Data Resource Profile: The Age-It Family Demography Survey (Age-It FDS)

Abstract

Introduction
Italy has recently witnessed profound transformations in family dynamics, including delayed union formation, rising cohabitation, increasing relationship instability, and postponed parenthood. These shifts have occurred alongside persistently lowest-low fertility rates and a growing use of medically assisted reproduction (MAR). Existing Italian datasets do not simultaneously capture these new family dynamics, nor do they address other emerging themes such as online dating patterns, MAR experiences and trajectories, and the forward-looking narratives through which individuals interpret uncertain futures. The Age-It Family Demography Survey (Age-It FDS), conducted within Spoke 1 of the Research Programme Age-It, is specifically designed to fill this gap.

Methods
The Age-It FDS is a cross-sectional, quota-controlled survey of 9,004 individuals aged 18--45 residing in Italy. Sampling followed a stratified design with quotas based on the intersection of age groups, sex, and macro-area (at NUTS-1 level), as well as independent quotas based on municipality size, educational attainment, and citizenship. Data were collected between May and July 2025 using a mixed-mode design (CAPI, CATI, CAWI), after extensive questionnaire design, piloting, and interviewer training.

Results
The dataset contains detailed union and childbearing histories, information on partners' characteristics across successive unions, a family complexity module, online dating, and an extensive module on MAR. A key innovation is the inclusion of narratives of the future measures, which record expectations regarding economic (in)security, employment, housing, environmental risks, political stability, and social cohesion. Data quality is supported by built-in validation routines in the computer-assisted interviewing platform (including range and consistency checks), dedicated try-out phases, and ex-post validation, including recalls and examination of non-response patterns.

Conclusion
The Age-It FDS provides an unprecedented resource for studying contemporary fertility and family dynamics in Italy. Data are stored at the Department of Statistics, Computer Science, Applications "G. Parenti" (DiSIA), University of Florence, available upon request to the corresponding author for non-commercial, scientific purposes.

Key Features

• The Age-It Family Demography Survey (Age-It FDS) is a nationally representative, quota-controlled survey of adults aged 18–45 in Italy, specifically designed to capture novel dimensions of contemporary family dynamics, including narratives of the future, medically assisted reproduction, family complexity, and digital dating.
• The survey was created in response to the lack of up-to-date, integrated information on family demographics in Italy, where new family behaviours coexist with a total fertility rate (TFR) estimated at 1.13 in 2025, a new historical minimum well below replacement level, and a growing role of medically assisted reproduction in the fertility regime.
• The dataset includes rich retrospective union and childbearing histories for respondents and their partners, detailed information on relationship trajectories across partnerships, and a dedicated retrospective family complexity module on the family of origin (parental separation and post-separation family arrangements, including details on stepfamilies and complex households).
• A distinctive innovation is the battery of questions on narratives of the future, which measures forward-looking expectations across multiple domains—economic, environmental, social, and political—at the personal, national, and intergenerational level.
• The survey combines face-to-face (CAPI) and telephone (CATI) interviews, and web-based self-administered questionnaire (CAWI) within a stratified sampling design with quotas based on the intersection of age, sex, and macro-region; municipality size, educational attainment, and citizenship; 9,004 interviews were completed, with extensive piloting, range checks, and ex-post quality controls.
• The Age-It FDS dataset is hosted at the University of Florence (DiSIA). Researchers may request access for scientific, non-commercial use by contacting the corresponding author (elisa.brini@unifi.it); access is granted only upon approval of a project application and signature of a data use agreement.

Background

In recent years, Italy has experienced one of the most profound demographic novelties of its post-war history, with a rapid transformation of family behaviours [1–3]. Long regarded as a stronghold of familism, Italy is now rapidly converging toward more individualised and diversified family patterns. Cohabitation has expanded across cohorts, nonmarital births have tripled since the early 2000s, and union dissolution has risen sharply—even in the historically conservative South—signalling a pervasive and once-unimaginable transformation in its family demographics [4, 5]. A further component of this new demographic reality concerns the digitalisation of partnership formation. Online dating has rapidly expanded in Italy, becoming a common meeting setting and reshaping opportunities for encounters across social groups. Despite its growing relevance, no existing national survey integrates detailed measures of online partner search—platform use, meeting places, and digital behaviours—within the broader architecture of union histories.

