A propósito del artículo: Esquema de ayuno intermitente y reducción de medidas antropométricas, perfil lipídico, presión arterial y riesgo cardiovascular: About the article: Intermittent fasting scheme and reduction of anthropometric measurements, lipid profile, blood pressure and cardiovascular risk

Dear Editor:We have read with great interest the article "Intermittent fasting scheme and reduction of anthropometric measurements, lipid profile, blood pressure and cardiovascular risk" published by Dr Javier Wong-Gonzáles et al, in number 1, volume 22 of your magazine; where the purpose of the research focuses on the assessment of the efficacy of intermittent fasting as a strategy for the modification of anthropometric parameters and cardiovascular risk variables; We would like to contribute the importance of defining the times of the day in which the periods of food intake and abstinence are framed during intermittent fasting, since the induced metabolic effects are highly dependent on circadian fluctuations.Estimado señor editor:Hemos leído con gran interés el artículo “Esquema de ayuno intermitente y reducción de medidas antropométricas, perfil lipídico, presión arterial y riesgo cardiovascular” publicado por el Dr Javier Wong-Gonzáles et al, en el número 1, volumen 22 de su revista; donde el propósito de la investigación se centra en la valoración de la eficacia del ayuno intermitente como estrategia para la modificación de parámetros antropométricos y variables de riesgo cardiovascular; quisiéramos aportar la importancia de definir los momentos del día en los que se enmarcan los periodos de ingesta y abstinencia de alimentos durante el ayuno intermitente, puesto que los efectos metabólicos inducidos son altamente dependientes de las fluctuaciones circadianas.&nbsp

Factors Associated with Normal-Weight Abdominal Obesity Phenotype in a Representative Sample of the Peruvian Population: A 4-Year Pooled Cross-Sectional Study

To examine factors associated with abdominal obesity among normal-weight individuals from the Demographic and Health Survey of Peru (2018–2021). Cross-sectional analytical study. The outcome variable was abdominal obesity defined according to JIS criteria. Crude (cPR) and adjusted prevalence ratios (aPR) were estimated for the association between sociodemographic and health-related variables and abdominal obesity using the GLM Poisson distribution with robust variance estimates. A total of 32,109 subjects were included. The prevalence of abdominal obesity was 26.7%. The multivariate analysis showed a statistically significant association between abdominal obesity and female sex (aPR: 11.16; 95% CI 10.43–11.94); categorized age 35 to 59 (aPR: 1.71; 95% CI 1.65–1.78); 60 to 69 (aPR: 1.91; 95% CI 1.81–2.02); and 70 or older(aPR: 1.99; 95% CI 1.87–2.10); survey year 2019 (aPR: 1.22; 95% CI 1.15–1.28); 2020 (aPR: 1.17; 95% CI 1.11–1.24); and 2021 (aPR: 1.12; 95% CI 1.06–1.18); living in Andean region (aPR: 0.91; 95% CI 0.86–0.95); wealth index poor (aPR: 1.26; 95% CI 1.18–1.35); middle (aPR: 1.17; 95% CI 1.08–1.26); rich (aPR: 1.26; 95% CI 1.17–1.36); and richest (aPR: 1.25; 95% CI 1.16–1.36); depressive symptoms (aPR: 0.95; 95% CI 0.92–0.98); history of hypertension (aPR: 1.08; 95% CI 1.03–1.13), type 2 diabetes (aPR: 1.13; 95% CI 1.07–1.20); and fruit intake 3 or more servings/day (aPR: 0.92; 95% CI 0.89–0.96). Female sex, older ages, and low and high income levels increased the prevalence ratio for abdominal obesity, while depressive symptoms

Factores asociados al fenotipo delgado metabólicamente obeso en pobladores peruanos

Introducción: Los pacientes con el fenotipo delgado metabólicamente obeso (DMO) pueden presentar el mismo riesgo que los obesos clásicos para desarrollar enfermedades crónicas a largo plazo. No obstante, la prevalencia y los factores que se encuentran asociados este varía de acuerdo con la población estudiada. Objetivo: determinar la prevalencia y los factores se encuentran asociados al fenotipo DMO en el Perú. Métodos: Estudio analítico de corte transversal. Análisis secundario de la base de datos del estudio PERU MIGRANT. Los factores asociados que se consideraron fueron: edad (30-44 años, de 45-59 años, y 60 a más años), sexo, estado socioeconómico, nivel de educación, migración, tabaquismo, consumo de alcohol y nivel actividad física. Resultados: La prevalencia del fenotipo DMO fue de 32,23% (IC95% 27,61-37,10). En el análisis multivariable, el sexo masculino mostró 39% menor probabilidad de presentar el fenotipo DMO (PRa: 0,610; IC95% 0,428-0,869; p=0,006), en comparación con el sexo femenino. Mientras que, pertenecer a los grupos de edad entre 45-59 años y de 60 años a más presentó 110,5% (PRa: 2,105; IC95% 1,484-2,988; p<0,001) y 97,6% (PRa: 1,976; IC95% 1,270-3,075; p=0,003), respectivamente, mayor probabilidad de presentar DMO, en comparación con el grupo de 29-44 años. Conclusiones: El pertenecer al sexo femenino y a los grupos de edad de 45 a 59 y 60 años a más, aumentaron la probabilidad de presentar el fenotipo DMO. Se recomienda la realización de futuros estudios con prospectivos y con un tamaño de muestra mayor para confirmar dichos hallazgos, así como la inclusión de nuevas variables

Factores asociados al cribado de Diabetes Mellitus en población Peruana ¿problema para la salud pública?

Highlights: El ser varón es un factor relevante asociado al no tamizaje de diabetes mellitus tipo 2 (DM2). Un mayor nivel de educación y socioeconómico se asocian positivamente con la posibilidad de realizarse tamizaje para DM2 El fortalecimiento de los servicios de atención primaria es crucial en la prevención primaria de DM2 a través del tamizaje. Introducción: La Diabetes Mellitus tipo 2 es una enfermedad que representa un reto para la salud pública por su tendencia al crecimiento e impacto sobre todo en países en desarrollo. Objetivo: determinar los factores asociados a la no realización del cribado de diabetes mellitus tipo 2 según la encuesta demográfica y de salud familiar del año 2020 (ENDES-2020). Materiales y métodos: Estudio analítico transversal secundario de la ENDES-2020. Resultados: Las variables que mostraron asociación estadísticamente significativa para cribado de DM2 fueron: sexo masculino (PR=1,06, IC95% 1,02–1,10; p<0,001), edad entre 30 a 59 años (0,92; IC95% 0,89–0,95; p<0,001) y 60 años a más (PR=0,72; IC95% 0,65–0,79; p<0,001), educación primaria (PR=0,94, IC 95% 0,92 - 0,99; p<0,020), secundaria (PR=0,93; IC 95% 0,88–0,97; p=0,008) y superior (PR=0,86, IC 95% 0,85–0,94; p<0,001), ser pobre (PR=0,96, IC95% 0,92–0,99; p=0,016), medio (PR=0,93; IC95% 0,88 – 0,96; p=0,001), rico (PR=0,89; IC95% 0,84 – 0,94; p<0,001), muy rico (PR=0,81; IC95% 0,75–0,86; p<0,001), e hipertensión (PR=0,91; IC 95% 0,867–0,969; p=0,002). Discusión: El sexo masculino fue el único factor asociado a la no realización del cribado de diabetes mellitus tipo 2, mientras que, pertenecer a un grupo de edad mayor, tener hipertensión arterial, mayor nivel educativo y socioeconómico aumentó la posibilidad de realizarlo. Conclusión: Es imprescindible reforzar las estrategias de cribado en el primer nivel de atención, mediante la implementación de medidas de prevención. Como citar este artículo: Fiorella Trujillo Minaya, Vera-Ponce Victor Juan, Torres-Malca Jenny Raquel, Zuzunaga-Montoya Fiorella E, Guerra Valencia Jamee, De la Cruz-Vargas Jhony A, Cruz Ausejo Liliana. Factores asociados al cribado de diabetes mellitus en población peruana ¿problema para la salud pública?. Revista Cuidarte. 2023;14(1):e2792. http://dx.doi.org/10.15649/cuidarte.279

Metabolically Obese Normal-Weight Phenotype as a Risk Factor for High Blood Pressure: A Five-Year Cohort

"Background: The metabolically obese normal-weight (MONW) phenotype has been considered a risk factor for different chronic diseases, but its role in high blood pressure (HBP) is still unclear. The aim of the study is to determine if the MONW phenotype constitutes a risk factor for hypertension in Peruvian adults belonging to a 5-year cohort. Methods: This is a retrospective cohort study. A secondary analysis from the database of the PERU MIGRANT study was carried out from the MONW and non-MONW cohorts; after a 5-year follow-up, the appearance of HBP was evaluated in the subjects of both cohorts. To assess the strength and magnitude of the association, a Poisson regression model (crude and adjusted) with robust variance was used. The measure of association was the relative risk (RR). Results: The incidence of HBP was 11.30%. In the multivariable analysis, subjects with the MONW phenotype had a 2.879-fold risk of presenting HBP in 5 years compared with those who were not MONW at the beginning of the study; this was adjusted for categorized age, sex, group, and state of smoker and alcohol drinker (RR: 2.055; 95% confidence interval (CI): 1.118 - 3.777; P = 0.020). Conclusions: The presence of the MONW phenotype doubled the incidence of HBP, even after adjusting for other covariates. However, studies in this field should continue. If these findings are confirmed, it should be considered that presenting an adequate weight for height should not be interpreted as a condition free of metabolic alterations, so screening for hypertension should be carried out regardless of w

The Fruit Intake–Adiposity Paradox: Findings from a Peruvian Cross-Sectional Study

"Due to the increase in obesity worldwide, international organizations have promoted the adoption of a healthy lifestyle, as part of which fruit consumption stands out. However, there are controversies regarding the role of fruit consumption in mitigating this disease. The objective of the present study was to analyze the association between fruit intake and body mass index (BMI) and waist circumference (WC) in a representative sample of Peruvians. This is an analytical cross-sectional study. Secondary data analysis was conducted using information from the Demographic and Health Survey of Peru (2019–2021). The outcome variables were BMI and WC. The exploratory variable was fruit intake, which was expressed in three different presentations: portion, salad, and juice. A generalized linear model of the Gaussian family and identity link function were performed to obtain the crude and adjusted beta coefficients. A total of 98,741 subjects were included in the study. Females comprised 54.4% of the sample. In the multivariate analysis, for each serving of fruit intake, the BMI decreased by 0.15 kg/m2 (β = −0.15; 95% CI −0.24 to −0.07), while the WC was reduced by 0.40 cm (β = −0.40; 95% CI −0.52 to −0.27). A negative association between fruit salad intake and WC was found (β = −0.28; 95% CI −0.56 to −0.01). No statistically significant association between fruit salad intake and BMI was found. In the case of fruit juice, for each glass of juice consumed, the BMI increased by 0.27 kg/m2 (β = 0.27; 95% CI 0.14 to 0.40), while the WC increased by 0.40 cm (β = 0.40; 95% CI 0.20 to 0.60). Fruit intake per serving is negatively related to general body adiposity and central fat distribution, while fruit salad intake is negatively related to central distribution adiposity. However, the consumption of fruit in the form of juices is positively associated with a significant increase in BMI and WC.

The Fruit Intake–Adiposity Paradox: Findings from a Peruvian Cross-Sectional Study

Due to the increase in obesity worldwide, international organizations have promoted the adoption of a healthy lifestyle, as part of which fruit consumption stands out. However, there are controversies regarding the role of fruit consumption in mitigating this disease. The objective of the present study was to analyze the association between fruit intake and body mass index (BMI) and waist circumference (WC) in a representative sample of Peruvians. This is an analytical cross-sectional study. Secondary data analysis was conducted using information from the Demographic and Health Survey of Peru (2019–2021). The outcome variables were BMI and WC. The exploratory variable was fruit intake, which was expressed in three different presentations: portion, salad, and juice. A generalized linear model of the Gaussian family and identity link function were performed to obtain the crude and adjusted beta coefficients. A total of 98,741 subjects were included in the study. Females comprised 54.4% of the sample. In the multivariate analysis, for each serving of fruit intake, the BMI decreased by 0.15 kg/m2 (β = −0.15; 95% CI −0.24 to −0.07), while the WC was reduced by 0.40 cm (β = −0.40; 95% CI −0.52 to −0.27). A negative association between fruit salad intake and WC was found (β = −0.28; 95% CI −0.56 to −0.01). No statistically significant association between fruit salad intake and BMI was found. In the case of fruit juice, for each glass of juice consumed, the BMI increased by 0.27 kg/m2 (β = 0.27; 95% CI 0.14 to 0.40), while the WC increased by 0.40 cm (β = 0.40; 95% CI 0.20 to 0.60). Fruit intake per serving is negatively related to general body adiposity and central fat distribution, while fruit salad intake is negatively related to central distribution adiposity. However, the consumption of fruit in the form of juices is positively associated with a significant increase in BMI and WC

The Fruit Intake–Adiposity Paradox: Findings from a Peruvian Cross-Sectional Study

