This table contains 2394 series, with data for years 1991 - 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Population group (19 items: Entire cohort; Income adequacy quintile 1 (lowest);Income adequacy quintile 2;Income adequacy quintile 3 ...), Age (14 items: At 25 years; At 30 years; At 40 years; At 35 years ...), Sex (3 items: Both sexes; Females; Males ...), Characteristics (3 items: Life expectancy; High 95% confidence interval; life expectancy; Low 95% confidence interval; life expectancy ...).

Life expectancy at birth and at age 65, by sex, on a three-year average basis.

The life expectancy figure used is for males aged under 1 year. Figures are based on the number of deaths registered and mid-year population estimates, aggregated over three consecutive years.

Expectation of life at a given age for an area is the average number of years a person would live if he or she experienced that area's age-specific mortality rates for that time period throughout his or her life. It is therefore not the number of years someone of that age in the area could actually expect to live, both because the death rates of the area are likely to change in the future and because people may live in other areas for at least part of their lives.

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Country: The country to which the data belongs. Year: The year in which the data was collected. Status: Whether the country is classified as "Developing" or "Developed". Life expectancy (men): The average life expectancy of men in that country for that year. Life expectancy (women): The average life expectancy of women in that country for that year. Adult Mortality (men): The mortality rate amongst adult men in that country for that year. Adult Mortality (women): The mortality rate amongst adult women in that country for that year. Infant deaths: The number of infant deaths in that country for that year. Alcohol: Per capita alcohol consumption (in litres of pure alcohol) in that country for that year. Percentage expenditure: Expenditure on health as a percentage of Gross Domestic Product per capita(%). Hepatitis B (men): Hepatitis B vaccination coverage in men (%). Hepatitis B (women): Hepatitis B vaccination coverage in women (%). Measles: Number of reported cases of measles in that country for that year. BMI: Average Body Mass Index of the country's population. Under-five deaths: Number of deaths under five years old. Polio: Polio (Pol3) immunization coverage among 1-year-olds (%). Total expenditure: General government expenditure on health as a percentage of total government expenditure (%). Diphtheria: Diphtheria tetanus toxoid and pertussis (DTP3) immunization coverage among 1-year-olds (%). HIV/AIDS: Deaths per 1 000 live births HIV/AIDS (0-4 years). GDP: Gross Domestic Product per capita (in USD). Population: Population of the country. thinness 1-19 years: Prevalence of thinness among children and adolescents for Age 10 to 19 (%). thinness 5-9 years: Prevalence of thinness among children for Age 5 to 9(%). Income composition of resources: Human Development Index in terms of income composition of resources (index ranging from 0 to 1). Schooling: Number of years of Schooling(years).

Context

The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions. The health dimension is assessed by life expectancy at birth, the education dimension is measured by mean of years of schooling for adults aged 25 years and more and expected years of schooling for children of school entering age. The standard of living dimension is measured by gross national income per capita. The HDI uses the logarithm of income, to reflect the diminishing importance of income with increasing GNI. The scores for the three HDI dimension indices are then aggregated into a composite index using geometric mean. Refer to Technical notes for more details. The HDI can be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The HDI simplifies and captures only part of what human development entails. It does not reflect on inequalities, poverty, human security, empowerment, etc. The HDRO provides other composite indices as a broader proxy on some of the key issues of human development, inequality, gender disparity, and poverty. A fuller picture of a country's level of human development requires analysis of other indicators and information presented in the HDR statistical annex.

Content

In this Dataset, we have Global, regional, and country/territory-level data on key dimensions of human development with various composite indices. The human development composite indices have been developed to capture broader dimensions of human development, identify groups falling behind in human progress and monitor the distribution of human development. In addition to the HDI, the indices include Multidimensional Poverty Index (MPI), Inequality-adjusted Human Development Index (IHDI), Gender Inequality Index (GII), Gender Development Index (GDI), Planetary pressures-adjusted HDI (PHDI) and Gender Social Norms Index (GSNI).

