Access to this full-text is provided by Springer Nature.
Content available from Scientific Reports
This content is subject to copyright. Terms and conditions apply.
1
Vol.:(0123456789)
Scientic Reports | (2024) 14:13766 | https://doi.org/10.1038/s41598-024-64737-7
www.nature.com/scientificreports
Residents’ future residential
preference and its aecting factors
in the rapid urbanization zone
of rural China from a family life
cycle perspective
Mengke Zhang
1,3, Yan Tong
2,3*, Yuhang Ge
1, Jin Guo
1, Hanlin Nie
1, Zhijun Wang
1 &
Liangxin Fan
1
Understanding farmers’ future residential preferences and the factors aecting these choices is crucial
for tackling the issues related to hollow village management and rural planning. Despite limited
research on the role of the family life cycle, this study explores how the family life cycle, characteristics
of the household head, livelihood strategies, and resource availability shape farmers’ future
residential preferences. Data were collected from 777 households in China’s main grain-producing
area. The ndings reveal that 52.90% of households prefer to stay in their current rural residences.
Other favored options are elderly care facilities (13.90%), living with children in the village (12.36%),
and ancestral homes (11.68%). The family life cycle signicantly aects these preferences (p < 0.01),
with changes in family structure and age leading to dierent living choices. Specically, households in
the initial (71.29%), burden (70.32%), and stable stages (40.14%) prefer their current rural residences,
while those in the maintenance and empty-nest stages opt for living with their children’s residences
(22.22% and 16.96%, respectively) or in elderly care facilities (30.00% and 33.93%). Meanwhile,
age, health, income, livelihood strategies, and land ownership also markedly inuence the choice
of residence. Recommendations include educational programs for elderly rural residents, improving
older individuals’ adaptability to rural changes, creating more rural employment opportunities, and
enhancing medical and infrastructural services for the sustainable rural development.
Keywords Residential preference, Homestead sites, Resident livelihood, Village planning, Rural China
Rapid urbanization signicantly aects the relationship between urban and rural areas in developing countries,
resulting in overcrowded cities, hollowed villages, and environmental degradation1,2. According to World Urbani-
zation Prospects, the global population reached 8 billion in 2022, with the urban population projected to increase
from 57% in 2022 to 68% by 2050, while the rural population is expected to decrease from 43% in 2022 to 32% by
20503. e World Bank has reported a decline in rural populations in various regions. For example, rural India
(1993–2022) witnessed a decline from 892 to 682 million, while urban populations rose from 242 to 460 million.
In Africa, rural population (1993–2018) decreased from 886 to 789 million, with the urban populations increas-
ing from 293 to 604 million. Similarly, rural China (1993–2022) experienced a decrease from 835 to 569 million.
In low-income countries, underdeveloped infrastructure, poor housing conditions4 and poverty5,6 are main
barriers for rural development. In Asian countries, the imbalance in rural–urban development has led to the
temporary internal migration of rural residents7. A signicant number of rural residents have moved to cities
and markedly developed regions in search of employment opportunities. Farmers’ education and their income
involved in agriculture are the primary factors inuencing their migration out of rural areas8,9. A survey of
Bangladesh showed that economic gaps of rural–urban caused their seasonal migration, and household income
and land ownership of farmers were key factors for their choice of future places of residence10.
OPEN
1School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, Henan,
China. 2School of Architectural and Artistic Design, Henan Polytechnic University, Jiaozuo 454000, China. 3These
authors contributed equally: Mengke Zhang and Yan Tong. *email: Tongyan0123@126.com
Content courtesy of Springer Nature, terms of use apply. Rights reserved
2
Vol:.(1234567890)
Scientic Reports | (2024) 14:13766 | https://doi.org/10.1038/s41598-024-64737-7
www.nature.com/scientificreports/
China, being one of the most populous agricultural countries in the world11, places great importance on the
development of rural areas for the overall economic and social stability of the nation. However, due to regional
dierences and imbalances, the process of urbanization in China’s rural areas involves substantial population
movements, with farmers moving from rural areas to cities in pursuit of employment opportunities12. is
kind of population mobility has given rise to various social problems, such as the issue of le-behind elderly
and children, as well as rural hollowing. Understanding the preferences and needs of farmers regarding future
residence, as well as the factors inuencing these preferences and needs, is crucial for eective urban and rural
planning13 and developing policies strategies for the Chinese rural development.
Numerous factors, including geographical location, environmental conditions, socio-economic background
and infrastructure, inuence farmers’ living preferences and future residence. In Yucatán Peninsula, Mexico,
the distance to the city centre is main factor aecting farmers’ agricultural activities and living choices14. In
Morocco, residents’ satisfaction with their current housing construction types relatively aects their future liv-
ing choices15. Daniel etal.16 noted that Indonesia has a signicant young population in rural areas, with many
enterprises operating in these regions. Consequently, young Indonesians prefer staying in their current rural
homes for the foreseeable future. In European countries, elderly households typically prefer rural living owing
to their economic circumstances and lifestyle preferences17,18. In China, the migration of young people is con-
sidered to be a process closely related to economic factors. Family structure and income may aect their future
living choices19. Chinese rural planning through rational allocation of rural construction land, thus improving
farmers’ living satisfaction20. Among them, social networks and resource endowments also may aect farmers’
living choices by changing living environment in rural China.
e concept of the family life cycle, proposed by Rowntree21 and further developed by Glick22, provides a
framework for understanding family decision-making and behaviour analysis involved in dierent families’ life
cycle stages. Rowntree’s23 ve-stage hypothesis, adjusted based on the characteristics of Chinese family social
structure, includes young couple families, growing nuclear families, mature nuclear families, extended families,
and empty nest couple families. Understanding the family life cycle is closely related to consumption, particularly
in terms of how it aects expenditures across dierent consumption items and inuences consumption intentions
and decisions24. Newly married families exhibit the highest willingness to purchase housing, and the single stage
is characterized by a vibrant rental market25. Farmers, from the standpoint of the family life cycle, have varying
consumption structures and migration patterns.
e family life cycle leads to variations in family size, structure, and subsequently aects housing demand,
employment choices, and economic status26. ese factors have signicant implications for farmers’ future resi-
dence preferences and consequently inuence rural settlement patterns27. erefore, studying the inherent con-
nection between the family life cycle and housing choice can help us better comprehend and predict the specic
housing needs of families at dierent stages. Farmers at dierent stages of the family life cycle may have diverse
requirements and preferences for future residence. e family life cycle theory provides a crucial theoretical
foundation for investigating farmers’ anticipated residential location preferences. erefore, the objectives of
this study are as follows: (1) To identify future residential site preferences from the perspective of the household
life cycle. (2) To explore farmers’ perceptions regarding future residential selection and the factors inuencing
their choices. (3) To investigate the reasons behind farmers’ future residential location choices at dierent stages
of the family life cycle and provide corresponding recommendations.
Although the existing literature has studied the inuencing factors of farmers’ residential preferences, empiri-
cal research in China is relatively insucient, especially from the perspective of the family life cycle. e unique-
ness of the current study is to identify farmers’ future residential preferences from views of the individual farmer
and family aspects. By exploring farmers’ residential preferences and the aecting factors, we provide a scientic
basis for rural residential planning, social policy and rural development strategies. is study also provides a
perspective for family-based decision-making studies from the family life cycle.
Materials and methods
Study area and sampled villages
As a prominent agricultural province and a key grain-producing region in China, Henan province has con-
sistently held a leading position in terms of its planting area and yield for major grain crops like wheat. With
a permanent population of 98.72 million as year of 2023 and notable population density28, Henan province
exhibits distinctive regional characteristics and holds signicant value on a national scale29. Furthermore, as
China’s urbanization process accelerates, the number of oating populations in Henan province continues to
grow, serving as a representative example that sheds light on rural social changes, the evolution of urban–rural
relations, and the assessment of policy implementation eects in China. As the population density and number
of oating populations increase in Henan province, substantial social and economic changes have occurred
within rural areas. Notably, the prevalence of hollow villages and the rise in idle homesteads have emerged as
prominent issues30. ese not only pose signicant challenges in the process of rural modernization in China but
also serve as typical research cases for comprehending nationwide rural social and economic transformations.
