Prevalence and potential determinants of primary infertility in India: Evidence from Indian demographic health survey

Purkayastha, Naina; Sharma, Himani

doi:10.1016/j.cegh.2020.08.008

Cited by 35 publications

(30 citation statements)

References 13 publications

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“…Appropriate diagnosis is essential for proper treatment plan. 9 The histological examination of the endometrial biopsy is the most reliable parameter for evaluating the cause of infertility. 10,11 Present study has been designed with an objective to categorize and evaluate the histopathological features of endometrium in primary infertility.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of histopathology of endometrium in primary infertile women, a prospective five years observational study in Konaseema region of Andhra Pradesh

Annapurna¹,

Pattnaik²

2022

Int J Reprod Contracept Obstet Gynecol

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Background: Histopathology of endometrium is considered important investigation in case of infertility. The functional disturbance involved in infertility may result in morphological changes in endometrium. Endometrial histopathology is helpful in dating of endometrium so that hormonal status, ovulation and infertility.Methods: The material for this study consists of endometrial tissue obtained from patients. It was collected either by endometrial biopsy or curettage of uterus done in the minor OT department of obstetrics and gynaecology. The specimen was processed paraffin tissue processing and section of five micrometer was cut and stained with hematoxylin and eosin and ZN staining as per requirement.Results: Morphological and histopathological pattern of endometrium of patients with primary infertility, anovulatory (proliferative endometrium was present in 24 (30%) patients, simple hyperplasia was present in 16 (20%), deficient secretary phase was present in 26 (32.50%) patients, adequate secretary phase was present in 7 (8.75%) patients. Endometrial tuberculosis was diagnosed in 4 (5%) patients and in one patient neoplastic change was found. Arias Stella reaction was present in 1 (1.25%) patients.Conclusions: From present study we can conclude that the mean age of patients with primary infertility was 25.76±3.21 years and most of the patients were between 26 to 35 years of age. Regular menstrual cycle was present in 54 (67.5%) patients and 32.5% patients were presented with irregular cycle. The duration of infertility between 3 to 6 years was present in 34 (42.5%) patients. Secretory endometrium was present in 52.5% patients and was most common finding followed by proliferative endometrium. Endometrial tuberculosis was present in 2.5% patients.

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Section: Discussionmentioning

confidence: 99%

Evaluation of histopathology of endometrium in primary infertile women, a prospective five years observational study in Konaseema region of Andhra Pradesh

Annapurna¹,

Pattnaik²

2022

Int J Reprod Contracept Obstet Gynecol

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“…In contrast to our study the study by purkayesta and Abdullah shows urban women are more prone to experience infertility in some regions, which might be due to the differentials in environment and lifestyles. This result might come due to women who live in urban more vulnerable to pollutants and chemicals such as; polluted air from factories, vehicles and electric generators, in addition frequent use of detergents, cosmetic and pesticides [5,28]. The probable justification for increased primary infertility among rural women in our case probably due to low access to health services particularly gynecology and obstetrics specialty clinic were not find in near proximate rural women which can be a barrier for them to undergo regular screening and majority of rural women also believe this infertility was God/Allah punishment and likely to seek health institution.…”

Section: Discussionmentioning

confidence: 99%

“…Despite the fact that infertility affects both men and women fairly equally, Most of the time, women are blamed for it, considering it as a particular problem among females, particularly in developing countries [5]. Accordingly about 30% of infertility is due to female problems, 30% to male problems, and 30% to combined male/female problems, while in 10%, there is no recognizable cause [6].…”

Section: Introductionmentioning

confidence: 99%

Determinants of Primary Infertility Among Married Women Attending Obstetrics and Gynecology Speciality Centers at Adama Town, Oromia, Ethiopia