Parallel to this restructuring of family dynamics, Italy continues to experience persistently lowest-low fertility rates, with new historical minimum (1.13 estimated in 2025) and an unprecedented postponement of childbirth, with the mean maternal age at first birth rising from 31.7 in 2023 to 31.9 years in 2025. Also, Italy exhibits one of Europe’s widest gaps between desired and realised fertility and a growing share of childless women [6]. A further demographic novelty concerns the expanding role of MAR. Recent evidence shows that the contribution of MAR to total fertility increased substantially in the past decade, reaching 3.7% of total fertility, over 16% among women aged 40 and above, and more than 30% of first births after age 40 [7]. This expansion reflects not only the postponement of childbearing but also the persistence of strong childbearing desires under structural constraints, thereby reshaping reproductive trajectories.

The emergence of new family demographics also points to a profound reshaping of underlying motivations. Recent theoretical developments emphasise that individuals do not base childbearing and family decisions solely on current or past conditions, but also on narratives of the future: socially shaped, forward-looking representations of what the future may hold [8–10]. These narratives synthesise perceived opportunities and constraints ahead and influence choices, beyond conventional economic indicators. Moreover, uncertainty today is multi-dimensional: in addition to employment and income uncertainties, individuals confront environmental threats, global health crises, and volatile political and institutional settings, all of which erode “existential security” and structure imagined futures [11]. Understanding how these diverse forms of uncertainty become embedded in personal narratives requires data that capture not only objective conditions but also subjective expectations in multiple domains—economic, environmental, social, and political.

Existing Italian data sources, such as the Household Multipurpose “Families and Social Subjects” (FSS) survey carried out by the Italian National Institute of Statistics (ISTAT), and the Italian Lives (ITA.LI) study carried out by the University of Milano-Bicocca [12], provide valuable information on family and life courses but do not integrate, in a single instrument, detailed union and fertility histories, MAR experiences, family complexity, novel online dating patterns, and narratives of the future.

To address these gaps in knowledge, within Spoke 1 (“The Demography of Ageing”) of the Age-It Research Program [13], part of the National Recovery and Resilience Plan (PNRR) Extended Partnership PE8 “Consequences and Challenges of Ageing”, we designed and implemented the Age-It Family Demography Survey (Age-It FDS). Age-It is one of the largest research initiatives on ageing ever launched in Europe, with an interdisciplinary network and substantial investment aimed not only at understanding ageing but also at designing concrete solutions [14]. The Age-It FDS contributes to this agenda by offering a new data resource to explore uncharted territory in the study of fertility and family life in Italy, with particular attention to emerging behaviours, MAR, and forward-looking narratives under uncertainty.

Methods

Study Design and Population

The Age-It FDS is a cross-sectional survey—with retrospective family modules—targeting cisgender, heterosexual residents of Italy aged 18–45 years. The survey was implemented within the Age-It research project, coordinated by the Population and Society Unit (UPS) at the University of Florence, and fielded by SWG S.p.A (www.swg.it).

Sampling Strategy

To obtain a quasi-representative sample, we relied on a mixed-mode, non-probability quota sampling scheme with mode-specific sampling frames [15]. The sampling plan, validated in March 2025, was jointly developed by the UPS research team and SWG. Recruitment was implemented through three mode-specific sampling frames, with identical quota controls applied across modes: computer-assisted personal interviewing (CAPI) based on intercept recruitment; computer-assisted telephone interviewing (CATI) based on landline public directories and consented mobile numbers; and computer-assisted web interviewing (CAWI) through SWG’s opt-in panel. This reduces coverage errors – particularly in small municipalities – and to reach population segments differently accessible through various contact modes.

