Building Knowledge Bases Research Articles

Association between Multimorbidity and Psychological Distress among Older Adults in India: The Moderating Role of Elder Abuse

ABSTRACT Objectives In this study, we examine the association between multimorbidity and psychological distress and to what extent elder abuse mediates the association. Methods We analyzed cross-sectional nationally representative data from the “Building Knowledge Base on Population Ageing in India (BKPAI).” Multivariate logistic regression was used to understand the association between multimorbidity and psychological distress. We used Karlson–Holm– Breen (KHB) method to understand the role of elder abuse in mediating the association between multimorbidity and psychological distress. Results Older adults who ever experienced abuse (OR = 1.92 95%CI = 1.62, 2.26, p < .001) or in last one month (OR = 2.09 95%CI = 1.65, 2.64, p < .001) reported higher odds of psychological distress. Further, older adults with four or more chronic diseases are thrice more likely to report psychological distress (OR = 3.03 95%CI = 2.38, 3.82, p < .001). The results further suggest the mediating role of abuse on the association between multimorbidity and psychological distress. Conclusions The results suggest the role of elder abuse on the association between multimorbidity and psychological distress among older population in India. Clinical implications Creating an environment to reduce the abuse among older adults who have multimorbidity will be essential to reducing the psychological distress among older adults in India

Diversity of Learners, their Special Learning Needs and Inclusive Education: Perspectives of Teachers in Public Secondary Schools in Kwara State, Nigeria.

The study was aimed at building knowledge base for addressing learners’ special learning needs and for promoting inclusive education. The purpose of the study was to provide a rich description of public secondary schools’ teachers’ perspectives on their learners and on inclusive education. The study adopted quantitative design to investigate teachers’ awareness and knowledge of diversity of learners in their classrooms, including the teachers’ understanding of their learners’ special learning needs as well as the teachers’ perspectives on their experiences with implementation of inclusive education The population for the study comprised all teachers in public secondary schools in Kwara State, Nigeria, and by convenient sampling method drew a sample of one hundred and forty-five teachers. The instrument for data gathering was a questionnaire which contained descriptive statements responded to by respondents who indicated their degrees of agreement on a four-point; liker-type scale. Data collected were analysed and with the use of the descriptive statistics of percentage frequencies and mean response scores to answer the research questions and to arrive at the achievement of the study objectives. The results revealed that teachers involved in the study were generally aware of learners’ diversity in their classrooms. To strengthen this awareness, the teachers also indicated their knowledge regarding the manifestations of the diversity in terms of the learners’ ability and activity levels as well as behavioural tendencies. Teacher-respondents reported some learners as gifted and talented, some as more active than others, some aggressive or withdrawn in behaviors, some with speech and language difficulties as well as auditory, visual and orthopaedic impairments, while some are with other disabilities. The results of the study have implications for pre-service and in-service training of teachers as well as better structuring of schools’ physical infrastructure in order to promote better access, participation and belongingness for pupils with disabilities.

Artificial Intelligence Stimulus Response System

The Stimulus Response System (SRS) is based on the concept of artificial intelligence (AI) based mark-up language. (AIML) and is used to train the system for recognizing the user input. By making use of the previously built knowledge base this system is trying to analyze the user input and it provides the response. The Chatter Bot’s, reported in the literature, and was used mainly the indexing technique. The method is strongly dependent on the contents that are stored in a file or a database. Thus there is a need to develop a new system that allows you to carry on conversations with the system as long as possible. Stimulus Response System creates and adds knowledge to a computer. As a result, the computer will appear as human. The main objective of the work is to design an interactive software package which make the computer simple by building content that induces the client to carry on interactive conversations with the system as long as possible.

