Dataset Information

Psychological, social and biological determinants of ill health (pSoBid): study protocol of a population-based study.

ABSTRACT: Disadvantaged communities suffer higher levels of physical and mental ill health than more advantaged communities. The purpose of the present study was to examine the psychosocial, behavioural and biological determinants of ill health within population groups in Glasgow that differed in socioeconomic status and in their propensity to develop chronic disease especially coronary heart disease and Type 2 diabetes mellitus.Participants were selected at random from areas known to be at the extremes of the socioeconomic continuum in Glasgow. Within the categories of least deprived and most deprived, recruitment was stratified by sex and age to achieve an overall sample containing approximately equal numbers of males and females and an even distribution across the age categories 35-44, 45-54 and 55-64 years. Individuals were invited by letter to attend for assessment of their medical history, risk factor status, cognitive function and psychological profile, morbidity, and carotid intima-media thickness and plaque count as indices of atherosclerosis. Anonymised data on study subjects were collected from the General Practice Administration System for Scotland to analyse characteristics of participants and non-participants.700 subjects were recruited. The response (active participants per 100 invitation letters) in the least deprived group was 35.1% and in the most deprived group was 20.3%. Lowest response was seen in young males (least deprived 22.4% and most deprived 14.1%).This cross-sectional study recruited the planned sample of subjects from least deprived and most deprived areas within Glasgow. As evident in other studies response differed between the most and least deprived areas. This study brought together researchers/academics from diverse disciplines to build a more sophisticated understanding of the determinants of health inequalities than can be achieved through unidisciplinary approaches. Future analyses will enable an understanding of the relationships between the different types of measure, and of the pathways that link poverty, biology, behaviour and psychology and lead to health inequalities.

SUBMITTER: Velupillai YN

PROVIDER: S-EPMC2386810 | biostudies-other | 2008 Apr

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Psychological, social and biological determinants of ill health (pSoBid): study protocol of a population-based study.

Velupillai Yoga N YN Packard Chris J CJ Batty G David GD Bezlyak Vladimir V Burns Harry H Cavanagh Jonathan J Deans Kevin K Ford Ian I McGinty Agnes A Millar Keith K Sattar Naveed N Shiels Paul P Tannahill Carol C

BMC public health 20080421

<h4>Background</h4>Disadvantaged communities suffer higher levels of physical and mental ill health than more advantaged communities. The purpose of the present study was to examine the psychosocial, behavioural and biological determinants of ill health within population groups in Glasgow that differed in socioeconomic status and in their propensity to develop chronic disease especially coronary heart disease and Type 2 diabetes mellitus.<h4>Methods</h4>Participants were selected at random from ...[more]

PMID: 18426568

Similar Datasets

Project description:BackgroundThe COVID-19 outbreak and consequent physical distance measures implemented worldwide have caused significant stress, anxiety, and mental health implications among the general population. Unemployment, working from home, and day-to-day changes may lead to a greater risk of poor mental health outcomes.ObjectiveThis paper describes the protocol for a web-based cross-sectional study that aims to address the impact of the COVID-19 pandemic on mental health.MethodsIndividuals from the general population aged 18 years or more and living in Portugal were included in this study. Data collection took place between November 10, 2020, and February 10, 2021. An exponential, nondiscriminative, snowball sampling method was applied to recruit participants. A web-based survey was developed and shared on social media platforms (eg, Facebook, Instagram, Twitter, LinkedIn, and WhatsApp groups) and through e-mail lists for recruitment of the seeds.ResultsData analysis will be performed in accordance with the different variables and outcomes of interest by using quantitative methods, qualitative methods, or mixed methods, as applicable. A total of 929 individuals had completed the web-based survey during the 3-month period; thus, our final sample comprised 929 participants. Results of the survey will be disseminated in national and international scientific journals in 2021-2022.ConclusionsWe believe that the findings of this study will have broad implications for understanding the psychological impact of the COVID-19 pandemic on Portuguese residents, as well as aspects related to the informal economy. We also hope that the findings of this study are able to provide insights and guidelines for the Portuguese government to implement action. Finally, we expect this protocol to provide a roadmap for other countries and researchers that would like to implement a similar questionnaire considering the related conclusions.International registered report identifier (irrid)DERR1-10.2196/28071.