Quota controls were defined at the intersection of age groups (18–24, 25–34, 35–45), sex (male, female), and macro-area of residence (North-West, North-East, Centre, South, Islands), with additional independent quotas for municipality size (<5,000; 5,000–9,999; 10,000–29,999; 30,000–99,999; 100,000–249,999; >=250,000 inhabitants), educational attainment (lower secondary or less, upper secondary, tertiary), and citizenship (Italian vs foreign). Quota sampling ensures that the final sample closely mirrors the population distribution along key socio-demographic dimensions, in line with the statistics provided by ISTAT. A detailed comparison between expected and achieved distributions is reported in the Supplementary Material, showing that the achieved distribution of the sampled population closely matches the expected one (Tables S1–S8).

The CAPI collection relied on street-based recruitment in selected municipalities to reflect the quota controls. Interviewers approached individuals in public areas, performed eligibility screening (age 18–45), and verified quota availability. This procedure ensured dispersion across local contexts while maintaining alignment with the controlled quota matrix.

The CATI component used a telephone sampling frame comprising landline numbers from public registries and mobile numbers for which prior contact consent existed. When numbers were already associated with specific characteristics of the subscriber, their extraction was managed following the quota controls. For landline numbers referring to household units, interviewers verified whether an eligible respondent matching the quota control was present within the household. In cases of non-contact or refusal, replacements were selected by identifying a respondent with characteristics as similar as possible to those of the dropped case.

The CAWI component drew from SWG’s online opt-in panel (around 60,000 active members). Panellists with updated socio-demographic profiles were sampled within quota controls, with invitations issued until each quota was filled. Access was controlled through single-use encrypted tokens, and only cases that passed SWG’s standard quality control filters (e.g., consistency checks, speed thresholds, IP validation) were retained.

The target sample size was 9,000 interviews; 9,004 valid interviews were completed, with full coverage of planned quotas across age groups, sex, and territorial strata.

Data Collection Modes and Fieldwork

Data collection employed a mixed-mode strategy combining the use of three data collection modes: CAPI (approximately 7,000 interviews), CATI (around 1,000 interviews), and CAWI (around 1,000 interviews). Unlike many mixed-mode surveys where additional modes are used mainly as back-up to the main one, in the Age-It FDS, each mode constituted a separate but coordinated sample, with independent sampling frames, allowing for the detection of any mode-specific distortions. Fieldwork started in early May 2025, following a pilot phase, and concluded in July 2025.

Questionnaire Development and Informatisation

The questionnaire was developed by the UPS research team at the University of Florence and iteratively refined in collaboration with SWG. Crucially, the design of the Age-It FDS builds on international best practices. Wherever possible, survey items, batteries, and constructs were adapted from validated instruments and well-established comparative surveys—including the Generations and Gender Survey (GGS), the European Social Survey (ESS), the Italian FSS survey, and other leading demographic and social science data infrastructures [16]. This strategy ensures conceptual robustness, comparability, and alignment with global standards, while allowing integration of innovative modules tailored to the Italian demographic context.

After the questionnaire was finalised and the study protocol received ethics approval from the University of Florence Research Ethics Committee in April 2025, the instrument was fully computerised using SWG’s proprietary MACP4 software. Particular attention was devoted to implementing range checks, skip and incompatibility controls, and automated coding routines (including integration of the latest version of ISTAT’s occupational coding). Online help and explanatory texts were embedded for complex questions. The computerised questionnaire underwent systematic internal testing to verify flows, coding, and logical consistency.

Interviewer Selection and Training

Interviewers for CATI and CAPI were selected from SWG’s experienced network. A dedicated briefing was organised to present the study aims, questionnaire structure, and fieldwork procedures. Interviewers received advance access to the questionnaire to familiarise themselves with the content and flow, and completed a training assessment at the end of the session.