3D AND HBIM MODELS: DIGITAL TOOLS FOR THE DIAGNOSTIC STUDY OF THE STAIR TURRET OF THE SOUTH-EAST CORNER OF THE MAIN TOWER OF STRASBOURG CATHEDRAL

Abstract. During the construction of Strasbourg Cathedral, men aspired to see it radiate eternally. However, like any monument, it experiences structural weakening due to the effects of time, but also to the many external aggressions that damage the materials. Regular interventions therefore make it possible to preserve this building over time. It is in this context of conservation that the cathedral lives to the rhythm of a major restoration campaign since 2014. The objective of this project was to carry out a modeling and a BIM model of the stair turret in the south-east corner of the main tower built entirely of sandstone. This work was part of the preparatory phase of the restoration work on the south-east stair turret of the high tower scheduled for 2024–2025. The objective was to carry out a diagnosis of the turret (35 m high, 168 steps) with the help of a 3D and BIM model. This study could be understood as the beginning of a more global work of 3D representation extendable to the entire monument. In addition, in the spirit of gathering information and building knowledge base, it could be interesting to develop a complete BIM model of the entire building later.

EXPERT SYSTEM FOR DIAGNOSING DISEASE USING FUZZY LOGIC

In this research, a system for diagnosing disease was designed and implemented. This system will be used for paramedics expert. They need to enter many symptoms. The symptoms are classified into two categories, crisps and fuzzy. The fuzzy symptoms are input using slider. It is used for uncertainty symptoms. Building this system, needs three steps knowledge acquisition, knowledge representation and then building knowledge base, and finally building inference engine. This system uses standard class operator, algebraic class operator, and Einstein class operator. Implication rule uses Dienes-Rescher and for combine all rules use Mamdani Combination. Based on all symptom that have been entered using standard class operator, this system is a success for diagnosing disease and its inference value. Keywords : diagnose disease, expert system, fuzzy logic.

SIMEON: Prediction of Chemical-protein Interaction via Stacked Bi-GRU-normalization Network and External Biomedical Knowledge

Background: Chemical compounds and proteins/genes are an important class of entities in biomedical research, and their interactions play a key role in precision medicine, drug discovery, basic clinical research, and building knowledge bases. Many computational methods have been proposed to identify chemical–protein interactions. However, the majority of these proposed models cannot model long-distance dependencies between chemical and protein, and the neural networks used to suffer from gradient descent, with little taking into account the characteristics of the chemical structure characteristics of the compound. Methods: To address the above limitations, we propose a novel model, SIMEON, to identify chemical– protein interactions. First, an input sequence is represented with pre-trained language model and an attention mechanism is used to uncover contribution degree of different words to entity relations and potential semantic information. Secondly, key features are extracted by a multi-layer stacked Bidirectional Gated Recurrent Units (Bi-GRU)-normalization residual network module to resolve higherorder dependencies while overcoming network degradation. Finally, the representation is introduced to be enhanced by external knowledge regarding the chemical structure characteristics of the compound external knowledge Results: Excellent experimental results show that our stacked integration model combines the advantages of Bi-GRU, normalization methods, and external knowledge to improve the performance of the model by complementing each other Conclusion: Our proposed model shows good performance in chemical-protein interaction extraction, and it can be used as a useful complement to biological experiments to identify chemical-protein interactions.

WikiDes: A Wikipedia-based dataset for generating short descriptions from paragraphs

