Dietary patterns and relationship to obesity-related health outcomes and mortality in adults 75 years of age or greater.

BACKGROUND: The prevalence of obesity-related adverse health outcomes is increasing among older adults. Because it is thought that nutrition plays an important role in successful aging, there has been considerable interest in the association between dietary patterns of older adults and obesity-related health outcomes. OBJECTIVE: This study examined the association between dietary patterns and mortality and prevalence of obesity-related health outcomes, namely cardiovascular disease (CVD), type 2 diabetes mellitus, hypertension, and metabolic syndrome (MetSyn), over a 5-year follow-up period in adults aged 75 years or greater. DESIGN: A longitudinal observational study with cross-sectional dietary assessment. SETTING: Rural Central Pennsylvania. PARTICIPANTS: Community-dwelling older adults (N = 449; 76.5 years old; 57% female). MEASUREMENTS: Multiple, unannounced, 24-hour dietary recalls were used to collect dietary intake. Cluster analysis was used to derive dietary patterns. Prevalence of CVD, diabetes mellitus, hypertension, and MetSyn was extracted from outpatient electronic medical records. Logistic regression was used to examine the associations between dietary patterns and health outcomes and mortality. RESULTS: 'Sweets and Dairy', 'Health-Conscious' and 'Western' dietary patterns were identified. Compared to the 'Health-Conscious' pattern, those in the 'Sweets and Dairy' pattern had increased odds of hypertension over the follow-up period; adjusted odds ratio (95% CI) was 2.18 (1.11-4.30). No significant associations were found for CVD, diabetes mellitus, MetSyn or mortality with dietary patterns. CONCLUSIONS: These findings support the potential value of healthy dietary patterns in the management of hypertension in older adults. We did not observe any other strong associations between dietary patterns and health outcomes or mortality in persons ≥ 75 years of age; thus failing to support the use of overly restrictive diet prescriptions for older persons, especially where food intake may be inadequate.

Dietary patterns and diet quality among diverse older adults: the University of Alabama at Birmingham Study of Aging.

OBJECTIVES: To characterize dietary patterns among a diverse sample of older adults (≥ 65 years). DESIGN: Cross-sectional. SETTING: Five counties in west central Alabama. PARTICIPANTS: Community-dwelling Medicare beneficiaries (N=416; 76.8 ± 5.2 years, 56% female, 39% African American) in the University of Alabama at Birmingham (UAB) Study of Aging. MEASUREMENTS: Dietary data collected via three, unannounced 24-hour dietary recalls was used to identify dietary patterns. Foods were aggregated into 13 groups. Finite mixture modeling (FMM) was used to classify individuals into three dietary patterns. Differences across dietary patterns for nutrient intakes, sociodemographic, and anthropometric measurements were examined using chi-square and general linear models. RESULTS: Three dietary patterns were derived. A "more healthful" dietary pattern, with relatively higher intakes of fruit, vegetables, whole grains, eggs, nuts, legumes and dairy, was associated with lower energy density, higher quality diets as determined by healthy eating index (HEI)-2005 scores and higher intakes of fiber, folate, vitamins C and B6, calcium, iron, magnesium, and zinc. The "western-like" pattern was defined by an intake of starchy vegetables, refined grains, meats, fried poultry and fish, oils and fats and was associated with lower HEI-2005 scores. The "low produce, high sweets" pattern was characterized by high saturated fat, and low dietary fiber and vitamin C intakes. The strongest predictors of better diet quality were female gender and non-Hispanic white race. CONCLUSION: The dietary patterns identified may provide a useful basis on which to base dietary interventions targeted at older adults. Examination of nutrient intakes regardless of the dietary pattern suggests that older adults are not meeting nutrient recommendations and should continue to be encouraged to choose high quality diets.

Prenatal diagnosis of de novo interstitial deletion of proximal 4q by maternal serum screening for Down syndrome.

Deletion of the proximal portion of chromosome 4q is apparently rare. To our knowledge, prenatal diagnosis of the interstitial deletion of 4q12-21.1 has never been reported. We present a prenatal case of 4q deletion in association with a positive Down syndrome screening test of an elevated maternal serum free beta human chorionic gonadotrophin (beta-hCG) level. The prenatal sonogram revealed intra-uterine growth retardation (IUGR) and shortening of the femur. Facial dysmorphism included micrognathia, depressed nasal bridge and low-set ears, these anomalies were evident at the postnatal examination. All of the anomalies were consistent with those described in proximal 4q deletion syndrome. Our case suggests that chromosome studies may be indicated for patients with high maternal serum free beta-hCG and IUGR in the early second trimester.

Unsupervised query-based learning of neural networks using selective-attention and self-regulation.

Query-based learning (QBL) has been introduced for training a supervised network model with additional queried samples. Experiments demonstrated that the classification accuracy is further increased. Although QBL has been successfully applied to supervised neural networks, it is not suitable for unsupervised learning models without external supervisors. In this paper, an unsupervised QBL (UQBL) algorithm using selective-attention and self-regulation is proposed. Applying the selective-attention, we can ask the network to respond to its goal-directed behavior with self-focus. Since there is no supervisor to verify the self-focus, a compromise is then made to environment-focus with self-regulation. In this paper, we introduce UQBL1 and UQBL2 as two versions of UQBL; both of them can provide fast convergence. Our experiments indicate that the proposed methods are more insensitive to network initialization. They have better generalization performance and can be a significant reduction in their training size.

VLSI circuit placement with rectilinear modules using three-layer force-directed self-organizing maps.

In this paper, a three-layer force-directed self-organizing map is designed to resolve the circuit placement problem with arbitrarily shaped rectilinear modules. The proposed neural model with an additional hidden layer can easily model a rectilinear module by a set of hidden neurons to correspond the partitioned rectangles. With the collective computing from hidden neurons, these rectilinear modules can correctly interact with each other and finally converge to a good placement result. In this paper, multiple contradictory criteria are accounted simultaneously during the placement process, in which, both the wire length and the module overlap are reduced. The proposed model has been successfully exploited to solve the time consuming rectilinear module placement problem. The placement results of real rectilinear test examples are presented, which demonstrate that the proposed method is better than the simulated annealing approach in the total wire length. The appropriate parameter values which yield good solutions are also investigated.