Pilot and Try-out

The pilot phase tested not only the comprehensibility of the questionnaire, but also the full cycle of contact, interview administration, and monitoring. Interviewers first completed the questionnaire as respondents to identify any flow or comprehension issues and then conducted pilot interviews under conditions mirroring the fieldwork. Supervisors and the project leaders monitored pilot interviews to detect any difficulties related to respondent selection, question understanding, response burden, or interview length. A debriefing with interviewers informed the final minor adjustments before the fieldwork phase.

Data Cleaning and Quality control

At the end of fieldwork, a multi-step cleaning procedure was applied to (a) verify the sample balance; (b) conduct telephone recalls of 10% of interviews to confirm participation and key answers; (c) perform consistency checks across modules; and (d) conduct a detailed inspection of missingness patterns, especially in sensitive sections (sexuality, contraception, fertility, previous partnerships). Despite the sensitivity of several modules, non-response was low, thanks to careful interviewer training and standardised protocols for handling delicate questions.

Results

Dataset Structure

The Age-It FDS dataset is organised at the individual level, with information on the timing of key life-course transitions, allowing users to construct episode-level analyses. The main components are:

• Current unions and partnership histories: partnership status, type of union (marriage, cohabitation, and living-apart-together), current partner’s socio-demographic characteristics, timing of partnership transitions, relationship satisfaction, and value similarity between partners. Retrospective partnership histories encompass first to third co-residential or marital unions, including the starting and ending dates, type of union, socio-demographic characteristics of each partner, value similarity between partners, number of children born with each partner, reason for dissolution, and dissolution initiator.
• Digital dating and meeting places: online dating behaviours, digital platforms used, duration of partner search, and information on where and how respondents met current and former partners (including online and offline settings).
• Fertility and reproductive histories: complete biological and adoptive childbirth histories (timing, parity, and union context at each birth), and information on short-term fertility intentions, desired family size, desired fertility timing, presence of stepchildren, reasons for postponement or childlessness, availability of grandparental support for future childcare, and climate-related fertility norms.
• Family complexity: parental separation and respondent’s age at parental separation, shared physical custody at key childhood ages, complex living arrangements, and exposure to parental conflict.
• MAR module: knowledge of age-related fecundity decline, diagnoses of infertility, conception attempts and outcomes, and experiences with MAR (type of treatment, number and duration of cycles, treatment location, subjective evaluation of treatment experience, and reason for discontinuation).
• Contraception and sexual function: sexual activity, contraceptive use and motivations for non-use, sexual desire, and sexual satisfaction.
• Narratives of the future and uncertainty: expectations regarding the future in multiple domains (financial condition, employment, romantic life, housing, environmental risks, political conditions, welfare institutions), perceived job-loss risk for self and partner, and expected re-employment possibilities.
• Socio-demographic and economic background: birth date, sex at birth, place of birth (Italy vs abroad), including region of birth for Italian-born respondents and country of birth for foreign-born respondents, time of arrival in Italy for foreign-born respondents, mother’s and father’s country of birth, partners’ country of birth, municipality of residence, educational attainment and timing, household size and composition, home ownership, housing costs, family income, parental socio-economic background, perceived intergenerational mobility, childhood financial hardship. Labour market information includes current employment status, occupation, working hours, job sector (public/private), job satisfaction, characteristics of the first significant job, and type of first job contract.
• Additional questions: life satisfaction, health and wellbeing, religiosity, risk aversion, pet ownership and attachment.

Data Quality

The dataset reached a high level of quality through the combination of stringent range checks, skip and incompatibility controls in the computer-assisted interviewing environment, extensive pilot testing, and ex-post verification.

Because the survey employed three independent sampling frames, mode-specific response indicators were carefully monitored. CAPI achieved 7,007 valid interviews, with 23 out-of-quota cases and 123 break-offs. CATI yielded 1,000 valid interviews, alongside frequent refusals (4,527) and 2,681 out-of-quota cases, in line with the declining reachability typical of telephone surveys in Italy. CAWI produced 997 valid interviews from 8,243 email invitations, with 329 out-of-quota cases and 624 break-offs, a pattern consistent with self-administered web surveys. Only valid interviews are included in the released dataset.