Huaxian, located in the northern part of Henan province (Fig.1), boasting a predominantly at terrain with
an elevation of 60m. e region experiences a humid climate, characterized by an annual precipitation range
of 500–700mm, while annual evaporation rates uctuate between 1000 and 2000mm. Covering a total area
of 1814 km2, which includes 1340 km2 of arable land, Huaxian serves as the primary grain production zone
within Henan province, focusing on the cultivation of wheat and corn as the main crops. e total population
of Huaxian stands at 1,156,400, with 710,900 individuals residing in rural areas. e average annual household
income in the region amounts to 11,087.81 USD, primarily derived from agriculture, animal husbandry, and
labor export in rural areas.
Content courtesy of Springer Nature, terms of use apply. Rights reserved
3
Vol.:(0123456789)
Scientic Reports | (2024) 14:13766 | https://doi.org/10.1038/s41598-024-64737-7
www.nature.com/scientificreports/
For the purpose of this study, four villages were selected: Zhangzhuang, Qianliucun, Lihusi, and Beishizhuang.
ese villages were chosen based on their proximity to the county center and their sources of household income
(Table1).
Zhangzhuang is positioned as a suburban village, located 5.6km away from the county center. It is situated
within the urban‒rural fringe of the town (Chengguan) and covers an area of 0.29 km2, including 0.18 km2
of arable land. is village is home to a total of 123 households, with an average annual household income of
12,510.60 USD. e primary sources of income in Zhangzhuang are the handicra industry, small businesses,
and labor export.
Qianliucun is classied as an outer suburb village and is situated 19.2km away from the county center. It
spans an area of 1.83 km2, with 1.58 km2 dedicated to arable land. e village accommodates a total of 290
households, with an annual household income of 11,821.07 USD. e primary sources of income in Qianliucun
are agriculture and labor exports.
Lihusi is another outer suburb village, located 24.1km away from the county center. e village covers an area
of 0.16 km2, with 1.33 km2 allocated for arable land. Lihusi comprises 257 households, with an annual household
income of 10,912.72 USD. e primary sources of income in Lihusi are agriculture and handicras.
Beishizhuang, which is also positioned as an outer suburb village, stands at a distance of 30.0km from the
county center. It covers an area of 0.70 km2, including 0.57 km2 of arable land, and is home to 107 households.
e average annual household income in Beishizhuang is 10,340.61 USD (Table4).
Data collection
We conducted a questionnaire from July to September 2022 through face-to-face interviews. Prior to the inter-
views, households were notied by village leaders. Participation in the survey was voluntary. As a token of appre-
ciation, each respondent received towels valued at USD 2 upon completion of the survey. e interviews were
Figure1. Location of the study area.
Table 1. Distribution of sampled villages and households.
Tow n Sampled vi llage Distance from county center/km Sampled household Percentage (%) Main source of households
income
Chengguan Zhangzhuang 5.6 123 15.83 Handicra, small business,
and labor export
Baidaokou Qianliucun 19.2 290 37.32 Agriculture and labor export
Baidaokou Lihusi 24.1 257 33.08 Agriculture and handicras
Baliying Beishizhuang 30.0 107 13.78 Agriculture and small
business
Tot al – – 777 100 –
Content courtesy of Springer Nature, terms of use apply. Rights reserved
4
Vol:.(1234567890)
Scientic Reports | (2024) 14:13766 | https://doi.org/10.1038/s41598-024-64737-7
www.nature.com/scientificreports/
conducted with the head of the household, as they hold the decision-making power within the family. In cases
where the wife’s preferred residence diered from that of the husband, the decision of the head of the household
prevailed, as they typically have the highest decision-making authority regarding the choice of residence in the
family. For adult children living with their parents, we investigated the head of the adult children’s household.
We collected a total of 777 valid questionnaires, with the breakdown as follows: Zhangzhuang (123), Qianliucun
(290), Lihusi (257), and Beishizhuang (107). Additionally, we conducted telephone interviews for unoccupied
dwellings and obtained 93 responses in total: Zhangzhuang (15), Qianliucun (30), Lihusi (27), and Beishizhuang
(21) (Table1). e survey was administered by one postgraduate student and two senior college students serv-
ing as interviewers. e survey collected information the following aspects: (1) Characteristics of the household
head (age, educational status, and health), living arrangements (solitary, couples residing together, two genera-
tions cohabiting, three generations living together). (2) Economic features of the households (annual household
income, sources of income, level of economic growth, and land ownership). (3) Economic characteristics (annual
income, sources of income, place of residence). (4) Attributes of the houses (aliated properties, area, and year
of construction) and future choice of residence (Table2).
Data analysis
Multiple unordered logistic regression models were used to analyse the dependent variable as an unordered
multicategorical situation. e future residential sites for farm households include: father’s old house, current
house, children’s house in the village, house in the city (children’s house), and nursing home, which represent a
multivariate unordered choice. In this study, we selected the multivariate unordered logistic model to analyze
the factors inuencing the residential space selection of farm households.
where P(y = j) denotes the probability of a farmer’s choice of the willingness, Xk denotes the kth independent
variable aecting the future residential site selection, the independent variables are divided into three major
categories: basic household characteristics, household economic characteristics and resource endowment, and
βjk denotes a vector of regression coecients for the independent variables. Taking J as the reference type, the
ratio
Py
=
j
/
Py
=
J
of the probability of a farmer’s other types of residential site selection to the probability
of a J type of residence,
P(
y=j
|
x
)
P(
y=J|x
)
is the event-occurrence ratio, abbreviated odds.
is study aims to synthesize research ndings from related elds both domestically and internationally.
Foreign studies on farm households’ residential site selection have identied the main inuencing factors as
the family’s economic and social characteristics, housing construction, and the type of housing31. Domesti-
cally, research has shown that farmers’ willingness to select a residential location primarily takes into account
social networks32, income, and family characteristics33. Based on these factors, this paper selects three types of
inuencing factors: personal characteristics, family characteristics, and resource endowment, as independent
variables. As the empty nest period represents the nal stage of the family life cycle, it is used as the reference
group for this variable. e dependent variable in this study is the type of future residential site selection for
farmers (ancestral house, current rural house, children’s house in the village, children’s house in the city, elder
care facility). Given that elder care facilities are emerging as a new trend in China’s future old-age care, they are
considered the reference group (Table5).
Division of family life cycle
e family life cycle represents the comprehensive trajectory of a family, including stages of formation, growth,
maturation, and eventual decline or extinction34. is life cycle involves changes in family composition and
membership, including the establishment and dissolution of marital unions, the birth and departure of children,
and the passing of family members35. In 1947, Glick proposed a six-stage classication method to categorize
surveyed families into dierent life cycle stages22. However, his structural division only considers the core and
stable forms of the family, assumes a family size of two, and overlooks other forms such as single-child families,
unmarried individuals, divorced individuals, and remarried individuals, resulting in theoretical limitations.
erefore, when applying the family life cycle theory to study various regions, it is essential to consider China’s
national conditions and regional dierences36. In rural China, the birth of a family is not marked by marriage
but by the division of the family into separate households. is leads to a more complex family structure, with
(1)
ln
P
y=j|x
P
y=J|x
=αj+
K
k=1
βjkX
k
Table 2. Life cycle phasing of a family (Glick, 1947).
Life cycle stage of a family Description Identify
Formative stages Initial households Young newly married couple or may have children under the age of 16 and there are no individuals over the age of
65
Growth stages Households in a stage of burden e youngest child is under 16 years old, and the oldest member of the couple is over 65 years old
Maturity stages Stabilized households e youngest child in the family is over 16 years old, and there are no elderly individuals over 65 years old
Expansionist stages Maintenance-stage households e youngest child in the family is over 16 years old, and there are elderly individuals over 65 years old
Systolic stages Empty-nesting households Aer the division of family property, parents live alone
Content courtesy of Springer Nature, terms of use apply. Rights reserved
5
Vol.:(0123456789)
Scientic Reports | (2024) 14:13766 | https://doi.org/10.1038/s41598-024-64737-7
www.nature.com/scientificreports/
some elderly individuals living with their children37. As a result, the family life cycle theory acknowledges that
families have dierent contents and tasks in dierent life courses but does not provide a dened set of stages.
Researchers can thus divide the stages of the family life cycle based on the specic research content and purpose,
aligning them with the research theme. Taking into account the structure of rural households in China and local
realities, and considering the focus of our study, the classication is based on the life cycle of households with
adult children, and we classify families into ve distinct life cycle stages: the initial stage, burden stage, stable
stage, maintenance stage, and empty nest stage (Table2). is classication is grounded in the consideration of
whether teenagers have reached the age of 16 and whether elderly individuals have attained the age of 65, serving
as the basis for categorizing the family life cycle. Given the context of rural China, where multiple generations
oen live together, we did not account for the core family structure of couples. us, in this investigation, we
relied on the family life cycle division proposed by scholars Wang Wei and Wu Haitao, combined with our eld
research, we classied families into ve distinct life cycle stages, namely, the initial stage, burden stage, stable
stage, maintenance stage, and empty nest stage (Table2).
(1)e initial stage of a family pertains to couples who have recently married. Within this stage, family mem-
bers may not yet have children or may have children under the age of 16. Additionally, there are no individuals
over the age of 65. (2) e burden stage includes couples with one or more young children, where the youngest
child is under 16years old, and the oldest member of the couple is over 65years old. (3) e stabilization stage
corresponds to a phase in which children gradually mature and enter adolescence. In this stage, the youngest
child in the family is over 16years old, and there are no elderly individuals over 65years old. (4) e maintenance
stage occurs when a child leaves home to embark on adult life. At this point, the youngest child in the family
is over 16years old, and there are elderly individuals over 65years old. (5) e empty nest period refers to the
establishment of an independent living arrangement aer the children leave the family, following the separation
of the parents, the division of family property, and when only the parents live alone (Table2).
Ethical approval
is research study is performed per the principles of the Declaration of Helsinki. It did not require ethical
approval because the participants willingly shared their future residential preference. e data for this study
were obtained through a voluntary survey involving adult participants. roughout the course of this research,
we adhered to relevant ethical guidelines, ensuring the respect of participants’ rights and privacy. e design
and implementation of the survey followed ethical principles, including the protection of participant privacy,
assurance of data condentiality, and respect for voluntary participation. We further conrm that this study
posed no risks of physical, psychological, or social harm to participants, and all research procedures complied
with international ethical research standards. We declare that all data collection and questionnaires survey of the
manuscript is under supervised and approved by Academic and Review Board of Henan Polytechnic University.
Informed consent
e authoritative oce gave written consent, and the authors got everyone’s verbal informed consent.
Result
Characteristics of sampled households
e mean age of household heads stands at 51.40 (± 13.51) years, while the average years of education received
is 7.68 (± 3.55) years. e average annual household income is 11.08 (± 20.96) thousand USD (Table3), and
the average number of children per household is 2.15 (Table5). On average, each family possesses 1.37 (± 0.92)
houses, and approximately 32.56% of families own two or more houses. Among the four sampled villages,
Beishizhuang boasts the highest average number of houses per household, with an average of 1.73 (± 2.05)
houses per household, followed by Lihusi (1.44 ± 0.56), Zhangzhuang (1.38 ± 0.54), and Qianliucun (1.16 ± 0.45)
(Table3). Regarding the distribution of life cycle stages across the villages, the burden stage holds the largest
proportion, spanning from 26.17 to 30.35%. It is succeeded by the initial stage, which ranges from 23.79 to
Table 3. Characteristics of sampled household (mean ± SD). Note: Family life cycle stages: 1, initial stage;
2, burden stage; 3, stable stage; 4, maintenance stage; 5, empty nest stage. Dierent letters within a column
indicate statistically dierences at p < 0.05, Tukey’s post-hoc tests: (a > b > c). “a”, “b” and “c” represent dierent
groups of means, and the alphabetical order reects the ranking of the means from highest to lowest, “ab”,
“bc” and “ac” indicated that the dierence between the corresponding groups did not reach a signicant level
(p ≥ 0.05).
Villages Age of household head (years) Education of household head
(years) Number of homesteads owned Household annual income
(1000 USD) Family life cycle stages
Zhangzhuang 54.28 ± 14.44a7.85 ± 3.54 1.38 ± 0.54bc 12.51 ± 23.86 1.99 ± 1.19
Qianliucun 49.80 ± 13.32b7.84 ± 3.37 1.16 ± 0.45c11.82 ± 22.04 2.47 ± 1.10
Lihusi 52.23 ± 13.11ab 7.46 ± 3.60 1.44 ± 0.56b10.91 ± 19.68 2.43 ± 1.17
Beishizhuang 50.65 ± 13.13ab 7.55 ± 3.87 1.73 ± 2.05a10.35 ± 15.86 2.79 ± 1.36
Mean 51.40 ± 13.51 7.68 ± 3.55 1.37 ± 0.92 11.08 ± 20.96 2.45 ± 1.16
Content courtesy of Springer Nature, terms of use apply. Rights reserved
6
Vol:.(1234567890)
Scientic Reports | (2024) 14:13766 | https://doi.org/10.1038/s41598-024-64737-7
www.nature.com/scientificreports/
30.89%. e stable stage ranges from 12.15 to 21.03%, while the empty-nest stage varies from 12.41 to 23.36%.
e maintenance stage constituted 11.71% of the distribution (Table4 and Fig.2).
Residents’ preference for housing choices in the future
e primary preference for future housing selection among residents is residing in their current rural house,
accounting for 52.90% of the selections. is is followed by a preference for elderly care facilities (13.90%),
children’s houses within the village (12.36%), and ancestral houses (11.68%). e option with the lowest ratio is
residing in children’s houses in the city (9.78%) (Fig.3).
Residents’ intentions regarding their future living place exhibit variations across dierent stages of the fam-
ily life cycle. Individuals in the initial stage, burden stage, and stable stage of the family life cycle tend to favor
their current rural house as their future abode, with proportions ranging from 40.14 to 71.29%. Conversely, for
families in the maintenance stage and empty-nest stage, living in their children’s village house become the pre-
ferred choices, with ratios ranging from 30.00 to 33.93%. Notably, the proportion of residents selecting elderly
care facilities as their future housing settlement in the stable stage, maintenance stage, and empty-nest stage is
higher, ranging from 16.96 to 22.22%, compared to the initial stage and burden stage, which range from 9.13 to
9.57% (Figs.4and 5).
Furthermore, the proximity of villages to the county center inuences residents’ intentions for future housing
settlement. Housing choices dier among villages, with those closer to the county center showing a tendency
for fewer residents to select living in their children’s houses in the future and a greater inclination toward elderly
care facilities as their future living place (Table6).
Factors aecting residents’ future residential preference
We conducted a logistic regression analysis to investigate the eect of family life cycle, individual characteristics,
socioeconomic factors and resource endowment on the likelihood of future residential preference. A total of 11
variables were included in the model and elderly care facility set as a reference variable of the model (Tables5,
6 and 7).
Compared with living in elderly care facility, families in the initial stage (odds ratio, OR = 83.34, p < 0.01),
burden stage (OR = 44.40, p < 0.01) and stable stage (OR = 5.23, p < 0.05) are more willing to choose to live in the
current rural house in the future. Families in the maintenance stage (i.e., supporting families) are more likely to
choose to live in a current rural house (OR = 9.21, p < 0.01) and their children’s houses in villages (OR = 17.80,
p < 0.01) than live in elderly care facilities.
Elders are likely to choose to live in a current rural house (OR = 1.08, p < 0.01) and children’s houses in villages
(OR = 1.10, p < 0.01). Households with high annual incomes are reluctant to choose to live in their children’s
houses in cities (OR = 0.90, p < 0.05) in the future. By contrast, farmers who perceived low household income
growth tend to live in their children’s houses in villages (OR = 6.96, p < 0.05) in the future. Farmers with low health
condition were less likely to choose to live in their children’s house in the villages (OR = 0.15, p < 0.05) and cities
(OR = 0.19, p < 0.05) in the future compare to elderly care facilities.
Families living alone and two-generation families, compared to those who live in elderly care facilities, choose
to continue living in their current rural houses (OR = 6.23 and 5.60, p < 0.01) and children’s houses in villages
(OR = 1.02, p < 0.01 and OR = 1.48, p < 0.05). By contrast, two-generation families are less likely to choose to live
in ancestral houses (OR = 0.26, p < 0.05) or children’s houses in cities (OR = 0.04, p < 0.01). Households close to
county centres are unwilling choose to live in their current rural houses (OR = 0.39, p < 0.01) and prefer to live in
their children’s houses in cities (OR = 13.60, p < 0.01) as their future residential sites. Farmers with more houses
are willing to live in their urban children’s houses (OR = 2.11, p < 0.05) in the future. By contrast, farmers owning
more farmland are less willing to stay in their ancestral houses (OR = 0.85, p < 0.01) (Table6).
