AGEING AND SOCIAL EXCLUSION IN PAKISTAN

Abstract

Despite being a young nation, Pakistan is one of those countries facing demographic changes. Global data reveal a consistent increase in population at age 60 and above. The study was divided into three objectives: firstly, exploring socio-economic and demographic profile of respondents, secondly, studying the patterns of social exclusion among the elderly, and thirdly, observing the relationship between age phenomenon and levels of social exclusion. For data collection, Sohan in Islamabad was selected. A quantitative research approach was applied for data collection, such as face-to-face interviews. A sample of 97 respondents were interviewed for this research. After data collection, data editing, code planning, data entry, data cleaning, and analysis were performed in CSPro and SPSS. The data show 37 percent respondents belonging to age 60-64 years, 25.8 percent were 65-69 years old, and rest were all 70 years and above. Regarding seven dimensions of social exclusion, regression analysis revealed that five out of seven dimensions had non-linear effects regarding age (excluding neighborhood/community and digital exclusion). It was concluded that the mean occurrence of these five dimensions varied not only among age groups but also for age distribution variation (Annexure - B). Inferential analysis of study represents that age and social exclusion had a statistically significant relationship (calculated p-value of MANOVA as .004 in the test Wilks Lambda effect). The age factor mean level was significantly different from each other across all responses in the model, which also concluded that the assumption was approved in the study that prevalence of social exclusion was significantly dependent on age. In contrast, on the next level, Leven’s test of equality of error variances showed that excluding services’ exclusion, all six dimensions of social exclusion error variance were equal among all age groups. Few major findings of the study are; ageing as an independent variable significantly affects social exclusion in old age, covariance matrices of the dependent variables are dependent are equal across age groups, the civic exclusion was disproportionality faced by different age groups – linear line has a positive slope, exclusion from social relations was disproportionality faced by different age groups with highest SD reported by 80 years and above OPs – linear line has a positive slope. This research recommends collecting national-level data of OPs to get a more precise picture, including socio-cultural, economic, political, service provision, health, and well-being, food, housing sections, etc. Without primary numerical or empirical data on this critical topic, it is impossible to develop a national-level policy to handle this issue effectively and efficiently and provide friendly opportunities to the elderly in the country.