As free online encyclopedias with massive volumes of content, Wikipedia and Wikidata are key to many Natural Language Processing (NLP) tasks, such as information retrieval, knowledge base building, machine translation, text classification, and text summarization. In this paper, we introduce WikiDes, a novel dataset to generate short descriptions of Wikipedia articles for the problem of text summarization. The dataset consists of over 80k English samples on 6987 topics. We set up a two-phase summarization method — description generation (Phase I) and candidate ranking (Phase II) — as a strong approach that relies on transfer and contrastive learning. For description generation, T5 and BART show their superiority compared to other small-scale pre-trained models. By applying contrastive learning with the diverse input from beam search, the metric fusion-based ranking models outperform the direct description generation models significantly up to ≈ 22 ROUGE in topic-exclusive split and topic-independent split. Furthermore, the outcome descriptions in Phase II are supported by human evaluation in over 45.33% chosen compared to 23.66% in Phase I against the gold descriptions. In the aspect of sentiment analysis, the generated descriptions cannot effectively capture all sentiment polarities from paragraphs while doing this task better from the gold descriptions. The automatic generation of new descriptions reduces the human efforts in creating them and enriches Wikidata-based knowledge graphs. Our paper shows a practical impact on Wikipedia and Wikidata since there are thousands of missing descriptions. Finally, we expect WikiDes to be a useful dataset for related works in capturing salient information from short paragraphs. The curated dataset is publicly available at: https://github.com/declare-lab/WikiDes.

Enhanced Indoor Environmental Quality and the Link to Individual Productivity and Organisational Performance: A Scoping Review

This paper provides a scoping literature review of research methods that seek to measure individual productivity and organisational performance in office buildings containing enhanced green building features and initiatives that focus on Indoor Environmental Quality (IEQ). The paper follows the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) framework and includes thirty-nine academic papers for the period 2000 to 2020. Different research instruments are discussed, including post-occupancy evaluations (POE), longitudinal surveys, and interviews. Furthermore, a narrative focuses on specific measures, including location, amenities, comfort, engagement, individual productivity, and organisational performance. This provides insight into common research approaches and highlights where lesser used research approaches could be applied in the field of green building features and initiatives (GBFIs), including the assessment of individual productivity and organisational performance. Key findings highlight that individual productivity was measured via self-assessment in previous research. At the same time, there has been no research that has successfully measured organisational performance within the context of GBFIs. Gaps have been identified in the literature concerning the relationship between knowledge-based building occupants and measuring/monetising the implementation of GBFIs. Implications of this research indicate that there are common approaches that highlight both strengths and, more importantly, weaknesses concerning linking GBFIs to individual productivity and organisational performance. Addressing weaknesses that predominantly encompass measuring organisational performance creates the opportunity for future research in this field.

Assessing socioeconomic inequalities in cognitive impairment among older adults: a study based on a cross-sectional survey in India

BackgroundThe rapidly aging population is a major concern for countries, especially where cognitive health in older age is poor. The study examined the socioeconomic and health-related factors associated with cognitive impairment among older adults and the contribution of those factors to the concentration of low cognitive functioning among older adults from economically poor households.MethodsData this study were derived from the “Building Knowledge Base on Population Ageing in India” (BKPAI) survey, which was carried out in seven major states of India. The effective sample size for the analysis was 9176 older adults aged 60 years and above. Results from descriptive and bivariate analysis were reported in the initial stage. Multivariable logistic regression analysis was conducted to explore the associations. Additionally, the concentration index and concentration curve were used to measure socioeconomic inequality in cognitive impairment among older adults. Wagstaff decomposition was employed to explore the key contributors in the concentration index.ResultsNearly 60% of older adults suffered from cognitive impairment in the study. The likelihood of cognitive impairment were higher among older adults with a low level of self-perceived income sufficiency [coefficient: 0.29; confidence interval (CI): 0.07- 0.52] compared to older adults with higher levels of perceived income status. Older adults with more than 10 years of schooling were less likely to be cognitively impaired [coefficient: -1.27; CI: − 1.50- -1.04] in comparison to those with no education. Cognitive impairment was concentrated among older adults from households with the lowest wealth quintile (concentration index (CCI): − 0.10: p < 0.05). Educational status explained 44.6% of socioeconomic inequality, followed by 31.8% by wealth status and 11.5% by psychological health. Apart from these factors, difficulty in instrumental activities of daily living (3.7%), caste (3.7%), and perceived income sufficiency to fulfil basic needs (3.0%) explained socioeconomic inequality in cognitive impairment among older adults.ConclusionsFindings suggest that older adults with lower perceived income, lower levels of education, poor physical and mental health, and poor physical and social resources were more likely to be cognitively impaired. Education, wealth and psychological health are major contributors in socioeconomic inequality in late-life cognitive impairment, which may be target areas in future policy formulation to reduce the inequality in cognitive impairment in older Indian adults.

