This study examined associations between family income, family structure and relationship quality among members of Brazilian families. Participants (n = 77). The PDF file you selected should load here if your Web browser has a PDF reader plug-in installed (for example, a recent version of Adobe Acrobat Reader). Learn how socioeconomic status affects psychological and physical health, SES Impacts the Lives of Children, Youth and Families . Relation of education and occupation-based socioeconomic status to incident Alzheimer's disease.
How often has your family traveled during the past 12 months? The Programme for International Student Assessment PISA requires students to report the type and amount of electrical equipment in their home, the number of cars in the family, housing conditions, bathing conditions, and so forth. This method was also used in empirical research with a Chinese cultural background Ren and Xin, In this paper, we adopted the second method.
With the aim to better represent or easily distinguish the family economic conditions, taking the practical situation in China into consideration, we chose equipment such as TV, refrigerator, home ownership, car, washing machine, air conditioner, and computers as indicators of the index.
The measuring index of academic achievement functions as another moderator variable. In the educational context, academic achievement can be measured not only by a general index such as GPA or IQ but also by a specific index such as language and math scores.
We proposed an operational definition and measuring framework of reading ability based on well-known pre-existing measuring programs i. Given that the form and the content of reading materials are two important influencing factors, we set three different conditions: We investigated three different reading abilities reflected during the reading procedure: The form of reading material refers to how a text is organized, that is, continuous text or non-continuous text.
The content of reading material refers to the type of information transmitted, that is, literary text or informational text. Therefore, combining the two forms and two types of content would result in four pairs. Accordingly, three reading situations were adopted in this study. The first condition was reading literary texts; the test material included fairy tales, fables, fiction, or prose. The second condition was reading continuous informational texts; the test material included introductions and explanatory texts such as expositions, scientific essays, and argumentations.
The third condition was reading non-continuous informational texts; the test material mainly included practical texts such as graphs, tables, and advertisements. Three kinds of reading ability were examined: Retrieving and inferencing involves retrieving explicit information and making simple inferences from it. Integrating and interpreting involves forming an overall perception and initial summary of the article and then inferring and explaining the implicit information within it.
Evaluating and reflecting requires readers, with pertinent background information, to think critically regarding the content and form of the reading material. By far, there are a number of research have discussed the relationship between SES and reading ability in both Chinese and western cultural background Hoff, ; Noble et al. However, they paid less attention to the internal mechanism of the relationship. Additionally, there are some deficiencies in the measurement of SES and reading ability in these studies.
To achieve this goal, we adopted an SES index suited to the Chinese context and estimated reading ability using the item response theory IRT technique. Many studies have made discoveries regarding the relationship between SES and reading ability Hoff, ; Noble et al. They found that SES contributed to variance in phonological skills and vocabulary in the early developmental stages.
A longitudinal study conducted by Su et al. The results indicated that family SES and parent—child reading engagement were associated with literacy skills. The mediating variables of child, family, and school characteristics may be substantial channels for the influence of SES on academic achievement Sirin, Based on an integration of results from studies of preschool, primary, and grade school children, Hess and Holloway identified that the relation between parents and children is one of the important variables linking socioeconomic factors to school achievement.
Family SES is a reflection of the social and economic resources that parents can provide Bradley and Corwyn, According to the family stress model, parents in low SES families face more financial pressure and emotional exhaustion, which are associated with low income and self-efficacy Conger and Donnellan, This may cause parents to use negative, unkind strategies to get along with their children and result in an undesirable parent—child relationship McLoyd, ; Conger et al.
The undesirable relationship may deprive children of advantageous psychological circumstances that benefit their cognitive development. By contrast, parents in high SES families have much more time, energy and knowledge about education, and they are inclined to express more warmth and affection in order to cultivate a favorable parent—child relationship Kraus et al.
Positive parent—child interactions or relationships have been found to be correlated with good reading ability development Chan, Lau and Leung found that better relationships with parents and school peers lead to higher academic performance, including higher class rank, higher final exam scores, and higher scores in Chinese, English, mathematics, physical education, and music. This is because in a favorable relationship, parents devote more attention to educating their children and show more enthusiasm, which can provide children emotional support and in turn enhance their academic performance and reading ability.
Moderating variables, including demographic variables such as grade, age, and race, and external supporting variables such as family, school, and community, is most often discussed White, ; Bradley and Corwyn, ; Sirin, From the academic resilience perspective Arellano and Padilla,although academic risk factors can block academic development, resilience factors such as learning motivation help children overcome risk factors Alfaro et al.
