National Sample Survey Organization Research Articles

Detection of outliers in survey–weighted linear regression

ABSTRACT Regression diagnostics help identify influential data points in a model. Detecting outliers in complex survey design data involving stratification, clustering, and unequal probability sampling is difficult due to the presence of masking, where one outlier makes it hard to detect others. The masking factor for survey–weighted linear regression is developed and applied to analyzing the Household Consumer Expenditure dataset of 68th round of the National Sample Survey Organization survey of India. Regression parameters are calculated before and after detection and removal of outliers. The standard error of regression parameters for survey-weighted least squares models is reduced by 2% for the intercept, 5% for variable “meat” (X 5), 4% for “served processed food” (X 9), and 4% for “packaged processed food” (X 10). Inference alters the significance of regression coefficients of the variable “served processed food” (X 9) leading to the emergence of significance. There is no change in inference for other variables.

Gender Conundrum and Unpaid Work in India: Empirical Evidence from India’s First Large-scale Time Use Survey

The study was aimed at (a) exploring the anomalies in conceptualising and measuring work, especially that of the women, (b) analysing the patterns of unpaid work distribution between men and women, and (c) examining the drivers of time spent on unpaid work in India. It has been argued that the under-conceptualisation of work and the methodological constraints led to invisibilising several activities, mostly performed by girls and women, in the prevailing labour force statistics and national income accountings. We have noted that such anomalies could be overcome with the advancement of robust statistical tools like that of time use survey. By employing the first and the most recent pan time use survey, conducted by the National Sample Survey Organization across the country in 2019, we have assessed the gender patterns of unpaid work and its determinants. We found the existence of a stark gender gap both in terms of participation and average time spent on unpaid work across rural and urban regions. Again, the findings, obtained through the Tobit regression model, reveal that the nature of the association and the extent of time allocated to unpaid work vary substantially across the demographic and socio-economic characteristics. JEL Codes: J22, J21, J40, J46, C10

Decomposing the inequalities in the catastrophic health expenditures on the hospitalization in India: empirical evidence from national sample survey data.

Sustainable Development Goal (SDG) Target 3.8.2 entails financial protection against catastrophic health expenditure (CHE) by reducing out-of-pocket expenditure (OOPE) on healthcare. India is characterized by one of the highest OOPE on healthcare, in conjunction with the pervasive socio-economic disparities entrenched in the population. As a corollary, India has embarked on the trajectory of ensuring financial risk protection, particularly for the poor, with the launch of various flagship initiatives. Overall, the evidence on wealth-related inequities in the incidence of CHE in low- and middle-Income countries has been heterogenous. Thus, this study was conducted to estimate the income-related inequalities in the incidence of CHE on hospitalization and glean the individual contributions of wider socio-economic determinants in influencing these inequalities in India. The study employed cross-sectional data from the nationally represented survey on morbidity and healthcare (75th round of National Sample Survey Organization) conducted during 2017-2018, which circumscribed a sample size of 1,13,823 households and 5,57,887 individuals. The inequalities and need-adjusted inequities in the incidence of CHE on hospitalization care were assessed via the Erreygers corrected concentration index. Need-standardized concentration indices were further used to unravel the inter- and intra-regional income-related inequities in the outcome of interest. The factors associated with the incidence of CHE were explored using multivariate logistic regression within the framework of Andersen's model of behavioral health. Additionally, regression-based decomposition was performed to delineate the individual contributions of legitimate and illegitimate factors in the measured inequalities of CHE. Our findings revealed pervasive wealth-related inequalities in the CHE for hospitalization care in India, with a profound gap between the poorest and richest income quintiles. The negative value of the concentration index (EI: -0.19) indicated that the inequalities were significantly concentrated among the poor. Furthermore, the need-adjusted inequalities also demonstrated the pro-poor concentration (EI: -0.26), denoting the unfair systemic inequalities in the CHE, which are disadvantageous to the poor. Multivariate logistic results indicated that households with older adult, smaller size, vulnerable caste affiliation, poorest income quintile, no insurance cover, hospitalization in a private facility, longer stay duration in the hospital, and residence in the region at a lower level of epidemiological transition level were associated with increased likelihood of incurring CHE on hospitalization. The decomposition analysis unraveled that the contribution of non-need/illegitimate factors (127.1%) in driving the inequality was positive and relatively high vis-à-vis negative low contribution of need/legitimate factors (35.3%). However, most of the unfair inequalities were accounted for by socio-structural factors such as the size of the household and enabling factors such as income group and utilization pattern. The study underscored the skewed distribution of CHE as the poor were found to incur more CHE on hospitalization care despite the targeted programs by the government. Concomitantly, most of the inequality was driven by illegitimate factors amenable to policy change. Thus, policy interventions such as increasing the awareness, enrollment, and utilization of Publicly Financed Health Insurance schemes, strengthening the public hospitals to provide improved quality of specialized care and referral mechanisms, and increasing the overall budgetary share of healthcare to improve the institutional capacities are suggested.

