Assessing Sleep during Pregnancy - a study across two time points examining the pittsburg sleep quality index and associations with depressive symptoms

Background and Purpose: Sleep quality seems to be an antecedent to depressive symptoms during pregnancy. We sought to 1) examine the psychometrics of the Pittsburgh Sleep Quality Index (PSQI) in pregnancy; 2) examine whether sleep quality predicted increases in depressive symptoms; and 3) compare PSQI scores across 3 or 2 levels of depressive symptoms.

Methods: Each of the 252 participants completed the Beck Depression Inventory (short form) and a sleep quality measure at mid and late pregnancy.

Results: PSQI total scores showed good internal consistency and construct validity. An improved model of the internal structure of the PSQI in pregnancy was found with 1 factor labeled Sleep Efficiency, a second labeled Night and Daytime Disturbances, and an Overall Sleep Quality component associated with, but separate from, both of these 2 factors. Although PSQI scores showed moderate stability over time, sleep disturbance scores increased in late pregnancy. Importantly, PSQI prospectively predicted increases in depressive symptoms.

Conclusions: Findings suggest that the PSQI is useful in pregnancy research. Findings also support the idea that sleep problems are prospective risk factors for increases in depressive symptoms during pregnancy. Practitioners are advised to screen for sleep quality during early pregnancy.

A quadtree driven image fusion quality assessment

In this paper a new method to compute saliency of source images is presented. This work is an extension to universal quality index founded by Wang and Bovik and improved by Piella. It defines the saliency according to the change of topology of quadratic tree decomposition between source images and the fused image. The saliency function provides higher weight for the tree nodes that differs more in the fused image in terms topology. Quadratic tree decomposition provides an easy and systematic way to add a saliency factor based on the segmented regions in the images.

Sleep quality and depression during pregnancy: a prospective study

For the first time, the relationship between depressive symptoms and sleep quality was explored prospectively during pregnancy. Participants (n = 273) completed the Pittsburgh Sleep Quality Index and Beck Depression Inventory at three 8-week intervals, starting from 15–23 weeks gestation. In addition to sleep quality and depression remaining relatively stable during pregnancy, findings revealed that sleep quality earlier in pregnancy predicted higher levels of depressive symptoms at later stage in pregnancy (after controlling for prior depression levels). In contrast, there was no evidence to suggest that depressive symptoms earlier in pregnancy impacted on sleep quality later on. Given that depressive symptomatology can lead to major depression and given the prevalence of pre- and postnatal depression, our findings suggest that screening for sleep problems during pregnancy may be of clinical significance.

Examination of a multi-factorial model of body-related experiences during pregnancy : the relationships among physical symptoms, sleep quality, depression, self-esteem, and negative body attitudes

The aim of this cross-sectional study was to investigate relationships among women's body attitudes, physical symptoms, self-esteem, depression, and sleep quality during pregnancy. Pregnant women (N = 215) at 15–25 weeks gestation completed a questionnaire including four body image subscales assessing self-reported feeling fat, attractiveness, strength/fitness, and salience of weight and shape. Women reported on 29 pregnancy-related physical complaints, and completed the Beck Depression Inventory, Rosenberg Self-esteem Scale, and Pittsburgh Sleep Quality Index. In regressions, controlling for retrospective reports of body image, more frequent and intense physical symptoms were related to viewing the self as less strong/fit, and to poorer sleep quality and more depressive symptoms. In a multi-factorial model extending previous research, paths were found from sleep quality to depressive symptoms to self-esteem; self-esteem was found to be a mediator associated with lower scores on feeling fat and salience of weight and shape, and on higher perceived attractiveness.

The association between socio-economic position and diet quality in Australian adults

Objective: We aimed to investigate the association between multiple measures of socio-economic position (SEP) and diet quality, using a diet quality index representing current national dietary guidelines, in the Australian adult population. Design: Cross-sectional study. Linear regression analyses were used to estimate the association between indicators of SEP (educational attainment, level of income and area-level disadvantage) and diet quality (measured using the Dietary Guideline Index (DGI)) in the total sample and stratified by sex and age (≤55 years and >55 years). Setting: A large randomly selected sample of the Australian adult population. Subjects: Australian adults (n 9296; aged ≥25 years) from the Australian Diabetes, Obesity and Lifestyle Study. Results: A higher level of educational attainment and income and a lower level of area-level disadvantage were significantly associated with a higher DGI score, across the gradient of SEP. The association between indicators of SEP and DGI score was consistently stronger among those aged ≤55 years compared with their older counterparts. The most disadvantaged group had a DGI score between 2 and 5 units lower (depending on the marker of SEP) compared with the group with the least disadvantage. Conclusions: A higher level of SEP was consistently associated with a higher level of diet quality for all indicators of SEP examined. In order to reduce socio-economic inequalities in diet quality, healthy eating initiatives need to act across the gradient of socio-economic disadvantage with a proportionate focus on those with greater socio-economic disadvantage.

