Causes for employee absenteeism vary. The commonest cause of work absenteeism is “illness-related.” Mongolia’s capital city, Ulaanbaatar, experiences high employee absenteeism during the winter than during other seasons due to the combination of extreme cold and extreme air pollution. We identified direct and indirect costs of absenteeism attributed to air pollution among private-sector employees in Ulaanbaatar. Using a purposive sampling design, we obtained questionnaire data for 1,330 employees working for private-sector companies spanning six economic sectors. We conducted 26 employee focus groups and 20 individual employer in-depth interviews. We used both quantitative and qualitative instruments to characterize the direct and indirect costs of absence due to illnesses attributed to severe air pollution during wintertime. Female employees and employees with a young child at home were more likely to be absent. Respiratory diseases accounted for the majority of reported air pollution-related illnesses. All participants perceived that air pollution adversely affected their health. Individual employee direct costs related to absence totaled 875,000 MNT ($307.10) for an average of three instances of three-day illness-related absences during the winter. This sum included diagnostic and doctor visit-related, medication costs and hospitalization costs. Non-healthcare-related direct cost (transportation) per absence was 50,000₮ ($17.60). Individual indirect costs included the value of lost wages for the typical 3-day absence, amounting to 120,000₮ ($42.10). These total costs to employees, therefore, may amount to as much as 10% of annual income. The majority of sick absences were unpaid. Overall, the cost of wintertime absences is substantial and fell disproportionately on female employees with young children.
The world population is aging and no country is immune to the consequences. We are not aware of any country-specific skin aging risk factors data for the Mongolian people. Thus, we aimed to study the risk factors associated with skin aging in the Mongolian population. A population-based cross-sectional study of 2720 study participants 18 years of age and older was performed evaluating the severity of skin aging based on cutaneous microtopography. Questionnaire data and skin physiological measurements were obtained. The odds ratios for skin aging grades associated with risk factors were estimated using ordinal logistic regression. Study participant’s mean age was 45 years, ranging from 18 to 87. After adjustment for known risk factors, skin aging was associated with demographic risk factors such as increasing age (aOR = 1.19, 95% CI 1.18–1.20), living in an urban area (aOR = 1.31, 95% CI 1.12–1.55) and lifestyle factors including being a smoker (aOR = 1.32, 95% CI 1.09–1.61), having a higher body mass index (aOR = 1.04, 95% CI 1.02–1.06) and higher levels of sun exposure time (aOR = 1.03, 95% CI 1.00–1.06) were significantly associated with higher skin aging grades. Having dry (aOR = 1.94, 95% CI 1.45–2.59) and combination skin (aOR = 1.62, 95% CI 1.22–2.16) types were also independent risk factors associated with skin aging. Having very low skin surface moisture at the T-zone (aOR = 2.10, 95% CI 1.42–3.11) was significantly related to skin aging. Older age, urban living and toxic working conditions were independent demographic risk factors related to skin aging. Smoking, higher BMI, greater levels of sun exposure were significant lifestyle risk factors. Having a skin type other than normal was a physiologic risk factor for skin aging.
Background Ulaanbaatar, Mongolia, the coldest national capital city, has the highest winter seasonal mean concentrations of PM2.5 and PM10. During January, the coldest month, peak pollution levels are > 8 times higher than the World Health Organization (WHO) guideline values are reached, on average, 15.7 times. Over 80% of this seasonal air pollution is due to domestic heating with coal stoves in large ger residential communities that surround much of the city. This report presents an analysis of the direct and indirect costs of wintertime seasonal air pollution due to the absenteeism of private-sector employees.Methods Questionnaire data were obtained for 1330 employees working for private sector companies over six economic sectors. To assess employee’s direct and indirect costs, healthcare-related costs such as cost per hospitalization, medication, and outpatient visits were calculated using the Cost-of-Illness approach. Non-healthcare costs, such as transportation and food, were also estimated in the study. Individual Indirect costs were calculated with the Human Capital Approach, which estimates the hours of work lost by the person due to disease and then multiplies total lost hours by the hourly wage.Results Approximately 60% of employee absences occurred during the coldest and hence most air polluted time of 4 months of the year from November to February. Female employees were proportionately more likely to be absent than their male counterparts. Individual direct healthcare costs attributed to air pollution related-sickness absences totaled 1,005,000₮ ($361.50) per year due to being absent from work an average of 3 days three times during the winter in Ulaanbaatar. The median cost of lost wages for 3 days’ absence is 120,000₮ ($43.20).Conclusions We conclude that wintertime pollution has a major impact on absenteeism rates among private-sector employees, and therefore, we postulate that this must be a significant driver of opportunity costs, affecting not only corporate bottom lines but also employees.
The world population is aging and no country is immune to the consequences. We are not aware of any country-specific skin aging risk factors data for the Mongolian people. Thus, we aimed to study the risk factors associated with skin aging in the Mongolian population. A population-based cross-sectional study of 2720 study participants 18 years of age and older was performed evaluating the severity of skin aging based on cutaneous microtopography. Questionnaire data and skin physiological measurements were obtained. The odds ratios for skin aging grades associated with risk factors were estimated using ordinal logistic regression. Study participant's mean age was 45 years, ranging from 18 to 87. After adjustment for known risk factors, skin aging was associated with demographic risk factors such as increasing age (aOR=1.19, 95% CI 1.18-1.20), living in an urban area (aOR=1.31, 95% CI 1.12-1.55) and working outside (aOR=1.44, 95% CI 0.88-2.39) and lifestyle factors including non-usage of sunscreen cream (aOR=1.09 95% CI 0.87-1.37), being a smoker (aOR=1.32, 95% CI 1.09-1.61), having a higher body mass index (BMI) (aOR=1.04, 95% CI 1.02-1.06) and higher levels of sun exposure time (aOR=1.03, 95% CI 1.00-1.06 ) were significantly associated with higher skin aging grades. Having dry (aOR=1.94, 95% CI 1.45-2.59) and combination skin (aOR=1.62, 95% CI 1.22-2.16) types were also independent risk factors associated with skin aging. Having very low skin surface moisture at the T-zone (aOR=2.10, 95% CI 1.42-3.11) and U-zone (aOR=1.25, 95% CI 0.95-1.65) were significantly related to skin aging. Older age, urban living, harsh working conditions, living in a ger district were independent demographic risk factors related to skin aging. Not using sunscreen cream, smoking, higher BMI, greater levels of sun exposure were significant lifestyle risk factors. Having a skin type other than normal was a physiologic risk factor for skin aging.
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