Do hospitalizations push households into poverty in India: evidence from national data.

High percentage of OOP (Out-of-Pocket) costs can lead to poverty and exacerbate existing poverty, with 21.9% of India's 1.324 billion people living below the poverty line. Factors such as increased patient cost-sharing, high-deductible health plans, and expensive medications contribute to high OOP costs. Understanding the poverty-inducing impact of healthcare payments is essential for formulating effective measures to alleviate it. The study used data from the 75th round of the National Sample Survey Organization (Household Social Consumption in India: Health) from July 2017-June 2018, focusing on demographic-socio-economic characteristics, morbidity status, healthcare utilization, and expenditure. The analysis included 66,237 hospitalized individuals in the last 365 days. Logistic regression model was used to examine the impact of OOP expenditures on impoverishment. Logistic regression analysis shows that there is 0.2868 lower odds of experiencing poverty due to OOP expenditures in households where there is the presence of at least one child aged 5 years and less present in the household compared to households who do not have any children. There is 0.601 higher odds of experiencing poverty due to OOP expenditures in urban areas compared to households in rural areas. With an increasing duration of stay in the hospital, there is a higher odds of experiencing poverty due to OOP health expenditures. There is 1.9013 higher odds of experiencing poverty due to OOP expenditures if at least one member in the household used private healthcare facility compared to households who never used private healthcare facilities. In order to transfer demand from private to public hospitals and reduce OOPHE, policymakers should restructure the current inefficient public hospitals. More crucially, there needs to be significant investment in rural areas, where more than 70% of the poorest people reside and who are more vulnerable to OOP expenditures because they lack coping skills.

Distribution and Usage of Digital Payment Cards in India: Findings from NSS 77th Round Survey

Promoting digital economy is a policy priority of the Government of India. The latest available large-scale survey data on households’ debt and investment from National Sample Survey Organization (NSSO, 2021) provides details on the possession and utilization of payment cards for adults across India. Using the information, this article explores the state and district-level variations in its distribution and usage in India—which is a crucial knowledge gap in the existing literature. The article finds that while 85% of Indian adults have a bank account, less than half of them have a debit or credit card. Also, 82% of card-holders have actually used their cards for transactions during 365 days prior to the survey. Access to payment cards seems crucial for digital integration. This article attempts to identify policy handles that can help in the spread of payment cards. Their possession is aggregated at district levels and regressed on several indicators. The article identifies that literacy rate, access to banking, road density, prevalence of Self-Help Groups and Co-operative Credit Societies are all significant positive influencers towards digital integration. A similar result is obtained for the usage of payment cards as well. This article comes up with a first glimpse of digital integration at the pan-India level while also providing some policy suggestions for enhancing cashless transactions in India.

Magnitude of health expenditure induced removable poverty in India: Some reflections of Ayushman Bharat

The authors have measured the health expenditure-induced removable poverty in India using nationally representative consumer expenditure surveys of three quinquennial rounds conducted by the National Sample Survey Organization (NSSO). This study has also focused on the reflections of Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana (AB-PMJAY), the world's largest Government-funded health insurance scheme, on these poverty rates in the country. The study has used headcount, payment gap, and concentration index to measure the economic burden and impoverishment impact of out-of-pocket (OOP) health expenditure. The analysis shows that the incidence and depth of poverty are substantially understated because of overlooking OOP health expenditure in the country's standard poverty measure. Outpatient care contributes almost four times more than inpatient care to health expenditure-induced impoverishment in India, though this care has not been covered in the AB-PMJAY. Muslims, among all religious groups, Scheduled Castes among social groups, and casual labourers among different household types are more vulnerable to OOP health expenditure-induced removable poverty in the country. Poverty, in general, has dropped significantly, but the share of health expenditure-induced poverty in general poverty has increased substantially. It has risen considerably in rural areas and among India's most vulnerable sections of society in the past 20 years. We emphasised that universal health insurance coverage is needed in India. Implementing comprehensive health insurance schemes that cover both inpatient and outpatient care can help alleviate the financial burden of healthcare expenses on households and contribute to reducing poverty rates.

