Objective To investigate relationships between dietary patterns and the development of overweight.Design Longitudinal analyses during 12 years of follow-up involved the identification of dietary patterns at baseline using cluster analysis applied to a 145-item semiquantitative food frequency questionnaire.Subjects/setting 737 non-overweight women in the Framingham Offspring/Spouse cohort (mean age, 45 years).Main Outcome Measure Development of overweight (BMI 25) at follow-up.Statistical Analyses Relative risks were calculated using Proc Genmod and multivariate models comprehensively considered potential confounders.Results Five dietary patterns were identified among the cohort at baseline: Heart Healthy, Light Eating, Wine and Moderate Eating, High Fat, and Empty Calorie. Over 12 years, the crude risk of becoming overweight was 29% overall, ranging from 22% of women in the Wine and Moderate Eating cluster to 41% of women in the Empty Calorie cluster. Compared with women who ate a lower-fat, nutritionally varied Heart Healthy diet, women who ate an Empty Calorie diet that was rich in sweets and fats with fewer servings of nutrient-dense fruits, vegetables, and lean food choices were at higher risk for developing overweight [RR 1.4, 95% Cl (0.9, 2.2)] after adjusting for age, smoking status, physical activity, menopausal status, energy intake, intentional dieting, and usual weight pattern. Women who ate an Empty Calorie dietary pattern were also younger and were more likely to smoke.Conclusions Behavioral interventions for weight management and obesity prevention may be enhanced by creatively targeting differences in eating patterns, dietary quality, and other lifestyle behaviors of distinct subgroups of the population.

Study objectives: To examine the internal validity of a dietary pattern analysis and its ability to discriminate clusters of people with similar dietary patterns using independently assessed nutrient intakes and heart disease risk factors. Design and participants: Population based study characterising dietary patterns using cluster analysis applied to data from the semiquantitative Framingham food frequency questionnaire collected from 1942 women ages 18–76 years, between 1984–88. Setting: Framingham, Massachusetts. Main results: Of 1942 women included in the cluster analysis, 1828 (94%) were assigned to one of the five dietary pattern clusters: Heart Healthy, Light Eating, Wine and Moderate Eating, High Fat, and Empty Calorie. Dietary patterns differed substantially in terms of individual nutrient intakes, overall dietary risk, heart disease risk factors, and predicted heart disease risk. Women in the Heart Healthy cluster had the most nutrient dense eating pattern, the lowest level of dietary risk, more favourable risk factor levels, and the lowest probability of developing heart disease. Those in the Empty Calorie cluster had a less nutritious dietary pattern, the greatest level of dietary risk, a heavier burden of heart disease risk factors, and a relatively higher probability of developing heart disease. Cluster reproducibility using discriminant analysis showed that 80% of the sample was correctly classified. The cluster technique was highly sensitive and specific (75% to 100%). Conclusions: These findings support the internal validity of a dietary pattern analysis for characterising dietary exposures in epidemiological research. The authors encourage other researchers to explore this technique when investigating relations between nutrition, health, and disease.

BACKGROUNDReports on the association between alcohol consumption and the risk of lung cancer have been inconsistent. The purpose of this study was to assess this association in a cohort study.METHODSThis study included 4265 participants in the original population-based Framingham Study cohort and 4973 subjects in the offspring cohort. Alcohol consumption data were collected periodically for both cohorts. We used the risk sets method to match control subjects to each case patient based on age, sex, smoking variables, and year of birth. We used a conditional logistic regression model to estimate the relative risk of lung cancer according to alcohol consumption.RESULTSAlcohol consumption was generally light to moderate (i.e., <12 g/day) in both cohorts. During mean follow-ups of 32.8 years in the original and 16.2 years in the offspring cohorts, 269 cases of lung cancer occurred. In categories of total alcohol consumption of 0, 0.1-12, 12.1-24, and greater than 24 g/day, the crude incidence rates of lung cancer were 7.4, 13.6, 16.4, and 25.2 cases per 10 000 person-years, respectively, in the original cohort and 6.6, 4.3, 7.9, and 12.3 cases per 10 000 person-years, respectively, in the offspring cohort. However, after adjustment for age, sex, pack-years of smoking, smoking status, and year of birth in a multivariable conditional logistic regression model, relative risks for lung cancer from the lowest to the highest category of alcohol consumption were 1.0 (referent), 1.0 (95% confidence interval [CI] = 0.5 to 2.1), 1.0 (95% CI = 0.5 to 2.3), and 1.1 (95% CI = 0.5 to 2.3), respectively, in the original cohort and 1.0, 1.4 (95% CI = 0.5 to 3.6), 1.1 (95% CI = 0.3 to 3.6), and 2.0 (95% CI = 0.7 to 5.7), respectively, in the offspring cohort.CONCLUSIONAlcohol consumption among subjects in the Framingham Study, most of whom were light to moderate drinkers, was not statistically significantly associated with the risk of lung cancer.

