Qinhuangdao City's Elderly Care Industry Planning Based on the Least Squares Method

Yaqiao Yang

doi:10.54097/r6kccs26

Authors

Yaqiao Yang

DOI:

https://doi.org/10.54097/r6kccs26

Keywords:

Aging Population, Least Square Method, Elderly Care Industry, Planning

Abstract

This study focuses on the planning of elderly care industry in Qinhuangdao City, utilizing the least squares method to conduct predictive analysis of population aging data, aiming to provide scientific basis for elderly care industry development. The research collected demographic data from 2006 to 2023 in Qinhuangdao City, including birth population, population aged over 60, immigration/emigration population, and permanent resident population. These datasets exhibited distinct linear or exponential trends. Through linear regression analysis using MATLAB, predictions indicate that the population aged over 60 will increase to 931,250 within the next five years, accompanied by required increments of 1,403 elderly care beds and 3,672 medical beds. Considering current shortages in elderly care and medical bed resources, actual future demand may exceed these projections. Recommendations include: increasing government fiscal budgets for elderly services, reducing tax burdens, advancing smart home-based elderly care bed construction, encouraging enterprise renovation of elderly care facilities, and promoting integrated medical-care bed supplies. Additionally, implementing artificial intelligence (AI) technologies to develop intelligent bed management systems could enhance resource utilization efficiency. The study emphasizes that addressing aging population challenges requires countries to refine policies according to national conditions, support elderly care industry and medical service development, and ensure comprehensive care for elderly populations.

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