Pattern and drivers of profitability in India’s unorganised manufacturing sector

Using data from National Sample Survey Organisation surveys, the paper analyses the profit rate and its drivers in India’s unorganised manufacturing sector for the period 2000–01 to 2015–16. The entire period has been subdivided into three smaller periods to examine the short-run fluctuations in profitability. The study has been carried out at disaggregate level, namely, state and industry levels as well. The output-capital ratio has behaved cyclically over the years, whereas a steady rise in the profit share has been the driver of cyclically rising profit rate over the period. A rapid growth in labour productivity with a non-commensurate rise in wage rate has been the reason behind the rise in profit share. The ranking of states and industries on profit rate has been found to be relatively unchanged.

If you can't fix the problem change the standards.

Over the last few months, established data systems in India have been the target of heated dispute, chiefly by members of the Economic Advisory Council to the Prime Minister, ranging from the inflation numbers [1], to the sampling frame for surveys done by the National Sample Survey Organisation (NSS), the National Family Health Survey (NFHS) and the Periodic Labour Force Survey (PLFS)[2], haemoglobin cut-offs for anaemia [3] and childhood growth standards, female labour force participation rate and life expectancy at birth [4]. The attempts to revise economic data systems has invited a raging debate [5, 6], prompting the government to set up a panel to review the NSS's methodology. However, the arguments being made in favor of downward revision of nutritional standards have received much less scrutiny, except for a recent editorial which comments on the general problem of drawing up standards [7]. This is despite the fact that these proposals have already caught the fancy of the government. A policy decision has already been taken to discontinue gathering of data on Hb-levels as part of the quinquennial National Family Health Surveys, which would now be collected as part of a new Dietary and Bio-markers Survey. Neither the rationale for such a move, nor the details of the methodology of the new survey, or the time-frame within which such data would be released have been made available for public deliberation. Similarly, discussions have been initiated on devising "indigenous" growth standards for children [8]. Hence, it becomes imperative to examine the basis of these renewed calls for revision of existing standards.

Structural Change, Services Sector and Intergenerational Occupational Mobility in India: Some Exploratory Evidence

This study investigates into intergenerational occupational mobility of Indian workers towards and within service sectors during globalization. In particular, such mobility of workers is observed in the presence of structural shift of the economy towards service industry, especially towards service trade, and explores whether there is intergenerational mobility towards services and more ­skill-oriented occupations in India during 1999–2011. The Altham measure of relative mobility is applied on the National Sample Survey Organization employment–unemployment survey database to measure the degree of association between occupational choice of fathers and co-resident sons in urban India. An upward mobility among sons is observed between 1999–2000 and 2011–2012. JEL Codes: F14, F16, J62, L80, C46

Need for living wages in India: Case studies of agricultural workers in rural Madhya Pradesh

AbstractThe present study discusses the current wage situation in India and the need for living wages as workers and employees grapple with the cost of living crisis. A case study of two districts of Madhya Pradesh (MP) state is presented to demonstrate how the living wage benchmarks based on the Anker Methodology compare with existing minimum wage fixations and other development indicators. The living wage benchmarking is based on field surveys conducted in Ratlam and Chhindwara districts in October–December 2021, and a rigorous analysis of nationally representative consumption and expenditure surveys conducted by the National Sample Survey Organisation and the Centre for Monitoring Indian Economy. Our living wage estimates are 1.8 times the minimum wages for agricultural labourers and 43% more than those earned by non-agricultural unskilled labourers. Moreover, the actual wages reported are less than half of the estimated living wages, indicating that the current incomes and wages for workers and farmers of rural MP are far from adequate to lead a decent life.

Access and Uses of ICTs: Can Virtual Learning Be an Alternative Mode of Education in India?

This study analyses household access and persons’ uses of information and communication technologies (ICTs) in India by using the latest National Sample Survey Organization’s (NSSO) Education survey (2017–2018) datasets. Accordingly, an ICT Index is computed, and a logistic model is applied to examine the pattern and likelihood of digital technology usage and access. The result shows that access to ICTs is lower in rural areas and access increases with the level of education. The study also observes that factors like education, income and regional variations are significant aspects of the disproportionate uses and access of ICTs at the household and individual levels. This study also observed that the low level of access to ICTs will be a huge challenge for the Government to ensure alternate online or virtual modes of education.