Project description:INTRODUCTION:The goal of burn care is that 'the quality of the outcome must be worth the pain of survival'. More research is needed to understand how best to deliver care for patients with burns to achieve this aim. Loss of independence, function as well as loss of income for patients with burns and carers cause a significant burden at both individual and societal levels. Much is being done to advance knowledge in the clinical care field; however, there has been a paucity of research exploring psychosocial outcomes. This paper describes the study background and methods, as implemented in an Australian cohort study of psychosocial outcomes after major burn injuries. METHODS AND ANALYSIS:In this inception cohort study, a target sample of 230 participants, aged 18 years or over, admitted to a single statewide burns centre with a burn injury are identified by hospital staff for inclusion. Baseline survey data are collected either in person or by telephone within 28 days of the injury and participants then followed up with telephone interviews at 3, 6 and 12 months postburn. Injury and burns treatment information is collected from medical records. Social support is measured as a predictor variable using the Multidimensional Scale of Perceived Social Support. Outcome data are collected via standardised measures in the domains of Quality of Life (SF-12, EQ-5D, BSHS-B), depression (PHQ-9), post-traumatic stress disorder (PCL-C, PAS), community integration (CIQ-R) and Quality-Adjusted Life Years (EQ-5D). Additional survey questions measure life satisfaction, return to work and public services utilisation at 12 months postinjury. Data analysis methods will include analysis of variance, Pearson correlation and hierarchical multiple regression analyses. ETHICS AND DISSEMINATION:Hospital-based and University of Queensland Human Research Ethics Committees have approved the protocol. Results from the study will be disseminated at national and international conferences, in peer-reviewed journals and in a doctoral thesis. TRIAL REGISTRATION NUMBER:Australia New Zealand Clinical Trials Registry (ACTRN12616000828426). Retrospectively registered on 23 June 2016; pre-results.

Project description:Social determinants of health may affect ICU outcome, but the association between social determinants of health and delirium remains unclear. We evaluated the association between three social determinants of health and delirium occurrence and duration in critically ill adults.DesignSecondary, subgroup analysis of a cohort study.SettingSingle, 36-bed mixed medical-surgical ICU in the Netherlands.PatientsNine hundred fifty-six adults consecutively admitted from July 2016 to February 2020. Patients admitted after elective surgery, residing in a nursing home, or not expected to survive greater than or equal to 48 hours were excluded.InterventionNone.Measurements and main resultsFour factors related to three Center for Disease Control social determinants of health domains (social/community context [ethnicity], education access/quality [educational level], and economic stability [employment status and monthly income]) were collected at ICU admission from patients (or families). Well-trained ICU nurses evaluated patients without coma (Richmond Agitation Sedation Scale, -4, -5) and with the Confusion Assessment Method-ICU and/or a delirium day was defined by greater than or equal to 1 + Confusion Assessment Method-ICU and/or scheduled antipsychotic use. Multivariable logistic regression models controlling for ICU days and 10 delirium risk variables (before-ICU: age, Charlson, cognitive impairment, any antidepressant, antipsychotic, or benzodiazepine use; ICU baseline: Acute Physiology and Chronic Health Evaluation IV and admission type; daily ICU: Sequential Organ Failure Assessment, restraint use, coma, benzodiazepine, or opioid use) evaluated associations between each social determinant of health factor and both ICU delirium occurrence and duration. Delirium occurred in 393/956 patients (45.4%) for 2 days (1-5 d). Patients with low (vs high) income had more ICU delirium (p = 0.05). Multivariate analyses revealed no social determinants of health to be significantly associated with increased delirium occurrence or duration. Low (vs high) income was weakly associated with increased delirium occurrence (adjusted odds ratio, 1.83; 95% CI, 0.91-3.89). Low (vs high) education (adjusted relative risk, 1.21; 95% CI, 0.97-1.53) was weakly associated with a longer delirium duration.ConclusionsSocial determinants of health did not affect ICU delirium in one Dutch region. Additional research across different countries/regions and where additional social determinants of health are considered is needed to define the association between social determinants of health and ICU delirium.

