A relationship between the Florida Comprehensive Assessment Test 2.0 mathematics scores and racial and ethnic concentration when considering socio-economic status, ESOL student population, and school climate

From the moment children are born, they begin a lifetime journey of learning about themselves and their surroundings. With the establishment of the No Child Left Behind Act of 2001, it mandates that all children receive a high-quality education in a positive school climate. Regardless of the school the child attends or the neighborhood in which the child lives, proper and quality education and resources must be provided and made available in order for the child to be academically successful. The purpose of this ex post facto study was to investigate the relationship between the FCAT 2.0 mathematics scores of public middle school students in Miami-Dade County, Florida and the concentrations of a school's racial and ethnic make-up (Whites, Blacks, and Hispanics), English for Speakers of other Languages (ESOL) population, socio-economic status (SES), and school climate. The research question of this study was: Is there a significant relationship between the FCAT 2.0 Mathematics scores and racial and ethnic concentration of public middle school students in Miami-Dade County when controlling SES, ESOL student population, and school climate for the 2010-2011 school year? The instruments used to collect the data were the FCAT 2.0 and Miami-Dade County Public Schools (M-DCPS) School Climate Survey. The study found that Economically Disadvantaged (SES) students socio-economic status had the strongest correlation with the FCAT 2.0 mathematics scores (r = -.830). The next strongest correlation was with the number of students who agreed that their school climate was positive and helped them learn (r = .741) and the third strongest correlation was a school percentage of White students (r = .668). The study concluded that the FCAT 2.0 mathematics scores of M-DCPS middle school students have a significant relationship with socio-economic status, school climate, and racial concentration.

Measured parental weight status and familial socio-economic status correlates with childhood overweight and obesity at age 9

Background: Parental obesity is a predominant risk factor for childhood obesity. Family factors including socio-economic status (SES) play a role in determining parent weight. It is essential to unpick how shared family factors impact on child weight. This study aims to investigate the association between measured parent weight status, familial socio-economic factors and the risk of childhood obesity at age 9. Methodology/Principal Findings: Cross sectional analysis of the first wave (2008) of the Growing Up in Ireland (GUI) study. GUI is a nationally representative study of 9-year-old children (N = 8,568). Schools were selected from the national total (response rate 82%) and age eligible children (response rate 57%) were invited to participate. Children and their parents had height and weight measurements taken using standard methods. Data were reweighted to account for the sampling design. Childhood overweight and obesity prevalence were calculated using International Obesity Taskforce definitions. Multinomial logistic regression examined the association between parent weight status, indicators of SES and child weight. Overall, 25% of children were either overweight (19.3%) or obese (6.6%). Parental obesity was a significant predictor of child obesity. Of children with normal weight parents, 14.4% were overweight or obese whereas 46.2% of children with obese parents were overweight or obese. Maternal education and household class were more consistently associated with a child being in a higher body mass index category than household income. Adjusted regression indicated that female gender, one parent family type, lower maternal education, lower household class and a heavier parent weight status significantly increased the odds of childhood obesity. Conclusions/Significance: Parental weight appears to be the most influential factor driving the childhood obesity epidemic in Ireland and is an independent predictor of child obesity across SES groups. Due to the high prevalence of obesity in parents and children, population based interventions are required.

Northern Ireland Neighbourhood Watch: Participatory Mapping and Socio Demographic Uptake

Northern Ireland Neighbourhood Watch (NINW) was formally introduced to Northern Ireland in 2004 by the Police Service of Northern Ireland, Northern Ireland Policing Board and Northern Ireland Office. However, there has been little research to data as to participation in, or success of, the schemes. This research report provides one of the few empirical examinations of NINW. Using GIS mapping and socio-demographic data from the Northern Ireland Neighbourhood Information Service (NINIS), the research explores participation in NINW schemes set against religion, deprivation and crime levels at the Census Output Area (COA) level across Northern Ireland. While the research largely confirms the limited impact of neighbourhood schemes as noted in international literature, at a local level in Northern Ireland the findings evidence a distinct pattern of uptake, with the vast majority of participants in the schemes residing in affluent, low-crime, mainly Protestant areas of the country

Testing the psychometric properties of Kidscreen-27 with Irish children of low socio-economic status

Background

Kidscreen-27 was developed as part of a cross-cultural European Union-funded project to standardise the measurement of children’s health-related quality of life. Yet, research has reported mixed evidence for the hypothesised 5-factor model, and no confirmatory factor analysis (CFA) has been conducted on the instrument with children of low socio-economic status (SES) across Ireland (Northern and Republic).

