Associations of polysocial risk score, lifestyle and genetic factors with incident type 2 diabetes: a prospective cohort study

Zhao, Yimin; Li, Yueying; Zhuang, Zhenhuang; Song, Zimin; Wang, Wenxiu; Huang, Ninghao; Dong, Xue; Xiao, Wendi; Jia, Jinzhu; Z, Liu; Li, Duo; Huang, Tao

doi:10.1007/s00125-022-05761-y

Cited by 26 publications

(14 citation statements)

References 54 publications

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“…25 For example, Javed et al 26 developed and validated a poly social risk score that included 7 different SDoH domains and reported that it had good discriminatory capacity to predict atherosclerotic CVD. Similarly, Zhao et al 27 examined social risk and incident T2DM in the UK Biobank study and showed that a poly social risk score (derived from 3 SDoH domains) could reliably predict incident T2DM. Hence, these studies support our observations regarding the important role that SDoH play in determining cardiovascular risk.…”

Section: Discussionmentioning

confidence: 99%

Impact of Residential Social Deprivation on Prediction of Heart Failure in Patients With Type 2 Diabetes: External Validation and Recalibration of the WATCH-DM Score Using Real World Data

Deo,

Al-Kindi,

Motairek

et al. 2024

Circ: Cardiovascular Quality and Outcomes

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Background: Patients with type 2 diabetes are at risk of heart failure hospitalization. As social determinants of health are rarely included in risk models, we validated and recalibrated the WATCH-DM score in a diverse patient-group using their social deprivation index (SDI). Methods: We identified US Veterans with type 2 diabetes without heart failure that received outpatient care during 2010 at Veterans Affairs medical centers nationwide, linked them to their SDI using residential ZIP codes and grouped them as SDI <20%, 21% to 40%, 41% to 60%, 61% to 80%, and >80% (higher values represent increased deprivation). Accounting for all-cause mortality, we obtained the incidence for heart failure hospitalization at 5 years follow-up; overall and in each SDI group. We evaluated the WATCH-DM score using the C statistic, the Greenwood Nam D’Agostino test χ 2 test and calibration plots and further recalibrated the WATCH-DM score for each SDI group using a statistical correction factor. Results: In 1 065 691 studied patients (mean age 67 years, 25% Black and 6% Hispanic patients), the 5-year incidence of heart failure hospitalization was 5.39%. In SDI group 1 (least deprived) and 5 (most deprived), the 5-year heart failure hospitalization was 3.18% and 11%, respectively. The score C statistic was 0.62; WATCH-DM systematically overestimated heart failure risk in SDI groups 1 to 2 (expected/observed ratios, 1.38 and 1.36, respectively) and underestimated the heart failure risk in groups 4 to 5 (expected/observed ratios, 0.95 and 0.80, respectively). Graphical evaluation demonstrated that the recalibration of WATCH-DM using an SDI group-based correction factor improved predictive capabilities as supported by reduction in the χ 2 test results (801–27 in SDI groups I; 623–23 in SDI group V). Conclusions: Including social determinants of health to recalibrate the WATCH-DM score improved risk prediction highlighting the importance of including social determinants in future clinical risk prediction models.

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Section: Discussionmentioning

confidence: 99%

Impact of Residential Social Deprivation on Prediction of Heart Failure in Patients With Type 2 Diabetes: External Validation and Recalibration of the WATCH-DM Score Using Real World Data

Deo,

Al-Kindi,

Motairek

et al. 2024

Circ: Cardiovascular Quality and Outcomes

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“…We are the first to jointly evaluate the impact of multiple domains of social risk factors including socioeconomic status, psychosocial factors, and living environment on incident rosacea. And this PsRS approach allows for a comprehensive estimation of participant-level exposure to social risks from various domains ( 18 ). However, several limitations of our study warrant attention.…”

Section: Discussionmentioning

confidence: 99%

“…Guided by previous literatures ( 18 , 21 , 22 ), we classified nine social determinants of health into three domains (socioeconomic status, psychosocial factors, and living environment) to capture the overall individual-level social risk. For socioeconomic status, when the participants met the following criteria (1) the annual household income was <100,000 Chinese Yuan (low household income; bellow median); (2) the education level was lower than undergraduate degree (low education level; bellow median), they were considered at risk.…”

Section: Methodsmentioning

confidence: 99%

“…This may result from the limitation of the study that they quantified the contribution of the single psychogenic factors only, ignoring complex interconnection of social determinants of health such as individual factors, the wider social, community, physical environment factors, etc. For example, psychogenic factors, combined with socioeconomic status, neighborhood, and living environment, have been found to be the factors affecting health outcomes recently ( 18 ). Different aspects of social determinants affect people heath in a cumulative way ( 19 ), however, to our knowledge, there are no studies conducted to overall evaluate the impact of these social determinants on rosacea.…”

Section: Introductionmentioning

confidence: 99%

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Associations of polysocial risk score with incident rosacea: a prospective cohort study of government employees in China