Project description:BackgroundDisease clustering is a growing public health concern and is increasingly linked to adverse socioeconomic conditions. Few population-based studies have focussed on interaction between non-communicable diseases. In this cross-sectional study, we examine clustering of, and synergistic interactions between, frequently occurring non-communicable diseases in Katwijk, a former fishing village in the Netherlands. Additionally, our study identifies contextual variables associated with these clusters of non-communicable diseases.MethodsIn a survey among adults (>19 years) living in the former fishing village Katwijk, Netherlands, were asked about non-communicable diseases, psychological distress, self-rated health scores and contextual factors, eg, socio-demographic, psychosocial and health behavior characteristics. Interaction was measured on the additive and the multiplicative scale. We used generalized ordered logistic regression analysis to examine associations with contextual variables.ResultsThree disease clusters were found to be most prevalent among the study participants (n = 1408). Each cluster involved a combination of frequently occurring conditions in this population: psychological distress (n = 261, 19%), cardiometabolic diseases (n = 449, 32%) and musculoskeletal pain (n = 462, 33%). These three diseases interact synergistically on the additive scale to increase the odds of reporting a low self-rated health. None of the disease clusters showed a statistically significant positive interaction on a multiplicative scale. Multiple contextual factors were associated with these disease clusters, including gender, loneliness, experiencing financial stress, and a BMI≥30.ConclusionOur findings imply that psychological distress, cardiometabolic diseases and musculoskeletal pain synergistically interact, leading to a much lower self-rated health than expected. Several contextual factors are related to this interaction emphasizing the importance of a multicomponent, ecological approach.

Project description:BackgroundWith the increased availability of data, a growing number of studies have been conducted to address the impact of social determinants of health (SDOH) factors on population health outcomes. However, such an impact is either examined at the county level or the state level in the United States. The results of analysis at lower administrative levels would be useful for local policy makers to make informed health policy decisions.ObjectiveThis study aimed to investigate the ecological association between SDOH factors and population health outcomes at the census tract level and the city level. The findings of this study can be applied to support local policy makers in efforts to improve population health, enhance the quality of care, and reduce health inequity.MethodsThis ecological analysis was conducted based on 29,126 census tracts in 499 cities across all 50 states in the United States. These cities were grouped into 5 categories based on their population density and political affiliation. Feature selection was applied to reduce the number of SDOH variables from 148 to 9. A linear mixed-effects model was then applied to account for the fixed effect and random effects of SDOH variables at both the census tract level and the city level.ResultsThe finding reveals that all 9 selected SDOH variables had a statistically significant impact on population health outcomes for ≥2 city groups classified by population density and political affiliation; however, the magnitude of the impact varied among the different groups. The results also show that 4 SDOH risk factors, namely, asthma, kidney disease, smoking, and food stamps, significantly affect population health outcomes in all groups (P<.01 or P<.001). The group differences in health outcomes for the 4 factors were further assessed using a predictive margin analysis.ConclusionsThe analysis reveals that population density and political affiliation are effective delineations for separating how the SDOH affects health outcomes. In addition, different SDOH risk factors have varied effects on health outcomes among different city groups but similar effects within city groups. Our study has 2 policy implications. First, cities in different groups should prioritize different resources for SDOH risk mitigation to maximize health outcomes. Second, cities in the same group can share knowledge and enable more effective SDOH-enabled policy transfers for population health.

Dataset Information

Psychological, social and biological determinants of ill health (pSoBid): study protocol of a population-based study.

Publications

Psychological, social and biological determinants of ill health (pSoBid): study protocol of a population-based study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets