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Tables and Figures Sample Clauses

Tables and FiguresTable 1A - Demographic characteristics of the Co-Vaccinations*~ weighted sample stratified by co-vaccination Total sample^ T & M & H T & M T & H M & H T / M / H p-value status and sex (female) (weighted %) % % % % %
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Tables and Figures. 32 Depression is the leading cause of disability and the fourth leading contributor to the global burden of disease and is recognized as an important cause of morbidity and mortality worldwide (1,2). This disorder is the most common type of mental illness, affecting more than 26% of the U.S. adult population (3) and is characterized as a mental disorder associated with a range of emotional, cognitive, and physical behavioral symptoms including loss of interest or pleasure, feelings of guilt, disturbed sleep or appetite, low energy, and poor concentration (2,4). Depressive symptoms interfere with daily life and can contribute to personal adverse health effects (4,5). Women are twice as likely as men to report a lifetime history of major depressive episodes (1). According to the 2009-2012 National Health and Nutrition Examination Survey (NHANES), among a population of 18-39 year old, the prevalence of those displaying significant depressive symptoms was 9.3% in women compared to 5.8% in men (6). Biological processes are thought to be involved in the predisposition of women to depression, including genetically determined vulnerability and hormonal fluctuations (7). Psychosocial events, such as role-stress and sex-specific socialization, are considered to increase the vulnerability of women to depression (7). Depression among 50% of reproductive aged women is undiagnosed and untreated due to high cost, opposition to treatment, and stigma related to perceived mental illness in society (1). Women with depression are at a high risk for adverse reproductive outcomes, including lower fertility and negative pregnancy outcomes (e.g., preterm births and low birth weight infants), and impaired maternal functioning and bonding (1,8,9). Nutrition can play a key role in the onset as well as the severity and duration of depression (10,11). Evidence has suggested that low folate levels may play an additional role in the risk of depression. (12–14). Folate is a B-vitamin that is derived from diet or supplementation. Dietary folate is found in green leafy vegetables, legumes, beans, liver, citrus fruits, and yeast (15). Depressed patients have consistently been found to have lower serum folate concentrations, and patients with very low folate levels were associated with higher depression scores than patients with normal folate levels (12,16). Folate plays an important role in critical brain metabolic pathways (12), this vitamin is involved in the methylation processes and the...
Tables and FiguresFigure 1: Conceptual Framework of Xxxxx Caused by 4 Conscientious Objection to Abortion Provision Figure 2: Map of Uruguay 18 Figure 3: Scale Model of Gynecologist Decision-Making 43 Regarding Abortion Provision in Montevideo, Uruguay Table 1: Quotes Supporting Gynecologist Positions toward Abortion in Each Category 44 In October of 2012 Uruguay enacted Law 18.987, one of the most liberal abortion policies in Latin America, decriminalizing (removing criminal punishments for) first-trimester abortions for any reason, up to 14 weeks gestational age in cases of rape or incest, and at any time for fetal malformations incompatible with life or to save the life of the mother (Chamber of Representatives, 2012). Although this law was meant to expand access to abortion and reduce maternal health complications associated with clandestine abortions, several potential barriers to increased access have been identified. One serious barrier to abortion access is provider’s conscientious objection to abortion. Under Law 18.987 gynecologists and health care organizations with religious or moral objections to abortion have the right to abstain from providing legal abortions. According to Uruguay’s Ministry of Health, approximately 30% of gynecologists nationwide are registered as conscientious objectors to abortion provision. In some rural regions, 100% of gynecologists have registered (Presidencia de la República del Uruguay, 2013). High levels of provider conscientious objection can seriously impede patients’ access to abortion services by delaying provision of services and creating other barriers such as the need to travel or to use more expensive private clinics (Xxxxxxx et al., 2013). Despite widespread use of conscientious objection to abortion and its potential impact on access to abortion services, little is known about gynecologists’ decision-making process or rationale behind abortion provision in Uruguay. The purpose of this study is to address this knowledge gap in Montevideo, Uruguay in order to mitigate against issues arising from conscientious objection and to determine gynecologist attitudes towards legal abortion provision. Abortion is highly restricted in the majority of countries in Latin America. In part due to this restriction, the region’s unsafe abortion rate is the highest in the world (32 per 1,000 women) (Guttmacher Institute, 2012). Legal restrictions on abortion are known to cause high levels of unsafe abortion and there is a proven link between ...