Chen

Yang

Fan

et al. 2023

Front. Public Health

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BackgroundThe associations between single risk factors and incident rosacea have been reported, but the effects of social risk factors from multiple domains coupled remain less studied.ObjectivesTo quantify the influence of social determinants on rosacea comprehensively and investigate associations between the polysocial risk score (PsRS) with the risks of incident rosacea.MethodsThis was a prospective cohort study of government employees undertaken from January 2018 to December 2021 among participants aged >20 from five cities in Hunan province of China. At baseline, information was collected by a questionnaire and participants were involved in an examination of the skin. Dermatologists with certification confirmed the diagnosis of rosacea. The skin health status of participants was reassessed every year since the enrolment of study during the follow-up period. The PsRS was determined using the nine social determinants of health from three social risk domains (namely socioeconomic status, psychosocial factors, and living environment). Incident rosacea was estimated using binary logistic regression models adjusted for possible confounding variables.ResultsAmong the 3,773 participants who completed at least two consecutive skin examinations, there were 2,993 participants included in the primary analyses. With 7,457 person-years of total follow-up, we detected 69 incident rosacea cases. After adjustment for major confounders, participants in the group with high social risk had significantly raised risks of incident rosacea with the adjusted odds ratio (aOR) being 2.42 (95% CI 1.06, 5.55), compared to those in low social risk group.ConclusionOur findings suggest that a higher PsRS was associated with an elevated risk of incident rosacea in our study population.

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“…As described in the previous literature, the lifestyle score is classified by 5 lifestyle factors: body mass index (BMI), physical activity, diet, smoking status, and alcohol intake. 28 A BMI <25 kg/m 2 is defined as healthy; ≥150 minutes of moderate activity per week or ≥75 minutes vigorous activity per week, or a combination thereof, is defined as healthy; a healthy diet was described as an appropriate intake of 4 types of food (vegetables, fruits, fish, processed meat and nonprocessed meat); 29 , 30 never smoking is defined as healthy; and alcohol intake ≤14 g/d for women and ≤28 g/d for men is defined as healthy. A score of one point was given if “healthy” was met.…”

Section: Methodsmentioning

confidence: 99%

Associations of Modified Healthy Aging Index With Major Adverse Cardiac Events, Major Coronary Events, and Ischemic Heart Disease

Huang

Zhuang

Song

et al. 2023

JAHA

Self Cite

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Background The Healthy Aging Index (HAI) has been regarded as useful in capturing the health status of multiple organ systems. However, to what extent the HAI is associated with major cardiovascular events remains largely unknown. The authors constructed a modified HAI (mHAI) to quantify the association of physiological aging with major vascular events and explored how the effects of a healthy lifestyle can modify this association. Methods and Results The participants with either missing values of any individual mHAI component or major illnesses such as heart attack, angina and stroke, and self‐reported cancer at baseline were excluded. The mHAI components include systolic blood pressure, reaction time, forced vital capacity, serum cystatin c, and serum glucose. The authors used Cox proportional hazard models to quantify the association of mHAI with major adverse cardiac events, major coronary events, and ischemic heart disease. Cumulative incidence at 5 and 10 years was estimated, and joint analyses were stratified by age group and 4 mHAI categories. The mHAI was significantly correlated with major cardiovascular events, which is a better reflection of the aging level of the body than chronological age. An mHAI was calculated in 338 044 participants aged 38 to 73 years in the UK Biobank. Each point increase in the mHAI was associated with a 44% higher risk of major adverse cardiac events (adjusted hazard ratio [aHR], 1.44 [95% CI, 1.40–1.49]), 44% higher risk of major coronary events (aHR, 1.44 [95% CI, 1.40–1.48]), and 36% higher risk of ischemic heart disease (aHR, 1.36 [95% CI, 1.33–1.39]). The percentage of population‐attribution risk was 51% (95% CI, 47–55) for major adverse cardiac events, 49% (95% CI, 45–53) for major coronary events, and 47% (95% CI, 44–50) for ischemic heart disease, which means that a substantial portion of these events could be prevented. Systolic blood pressure was the factor most significantly associated with major adverse cardiac events (aHR, 1.94 [95% CI, 1.82–2.08]; percentage of population‐attribution risk, 36%), major coronary events (aHR, 2.01 [95% CI, 1.85–2.17]; percentage of population‐attribution risk, 38%), and ischemic heart disease (aHR, 1.80 [95% CI, 1.71–1.89]; percentage of population‐attribution risk, 32%). A healthy lifestyle significantly attenuated mHAI associations with incidence of vascular events. Conclusions Our findings indicate that higher mHAI is associated with increased major vascular events. A healthy lifestyle may attenuate these associations.

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Associations of polysocial risk score, lifestyle and genetic factors with incident type 2 diabetes: a prospective cohort study

Cited by 26 publications

References 54 publications

Impact of Residential Social Deprivation on Prediction of Heart Failure in Patients With Type 2 Diabetes: External Validation and Recalibration of the WATCH-DM Score Using Real World Data

Impact of Residential Social Deprivation on Prediction of Heart Failure in Patients With Type 2 Diabetes: External Validation and Recalibration of the WATCH-DM Score Using Real World Data

Associations of polysocial risk score with incident rosacea: a prospective cohort study of government employees in China

Associations of Modified Healthy Aging Index With Major Adverse Cardiac Events, Major Coronary Events, and Ischemic Heart Disease

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