Prevalence and risk factors of fall-related injury among older adults in India: evidence from a cross-sectional observational study

BackgroundFalls and related injuries in older ages have become a major public health problem. This study aims to identify the prevalence of self-reported fall-related injury and to describe risk factors associated with fall-related injury among older adults in India.MethodThe study used data from the "Building Knowledge Base on Population Ageing in India" (BKPAI), which was carried out in seven major states in India (2011). Bivariate and multivariable logistic regression analyses were conducted to examine the prevalence and risk factors of fall-related injury among older people.ResultsThe study found that 3.6% of older adults had a fall-related injury. Older adults with walk difficulty had a significantly higher likelihood of reporting fall-related injuries in comparison to their counterparts [adjusted odds ratio (AOR):1.80; confidence interval (CI): 1.38–2.36]. Older adults who consumed alcohol had significantly higher odds of reporting fall-related injuries than those who did not consume alcohol [AOR: 1.97; CI: 1.31–2.97]. Poor self-rated health was another risk factor for fall-related injury [AOR: 1.24; CI: 1.05–1.61]. Further, older adults with dementia were 2.15 times significantly more likely to report fall-related injuries than older adults with no dementia [AOR: 2.15; CI: 1.03–5.05]. Also, older women compared to men were 98% significantly more likely to report fall-related injury [AOR: 1.98; CI: 1.43–2.75]. The odds of reporting fall-related injury was significantly higher among those who had a secondary level education compared to those with no education [AOR: 1.44; CI: 1.01–2.06].ConclusionsWalking disabilities, alcohol consumption, poor self-rated health, dementia, and female gender were found to be the risk factors for fall-related injury among older adults. The results highlight the importance of improving physical as well as mental health of older individuals including dementia in terms of reducing the risk of experiencing fall-related injury.

Tooth loss and associated self-rated health and psychological and subjective wellbeing among community-dwelling older adults: A cross-sectional study in India

BackgroundLosing teeth has been considered as part of normal aging. However, in developing countries, tooth loss among older adults is shown to be more negatively associated with self-image and quality of life compared to their western counterparts. This study examines the association of tooth loss with self-rated health and psychological and subjective wellbeing among older adults in India.MethodsData were derived from the "Building Knowledge Base on Population Ageing in India" (BKPAI) survey which was carried out in 2011. The final sample size for the analysis was 9231 older adults. Descriptive statistics and bivariate analysis along with binary logistic regression analysis were conducted to fulfil the objective of the study.ResultsA proportion of 12.3% of older adults reported complete tooth loss. It was found that older adults who reported tooth loss were 2.38 times significantly more likely to have poor self-rated health (SRH) [2.38; CI: 1.99,2.83] than older adults who did not report tooth loss. The odds of low psychological health were high among older adults who suffered from tooth loss than their counterparts [OR: 1.59; CI: 1.33,1.91]. Older adults who reported tooth loss had 65% significantly higher odds of low subjective well-being than older adults who did not report tooth loss [OR: 1.65; CI: 1.38,1.97].ConclusionComplete loss of teeth is associated with older individuals’ poor SRH as well as low psychological and subjective well-being, but such a consequence is avoidable by practising the efforts to maintain good oral health.

