Introduction: Elder abuse (abuse/violence/neglect or disrespect as defined by BKPAI data) among elderly is a deserted and overlooked issue especially in developing countries including India. Aim: To assess the elder abuse and its association with socio-demographic factors among elderly population. Materials and Methods: This study comprises data from BKPAI 2011. Descriptive statistics, Chi-square test and binary logistic regression analysis have been used for the following study. Results: A total of 9852 elderly people were included in this study which was carried out in seven states of India. The mean age of the study subjects was 68.04 ± 7.29 years. Among 9852 elderly people 10% (987) were faced elder abuse. In unadjusted odd-ratio the status of elder abuse was found statistically significant with state, type of residence, sex, age group, caste, education, marital status, migration status, occupation, health condition and economic dependency etc. But in binary logistic regression analysis state, type of residence, sex, education, caste and their migration status were found statistically significant with elder abuse. Conclusion: From the result of this study, the existence of "violence", "neglect", and "disrespect" within the society and community is approved. The problems of abuse among older persons were more mental than physical and elderly at getting older, without partner, with bad health condition, having less money or with no security are on more risk of getting abused.

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Singh and Kumar (A family of estimators of population variance using information on auxiliary attribute. Studies in sampling techniques and time series analysis, 2011) and Singh and Malik (Appl Math Comput 235:43-49, 2014) suggested some estimators for estimating the population variance using an auxiliary attribute. This paper suggests a generalized class of estimators based on the adaption of the estimator presented by Koyuncu (Appl Math Comput 218:10900-10905, 2012) for population variance using information on an auxiliary attribute in simple random sampling. The properties of the suggested class of estimators are derived and asymptotic optimum estimator identified with its properties. The large numbers of known estimators are member of the suggested generalized class and it has been shown that proposed generalized class of estimators are more efficient than usual unbiased estimator, ratio, exponential ratio and regression estimator, estimators due to Singh and Malik (Appl Math Comput 235:43-49, 2014) and Singh and Kumar (A family of estimators of population variance using information on auxiliary attribute. Studies in sampling techniques and time series analysis, 2011) using information on auxiliary attribute. In addition, theoretical results are supported by an empirical study and findings are encouraging and support the soundness of present study.