Tables and FiguresDistribution of the cycle threshold (CT) of positive admission nasal MRSA screens (Xpert MRSA assay) among Atlanta veterans (n = 205) Table 1: Baseline patient characteristics among MRSA colonized and non-colonized (N = 346) Nasal Colonization Status Age (years) Gender Race Clinical Characteristics Co-morbidities Subsequent Infection Readmission during 4 years of follow up Table 3. Baseline patient characteristics among patients without MRSA colonization, low MRSA colonization burden, and high MRSA colonization burden (N = 346) Colonization Status Age (years) Gender Race Clinical Characteristics Co-morbidities Table 4. Univariate analysis of potential risk factors for subsequent MRSA infection in veterans (n=346) Clinical Characteristics Table 5. Multivariate Analysis of predictors of subsequent MRSA infection among veterans
Tables and FiguresFigure 1. Diagram of randomized assignment of kebeles into full intervention, partial intervention, and control group. Image retrieved from Emory University Institutional Review Board proposal for the Quality Diets for Better Health cluster-randomized controlled trial. OFSP, orange-fleshed sweet potatoes. Table 1. Descriptive characteristics of the 605 households enrolled in the QDBH longitudinal study in SNNPR, Ethiopia1 Overall Full Partial Control P -difference2 n 605 182 154 269 Woredas < 0.0001 Xxxxx Xxxxx 244 (40.3) 90 (49.5) 96 (62.3) 58 (21.6) Dila Zuria 245 (40.5) 62 (34.1) 36 (23.4) 147 (54.7) Wonago 19.17 (19.2) 30 (16.5) 22 (14.3) 64 (23.8) Maternal age, years 26.04 ± 1.48 26.26 ± 4.99 25.91 ± 3.02 25.97 ± 7.27 < 0.0001 Maternal education, n(%) 0.02 No formal education 185 (30.6) 47 (25.8) 33 (21.4) 105 (39.0) 1 - 6 y 212 (35.0) 2 (38.5) 68 (44.2) 74 (27.5) 7 - 12 y 198 (32.7) 64 (35.2) 53 (34.4) 81 (30.1) Technical or vocational 8 (1.3) 1 (0.6) 0 (0.0) 7 (2.6) University 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) Missing 2 (0.3) 0 (0.0) 0 (0.0) 2 (0.7) Maternal occupation, n (%) < 0.0001 Does not work / housewife 473 (78.2) 141 (77.5) 109 (70.8) 223 (82.9) Agriculture 65 (10.7) 22 (12.1) 21 (13.6) 22 (8.2) Professional or technical 8 (1.3) 0 (0.0) 4 (2.6) 4 (1.5) Other source of income 58 (9.6) 19 (10.4) 20 (13.0) 19 (7.1) Missing 1 (0.17) 0 (0.0) 0 (0.0) 1 (0.4) Head of household education, n(%) 0.27 No education 48 (7.9) 11 (6.0) 5 (3.3) 32 (11.9) 1 - 6 y 168 (27.8) 52 (28.6) 53 (34.4) 63 (23.4) 7 - 12 y 354 (58.5) 115 (63.2) 83 (53.9) 156 (58.0) Technical or vocational 22 (3.6) 3 (1.7) 9 (5.8) 10 (3.7) University 10 (1.7) 1 (0.6) 3 (2.0) 6 (2.2) Missing 3 (0.5) 0 (0.0) 1 (0.7) 2 (0.7) Head of household occupation, n (%) 0.01 Does not work 8 (1.3) 2 (1.1) 1 (0.7) 5 (1.9) Agriculture 391 (64.7) 126 (69.2) 96 (62.3) 169 (62.8) Professional or technical 68 (11.2) 11 (6.04) 23 (14.9) 34 (12.6) Other source of income 137 (22.6) 43 (23.6) 34 (22.1) 60 (22.3) Missing 1 (0.2) 0 (0.0) 0 (0.0) 1 (0.4) Household wealth quintile, n (%) 0.02 Lowest 121 (20.0) 41 (22.5) 20 (13.0) 60 (22.3) Second 121 (20.0) 38 (20.9) 37 (24.0) 46 (17.1) Middle 121 (20.0) 31 (17.0) 37 (24.0) 53 (19.7) Fourth 121 (20.0) 30 (16.5) 33 (21.4) 58 (21.6) Highest Household food insecurity at baseline3, n (%) 121 (20.0) 42 (23.1) 27 (17.53) 52 (19.3) 0.05 Food Secure 132 (21.8) 40 (22.0) 33 (21.4) 59 (21.9) Some indication of insecurity 172 (28.4) 45 (24.7) 45 (29.2) 82 (30.5) Moderate insec...