Some evidence has shown that learning motivation plays a moderating role in the relation between academic performance and certain personal variables, especially intrinsic motivation, which occurs when individuals engage in activities based on interests and enjoyment Ryan and Deci, ; Spinath and Steinmayr, The abovementioned personal variables also include learning experience, test anxiety, and psychological distress Salami, ; Ning and Downing, ; Khalaila, Another study found that intrinsic motivation explained more variance in the reading performance of low ability readers than that of high-ability readers Logan et al.
The results of this study indicated that children with low reading skill who had higher intrinsic motivation tended to persevere more in developing their abilities, but those who had lower intrinsic motivation tended more to abandon the effort to learn.
Likewise, low SES is also an undesirable condition, and motivation might moderate the relationship between SES and reading ability because the role of motivation may be more crucial for low SES children than for high SES children.
Recently, Kim et al. Based on interviews with 48 respondents, they found that students of poorer parents were more motivated to gain upward mobility through academic achievement. There is an old saying in China: They may want to change their current situation more urgently than students who are better off, and they may think that it will be easier to do so if they study harder and do better at school.
In other words, family SES influences individual success differently according to the motivation.
Children with similar family SES may not have the same academic achievement. We proposed that such discrepancies may be caused by the different levels of learning motivation among children. We assumed that for students with strong motivation, the influence of SES on reading ability is weakened. However, for students with weak motivation, the influence of SES through the mediating variable is strengthened.
Based on the previous literature e.
Materials and Methods Participants We used a cluster random sampling method to recruit middle-school students in grades 8 from 11 schools in Beijing and Guangzhou to participate in our study.
All participants provided their oral informed consent before completing the measures. The data were collected and analyzed anonymously. Several cross-sectional studies have reported that the association of neighborhood poverty with obesity risk is stronger among Whites than among Blacks Wickrama et al. It is also possible that these attenuated effects result from compressed variation in neighborhood SEC among minority populations. In addition, trajectories of adiposity appear to differ between Black and White women.
Given these observations from the literature, we investigate the following hypotheses with regard to the longitudinal effects of family SES and neighborhood SEC on adiposity, as measured by sex- and age-specific body mass index z-scores BMIz: Independent of family SES, neighborhood SEC are associated with BMIz trajectories; specifically, girls living in low socioeconomic neighborhoods experience greater increases in BMIz during adolescence compared to girls living in high socioeconomic neighborhoods.
Race moderates these associations such that the effects of neighborhoods on BMIz trajectories are attenuated among Black girls compared to White girls.
Taking advantage of the comparatively long period of observation and high frequency of anthropometric measurements annuallywe focus on examining longitudinal patterns of adiposity and their association with family SES and neighborhood SEC.
Methods Study Design and Sample Data analyzed for this study are from NGHS, a year prospective cohort study of girls, enrolled at age years indesigned to identify factors associated with the onset and development of obesity in Black and White preadolescent girls NGHS Research Group, At each annual examination visitheight and weight were measured and all residential addresses of the participants in the preceding year were recorded.
Information on education and income was obtained from parents during the first year of the study. NGHS had three recruitment sites. These participants resided in Contra Costa County, California at study entry. Participants experiencing pregnancy during the study were excluded from our analyses. Measures The dependent variable was sex- and age-specific BMIz, which indicates BMI relative to other individuals of the same age and sex on a standard deviation scale.
We considered several measures of neighborhood SEC available from the U. Because its distribution was less skewed and its ranges for Blacks and Whites had greater overlap compared to other measures, census tract median income from the U. Census, was selected to characterize neighborhood SEC. When a participant had lived in multiple census tracts during a preceding year, the mean of the median income values over all reported census tracts of residence was used.
A single average value was computed for each year, and these yearly values were used as a time-varying covariate, which changed when participants moved. Time points at which participants resided outside Contra Costa County or adjacent Alameda County were not included in analyses. We repeated the analyses using neighborhood disadvantage index. Family-level SES was assessed by family annual income and the educational attainment level of the parent or guardian with the higher level of education maximal parental education.
These two variables were combined into a single composite family SES index by coding each variable on an ordinal scale with the same range and then taking the mean. This composite score was dichotomized at the midpoint to classify the participants as having high or low family SES.
A continuous version of this index was not used in analyses since this variable did not have a proper numeric scale. Because these variables were collected only in year one, they were modeled as time-invariant.