Discussion
Farmers’ attitudes regarding their future residential preference play a crucial role in rural planning and the
eective management of hollow villages38. In China, residential locations hold particular signicance for farmers
due to their connection with land, traditional culture, and rural well-being39. Attitudes toward future residential
preference among farmers are complex and divergent across dierent stages of the family life cycle, serving as
signicant barriers to the sustainable development of rural areas. In this study, we selected villages with similar
family structures but varying geographical locations, income sources, and livelihoods, distinct from the main
grain-producing zones of China. We found that the majority of households express a willingness to choose
their current rural house as their future residence. is choice is signicantly inuenced by the characteris-
tics of household heads, family income and livelihood, aliated houses and lands, and the life-cycle stages of
households.
e preference and choice of farmers’ future residence can be inuenced by the family life cycle. Based on
our research ndings, it is evident that the family life cycle plays a signicant role in determining both the future
ancestral house and the current house choices. Our research indicates that households in the burden stage
are more likely to make these choices, and there is a clear correlation between the family life cycle and socio-
economic phenomena such as non-agricultural labor migration40, abandonment of rural homesteads, and family
migration. is nding is in line with the research conducted by Xia etal.41.
Regardless of the stage in the family life cycle, our study nds that farmers are generally more inclined to
choose to stay in existing homes than in elderly care facilities. Except for households in the maintenance stage
and empty nest stage, who prefer living in their children’s homes within the village, households in all ve stages
primarily choose to continue residing in their current rural houses in the future. e family life cycle reects the
diverse ages and compositions within a family, and how it evolves over time. In smaller households, middle-aged
Content courtesy of Springer Nature, terms of use apply. Rights reserved
7
Vol.:(0123456789)
Scientic Reports | (2024) 14:13766 | https://doi.org/10.1038/s41598-024-64737-7
www.nature.com/scientificreports/
Table 4. Family life cycle and vacant housing ratio. Note: Vacant house excludes housing that is occupied more than two months per year.
Village
Initial stage Burden stage Stable stage Maintenance stage Empty nest stage
Number of
household Proportion
(%)
Vacant
house
(%) Number of
household Proportions
(%)
Vacant
house
(%) Number of
household Proportions
(%)
Vacant
house
(%) Number of
household Proportions
(%)
Vacant
house
(%) Number of
household Proportions
(%)
Vacant
house
(%)
Beishizhuang 30 28.04 16.67 28 26.17 10.71 13 12.15 7.69 11 10.28 0 25 23.36 4
Lihusi 66 25.68 1.51 78 30.35 5.13 45 17.51 15.56 30 11.67 16.67 38 14.79 10.53
Qianliucun 69 23.79 4.35 83 28.62 7.23 61 21.03 9.84 41 14.14 4.88 36 12.41 5.56
Zhangzhaung 38 30.89 5.23 36 29.26 2.78 22 17.89 13.64 9 7.32 33.33 18 14.63 11.11
Tot al 203 26.13 5.42 225 28.96 6.22 141 18.15 12.06 91 11.71 10.99 117 15.06 6.84
Content courtesy of Springer Nature, terms of use apply. Rights reserved
8
Vol:.(1234567890)
Scientic Reports | (2024) 14:13766 | https://doi.org/10.1038/s41598-024-64737-7
www.nature.com/scientificreports/
individuals oen experience the pressure of caring for elderly family members. Consequently, they tend to engage
in livelihood activities outside their hometowns during the maintenance stage. As the family stages evolve, hous-
ing choices also change29.
China has a rural population of approximately 500 million individuals42,43. Zhong44 emphasised the impor-
tance of gradually reducing the disparities between urban and rural development and enhancing the living
standards of the rural population. In urbanization, the sustainable development of rural areas must be prioritised.
Traditional village culture and customs have the potential to inuence the future residential preferences of
farming households45. Traditional rural areas are characterized by subsistence agricultural production, with one’s
hometown representing traditional Chinese agricultural civilization and serving as a signicant psychological and
behavioral characteristic among traditional farmers46. Chinese households adhere to traditional living patterns,
Figure2. Life cycle stage distributions of families in dierent types of villages.
Ancestral house
Current rural house
Children's house in the village
Children's house in the city
Elderly care facility
Figure3. Proportion of future residential preference.
Content courtesy of Springer Nature, terms of use apply. Rights reserved
9
Vol.:(0123456789)
Scientic Reports | (2024) 14:13766 | https://doi.org/10.1038/s41598-024-64737-7
www.nature.com/scientificreports/
8.13%
9.13%
13.61%
16.67%
12.50%
71.29%
70.32%
40.14%
25.56%
23.21%
3.83%
5.48%
7.48%
30.00%
33.93%
7.18%
5.94%
19.05%
5.56%
13.39%
9.57%
9.13%
19.73%
22.22%
16.96%
0% 20%40% 60% 80
%1
00
%
Initial stage
Burden stage
Stable stage
Maintenance stage
Empty nest stage
Residential preference
Family life cycle
Ancestral houseCurrent rural house
Children's house in the village Children's house in the city
Elderly care facility
Figure4. Proportions of future residential preference for dierent types of households.
Figure5. Chord diagram of future residential preference for dierent types of family. Notes: e ow from FLC
to A represents the choice of residential location during dierent stages of the lifecycle, and the area represents
the proportion of each choice. A1: Ancestral house, A2: Current rural house, A3: Children’s house in the village,
A4: Children’s house in the city, A5: Elderly care facility. FLC1: Initial stage, FLC2: Burden stage, FLC3: Stable
stage, FLC4: Support stage, FLC5: Empty nest stage. Distance from village to county center: d > c > b > a.
Content courtesy of Springer Nature, terms of use apply. Rights reserved
10
Vol:.(1234567890)
Scientic Reports | (2024) 14:13766 | https://doi.org/10.1038/s41598-024-64737-7
www.nature.com/scientificreports/
leisure activities, social interactions, and housing styles. Multigenerational cohabitation is prevalent among the
majority of households47. e strong emotional attachment of Chinese individuals to their homes and hometowns
inuences their decision to return to their hometowns in old age. At present, farmers’ way of life has an impact
on their future choices of residence48. Research by Dueppen highlights that in ancient West Africa, farm dwell-
ings served various purposes, such as farming, cultivation, and habitation, with multigenerational cohabitation
being the dominant settlement pattern of that era49. Long-term living arrangements, such as living alone or with
two or three generations, signicantly aect farmers’ future housing choices50. Elderly individuals who live alone
are inclined to either stay in their current rural house or relocate to their children’s homes in rural areas. eir
decision is primarily inuenced by their familiarity with the surroundings and the absence of consistent com-
pany from their children over extended periods51. erefore, an empirical examination of the future residential
preferences of rural households in traditional Chinese rural areas, from the perspective of the family life cycle,
can contribute to the enhancement of rural development and serve as a reference for future rural planning.
e role of the household head in making nal decisions regarding family matters, including housing choices
and land management, is of crucial importance. Various factors related to the household head, such as age, health,
and education, can have an impact on their future residential preferences. Our study indicates that older house-
hold heads oen face diculties in adapting to urban life and generally prefer remaining in their rural homes in
the future. is nding is consistent with a report from New Zealand which suggests that older individuals tend to
prefer familiar areas52. On the other hand, young people in developing countries tend to migrate frequently from
rural to urban areas due to the need for urban employment to sustain their livelihoods53. Household heads in
poor health are likely to rely on the companionship and care of their children, leading them to choose to live with
their children in the future. is is supported by research conducted by Ranga54. In many developing countries,
the aged agricultural workforce and the migration of young people away from agriculture are common trends55.
e nancial situation and livelihood of a family are crucial factors that signicantly inuence the quality of
family life and future residential preferences. Family income is also a determining factor in rural development56,57.
Households with lower incomes are less likely to aord homes in urban areas and are generally markedly inclined
to remain in rural settings. Conversely, households with higher incomes have the means and the desire for
improved residential facilities and medical services, making them more likely to opt for elderly care facilities
in the future. e livelihoods of the sampled households include various activities such as agriculture, labor,
handicras, and small businesses, with agriculture oen serving as the primary source of livelihood. erefore,
most households are disinclined to move to urban areas. is aligns with traditional rural settings in countries
like India, where the primary sources of income are land and agriculture and higher income levels lead to bet-
ter housing conditions58. Increased agricultural productivity, as demonstrated by Adetoro59, can raise income,
enhance livelihoods, improve household consumption levels, and inuence housing choices among households.
