The private (commercial) sector in India can complement public sector for family planning services, but the roadmap to engage these two sectors remains a challenge. The total market approach (TMA) offers a strategy by understanding the comparative advantage of public, commercial, and nonprofit sectors. We estimated TMA indicators using data of four rounds of the National Family Health Surveys: 1992-93, 1998-99, 2005-06, and 2015-16. The contraceptive prevalence of modern methods in India did not increase in recent years, but the number of users increased, and so did the market size for the commercial sector. In rural areas, the current market size in 2015-16 (75 million) failed to reach its potential size in 1992-93 (84 million). In urban areas, the market of modern contraceptives is mostly composed of the users from higher wealth, and a high percentage of users obtain contraceptives from subsidized sources. The family planning market of northern part of Bihar and Uttar Pradesh and of Northeast India are in the "early" stage and need more demand generation; "matured" markets are mostly concentrated in and around big metros. Subsidization in urban areas should be offered to the targeted population who need family planning products and services at low cost.
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http://dx.doi.org/10.1002/hpm.2753 | DOI Listing |
Cancer Sci
January 2025
Department of colorectal surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China.
This study analyzed targeted sequencing data from 6530 tissue samples from patients with metastatic Chinese colorectal cancer (CRC) to identify low mutation frequency and subgroup-specific driver genes, using three algorithms for overall CRC as well as across different clinicopathological subgroups. We analyzed 425 cancer-related genes, identifying 101 potential driver genes, including 36 novel to CRC. Notably, some genes demonstrated subgroup specificity; for instance, ERBB4 was found as a male-specific driver gene and mutations of ERBB4 only influenced the prognosis of male patients with CRC.
View Article and Find Full Text PDFJ Clin Med
December 2024
Department of Internal Medicine and Rheumatology, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania.
This paper explores the essential role of pre-pregnancy counselling for women with rheumatoid arthritis (RA), focusing on minimising risks and optimising pregnancy outcomes. RA, a prevalent inflammatory arthritis with onset during childbearing years, necessitates targeted preconception counselling to manage disease activity and comorbidities effectively. The counselling ensures medication compatibility and planning around disease flares, and it involves a multidisciplinary team comprising rheumatologists, obstetricians, and other specialists to develop individualised care plans.
View Article and Find Full Text PDFCancers (Basel)
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Department of Next Generation Information Center, Kangwon National University Hospital, Chuncheon 24289, Republic of Korea.
Gastric cancer is a leading cause of cancer-related mortality, particularly in East Asia, with a notable burden in Republic of Korea. This study aimed to construct and develop machine learning models for the prediction of gastric cancer mortality and the identification of risk factors. All data were acquired from the Korean Clinical Data Utilization for Research Excellence by multiple medical centers in South Korea.
View Article and Find Full Text PDFBMC Palliat Care
January 2025
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Background: Singapore has an ageing population. End-of-life care and advance care planning are becoming increasingly important. To assess advance care planning engagement, valid tools are required.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Orthopaedic Surgery and Traumatology, Bern University Hospital, Inselspital, University of Bern, Bern, Switzerland.
Scapular morphological attributes show promise as prognostic indicators of retear following rotator cuff repair. Current evaluation techniques using single-slice magnetic-resonance imaging (MRI) are, however, prone to error, while more accurate computed tomography (CT)-based three-dimensional techniques, are limited by cost and radiation exposure. In this study we propose deep learning-based methods that enable automatic scapular morphological analysis from diagnostic MRI despite the anisotropic resolution and reduced field of view, compared to CT.
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