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Conference Paper: Allostatic Load and Its Determinants In the Hong Kong General Population

TitleAllostatic Load and Its Determinants In the Hong Kong General Population
Authors
Issue Date2019
PublisherHong Kong Academy of Medicine.
Citation
Hong Kong Academy of Medicine Conference & Hong Kong Primary Care Conference 2019: People-centred Care: Towards Value-based Innovations, Hong Kong, 6-8 December 2019 How to Cite?
AbstractIntroduction: Chronic life stress can lead to physiological dysregulation and adverse health outcomes. Allostatic Load Index (ALI) is a composite index of biological markers that conceptualizes the overall physiological impact of chronic life stress, which can predict disease in later life and allow for early prevention when conditions are still reversible. However, few studies have explored determinants of ALI in Asian populations. This study aims to explore the determinants of Allostatic Load in the Hong Kong general population. Methodology: A cross-sectional study of 1,551 subjects aged 18-64 without known disease diagnosis was conducted on data from the Population Health Survey 2014/15 of the HKSAR government. Biomarkers of ALI and respective increasedrisk cut-offs were: waist-to-hip ratio≥0.9(male)/0.8(female), total-cholesterol to high-density-lipoprotein-cholesterol ratio≥4.5(male)/4.0(female), triglyceride≥1.7mmol/L, haemoglobin A1c≥5.7%, systolic blood pressure≥130mmHg and diastolic blood pressure≥80mmHg. ALI was calculated by the sum of biomarkers that fall above increased-risk cutoffs, ranging from 0-6. Potential determinants of ALI included sociodemographic (age, sex, marital status, income, education, working status) and lifestyle factors (smoking, drinking, exercise, diet, sleep). Generalized linear models with Poisson family and identity link were fitted to assess both unadjusted and adjusted effect of factors associated with ALI. Backward elimination was performed to select the most significant factors. Results: 47.2% of subjects were male and mean age was 37.5 [standard deviation (SD)=13.8]. The mean ALI was 1.6 (SD=1.6). After adjusting all baseline covariates and performing backward model selection, male (Coefficient=0.231, p<0.001), older age (Coefficient=0.058, p<0.001), current smoker (Coefficient=0.262, p=0.012) and inadequate sleep (<6hours/night) (Coefficient=0.409, p<0.001) were significantly associated with increasing ALI. Conclusions: Older age, male, smoking and inadequate sleep are associated with increased allostatic load, which smoking and sleep are the most modifiable factors. While smoking cessation is a popular health promotion strategy, the importance of adequate sleep, an easily overlooked but important modifiable factor, should be advocated.
DescriptionFree Paper Competition: Poster Presentation - Poster 012
Persistent Identifierhttp://hdl.handle.net/10722/281666

 

DC FieldValueLanguage
dc.contributor.authorYu, YTE-
dc.contributor.authorYeung, CHN-
dc.contributor.authorTang, HM-
dc.contributor.authorWan, YFE-
dc.contributor.authorLam, CLK-
dc.date.accessioned2020-03-22T04:18:01Z-
dc.date.available2020-03-22T04:18:01Z-
dc.date.issued2019-
dc.identifier.citationHong Kong Academy of Medicine Conference & Hong Kong Primary Care Conference 2019: People-centred Care: Towards Value-based Innovations, Hong Kong, 6-8 December 2019-
dc.identifier.urihttp://hdl.handle.net/10722/281666-
dc.descriptionFree Paper Competition: Poster Presentation - Poster 012-
dc.description.abstractIntroduction: Chronic life stress can lead to physiological dysregulation and adverse health outcomes. Allostatic Load Index (ALI) is a composite index of biological markers that conceptualizes the overall physiological impact of chronic life stress, which can predict disease in later life and allow for early prevention when conditions are still reversible. However, few studies have explored determinants of ALI in Asian populations. This study aims to explore the determinants of Allostatic Load in the Hong Kong general population. Methodology: A cross-sectional study of 1,551 subjects aged 18-64 without known disease diagnosis was conducted on data from the Population Health Survey 2014/15 of the HKSAR government. Biomarkers of ALI and respective increasedrisk cut-offs were: waist-to-hip ratio≥0.9(male)/0.8(female), total-cholesterol to high-density-lipoprotein-cholesterol ratio≥4.5(male)/4.0(female), triglyceride≥1.7mmol/L, haemoglobin A1c≥5.7%, systolic blood pressure≥130mmHg and diastolic blood pressure≥80mmHg. ALI was calculated by the sum of biomarkers that fall above increased-risk cutoffs, ranging from 0-6. Potential determinants of ALI included sociodemographic (age, sex, marital status, income, education, working status) and lifestyle factors (smoking, drinking, exercise, diet, sleep). Generalized linear models with Poisson family and identity link were fitted to assess both unadjusted and adjusted effect of factors associated with ALI. Backward elimination was performed to select the most significant factors. Results: 47.2% of subjects were male and mean age was 37.5 [standard deviation (SD)=13.8]. The mean ALI was 1.6 (SD=1.6). After adjusting all baseline covariates and performing backward model selection, male (Coefficient=0.231, p<0.001), older age (Coefficient=0.058, p<0.001), current smoker (Coefficient=0.262, p=0.012) and inadequate sleep (<6hours/night) (Coefficient=0.409, p<0.001) were significantly associated with increasing ALI. Conclusions: Older age, male, smoking and inadequate sleep are associated with increased allostatic load, which smoking and sleep are the most modifiable factors. While smoking cessation is a popular health promotion strategy, the importance of adequate sleep, an easily overlooked but important modifiable factor, should be advocated.-
dc.languageeng-
dc.publisherHong Kong Academy of Medicine. -
dc.relation.ispartofHong Kong Academy of Medicine Conference & Hong Kong Primary Care Conference 2019-
dc.titleAllostatic Load and Its Determinants In the Hong Kong General Population-
dc.typeConference_Paper-
dc.identifier.emailYu, YTE: ytyu@hku.hk-
dc.identifier.emailYeung, CHN: caity@connect.hku.hk-
dc.identifier.emailTang, HM: erichm@hku.hk-
dc.identifier.emailWan, YFE: yfwan@hku.hk-
dc.identifier.emailLam, CLK: clklam@hku.hk-
dc.identifier.authorityYu, YTE=rp01693-
dc.identifier.authorityWan, YFE=rp02518-
dc.identifier.authorityLam, CLK=rp00350-
dc.identifier.hkuros309452-
dc.publisher.placeHong Kong-

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