Utilizing Wearable Devices To Design Personal Thermal Comfort Model

Apart from the common environmental factors such as relative humidity, radiant and ambient temperatures, studies have confirmed that thermal comfort significantly depends on internal personal parameters such as metabolic rate, age and health status. This is manifested as a difference in comfort levels between people residing under the same roof, and hence no general comprehensive comfort model satisfying everyone. Current and newly emerging advancements in state of the art wearable technology have made it possible to continuously acquire biometric information. This work proposes to access and exploit this data to build personal thermal comfort model. Relying on various supervised machine learning methods, a personal thermal comfort model will be produced and compared to a general model to show its superior performance

Localized Indoor Temperature Estimation Using Smartphone and Laptop Internal Sensors

This paper investigates a mechanism in which indoor air temperature can be predicted using the temperature sensor on the battery and the CPU of smartphones or laptops, where data is easily accessible and ubiquitous. As a case study, several machine-learning methods were used to build models from a MacBook Pro’s data and the measured surrounding air temperature. The effects of the machine learning type and input feature size (by including other parameters such as CPU processing usage and battery charge percentage) on the model accuracy were investigated. The goal is to determine a set of feature combinations that can be used to build models which can accurately predict the indoor temperature. The accuracy of these models was measured by comparing their prediction to the actual indoor temperature

Level of adherence to ocular hypotensive agents and its determinant factors among glaucoma patients in Menelik II Referral Hospital, Ethiopia

BACKGROUND: Good adherence to ocular hypotensive agents is important to control intraocular pressure and hence to prevent progressive glaucomatous optic nerve head damage. Periodic investigation of adherence is crucial in glaucoma treatment. The purpose of this study was to assess level of adherence to ocular hypotensive agents and to identify factors affecting adherence among glaucoma patients at a tertiary public eye care center. METHODS: The study was a hospital-based cross-sectional study that was conducted in Menelik II Referral Hospital from June 1, 2015 to July 31, 2015. A systematic random sampling technique was used to select 359 study participants from the source population. The study patients were interviewed and their medical charts were reviewed using a pretested structured questionnaire. Adherence was assessed using Morisky Medication Adherence Scale - 8 and adherence determinant factors were identified using multivariate binary logistic regression analysis. The association was declared statistically significant at p < 0.05. RESULTS: Among the 359 study glaucoma patients, 42.6 % were adherent to their prescribed hypotensive agents. Higher educational level (AOR = 4.60, 95 % CI: 1.01–21.03, p < 0.049), being self - employed (AOR = 6.14, 95 % CI: 1.37–27.50, p < 0.018) and taking lesser frequency of drops (AOR = 2.89, 95 % CI: 1.25–6.66, p < 0.013) were significantly associated with adherence, whereas being a farmer (AOR = 0.07, 95 % CI: 0.01–0.75, p < 0.028), having very low monthly family income (AOR = 0.22, 95 % CI: 0.06–0.77, p < 0.019) and self - purchasing of medications (AOR = 0.30, 95 % CI: 0.10–0.93, p < 0.036) were significantly associated with non-adherence. CONCLUSIONS: The study has identified the adherence level to the prescribed ocular hypotensive agents to be sub-optimal and is influenced by different factors among glaucoma patients of the public tertiary center. We recommend glaucoma care providers to pay due attention on the importance of adherence

MAGNITUDE AND ASSOCIATED FACTORS OF ZINC DEFICIENCY AMONG PATIENTS WITH ACNE VULGARIS: A CROSS-SECTIONAL STUDY

Background: Zinc deficiency is one of the main health problems affecting many peoples in developing countries. The acne like papule pustular lesions in zinc deficiency and their rapid improvement with zinc supplementation have led to assess the relationship between serum zinc levels and acne. Methods: the Facility-based cross-sectional study was conducted on 102 patients with acne vulgaris in Ayder Referral Hospital from March to April 2016. Individual dietary diversity score was determined as the sum of the number of food groups consumed in 24 hours prior to the study. Serum zinc concentration was determined using Flame Atomic Absorption Spectroscopy and zinc deficiency was defined at serum levels less than 70µg/dL. Logistic regression analysis was conducted to identify factors associated with serum zinc deficiency. Moreover, independent t-test and one-way ANOVA were done to compare the mean serum zinc level between different groups. The significance was declared at p&lt; 0.05. Results: The mean serum zinc concentration was 95.38 ± 20.95 µg/dL (95% confidence interval [CI]: 91.28 – 99.49) and 19.61% of the patients were zinc deficient. Higher prevalence of zinc deficiency was noticed in patients with acne who were regularly doing exercise (Adjusted odds ratio [AOR]=3.27; 95% CI: 1.211−8.20), drinking alcohol (AOR=3; 95% CI:1.95−11.00), consuming no meat (AOR = 4; 95% CI: 1.86−10.00) and taking milk (AOR = 5; 95% CI: 1.52−11.70). There was also a significant difference in mean score of serum zinc level among groups who experience diarrhea; women with regular menses; with cereal, vegetable, and meat consumption; and acne duration. Conclusion: The prevalence of zinc deficiency was higher among patients with acne vulgaris in the hospital. Regular exercise, no meat consumption, high alcohol and milk intake were factors associated with zinc deficiency. Clinicians should consider serum zinc level and the contributing factors while diagnosing and treating patients with acne vulgaris