Aliated properties and lands hold signicant importance for a household’s sustenance and play a pivotal
role in determining whether households choose to remain in the village in the long term. Some households
not only own homes within the village, but also invest in commercial properties in the county or city. ese
additional properties are oen used for purposes such as marriages or providing educational opportunities for
their children60. Research has shown that households with multiple properties are more likely to pursue urban
residences in the future. Furthermore, land ownership has a signicant impact on rural economic development61.
In regions like Amhara, land ownership is considered a criterion for socioeconomic development, and possessing
Table 5. Measures and description of future residential preference and its inuencing factors.
Variables name Code Items Mean SD
Dependent variable
Future residential preference FRP Ancestral house = 1, current rural house = 2, children’s house in the village = 3, children’s
house in the city = 4, elderly care facility = 5 2.60 1.24
Independent variables
Family life cycle FLC Initial households = 1, burden stage = 2, stabilized households = 3, maintenance-stage house-
holds = 4, empty-nesting households = 5 – –
Personal characteristic of household head
Household head Age HHA Years 51.44 13.51
Health HEAL Very poor or po or = 1, fair = 2, good = 3, very good = 4 2.30 0.96
Education EDU Year s 7.68 3.55
Family characteristics
Household annual income HAI Unit: 1000 USD 11.08 20.96
Degree of household economic growth (latest 5 years) DEG Rapid or slow decrease = 1, constant = 2, slow growth = 3, rapid growth – –
Living pattern LP Solitary = 1, couples living together = 2, two generations living together = 3, three generations
live together = 4 – –
Number of children NC – 2.15 0.79
Endowment of resources
Village location VL Distance to county center: 1–10 km = 1; 11–20 km = 2; 21 km -30 km = 3; 30km-40km = 4 2.55 0.92
Number of homesteads owned NH – 1.37 0.92
Acres of land owned AL – 5.92 9.18
Content courtesy of Springer Nature, terms of use apply. Rights reserved
11
Vol.:(0123456789)
Scientic Reports | (2024) 14:13766 | https://doi.org/10.1038/s41598-024-64737-7
www.nature.com/scientificreports/
more land gives households greater exibility in terms of housing choices. Our research ndings align with this
perspective, indicating that farmers with larger land holdings are less inclined to choose ancestral houses as
their future residences. A similar trend has been observed in Kenya62 and Vietnam63, where traditional house-
holds heavily reliant on agriculture base their future housing decisions on the extent of their land ownership.
Balezentis64 has highlighted that the closer a village is to a city, the lower the participation of young individuals
in agriculture. is emphasizes the importance of convenient transportation and diverse agricultural opportu-
nities in attracting young migrant workers to return to their villages in old age. e housing environment plays
a crucial role in the decision-making process of migrant workers looking to return52. Consequently, our study
underscores the necessity of gradually improving the management of rural homesteads and implementing better
land use planning.
Table 6. Inuence of family life cycle on the willingness of residents to locate their dwellings. Note: e
elderly care facility is the reference item of the model. Reference means that other variables in this category
refer to this variable. OR: Odd Ratio. * Signicant at p < 0.05. ** Signicant at p < 0.01. HHA, Household head
Age; HEAL, Health; EDU, Education; HAI, Household annual income; DEG, Degree of household economic
growth (latest 5years); LP, Living pattern; NC, Number of children; VL, Village location; NH, Number of
homesteads owned; AL, Acres of land owned.
Independent
variable
Ancestral house Current rural house Children’s house in the village Children’s house in the city Collinearity test
B Signicance OR B Signicance OR B Signicance OR B Signicance OR Tolerance VIF
Initial stage 0.30 0.74 1.35 4.42** 0.00 83.34 1.02 0.26 2.76 −1.37 0.23 0.25
0.71 1.41
Burden stage 0.32 0.68 1.38 3.79** 0.00 44.40 0.72 0.38 2.06 −1.01 0.29 0.36
Stable stage −0.48 0.47 0.62 1.66** 0.01 5.23 0.70 0.33 2.02 0.19 0.80 1.21
Maintenance
stage −0.38 0.62 0.69 2.22** 0.00 9.21 2.88** 0.00 17.80 −1.57 0.11 0.21
Empty-nest
stage Reference
HHA 0.02 0.49 1.02 0.08** 0.00 1.08 0.10** 0.00 1.10 −0.06 0.11 0.94 0.57 1.76
HEAL (very
poor and poor) −0.17 0.86 0.84 0.34 0.64 1.40 -0.89 0.35 0.41 −1.64 0.13 0.19
0.44 2.27
HEAL (general) 0.31 0.68 1.36 −0.07 0.90 0.93 −1.93* 0.03 0.15 −1.54 0.08 0.22
HEAL (good) 0.22 0.73 1.24 −0.24 0.63 0.79 −1.19 0.10 0.31 −1.67* 0.03 0.19
HEAL (very
good) Reference
EDU 0.01 0.93 1.01 −0.06 0.24 0.94 −0.09 0.22 0.92 0.01 0.90 1.01 0.57 1.75
HAI −0.20 0.15 0.98 −0.01 0.41 0.99 −0.01 0.33 0.99 −0.11* 0.01 0.90 0.87 1.15
DEG (rapid or
slow decrease) −0.41 0.64 0.66 0.36 0.25 1.43 1.94* 0.04 6.96 −0.43 0.69 0.65
0.57 1.76DEG (constant) −0.29 0.63 0.74 0.03 0.95 1.03 1.35 0.08 3.87 −1.20 0.15 0.30
DEG (slow
growth) 0.01 0.98 1.01 0.33 0.48 1.39 1.09 0.12 2.96 −0.84 0.23 0.43
DEG (rapid
growth) Reference
LP (solitary) −0.75 0.16 0.47 1.83** 0.00 6.23 17.69** 0.00 1.02 −5.16 0.12 1.33
0.90 1.11
LP (two-
generation
cohabiting) −1.35** 0.01 0.26 1.72** 0.00 5.60 10.26* 0.01 1.48 −3.25** 0.00 0.04
LP (three-
generation
cohabiting) Reference
NC −0.01 0.95 0.99 −0.04 0.82 0.96 0.45 0.54 1.16 0.04 0.88 1.04 0.96 1.05
VL (1 -10 km) 1.33 0.17 3.79 −0.94** 0.00 0.39 −0.13 0.86 0.88 1.06 0.16 2.90
0.85 1.18
VL (11–20 km) 1.99* 0.03 7.31 0.61 0.20 1.83 0.09 0.89 1.09 2.61** 0.00 13.60
VL (20km-
30km) 3.70** 0.00 40.55 −0.18 0.51 0.83 0.25 0.70 1.28 0.11 0.84 1.12
VL (30km-
40km ) Reference
NH 0.09 0.73 1.10 0.04 0.89 1.04 −0.06 0.87 0.94 0.75* 0.04 2.11 0.95 1.06
AL −0.16** 0.00 0.85 −0.01 0.96 0.99 −0.07 0.00 0.93 −0.03 0.48 0.97 0.87 1.15
Nagelkerke
Pseudo
R-squared 0.76
F 9.57
Sig 0.00
Content courtesy of Springer Nature, terms of use apply. Rights reserved
12
Vol:.(1234567890)
Scientic Reports | (2024) 14:13766 | https://doi.org/10.1038/s41598-024-64737-7
www.nature.com/scientificreports/
Furthermore, our study raises new questions regarding the aging population in rural areas within the context
of rapid urbanization. In China, the migration of a signicant number of young rural laborers to urban areas has
resulted in reduced agricultural productivity in villages. is, in turn, has led to an increase in the rural elderly
population. e implications of this phenomenon extend not only to China but also to other countries with
predominantly smallholder agricultural systems65. Afghanistan, for example, where over 54.5% of the population
lives in poverty and agriculture is the primary livelihood in rural areas, relies heavily on arable land and cultiva-
tion for the survival of its farmers66. Kenya62 and Vietnam63 face a similar situation, with traditional households
heavily dependent on agriculture. e extent of land ownership signicantly inuences their future housing
choices. erefore, the introduction of new models of agricultural production becomes crucial in order to incen-
tivize young laborers to remain in rural areas. Simultaneously, improving rural infrastructure and enhancing
household satisfaction are necessary measures to mitigate the phenomenon of village hollowing out65,67.