Evidence-Aware Multilingual Fake News Detection

Due to the rapid growth of the Internet and the subsequent rise of social media users, sharing information has become more flexible than ever before. This unrestricted freedom has also led to an increase in fake news. During the Covid-19 outbreak, fake news spread globally, negatively affecting authorities’ decisions and the health of individuals. As a result, governments, media agencies, and academics have established fact-checking units and developed automatic detection systems. Research approaches focused largely on writing styles, propagation patterns, and building knowledge bases that serve as a reference for fact checking. However, little work has been done to assess the credibility of the source of the claim to be checked. This paper proposes a general framework for detecting fake news that uses external evidence to verify the veracity of online news in a multilingual setting. Search results from Google are used as evidence, and the claim is cross-checked with the top five search results. Additionally, we associate a vector of credibility scores with each evidence source based on the domain name and website reputation metrics. All of these components are combined to derive better predictions of the veracity of claims. Further, we analyze the claim-evidence entailment relationship and select supporting and refuting evidence to cross-check with the claim. The selection free approach yields better detection performance. In this work, we consider as a case study Covid-19 related news. Our framework achieves an F1-score of 0.85 and 0.97 in distinguishing fake from true news on XFact and Constraint datasets respectively. With the achieved results, the proposed framework present a promising automatic fact checker for both early and late detection.

Natural language query formalization to SPARQL for querying knowledge bases using Rasa

The idea of data to be semantically linked and the subsequent usage of this linked data with modern computer applications has been one of the most important aspects of Web 3.0. However, the actualization of this aspect has been challenging due to the difficulties associated with building knowledge bases and using formal languages to query them. In this regard, SPARQL, a recursive acronym for standard query language and protocol for Linked Open Data and Resource Description Framework databases, is a most popular formal querying language. Nonetheless, writing SPARQL queries is known to be difficult, even for experts. Natural language query formalization, which involves semantically parsing natural language queries to their formal language equivalents, has been an essential step in overcoming this steep learning curve. Recent work in the field has seen the usage of artificial intelligence (AI) techniques for language modelling with adequate accuracy. This paper discusses a design for creating a closed domain ontology, which is then used by an AI-powered chat-bot that incorporates natural language query formalization for querying linked data using Rasa for entity extraction after intent recognition. A precision–recall analysis is performed using in-built Rasa tools in conjunction with our own testing parameters, and it is found that our system achieves a precision of 0.78, recall of 0.79 and F1-score of 0.79, which are better than the current state of the art.

Association of self-perceived income status with psychological distress and subjective well-being: a cross-sectional study among older adults in India

BackgroundAs the older population aged 65 and over worldwide, is estimated to increase from 9% in 2019 to 16% in 2050, rapid aging will transform the aspects such as economic security, employment status, and family structure. The effects of lower levels of perceived income and poor socioeconomic status on the mental health of older adults appear to be large and enduring. Therefore, the present study contributes to the literature on understanding the association of socioeconomic conditions and self-perceived income status in particular, with self-assessed mental health outcomes (psychological distress and subjective well-being) among older adults in India.MethodsData for the present study was derived from the Building Knowledge Base on Population Ageing (BKPAI) in India. Bivariate and binary logistic regression analyses were conducted to understand the relationship between socioeconomic status and outcome variables.ResultsAbout 43% of older adults had no income whereas 7% had income but perceived as not sufficient to fulfil their basic needs. Nearly, 9% of older adults were retired from regular employment. Almost 70% older adults had received no pension and nearly 18% of older adults had no asset ownership. It is revealed that older adults with income that is partially sufficient to fulfil their basic needs were 2.23 times [OR: 2.23, CI: 1.75–2.84] and 1.96 times [OR: 1.96, CI: 1.55–2.47] significantly more likely to suffer from psychological distress and low subjective well-being than those who had income which was sufficient to fulfil their basic needs.ConclusionsBy focusing on four target areas such as the income support, education, family oriented initiatives and local or regional policies, the current framework for assessing the mental health among older adults in India can be modified. A move towards a guaranteed pension for eligible older individuals by which they do not have to remain as a financial burden on their children, may reduce their self-perceived economic distress and result in higher levels of wellbeing in older ages. Also, strategies to address socioeconomic disadvantages and gender differentials related to mental health status among older population are urgently needed.

