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The association between early reproductive events and health status in later life has always been of interest across disciplines. The purpose of this study was to investigate whether there was an association between the number of children born in the early years of elderly women and their depression in later life based on a sample of older women aged 65 years and above with at least one child in rural China. Data from the Chinese Longitudinal Healthy Longevity Survey in 2018, this study used the ordinary least square method to conduct empirical research. This study has found a significant correlation between an increase in the number of children and depression in older rural women. When considering the sex of the child, the number of daughters had a greater and more significant impact on depression. Number of children may exacerbate depression of older women through declining self-rated health and reduced social activity, while increased inter-generational support alleviated depression. The association between number of children born and depression also existed in urban older women, though not significant. Therefore, it is suggested to accelerate the improvement of supporting policies related to childbirth, developing a healthy and scientific fertility culture, and improving rural maternal and child health services. Women should be assisted in balancing their roles in the family and in society, and in particular in sharing the burden of caring for children. Targeted efforts to increase old-age protection for older people.
Major depressive disorder (MDD) is a clinically and biologically heterogeneous syndrome. Identifying discrete subtypes of illness with distinguishing neurobiological substrates and clinical features is a promising strategy for guiding personalised therapeutics.
This study aimed to identify depression subtypes with correlated patterns of functional network connectivity and clinical symptoms by clustering patients according to a weighted linear combination of both features in a relatively large, medication-naïve depression sample.
We recruited 115 medication-naïve adults with MDD and 129 matched healthy controls, and evaluated all participants with magnetic resonance imaging. We used regularised canonical correlation analysis to identify component mapping relationships between functional network connectivity and symptom profiles, and K-means clustering was used to define distinct subtypes of patients.
Two subtypes of MDD were identified: insomnia-dominated subtype 1 and anhedonia-dominated subtype 2. Subtype 1 was characterised by abnormal hyperconnectivity within the ventral attention network and sleep maintenance insomnia. Subtype 2 was characterised by abnormal hypoconnectivity in the subcortical and dorsal attention networks, and prominent anhedonia symptoms.
Our study identified two distinct subtypes of patients with specific neurobiological and clinical symptom profiles. These findings advance understanding of the biological and clinical heterogeneity of MDD, offering a pathway for defining categorical subtypes of illness via consideration of both biological and clinical features.
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