Correlation matrix for covariates tabulated in the analysis (left) and principal components analysis results (right).

Scree plot (right) for total variance explained for included variables in principal components analysis (CKD, Diabetes, Stroke, HHD). CKD, Chronic Kidney Disease. DM, Diabetes mellitus. HHD, Hypertensive Heart Disease, HIV, Human Immunodeficiency Virus. KMO, Kaiser-Meyer-Olkin test. BST, Bartlett’s Sphericity Test.</p

Simple univariate linear regression models for the correlation between covariates and OPD Adjusted (OPD divided by fertility rate).

x-axis expressed as proportion (between 0 and 1) except for GDP per capita (expressed as $US). P-values calculated for regression model. Y-axis transformed to the logit scale. Note that the y-axis intervals are not evenly spaced. Orphans per death adjusted = orphans per death divided by national average total fertility rate. Solid lines represent regression prediction, grey bands represent 95$US.</p

Kernel density functions for OPD by GDP category (Left) and boxplots of OPD by GDP category (right).

GDP categories calculated as countries with a GDP below the median value in the study data, and those countries with a GDP above the median value. Median value = US $12,939 per capita.</p

Multiple linear regression model for OPD adjusted with a logit link function.

Multiple linear regression model for OPD adjusted with a logit link function.</p

Association between 2^nd dose vaccination coverage and OPD by region.

Correlation coefficient and p-value for univariate linear regression models displayed in text in main panels. Gray bands represent 95% confidence intervals. Vaccination data as of 1st December 2021.</p

Distribution of orphans per death by country.

Countries organized by WHO region.</p

DataSheet1_The Impact of Multimorbidity on All-Cause Mortality: A Longitudinal Study of 87,151 Thai Adults.docx

Objectives: To investigate associations between multimorbidity, socio-demographic and health behaviour factors, and their interactions (multimorbidity and these factors) with all-cause mortality among Thai adults.Methods: Associations between multimorbidity (coexistence of two + chronic diseases) and mortality between 2005 and 2019 were investigated among Thai Cohort Study (TCS) participants (n = 87,151). Kaplan-Meier survival curves estimated and compared survival times. Multivariate Cox proportional hazards models examined associations between risk factors, and interactions between multimorbidity, these factors, and survival.Results: 1,958 cohort members died between 2005 and 2019. The risk of death was 43% higher for multimorbid people. In multivariate Cox proportional hazard models, multimorbidity/number of chronic conditions, age, long sleep duration, smoking and drinking were all independent factors that increased mortality risk. Women, urbanizers, university education, over 20,000-baht personal monthly income and soybean products consumption lowered risk. The interactions between multimorbidity and these variables (except for female, urbanizers and soybeans intake) also had significant (p Conclusion: The results emphasise the importance of healthy lifestyle and reduced intake of alcohol and tobacco, in reducing premature mortality, especially when suffering from multimorbidity.</p

Table_1_Hard work, long hours, and Singaporean young adults' health—A qualitative study.DOCX

BackgroundAs young adults in their 20s to 30s transitioning toward new careers and independence, their dietary and physical activity practices often change, increasing their risk of weight gain. This study explored the ways that Singaporean young adults perceived and experienced the interaction between their working hours, work, and health practices.MethodsThis research used semi-structured interviews to explore the perspectives and experiences of participants. Purposive and snowball sampling was used to recruit 15 men and 18 women, aged 23 to 36, who had worked full-time at their respective jobs in Singapore for at least 1 year. An inductive and deductive thematic analysis approach was employed.ResultsYoung working adults' commitment to work was driven by a hard-working culture, a desire to attain better jobs and remuneration, and to fulfill cultural expectations to support their multi-generation families. Their non-work time was largely spent recuperating from work by socializing over food and in sedentary activities.ConclusionFor young working adults, long work hours are normalized, even though they are a barrier to healthy diets and physical activity. Existing social and institutional norms support a culture that values commitment to work and encourages young adults to devote long hours to building a sound financial future and achieving personal and cultural aspirations. These findings have implications for long-term population health and should be considered in health promotion activities targeting young adults and barriers.</p

Fully adjusted models of any traffic injury, motorcycle (m.c.) injury, and car crash injury.

<p>* Number of study participants with injury / number of study participants exposed.</p><p>Fully adjusted models of any traffic injury, motorcycle (m.c.) injury, and car crash injury.</p

Ratio of registered motorcycles / passenger cars in Thailand between 2004 and 2012; ratio of new driving licences issued for motorcycles / automobiles.

<p>Based on source data: Road Transport Thailand—AJTP Information Center [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0120617#pone.0120617.ref007" target="_blank">7</a>]</p