of anemia was 24.2% (95% confidence interval [95% CI]: 24.0-24.3%), the rural prevalence was 30.5%, and the urban prevalence was 22.0%. The regions of Huancavelica (45.5%; 95% CI: 44.2-46.7%), Puno (42.8%; 95% CI: 41.9-43.7%), Pasco (38.5%; 95% CI: 36.9-40.0%), Cusco (36.0%; 95% CI: 35.3-36.8%), and Apurímac (32.0%; 95% CI: 30.8-33.1%) had the highest prevalences of anemia. The local Moran Index identified 202 high-priority districts (hot spots) (12.3% of total; 44 urban and 158 rural) located in Ancash, Apurímac, Arequipa, Ayacucho, Cajamarca, Cusco, Huancavelica, Huánuco, Junín, La Libertad, Lima, Pasco, and Puno containing high-prevalence district conglomerates. Conclusions. Gestational anemia in Peru has its highest prevalence rates in rural and southern mountainous areas. The district conglomerates with high prevalence rates of gestational anemia coincide with the areas of high regional prevalence.Objetivos. Establecer las prevalencias regionales e identificar conglomerados distritales con altas prevalencias de anemia en gestantes atendidas en los establecimientos de salud públicos del Perú en el 2015. Materiales y métodos. Se realizó un estudio ecológico de datos de gestantes con anemia, registrados en el Sistema de Información del Estado Nutricional (SIEN), que fueron atendidas en 7703 establecimientos públicos de salud durante el 2015. Se calcularon prevalencias de anemia gestacional regionales y distritales. Mediante el índice de Moran se identificaron conglomerados distritales con alta prevalencia de anemia gestacional. Resultados. Se recolectó información de 311 521 gestantes, distribuidas en 1638 distritos del Perú. La prevalencia nacional de anemia fue de 24,2% (IC 95%: 24,0-24,3) y 30,5% en el área rural vs. 22,0% en el área urbana. Las regiones de Huancavelica (45,5%; IC 95%: 44,2-46,7), Puno (42,8%; IC 95%: 41,9-43,7), Pasco (38,5%; IC 95%: 36,9-40,0), Cusco (36,0%; IC 95%: 35,3-36,8) y Apurímac (32,0%; IC 95%: 30,8-33,1) tuvieron las mayores prevalencias de anemia. El índice local de Moran identificó 202 distritos (12,3%) (44 urbanos y 158 rurales) de alta prioridad (alto-alto o hot spots) situados en Ancash, Apurímac, Arequipa, Ayacucho, Cajamarca, Cusco, Huancavelica, Huánuco, Junín, La Libertad, Lima, Pasco y Puno, que muestran conglomerados distritales con altas prevalencias. Conclusiones. La anemia gestacional en Perú concentra sus mayores prevalencias en las áreas rural y sur de la sierra. Los conglomerados distritales con altas prevalencias de anemia gestacional coinciden con las zonas de alta prevalencia regional

Desafíos y prioridades : política de adolescentes y jóvenes en el Perú

Esta publicación sobre los desafíos y prioridades de la política de adolescentes y jóvenes en el Perú aspira a aportar datos cruciales sobre la situación en cinco ejes priorizados: culminación escolar, acceso a empleo, violencia, salud mental y embarazo adolescente

Spatial analysis of childhood obesity and overweight in Peru, 2014

Objectives. To estimate regional prevalence and identify the spatial patterns of the degree of overweight and obesity by districts in under five years children in Peru during 2014. Materials and methods. Analysis of the information reported by the Information System Nutritional Status (SIEN) of the number of cases of overweight and obesity in children under five years recorded during 2014. Regional prevalence for overweight and obesity, and their respective confidence intervals to 95% were calculated. Moran index was used to determine patterns of grouping districts with high prevalence of overweight and/or obesity. Results. Data from 1834 districts and 2,318,980 children under five years were analyzed. 158,738 cases (6.84%; CI 95%: 6.81 to 6.87) were overweight, while 56,125 (2.42%; CI 95%: 2.40 to 2.44) obesity. The highest prevalence of overweight were identified in the regions of Tacna (13.9%), Moquegua (11.8%), Callao (10.4%), Lima (10.2%) and Ica (9.3%), and in the same regions for obesity with 5.3%; 4.3%; 4.0%; 4.0% and 3.8% respectively. The spatial analysis found grouping districts of high prevalence in 10% of all districts for both overweight and obesity, identifying 199 districts for overweight (126 urban and 73 rural), and 184 for obesity (136 urban and 48 rural). Conclusions. The highest prevalence of overweight and obesity were identified in the Peruvian coast regions. Moreover, these regions are predominantly exhibited a spatial clustering of districts with high prevalence of overweight and obesity

