Historical dataset of population level and growth rate for the Cluj-Napoca, Romania metro area from 1950 to 2025.

The Romanian city with the most permanent residents in 2023 was Bucharest, with over 2.14 million inhabitants. Iași was the second largest city, populated by around 392.6 thousand people, followed by Cluj-Napoca and Timișoara.

Abstract

This data repository contains survey responses collected from a telephone-based survey in January 2022, obtaining 735 valid responses from adults, above 18 years, residing in Cluj-Napoca Metropolitan Area, Romania. It surveys cultural participation practices, cultural appreciation, subjective well-being, and socio-economic position.

Methods

The data collection process involved two stages of interviews. In the first stage, the research instrument was tested through 50 interviews resulting in an average interview duration of 24 minutes and high inter-item consistency questions. The second stage consisted of 779 interviews with an average duration of 16 minutes, resulting in 829 responses, out of which 94 were excluded during the interview. Ultimately, a final database of 735 cases was used for analysis.

To ensure meaningful comparisons between the population of the municipality and the population of the metropolitan communes, the sample was designed with an oversampling of the metropolitan area of Cluj-Napoca, which accounted for 33% of the total sample or 247 cases. However, there was an unintended underrepresentation of men and young people aged 29 and below, with differences of no more than 3 percentage points. To address this issue, the responses were weighted based on the Romanian National Institute of Statistics Tempo dataset.

To ensure representativeness, the sample should be weighted using the Weight variable. The weighting is controlling for age, gender, and distribution across municipalities. The sample is statistically representative of the Cluj Metropolitan Area population with a maximum margin of error of ±3.6%. The distribution of education and occupational status in the sample closely mirrors that of the general population. Specifically, 4.1% have primary and secondary education, 46% have secondary education, and 49% have higher education.

Scales

The survey questionnaire utilized several scales and also collected socio-demographic information. The scales employed were: A. CULTURAL PARTICIPATION (Croitoru and Becuț-Marinescu, 2019; Holt, 1995, 1998) B1. THE CULTURAL APRISAL INDEX (original measure) B2. ART & CULTURE APPRECIATION (original measure) C. SUBJECTIVE WELL-BEING (SWB) Benson et al. (2019). D. SOCIO-ECONOMIC STATUS (SES) (Ganzeboom et al., 1992;Treiman, 2019). F. MEAN RATER RELIABILITY OF CULTURAL PARTICIPATION (Demanet and van Houtte, 2012; Glick, 1985; Huyge et al., 2014; Shrout and Fleiss, 1979). (significant other), MSPSS_Fam_Scale (family), MSPSS_Fr_Scale (friends).

The survey was in the Romanian language. All data in the dataset are in English, the original Romanian language formulation is provided in a separate file.

Codebook

The survey questionnaire utilized several scales and also collected socio-demographic information. The scales employed were:

SUBJECT ID id. Variable index start. Interview start timestamp end. Timestamp end interview Weight. Weighting scheme based on age, gender, metropolitan area.

A. CULTURAL PARTICIPATION In the last 12 months, how often did you carry out the following activities (whether in your locality or elsewhere). Likert scale: 6. Five or more times; 5. Four times; 4. Three times; 3. Twice; 2. Once; 1. Never; 9. DK/DA A1. I went to the cinema A2. I went to the theater A3. Visited museums, galleries or exhibitions A4. Attended indoor concerts A5. I went to the opera A6. Participated in entertainment shows (eg stand-up comedy) A7. I went to festivals A8. I read printed books A9. Involved in creative manual activities (DIY, sewing) A10. Practiced in artistic activities (eg writing, drawing, singing) A11. Participated in dance classes, creative workshops A12. Participated in online cultural activities (art galleries, performances) A13. Read e-books or listen to audio books A14. Participated in courses or workshops in spare time A15. Played online games

CulturalParticipation_Activ_CPCAscore: Categorical Principal Component Analysis A1-15, Equamax rotation, CP1, regression score. CulturalParticipation_Receptive_CPCAscore: Categorical Principal Component Analysis A1-15, Equamax rotation, CP3, , regression score. CulturalParticipation_Entertaimant_CPCAscore: Categorical Principal Component Analysis A1-15, Equamax rotation, CP2, , regression score.