Method

The data for this study were collected as part of a clustered randomised controlled trial. A total of 663 (347 male, 315 female) 8–9-year-old children (M = 8.74, SD = .50) of low SES took part. A 5- and modified 7-factor CFA models were specified using the maximum likelihood estimation. A nested Chi-square difference test was conducted to compare the fit of the models. Internal consistency and floor and ceiling effects were also examined.

Results

CFA found that the hypothesised 5-factor model was an unacceptable fit. However, the modified 7-factor model was supported. A nested Chi-square difference test confirmed that the fit of the 7-factor model was significantly better than that of the 5-factor model. Internal consistency was unacceptable for just one scale. Ceiling effects were present in all but one of the factors.

Conclusions

Future research should apply the 7-factor model with children of low socio-economic status. Such efforts would help monitor the health status of the population.

The influence of socio-demographic, psychological and knowledge-related variables alongside perceived cooking and food skills abilities in the prediction of diet quality in adults: a nationally representative cross-sectional study

Background: Interventions to increase cooking skills (CS) and food skills (FS) as a route to improving overall diet are popular within public health. This study tested a comprehensive model of diet quality by assessing the influence of socio-demographic, knowledge- and psychological-related variables alongside perceived CS and FS abilities. The correspondence of two measures of diet quality further validated the Eating Choices Index (ECI) for use in quantitative research.
Methods: A cross-sectional survey was conducted in a quota-controlled nationally representative sample of 1049 adults aged 20–60 years drawn from the Island of Ireland. Surveys were administered in participants’ homes via computer-assisted personal interviewing (CAPI) assessing a range of socio-demographic, knowledge- and psychological-related variables alongside perceived CS and FS abilities. Regression models were used to model factors influencing diet quality. Correspondence between 2 measures of diet quality was assessed using chi-square and Pearson correlations.
Results: ECI score was significantly negatively correlated with DINE Fat intake (r = -0.24, p < 0.001), and ECI score was significantly positively correlated with DINE Fibre intake (r = 0.38, p < 0.001), demonstrating a high agreement. Findings indicated that males, younger respondents and those with no/few educational qualifications scored significantly lower on both CS and FS abilities. The relative influence of socio-demographic, knowledge, psychological variables and CS and FS abilities on dietary outcomes varied, with regression models explaining 10–20 % of diet quality variance. CS ability exerted the strongest relationship with saturated fat intake (β = -0.296, p < 0.001) and was a significant predictor of fibre intake (β = -0.113, p < 0.05), although not for healthy food choices (ECI) (β = 0.04, p > 0.05).
Conclusion: Greater CS and FS abilities may not lead directly to healthier dietary choices given the myriad of other factors implicated; however, CS appear to have differential influences on aspects of the diet, most notably in relation to lowering saturated fat intake. Findings suggest that CS and FS should not be singular targets of interventions designed to improve diet; but targeting specific sub-groups of the population e.g. males, younger adults, those with limited education might be more fruitful. A greater understanding of the interaction of factors influencing cooking and food practices within the home is needed.

Location analysis of city sections: socio-demographic segmentation and restaurant potentiality estimation : a case study of Lisbon

One of the objectives of this study is to perform classification of socio-demographic components for the level of city section in City of Lisbon. In order to accomplish suitable platform for the restaurant potentiality map, the socio-demographic components were selected to produce a map of spatial clusters in accordance to restaurant suitability. Consequently, the second objective is to obtain potentiality map in terms of underestimation and overestimation in number of restaurants. To the best of our knowledge there has not been found identical methodology for the estimation of restaurant potentiality. The results were achieved with combination of SOM (Self-Organized Map) which provides a segmentation map and GAM (Generalized Additive Model) with spatial component for restaurant potentiality. Final results indicate that the highest influence in restaurant potentiality is given to tourist sites, spatial autocorrelation in terms of neighboring restaurants (spatial component), and tax value, where lower importance is given to household with 1 or 2 members and employed population, respectively. In addition, an important conclusion is that the most attractive market sites have shown no change or moderate underestimation in terms of restaurants potentiality.

How reliable is internet-based self-reported identity, socio-demographic and obesity measures in European adults?

In e-health intervention studies, there are concerns about the reliability of internet-based, self-reported (SR) data and about the potential for identity fraud. This study introduced and tested a novel procedure for assessing the validity of internet-based, SR identity and validated anthropometric and demographic data via measurements performed face-to-face in a validation study (VS). Participants (n = 140) from seven European countries, participating in the Food4Me intervention study which aimed to test the efficacy of personalised nutrition approaches delivered via the internet, were invited to take part in the VS. Participants visited a research centre in each country within 2 weeks of providing SR data via the internet. Participants received detailed instructions on how to perform each measurement. Individual's identity was checked visually and by repeated collection and analysis of buccal cell DNA for 33 genetic variants. Validation of identity using genomic information showed perfect concordance between SR and VS. Similar results were found for demographic data (age and sex verification). We observed strong intra-class correlation coefficients between SR and VS for anthropometric data (height 0.990, weight 0.994 and BMI 0.983). However, internet-based SR weight was under-reported (Δ -0.70 kg [-3.6 to 2.1], p < 0.0001) and, therefore, BMI was lower for SR data (Δ -0.29 kg m(-2) [-1.5 to 1.0], p < 0.0001). BMI classification was correct in 93 % of cases. We demonstrate the utility of genotype information for detection of possible identity fraud in e-health studies and confirm the reliability of internet-based, SR anthropometric and demographic data collected in the Food4Me study. TRIAL REGISTRATION: NCT01530139 ( http://clinicaltrials.gov/show/NCT01530139 ).

An internet-supported physical activity intervention delivered in secondary schools located in low socio-economic status communities : study protocol for the activity and motivation in physical education (AMPED) cluster randomized controlled trial

BACKGROUND: School-based physical education is an important public health initiative as it has the potential to provide students with regular opportunities to participate in moderate-to-vigorous physical activity (MVPA). Unfortunately, in many physical education lessons students do not engage in sufficient MVPA to achieve health benefits. In this trial we will test the efficacy of a teacher professional development intervention, delivered partially via the Internet, on secondary school students' MVPA during physical education lessons. Teaching strategies covered in this training are designed to (i) maximize opportunities for students to be physically active during lessons and (ii) enhance students' autonomous motivation towards physical activity. METHOD: A two-arm cluster randomized controlled trial with allocation at the school level (intervention vs. usual care control). Teachers and Year 8 students in government-funded secondary schools in low socio-economic areas of the Western Sydney region of Australia will be eligible to participate. During the main portion of the intervention (6 months), teachers will participate in two workshops and complete two implementation tasks at their school. Implementation tasks will involve video-based self-reflection via the project's Web 2.0 platform and an individualized feedback meeting with a project mentor. Each intervention school will also complete two group peer-mentoring sessions at their school (one per term) in which they will discuss implementation with members of their school physical education staff. In the booster period (3 months), teachers will complete a half-day workshop at their school, plus one online implementation task, and a group mentoring session at their school. Throughout the entire intervention period (main intervention plus booster period), teachers will have access to online resources. Data collection will include baseline, post-intervention (7-8 months after baseline) and maintenance phase (14-15 months after baseline) assessments. Research assistants blinded to group allocation will collect all data. The primary outcome will be the proportion of physical education lesson time that students spend in MVPA. Secondary outcomes will include leisure-time physical activity, subjective well-being, and motivation towards physical activity.
DISCUSSION: The provision of an online training platform for teachers could help facilitate more widespread dissemination of evidence-based interventions compared with programs that rely exclusively on face-to-face training.

Skeletal maturity and socio-economic status in portuguese children and youths: the Madeira growth study

Skeletal maturity is used to evaluate biological maturity status. Information about the association between socio-economic status (SES) and skeletal maturity is limited in Portugal. Aims: The aim of this study is to document the skeletal maturity of youths in Madeira and to evaluate variation in maturity associated with SES. Subjects and methods: The study involved 507 subjects (256 boys and 251 girls) from the Madeira Growth Study, a mixed-longitudinal study of five cohorts (8, 10, 12, 14 and 16 years of age) followed at yearly intervals over 3 years (1996–1998). A total of 1493 observations were made. Skeletal age was estimated from radiographs of the hand and wrist using the Tanner–Whitehouse 2 method (TW2). Social class rankings were based on Graffar’s (1956) method. Five social rankings were subsequently grouped into three SES categories: high, average and low. Results: Median for the radius, ulna and short finger bones (RUS scores) in the total sample of boys and girls increased curvilinearly across age whereas median for the 7 (without pisiform) carpal bones (Carpal scores) increased almost linearly. The 20-bone maturity scores demonstrated distinctive trends by gender: the medians for boys increased almost linearly while the medians for girls increased curvilinearly. SES differences were minimal. Only among children aged 10–11 years were high SES boys and girls advanced in skeletal maturity. Madeira adolescents were advanced in skeletal maturity compared with Belgian reference values. Conclusion: The data suggests population variation in TW2 estimates of skeletal maturation. Skeletal maturity was not related to SES in youths from Madeira.

