Summary of the methodological constructs of the four frailty indexes compared.

<p>FI-SOF: Frailty Index derived from the Study of Osteoporotic Fractures;</p><p>FI-CD: Frailty Index based on cumulative deficits;</p><p>FI-CGA: Frailty Index based on a Comprehensive Geriatric Assessment;</p><p>ADL: activities of daily living;</p><p>IADL: instrumental activities of daily living;</p><p>SPMSQ: Short Portable Mental Status Questionnaire;</p><p>CIRS: Cumulative Illness Rating Scale;</p><p>MNA: Mini Nutritional Assessment;</p><p>ESS: Exton-Smith Scale;</p><p>MPI: Multidimensional Prognostic Index.</p

Pre-matching baseline characteristics of community-dwelling older patients with diabetes mellitus according to statin use.

<p>VCOG: cognitive status; VIP: Nursing Care Needs; VPIA: pressure sores risk; VADL: activities of daily living; VMOB: mobility; VSOC: social support; MPI: Multidimensional Prognostic Index</p><p>MPI-SVaMA: Multidimensional Prognostic Index based on the Standardized Multidimensional Assessment Schedule for Adults and Aged Persons</p><p>* Number of all medications prescribed within one year before patient’s enrollment</p><p>Pre-matching baseline characteristics of community-dwelling older patients with diabetes mellitus according to statin use.</p

Risk of one-month and one-year all-cause mortality according to the four frailty instruments in hospitalized older patients.

<p>*continuous variables.</p><p>**p-values obtained fitting univariate proportional hazard regression models, accounting for clustering due to centre effect.</p><p>HR: hazard ratio; CI: confidence intervals; FI-SOF: Frailty Index derived from the Study of Osteoporotic Fractures; FI-CD: Frailty Index based on cumulative deficits; FI-CGA: Frailty Index based on a Comprehensive Geriatric Assessment; MPI: Multidimensional Prognostic Index.</p

Comparison of the areas under the receiver operating characteristic (ROC) curves of the four frailty instruments compared.^*

<p>AUC: areas under curve; SE: standard error; CI: confidence interval; MPI: Multidimensional Prognostic Index; FI-SOF: Frailty Index derived from the Study of Osteoporotic Fractures; FI-CD: Frailty Index based on cumulative deficits; FI-CGA: Frailty Index based on a Comprehensive Geriatric Assessment.</p><p>*AUCs were assessed by crude and adjusted logistic regression models, accounting for clustering due to centre effect.</p

Baseline characteristics of community-dwelling older patients with diabetes mellitus divided according to their Multidimensional Prognostic Index (MPI) grade based on the Standardized Multidimensional Assessment Schedule for Adults and Aged Persons (SVaMA).

<p>VADL: activities of daily living; VCOG: cognitive status; VIP: Nursing Care Needs; VMOB: mobility; VPIA: pressure sores risk; VSOC: social support</p><p>* Number of all medications per month, taken before the patient’s enrollment</p><p>^ ev/py: events/person-years, ir%: incidence rate (number of events per 100 person-years)</p><p>Baseline characteristics of community-dwelling older patients with diabetes mellitus divided according to their Multidimensional Prognostic Index (MPI) grade based on the Standardized Multidimensional Assessment Schedule for Adults and Aged Persons (SVaMA).</p

Subgroups of hospitalized older patients where different frailty indexes showed a significant different predictive discriminatory power for one-year all-cause mortality.^*

<p>AUC: areas under curve; SE: standard error; CI: confidence interval; ADL: activities of daily living; MPI: Multidimensional Prognostic Index; FI-SOF: Frailty Index derived from the Study of Osteoporotic Fractures; FI-CD: Frailty Index based on cumulative deficits; FI-CGA: Frailty Index based on a Comprehensive Geriatric Assessment; IADL: instrumental activities of daily living; SPMSQ: Short Portable Mental Status Questionnaire; CIRS: Cumulative Illness Rating Scale;</p><p>MNA: Mini Nutritional Assessment.</p><p>*AUCs were assessed by crude and adjusted logistic regression models, accounting for clustering due to centre effect.</p

Baseline characteristics of hospitalized older patients according to gender.