Abdisa¹,

Nemo²,

Kebede³

et al. 2022

AJLS

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Primary infertility is denoted for those women who have not been conceived previously. There are many biological causes of infertility such as ovulatory factors, utero-tubal peritoneal factor, semen migration factor and the male factor respectively. However, comprehensive epidemiological studies on the risk factors for primary infertility are not well documented in Ethiopia in particular current study area so far. Therefore the objective of this study was to assess determinants of primary infertility and outcome among married women attending obstetrics and gynecology specialty centers at Adama Town, Oromia, Ethiopia, 2020. Methods: Institution based unmatched case control study was conducted from November 16 to December 30, 2020. A sample of 178 married women with 1:2 ratio (59: cases and 119; controls) who attended obstetrics and gynecology clinic at Adama Town were included in the study by stratified random sampling technique. Data were collected using structured interview-administered questionnaire. Then data were entered in to Epi-Info version 7 then exported to SPSS version 24 for processing and analysis. To identify determinants of primary infertility, binary logistic regression model was used. In final fitted regression model a p-value of less than 0.05 was considered to declare significance of association. Result: A total of 178 participants (59 cases and 119 controls) were included in the study making a response rate of 100%. A significant determinants of primary infertility in this study were: Rural residence [AOR]: 27.95 (7.0, 111)], Husband Engaged in High Temperature Occupation [AOR]: 18.86 (3.8, 93.4)], eating diet enriched with saturated fat [AOR]: 10.97 (3, 40.1)], not undergoing adequate sex [AOR]: 0.120 (0.03, 0.57)], Menstruation flow greater than 3 days [AOR]: 4.4 (1.17, 16.6)], Ever use contraceptives [AOR]: 0.146 (0.05, 0.405)] and Chronic pelvic pain [AOR]: 18.7 (3.6, 94)]. More than one third of cases (33.9%) reported that perceived causes of infertility were punishment from God/Allah. Conclusion and recommendation: Being Rural residence, husband engaged in high temperature occupation, eating diet enriched with saturated fat, not undergoing adequate sex, Menstruation flow greater than 3 days, Ever used contraceptives and Chronic pelvic pain were identified as determinants of women's primary infertility. Therefore we recommend all married women to take treatment of any gynecological diseases like pelvic inflammatory disease.

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“…Infertility is a major clinical condition and a serious concern that affects 8-12% of couples, accounting for approximately 80 million couples worldwide [1]. The infertility rate has continuously grown across the globe, and even some West African communities are approaching an infertility rate of 50% [2].…”

Section: Introductionmentioning

confidence: 99%

Detecting Blastocyst Components by Artificial Intelligence for Human Embryological Analysis to Improve Success Rate of In Vitro Fertilization

Arsalan

Haider

Choi

et al. 2022

JPM

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Morphological attributes of human blastocyst components and their characteristics are highly correlated with the success rate of in vitro fertilization (IVF). Blastocyst component analysis aims to choose the most viable embryos to improve the success rate of IVF. The embryologist evaluates blastocyst viability by manual microscopic assessment of its components, such as zona pellucida (ZP), trophectoderm (TE), blastocoel (BL), and inner cell mass (ICM). With the success of deep learning in the medical diagnosis domain, semantic segmentation has the potential to detect crucial components of human blastocysts for computerized analysis. In this study, a sprint semantic segmentation network (SSS-Net) is proposed to accurately detect blastocyst components for embryological analysis. The proposed method is based on a fully convolutional semantic segmentation scheme that provides the pixel-wise classification of important blastocyst components that help to automatically check the morphologies of these elements. The proposed SSS-Net uses the sprint convolutional block (SCB), which uses asymmetric kernel convolutions in combination with depth-wise separable convolutions to reduce the overall cost of the network. SSS-Net is a shallow architecture with dense feature aggregation, which helps in better segmentation. The proposed SSS-Net consumes a smaller number of trainable parameters (4.04 million) compared to state-of-the-art methods. The SSS-Net was evaluated using a publicly available human blastocyst image dataset for component segmentation. The experimental results confirm that our proposal provides promising segmentation performance with a Jaccard Index of 82.88%, 77.40%, 88.39%, 84.94%, and 96.03% for ZP, TE, BL, ICM, and background, with residual connectivity, respectively. It is also provides a Jaccard Index of 84.51%, 78.15%, 88.68%, 84.50%, and 95.82% for ZP, TE, BL, ICM, and background, with dense connectivity, respectively. The proposed SSS-Net is providing a mean Jaccard Index (Mean JI) of 85.93% and 86.34% with residual and dense connectivity, respectively; this shows effective segmentation of blastocyst components for embryological analysis.

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Prevalence and potential determinants of primary infertility in India: Evidence from Indian demographic health survey

Cited by 35 publications

References 13 publications

Evaluation of histopathology of endometrium in primary infertile women, a prospective five years observational study in Konaseema region of Andhra Pradesh

Evaluation of histopathology of endometrium in primary infertile women, a prospective five years observational study in Konaseema region of Andhra Pradesh

Determinants of Primary Infertility Among Married Women Attending Obstetrics and Gynecology Speciality Centers at Adama Town, Oromia, Ethiopia

Detecting Blastocyst Components by Artificial Intelligence for Human Embryological Analysis to Improve Success Rate of In Vitro Fertilization

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