PURPOSE:To establish the prevalence of nutritional problems and their related socio-demographic and health-related risk factors in the homebound elderly population. METHODS:Subjects included 239 men and women, ages 65 to 105 years. Trained, two-person field teams conducted comprehensive in-home assessments. Medical record reviews assessed co-morbidity and medication use. RESULTS:The majority of these urban study subjects are of very advanced age (mean age 81 years), female (72%), non-white (73%), living alone (51%), of low income (76%), and somewhat socially isolated (26% had no weekly social contact). More older women than men were widowed (60 vs. 33%, respectively) and poor (80 vs. 67%). The disease burden and functional dependency were both high in men and women; 77% had three or more chronic medical conditions; 76% were functionally dependent in one or more ADL's and 95% in one or more IADL's. Poor dietary quality was universal in these older men and women; half or more consumed diets that deviated from recommended standards for at least 13 of the 24 nutritional guidelines studied. Five percent of subjects were underweight (Body Mass Index (BMI) <18.5); 22% were overweight (BMI 25.0-29.9); and 33% were obese (BMI >30.0). Fasting albumin, hemoglobin, and absolute lymphocyte concentrations were borderline to very low in 18-32%. Dyslipidemia was more common in women; however, men and women had similar Total:HDL cholesterol ratios. CONCLUSIONS:Nutritional status is poor in homebound persons of very advanced age with substantial co-morbidity and functional dependency. The complexities of nutritional risk necessitate multi-disciplinary and individualized nutritional intervention strategies.

Objective To validate the use of cluster analysis for characterizing population dietary patterns.Design Cluster analysis was applied to a food frequency questionnaire to define dietary patterns. Independent estimates of nutrient intake were derived from 3-day food records. Heart disease risk factors were assessed using standardized protocols in a clinic setting.Setting Adult women (n = 1,828) participating in the Framingham Offspring-Spouse study.Statistical analyses Age-adjusted mean nutrient intakes were determined for each cluster. Analysis of covariance was used to evaluate pairwise differences in intake across clusters. Compliance with published recommendations was determined for selected heart disease risk factors. Differences in age-adjusted compliance across clusters were evaluated using logistic regression.Results Cluster analysis identified 5 distinct dietary patterns characterized by unique food behaviors and significantly different nutrient intake profiles. Patterns rich in fruits, vegetables, grains, low-fat dairy, and lean protein foods resulted in higher nutrient density. Patterns rich in fatty foods, added fats, desserts, and sweets were less nutrient-dense. Women who consumed an Empty Calorie pattern were less likely to achieve compliance with clinical risk factor guidelines in contrast to most other groups of women.Conclusions Cluster analysis is a valid tool for evaluating nutrition risk by considering overall patterns and food behaviors. This is important because dietary patterns appear to be linked with other health-related behaviors that confer risk for chronic disease. Therefore, insight into dietary behaviors of distinct clusters within a population can help to design intervention strategies for prevention and management of chronic health conditions including obesity and cardiovascular disease.

Objective To estimate population nutrient intake levels and to assess adherence to current dietary recommendations for health promotion and disease prevention.Design Cross-sectional analysis of nutrient intake estimated from 3-day food records. Median macronutrient and micronutrient intake levels for men, women, and the total population are reported along with the proportions of men and women who achieved intakes compatible with nutrient goals defined by published guidelines.Setting Adult participants (2,520: 1,375 women and 1,145 men) in the Framingham Offspring-Spouse Study surveyed between 1991 and 1995.Statistical analyses chi(2) Analyses were used to test for gender differences in the proportions of persons who had intakes that met nutrient guidelines.Results Population intake levels of certain key nutrients, including total and saturated fat, appear to be approaching recommended levels. High proportions of the Framingham population (70% or more) met current recommendations for intakes of protein, polyunsaturated and monounsaturated fat, cholesterol, alcohol, vitamins C and B-12, and folacin. About half or fewer met guidelines for carbohydrate; total and saturated fat; fiber; beta carotene; vitamins A, E, and B-6; calcium; and sodium. Important gender differences in the proportion of those meeting nutrient guidelines were observed for 12 of the 18 nutrients examined, including carbohydrate; total, saturated, and monounsaturated fat, cholesterol; fiber, sodium; calcium; and several vitamins.Conclusion Although progress has been made toward achieving population adherence to preventive nutrition recommendations, large proportions of adults fall short of guidelines for some key nutrients. Differences in adherence rates between men and women suggest areas for gender-specific, targeted nutrition messages and behavioral interventions.

LEARNING OUTCOME:To identify key nutrients to target in nutrition interventions designed specifically for younger or older adults.