A revised Australian dietary guideline index and its association with key sociodemographic factors, health behaviors and body mass index in peri-retirement aged adults

The Dietary Guideline Index, a measure of diet quality, was updated to reflect the 2013 Australian Dietary Guidelines. This paper describes the revision of the index (DGI-2013) and examines its use in older adults. The DGI-2013 consists of 13 components reflecting food-based daily intake recommendations of the Australian Dietary Guidelines. In this cross-sectional study, the DGI-2013 score was calculated using dietary data collected via an 111-item food frequency questionnaire and additional food-related behaviour questions. The DGI-2013 score was examined in Australian adults (aged 55-65 years; n = 1667 men; 1801 women) according to sociodemographics, health-related behaviours and BMI. Women scored higher than men on the total DGI-2013 and all components except for dairy. Those who were from a rural area (men only), working full-time (men only), with lower education, smoked, did not meet physical activity guidelines, and who had a higher BMI, scored lower on the DGI-2013, highlighting a group of older adults at risk of poor health. The DGI-2013 is a tool for assessing compliance with the Australian Dietary Guidelines. We demonstrated associations between diet quality and a range of participant characteristics, consistent with previous literature. This suggests that the DGI-2013 continues to demonstrate convergent validity, consistent with the original Dietary Guideline Index.

The predictors of diet quality among Australian children aged 3.5 years

BACKGROUND: It is critical to promote healthy eating early in life. OBJECTIVE: The aim of this study was to examine diet quality and its predictors among Australian preschool-aged children. DESIGN: Diet was assessed at age 3.5 years using multiple 24-hour recalls. Diet quality was assessed using an adapted version of the Revised Children's Diet Quality Index (RC-DQI). Potential predictors of diet quality were from questionnaires at age 3, 9, and 18 months and informed by the ecologic model of childhood overweight. Potential predictors included child's sex, age of introduction to solid foods, breastfeeding status, food acceptance, maternal nutrition knowledge, modeling of healthy eating, self-efficacy, education, and home food availability. PARTICIPANTS: Data from 244 children participating in the Melbourne Infant Feeding, Activity, and Nutrition Trial in 2008-2010 and follow-up data collection in 2011-2013 were examined. MAIN OUTCOME MEASURES: Diet quality at age 3.5 years. STATISTICAL ANALYSES PERFORMED: Bivariate logistic regression was performed to assess the relationship between diet quality and each predictor. A multivariable logistic regression model accounting for influences of covariates, treatment arm, and clustering by group tested associations between diet quality and significant predictors from bivariate analyses. RESULTS: RC-DQI scores had a mean±standard deviation score of 62.8±8.3 points out of a maximum of 85 points. Breastfeeding status (odds ratio [OR] 2.34, 95% CI 1.33 to 4.10) and maternal modeling of healthy eating (OR 1.75, 95% CI 1.01 to 3.03) were positively associated with RC-DQI scores. Both breastfeeding status (OR 3.09, 95% CI 1.63 to 5.85) and modeling (OR 2.01, 95% CI 1.04 to 3.88) remained positively associated with diet quality after adjustment for child age, body mass index z score, energy intake, treatment arm, and clustering. CONCLUSIONS: Breastfeeding status and modeling of healthy eating were independently associated with children's diet quality. Early intervention could assist mothers to practice these behaviors to provide support for improving child diet quality.

Subjective sleep impairment in adults with type 1 or type 2 diabetes: results from Diabetes MILES - the Netherlands

AIMS: Despite growing recognition of the impact of sleep on diabetes, a clear profile of people with diabetes regarding subjective sleep impairment has yet to be established. This study examines: (1) subjective sleep characteristics in adults with type 1 and type 2 diabetes; (2) the relationship of poor subjective sleep quality with glycaemic control, self-care and daytime functioning; (3) possible risk markers for poor sleep quality. METHODS: In a cross-sectional study, Dutch adults with type 1 (n=267) or type 2 diabetes (n=361) completed an online survey, including the Pittsburgh Sleep Quality Index (PSQI), socio-demographic, clinical, self-care and psychological measures. RESULTS: Poor sleep quality (PSQI-score >5) was reported by 31% of adults with type 1 and 42% of adults with type 2 diabetes. Participants with good and poor sleep quality did not differ in self-reported HbA1c or the frequency of meeting lifestyle recommendations. Poor sleep quality was related to a higher self-care burden and higher levels of daytime sleepiness, fatigue, depressive and anxiety symptoms, and diabetes-specific distress. In multivariable logistic regression analyses examining risk markers, poor sleep quality was associated with depressive symptoms in adults with type 1 (OR=1.39, 95% CI 1.25-1.54) and type 2 diabetes (OR=1.31, 1.16-1.47), and with being female in those with type 2 diabetes (OR=2.72, 1.42-5.20). CONCLUSIONS: Poor subjective sleep quality is prevalent both in adults with type 1 and type 2 diabetes, and is related to poor daytime functioning and higher self-care burden. The temporal relation with depression and merits of therapy should be explored.