"Due to the increase in obesity worldwide, international organizations have promoted the adoption of a healthy lifestyle, as part of which fruit consumption stands out. However, there are controversies regarding the role of fruit consumption in mitigating this disease. The objective of the present study was to analyze the association between fruit intake and body mass index (BMI) and waist circumference (WC) in a representative sample of Peruvians. This is an analytical cross-sectional study. Secondary data analysis was conducted using information from the Demographic and Health Survey of Peru (2019–2021). The outcome variables were BMI and WC. The exploratory variable was fruit intake, which was expressed in three different presentations: portion, salad, and juice. A generalized linear model of the Gaussian family and identity link function were performed to obtain the crude and adjusted beta coefficients. A total of 98,741 subjects were included in the study. Females comprised 54.4% of the sample. In the multivariate analysis, for each serving of fruit intake, the BMI decreased by 0.15 kg/m2 (β = −0.15; 95% CI −0.24 to −0.07), while the WC was reduced by 0.40 cm (β = −0.40; 95% CI −0.52 to −0.27). A negative association between fruit salad intake and WC was found (β = −0.28; 95% CI −0.56 to −0.01). No statistically significant association between fruit salad intake and BMI was found. In the case of fruit juice, for each glass of juice consumed, the BMI increased by 0.27 kg/m2 (β = 0.27; 95% CI 0.14 to 0.40), while the WC increased by 0.40 cm (β = 0.40; 95% CI 0.20 to 0.60). Fruit intake per serving is negatively related to general body adiposity and central fat distribution, while fruit salad intake is negatively related to central distribution adiposity. However, the consumption of fruit in the form of juices is positively associated with a significant increase in BMI and WC.

Rendimiento diagnóstico de once indicadores para resistencia a la insulina en una muestra de pobladores peruanos

Introducción: La resistencia a la insulina (RI) es una de las principales causas del desarrollo de patologías crónicas. Es indispensable su detección temprana, por ello es importante estudiar métodos más asequibles y menos costosos como los biomarcadores. Objetivo: Determinar la precisión diagnóstica de once biomarcadores para RI en una muestra de pobladores peruanos. Metodología: Estudio de pruebas diagnósticas. Análisis de base de datos secundario del estudio PERU MIGRANT. Para medir RI se utilizó como referencia la evaluación del modelo homeostático (HOMA-IR) ? 2,8. Los biomarcadores se basaron en la ratio de lípidos, los indicadores de lípido visceral, los indicadores con triglicéridos y glucosa (TyG), y los indicadores con cintura abdominal. Para la precisión se utilizó el análisis de la curva de características operativas del receptor y el área bajo la curva (AUC) con sus respectivos intervalos de confianza al 95% (IC95%). Resultados: Se estudió a 938 participantes. La prevalencia de RI fue del 9,91%. En relación con el análisis ROC, el índice TyG – índice de masa corporal (TyG – IMC) tuvo el mayor AUC, tanto en hombres: AUC=0,85 (0,81 - 0,90), corte=241,55; sens=92,5 (79,6 - 98,4) y esp=78,3 (73,9 - 82,2); como en mujeres: AUC=0,81 (0,76 - 0,85), corte=258,77; sens=79,2 (70,3 - 86,5) y esp= 82,1 (78,0 - 85,8). Discusión: Según los datos analizados, el índice TyG-IMC es el mejor indicador para medir RI. Es un índice simple que se puede tomar de manera rutinaria en la práctica clínica diaria. Es conveniente añadir futuros estudios prospectivos que confirmen su capacidad predictiva.

Factors associated with symptoms of depression among people with obesity: analysis of a 3-year-Peruvian national survey

Introduction: Obesity and depression contribute to the global burden of economic cost, morbidity, and mortality. Nevertheless, not all people with obesity develop depression. Objective: To determine the factors associated with depressive symptoms among people aged 15 or older with obesity from the National Demographic and Family Health Survey (ENDES in Spanish 2019–2021). Methods: Cross-sectional analytical study. The outcome of interest was the presence of depressive symptoms, assessed using the Patient Health Questionnaire-9 (PHQ-9). Crude (cPR) and adjusted (aPR) prevalence ratios were estimated using GLM Poisson distribution with robust variance estimates. Results: The prevalence of depression symptoms was 6.97%. In the multivariate analysis, a statistically significant association was found between depressive symptoms and female sex (PRa: 2.59; 95% CI 1.95–3.43); mountain region (PRa: 1.51; 95% CI 1.18–1.92); wealth index poor (PRa: 1.37; 95% CI 1.05–1.79, medium (PRa: 1.49; 95% CI 1.11–2.02), and rich (PRa: 1.65; 95% CI 1.21–2.26); daily tobacco use (PRa: 2.05, 95% CI 1.09–3.87); physical disability (PRa: 1.96, 95% CI 1.07–3.57); and a history of arterial hypertension (PRa: 2.05; 95% CI 1.63–2.55). Conclusion: There are several sociodemographic factors (such as being female and living in the Andean region) and individual factors (daily use of tobacco and history of hypertension) associated with depressive symptoms in Peruvian inhabitants aged 15 or older with obesity. In this study, the COVID-19 pandemic was associated with an increase in depressive symptoms.Campus Lima Nort