As farmers age and young individuals with higher levels of education show reluctance to engage in agricultural
activities, there is a growing inclination among young people to live in urban areas in the future68. Our study also
reveals that healthier household heads exhibit reduced dependence on their children, making them less likely to
choose to live with their children in the future and instead opt for elderly care facilities. erefore, focusing on
the health of the elderly residing in rural areas and enhancing the provision of medical and healthcare services
are of utmost importance. ough education itself may not directly determine future residential preferences, the
low education levels among elderly individuals in rural areas are cause for concern. Eorts should be made to
improve the education level of farmers in the future. is can be achieved through the establishment of farmer-
focused schools, increased investments in rural educational resources, and the development of enterprises to
provide additional income opportunities for rural residents. ese strategies increase the likelihood that farmers
will choose to stay in the countryside and minimize the abandonment of unused homesteads.
Conclusion
is study examines farmers’ future residential preferences and the aecting factors from the family life cycle
perspective in rural China. Increased income, access to education for children, healthcare availability, and
transportation options are the primary drivers behind their decision to leave their villages. Meanwhile, rapid
urbanization has resulted in a rise in empty nesters and unused properties in rural areas, exacerbating the issue
of rural depopulation. Our ndings indicate that the majority of households choose to stay in their current rural
residences in the future, while an increasing number of younger individuals are relocating to urban centers, con-
tributing to a decline in rural productivity. e age and health status of the household head, household income
and sources of livelihood, property ownership, and current stage of residence are potential factors that inuence
their future living preferences. Based on these ndings, interventions aimed at promoting the ecient utilization
of unused rural properties should be contemplated: (1) Improving rural medical services and infrastructure is
essential to address the healthcare needs of the elderly population in rural areas. (2) Establishing farmers’ schools
is crucial for enhancing the education levels of farmers, particularly elderly individuals, to help them adapt to
rural development. (3) Enhancing employment opportunities and security for rural–urban migrants can attract
laborers back to their villages, mitigating the issue of rural depopulation.
Data availability
e data presented in this study are available on request from the corresponding author.
Received: 7 November 2023; Accepted: 12 June 2024
Table 7. Likelihood ratio test. Note: Square statistics is the dierence between the −2 log-likelihood of the
nal model and the simplied model. e simplied model is formed by omitting an eect in the nal model.
e null hypothesis is that all the parameters of this eect are 0.
Eect e model tting conditions simplify the-2 log-likelihood
of the model
Likelihood ratio test
Chi-square Deg rees of Freedom Signicance
Education 1121.947 2.568 4 0.63
Acres of land owned 1140.287 20.909 4 0
Number of children 1120.375 0.997 4 0.91
Number of homesteads owned 1124.249 4.87 4 0.3
Household annual income 1131.55 12.172 4 0.02
Household head Age 1142.885 23.506 4 0
Family life cycle 1290.708 171.329 16 0
Health 1137.433 18.054 12 0.114
Living pattern 1600.467 481.088 12 0
Degree of economic growth 1130.428 11.05 12 0.525
Village location 1242.938 123.559 12 0
Content courtesy of Springer Nature, terms of use apply. Rights reserved
13
Vol.:(0123456789)
Scientic Reports | (2024) 14:13766 | https://doi.org/10.1038/s41598-024-64737-7
www.nature.com/scientificreports/
References
1. Amponsah, O. et al. Global urban sprawl containment strategies and their implications for rapidly urbanising cities in Ghana.
Land Use Policy 114, 105979. https:// doi. org/ 10. 1016/j. landu sepol. 2022. 105979 (2022).
2. Koopmans, M. E., Rogge, E., Mettepenningen, E., Knickel, K. & Sūmane, S. e role of multi-actor governance in aligning farm
modernization and sustainable rural development. J. Rural Stud. https:// doi. org/ 10. 1016/j. jrurs tud. 2017. 03. 012 (2017).
3. Randolph, G. F. & Storper, M. Is urbanisation in the Global South fundamentally dierent? Comparative global urban analysis for
the 21st century. Urban Stud. 60, 3–25. https:// doi. org/ 10. 1177/ 00420 98021 10679 26 (2023).
4. Udoh, U. & Uyanga, J. Housing conditions and health in rural Nigeria: A study of Akwa Ibom State. In Research on Humanities
Social Sciences (2013). http:// www. iiste. org/ confe rence/.
5. Dwomoh, D. et al. Modeling inequality in access to agricultural productive resources and socioeconomic determinants of household
food security in Ghana: A cross-sectional study. Agric. Food Econ. 11, 24. https:// doi. org/ 10. 1186/ s40100- 023- 00267-6 (2023).
6. Omotoso, A. B., Daud, S. A., Okojie, L. & Omotayo, A. O. Rural infrastructure and production eciency of food crop farmers:
Implication for rural development in Nigeria, African. J. Sci. Technol. Innov. Dev. 14, 197–203. https:// doi. org/ 10. 1080/ 20421 338.
2020. 18214 41 (2022).
7. Hirway, I. & Singh, U. B. Migration and development: Rural-to-urban temporary migration to Gujarat. In Rural Labour Mobil-
ity in Times of Structural Transformation: Dynamics Perspectives from Asian Economies 269-297 (2017). https:// doi. org/ 10. 1007/
978- 981- 10- 5628- 412.
8 . Bellampalli, P. N. & Yadava, N. Distress out-migration from rural India: Exploring livelihood realities and interventions to Mitigate.
J. Hum. Rights Soc. Work 8, 262–272. https:// doi. org/ 10. 1007/ s41134- 023- 00258-z (2023).
9. Surie, A. & Sharma, L. V. Climate change, Agrarian distress, and the role of digital labour markets: Evidence from Bengaluru,
Karnataka. Decision 46, 127–138. https:// doi. org/ 10. 1007/ s40622- 019- 00213-w (2019).
10. Mallick, B. & Vogt, J. Population displacement aer cyclone and its consequences: Empirical evidence from coastal Bangladesh.
Nat. Hazards 73, 191–212. https:// doi. org/ 10. 1007/ s11069- 013- 0803-y (2014).
11. Wang, S. et al. Urbanization can benet agricultural production with large-scale farming in China. Nat. Food 2, 183–191. https://
doi. org/ 10. 1038/ s43016- 021- 00228-6 (2021).
12. Liu, S., Xiao, W., Ye, Y., He, T. & Luo, H. Rural residential land expansion and its impacts on cultivated land in China between 1990
and 2020. Land Use Policy 132, 106816. https:// doi. org/ 10. 1016/j. landu sepol. 2023. 106816 (2023).
13. Sullivan, W. C. Perceptions of the rural-urban fringe: Citizen preferences for natural and developed settings. Landsc. Urban Plan.
29, 85–101. https:// doi. org/ 10. 1016/ 0169- 2046(94) 90020-5 (1994).
14. D edrick, M. et al. Inuential landscapes: Temporal trends in the agricultural use of rejolladas at Tahcabo, Yucatán, Mexico. J.
Anthropol. Archaeol. 59, 101175. https:// doi. org/ 10. 1016/j. jaa. 2020. 101175 (2020).
15. Essaghouri, L., Mao, R. & Li, X. Environmental benets of using hempcrete walls in residential construction: An LCA-based
comparative case study in Morocco. Environ. Impact Assess. Rev. 100, 107085. https:// doi. org/ 10. 1016/j. eiar. 2023. 107085 (2023).
16. Daniel, D., Djono, T. P. A. & Iswarani, W. P. Factors related to the functionality of community-based rural water supply and sanita-
tion program in Indonesia. Geogr. Sustain. 4, 29–38. https:// doi. org/ 10. 1016/j. geosus. 2022. 12. 002 (2023).
17. Charsley, K. & Wray, H. Kept apart: Routine family separation in the UK family immigration system as times of crises. Migrat.
Stud. https:// doi. org/ 10. 1093/ migra tion/ mnad0 08 (2023).
18. Spaas, C. et al. Mental health of refugee and non-refugee migrant young people in European secondary education: e role of
family separation, daily material stress and perceived discrimination in resettlement. J. Youth Adolesc. 2022, 1–23. https:// doi. org/
10. 1007/ s10964- 021- 01515-y (2022).