<p>*continuous variables;</p>†<p>categorical variables; pm = person-month; py = person-years; ir = incidence rate.</p><p>**p-values obtained fitting generalized linear mixed-effects models, using variable rank values, accounting for clustering due to centre effect.</p>††<p>Excluding cerebrovascular disease.</p><p>FI-SOF: Frailty Index derived from the Study of Osteoporotic Fractures; FI-CD: Frailty Index based on cumulative deficits; FI-CGA: Frailty Index based on a Comprehensive Geriatric Assessment; ADL: activities of daily living; IADL: instrumental activities of daily living; SPMSQ: Short Portable Mental Status Questionnaire; CIRS: Cumulative Illness Rating Scale; MNA: Mini Nutritional Assessment;</p><p>ESS: Exton-Smith Scale; MPI: Multidimensional Prognostic Index.</p

Table_1_Dietary Customs and Social Deprivation in an Aging Population From Southern Italy: A Machine Learning Approach.DOCX

BackgroundDiet and social determinants influence the state of human health. In older adults, the presence of social, physical and psychological barriers increases the probability of deprivation. This study investigated the relationship between social deprivation and eating habits in non-institutionalized older adults from Southern Italy, and identified foods and dietary habits associated with social deprivation.MethodsWe recruited 1,002 subjects, mean age 74 years, from the large population based Salus in Apulia Study. In this cross-sectional study, eating habits and the level of deprivation were assessed with FFQ and DiPCare-Q, respectively.ResultsDeprived subjects (n = 441) included slightly more females, who were slightly older and with a lower level of education. They consumed less fish (23 vs. 26 g), fruiting vegetables (87 vs. 102 g), nuts (6 vs. 9 g) and less “ready to eat” dishes (29 vs. 33 g). A Random Forest (RF) model was used to identify a dietary pattern associated with social deprivation. This pattern included an increased consumption of low-fat dairy products and white meat, and a decreased consumption of wine, leafy vegetables, seafood/shellfish, processed meat, red meat, dairy products, and eggs.ConclusionThe present study showed that social factors also define diet and eating habits. Subjects with higher levels of deprivation consume cheaper and more readily available food.</p

New genome-wide significant genes associated with AD in the vicinity of recently reported single SNP genome-wide significant hits[9], [19].

<p>Gene-wide p-values are shown for those genes with p<2.5×10⁻⁶ for which the best single-SNP p-value in that gene is greater than 5×10⁻⁸ in the combined Stage 1 and Stage 2 sample. Previously reported genes<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094661#pone.0094661-Harold1" target="_blank">[4]</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094661#pone.0094661-Seshadri1" target="_blank">[8]</a> ± 0.5 Mb around them are excluded.</p><p>Gene-wide p-values in the combined Stage 1 and Stage 2 sample obtained by combining the p-values from the Stage 1 with those from the Stage 2 using Fisher's method. The LD between rs1476679 (chr7∶100,004,446) reported by IGAP <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094661#pone.0094661-Lambert2" target="_blank">[9]</a> and the best SNP in ZNF3 is r² = 0.16. The LD between rs10838725 (chr11: 47,557,871) reported by IGAP <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094661#pone.0094661-Lambert2" target="_blank">[9]</a> and the best SNPs in the region on chr 11 in the table are r² = 0.3 and 0.88 for <i>NDUFS3</i> and <i>MTCH2</i> respectively.</p

Overrepresentation of significant loci, excluding regions of 0.5[4]–[8] and Stage 1 IGAP genes[9], [19] containing genome-wide significant SNPs.

<p>The observed number of genes is calculated by combining significant loci within 0.5 Mb into one signal. The APOE region is excluded (CHR19; 44,411,940–46,411,945bp). The total number of genes after exclusions is 24,849.</p