Predictors of Women’s Satisfaction with Hospital-Based Intrapartum Care in Asmara Public Hospitals, Eritrea

Background. Exploring patient satisfaction contributes to provide quality maternity care, but there is paucity of epidemiologic data in Eritrea. Objectives. To determine the predictors of women's satisfaction with intrapartum care in Asmara public maternity hospitals in Eritrea. Methods. A cross-sectional study among 771 mothers who gave birth in three public Hospitals. Chi-square tests were done to analyze the difference in proportion and logistic regression to assess the predictors of satisfaction with intrapartum care. Results. Overall, only 20.8% of the participants were satisfied with intrapartum service. The key predictors of satisfaction with intrapartum care were provision of clean bed and beddings (AOR = 18.87, 2.33–15.75), privacy during examinations (AOR = 10.22, 4.86–21.48), using understandable language (AOR = 8.72, 3.57–21.27), showing how to summon for help (AOR = 8.16, 4.30–15.48), showing baby immediately after birth (AOR = 8.14, 2.87–23.07), control of the delivery room (AOR = 6.86, 2.65–17.75), receiving back massage (AOR = 6.43, 3.23–12.81), toilet access and cleanliness (AOR = 6.09, 3.25–11.42), availability of chairs for relatives (AOR = 5.96, 3.14–11.30), allowing parents to stay during labour (AOR = 3.52, 1.299–9.56), and request for permission before any procedure (AOR = 2.39, 1.28–4.46). Conclusion. To increase satisfaction with intrapartum care, maternity service providers need to address the general maternity ward cleanliness, improve the quality of physical facilities, and sensitize health providers for better communication with clients. Policy makers need to adopt strategies that ensure more women involvement in decision making and consideration of privacy and reassurance needs during the whole delivery process

Future and potential spending on health 2015-40 : development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

Background The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings We estimated that global spending on health will increase from US$9.21 trillion in 2014 to$24.24 trillion (uncertainty interval [UI] 20.47-29.72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5.3% (UI 4.1-6.8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4.2% (3.8-4.9). High-income countries are expected to grow at 2.1% (UI 1.8-2.4) and low-income countries are expected to grow at 1.8% (1.0-2.8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133-181) per capita in 2030 and$195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries. Interpretation Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential.Peer reviewe

Future and potential spending on health 2015-40: Development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

Background: The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods: We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings: We estimated that global spending on health will increase from US$9.21 trillion in 2014 to$24.24 trillion (uncertainty interval [UI] 20.47-29.72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5.3% (UI 4.1-6.8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4.2% (3.8-4.9). High-income countries are expected to grow at 2.1% (UI 1.8-2.4) and low-income countries are expected to grow at 1.8% (1.0-2.8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133-181) per capita in 2030 and$195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries. Interpretation: Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential

Trends in future health financing and coverage:future health spending and universal health coverage in 188 countries, 2016–40

BackgroundAchieving universal health coverage (UHC) requires health financing systems that provide prepaid pooled resources for key health services without placing undue financial stress on households. Understanding current and future trajectories of health financing is vital for progress towards UHC. We used historical health financing data for 188 countries from 1995 to 2015 to estimate future scenarios of health spending and pooled health spending through to 2040. MethodsWe extracted historical data on gross domestic product (GDP) and health spending for 188 countries from 1995 to 2015, and projected annual GDP, development assistance for health, and government, out-of-pocket, and prepaid private health spending from 2015 through to 2040 as a reference scenario. These estimates were generated using an ensemble of models that varied key demographic and socioeconomic determinants. We generated better and worse alternative future scenarios based on the global distribution of historic health spending growth rates. Last, we used stochastic frontier analysis to investigate the association between pooled health resources and UHC index, a measure of a country's UHC service coverage. Finally, we estimated future UHC performance and the number of people covered under the three future scenarios. FindingsIn the reference scenario, global health spending was projected to increase from US$10 trillion (95$20 trillion (18 trillion to 22 trillion) in 2040. Per capita health spending was projected to increase fastest in upper-middle-income countries, at 4·2% (3·4–5·1) per year, followed by lower-middle-income countries (4·0%, 3·6–4·5) and low-income countries (2·2%, 1·7–2·8). Despite global growth, per capita health spending was projected to range from only $40 (24–65) to$413 (263–668) in 2040 in low-income countries, and from $140 (90–200) to$1699 (711–3423) in lower-middle-income countries. Globally, the share of health spending covered by pooled resources would range widely, from 19·8% (10·3–38·6) in Nigeria to 97·9% (96·4–98·5) in Seychelles. Historical performance on the UHC index was significantly associated with pooled resources per capita. Across the alternative scenarios, we estimate UHC reaching between 5·1 billion (4·9 billion to 5·3 billion) and 5·6 billion (5·3 billion to 5·8 billion) lives in 2030. Interpretation: We chart future scenarios for health spending and its relationship with UHC. Ensuring that all countries have sustainable pooled health resources is crucial to the achievement of UHC.FundingThe Bill &amp; Melinda Gates Foundation.</p