Population Institute

ABSTRACT

Globally, one-person households (OPHs), or people who live alone, are the fastest growing type of households. In the Philippines, there is also a notable increase in the number of people living alone over the past several decades. This study investigates the growing number of one-person households in the country by examining their typology and their healthcare utilization. This analysis employed data from the 2017 National Health and Demographic Survey (NDHS).

Results revealed that one-person households accounted for 9.2% of the total number of households in 2017. Cluster analysis also produced five different clusters of people living alone in the country. These clusters include: 1) younger never married males; 2) currently married or separated adult males; 3) older widowed males; 4) older widowed females; and 5) other adult females. These clusters vary demographically and by their socioeconomic, geographic and health characteristics that point to their heterogeneity. Meanwhile, binomial hierarchical regression using predisposing, enabling and need factors adapted from the Andersen Behavioral Model of Use of Health Services showed six significant determinants of healthcare utilization among OPHs. Specifically, being female, having insurance from HMOs, belonging to the richest wealth bracket, living in a rural area, and having been sick 30 days prior to the survey were found to raise the probability of seeking health services among solitary dwellers. In contrast, having GSIS/SSS membership was linked to lower likelihood of using health services. Other factors such as age group, marital status, education, and region of residence were not significant predictors of healthcare utilization among people living alone.

The number of one-person households in the Philippines is on the rise and will continue to rise given recent changes in the demographic structure and composition in the country. The findings of this study can aid other researchers and duty-bearers in ensuring that this population are targeted and integrated in demographic accounts, policy response, and health safety nets.