Tables and Figures. Family and Self-Care Framework24 *permission to reprint (Appendix A) Figure 2. ACHD Self-Care Search Terms
Tables and FiguresTable 1. Current demographic, substance use and mental health characteristics of adult opioid users, by opioid use type—NSDUH 2013-2014 All opioids NMPO-only Heroin-only NMPO heroin co- NMPO- only vs Heroin- only vs N=4,496 N=4,076 N=133 use co-use co-use Wt% (SE) Wt% (SE) Wt% (SE) N=287 p-value p-value Wt% (SE) Sex Male 54.65 (1.15) 53.41 (1.21) 63.51 (5.67) 70.99 (3.15) <0.001 0.23 Female 45.35 (1.15) 46.59 (1.21) 36.49 (5.67) 29.01 (3.15) Age 18-25 30.12 (0.90) 29.93 (0.94) 27.97 (4.98) 34.12 (3.70) <0.001 <0.05 26-34 26.06 (1.15) 24.89 (1.16) 26.62 (5.29) 44.73 (4.40) 35-49 24.03 (0.98) 24.66 (1.04) 23.85 (5.33) 13.96 (3.04) 50+ 19.78 (1.33) 20.52 (1.38) 21.56 (5.56) 7.19 (2.57) Race/ethnicity Non-Hispanic White 66.30 (1.05) 65.42 (1.12) 67.67 (5.91) 79.96 (3.06) <0.01 0.19 Non-Hispanic Black 11.51 (0.80) 11.67 (0.84) 17.81 (5.02) 6.36 (2.25) Non-Hispanic other 6.16 (0.56) 6.42 (0.59) 3.46 (2.21) 3.20 (1.31) Hispanic 16.03 (0.89) 16.50 (0.94) 11.06 (4.03) 10.48 (2.21) Rurality Non-urban 14.81 (0.95) 15.34 (1.01) 9.33 (2.82) 8.41 (1.88) <0.01 0.77 Urban 85.19 (0.95) 84.66 (1.01) 90.67 (2.82) 91.59 (1.88) Education Less than HSa 17.65 (0.84) 17.32 (0.90) 15.34 (3.75) 24.03 (3.22) <0.001 0.44 HS graduate/ Some 61.63 (1.16) 60.79 (1.21) 76.92 (5.06) 68.82 (3.51) collegea College grad 20.72 (1.03) 21.89 (1.08) 7.73 (3.23) 7.15 (1.95) Employment status Full-time 50.91 (1.12) 52.19 (1.18) 39.02 (5.88) 35.15 (4.15) <0.001 0.06 Part-time 17.07 (0.84) 17.01 (0.88) 18.32 (4.38) 17.57 (3.48) Unemployed 9.83 (0.67) 9.19 (0.71) 8.30 (2.72) 20.90 (3.18) Not in labor force 22.18 (0.94) 21.61 (0.99) 34.36 (6.10) 26.38 (3.57) Marital status Married 31.23 (1.26) 33.00 (1.32) 8.74 (3.62) 11.87 (0.45) <0.001 0.79 Divorced/Sep/Widowed 15.99 (1.03) 16.04 (1.09) 15.88 (4.30) 15.20 (2.97) Never married 52.79 (0.90) 50.96 (0.94) 75.39 (4.36) 72.93 (2.96) Health insurance coverage Covered 75.46 (1.10) 76.52 (1.14) 65.51 (5.68) 62.34 (4.00) <0.01 0.67 Not covered 24.54 (1.10) 23.48 (1.14) 34.49 (5.68) 37.66 (4.00) Substance abuse and mental health Any tobacco use 65.24 (1.16) 62.80 (1.27) 88.62 (4.81) 94.84 (2.33) <0.001 0.26 Alcohol abuse 13.90 (0.88) 14.22 (0.93) 6.13 (2.57) 12.05 (2.56) 0.731 0.10 Major depressive episode 16.08 (0.92) 15.28 (0.91) 22.43 (4.81) 26.56 (3.54) <0.05 0.48 Psychological distress 29.70 (1.10) 27.99 (1.10) 32.45 (4.82) 56.19 (4.40) <0.001 <0.01 Illicit drug useb 42.68 (1.14) 39.14 (1.13) 68.43 (5.26) 89.15 (2.47) <0.001 <0.001 Illicit drug abuseb 3.29...