Impact of Low Birth Weight on the Prevalence and Economic Burden of Common Childhood Illnesses Among Under-Five Children in India: Findings From Nationally Representative Surveys.

Background Common childhood illnesses such as diarrhea, fever, and acute respiratory infection impose substantial health burdensamong under-five children, and Low Birth Weight (LBW) has been associated with an increased prevalence of these illnesses. However, the impact of LBW on healthcare utilization and the economic burden of these illnesses remains understudied. Aim To assess the impact of LBW on the prevalence, healthcare utilization, and Out of Pocket Expenditure (OOPE) for outpatient (OP) treatment of selected Common Childhood Illnesses(CCHI) among under-five children in India. Methodology This study utilized data from two nationally representative surveys conducted in India; National Family Health Survey (NFHS-5) (2019-2021) and the National Sample Survey Organization (NSSO) 75th Round Schedule Social Consumption: Health (2017-2018). Data from the NFHS-5 was analyzed to assess the impact of LBW on the prevalence of selected CCHI and healthcare utilization. Comparison of OOPE for OP treatment of selected CCHI between LBW and Normal Birth Weight (NBW) children done using the median OOPE for OP visits of CCHI estimated from the NSSO data. Results The two-week prevalence of selected CCHI among LBW and NBW children was found to be 20.0% (95% CI19.6 -20.4) and 18.0% (95% CI 17.8 -18.2), respectively. There was no significant difference between LBW and NBW children on healthcare utilization for the treatment of CCHI; both groups had a similar proportion (around 70%) of formal medical treatment utilization for CCHI. The median OOPE spending for OP visits per episode of CCHI was comparable between LBW and NBW children. However, families of LBW children had higher annual OOPE spending for OP visits related to CCHI, with projected estimates of INR 1,446 ($19.56) for LBW children and INR 1,271 ($17.2) for NBW children. Conclusion LBW was associated with a higher prevalence of CCHI. Even though healthcare utilization was similar among LBW and NBW children, a higher prevalence of CCHI among LBW children led to higher OOPE. LBW children have approximately 13% higher annual OOPE spending for the OP visits related to selectedCCHI compared to NBW children.

Long-term health and human capital effects of in utero exposure to an industrial disaster: a spatial difference-in-differences analysis of the Bhopal gas tragedy

ObjectivesGlobalisation and industrialisation can increase economic opportunity for low/middle-income nations, but these processes may also increase industrial accidents and harm workers. This paper examines the long-term, cohort-based health effects of...

Access and Determinants of Formal Agriculture Credit In Uttar Pradesh, India

The study has attempted to examine the determinants of formal agricultural credit in rural Uttar Pradesh using National Sample Survey Organisation data from the 70th round (2012–13). The Binary Logistic Regression (BLR) model is used to examine the determinants of formal credit in Uttar Pradesh. Socio-economic and demographic characteristics such as age, gender, social group, and family size are grouped into social, economic, and extension services. The findings from this study revealed that indebtedness exists and that almost 45 per cent of farmers have taken credit from informal credit agencies. Further, there is significant heterogeneity in terms of socio-economic and demographic features among farmers who have taken credit from formal and informal credit agencies. The BLR results show that gender, literacy rate, operated area, bank account, livestock, and Kisan Credit Card are key social and economic determinants of formal credit in rural Uttar Pradesh. The calculated odds ratio shows a 2.008 times higher probability of literate male farmers taking a loan from formal credit than others. Likewise, there is a 3.10 times higher probability of taking formal credit if farmers follow technical advice provided by agricultural universities, NGOs, and scientists through open-source platforms. Hence, the following policies are suggested to deal with indebtedness: (i) Policymakers can choose to intervene in the rural credit lending system by liberalising policy to more accurately reflect the characteristics of potential borrowers and in light of their current borrowing strategies, (ii) the BLR results depict a positive relationship with land size, and agricultural households with larger land seem to get more benefits. Therefore, the government should focus on marginal and small farmers, who have larger shares in the total operational landholdings, (iii) safety net programmes like the Public Distribution System (ration cards), in the presence of formal credit, may induce farmers and their families to increase their per capita monthly consumption expenditures, and (vi) State intervention is also required in terms of increasing the size of livestock, as this can be an area where Uttar Pradesh can lead the other States as this will help in diversification in the field of agriculture .