B. CULTURE APPRECIATION With which of the following do you associate art and cultural experiences? Dichotomous echo scale: 1. Yes; 0. No; 9. NO/NO B1. Time spent with other people, new friends B2. Emotional experiences B3. Escape from everyday life B4. New knowledge B5. Beauty B6. Entertainment B7. Tradition B8. Diversity ArtApprisal_CPCAscore: Categorical Principal Component Analysis B1-B8, regression score.

ArtAppreciation. How important is art in your life? Likert scale: 0. Not at all important; 1. Little important; 2. Important; 3. Very important; NS/NO

C. SUBJECTIVE WELL-BEING To what extent do you agree with the following statements? (Benson et al., 2019) Likert scale: 1. Total agreement; 2. Partial agreement; 3. Partial disagreement; 4. Totally disagree C1. I am satisfied with my life. C2. What I do with my life makes sense. C3. Yesterday I was happy. C4. I wasn't anxious yesterday. WellBeing_BensonScore: Benson et al. (2019) score. WellBeing_Score_CPCAscore: Categorical Principal Component Analysis C1-C4, regression score.

E. SOCIO-ECONOMIC STATUS Education8. What is the last school you graduated from?: 1. Primary school; 2. Finished high school; 3. High school, first level (10 classes); 4. Vocational school or trades; 5. High school; 6. Post-secondary or foreman school; 7. Undergraduate university studies; 8. Postgraduate studies; 99. NS/NR; SchoolYears. Number of years of schooling IncomeHousehold. What is the total net income per month from your household, regardless of source?[...] RON 9. DK/NA HoseholdSize. How many people currently live in your household? 9. DK/NA Income_per_Capita. Income per household ISCO_4digits: What is your occupation? (recoded according to COR in four digits) Professional_Status_Score: Ganzeboom et al. (1992) SES_CPCAscore. Categorical Principal Component Analysis: SchoolYears, Income_per_Capita, Professional_Status_Score.

F. SOCIO-DEMOGRAPHIC Municipality. Where do you currently live? (drop-down list with all localities in ZMC) – SCREEN OUT FOR OTHERS Female. Gender (to be identified by the operator):. 1. Feminine. 0. Masculine Age. How old are you? (9 – for refusal/no response) Age65Plus. 1. People over 65 years old, inclusive, 0. The rest of the people Ethnicity. What is your ethnicity? 1. Romanian; 2. Hungarian; 3. Rome; 4. German; 5. Other Minority: Ethnicity 1 all non-Romanians. 0. Romanian CultureAuto Is your work connected to the field of culture?. 1. Yes. 2. No. 3. DK/NA

G. MEAN RATER RELIABILITY OF CULTURAL PARTICIPATION MRR_ActivCP_D. Dichotomized Index of Active Cultural Participation [0 is the cutpoint] MRR_RecepitvCP D. Dichotomized Index of Receptive Cultura Participation [0 is te cutpoint] MRR_EntertainmentCP_D. Dichotomized Index of Entertaimant Cultura Participation [0 is te cutpoint] MRR_CP_D. Shared types of Cultural Participation [0-3]

