Social Inequalities on Selected Determinants of Active Aging and Health Status Indicators in a Large Brazilian City (2003-2010)

2015 ◽  
Vol 28 (1) ◽  
pp. 180-196 ◽  
Author(s):  
Luciana de Souza Braga ◽  
Maria Fernanda Lima-Costa ◽  
Cibele Comini César ◽  
James Macinko
Keyword(s):  
Health Status ◽  
Social Inequalities ◽  
Health Status Indicators ◽  
Active Aging ◽  
Aging And Health

Time Trends in Inequalities in Health

1988 ◽  
Vol 20 (3) ◽  
pp. 265-274 ◽  
Author(s):  
Roy A. Carr-Hill
Keyword(s):  
Health Status ◽  
Time Trends ◽  
Social Inequalities ◽  
Group Analysis ◽  
Health Status Measure ◽  
Inequalities In Health ◽  
Current Trends ◽  
Current Health Status ◽  
Status Measure ◽  
A Current

SummaryThe conventional belief since the publication of the Black Report is that social inequalities in health have been increasing since 1931–32 although it has been argued that the measure of inequality used is inappropriate. All analyses have been based on mortality rates which, in large part, reflect inequalities in health over the previous 50 years and not current trends. This paper argues that time trends should be assessed with a current health status measure and suggests using height at age 20 as a good measure of the achieved health status of a group. Analysis of a government survey shows that inequalities have stayed the same since 1940, both for men classified by their own occupation and for women classified by their father's occupation.

scholarly journals CARING FOR THE CAREGIVER: EXPLORING THE EXPERIENCE OF CAREGIVING FOR A CHID WITH MEDICAL COMPLEXITY

2018 ◽  
Vol 23 (suppl_1) ◽  
pp. e55-e56
Author(s):  
Jessica Teicher ◽  
Natalie Weiser ◽  
Danielle Arje ◽  
Julia Orkin
Keyword(s):  
Health Status ◽  
Social Inequalities ◽  
Qualitative Content Analysis ◽  
Qualitative Description ◽  
Medical Educator ◽  
Holistic View ◽  
The Family ◽  
Medical Complexity ◽  
The Impact ◽  
Caregiver Burnout

Abstract BACKGROUND Children with medical complexity (CMC) represent a growing population in the paediatric healthcare system. CMCs’ multiple health needs, illness severity, and fragility lead to a high degree of caregiver burnout, parental employment loss, and other social and financial consequences. Healthcare providers must consider a holistic view of the family, including consideration of social determinants of health [SDOH]: socio-economic status, employment, quality of housing, availability of social support, and access to healthcare services. This study addresses a gap in current research by exploring how caring for a CMC exacerbates social inequalities, and how these challenges may be mitigated. OBJECTIVES 1. What are the SDOH impacting CMC and their families? 2. How do families report the impact of their child’s medical complexity on their social circumstances? DESIGN/METHODS A qualitative description approach was used to enable rich data collection through semi-structured interviews until thematic saturation was reached. Nine interviews were conducted with CMC caregivers who were chosen by purposeful sampling. The interview guide was developed by expert consultation and iteratively refined. Ethics approval and written consent were obtained. Interviews were recorded and transcribed verbatim. Three team members independently coded the interviews for recurrent themes to inform qualitative content analysis. RESULTS Caregiving for a CMC is all-consuming, requiring parents to take on roles including planner, medical professional, medical educator, and advocate. Parents of CMC report three major areas negatively impacted by caregiving: 1) physical and mental health; 2) personal relationships; and 3) finances. Additionally, three themes emerged describing enablers for resiliency: 1) the CMC’s health status when well or stable in hospital; 2) acceptance of one’s limitations as a caregiver and of the family’s ‘new normal’; and 3) broad supports including medical, personal, financial, and educational. CONCLUSION The wellbeing of CMC families is impacted by medical and social factors. An interdisciplinary model of care may offset some of the caregiver’s advocacy and medical educator responsibilities. Paediatricians can support families of CMC by providing comprehensive care for all components of the child’s health status, and by including routine assessment of the family’s SDOH. Finally, explicit discussion about parental expectations and caregiver burnout helps foster a positive therapeutic relationship with the family.

scholarly journals Eating alone at each meal and associated health status by cohabitation situation among Japanese community-dwelling elderly: a cross-sectional analysis of the KAGUYA study