Quotas and realised sample figures match closely, with overall coverage of 100% for age groups, sex, macro-area of residence, and citizenship strata, and nearly complete for municipality size and education.

Non-response is generally low and concentrated in the most sensitive items (sexual function, and MAR), where interviewer experience and standardised protocols mitigated item non-response.

Discussion

The Age-It FDS offers rich new insights into changing demographic trends and family behaviours in Italy. First, it provides an up-to-date, quota-controlled sample reflecting the national population distribution with microdata on fertility and family life courses in Italy, at a time when rapid family change and persistent lowest-low fertility make such data crucial. Second, it integrates information that was previously scattered across multiple sources or absent, particularly regarding MAR experiences, family complexity, partners’ characteristics across successive unions, online dating, and detailed meeting histories. Third, it is theoretically anchored in the narrative framework, explicitly measuring narratives of the future and multi-dimensional uncertainty, thus allowing researchers to link subjective expectations to family behaviours [8–11]. Fourth, the multi-mode design and rigorous quality controls yield a large, balanced sample with detailed retrospective histories.

While the Age-It FDS closely aligns with population benchmarks along the main stratification variables, it should not be regarded as a substitute for probabilistic surveys designed for population-level estimation. Instead, its contribution lies in its explanatory and theoretical potential, enabling analytical and mechanism-oriented research through the integration of innovative content and multiple domains within a single survey instrument.

The primary limitation is the survey’s cross-sectional nature. Despite rich retrospective histories, the dataset cannot fully replace prospective panel data. In Italy, research on families has long suffered from a lack of timely and longitudinal data capturing the evolving complexity of life courses. Repeated calls from both the Commission for the Assurance of the Quality of Statistical Information of the Presidency of the Council of Ministers and the academic community have highlighted the need for a family panel survey and for integrated administrative–survey data to monitor increasingly complex trajectories [17–20]. The Age-It FDS does not fill this structural gap but adds an essential piece to the mosaic by delivering a high-quality cross-sectional resource aligned with contemporary theoretical debates.

A further limitation concerns the survey’s focus on cisgender heterosexual individuals, which prevents analyses of family and reproductive experiences among individuals with different gender identities and sexual orientations. This choice reflects the survey’s emphasis on fertility and MAR, which in Italy is regulated under Law 40/2004 and restricted to different-sex couples. Meaningful inclusion of same-sex couples would have required targeted oversampling, which was beyond the scope of this study. The dataset is already being used within Age-It to investigate the interplay between labour market uncertainty, narratives of the future, and fertility intentions; the experience of MAR in family life courses; and the diffusion and consequences of family complexity in Italy. Beyond these initial applications, the Age-It FDS can support research on union formation and dissolution, reproductive decision-making under uncertainty, social inequalities in access to MAR, digital dating and assortative mating, and the links between imagined futures and family behaviours. Comparative work is also possible, especially where similar modules exist in other national or international surveys.

The Age-It FDS data are stored at the Department of Statistics, Computer Science, Applications “G. Parenti” (DiSIA), University of Florence. The dataset is not publicly available in an open repository but can be obtained directly from the authors for non-commercial scientific research purposes, under a data use agreement that safeguards confidentiality. Researchers may request access by contacting the corresponding author, Dr Elisa Brini (elisa.brini@unifi.it), providing a brief project description and institutional affiliation. Access is subject to approval of the request and to a data use agreement safeguarding confidentiality. Access requests may be submitted starting 12 months after publication of this data resource.

Conclusions

The Age-It Family Demography Survey (Age-It FDS) provides a unique opportunity to advance the study of contemporary family dynamics in Italy, with novel coverage of emerging domains such as family complexity, MAR, and narratives of the future across socio-economic, environmental, and political spheres. It meets an urgent need for innovative data that can capture both objective life-course conditions and the subjective expectations through which individuals interpret an increasingly uncertain world. In addition, by integrating detailed information on digital partner search and online meeting places, the Age-It FDS opens new avenues for analysing how digital environments reshape partnership markets and interact with reproductive and family trajectories.