Strengths-based Gram Sabhas? Challenges and radical possibilities when ‘measuring’ poverty in India

Poverty as an object of study in India continues to be the domain of economists, statisticians and demographers. The National Sample Survey Organisation (NSS) serves as the main instrument of data collection to measure poverty relative to economic indicators. In this paper we draw on strengths-based research undertaken in an Indian village to foreground alternative ways of conceptualising and practising data collection when measuring poverty. Explored through an analytics of biopolitics, asset-mapping exercises with young people and women revealed new subjectivities that emerged via illustrative meaning-making and dialogue. This approach to poverty measurement facilitated methods and produced outcomes that were less calculated and predefined than the NSS, and encouraged participation, even questioning of the status quo, in the ‘doing’ of the methodology itself. A strengths orientation to poverty opens up radical possibilities, particularly in India where the state-sanctioned self-­governing body, the Gram Sabhas, has a mandate to provide for the most marginalised groups. And while this governing body is not free from power imbalances, the potential it offers, when combined with strengths-based approaches (SBA) that value people for the expertise they already have, demands renewed attention in practitioner and policy debates in the country.

Falling Between the Cracks: Women’s Work and the Periodic Labour Force Survey

This article reflects upon the changes introduced in the Periodic Labour Force Survey (PLFS) and their impact on the visibility of women’s work in India. In 2017–2018, the National Sample Survey Organisation’s five-yearly employment–unemployment surveys (EUS) were replaced by the annual PLFS, and in the transition, the section that comprised probing questions was dropped. These questions had been introduced in 1972–1973 to highlight women’s productive activities, which otherwise remain invisible. The section was key to collecting information on not only women’s reproductive work but also the unrecognised productive work women undertake within the walls of their homes. It provided a window in a society where women’s work is underestimated as well as unappreciated.

Do climatic and socioeconomic factors explain population vulnerability to malaria? Evidence from a national survey, India.

Malaria remains a public health challenge across several African and South-East Asia Region countries, including India, despite making gains in malaria-related morbidity and mortality. Poor climatic and socioeconomic factors are known to increase population vulnerability to malaria. However, there is scant literature from India exploring this link using large population-based data. This study aims to study the role of climatic and socioeconomic factors in determining population vulnerability to malaria in India. We used logistic regression models on a nationally representative sample of 91,207 households, obtained from the National Sample Survey Organization (69th round), to study the determinants of household vulnerability. Households that resided in high (odds ratio [OR]: 1.876, P < 0.01) and moderately high (OR: 3.427, P < 0.01), compared to low climatically vulnerable states were at greater odds of suffering from malaria. Among households that faced the problem of mosquitoes/flies compared to the reference group, the urban households were at higher risk of suffering from malaria (OR: 8.318, P < 0.01) compared to rural households (OR: 2.951, P < 0.01). Households from the lower income quintiles, caste, poor physical condition of their houses, poor garbage management, and water stagnation around the source of drinking water, strongly predicted malaria vulnerability. Household's vulnerability to malaria differed according to state climatic vulnerability level and socioeconomic factors. More efforts by integrating local endemicity, epidemiological, and entomological information about malaria transmission must be considered while designing malaria mitigation strategies for better prevention and treatment outcomes.

Mental health and anxiety among unorganized sector labour

Background: National Sample Survey Organisation (NSSO) in 2009–10, the total employment in the country was of 46.5 crore comprising around 2.8 crore in the organised and the remaining 43.7 crore workers in the unorganised sector. Out of these workers in the unorganised sector, there are 24.6 crore workers employed in agricultural sector, about 4.4 crore in construction work and remaining in manufacturing and service. The unorganized labour is overwhelming in terms of its number range and therefore they are omnipresent throughout India. As the unorganized sector suffers from cycles of excessive seasonality of employment, majority of the unorganized workers does not have stable durable avenues of employment. Even those who appear to be visibly employed are not gainfully and substantially employed, indicating the existence of disguised unemployment. Though unorganized sectors contribute substantially to the country’s growth, the status of labour force remains unchanged. In developing and over populated countries like India persons working in unorganized sector are at high risk of job insecurities. As per the India labour Market Update, July 2016, the Construction sector has been the main creator of job. Objectives: to study the mental health of labour in unorganized sector and anxiety among them. Methods: This study is conducted at construction sites in City of Pune, Maharashtra, India. This study included 110 randomly selected construction site labours (62 males and 48 females). For data collection researcher used Sinhas’s Comprehensive Anxiety Inventory (SCAT) and Mental Health Checklist (MHC) by Kumar (1992). Results: The findings of the study suggest that there lies significant difference in anxiety and mental health of male and female labour as well. It was further concluded that there lies a high correlation between anxiety and mental health of labour in unorganized sector. Conclusions: The study shows that the work in organized sector contribute moderate to high level of anxiety amongst the labour. There must be a management policy with reference to mental as well as physical health of these workers. It should take into consideration the issues concerned with in time assessment and treatment as well as rehabilitation. Work stress can be prevented by the techniques of human engineering, by designing the work environment effectively. The work environment and working conditions has to be developed in a very sensitive and responsive management system.

