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      Dietary intake of fish and n-3 polyunsaturated fatty acids and risk of postpartum depression: a nationwide longitudinal study – the Japan Environment and Children's Study (JECS)

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          Abstract

          Background

          Pregnant women require increased levels of n-3 polyunsaturated fatty acids (PUFAs) due to the demands of the growing fetus. Although some evidence indicates that maternal intake of fish and n-3 PUFAs is associated with reduced risk of postpartum depression, the results are inconsistent.

          Methods

          We investigated whether dietary consumption of fish and/or n-3 PUFAs during pregnancy is associated with a reduced risk of maternal postpartum depression at 6 months after delivery and of serious mental illness at 1 year in a Japanese population. After exclusion and multiple imputation from a dataset comprising 103 062 pregnancies obtained in the Japan Environment and Children's Study, we evaluated 84 181 and 81 924 women at 6 months and 1 year after delivery, respectively.

          Results

          Multivariable logistic regression showed a reduced risk of postpartum depression at 6 months in the second to fifth quintiles v. the lowest quintile for fish and n-3 PUFA intake, with trend tests also revealing a significant linear association. At 1 year after delivery, fish intake was associated with a reduced risk of serious mental illness in the second to fifth quintiles v. the lowest quintile for fish and in the third to fifth quintiles v. the lowest quintile for n-3 PUFA intake, with trend tests also revealing a significant linear association.

          Conclusions

          Women with higher fish and/or n-3 PUFA intake showed reduced risk of postpartum depression at 6 months after delivery and of serious mental illness at 1 year after delivery.

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          Most cited references46

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          Detection of postnatal depression. Development of the 10-item Edinburgh Postnatal Depression Scale

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            Adjustment for total energy intake in epidemiologic studies

            In epidemiologic studies, total energy intake is often related to disease risk because of associations between physical activity or body size and the probability of disease. In theory, differences in disease incidence may also be related to metabolic efficiency and therefore to total energy intake. Because intakes of most specific nutrients, particularly macronutrients, are correlated with total energy intake, they may be noncausally associated with disease as a result of confounding by total energy intake. In addition, extraneous variation in nutrient intake resulting from variation in total energy intake that is unrelated to disease risk may weaken associations. Furthermore, individuals or populations must alter their intake of specific nutrients primarily by altering the composition of their diets rather than by changing their total energy intake, unless physical activity or body weight are changed substantially. Thus, adjustment for total energy intake is usually appropriate in epidemiologic studies to control for confounding, reduce extraneous variation, and predict the effect of dietary interventions. Failure to account for total energy intake can obscure associations between nutrient intakes and disease risk or even reverse the direction of association. Several disease-risk models and formulations of these models are available to account for energy intake in epidemiologic analyses, including adjustment of nutrient intakes for total energy intake by regression analysis and addition of total energy to a model with the nutrient density (nutrient divided by energy).
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              Multiple imputation of discrete and continuous data by fully conditional specification.

              The goal of multiple imputation is to provide valid inferences for statistical estimates from incomplete data. To achieve that goal, imputed values should preserve the structure in the data, as well as the uncertainty about this structure, and include any knowledge about the process that generated the missing data. Two approaches for imputing multivariate data exist: joint modeling (JM) and fully conditional specification (FCS). JM is based on parametric statistical theory, and leads to imputation procedures whose statistical properties are known. JM is theoretically sound, but the joint model may lack flexibility needed to represent typical data features, potentially leading to bias. FCS is a semi-parametric and flexible alternative that specifies the multivariate model by a series of conditional models, one for each incomplete variable. FCS provides tremendous flexibility and is easy to apply, but its statistical properties are difficult to establish. Simulation work shows that FCS behaves very well in the cases studied. The present paper reviews and compares the approaches. JM and FCS were applied to pubertal development data of 3801 Dutch girls that had missing data on menarche (two categories), breast development (five categories) and pubic hair development (six stages). Imputations for these data were created under two models: a multivariate normal model with rounding and a conditionally specified discrete model. The JM approach introduced biases in the reference curves, whereas FCS did not. The paper concludes that FCS is a useful and easily applied flexible alternative to JM when no convenient and realistic joint distribution can be specified.
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                Author and article information

                Journal
                Psychol Med
                Psychol Med
                PSM
                Psychological Medicine
                Cambridge University Press (Cambridge, UK )
                0033-2917
                1469-8978
                October 2020
                19 September 2019
                : 50
                : 14
                : 2416-2424
                Affiliations
                [1 ]Department of Public Health, Faculty of Medicine, University of Toyama , Toyama, Japan
                [2 ]Toyama Regional Center for JECS, University of Toyama , Toyama, Japan
                [3 ]Department of Pediatrics, Faculty of Medicine, University of Toyama , Toyama, Japan
                [4 ]Department of Obstetrics and Gynecology, Faculty of Medicine, University of Toyama , Toyama, Japan
                Author notes
                Author for correspondence: Kei Hamazaki, E-mail: keihama@ 123456med.u-toyama.ac.jp
                [*]

                Study Group members are listed in the Appendix.

                Article
                S0033291719002587
                10.1017/S0033291719002587
                7610183
                31535610
                2c319efe-d748-4f4f-8def-08e274aa8f16
                © The Author(s) 2019

                This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 03 April 2019
                : 16 August 2019
                : 30 August 2019
                Page count
                Figures: 1, Tables: 2, References: 47, Pages: 9
                Categories
                Original Articles

                Clinical Psychology & Psychiatry
                fish intake,n-3 polyunsaturated fatty acids,postpartum depression,pregnancy,serious mental illness

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