A systematic mapping study on teaching and learning Computational Thinking through programming in higher education

Computational Thinking (CT) through programming in higher education is considered an important skill for students to become problem solvers and thrive in the new digital workplace. Despite the wide interest, a systematic map of CT through programming in higher education is still missing. The aim of this study is twofold. First, we aim to provide a systematic map of the relevant research by identifying the areas and sub-areas of CT through programming teaching and learning in higher education. Second, we aim to investigate these areas based on two dimensions: their evolution over the years and the branches to which CT is applied. For this purpose, we apply a systematic mapping methodology. Main results include the identification of the CT areas of Knowledge Base, Assessment, Learning Strategies, Tools, Factors and Capacity Building. Of these, Knowledge Base, Assessment and Tools have significantly evolved throughout the years, while Capacity Building has only recently emerged. In addition, the introduction of CT to undergraduate students and preservice teachers differs mainly in the tools used and the CT elements that are assessed. The study contributes to the field by providing a structured type of research conducted and identifying gaps and opportunities for future research.

Association of self-perceived income sufficiency with cognitive impairment among older adults: a population-based study in India

BackgroundGreater cognitive performance has been shown to be associated with better mental and physical health and lower mortality. The present study contributes to the existing literature on the linkages of self-perceived income sufficiency and cognitive impairment. Study also provides additional insights on other socioeconomic and health-related variables that are associated with cognitive impairment in older ages.MethodsData for this study is derived from the 'Building Knowledge Base on Population Ageing in India'. The final sample size for the analysis after removing missing cases was 9176 older adults. Descriptive along with bivariate analyses were presented to show the plausible associations of cognitive impairment with potential risk factors using the chi-square test. Also, binary logistic regression analysis was performed to provide the relationship between cognitive impairment and risk factors. The software used was STATA 14.ResultsAbout 43% of older adults reported that they had no source of income and 7.2% had income but not sufficient to fulfil their basic needs. Older adults with income but partially sufficient to fulfil their basic needs had 39% significantly higher likelihood to suffer from cognitive impairment than older adults who had sufficient income [OR: 1.39; OR: 1.21–1.59]. Likelihood of cognitive impairment was low among older adults with asset ownership than older adults with no asset ownership [OR: 0.83; CI: 0.72–0.95]. Again, older adults who work by compulsion (73.3%) or felt mental or physical stress due to work (57.6%) had highest percentage of cognitive impairment. Moreover, older adults with poor self-rated health, low instrumental activities of daily living, low activities of daily living, low subjective well-being and low psychological health were at increased risk for cognitive impairment.ConclusionThe study highlights the pressing need for care and support and especially financial incentives in the old age to preserve cognitive health. Further, while planning geriatric health care for older adults in India, priority must be given to financially backward, with no asset ownership, with poor health status, older-older, widowed, and illiterate older individuals, as they are more vulnerable to cognitive impairment.

Socio-economic and health determinants of preference for separate living among older adults: A cross-sectional study in India.

IntroductionThe living arrangements among the older population form a basic pointer to the care and support of older adults in India, and living with extended kin is clearly differentiated from living separately. This paper attempts to understand the associations between socio-economic and health-related variables with preference for the separate living among older adults in India.Materials and methodsUsing data from Building Knowledge Base on Population Ageing in India (BKPAI), we employed bivariate and probit regressions on a sample of 9540 older adults to fulfil the study objective.ResultsNearly 21% of older adults were living alone/with a spouse. Additionally, those older adults who lived alone/with spouse had specific reasons, i.e. about 14.6% reported that they had no children, 47.3% of older adults had their children away and 15.9% of older adults reported a family conflict. Availability of children is consistently found to be negatively associated with the preference of separate living. Besides, better self-rated health, independence in daily activities, and facing any type of violence were the strongest predictors of preference for separate living. In addition, the background characteristics, including age, sex, education, religion, and ethnicity, were found as significant predictors of living arrangement preference. Preference for co-residential arrangements emerges among older persons who have a feeling of importance within their family.ConclusionPhysical proximity to kin and health conditions, in addition to economic conditions, substantially determine the swing towards separate living among older adults in India. This suggests that attention has to be paid to the demand for specialized care and health services among older adults living separately.