Dataset Glossary (Alphabetical Order)

• Adolescent Birth Rate - Births per 1000 Women Ages 15 to 19
• Carbon Dioxide Emissions per Capita Production in Tonnes
• Coefficient of Human Inequality
• Expected Years of Schooling - Female
• Expected Years of Schooling - Male
• Expected Years of Schooling
• Gender Development Index
• Gender Inequality Index
• Gross National Income Per Capita - Female
• Gross National Income Per Capita - Male
• Gross National Income Per Capita
• HDI Female
• HDI Male
• Human Development Index
• Inequality Adjusted Human Development Index
• Inequality in Education
• Inequality in Income
• Inequality in Life Expectancy
• Labour Force Participation Rate - Female Percentage Ages 15 and Older
• Labour Force Participation Rate - Male Percentage Ages 15 and Older
• Life Expectancy at Birth - Female
• Life Expectancy at Birth - Male
• Life Expectancy at Birth
• Material Footprint per Capita in Tonnes
• Maternal Mortality Ratio - Deaths per 100000 Live Births
• Mean Years of Schooling - Female
• Mean Years of Schooling - Male
• Mean Years of Schooling
• Planetary Pressures Adjusted Human Development Index

Cover Photo by: pch.vector on Freepik

This indicator measures inequalities in life expectancy at birth within England as a whole, each English region, and each local authority. Life expectancy at birth is calculated for each deprivation decile of lower super output areas within each area and then the slope index of inequality (SII) is calculated based on these figures.

The SII is a measure of the social gradient in life expectancy, i.e., how much life expectancy varies with deprivation. It takes account of health inequalities across the whole range of deprivation within each area and summarises this in a single number. This represents the range in years of life expectancy across the social gradient from most to least deprived, based on a statistical analysis of the relationship between life expectancy and deprivation across all deprivation deciles.

Life expectancy at birth is a measure of the average number of years a person would expect to live based on contemporary mortality rates. For a particular area and time period, it is an estimate of the average number of years a newborn baby would survive if he or she experienced the age-specific mortality rates for that area and time period throughout his or her life.

The SII for England and for regions have been presented alongside the local authority figures in order to improve the display of the indicators on the overview page. However, they should not be considered as comparators for the local authority figures. The SII for England takes account of the full range of deprivation and mortality across the whole country. This does not therefore provide a suitable benchmark with which to compare local authority results, which take into account the range of deprivation and mortality within much smaller geographies.

Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

Life expectancy at birth for males and females for Middle Layer Super Output Areas (MSOAs), Leicester: 2016 to 2020The average number of years a person would expect to live based on contemporary mortality rates.For a particular area and time period, it is an estimate of the average number of years a newborn baby would survive if he or she experienced the age-specific mortality rates for that area and time period throughout his or her life.Life expectancy figures have been calculated based on death registrations between 2016 to 2020, which includes the first wave and part of the second wave of the coronavirus (COVID-19) pandemic.

Number of deaths and mortality rates, by age group, sex, and place of residence, 1991 to most recent year.

Management summary

Decent Wage Bangladesh phase 1

The aims of the project Decent Wage Bangladesh phase 1 aimed to gain insight in actual wages, the cost of living and the collective labour agreements in four low-paid sectors in three regions of Bangladesh, in order to strengthen the power of trade unions. The project received funding from Mondiaal FNV in the Netherlands and seeks to contribute to the to the knowledge and research pathway of Mondiaal’s theory of change related to social dialogue. Between August and November 2020 five studies have been undertaken. In a face-to-face survey on wages and work 1,894 workers have been interviewed. In a survey on the cost-of-living 19,252 prices have been observed. The content of 27 collective agreements have been analysed. Fifth, desk research regarding the four sectors was undertaken. The project was coordinated by WageIndicator Foundation, an NGO operating websites with information about work and wages in 140 countries, a wide network of correspondents and a track record in collecting and analysing data regarding wage patters, cost of living, minimum wages and collective agreements. For this project WageIndicator collaborated with its partner Bangladesh Institute of Development Studies (BIDS) in Dhaka, with a track record in conducting surveys in the country and with whom a long-lasting relationship exists. Relevant information was posted on the WageIndicator Bangladesh website and visual graphics and photos on the project webpage. The results of the Cost-of-Living survey can be seen here.

Ready Made Garment (RMG), Leather and footwear, Construction and Tea gardens and estates are the key sectors in the report. In the Wages and Work Survey interviews have been held with 724 RMG workers in 65 factories, 337 leather and footwear workers in 34 factories, 432 construction workers in several construction sites and 401 workers in 5 tea gardens and 15 tea estates. The Wages and Work Survey 2020 was conducted in the Chattagram, Dhaka and Sylhet Divisions.

