107 extractive question-and-answer pairs built from 2 Data, published by iipsindia.ac.in. Every answer is a verbatim span of text the source prints, and each row carries the passage it sits in, its offset in that passage, the source quote, the page and the location in the document, so any row can be checked against the original. 75 of the 107 pairs (70.1%) are explanatory questions and 32 restate a figure. 98.13% of rows pass the corpus quality gate.
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import desidata
df = desidata.load("national-family-health-survey-and-sti-risk-factors-question-and-answer-dataset")
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Strong coverage with minor gaps in documentation or freshness.
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First 10 of 107 rows
| question | answer | context | answer_start | question_type | knowledge_quality_score | source_quote | source_page | source_location | confidence | validation_status |
|---|---|---|---|---|---|---|---|---|---|---|
| What is the National Family Health Survey a part of? | part of the Indian Demographic and Health Survey (DHS), a nationally representative household-based health surveillance system | 2.1 Data source This study is a cross-sectional secondary analysis of nationally representative data from the National Family Health Survey (NFHS-4, 2015–16 and NFHS-5, 2019–21). The National Family Health Survey (NFHS) is part of the Indian Demographic and Health Survey (DHS), a nationally representative household-based health surveillance system. In the NFHS-4 survey, data were collected from 640 districts. | 223 | definition | 1.000 | The National Family Health Survey (NFHS) is part of the Indian Demographic and Health Survey (DHS), a nationally representative household-based health surveillance system. | 2 | page=2,block=4 | 0.850 | valid |
| What sampling design was employed by the National Family Health Survey? | a stratified, two-stage cluster sampling design | 2. Data source This study is a cross-sectional secondary analysis of nationally representative data from the National Family Health Survey (NFHS-4, 2015–16 and NFHS-5, 2019–21). The National Family Health Survey (NFHS) is part of the Indian Demographic and Health Survey (DHS), a nationally representative household-based health surveillance system. In the NFHS-4 survey, data were collected from 640 districts. by the time the NFHS-5 was conducted, the number of districts had increased by 67 (n = 707). The National Family Health Survey employed a stratified, two-stage cluster sampling design, with enumeration areas (EAs) from the 2011 India census as the primary sampling unit (PSU) and households as the secondary sampling unit (SSU). Informed consent for par ticipation in the survey was obtained for all respondents prior to the interview. | 548 | definition | 1.000 | The National Family Health Survey employed a stratified, two-stage cluster sampling design, with enumeration areas (EAs) from the 2011 India census as the primary sampling unit (PSU) and households as the secondary sampling unit (SSU). | 2 | page=2,block=4 | ||
| Why does the NFHS men’s survey include men aged 50–54 years? | the NFHS men’s survey collects sexual behaviour and STI symptom information for this age group, allowing assessment among older sexually active men | 3.1.1 Outcome variable In both NFHS-4 and NFHS-5 rounds, respondents were asked whether they had ever had sexual intercourse and whether they had heard about sexually transmitted infections (STIs). Men aged 50–54 years were included because the NFHS men’s survey collects sexual behaviour and STI symptom information for this age group, allowing assessment among older sexually active men. Men who reported having had sexual intercourse were asked whether, during the last 12 months, they had a disease that they acquired through sexual contact. | 241 | relationship | 0.970 | Men aged 50–54 years were included because the NFHS men’s survey collects sexual behaviour and STI symptom information for this age group, allowing assessment among older sexually active men. | 3 | page=3,block=4 | 0.800 | valid |
| Why were separate models used for NFHS-4 and NFHS-5 instead of combining the data? | changes in administrative boundaries and updated sampling frames between survey rounds, and to allow clear comparison of patterns across time | Model adequacy was evaluated using the Hosmer–Lemeshow goodness-of-fit test, which indicated accept able model fit for both NFHS-4 and NFHS-5 models (p > 0.05). Separate models were estimated for NFHS-4 and NFHS-5 rather than a pooled analysis because of changes in administrative boundaries and updated sampling frames between survey rounds, and to allow clear comparison of patterns across time. The results from the descriptive analysis were presented as proportions, while the regression outcomes were reported as adjusted odds ratios (aORs) with corresponding 95% confidence intervals and p-values. | 255 | relationship | 0.970 | Separate models were estimated for NFHS-4 and NFHS-5 rather than a pooled analysis because of changes in administrative boundaries and updated sampling frames between survey rounds, and to allow clear comparison of patterns across time. | 4 | page=4,block=0 | 0.800 | valid |
| Why can self-reported STI symptoms lead to misclassification? | some symptoms may arise from conditions other than sexually transmitted infections | These two separate SR-STI symptom variables were combined and coded as a single dichot omous variable indicating the presence of any SR-STI symptom, including abnormal penile discharge, genital sore, or genital ulcer. In this study, abnormal penile discharge and genital ulcer symptoms were combined to construct a single indicator of self-reported STI symptoms (SR-STIs). These symp toms are commonly used in large population-based surveys as proxy indicators of pos sible STI exposure when laboratory-confirmed diagnoses are not available. it is important to note that these measures represent self-reported symptoms rather than clinically confirmed infections and may therefore be subject to misclassification bias, as some symptoms may arise from conditions other than sexually transmitted infections. | 722 | relationship | 0.970 | it is important to note that these measures represent self-reported symptoms rather than clinically confirmed infections and may therefore be subject to misclassification bias, as some symptoms may arise from conditions other than sexually transmitted infections. | 3 | page=3,block=4 | ||