Illnesses and hardship financing in India: an evaluation of inpatient and outpatient cases, 2014-18

BackgroundProgress towards universal health coverage requires strengthening the country's health system. In developing countries, the increasing disease burden puts a lot of stress on scarce household finances. However, this burden is not the same for everyone. The economic burden varies across the disease groups and care levels. Government intervention is vital in formulating policies in addressing financial distress at the household level. In India, even when outpatient care forms a significant proportion of out-of-pocket expenditure, government schemes focus on reducing household expenditure on inpatient care alone. Thus, people resort to hardship financing practices like informal borrowing or selling of assets in the event of health shocks. In this context, the present study aims to identify the disease(s) that correlates with maximum hardship financing for outpatients and inpatients and to understand the change in hardship financing over time.MethodsWe used two waves of National Sample Survey Organisation’s data on social consumption on health- the 71st and the 75th rounds. Descriptive statistics are reported, and logistic regression is carried out to explain the adjusted impact of illness on hardship financing. Pooled logistic regression of the two rounds is estimated for inpatients and outpatients. Marginal effects are reported to study the changes in hardship financing over time.ResultsThe results suggest that cancer had the maximum likelihood of causing hardship financing in India for both inpatients (Odds ratio 2.41; 95% Confidence Interval (CI): 2.03 - 2.86 (71st round), 2.54; 95% CI: 2.21 - 2.93 (75th round)) and outpatients (Odds ratio 6.11; 95% CI: 2.95 - 12.64 (71st round), 3.07; 95% CI: 2.14 - 4.40 (75th round)). In 2018, for outpatients, the hardship financing for health care needs was higher at public health facilities, compared to private health facilities (Odds ratio 0.72; 95% CI: 0.62 - 0.83 (75th round). The marginal effects model of pooled cross-section analysis reveals that from 2014 to 2018, the hardship financing had decreased for inpatients (Odds ratio 0.747; 95% CI:0.80 - -0.70), whereas it had increased for outpatients (Odds ratio 0.0126; 95% CI: 0.01 - 0.02). Our results also show that the likelihood of resorting to hardship financing for illness among women was lesser than that of men.ConclusionGovernment intervention is quintessential to decrease the hardship financing caused by cancer. The intra-household inequalities play an important role in explaining their hardship financing strategies. We suggest the need for more financial risk protection for outpatient care to address hardship financing.

Disability prevalence: comparing four types of disability measures in the community

BackgroundThere is no general consensus on how to measure disability and disability prevalence rates. The results of previous estimates could not be compared due to the varied nature of the methodologies used and the lack of standardization in the measurement of disability. The primary objective of the study was to estimate the prevalence of disability using a population-based disability survey and questions selected by the National Center for Promotion of Employment for Disabled People (NCPEDP). The secondary objective is to determine whether there was any relationship between the severity of disability and essential sociodemographic factors.The survey was carried out in the Indian state of Gujarat’s Piplag village. Eight final-year physiotherapy students gathered sociodemographic data and answers to the four disability-related questions—disability question asked in India census 2011, Washington Group (WG)-suggested question, United Nations Convention on the Rights of Persons with Disabilities (UNCRPD)-based question, and National Sample Survey Organization (NSSO)-based question.ResultsA greater percentage of the population was classified as having a functional limitation in the questions based on the UNCRPD (28.29%) (95% CI 25.1–31.3%) and the WG (29.69%) (95% CI 26.0–34.4%). Our findings demonstrated that there were significant relationships between the questions in different questionnaires (p < 0.01). Female gender strongly influences how people self-identify as having a disability (by 5.7 to 12.07 times), and the predictor variables based on the Indian census 2011 questions explained 61.7% of the variation in prevalence of disability.ConclusionsThe prevalence statistics may vary based on the questions used to gather information about disabilities. As gender and socioeconomic status can impact the prevalence of disabilities, it is important to focus on ways to improve economic growth, especially for women.