Food Environments around American Indian Reservations: A Mixed Methods Study

Objectives: To describe the food environments experienced by American Indians living on tribal lands in California. Methods: Geocoded statewide food business data were used to define and categorize existing food vendors into healthy, unhealthy, and intermediate composite categories. Distance to and density of each of the composite food vendor categories for tribal lands and nontribal lands were compared using multivariate linear regression. Quantitative results were concurrently triangulated with qualitative data from in-depth interviews with tribal members (n = 24). Results: After adjusting for census tract-level urbanicity and per capita income, results indicate there were significantly fewer healthy food outlets per square mile for tribal areas compared to non-tribal areas. Density of unhealthy outlets was not significantly different for tribal versus non-tribal areas. Tribal members perceived their food environment negatively and reported barriers to the acquisition of healthy food. Conclusions: Urbanicity and per capita income do not completely account for disparities in food environments among American Indians tribal lands compared to nontribal lands. This disparity in access to healthy food may present a barrier to acting on the intention to consume healthy food

Multivariate Linear Regression results^a for density of and distance to food outlets for tribal areas^b compared to non-tribal areas^c.

<p>Multivariate Linear Regression results<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0161132#t004fn002" target="_blank">^a</a> for density of and distance to food outlets for tribal areas<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0161132#t004fn003" target="_blank">^b</a> compared to non-tribal areas<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0161132#t004fn004" target="_blank">^c</a>.</p

Socio-Economic and Demographic Characteristics for All Census Tracts, Census Tracts with and without Tribal Land, and Tribal Census Tracts.

<p>Socio-Economic and Demographic Characteristics for All Census Tracts, Census Tracts with and without Tribal Land, and Tribal Census Tracts.</p

Demographic Characteristics of Participants Providing Qualitative Interviews.

<p>Demographic Characteristics of Participants Providing Qualitative Interviews.</p

Bivariate Results^a for Density of and Distance to Food Outlets between Tribal Areas^b and Non-Tribal Areas^c.

<p>Bivariate Results<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0161132#t003fn001" target="_blank">^a</a> for Density of and Distance to Food Outlets between Tribal Areas<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0161132#t003fn002" target="_blank">^b</a> and Non-Tribal Areas<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0161132#t003fn003" target="_blank">^c</a>.</p

Caregiver and Youth Mental Health during COVID-19: Risk and Resilience Factors in a Large National Sample in Peru

The present study examined the prevalence and correlates of psychosocial impairment in a large, national sample of Peruvian children and adolescents (ages 5.0&ndash;17.9) during the COVID-19 pandemic in late 2020. A sample of 8263 online questionnaires were completed by caregivers in Peru between 23 October&ndash;26 November 2020. In addition to sociodemographic and pandemic-related factors, the survey administered the Peruvian Spanish version of the Pediatric Symptom Checklist (PSC-17) to assess child psychosocial risk. The Patient Health Questionnaire (PHQ-9), Kessler-6 (K-6), and Brief Resilience Scale (BRS-6) assessed caregiver depression, psychological distress, and resilience, respectively. In this case, 33% of the children were at overall risk on the PSC-17. In adjusted models, caregiver distress, depression, and low resilience, as well as having a family member with a health risk factor were the strongest predictors of child psychosocial risk, accounting for nearly 1.2 to 2.1 times the likelihood of risk individually and 2.4 to 3.4 times the likelihood of risk when summed. Due to the opt-in sampling method, the obtained sample was likely skewed toward more advantaged families, suggesting that the study&rsquo;s high prevalence of PSC-17 positivity might have been even higher in a more economically representative sample. Given the prevalence of psychosocial problems in Peruvian youth during COVID-19, preventive interventions, with a special focus on family-level approaches that involve and support parents as well as children, are clearly warranted