| How is the number of non-spousal sexual partners related to SR-STI prevalence in NFHS 4? | men with 4 + sexual partners have around five times more SR-STIs than those with zero sexual partners apart from spouses | We have tried to see more in detail about SR-STIs among married men. Figure 4 shows a higher prevalence of SR-STI symptoms among men reporting a greater number of non-spousal sexual partners. In NFHS 4, men with 4 + sexual partners have around five times more SR-STIs than those with zero sexual partners apart from spouses. This trend continues even in NFHS 5, as men having 4 + sexual partners have around three times more SR-STIs than those men having zero sexual partners apart from spouses. The relationship between the most recent sex partner and SR-STIs prevalence among men is shown in Fig. 5. It is indicated that men who had sex with TG/ Male partners have reported having the highest SR-STIs compared to the rest. | 203 | relationship | 0.970 | In NFHS 4, men with 4 + sexual partners have around five times more SR-STIs than those with zero sexual partners apart from spouses. | 6 | page=6,block=4 | 0.700 | valid |
| What pattern in SR-STI prevalence among men with multiple sexual partners was observed in NFHS 5? | men having 4 + sexual partners have around three times more SR-STIs than those men having zero sexual partners apart from spouses | We have tried to see more in detail about SR-STIs among married men. Figure 4 shows a higher prevalence of SR-STI symptoms among men reporting a greater number of non-spousal sexual partners. In NFHS 4, men with 4 + sexual partners have around five times more SR-STIs than those with zero sexual partners apart from spouses. This trend continues even in NFHS 5, as men having 4 + sexual partners have around three times more SR-STIs than those men having zero sexual partners apart from spouses. The relationship between the most recent sex partner and SR-STIs prevalence among men is shown in Fig. 5. It is indicated that men who had sex with TG/ Male partners have reported having the highest SR-STIs compared to the rest. | 365 | relationship | 0.970 | This trend continues even in NFHS 5, as men having 4 + sexual partners have around three times more SR-STIs than those men having zero sexual partners apart from spouses. | 6 | page=6,block=4 | 0.700 | valid |
| What factors are identified as contributing to STI risk among Muslim men? | differences in marital composition, partnership patterns, and broader socio-cultural contexts | Page 11 of 14 R. S. et al. Discover Public Health (2026) 23:434 The study finds that Muslim men have higher chances of STIs compared to other reli gious groups, which aligns with previous literature. This pattern may reflect differences in marital composition, partnership patterns, and broader socio-cultural contexts that may influence STI risk [21, 24–26]. Taken together, these factors underscore the impor tance of considering both marital status and cultural practices when formulating tar geted STI prevention and intervention strategies among different populations in India. A comprehensive approach that addresses these specific risk factors can lead to more effective control and reduced STI transmission within affected communities. The study highlights that higher educational attainment is protective against STIs. | 225 | relationship | 0.970 | This pattern may reflect differences in marital composition, partnership patterns, and broader socio-cultural contexts that may influence STI risk [21, 24–26]. | 11 | page=11,block=0 | 0.700 | |
| Why are men often underrepresented in STI surveillance data? | Men are often asymptomatic carriers and may underutilize sexual health services | Given the public health impact of STIs against the fact that most infections are curable, the WHO Global Health Sector Strategy on Sexu ally Transmitted Infections (2016–2021) laid out a roadmap for STI prevention and control [6]. Although STIs affect both men and women, evidence on STI burden among men remains limited, particularly in low- and middle-income countries like India. Men are often asymptomatic carriers and may underutilize sexual health services, contribut ing to sustained transmission and under-representation in surveillance data. Socio-demographic factors and economic conditions are associated with STI preva lence to varying degrees. Several such factors increase susceptibility to STIs, including low education, poverty and rural or urban place of residence [7–10]. | 383 | relationship | 0.970 | Although STIs affect both men and women, evidence on STI burden among men remains limited, particularly in low- and middle-income countries like India. Men are often asymptomatic carriers and may underutilize sexual health services, contribut ing to sustained transmission and under-representation in surveillance data. | 2 | |||
| Why were separate models estimated for NFHS-4 and NFHS-5 instead of a pooled analysis? | because of changes in administrative boundaries and updated sampling frames between survey rounds, and to allow clear comparison of patterns across time | Model adequacy was evaluated using the Hosmer–Lemeshow goodness-of-fit test, which indicated accept able model fit for both NFHS-4 and NFHS-5 models (p > 0.05). Separate models were estimated for NFHS-4 and NFHS-5 rather than a pooled analysis because of changes in administrative boundaries and updated sampling frames between survey rounds, and to allow clear comparison of patterns across time. The results from the descriptive analysis were presented as proportions, while the regression outcomes were reported as adjusted odds ratios (aORs) with corresponding 95% confidence intervals and p-values. This rig orous and comprehensive statistical approach provides a reliable basis for understanding the factors influencing SR-STIs prevalence, allowing for informed decision-making in the development of targeted interventions and strategies to combat sexually transmit ted infections. | 244 | relationship | 0.970 | Separate models were estimated for NFHS-4 and NFHS-5 rather than a pooled analysis because of changes in administrative boundaries and updated sampling frames between survey rounds, and to allow clear comparison of patterns across time. |
Read straight from the file — download or use the API URL for the full dataset.
| 0.700 |
| valid |
| 0.700 |
| valid |
| valid |
| page=2,block=0 |
| 0.700 |
| valid |
| 4 |
| page=4,block=0 |
| 0.700 |
| valid |