Earnings have been measured in great detail. Monthly median wages for a standard working week are BDT 3,092 in tea gardens and estates, BDT 9,857 in Ready made garment, Bangladeshi Taka (BDT) 10,800 in leather and footwear and BDT 11,547 in construction. The females’ median wage is 77% lower than that of the males, reflecting the gender pay gap noticed around the world. The main reason is not that women and men are paid differently for the same work, but that men and women work in gender-segregated parts of the labour market. Women are dominating the low-paid work in the tea gardens and estates. Workers aged 40 and over are substantially lower paid than younger workers, and this can partly be ascribed to the presence of older women in the tea gardens and estates. Workers hired via an intermediary have higher median wages than workers with a permanent contract or without a contract. Seven in ten workers report that they receive an annual bonus. Almost three in ten workers report that they participate in a pension fund and this is remarkably high in the tea estates, thereby partly compensating the low wages in the sector. Participation in an unemployment fund, a disability fund or medical insurance is hardly observed, but entitlement to paid sick leave and access to medical facilites is frequently mentioned. Female workers participate more than males in all funds and facilities. Compared to workers in the other three sectors, workers in tea gardens and estates participate more in all funds apart from paid sick leave. Social security is almost absent in the construction sector. Does the employer provide non-monetary provisions such as food, housing, clothing, or transport? Food is reported by almost two in ten workers, housing is also reported by more than three in ten workers, clothing by hardly any worker and transport by just over one in ten workers. Food and housing are substantially more often reported in the tea gardens and estates than in the other sectors. A third of the workers reports that overtime hours are paid as normal hours plus a premium, a third reports that overtime hours are paid as normal hours and another third reports that these extra hours are not paid. The latter is particularly the case in construction, although construction workers work long contractual hours they hardly have “overtime hours”, making not paying overtime hours not a major problem.

Living Wage calculations aim to indicate a wage level that allows families to lead decent lives. It represents an estimate of the monthly expenses necessary to cover the cost of food, housing, transportation, health, education, water, phone and clothing. The prices of 61 food items, housing and transportation have been collected by means of a Cost-of-Living Survey, resulting in 19,252 prices. In Chattagram the living wage for a typical family is BDT 13,000 for a full-time working adult. In Dhaka the living wage for a typical family is BDT 14,400 for a full-time working adult. In both regions the wages of the lowest paid quarter of the semi-skilled workers are only sufficient for the living wage level of a single adult, the wages of the middle paid quarter are sufficient for a single adult and a standard 2+2 family, and the wages in the highest paid quarter are sufficient for a single adult, a standard 2+2 family, and a typical family. In Sylhet the living wage for a typical family is BDT 16,800 for a full-time working adult. In Sylhet the wages of the semi-skilled workers are not sufficient for the living wage level of a single adult, let alone for a standard 2+2 family or a typical family. However, the reader should take into account that these earnings are primarily based on the wages in the tea gardens and estates, where employers provide non-monetary provisions such as housing and food. Nevertheless, the wages in Sylhet are not sufficient for a living wage.

Employment contracts. Whereas almost all workers in construction have no contract, in the leather industry workers have predominantly a permanent contract, specifically in Chattagram. In RMG the workers in Chattagram mostly have a permanent contract, whereas in Dhaka this is only the case for four in ten workers. RMG workers in Dhaka are in majority hired through a labour intermediary. Workers in the tea gardens and estates in Chattagram in majority have no contract, whereas in Sylhet they have in majority a permanent contract. On average the workers have eleven years of work experience. Almost half of the employees say they have been promoted in their current workplace.