19. Wilson, G. A., Hu, Z. & Rahman, S. Community resilience in rural China: e case of Hu Village, Sichuan Province. J. Rural Stud.
60, 130–140. https:// doi. org/ 10. 1016/j. jrurs tud. 2018. 03. 016 (2018).
20. Wang, X., Wang, X., Wu, J. & Zhao, G. Social network analysis of actors in rural development: A case study of yanhe village, Hubei
Province, China. Growth Change 48, 869–882. https:// doi. org/ 10. 1111/ grow. 12195 (2017).
21. Rowntree, B. S. Poverty and progress. A second social survey of York. In Poverty Progress. A Second Social Survey of York (1941).
https:// doi. org/ 10. 2307/ 22263 73.
22. Glick, P. C. e family cycle. Am. Sociol. Rev. 12, 164–174. https:// doi. org/ 10. 2307/ 20869 82 (1947).
23. Rowntree, B. S. Poverty: A Study of Town Life (Macmillan, 1902). https:// doi. org/ 10. 56687/ 97814 47342 175- 014.
24. Dustmann, C. & Görlach, J.-S. e economics of temporary migrations. J. Econ. Literat. 54, 98–136. https:// doi. org/ 10. 2139/ ssrn.
25607 28 (2016).
25. Morrow-Jones, H. A. e housing life-cycle and the transition from renting to owning a home in the United States: A multistate
analysis. Env. Plan. A 20, 1165–1184. https:// doi. org/ 10. 1068/ a2011 65 (1988).
26. Keating, N. A research framework for the United Nations Decade of Healthy Ageing (2021–2030). Eur. J. Ageing 19, 775–787.
https:// doi. org/ 10. 1007/ s10433- 021- 00679-7 (2022).
27. Luo, S., Sun, Y. & Zhou, R. Can ntech innovation promote household consumption? Evidence from China family panel studies.
Int. Rev. Financ. Anal. 82, 102137 (2022).
28. Gao, P., Xie, Y., Song, C., Cheng, C. & Ye, S. Exploring detailed urban-rural development under intersecting population growth
and food production scenarios: Trajectories for China’s most populous agricultural province to 2030. J. Geogr. Sci. 33, 222–244.
https:// doi. org/ 10. 1007/ s11442- 023- 2080-3 (2023).
29. Zhang, R., Jiang, G. & Zhang, Q. Does urbanization always lead to rural hollowing? Assessing the spatio-temporal variations in
this relationship at the county level in China 2000–2015. J. Clean. Prod. 220, 9–22. https:// doi. org/ 10. 1016/j. jclep ro. 2019. 02. 148
(2019).
30. Li, X., Wang, Y., Wu, K. & Feng, Z. Analysis and prediction of carbon balance in production-living-ecological space of Henan
Province, China. Environ. Sci. Pollut. Res. 2023, 1–16. https:// doi. org/ 10. 21203/ rs.3. rs- 19777 08/ v1 (2023).
31. Zhang, Y., Halder, P., Zhang, X. & Qu, M. Analyzing the deviation between farmers’ Land transfer intention and behavior in China’s
impoverished mountainous Area: A Logistic-ISM model approach. Land Use Policy 94, 104534. https:// doi. org/ 10. 1016/j. landu
sepol. 2020. 104534 (2020).
32. Zeng, X., Guo, S., Deng, X., Zhou, W. & Xu, D. Livelihood risk and adaptation strategies of farmers in earthquake hazard threatened
areas: Evidence from sichuan province, China. Int. J. Disaster Risk Reduct. 53, 101971. https:// do i. org/ 10. 1016/j. ijdrr. 2020. 101971
(2021).
33. Wang, W., Zhao, X., Li, H. & Zhang, Q. Will social capital aect farmers’ choices of climate change adaptation strategies? Evidences
from rural households in the Qinghai-Tibetan Plateau, China. J. Rural Stud. 83, 127–137. https:// doi. org/ 10. 1016/j. jrurs tud. 2021.
02. 006 (2021).
34. Lawson, R. Patterns of tourist expenditure and types of vacation across the family life cycle. J. Travel Res. 29, 12–18. https:// doi.
org/ 10. 4324/ 97802 03047 613- 30 (1991).
35. Chen, L., Du, H., Hui, E.C.-M., Tan, J. & Zhou, Y. Why do skilled migrants’ housing tenure outcomes and tenure aspirations vary
among dierent family lifecycle stages?. Habitat Int. 123, 102553. https:// doi. org/ 10. 1016/j. habit atint. 2022. 102553 (2022).
36. Yan, Y. Private Life Under Socialism: Love, Intimacy, and Family Change In A Chinese Village, 1949–1999 (Stanford University Press,
2003). https:// doi. org/ 10. 1515/ 97808 04764 117.
Content courtesy of Springer Nature, terms of use apply. Rights reserved
14
Vol:.(1234567890)
Scientic Reports | (2024) 14:13766 | https://doi.org/10.1038/s41598-024-64737-7
www.nature.com/scientificreports/
37. Luo, D. et al. Chinese trends in adolescent marriage and fertility between 1990 and 2015: A systematic synthesis of national and
subnational population data. Lancet Glob. Health 8, e954–e964. https:// doi. org/ 10. 1016/ s2214- 109x(20) 30130-3 (2020).
38. Siu, K. Y. e end of the village: Planning the urbanization of rural China, by Nick R Smith. J. Urban Aairs 45, 290–292. https://
doi. org/ 10. 1080/ 07352 166. 2022. 20880 20 (2022).
39. Luo, X. et al. Revealing the formation mechanism of rural housing hollowing via considering the nonlinear eects of spatial factors
and planning variables. Appl. Geogr. https:// doi. org/ 10. 1016/j. apgeog. 2023. 102957 (2023).
40. Ataei, P., Mottaghi Dastenaei, A., Karimi, H., Izadi, N. & Menatizadeh, M. Strategic sustainability practices in intercropping-based
family farming systems: Study on rural communities of Iran. Sci. Rep. 13, 18163. https:// doi. org/ 10. 1038/ s41598- 023- 45454-z
(2023).
41. Xia, T., Carayannis, E. G., Sindakis, S., Showkat, S. & Kanellos, N. Technology transfer for sustainable rural development: Evidence
from homestead withdrawal with compensation in Chengdu-Chongqing. J. Technol. Transfer https:// doi. org/ 10. 1007/ s10961- 023-
10019-9 (2023).
42. Qi, W., Deng, Y. & Fu, B. Rural attraction: e spatial pattern and driving factors of China’s rural in-migration. J. Rural Stud. 93,
461–470. https:// doi. org/ 10. 1016/j. jrurs tud. 2019. 03. 008 (2022).
43. Zhao, J., Xiao, Y., Sun, S., Sang, W. & Axmacher, J. C. Does China’s increasing coupling of ‘urban population’ and ‘urban area’ growth
indicators reect a growing social and economic sustainability?. J. Environ. Manage. 301, 113932. https:// doi. org/ 10. 1016/j. jenvm
an. 2021. 113932 (2022).
44. Zhong, S., Wang, M., Zhu, Y., Chen, Z. & Huang, X. Urban expansion and the urban–rural income gap: Empirical evidence from
China. Cities 129, 103831. https:// doi. org/ 10. 1016/j. cities. 2022. 103831 (2022).
45. Zhang, Q., Kim, E., Yang, C. & Cao, F. Rural revitalization: Sustainable strategy for the development of cultural landscape of
traditional villages through optimized IPA approach. J. Cult. Heritage Managem. Sustain. Dev. 13, 66–86. https:// doi. org/ 10. 1108/
JCHMSD- 09- 2020- 0130 (2023).
46. Ye, C., Pan, J. W. & Liu, Z. M. e historical logics and geographical patterns of rural-urban governance in China. J. Geogr. Sci. 32,
1225–1240. https:// doi. org/ 10. 1007/ s11442- 022- 1994-5 (2022).
47. Li, C. K., Jiang, S. & Zhang, X. W. Intergenerational relationship, family social support, and depression among Chinese elderly: A
structural equation modeling analysis. J. Aect. Disord. 248, 73–80. https:// doi. org/ 10. 1016/j. jad. 2019. 01. 032 (2019).
