![]() Previous studies found that height and waist circumference were negatively correlated in both genders, although this association was weaker in females. This is particularly important because anthropometry is considered a proxy-measure of biological welfare, and height might be a variable of interest when analyzing obesity status in adults. This is the first study that addressed associations between height and BMI categories in a representative sample of adults. The dietary pattern ‘sugary and fatty foods' was positively correlated with, pastry, chocolate, and sweet desserts. The ‘fish, fruit, and vegetables' dietary pattern was positively correlated with fish, vegetables, and fruit. ![]() The dietary pattern ‘high fat, sugar, and salt' was positively correlated with pastry, chocolate and sweet desserts, other candies, salty snacks, chips, fruit juices, soft drinks, and alcoholic beverages. The ‘soup and starchy foods' dietary pattern was positively correlated with vegetable soup, bread, and pulses. Briefly, the ‘dairy and fruit' dietary pattern was positively correlated with fruit, milk, and dairy products. Based on this list, five dietary patterns were defined by latent trait models, as described elsewhere. Snacks included: fruit bread or sandwiches milk and dairy juices and soft drinks pastry, chocolates or sweet desserts other candies salty snacks chips and alcoholic beverages. The list of foods and beverages included: milk and dairy vegetable soup, vegetables and fruit bread and cereal products meat fish potatoes, rice and pasta pulses pastry, chocolates or sweet desserts at meals. NHS dietary questionnaire included a list of 20 dichotomous questions (‘Yesterday, did you consume any of the following foods?') about usual foods and beverages consumed at meals and snacks in the previous day. Anthropometric, Sociodemographic and Dietary Patterns Therefore, the present report includes a representative sample of 32,644 Portuguese adults. The assessment was performed by trained interviewers and included a questionnaire about social and demographic characteristics, health, and chronic diseases (including obesity). Two levels were defined: the district (townships) and units geographically defined of 240 housings (within the district). A primary sampling unit, based on the housing unit of the population census, was randomly selected within each territorial unit, and subjects living in the sampling unit were surveyed. A representative sample of 41,193 participants from all ages was gathered, distributed over the main Portuguese territorial units: North, Center, Lisbon, Alentejo, Algarve, and the archipelagos of Madeira and Azores. Briefly, sampling procedures included the selection of participants from households during 20, using a multi-stage random probability design (hospitals, prisons, military houses, and community care institutions were excluded). Methodology of the NHS is described elsewhere. This study gathered data from the Fourth Portuguese National Health Survey (NHS), developed by the National Institute of Statistics. Future intervention programs aiming at preventing overweight and obesity should monitor sociodemographic, health and environmental conditions that affect attained height potential. Conclusion: Our results suggest a significant difference in attained height between BMI categories. In females and males, after adjusting for confounders, estimates of attained height decreased when compared to the unadjusted model (β = -0.049, 95% CI = -0.050 -0.049 and β = -0.030, 95% CI = -0.031 -0.029, respectively), although they remained still significant. ![]() As BMI categories increased, height decreased. Adults with normal weight had a significantly higher height (females +7 cm and males +5 cm) when compared to obese class III. Results: BMI categories included underweight and normal weight (46.4%), overweight (37.6%), obese class I and II (15.2%), and obese class III (0.8%). ![]() We performed generalized linear models to assess the differences in attained height across BMI categories analyses were adjusted for age, gender, education, family income per month, proxy reporting information, dietary patterns, and smoking. Sociodemographic and lifestyle characteristics were obtained along with self-reported height and weight. Methods: This is a cross-sectional study with a representative sample of 32,644 Portuguese adults (52.4% females). Objective: To analyze the associations between height and BMI categories in a Portuguese representative sample. ![]()
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