REFERENCES

Benson, T., Sladen, J., Liles, A., Potts, H.W.W., 2019. Personal Wellbeing Score (PWS)—a short version of ONS4: development and validation in social prescribing. BMJ Open Qual. 8, e000394. https://doi.org/10.1136/BMJOQ-2018-000394 Croitoru, C., Becuț-Marinescu, A. (Eds.), 2019. Barometrul de consum cultural 2019: Experiența și practicile culturale de timp liber. Editura Universul Academic, Bucuresti. Demanet, J., van Houtte, M., 2012. School Belonging and School Misconduct: The Differing Role of Teacher and Peer Attachment. J. Youth Adolesc. 41, 499–514. https://doi.org/10.1007/S10964-011-9674-2 Ganzeboom, H.B., De Graaf, P.M., Treiman, D.J., 1992. A Standard International Socio-Economic Index of Occupational Status. Soc. Sci. Res. 1–56. https://doi.org/10.1016/0049-089X(92)90017-B Glick, W.H., 1985. Conceptualizing and Measuring Organizational and Psychological Climate: Pitfalls in Multilevel Research. Acad. Manag. Rev. 10, 601. https://doi.org/10.2307/258140 Holt, D.B., 1998. Does Cultural Capital Structure American Consumption? J. Consum. Res. 25, 1–25. https://doi.org/10.1086/209523 Holt, D.B., 1995. How Consumers Consume: A Typology of Consumption Practices. J. Consum. Res. 22, 1–16. https://doi.org/10.1086/209431 Huyge, E., Van Maele, D., Van Houtte, M., 2014. Does students’ machismo fit in school? Clarifying the implications of traditional gender role ideology for school belonging. Gend. Educ. 27, 1–18. https://doi.org/10.1080/09540253.2014.972921 Shrout, P.E., Fleiss, J.L., 1979. Intraclass correlations: Uses in assessing rater reliability. Psychol. Bull. 86, 420–428. https://doi.org/10.1037/0033-2909.86.2.420

Abstract

During the early 1990s Romania was faced with the reproductive health consequences of an aberrant pronatalist policy enforced for several decades by the Ceausescu's regime. Health policy makers tried to rapidly respond to these consequences by adopting new health strategies to reduce maternal and infant mortality. These strategies included development of the first national family planning program; introduction of new technologies in neonatal and maternal health services; implementation of active measurements to control the HIV/AIDS epidemic; and development of social programs for abandoned, institutionalized, and drug-using children and for domestic violence.

Such a rapidly changing array of critical reproductive health issues could not have been documented and addressed with only the help of vital records. More information was needed to assess the reproductive health status of the Romanian population during a period of rapid change in health care that influenced the health of women and children.

In 1993, the Romanian Ministry of Health, with technical assistance provided by the Division of Reproductive Health of the Centers for Disease Control and Prevention (DRH/CDC), conducted the first national population-based survey of women's reproductive health (93RRHS). The survey was designed to provide the Ministry of Health, international agencies, and nongovernmental organizations active in women's and children's health with essential information on fertility, women's reproductive practices, maternal care, maternal and child mortality, health behaviors, and attitudes toward selected reproductive health issues. The 93RRHS was instrumental in developing, evaluating, and fine-tuning the national family planning program and other reproductive health policies.

In 1996, a representative sample survey of women and men aged 15-24 was implemented to document young adult's sex education, attitudes, sexual behavior and use of contraception. Such survey had never before been carried out in Eastern Europe. Survey results were used to plan effective information campaigns, policies and programs targeting young people, and to monitor and evaluate the impact of programs already in place.

In 1999, a new nationwide reproductive health survey was designed and implemented in Romania (99RRHS) using the same methodology to allow for the study of reproductive health trends among the women aged 15-44 and to document the reproductive health of men aged 15-49. The surveys employed two separate probability samples to allow independent estimates for males and females. The survey's Final Report improves the already impressive contribution of the previous two studies because: a) documents reproductive health aspects among both women and men of reproductive age (men were selected from different households than women); and b) by oversampling three target judet (Constanta, Iasi and Cluj) documents the impact of region-wide interventions, implemented with USAID support, that consists of the establishment of modern women's health clinics, training of health professionals, development of IEC messages, social marketing, and provision of highquality contraceptive supplies.

In conclusion, the results of these large nationwide cross-sectional studies implemented in 1993 (sample size of 4,861 women aged 15-44), 1996 (sample size of 2025 women and 2047 men aged 15-24), and 1999 (sample size of 6,888 women aged 15-44 and 2,434 men aged 15-49), allow for generalizing the results to the entire reproductive age population of Romania. Although the surveys did not interview the same households, by applying similar questionnaires, the same sampling and field work methodology, they allow for a) a longitudinal examination of reproductive health issues among women, b) a detailed image of specific aspects of reproductive and sexual behaviors among men and c) a programmatic evaluation of reproductive health services in three regions.