Tables and Figures. Appendix Table 1. Schedule of Assessments
Tables and Figures. Table I: Demographic and baseline clinical characteristics of the study population comparing differences between the severe and non-severe ACS groups Genotype n(%) - SS - SC - Sβ0 Thal - Sβ+ Thal 37 (71.15) 12 (23.08) 1 (1.92) 2 (3.85) 7 (100) 0 0 0 30 ( 66.67) 12 (26.67) 1(2.22) 2 (4.44) 0.3896 Age (years), mean (SD) 9.65(4.6) 12.64 (4.6) 9.18 (4.4) 0.0862 Male Gender n (%) 28 (53.85) 5 (71.43) 23 (51.11) 0.4300 Hydroxyurea (Yes) n (%) 29 (55.77) 4 (57.14) 25 (55.56) 1.0000 TCD n (%) - Normal - Conditional - Abnormal - None recorded * n=19 were N/A due to age and genotype 5 (75.6) 5 (15.15) 0 2 (6.06) 4 (80.0) 0 1(20) 0 21 (63.64) 5 (17.86) 0 2 (7.14) 0.2092 Hx of Asthma (Yes) n (%) 15 (28.85) 2 (28.57) 13 (28.89) 1.0000 Hx of AVN (Yes) n (%) 2 (3.85) 0 2 (4.44) 1.0000 Hx of Priapism (Male=28, Yes) n (%) 7 (25) 2 (40) 5 (21.74) 0.5737 Hx of Chronic PRBC (Yes) n (%) 2 (3.85) 0 2 (4.44) 1.0000 Respiratory Rate n=51, mean (SD) 36.4 (11.5) 43.7 (12) 35.2 (11.1) 0.0786 Minimal sPO2 in room air (%) n=51, mean (SD) 92.9 (5.2) 84.1 (4.9) 94.3 (3.6) <0.0001*** Maximum Temp (C) n=51, mean (SD) 38.9 (1.2) 39.5 (0.7) 38.8 (1.2) 0.1100 PRBC Transfusion (Yes) n (%) 20 (47.62) 6 (85.71) 14 (40) 0.0408 Creatinine (mg/dl) n=29, mean (SD) 0.48 (0.3) 0.51 (0.3) 0.47 (0.2) 0.9588 BiPAP Therapy n=48 (Yes) n (%) 15 (31.25) 3 (50) 12 (28.57) 0.3598 ICU Admission (Yes) n (%) 5 (9.62) 5 (71.43) 0 <0.0001*** Mechanical Ventilation n=50 (Yes) n (%) 1 (2) 1 (14.29) 0 0.1400 LOS (days) n=49, mean (SD) 4 (3) 7 (5) 3 (4) 0.0042** *p<0.05, **p<0.01, ***p<0.001 Descriptive analyses of the study population were performed using Wilcoxon rank-sum tests to compare the populations of severe and non-severe ACS for continuous variables and Xxxxxx’x exact test for categorical variables. Table II: Association of severe ACS with demographic and baseline clinical characteristics of the study population Genotype n(%) - SS - SC - Sβ0 Thal - Sβ+ Thal 37 (71.15) 12 (23.08) 1 (1.92) 2 (3.85) 7 (100) 0 0 0 30 ( 66.67) 12 (26.67) 1(2.22) 2 (4.44) 0.3896 Age (years), median (IQR) 8.47 (7.45) 11.19 (8.68) 7.82 (6.97) 0.0703 Male Gender n (%) 28 (53.85) 5 (71.43) 23 (51.11) 0.4300 Hydroxyurea (Yes) n (%) 29 (55.77) 4 (57.14) 25 (55.56) 1.0000 TCD n (%) - Normal - Conditional - Abnormal - None recorded * n=19 were N/A due to age and genotype 5 (75.6) 5 (15.15) 0 2 (6.06) 4 (80.0) 0 1(20) 0 21 (63.64) 5 (17.86) 0 2 (7.14) 0.2092 Hx of Asthma (Yes) n (%) 15 (28.85) 2 (28.57) 13 (28.89) 1.0000 Hx of AVN (Yes) n ...