FOOD CONSUMPTION BEHAVIORS AND BODY MASS INDEX AMONG OLDER ADULTS IN MUEANG DISTRICT, LAMPANG PROVINCE, THAILAND

Abstract

This cross-sectional quantitative research aimed to examine dietary behaviors and body mass index (BMI) status, and to analyze factors associated with BMI among older adults in Mueang District, Lampang Province. A convenience sample of 403 older adults aged 60–80 years was surveyed via questionnaires and structured interviews. The research instruments met quality criteria (IOC = 1.00, Cronbach's alpha = 0.72). Data were analyzed using descriptive statistics, correlation coefficients, and multiple regression analysis (Enter method). The results revealed that the majority of participants were female (68.0%), had an education level below high school (73.4%), earned less than 15,000 THB/month (77.9%), and had underlying diseases (66.0%). Regarding BMI status, 47.4% were within the normal range, while 42.4% were overweight, with females having a higher mean BMI than males. Correlation analysis indicated that healthy behaviors, female gender, and underlying diseases were very weakly positively correlated with BMI (r = .137 to .190,  p < .01). Conversely, indirect risk behaviors, age, and physical exercise were very weakly negatively correlated with BMI (r = -.137 to -.180, p < .05). Multiple regression analysis showed that the three-dimension dietary behavior model accounted for 6.1% of the variance in BMI (Adjusted R² = .061, F = 9.784, p < .001). At the item level, healthy behaviors associated with a decreased BMI included daily consumption of meat, milk, eggs, or legumes (B = -.678, β = -.231, p < .001) and drinking 6–8 glasses of clean water daily  (B = -.393, β = -.117, p = .043), whereas eating meals on time (B = .608, β = .148, p = .016) was associated with an increased BMI. For indirect risk behaviors, consumption of fermented foods (B = .639, β = .264,           p < .001) and grilling or roasting cooking methods (B = .345, β = .146, p = .008) were associated with an increased BMI, while purchasing food in advance for storage (B = -.321, β = -.132, p = .007) and caffeinated beverage consumption (B = -.213, β = -.110, p = .024) were associated with a decreased BMI. The direct health-risk behavior model was not statistically significant (p = .237). In conclusion, dietary behaviors and local food culture are associated with older adults' BMI. Local public health agencies should use these findings to design health literacy programs promoting high-quality protein intake and reducing high-sodium foods. However, given the cross-sectional design and convenience sampling, which may underrepresent homebound or bedridden older adults, causal relationships cannot be inferred and findings should be interpreted within the study context.