Historical dataset of population level and growth rate for the Tehran, Iran metro area from 1950 to 2025.

The data include four datasets. The deaths dataset includes dead people and their attributes in the city of Tehran between 2008 and 2018. The attribute data includes the gender, date of the death, age and district where death occurred. Tehran has 22 geographical districts and population dataset in this study shows the population data separated by age groups and sex for each district. Furthermore, two spatial datasets about the city of Tehran are introduced; 1) the digital boundaries of districts and 2) urban suburbs of Tehran.

The difference between the aggregate numbers and sum of the items is because of the votes casted outside of Iran. The votes casted in Ardebil province before its introduction have been inserted in Azarbayjan-e-Sharghi province. The votes casted in Alborz province before its introduction have been inserted in Tehran province. The votes casted in Khorasan Jonoubi and Khorasan Shomali provinces before their introduction have been inserted in Khorasan Razavi province. The votes casted in Qazvin and Qom provinces before their introduction have been inserted in Tehran province. The votes casted in Golestan province before its introduction have been inserted in Mazandaran province.

Urban sprawl and urbanization as driving forces of land degradation have direct and indirect impacts on local climate dynamic. In this paper, the hypothesis that urban sprawl and unsustainable land use change cause local climate changes has been studied. Tehran as a megacity has been considered to show the urban sprawl and urbanization impacts on local climate. The methodology is divided into two main parts based on the primary datasets (satellite imagery and local climate data). The Landsat images and digital elevation model maps extracted from Shuttle Radar Topography Mission 1 Arc-Second Global data of Tehran acquired in every 5 years during June and July from 1975 to 2015 have been used for this study. The second dataset that has been used in this study contains daily mean temperature and precipitation (from 1990 to 2010) of eight meteorological synoptic stations in the study area. The results show that the rapid and unsustainable urban growth have significant effects on local climate. Moreover, it has been found that the urbanization and urban sprawl as well as unsustainable land use change caused significant change (P = 0.005) in evaporation rate in the study area (especially in east and center regions of the city with high population density).

We aimed to assess the potential socio-demographic, clinical, and lifestyle-related risk factors for kidney function decline (KFD), defined as ≥30% estimated glomerular filtration rate (eGFR) decline, in an Iranian cohort study. 7190 participants (4049 women) aged 20–90 years with 2–5 eGFR data from examinations (2001–2005 to 2015–2018) were included. Cox proportional hazard models were used to examine the association between potential risk factors and eGFR decline. During 11.5 years of follow-up, 1471 (889 women) participants had incident KFD with a crude incidence rate of 192.1 (182.6–202.2) per 10,000 person-year. Among the total population, older age, female gender, prehypertension, hypertension, diabetes, widowed/divorced states, higher triglycerides (TG), prevalent cardiovascular diseases (CVD), and higher baseline eGFR were significantly associated with higher, while moderate physical activity and a positive family history of diabetes were associated with lower risk of KFD (all p values

