BACKGROUND:Older adult cancer survivors are at greater risk of cancer recurrence and other comorbidities that can be prevented through improved diet and weight management. The tertiary prevention needs of rural-dwelling survivors can be even greater, yet little is known about rural and urban differences in lifestyle factors among this high-risk population. OBJECTIVES: To compare dietary patterns of urban and rural cancer survivors and to examine associations of dietary patterns with body mass index (BMI). DESIGN: A secondary analysis was performed of baseline data from the Reach Out to Enhance Wellness (RENEW) trial, a diet and exercise intervention among overweight, long-term (≥5 years), older survivors of colorectal, breast, and prostate cancer. Survivors in the present analysis (n=729) underwent two 45- to 60-minute telephone surveys, which included two 24-hour dietary recalls. Principal components analysis and multivariable general linear models were used to derive dietary patterns and to evaluate associations between dietary patterns and BMI, respectively. RESULTS: Principal components analysis identified three primary dietary patterns among rural dwellers (high sweets and starches, high reduced-fat dairy, cereal, nuts, and fruits, and mixed) and three among urban dwellers (high fruits and vegetables, high meat and refined grains, and high sugar-sweetened beverages). Among rural survivors, greater adherence to the high reduced-fat dairy, cereal, nuts, and fruits pattern was positively associated with lower BMI (P trend <0.05), whereas higher scores on the mixed pattern was associated with greater BMI (P trend <0.05). Greater adherence to the high fruits and vegetables pattern among urban survivors was inversely associated with BMI (P trend <0.05). CONCLUSIONS: Urban and rural differences in dietary intake behavior should be considered in designing public health interventions among the increasing population of older cancer survivors. In addition, targeting overall dietary patterns might be one approach to help reduce the burden of obesity among this population.
RCT Entities:
BACKGROUND: Older adult cancer survivors are at greater risk of cancer recurrence and other comorbidities that can be prevented through improved diet and weight management. The tertiary prevention needs of rural-dwelling survivors can be even greater, yet little is known about rural and urban differences in lifestyle factors among this high-risk population. OBJECTIVES: To compare dietary patterns of urban and rural cancer survivors and to examine associations of dietary patterns with body mass index (BMI). DESIGN: A secondary analysis was performed of baseline data from the Reach Out to Enhance Wellness (RENEW) trial, a diet and exercise intervention among overweight, long-term (≥5 years), older survivors of colorectal, breast, and prostate cancer. Survivors in the present analysis (n=729) underwent two 45- to 60-minute telephone surveys, which included two 24-hour dietary recalls. Principal components analysis and multivariable general linear models were used to derive dietary patterns and to evaluate associations between dietary patterns and BMI, respectively. RESULTS: Principal components analysis identified three primary dietary patterns among rural dwellers (high sweets and starches, high reduced-fat dairy, cereal, nuts, and fruits, and mixed) and three among urban dwellers (high fruits and vegetables, high meat and refined grains, and high sugar-sweetened beverages). Among rural survivors, greater adherence to the high reduced-fat dairy, cereal, nuts, and fruits pattern was positively associated with lower BMI (P trend <0.05), whereas higher scores on the mixed pattern was associated with greater BMI (P trend <0.05). Greater adherence to the high fruits and vegetables pattern among urban survivors was inversely associated with BMI (P trend <0.05). CONCLUSIONS: Urban and rural differences in dietary intake behavior should be considered in designing public health interventions among the increasing population of older cancer survivors. In addition, targeting overall dietary patterns might be one approach to help reduce the burden of obesity among this population.
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