INTRODUCTION

According to the World Health Organization (2024), 41 million people are killed each year by Noncommunicable diseases (NCDs) which is equivalent to 74% deaths globally and 68.5% in the Philippines NCDs considered as lifestyle related include cardiovascular conditions (hypertension, stroke), diabetes mellitus, lung/chronic respiratory diseases and a range of cancers. Tobacco use, physical inactivity, harmful use of alcohol and unhealthy diet increase the risk of death from noncommunicable diseases. Early identification of individuals who are at risk using lifestyle assessment tools is important in the prevention of these non-communicable diseases. 

OBJECTIVE

The aim of this study was to determine the lifestyle risk profile of an urban community under a Community Oriented Primary Care program.

METHODS

This was a cross-sectional survey conducted in an urban community under a Community-Oriented Primary Care program. Using systematic random sampling, one respondent from the included households completed a structured questionnaire on socio-demographic characteristics, physical assessment, and lifestyle behaviors using a validated Lifestyle Medicine Assessment (LMA) tool. The questionnaire was translated into the Hiligaynon dialect and underwent expert review and pilot testing, demonstrating excellent validity and reliability. Data were analyzed using descriptive and inferential statistics, with a significance level set at p < 0.05.

RESULTS

Eighty-seven among 112 households of the community participated in the study. Demographic profiling revealed that most respondents had above-normal waist-hip ratios, and nearly half had above-normal body mass index (BMI). The overall LMA scores indicated a “Very Good” lifestyle profile (scores 31–40). Among demographic factors, only work status showed a statistically significant association with total LMA scores (p = 0.037). Significant associations were found between specific lifestyle domains and socio-demographic factors. The domain of connectedness was significantly associated with age and educational attainment; nutrition showed significant associations with age, marital status, and income; and substance use was significantly associated with sex and work status.

CONCLUSION

Considering the influence of Lifestyle Behavior on health, especially that of acquiring non-communicable diseases, using lifestyle assessment tools may aid in the formulation of campaigns, projects targeted on the community’s problem. Like in every Family and Community Medicine Residency Programs, COPC programs is one way of using the data gathered on lifestyle behavior in the community. 

Human ; Lifestyle Behavior ; Life Style ; Noncommunicable Diseases