Classification tree analysis of postal questionnaire data to identify risk of excessive gestational weight gain

OBJECTIVE: overweight/obese weight status during pregnancy increases risk of a range of adverse health outcomes for mother and child. Whereas identification of those who are overweight/obese pre-pregnancy and in early pregnancy is straightforward, prediction of who will experience excessive gestational weight gain (EGWG), and thus be at greater risk of becoming overweight or obese during pregnancy is more challenging. The present study sought to better identify those at risk of EGWG by exploring pre-pregnancy BMI as well as a range of psychosocial risk factors identified as risk factors in prior research. METHODS: 225 pregnant women completed self-reported via postal survey measures of height, weight, and psychosocial variables at 16-18 weeks gestation, and reported their weight again at 32-34 weeks to calculate GWG. Classification and regression tree analysis (CART) was used to find subgroups in the data with increased risk of EGWG based on their pre-pregnancy BMI and psychosocial risk factor scores at Time 1. FINDINGS: CART confirmed that self-reported BMI status was a strong predictor of EGWG risk for women who were overweight/obese pre-pregnancy. Normal weight women with low motivation to maintain a healthy diet and who reported lower levels of partner support were also at considerable risk of EGWG. IMPLICATIONS FOR PRACTICE: present findings offer support for inclusion of psychosocial measures (in addition to BMI) in early antenatal visits to detect risk of EGWG. However, these findings also underscore the need for further consideration of effect modifiers that place women at increased or decreased risk of EGWG. Proposed additional constructs are discussed to direct further theory-driven research.

An index of diet and eating patterns is a valid measure of diet quality in an Australian population

Diet indices represent an integrated approach to assessing eating patterns and behaviors. The aim of this study was to develop a comprehensive food-based dietary index to reflect adherence to healthy eating recommendations, evaluate the construct validity of the index using nutrient intakes, and evaluate this index in relation to sociodemographic factors, health behaviors, risk factors, and self-assessed health status. Data were analyzed from adult participants of the Australian National Nutrition Survey who completed a 108-item FFQ and a food habits questionnaire (n = 8220). The dietary guideline index (DGI) consisted of 15 items reflecting the dietary guidelines, including dietary indicators of vegetables and legumes, fruit, total cereals, meat and alternatives, total dairy, beverages, sodium, saturated fat, alcoholic beverages, and added sugars. Diet quality was incorporated using indicators relating to whole-grain cereals, lean meat, reduced/low fat dairy, and dietary variety. We investigated associations between the DGI score, sociodemographic factors, health behaviors, chronic disease risk factors, and nutrient intakes. We found associations between the DGI scores and sex, age, income, area-level socioeconomic disadvantage, smoking, physical activity, waist:hip ratio, systolic blood pressure (males only), and self-assessed health status (females only) (all P < 0.05). Higher DGI scores were associated with lower intakes of energy, total fat, and saturated fat and higher intakes of fiber, β-carotene, vitamin C, folate, calcium, and iron (P < 0.05). This food-based dietary index is able to discriminate across a variety of sociodemographic factors, health behaviors, and self-assessed health and reflects intakes of key nutrients.

The health-related quality of life of overweight and obese adolescents - a study measuring body mass index and adolescent-reported perceptions

Objective. To determine whether the health-related quality of life (HRQOL) of overweight and obese adolescents is significantly lower than that of their healthy weight counterparts, and if so, whether any demographic trends exist and the relative contribution of each HRQOL dimension.

Methods. Cross-sectional analysis of 2,890 students participating in the Pacific Obesity Prevention in Communities Project, Australia. HRQOL was measured using the Pediatric Quality of Life Inventory (PedsQL) adolescent module. Adolescent height and weight were measured by trained field workers and weight categories assigned according to the International Obesity Task Force BMI cut-off points for adolescents. Multivariate linear regression analyses were undertaken to estimate the mean differences in HRQOL scores between (i) overweight and healthy weight, and (ii) obese and healthy weight adolescents, whilst adjusting for gender, age and socioeconomic status quartile.

Results. The sample had a mean age of 14.6 years (range 11–18), 56.2% boys, 20.2% overweight and 6.3% obese. Higher weight status categories were associated with lower HRQOL scores (mean PedsQL scores: healthy weight: 79.1, overweight: 77.7 and obese: 73.7). Relative to the healthy weight group, and after adjustments, overweight and obese adolescents reported 1.44 (p = 0.005) and 5.55 (p < 0.001) lower HRQOL summary scores, respectively. Overweight adolescents reported significantly lower scores in physical and social functioning, whilst obese adolescents reported significantly lower scores in the same dimensions plus emotional functioning. Girls and younger (< 15 years) adolescents reported greater mean negative HRQOL differences associated with excess weight.

Conclusions. Overweight and obesity in adolescents are associated with significantly lower HRQOL scores.