Geographic coverage

The 99RRHS was designed to collect information from a representative sample of women and men of reproductive age throughout Romania.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 99RRHS was designed to collect information from a representative sample of women and men of reproductive age throughout Romania. Respondents were selected from the universe of all females aged 15-44 years and all males aged 15-49 years, regardless of marital status, who were living in Romania when the survey was conducted. The desired sample for females was 6,500, including an oversample of women in the three US AID priority judets (Cluj, Constanta, and Iasi).

The desired sample size for males was 2,500. The female and male samples were selected independently.

The survey used a three-stage sampling design, which allows independent estimates for the female and male samples. An updated master sampling frame (EMZOT), based on the 1992 census enumeration areas, was used as the sampling frame (National Commission for Statistics, 1996). The EMZOT master sample represents 3% of the population in each judet. In the female sample, the US AID priority judets were oversampled in both urban and rural areas to allow for independent estimates with adequate precision for women's health behaviors in these judets.

Except for the three oversampled judets (in which all available census sectors in the sample were retained), the first stage of the sample design was a selection of census sectors with probability proportional to the number of households recorded in the EMZOT. This step was accomplished by using a systematic sample with a random start for the female sample. A 50% subsample of the census sectors selected in the female sample (not including the oversample in the priority judets) constituted the first stage of the male sample. Thus, the first-stage selection included 317 sectors for the female sample and 128 sectors for the male sample. In the second stage of sampling, clusters of households were randomly selected in each census sector chosen in the first stage (separate households were selected for the female and male samples). Finally, in each of the households in the female sample, one woman aged 15—44 years was selected at random for interviewing and in the male sample one man aged 15-49 years was randomly selected in each household.

Because only one woman was selected from each household with women of reproductive age, and one male was selected from households with men of reproductive age, all results have been weighted to compensate for the fact that some households included more than one eligible female or male respondent. Survey results were also weighted to adjust for oversampling of households in the three US AID priority judets, and two more weights were added to adjust for non-response and for urban-rural distribution of the population.

Cluster size was determined based on the number of households required to obtain an average of 20 completed interviews per cluster. The number of households in each cluster took into account estimates of unoccupied households, average number of women aged 15-44 per household (men aged 15-49 for the male sample), the interview of only one respondent per household, and an estimated response rate of 90% in urban areas and 92% in rural areas for women and of 85% overall for men. Cluster size was determined to be 51 households in urban areas and 59 households in rural areas for the female sample and 49 and 55 households, respectively, for the male sample.

Mode of data collection

Face-to-face [f2f]

Response rate

Of the 17,349 households selected in the female sample and 6,310 households selected in the male sample, 7,645 and 2,812 included at least one eligible respondent (a woman aged 15-44 or a man aged 15-49). Of these, 6,888 women and 2,434 men were successfully interviewed, yielding response rates of 90% and 87%, respectively. As many as four visits were placed to each household with eligible respondents who were not at home during the initial household approach.

Almost all respondents who were selected to participate and who could be reached agreed to be interviewed. Only 2% of respondents (regardless of gender) refused to be interviewed, and 7% of women and 11% of men could not be located. Response rates were not significantly different by residence, except for Bucharest, where the participation rate was slightly lower. Even though the overall response rate was similar in urban and rural areas, eligible respondents in urban areas were somewhat more likely to refuse to be interviewed; in rural areas eligible respondents were more likely to not be found at home.

