Demographic Characteristics. 36 medical service providers were enrolled into this program. The mean practice experience of all providers was 10.69 ± 8.63 (range from 0 to 40) years. These providers had an average of 7.66 ± 7.07 years of ED experience, ranging from 0 to 21 years at the beginning of the study. The percentage of female providers was 54.3%. Most of the providers were physicians (69.4%). More baseline demographic characteristics of the providers are presented in Table 1. 42,284 prescription records were collected. Among them 3,960 were prescribed before the intervention and 30,411 were prescribed five months after the implementation of EQUiPPED. There were 35,339 records categorized as no PIMs (I), 2,474 as PIMs with no conditions (II), 4,347 as PIMS with conditions and conditions met (III) and 73 as PIMs with conditions and conditions were not met or could not be determined (IV). Figure 1 showed the distribution of the number of PIMs and all prescriptions.
Demographic Characteristics. According to the 2010 U.S. Census, the population of the Borough of Farmingdale was 1,329, a decrease of 258 or 16.2 percent from 2000 when the population was 1,587 persons. There was also a decrease in the number of housing units from 638 to 578, a decrease of 60 units or 9.4 percent. Figure 3 shows the population by age and includes pre-school age, school age, working age and seniors.
Demographic Characteristics. Demographic characteristics of patients are shown in Table 1. There were 77 males and 38 females with a mean±SD age of 39.5±12.2 years. The mean age at illness onset was 22.6±7.0 years and the mean time after illness onset was 15.9±
Demographic Characteristics. Matara district has more than 800,000 people according to the census 2011. Majority of the population consists with Sinhalese and the main religion is Buddhism. Akuressa 49,752 52,676 2,924 Xxxxxxxxxx 30,176 32,173 1,997 Devinuwara 44,132 47,979 3,847 Dickwella 50,952 54,370 3,418 Hakmana 30,272 31,464 1,192 Kamburupitiya 37,420 40,803 3,383 Kirinda Puhulwella 19,458 20,135 677 Kotapola 63,951 63,072 -879 Malimbada 31,484 34,735 3,251 Matara Four Gravets 108,461 114,970 6,509 Mulatiyana 45,972 49,943 3,971 Pasgoda 56,188 58,869 2,681 Pitabeddara 49,313 50,827 1,514 Thihagoda 30,865 33,202 2,337 Weligama 66,528 72,511 5,983 Welipitiya 46,312 51,615 5,303 Source: - Department of Census and Statistics Highest population of Matara district has recorded in the Divisional Secretariate Division of Matara four Gravets in both census years of 2001 and 2011 and it is the only DSD which has more than 100,000 people. Except for Kotapola DSD all the other DSDs indicate an increasing trend of population. Kotapola is the only DSD shows decline of population during the decade. When considering the Population Density Matara Four Gravets DSD and Weligama DSD records the highest density which is more than 1600 people per sqkm. Northern part of the district indicates a very low density of population and the coastal region is it‟s opposite.
Demographic Characteristics. Mothers were predominately young; the percentage of women under 25 years of age ranged from 31.2% in Ghana to 50.7% in Zimbabwe. As such, they tended to marry young; Liberian women married youngest, at a mean age of 17.7 years (SD: 3.8); whereas, Ghanan women married the latest, at the age of 19.3 years (SD: 4.
Demographic Characteristics. The demographic characteristics of the children included age, gender, birth order, and schooling. Family characteristics consisted of marriage immigrants (yes or no), types of family (single-parent, nuclear, three-generation, extended, families of grandparents raising their grandchildren, others), parental marital status (married or otherwise), education level (1 = no schooling/elementary school to 5 = graduate school), employment status (employed or unemployed), and occupational category (professional, semiprofessional, skilled, semiskilled, unskilled). Following Xxxxxxxxxxx’x method of combining the two factors of education level and occupational category to calculate the socioeconomic status index (SSI), we used both parents’ data and ranked the parental occupational categories and education levels on a five-level ordinal scale (1 = Level I to 5 = Level V). We then calculated a combined score of occupational index multiplied by 7 and an education index multiplied by 4 (Xxxxxxxxxxx, 1957). The obtained score ranged from 22 to 110. The SSI was then categorized into low-level SSI (22-44), middle-level SSI (45-88), and high-level SSI (89-110).
Demographic Characteristics. The ethnic mix was representative of the prison system whereby Black Minority Ethnic (BME) groups are significantly over-represented (Ministry of Justice, 2012). Approximately a quarter of the young offenders (27%) had attained no educational qualifications which placed them above the general prison population where recent government statistics (Xxxxxx & Dar, 2013) have reported nearly half (47%) of UK prisoners do not hold any academic qualifications. However, only about a third of participants attained GCSE (24%) or A-Level (9%) qualifications, suggesting that a large proportion of the participants were early- school leavers. The low level of educational achievements within the current population is also in line with correlations found between illiteracy, innumeracy and offending (Xxxxxx, 2010). Furthermore, only half of the participants (n=28, 51%) were serving their first prison sentence and as such, in line with previous findings (e.g. Xxxxxx, 2010) many of the cohort were repeat offenders.
Demographic Characteristics. The overall rate of retention from enrollment to delivery was 56/59 participants (95%). Among those with incomplete data (n=3), two participants were lost to follow up and one participant was excluded due to a spontaneous abortion. Participants that did not have a recorded cord blood DDE measurement were not included in the analysis for this study. The final population used in the analysis includes 52 participants (Figure A.4). As previously mentioned some infants did not have measurements for all 7 clusters of the NBAS, but were still included in the analysis since the clusters are being treated as independent outcomes.
Demographic Characteristics. The patients were enrolled from Emory Xxxxxx Xxxxx Hospital ECT Service and the Emory University Xxxxx Center for Late-life Depression in Atlanta, Georgia. There are three participant groups: depression patients with ECT, depression patients without ECT, and healthy normal subjects. We summarized demographic characteristics in all subjects and compare them among the three participant groups, we got a general demographic information for each group based on Chi-squared test or Xxxxxx exact test for the categorical variable, race, and one-way ANOVA for continuous variables, age and number of education years. We summarized continuous variables by mean ± SD, and categorical variables by count and percentage.
Demographic Characteristics. We dichotomized demographic variables as follows: sex as male or female; household income as <$100,000 or ≥ 100,000; and education level as four-year college degree or less and master’s degree or higher. Income and education levels were dichotomized so that approximately one half of the participants were in each group. Body Mass Index (BMI) was calculated as the weight in kilograms divided by the height in squared meters. Asian-specific recommendations were used to categorize participants as underweight (BMI <18.5), normal weight (BMI 18.5-22.9), overweight (23-27.5), or obese (BMI ≥27.5) (World Health Organization, 2000). Height was measured without shoes using a stadiometer and weight was measured on a digital scale with the participant in light clothing. Weight loss self-efficacy was assessed in the SHAPE baseline survey using the Weight Efficacy Lifestyle Questionnaire, which uses self-efficacy theory to quantify a person’s judgement of his or her ability to effectively cope in a given situation (Clark, Abrams, Niaura, Eaton, & Rossi, 1991). This tool, first developed in 1991 and validated across multiple populations, assesses an individual’s ability to resist overeating in various situations by asking respondents to score his/her confidence for avoiding overeating in a given situation on a 10-point scale. A total score as well as five sub-scores are assessed: the negative emotions scale, the availability scale, the social pressure scale, the physical discomfort scale, and the positive activities scale.