COVID-19 Absenteeism from work was very high in the first months of the pandemic, when the government ordered a general lock down (closure) for all industries. Almost all workers in construction, RMG and leather reported that they were absent from work from late March to late May 2020. Female workers were far less absent than male workers, and this is primarily due to the fact that the tea gardens and estates with their highly female workforce did not close. From 77% in March-May absenteeism tremendously dropped till 5% in June-September. By September the number of absent days had dropped to almost zero in all sectors. Absenteeism was predominantly due to workplace closures, but in some cases due to the unavailability of transport. More than eight all absent workers faced a wage reduction. Wage reduction has been applied equally across the various groups of workers. The workers who faced reduced earnings reported borrowing from family or friends (66% of those who faced wage reduction), receiving food distribution of the government (23%), borrowing from a micro lenders (MFI) (20%), borrowing from other small lenders (14%), receiving rations from the employer (9%) or receiving cash assistance from the government or from non-governmental institutions (both 4%). Male workers have borrowed from family or friends more often than female workers, and so did workers aged 40-49 and couples with more than two children.

COVID-19 Hygiene at the workplace After return to work workers have assessed hygiene at the workplace and the supply of hygiene facilities. Workers are most positive about the safe distance or space in dining seating areas (56% assesses this as a low risk), followed by the independent use of all work equipment, as opposed to shared (46%). They were least positive about a safe distance between work stations and number of washrooms/toilets, and more than two in ten workers assess the number of washrooms/toilets even as a high risk. Handwashing facilities are by a large majority of the workers assessed as adequate with a low risk. In contrast, gloves were certainly not adequately supplied, as more than seven in ten workers state that these are not adequately supplied. This may be due to the fact that use of gloves could affect workers’ productivity, depending on the occupations.

Context

The Heart Attack Risk Prediction Dataset serves as a valuable resource for delving into the intricate dynamics of heart health and its predictors. Heart attacks, or myocardial infarctions, continue to be a significant global health issue, necessitating a deeper comprehension of their precursors and potential mitigating factors. This dataset encapsulates a diverse range of attributes including age, cholesterol levels, blood pressure, smoking habits, exercise patterns, dietary preferences, and more, aiming to elucidate the complex interplay of these variables in determining the likelihood of a heart attack. By employing predictive analytics and machine learning on this dataset, researchers and healthcare professionals can work towards proactive strategies for heart disease prevention and management. The dataset stands as a testament to collective efforts to enhance our understanding of cardiovascular health and pave the way for a healthier future.

Content

This synthetic dataset provides a comprehensive array of features relevant to heart health and lifestyle choices, encompassing patient-specific details such as age, gender, cholesterol levels, blood pressure, heart rate, and indicators like diabetes, family history, smoking habits, obesity, and alcohol consumption. Additionally, lifestyle factors like exercise hours, dietary habits, stress levels, and sedentary hours are included. Medical aspects comprising previous heart problems, medication usage, and triglyceride levels are considered. Socioeconomic aspects such as income and geographical attributes like country, continent, and hemisphere are incorporated. The dataset, consisting of 8763 records from patients around the globe, culminates in a crucial binary classification feature denoting the presence or absence of a heart attack risk, providing a comprehensive resource for predictive analysis and research in cardiovascular health.

Dataset Glossary (Column-wise)

• Patient ID - Unique identifier for each patient
• Age - Age of the patient
• Sex - Gender of the patient (Male/Female)
• Cholesterol - Cholesterol levels of the patient
• Blood Pressure - Blood pressure of the patient (systolic/diastolic)
• Heart Rate - Heart rate of the patient
• Diabetes - Whether the patient has diabetes (Yes/No)
• Family History - Family history of heart-related problems (1: Yes, 0: No)
• Smoking - Smoking status of the patient (1: Smoker, 0: Non-smoker)
• Obesity - Obesity status of the patient (1: Obese, 0: Not obese)
• Alcohol Consumption - Level of alcohol consumption by the patient (None/Light/Moderate/Heavy)
• Exercise Hours Per Week - Number of exercise hours per week
• Diet - Dietary habits of the patient (Healthy/Average/Unhealthy)
• Previous Heart Problems - Previous heart problems of the patient (1: Yes, 0: No)
• Medication Use - Medication usage by the patient (1: Yes, 0: No)
• Stress Level - Stress level reported by the patient (1-10)
• Sedentary Hours Per Day - Hours of sedentary activity per day
• Income - Income level of the patient
• BMI - Body Mass Index (BMI) of the patient
• Triglycerides - Triglyceride levels of the patient
• Physical Activity Days Per Week - Days of physical activity per week
• Sleep Hours Per Day - Hours of sleep per day
• Country - Country of the patient
• Continent - Continent where the patient resides
• Hemisphere - Hemisphere where the patient resides
• Heart Attack Risk - Presence of heart attack risk (1: Yes, 0: No)

Structure of the Dataset

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Acknowledgement

This dataset is a synthetic creation generated using ChatGPT to simulate a realistic experience. Its purpose is to provide a platform for beginners and data enthusiasts, allowing them to create, enjoy, practice, and learn from a dataset that mirrors real-world scenarios. The aim is to foster learning and experimentation in a simulated environment, encouraging a deeper understanding of data analysis and interpretation.

