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Context: Multimorbidity is considered as a priority for global health research. It is defined as the coexistence of two or more chronic health conditions in an individual. It is increasingly being recognized as a major concern for primary care physicians due to its huge impact on individual, family, and societal level. Aim: The aim of this study was to find the quantum of gender-related inequalities and determinants of multimorbidity among the elderly people in a rural part of West Bengal. Materials and Methods: This is a cross-sectional study carried out among 246 elderly people (60 years and above) in a community setting from Oct 2017 to Sep 2018. Logistic regression analysis was done to find out the predictors of multimorbidity. Data were analyzed using the SPSS software (version 16.0. Chicago, SPSS Inc.). Results: Approximately 82% of the study subjects were suffering from multi-morbidity with a significant difference between males (80.9%) and females (88.5%). In binary logistics, people of both the genders aged >70 years, who had less than primary level education, had more than three children, whose source of income was from their children (sons/daughters), were dependent on others for daily routine were at high risk of being multimorbid; whereas depression was a significant predictor of multimorbidity in females and not in males. In multivariable analysis, age remained the only significant predictor for both the gender and for females; depression remained significant after adjusting with significant variables in binary logistics. Conclusion: Morbidity screening at each visit, individual as well as family counseling and lifestyle modifications help to cope with the rising burden of multimorbidity at the primary care level. More insight into the epidemiology of multi-morbidity is necessary to take steps to prevent it, lower its burden and align health-care services as per needs.

Context: Household food insecurity (HFI) is considered one of the main risk factors of undernutrition. However, the evidence is not conclusive in our study settings. This study aimed to examine the association between HFI and nutritional status. Materials and Methods: It was a community-based cross-sectional observational study among children of age <5 years and their mothers (n = 257) conducted in a slum of Kolkata, West Bengal, carried out from March to May 2019. Data were analyzed using the Statistical Package for the Social Sciences software (version 16.0. Chicago, SPSS Inc.). Logistic regression analysis was performed to find out the association. Results: The current study found that 72.4% of participants living in food-insecure households and the proportion of underweight, wasting, and stunting among the under-five children found to be 29.9%, 17.8%, and 27.2%, respectively. Bivariate analysis showed wasting and stunting associated with HFI, whereas in multivariable regression, only stunting remained significant. Conclusion and Implications: Food insecurity (FI) remains a predictor of chronic undernutrition (wasting and stunting) highlighting the need for multisectoral strategies and policies to combat FI and multiple forms of malnutrition which will lay the foundation for sustainable and inclusive growth. [ABSTRACT FROM AUTHOR]

Context: Multimorbidity is considered as a priority for global health research. It is defined as the coexistence of two or more chronic health conditions in an individual. It is increasingly being recognized as a major concern for primary care physicians due to its huge impact on individual, family, and societal level., Aim: The aim of this study was to find the quantum of gender-related inequalities and determinants of multimorbidity among the elderly people in a rural part of West Bengal., Materials and Methods: This is a cross-sectional study carried out among 246 elderly people (60 years and above) in a community setting from Oct 2017 to Sep 2018. Logistic regression analysis was done to find out the predictors of multimorbidity. Data were analyzed using the SPSS software (version 16.0. Chicago, SPSS Inc.)., Results: Approximately 82% of the study subjects were suffering from multi-morbidity with a significant difference between males (80.9%) and females (88.5%). In binary logistics, people of both the genders aged >70 years, who had less than primary level education, had more than three children, whose source of income was from their children (sons/daughters), were dependent on others for daily routine were at high risk of being multimorbid; whereas depression was a significant predictor of multimorbidity in females and not in males. In multivariable analysis, age remained the only significant predictor for both the gender and for females; depression remained significant after adjusting with significant variables in binary logistics., Conclusion: Morbidity screening at each visit, individual as well as family counseling and lifestyle modifications help to cope with the rising burden of multimorbidity at the primary care level. More insight into the epidemiology of multi-morbidity is necessary to take steps to prevent it, lower its burden and align health-care services as per needs., Competing Interests: There are no conflicts of interest., (Copyright: © 2022 Journal of Family Medicine and Primary Care.)