Description: This data repository contains survey responses collected by the Romanian Institute for Social Research (IRES) using Computer-Assisted Telephone Interviewing (CATI) in January 2024. The dataset was designed to investigate the mediational pathways between environmental values, beliefs, norms, and energy efficiency behaviours in the context of nearly Zero Energy Building (nZEB) retrofitting. Specifically, we examine how values influence pro-environmental action purposes, mediated by climate beliefs, social norms, and trust, while considering socio-demographic attributes as confounders.The study contributes to understanding how psychological constructs and demographic factors shape pro-environmental behaviour in urban sustainability transitions. It applies the Value-Belief-Norm (VBN) theory, extending it to an urban context characterized by rapid development and demographic shifts.Data Collection & MethodologySurvey ImplementationTwo waves of interviews were conducted to ensure validity and reliability:Wave 1: 100 pilot interviews (average duration: 28 minutes) tested the internal consistency of scales, assessed using Cronbach's alpha and McDonald's omega.Wave 2: 1,226 interviews (average duration: 19 minutes) were conducted, from which 1,002 valid responses were retained (no data imputation was performed).Sampling & RepresentativityThe Cluj Metropolitan Area was oversampled, ensuring meaningful comparisons between urban and suburban areas.Initial underrepresentation of young respondents (under 29 years old) and men was corrected through post-stratification weighting based on official INS Tempo (2022) demographic data.After weighting, the final sample is statistically representative of the Cluj Metropolitan Area, with a maximum margin of error of ±3.6%.Occupational & educational distributions closely match regional labour market trends:Education levels: 4.1% primary/secondary, 46% secondary, 49% tertiary.Socio-economic Index (SEI): Constructed following Ganzeboom et al. (1992) and Treiman (2019) to measure income, education, and occupational prestige.Questionnaire Structure & ConstructsThe survey integrates validated psychometric scales from the literature, translated into Romanian, and structured into the following sections:A. Home InformationDwelling type, material, surface area, heating system, thermal insulation, and window types.B. Energy & Gas ConsumptionAppliance age, energy-saving devices, electricity/gas-saving efforts, and lighting types.C. Climate Change Beliefs, Values, Norms, and BehaviourValues (Hedonic, Egoistic, Altruistic, Biospheric) – Based on De Groot & Steg (2008).Beliefs (Climate Beliefs, Climate Urgency) – Based on van Valkengoed et al. (2021).Norms (Problem Awareness, Efficiency Commitment) – Based on van der Werff & Steg (2015).Action Purposes (Personal, Block-Level, Neighbourhood-Level) – Based on Hurst, Loo, & Walker (2023).Trust (Stakeholder trust in climate action & governance) – Based on Uslaner (2003).D. Socio-Economic & Demographic VariablesSocio-Economic Index (SEI): Composite of income, education, and occupational status.Demographics: Gender, age (55+), ethnic minority status.nZEB Retrofitting & Policy RelevanceThe dataset investigates the role of psychological and social factors in nZEB retrofitting adoption. Romania's 2023 nZEB legislation, aligned with Directive 2010/31/EU, mandates that at least 30% of a building’s energy consumption come from renewable sources (on-site or nearby). Key elements of nZEB retrofitting include:Improved insulationHigh-performance windowsOptimized heating/cooling systemsEnhanced ventilation & lightingRenewable energy integrationUnderstanding barriers and drivers of nZEB adoption is critical for designing effective policy interventions targeting sustainability in urban housing.Dataset Contentsdata.csv: Primary dataset with all survey responses (fully anonymized).transform variables.R: R script for Categorical Principal Component Analysis (C-CPA) using GiFi.lavaan.R: R script for Structural Equation Modelling (SEM) analysis using lavaan.Constructs Diagram.txt: mxGraph JScript for visual representation of the psychological constructs used in the study.VBN-A Diagram.txt: mxGraph JScript for conceptual diagram mapping VBN Theory onto nZEB retrofitting actions-purposesQuestionnaire in English.txt: Survey questionnaire (English translation).Questionnaire in Romanian.txt: Survey questionnaire (original Romanian version).Statistical AnalysisCategorical Principal Component Analysis (C-PCA):Weighting & Demographic AdjustmentsFactor loadings, KMO, Cronbach’s α, McDonald’s ω, eigenvalues provided for construct validity.Ensuring population representativity using INS Tempo (2022) benchmarks.Structural Equation Modelling (SEM):Lavaan package in RRegression coefficients reported with estimates, standard errors, and z-values.Confidence intervals included for transparency.Fit indices: R², CFI, RMSEA, and SRMR.Ethical ConsiderationsApproval & Consent: The study protocol was approved by our institution.Anonymity: Data collection adhered to strict confidentiality procedures.Informed Consent: Verbal consent was obtained before participation.