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Thumbnail by: vectorjuice on Freepik

Excel file contains 3 sheets:

Data (data used in the analyses)

ReadMe (explanation of variable names)

TL_repeat (data of repeated telomere measurements for quality control: 1 sample of 1 individual on multiple gels, 5 individuals with 2 samples on same gel)

Haldane’s rule predicts that particularly high fitness reduction should affect the heterogametic sex of interspecific hybrids. Despite the fact that hybridization is widespread in birds, survival of hybrid individuals is rarely addressed in studies of avian hybrid zones, possibly because of methodological constraints. Here, having applied capture-mark-recapture models to an extensive, 19-year-long dataset on individually marked birds, we estimate annual survival rates of hybrid individuals in the hybrid zone between herring (Larus argentatus) and Caspian (L. cachinnans) gulls. In both parental species, males have a slightly higher survival rate than females (model-weighted mean ± SE: herring gull males 0.88 ± 0.01, females 0.87 ± 0.01, Caspian gull males 0.88 ± 0.01, females 0.87 ± 0.01). Hybrid males do not survive for a shorter time than non-hybrid ones (0.88 ± 0.01), whereas hybrid females have the lowest survival rate among all groups of individuals (0.83 ± 0.03). This translates to a shorter adult (reproductive) lifespan (on average by 1.7-1.8 years, i.e. ca 25%) compared to non-hybrid females. We conclude that, in line with Haldane’s rule, the lower survival rate of female hybrids may contribute to selection against hybrids in this hybrid zone.

Estimated number of persons on July 1, by 5-year age groups and gender, and median age, for Canada, provinces and territories.

PurposeIncreasing the level of gravity passively on a centrifuge, should be equal to or even more beneficial not only to astronauts living in a microgravity environment but also to patients confined to bed. Gravity therapy (GT) may have beneficial effects on numerous conditions, such as immobility due to neuromuscular disorders, balance disorders, stroke, sports injuries. However, the appropriate configuration for administering the Gz load remains to be determined.MethodsTo address these issues, we studied graded G-loads from 0.5 to 2.0g in 24 young healthy, male and female participants, trained on a short arm human centrifuge (SAHC) combined with mild activity exercise within 40–59% MHR, provided by an onboard bicycle ergometer. Hemodynamic parameters, as cardiac output (CO), stroke volume (SV), mean arterial pressure (MAP), systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) were analyzed, as well as blood gas analysis. A one-way repeated measures ANOVA and pairwise comparisons were conducted with a level of significance p < 0.05.ResultsSignificant changes in heart rate variability (HRV) and its spectral components (Class, Fmax, and VHF) were found in all g loads when compared to standing (p < 0.001), except in 1.7 and 2.0g. There were significant changes in CO, cardiac index (CI), and cardiac power (CP) (p < 0.001), and in MAP (p = 0.003) at different artificial gravity (AG) levels. Dose-response curves were determined based on statistically significant changes in cardiovascular parameters, as well as in identifying the optimal G level for training, as well as the optimal G level for training. There were statistically significant gender differences in Cardiac Output/CO (p = 0.002) and Cardiac Power/CP (p = 0.016) during the AG training as compared to standing. More specifically, these cardiovascular parameters were significantly higher for male than female participants. Also, there was a statistically significant (p = 0.022) gender by experimental condition interaction, since the high-frequency parameter of the heart rate variability was attenuated during AG training as compared to standing but only for the female participants (p = 0.004).ConclusionThe comprehensive cardiovascular evaluation of the response to a range of graded AG loads, as compared to standing, in male and female subjects provides the dose-response framework that enables us to explore and validate the usefulness of the centrifuge as a medical device. It further allows its use in precisely selecting personalized gravity therapy (GT) as needed for treatment or rehabilitation of individuals confined to bed.