ObjectivesThe aim of the present study was to evaluate the prevalence of polycystic ovary syndrome (PCOS), its phenotypical and cardio-metabolic features in a community sample of the Iranian population in comparison to healthy eumenorrheic, non-hirsute women without polycystic ovaries. The second aim was to assess the cardio-metabolic characteristics of women who suffered from one criteria of PCOS compared to those healthy eumenorrheic, non-hirsute women.MethodsIn this cross-sectional population-based study, a total of 1,960 eligible women, aged (18–45 years) were recruited from the Tehran-Lipid and Glucose-Study participants and were classified as the three groups of (i) women with PCOS by the Rotterdam criteria, (ii) non-PCOS women with one criteria of PCOS and (iii) healthy eumenorrheic, non-hirsute women without polycystic ovaries morphology (PCOM) as the control group. Further PCOS women were extended to four phenotypes of hyperandrogenism, oligo-anovulation, polycystic ovaries (phenotype A), hyperandrogenism, oligo/anovulation (phenotype B), hyperandrogenism, polycystic ovaries (phenotype C) and oligo-anovulation, polycystic ovaries (phenotype D). Cardio-metabolic profiles and the prevalence of comorbidities of metabolic syndrome (MetS) and lipid abnormalities were compared among these groups linear, and the median regression models adjusted for age and body mass index.ResultsThe prevalence of PCOS according to the diagnostic criteria of the NIH, Rotterdam and AE-PCOS Society were 13.6, 19.4, and 17.8, respectively. Among those who met the Rotterdam criteria, 23.9, 46.3, 21.6, and 8.2% had phenotypes A, B, C, and D, respectively. Among the remaining 1,580 women who did not fulfil the PCOS criteria, 108 (6.8%) suffered from only oligo/anovulation, 332 (21%) only hyperandrogenism/hyperandrogenemia, 159 (16.2%) only PCOM in ultrasound and 981 (62%) were healthy eumenorrheic, non-hirsute women without PCOM. The study revealed that some adiposity indices and lipid abnormalities in PCOS phenotypes with hyperandrogenism (A, B, and C) were worse than in healthy women. By contrast, women with phenotype D did not differ from the healthy ones in terms of adiposity and lipid abnormalities. However, the respective values for other cardio-metabolic profiles and MetS rates in different phenotypes of PCOS were similar to the healthy women. Only the prevalence of MetS in phenotype A was significantly higher than in the healthy women. There were no statistically significant differences between participants with one criteria of PCOS and healthy counterparts in terms of most adiposity indexes, cardio-metabolic factors, and comorbidity of MetS and its components. However, women with hyperandrogenism had a significantly higher level of the waist to height ratio (WHtR) and hypertriglyceridemia than their healthy counterparts.ConclusionPCOS, mainly classical phenotypes A and B, are common among Iranian women of reproductive age. Women with PCOS who had androgen excess exhibited the worst lipid profile, and those who had full three criteria of the syndrome exhibited the higher rate of MetS. However, women with only ovulatory dysfunction and only PCOM had similar cardio-metabolic characteristics, compared to healthy subjects. These data suggest that routine screening for metabolic disturbances may be needed in the prevention of cardio-metabolic disorders in patients with more serious phenotypes of PCOS.

BackgroundTo examine the association between potentially modifiable risk factors with cardiovascular disease (CVD) and all-cause mortality and to quantify their population attributable fractions (PAFs) among a sample of Tehran residents.MethodsOverall, 8108 participants (3686 men) aged≥30 years, were investigated. To examine the association between risk factors and outcomes, multivariate sex-adjusted Cox proportional hazard regression analysis were conducted, using age as time-scale in two models including general/central adiposity: 1)adjusted for different independent variables including smoking, education, family history of CVD and sex for both outcomes and additionally adjusted for prevalent CVD for all-cause mortality 2)further adjusted for obesity mediators (hypertension, diabetes, lipid profile and chronic kidney disease). Separate models were used including either general or central adiposity.ResultsDuring median follow-up of >10 years, 827 first CVD events and 551 deaths occurred. Both being overweight (hazard ratio (HR), 95%CI: 1.41, 1.18–1.66, PAF 13.66) and obese (1.51, 1.24–1.84, PAF 9.79) played significant roles for incident CVD in the absence of obesity mediators. Predicting CVD, in the presence of general adiposity and its mediators, significant positive associations were found for hypercholesterolemia (1.59, 1.36–1.85, PAF 16.69), low HDL-C (1.21, 1.03–1.41, PAF 12.32), diabetes (1.86, 1.57–2.27, PAF 13.87), hypertension (1.79, 1.46–2.19, PAF 21.62) and current smoking (1.61, 1.34–1.94, PAF 7.57). Central adiposity remained a significant positive predictor, even after controlling for mediators (1.17, 1.01–1.35, PAF 7.55). For all-cause mortality, general/central obesity did not have any risk even in the absence of obesity mediators. Predictors including diabetes (2.56, 2.08–3.16, PAF 24.37), hypertension (1.43, 1.11–1.84, PAF 17.13), current smoking (1.75, 1.38–2.22, PAF 7.71), and low education level (1.59, 1.01–2.51, PAF 27.08) were associated with higher risk, however, hypertriglyceridemia (0.83, 0.68–1.01) and being overweight (0.71, 0.58–0.87) were associated with lower risk.ConclusionsModifiable risk factors account for more than 70% risk for both CVD and mortality events.

