Associations between dietary patterns and demographics, lifestyle, anthropometry and blood pressure in Chinese community-dwelling older men and women

中国社区居住老年男性和女性的饮食模式与人口统计学特征、生活方式、人体测量学和血压之间的关联

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Abstract

This cross-sectional study examined dietary patterns, and the associations of these patterns with demographics, lifestyle, anthropometry and blood pressure in 3707 Chinese people aged 65 years and above taking part in a population-based cohort study investigating the risk factors for osteoporosis. Baseline dietary data were collected using a validated FFQ. Dietary patterns were identified using factor analysis. Scores were calculated for each pattern. Demographics, lifestyle factors and self-reported hypertension history were collected through a questionnaire. BMI, waist circumference (WC), hip circumference (HC), waist-to-hip ratio, systolic blood pressure and diastolic blood pressure (DBP) were measured. Three dietary patterns were identified, namely 'vegetables-fruit', 'snacks-drinks-milk products' and 'meat-fish'. Participants who were more physically active, more educated, non-smokers and non-drinkers were more likely to have higher 'vegetables-fruit' dietary pattern scores. Current smoking habit and alcohol use were associated with higher 'snacks-drinks-milk products' dietary pattern scores and 'meat-fish' dietary pattern scores. 'Vegetables-fruit' dietary pattern scores were inversely (unstandardised regression coefficient B = -0·60 mmHg, 95 % CI -1·04, -0·16) and 'snacks-drinks-milk products' dietary pattern scores were positively (B = 0·50 mmHg, 95 % CI 0·08, 0·92) associated with DBP in men in multiple regressions. Higher 'meat-fish' dietary pattern scores were associated with higher BMI (B = 0·19 kg/m(2), 95 % CI 0·06, 0·33), waist-to-hip ratio (B = 0·004, 95 % CI 0·002, 0·007) and WC (B = 0·57 cm, 95 % CI 0·18, 0·97) in men, and higher BMI (B = 0·40 kg/m(2), 95 % CI 0·22, 0·57), WC (B = 0·87 cm, 95 % CI 0·39, 1·36) and HC (B = 0·61 cm, 95 % CI 0·26, 0·96) in women in multiple regressions. The influence of demographic and lifestyle characteristics on dietary patterns and the health risks associated with dietary patterns provides insights for the provision of tangible dietary advice to this population.

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