Nutritional Influences in Industrial Societies

Sinclair, John C.; Saigal, Saroj

doi:10.1001/archpedi.1975.02120420005002

Cited by 4 publications

(3 citation statements)

References 22 publications

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“…Our results are consistent with those obtained by other authors (Bergner & Susser, 1970;Jurado-García, 1970;Habicht et al, 1973;Sever et al, 1975;Sinclair & Saigal, 1975;Fedrick & Adelstein, 1978;Galbraith et al, 1979;Beal, 1981;Pitkin, 1981;van den Berg, 1981;Arias & Tomich, 1982;Benício et al, 1985;Casanueva, 1988;Elorza, 1988;Victora et al, 1989;Buyse, 1990;Ganzer, 1991;Cabrales-…”

Section: Discussionsupporting

confidence: 93%

Specific weights of nineteen explanatory variables in low birth weight in the Mayan Zone of the Mexican state of Quintana Roo according to the Multiple Logistic Regression Model. Analytical observational epidemiological study of cases and controls

2021

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Low birth weight is an indicator that allows predicting the probability of survival of a child. In fact, there is an exponential relationship between weight deficit, gestational age, and perinatal mortality. In addition, it is important to indicate that a percentage of term children (37 ≤ weeks of gestation ≤ 41) who have low birth weight present with various sequelae of variable severity –especially in the neurological sphere– and hence the importance of predicting the presentation of low birth weight. Multiple Logistic Regression is one of the most expressive and versatile statistical instruments available for data analysis in both clinical and epidemiology. Its origin dates to the sixties with the transcendent work of Cornfield, Gordon & Smith on the risk of suffering from coronary heart disease and, in the way we know it today, with the contribution of Walter & Duncan in which addresses the issue of estimating the probability of occurrence of a certain event based on several variables. Its use has been universalized and expanded since the early eighties, due to the computer facilities available since then. Quantitative approach. The study design corresponds to that of an analytical observational epidemiological study of cases and controls with directionality response variable→explanatory variables and with prospective temporality. One thousand eight hundred fifteen newborns were studied [178 (9.81%) cases and 1,637 (90.19%) controls], which corresponds to nine controls per case. All term newborns (37 ≤ weeks of gestation ≤ 41) with weights < 2,500 g and ≥ 2,500 g were defined, respectively, as a case and as a control. The values obtained from the β Exponents or Odds Ratios indicate the positive contribution (OR> 1) in ascending numerical order of the explanatory variables alcoholism (0.0018); low socioeconomic level (0.5694); initiation of prenatal care from or after the 20th week of gestation (0.6116); birth interval ≤ 24 months (0.7942); age at menarche ≤ 12 years (1.0792); “unmarried” marital status (1.0961); female gender of the product (1.1271); maternal weight < 50 kg (1.4700); history of abortion(s) (1.5407); number of deliveries = 1 (1.5524); number of prenatal visits ≤ 5 (1.5966); type of delivery or abdominal birth route (1.6169); smoking (2.2019); number of deliveries ≥ 5 (2.2714); maternal age ≤ 19 years (2.4827); maternal age ≥ 36 years (2.8070); pathological obstetric history (4.0735); pathological personal history (4.6475); and maternal height < 150 cm (5.5092).

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Section: Discussionsupporting

confidence: 93%

Specific weights of nineteen explanatory variables in low birth weight in the Mayan Zone of the Mexican state of Quintana Roo according to the Multiple Logistic Regression Model. Analytical observational epidemiological study of cases and controls

2021

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“…Vários fatores têm sido associados ao RNBP, entre eles, mães com menos de 20 anos ou mais de 35 anos, [13][14][15] desnutrição materna, 16 infecção do trato geniturinário durante a gestação, [17][18][19] outros filhos com baixo peso ao nascer ou gestações anteriores com resultados desfavoráveis, 9,20,21 intervalo interpartal menor do que 18 meses, parto prematuro, 15 consumo de cigarros durante a gravidez, 9,14,15,17,[21][22][23] …”

Section: Introdução Introduçãounclassified

Fatores de risco para o baixo peso ao nascer, com base em informações da Declaração de Nascido Vivo em Guaratinguetá, SP, no ano de 1998

Nascimento

Gotlieb²

2001

Inf. Epidemiol. Sus

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“…Se han estudiado numerosos factores de riesgo de BPN: madre de menos de 20 años (16-18) o de más de 40 (18), desnutrición materna (19)(20)(21)(22), infección durante la gestación (23)(24)(25), neonatos de bajo peso u otros resultados desfavorables en gestaciones anteriores (18,(26)(27)(28), intervalo intergenésico corto (18), parto prematuro (18) y consumo de tabaco durante la gestación (16-19, 26, 28-32).…”

Section: Introductionunclassified

Análisis multifactorial de los factores de riesgo de bajo peso al nacer en Salvador, Bahia

Solla¹,

Pereira²,

Medina³

et al. 1997

Rev Panam Salud Publica

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El presente estudio constituye un análisis multifactorial de los factores de riesgo de bajo peso al nacer en un grupo de recién nacidos en una zona urbana del Brasil. Se incluyeron en el estudio un total de 1 023 nacidos vivos, dados a luz en cuatro maternidades de Salvador, Bahia, entre julio de 1987 y febrero de 1988. Las fuentes de información fueron las historias clínicas y las entrevistas con las madres en la maternidad. El análisis se realizó mediante regresión logística. En el modelo final los factores de riesgo incluidos fueron los siguientes: edad materna menos de 21 años o más de 35; edad gestacional menos de 38 semanas; resultado desfavorable del embarazo anterior; intervalo intergenésico previo de 12 meses o menos; tabaquismo; e hipertensión. Se presentan los valores del riesgo atribuible poblacional para los factores de riesgo incluidos en el modelo final. Esos factores deben emplearse para detectar a las gestantes con alto riesgo de dar a luz un niño de bajo peso, a las que debe brindarse mayor atención prenatal.

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Nutritional Influences in Industrial Societies

Cited by 4 publications

References 22 publications

Specific weights of nineteen explanatory variables in low birth weight in the Mayan Zone of the Mexican state of Quintana Roo according to the Multiple Logistic Regression Model. Analytical observational epidemiological study of cases and controls

Specific weights of nineteen explanatory variables in low birth weight in the Mayan Zone of the Mexican state of Quintana Roo according to the Multiple Logistic Regression Model. Analytical observational epidemiological study of cases and controls

Fatores de risco para o baixo peso ao nascer, com base em informações da Declaração de Nascido Vivo em Guaratinguetá, SP, no ano de 1998

Análisis multifactorial de los factores de riesgo de bajo peso al nacer en Salvador, Bahia

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