Hazard ratio for coronary heart disease risk factors based on Cox proportional hazard model. (DOCX)

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden. The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones. The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

The survey covers Iran.

Analysis unit

• Household
• Individual

Universe

The WVS for Iran covers national population aged 16 years and over, for both sexes.

Kind of data

Sample survey data [ssd]

Sampling procedure

Because of the size and complexity of the survey population, multi-stage probability sampling methods are used to develop the sample frame for this study.

Stage 1: The total household population of Iran is divided into 28 strata based on the provincial boundariestwenty-seven provinces plus the province of Tehran. In each province, the household population is divided into urban and rural areas. And each urban and rural area is further divided into Census blocks. The SCI has detailed maps of all these urban and rural areas. These areas are divided into Census Enumeration Areas or blocks, which are the smallest geographically specified units. Each unit includes at least ten dwellings for the urban areas and at least one for the rural areas. A block is defined as an area where one can start enumeration from one point and go around the unit and return to the starting point. The size and the population density of these blocks vary. The number of these blocks and their distributions as urban versus rural areas also vary from province to province. In the 28 provinces, the blocks are sampled with probabilities proportionate to size measured in total dwelling units. In the 28 provinces, blocks are sampled in proportion to the total number of dwelling units. In metropolitan areas, where blocks fall into districts with varying socioeconomic status (high, medium, low), these areas are first stratified into homogeneous districts, and then blocks are sampled.

Stage 2: The second stage units of the surveys multi-stage sample design include individual dwelling units, in which respondents reside. The SCI has provided the list of all the dwelling units within each of the selected blocks. A random sample of dwellings units will be selected for contact from the listing for each block. The result will be about 3000 dwellings of which 1800 will be from urban and 1200 from rural areas. The table below shows the population size according to the 1996 Census and its distribution of the population in the urban and rural areas by provinces, the sampled Census blocks, and the share of the sample of households for the urban and rural areas of each province. A final adjustment of the sample size may be made according to the homogeneity or the heterogeneity of the area being sampled. The level of education and economic development are considered the major criteria for assessing the degree of homogeneity of the population.

Stage 3: A single respondent from each sample dwelling unit will be selected according to procedure specified in charts provided to the interviewers. There were three differences between the 2000 and 2005 samples. First, in 2000 sample, the interviewers were not able to get to the provinces of Sistan va Baluchistan and Kurdistan. But in 2005 these provinces were surveyed. Second, in the 2005 the province of Kurdistan was oversampled to allow comparison with Iraqi Kurds. Third, the number of province ware increased to thirty-one in 2005.

The sample size for Iran is N=2667 and includes the national population aged 16 years and over for both sexes.

Mode of data collection

Face-to-face [f2f]

Research instrument

The WVS questionnaire was translated into Persian from the English questionnaire by a member of the research team. The translated questionnaire was also pre-tested. The questionnaire was administered to 200 individuals. In 2005 survey, no question was omitted.

Key information about Iran Registered Motor Vehicles

• Iran Registered Motor Vehicles was reported at 15,962.671 Unit th in Dec 2020.
• This records an increase from the previous number of 14,130.000 Unit th for Dec 2015.
• Iran Registered Motor Vehicles data is updated yearly, averaging 9,763.933 Unit th from Dec 2005 to 2020, with 12 observations.
• The data reached an all-time high of 15,962.671 Unit th in 2020 and a record low of 7,360.000 Unit th in 2005.
• Iran Registered Motor Vehicles data remains active status in CEIC and is reported by International Organization of Motor Vehicle Manufacturers. The data is categorized under World Trend Plus’s Association: Automobile Sector – Table RA.OICA.VIU: Vehicle In Use: by Country (Discontinued).

داده‌های جمعیتی استان تهران شامل روند 50 ساله، ترکیب سنی-جنسی، خانوارها و توزیع شهری-روستایی

Adjusted prevalence of CVD risk factors in participants with prevalent CVD in each phase; Tehran Lipid and Glucose Study.

Characteristics of MS cases and controls, Tehran, 2013–2015.

Adjusted means of CVD risk factors in men and women participants in each phase; Tehran Lipid and Glucose Study.