2020 ◽  
Author(s):  
Osamu Kushida ◽  
Jong-Seong Moon ◽  
Daisuke Matsumoto ◽  
Naomi Yamasaki ◽  
Katsuhiko Takatori
Keyword(s):  
Health Status ◽  
Functional Capacity ◽  
Health Status Indicators ◽  
Subjective Health ◽  
Community Dwelling ◽  
Care Needs ◽  
Cross Sectional ◽  
Cross Sectional Analysis ◽  
History Of ◽  
Sectional Analysis

Abstract Background: This study investigated the association between eating alone at each meal and health status including functional capacity according to cohabitation situation among Japanese community-dwelling elderly.Methods: This was a cross-sectional analysis of baseline data from the Keeping Active across Generations Uniting the Youth and the Aged (KAGUYA) study in Japan. A self-administered questionnaire was mailed to all 8004 residents aged 65 or older residing in the same Japanese town the participants in March 2016. Eating alone was assessed by first asking whether participants ate three separate meals each day (i.e., breakfast, lunch, and dinner), and those who answered affirmatively were then asked how many people were usually present at each meal. Health status was assessed in terms of subjective health, medical history, care needs, body mass index, depression, and functional capacity.Results: Data from 3057 respondents were analyzed. Among those living with others, those who reported not being in good subjective health and a history of hypertension were significantly more likely to eat alone at breakfast (odds ratio 1.27; 95% confidence interval 1.01–1.61, and 1.26; 1.06–1.49). Depressive symptoms and many subscales of functional capacity were also significantly associated with eating alone at breakfast, lunch, and dinner (P < 0.05). Among those living alone, those eating alone at breakfast had lower scores for indicators of functional capacity including information practice (P = 0.010) and total scores (P = 0.049).Conclusions: For both cohabitation situations, many health status indicators were related to eating alone at each meal, especially breakfast.

scholarly journals Relationship between Horse Racing Addiction and Health Status Indicators

2018 ◽  
Vol 18 (2) ◽  
pp. 71
Author(s):  
Sang-Gu Na ◽  
Young-Kyu Park ◽  
Young-Ah Choi ◽  
Sung-Min Cho ◽  
Kyung-Shik Lee ◽  
...  
Keyword(s):  
Health Status ◽  
Health Status Indicators ◽  
Horse Racing

scholarly journals Temporal Dietary Patterns Are Associated with Obesity in US Adults

2020 ◽  
Vol 150 (12) ◽  
pp. 3259-3268
Author(s):  
Marah M Aqeel ◽  
Jiaqi Guo ◽  
Luotao Lin ◽  
Saul B Gelfand ◽  
Edward J Delp ◽  
...  
Keyword(s):  
Health Status ◽  
Energy Intake ◽  
Dietary Patterns ◽  
Survey Design ◽  
Health Status Indicators ◽  
Dietary Quality ◽  
Time Warping ◽  
Dietary Recall ◽  
Adult Participants ◽  
Dynamic Time

ABSTRACT Background The integration of time with dietary patterns throughout a day, or temporal dietary patterns (TDPs), have been linked with dietary quality but relations to health are unknown. Objective The association between TDPs and selected health status indicators and obesity, type 2 diabetes (T2D), and metabolic syndrome (MetS) was determined. Methods The first-day 24-h dietary recall from 1627 nonpregnant US adult participants aged 20–65 y from the NHANES 2003–2006 was used to determine timing, amount of energy intake, and sequence of eating occasions (EOs). Modified dynamic time warping (MDTW) and kernel k-means algorithm clustered participants into 4 groups representing distinct TDPs. Multivariate regression models determined associations between TDPs and health status, controlling for potential confounders, and adjusting for the survey design and multiple comparisons (P &lt;0.05/6). Results A cluster representing a TDP with evenly spaced, energy balanced EOs reaching ≤1200 kcal between 06:00 to 10:00, 12:00 to 15:00, and 18:00 to 22:00, had statistically significant and clinically meaningful lower mean BMI (P &lt;0.0001), waist circumference (WC) (P &lt;0.0001), and 75% lower odds of obesity compared with 3 other clusters representing patterns with much higher peaks of energy: 1000–2400 kcal between 15:00 and 18:00 (OR: 5.3; 95% CI: 2.8, 10.1), 800–2400 kcal between 11:00 and 15:00 (OR: 4.4; 95% CI: 2.5, 7.9), and 1000–2600 kcal between 18:00 and 23:00 (OR: 6.7; 95% CI: 3.9, 11.6). Conclusions Individuals with a TDP characterized by evenly spaced, energy balanced EOs had significantly lower mean BMI, WC, and odds of obesity compared with the other patterns with higher energy intake peaks at different times throughout the day, providing evidence that incorporating time with other aspects of a dietary pattern may be important to health status.

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