Socio-economic status, growth, physical activity and fitness: the Madeira growth study

Within a country social conditions change over time and these conditions vary from country to country. The associations between these conditions, somatic growth, physical activity and fitness reflect these changes. Aim: The study documented variation in somatic growth, physical activity and fitness associated with socio-economic status (SES). Subjects and methods: The study involved 507 subjects (256 boys and 251 girls) from the Madeira Growth Study, a mixed longitudinal study of five cohorts (8, 10, 12, 14 and 16 years of age) followed at yearly intervals over 3 years (1996–1998). A total of 1493 observations were made. Anthropometric measurements included lengths, body mass, skeletal breadths, girths and skinfolds. Physical activity and SES were collected via questionnaire and interview. Physical fitness was assessed using the Eurofit test battery. Variation in somatic growth, physical activity and physical fitness by SES (high, average and low) was tested with analysis of variance. Results: Significant differences between SES groups were observed for height, body mass and skinfolds. Boys and girls from high SES groups were taller, heavier and fatter (subscapular and triceps skinfolds) than their peers from average and low SES groups. At some age intervals, the high SES group had larger skeletal breadths (girls) and girths (boys and girls) than low SES. Small SES differences were observed for physical activity (sport and leisure-time indices). SES was significantly associated with physical fitness. At some age levels, boys from the low SES group performed better for muscular and aerobic endurance whereas girls from the high SES group performed better for power. Conclusion: Considerable variation in somatic growth and physical fitness in association with SES has been demonstrated, but little association was found for physical activity.

Skeletal maturity and socio-economic status in portuguese children and youths: the Madeira growth study

Skeletal maturity is used to evaluate biological maturity status. Information about the association between socio-economic status (SES) and skeletal maturity is limited in Portugal. Aims: The aim of this study is to document the skeletal maturity of youths in Madeira and to evaluate variation in maturity associated with SES. Subjects and methods: The study involved 507 subjects (256 boys and 251 girls) from the Madeira Growth Study, a mixed-longitudinal study of five cohorts (8, 10, 12, 14 and 16 years of age) followed at yearly intervals over 3 years (1996–1998). A total of 1493 observations were made. Skeletal age was estimated from radiographs of the hand and wrist using the Tanner–Whitehouse 2 method (TW2). Social class rankings were based on Graffar’s (1956) method. Five social rankings were subsequently grouped into three SES categories: high, average and low. Results: Median for the radius, ulna and short finger bones (RUS scores) in the total sample of boys and girls increased curvilinearly across age whereas median for the 7 (without pisiform) carpal bones (Carpal scores) increased almost linearly. The 20-bone maturity scores demonstrated distinctive trends by gender: the medians for boys increased almost linearly while the medians for girls increased curvilinearly. SES differences were minimal. Only among children aged 10–11 years were high SES boys and girls advanced in skeletal maturity. Madeira adolescents were advanced in skeletal maturity compared with Belgian reference values. Conclusion: The data suggests population variation in TW2 estimates of skeletal maturation. Skeletal maturity was not related to SES in youths from Madeira.

Socio-economic status, growth, physical activity and fitness: the Madeira growth study

Within a country social conditions change over time and these conditions vary from country to country. The associations between these conditions, somatic growth, physical activity and fitness reflect these changes. Aim: The study documented variation in somatic growth, physical activity and fitness associated with socio-economic status (SES). Subjects and methods: The study involved 507 subjects (256 boys and 251 girls) from the Madeira Growth Study, a mixed longitudinal study of five cohorts (8, 10, 12, 14 and 16 years of age) followed at yearly intervals over 3 years (1996–1998). A total of 1493 observations were made. Anthropometric measurements included lengths, body mass, skeletal breadths, girths and skinfolds. Physical activity and SES were collected via questionnaire and interview. Physical fitness was assessed using the Eurofit test battery. Variation in somatic growth, physical activity and physical fitness by SES (high, average and low) was tested with analysis of variance. Results: Significant differences between SES groups were observed for height, body mass and skinfolds. Boys and girls from high SES groups were taller, heavier and fatter (subscapular and triceps skinfolds) than their peers from average and low SES groups. At some age intervals, the high SES group had larger skeletal breadths (girls) and girths (boys and girls) than low SES. Small SES differences were observed for physical activity (sport and leisure-time indices). SES was significantly associated with physical fitness. At some age levels, boys from the low SES group performed better for muscular and aerobic endurance whereas girls from the high SES group performed better for power. Conclusion: Considerable variation in somatic growth and physical fitness in association with SES has been demonstrated, but little association was found for physical activity.