At the same time, the Age-It FDS highlights the structural limitations of the current Italian data infrastructure. Existing surveys are no longer sufficient to describe or explain the proliferation of non-standard, complex, and digitally mediated life courses. Italy still lacks the longitudinal, integrated data systems required to track individuals and families over time and capture the dynamic interplay between events, transitions, attitudes, and contextual changes.

The Age-It FDS should be viewed not as an endpoint but as a foundational step in building a modern evidence base for family research in Italy. It strengthens the empirical terrain, aligns with cutting-edge theoretical frameworks on uncertainty and future-oriented decision-making, and demonstrates the feasibility and scientific value of ambitious, conceptually driven population surveys. Looking ahead, the next essential steps include the creation of a national longitudinal family panel and the systematic linkage of survey and administrative sources, enabling researchers to trace family trajectories with precision and to better understand the determinants and consequences of Italy’s rapidly evolving family demography landscape. Upon availability of future funding, the survey could be fielded again in Italy or implemented in other countries experiencing sustained below replacement fertility.

Acknowledgements

We gratefully acknowledge the collaboration of SWG S.p.A. in questionnaire informatisation, fieldwork, and data processing, and the many interviewers and respondents who made the survey possible. We thank the Age-It consortium and, in particular, the partners of Spoke 1 for their feedback during the design phase of the questionnaire. Any remaining shortcomings are the sole responsibility of the authors.

Ethics Statement

The Age-It FDS obtained ethical approval from the University of Florence Research Ethics Committee (Approval n. 402, 16 April 2025). Following verification of compliance with the Committee’s recommendations, the Coordinator authorised the start of the research activities.

All participants were informed about the aims of the study, data protection procedures, and their rights, and provided informed consent prior to participation. Participation was voluntary, and respondents could skip questions or withdraw at any time. Data were stored in compliance with Regulation (EU) 2016/679 (GDPR) and processed in anonymised form in accordance with applicable ethical guidelines and data protection regulations.

Conflict of Interest Statement

None declared.

Publication Consent

All authors approved the final version of this manuscript and consent to the publication and controlled sharing of the Age-It FDS data resource for scientific research purposes, under the conditions specified in the Data Availability Statement.

Funding Statement

This article was produced with co-funding from the European Union–Next Generation EU, in the context of the National Recovery and Resilience Plan, Extended Partnership PE8 “Conseguenze e sfide dell’invecchiamento,” Project Age-It (Ageing Well in an Ageing Society).

Data Availability Statement

The Age-It Family Demography Survey (Age-It FDS) data are not publicly available in an open repository. Researchers interested in accessing the dataset for non-commercial, scientific purposes may submit a data access request by contacting the corresponding author, Dr Elisa Brini (elisa.brini@unifi.it), and providing a short description of the proposed project and institutional affiliation. Approved users will receive an anonymised dataset in .sav format, together with the questionnaire, conditional on the signature of a data use agreement to ensure confidentiality and appropriate use of the data.

AI Disclosure Statement

The authors used ChatGPT (GPT-5.3, OpenAI) for language editing. The output was reviewed and verified by the authors.

Abbreviations

Age-It:	Ageing Well in an Ageing Society (Extended Partnership PE8)
Age-It FDS:	Age-It Family Demography Survey
MAR:	Medically assisted reproduction
CAPI:	Computer-assisted personal interview
CATI:	Computer-assisted telephone interview
CAWI:	Computer-assisted web interview
DiSIA:	Department of Statistics, Computer Science, Applications “G. Parenti”, University of Florence
ISTAT:	Istituto Nazionale di Statistica (Italian National Institute of Statistics)
PNRR:	Piano Nazionale di Ripresa e Resilienza (National Recovery and Resilience Plan)
UPS:	Population and Society Unit

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