Knowledge-Based Approach to Detect Potentially Risky Websites

Nowadays, fraudulent and malicious websites are emerging as a harmful and very common problem on the Internet. It causes huge money losses and irreparable damage for both companies and particulars. To face this situation, governments have approved multiple law projects. This way, the legality on the Internet is being enforced and sanctions to those offenders who develop illegal or malicious activities are being imposed. However, governments still need a way to simplify the classification of websites into risky or non-risky, since most of this work is manual. This paper presents the DOmains Classifier based on RIsky Websites ( DOCRIW ) framework to detect domains that contain possible fraud or malicious content. It is based on two main components. The first component is a previously built knowledge base containing information from risky websites. The second one complements the system with a binary classifier able to label a website (as risky or not) considering just its domain. The system makes use of web information sources and includes host-based variables. It also applies similarity measures, supervised learning algorithms and optimization methods to enhance its performance. The presented work is experimental, rendering promising outcomes.

Методы и средства построения онтологически управляемых систем приобретения знаний

The article discusses the main existing methods and tools for automating the process of acquiring knowledge, and also presents the concept of an approach to the application of knowledge engineering methods of building the ontology driven knowledge acquisition systems. Automation of the process of production expert system knowledge base building uses the principles of adaptability to the specifics of the application domain and third-party information resources is demonstrated. A distinctive feature of the proposed approach is the active nature of the dialogue within the knowledge extraction system (dialogue script is generated in dynamics). This allows, during communication with an expert, to initiate a natural language dialogue adequate to the features of the problem being solved and focus on simplifying and automating the work of an expert and a knowledge engineer. The tools which allow the knowledge engineer to verify the quality of the developed knowledge base are discussed.

Multimorbidity as a Risk Factor of Elder Abuse/Mistreatment in India: A Cross-Sectional Study.

Globally, elder abuse/mistreatment is a common form of violence against the elderly. This study examines the association between multimorbidity and abuse/mistreatment among the elderly population (60+) in India. Cross-sectional data from the United Nations Population Fund (UNFPA)'s "Building Knowledge Base on Population Aging in India" (BKPAI, 2011) was analyzed. We generated a multimorbidity variable by combining 20 self-reported diagnosed chronic diseases. Bivariate analysis was used to understand the sample distribution and prevalence estimation of elder abuse/mistreatment by multimorbidity and state. Furthermore, multilevel mixed-effect logistic regression was used to examine the association between multimorbidity and elder abuse/mistreatment. The overall prevalence of elder abuse/mistreatment in the study population is 11.4%. The prevalence of elder abuse/mistreatment among elderly with no chronic diseases is 6.01% which increases to 22.7% among elderly with four or more chronic diseases. Furthermore, the result from the multilevel mixed-effect logistic regression showed a close association between multimorbidity and elder abuse. Elderly with two, three, and four or more chronic diseases are 3.02 (CI = 2.33, 3.91, p < .000), 4.16 (CI = 3.02, 5.74, p < .000), and 5.06 (CI = 3.50, 7.31, p <.000) times more likely to experience abuse/mistreatment than elderly with no chronic diseases, respectively. In specific, this association is stronger for the elderly population residing in the urban areas. Furthermore, economic status and educational attainment have a protective role in determining elder abuse/mistreatment in India. In conclusion, multimorbidity has emerged as a significant risk factor of elder abuse/mistreatment in India. Measures to prevent elder abuse should consider the role of multimorbidity.