48. Ofuafor, M. In African Development and Global Engagements (eds. Adebusuyi, I. A.) 313–332 (Springer International Publishing,
2023). https:// doi. org/ 10. 1007/ 978-3- 031- 21283-3_ 15.
49. Dueppen, S. A. & Gallagher, D. Networked farmers, ancestral rituals, regional marketplaces, and salt: New insights into the
complexity of rst millennium BC/AD farming societies in West Africa. Afr. Archaeol. Rev. 40, 21–52. https:// doi. org/ 10. 1007/
s10437- 022- 09509-2 (2023).
50. Adianto, J., Gabe, R. T. & Farraz, M. A. e inuence of family relations on the housing preferences of Millennials in Depok,
Indonesia. J. Urban. Int. Res. Placemaking Urban Sustain.y 16, 84–100. https:// doi. org/ 10. 1080/ 17549 175. 2021. 19442 82 (2023).
51. Zeng, Y., Lin, C. & Fang, Y. Factors inuencing the demands for home and community-based care services among older adults
living alone in China. J. Aging Soc. Policy 2023, 1–17. https:// doi. org/ 10. 1080/ 08959 420. 2023. 22262 97 (2023).
52. Napier, S., Neville, S., Adams, J. & Taylor, L. Age-friendly attributes of a rural town in Aotearoa New Zealand. J. Rural Stud. 2023,
100. https:// doi. org/ 10. 1016/j. jrurs tud. 2023. 103033 (2023).
53. Selod, H. & Shilpi, F. Rural-urban migration in developing countries: Lessons from the literature. Reg. Sci. Urban Econ. 91, 103713.
https:// doi. org/ 10. 1016/j. regsc iurbe co. 2021. 103713 (2021).
54. Ranga, D. Determinants of the return migration of household heads from South Eastern Zimbabwe to South Africa During Pro-
longed Crisis, 2000–16. J. Soc. Dev. Sci. 9, 26–35. https:// doi. org/ 10. 22610/ jsds. v9i4(S). 2688 (2018).
55. Varadan, R. J., Mamidanna, S., Kumar, S., Ahmed, S. K. Z. & Jaisankar, G. Technology, infrastructure and enterprise trade-o:
Strengthening smallholder farming systems in Tamil Nadu State of India for sustainable income and food security. Outlook Agric.
51, 197–212. https:// doi. org/ 10. 1177/ 00307 27022 10773 80 (2022).
56. Lu, H., Zhao, P., Hu, H., Yan, J. & Chen, X. Exploring the heterogeneous impact of road infrastructure on rural residents’ income:
Evidence from nationwide panel data in China. Transport Policy 134, 155–166. https:// doi. org/ 10. 1016/j. tranp ol. 2023. 02. 019 (2023).
57. Ray, B. & Mukherjee, P. Forest income and rural livelihoods in West Bengal, India. Stud. Microecon. 11, 10–35. h ttps:// doi. org/ 10.
1177/ 23210 22221 10243 89 (2021).
58. Das, S. e impact of diabetes on sarcopenia in community-dwelling older adults in India: Key ndings from the longitudinal
ageing study in India (LASI). Diabetes Epidemiol. Manage. https:// doi. org/ 10. 1016/j. deman. 2023. 100158 (2023).
59. Adetoso-Adebiyi-Adetoro, M. S. C. N., Gideon, D.-A., Temitope, O. O. & Abiodun, A. O. Impact of irrigation on welfare and
vulnerability to poverty in South African farming households. Sci. Afr. https:// doi. org/ 10. 1016/j. sciaf. 2022. e01177 (2022).
60. Gao, J., Song, G. & Liu, S. Factors inuencing farmers’ willingness and behavior choices to withdraw from rural homesteads in
China. Growth Change 53, 112–131. https:// doi. org/ 10. 1111/ grow. 12574 (2022).
61. Getie, A. M., Birhanu, T. A. & Dadi, T. T. Rural cadastral implementation and its eect on women’s landholding use rights in
Amhara region, Ethiopia. Land Use Policy 127, 106556. https:// doi. org/ 10. 1016/j. landu sepol. 2023. 106556 (2023).
62. Gewa, C. A., Stabile, B., omas, P., Onyango, A. C. & Angano, F. O. Agricultural production, traditional foods and household
food insecurity in Rural Kenya: Practice, perception and predictors. J. Hunger Environ. Nutr. 18, 540–563. https:// doi. or g/ 10. 1080/
19320 248. 2021. 19940 83 (2023).
63. Tran, G. T. H., Nanseki, T., Chomei, Y. & Nguyen, L. T. e impact of cooperative participation on income: e case of vegetable
production in Vietnam. J. Agribusiness Dev. Emerg. Econ. 13, 106–118. https:// doi. org/ 10. 1108/ JADEE- 05- 2021- 0108 (2023).
64. Balezentis, T. et al. Young farmers’ support under the Common Agricultural Policy and sustainability of rural regions: Evidence
from Lithuania. Land Use Policy 94, 104542. https:// doi. org/ 10. 1016/j. landu sepol. 2020. 104542 (2020).
65. Ren, C. C. et al. Ageing threatens sustainability of smallholder farming in China. Nature 616, 96–103. https:// doi. org/ 10. 1038/
s41586- 023- 05738-w (2023).
66. Miani, A. M. et al. Toward sustainable rural livelihoods approach: Application of grounded theory in Ghazni province, Afghanistan.
Appl. Geogr. 154, 102915. https:// doi. org/ 10. 1016/j. apgeog. 2023. 102915 (2023).
67. Huang, Q., Song, W. & Song, C. Consolidating the layout of rural settlements using system dynamics and the multi-agent system.
J. Clean. Prod. 274, 123150. https:// doi. org/ 10. 1016/j. jclep ro. 2020. 123150 (2020).
68. Mohanty, B. & Lenka, P. K. ‘For them farming may be the last resort, but for us it is a new hope’: Ageing, youth and farming in
India. J. Agrarian Change 23, 771–791. https:// doi. org/ 10. 1111/ joac. 12538 (2023).
Acknowledgements
We acknowledge all people who contributed to the data collection and processing, as well as the constructive
and insightful comments by the editor and anonymous reviewers.
Author contributions
Conceptualization, T.Y. (Yan Tong); methodology, M.Z. (Mengke Zhang) and L.F. (Liangxin Fan); soware, M.Z.
(Mengke Zhang); validation, Y.G. (Yuhang Ge) and J.G. (Jin Guo); formal analysis, T.Y. (Yan Tong); resources,
Content courtesy of Springer Nature, terms of use apply. Rights reserved
15
Vol.:(0123456789)
Scientic Reports | (2024) 14:13766 | https://doi.org/10.1038/s41598-024-64737-7
www.nature.com/scientificreports/
M.Z. (Mengke Zhang)., and H.N. (Hanlin Nie); data curation, M.Z. (Mengke Zhang), Z.W. (Zhijun Wang); writ-
ing—original dra preparation, M.Z. (Mengke Zhang); writing—review and editing, L.F.(Liangxin Fan), and
M.Z. (Mengke Zhang), visualization, M.Z. (Mengke Zhang); supervision, T.Y. (Yan Tong), Y.G. (Yuhang Ge),
and J.G. (Jin Guo); project administration, T.Y. (Yan Tong); funding acquisition, T.Y. (Yan Tong). All authors
have read and agreed to the published version of the manuscript.
Funding
is work was supported by Natural Science Foundation of Henan Province (22300420172), Henan Polytechnic
University: Special Program for Basic Research Operating Costs (Natural Science, No. NSFRF200339), Scien-
tic Research Fund Project of Henan University of Science and Technology: Project No. B2020-16, Program
for Innovative Research Team (in Philosophy and Social Science) in University of Henan Province (Grant Nos.
2022-CXTD-02) and Henan Province philosophy and social science planning project: 2023 BSH008.
Competing interests
e authors declare no competing interests.
Additional information
Correspondence and requests for materials should be addressed to Y.T.
Reprints and permissions information is available at www.nature.com/reprints.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and
institutional aliations.
Open Access is article is licensed under a Creative Commons Attribution 4.0 International
License, which permits use, sharing, adaptation, distribution and reproduction in any medium or
format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the
Creative Commons licence, and indicate if changes were made. e images or other third party material in this
article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the
material. If material is not included in the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from
the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
© e Author(s) 2024
Content courtesy of Springer Nature, terms of use apply. Rights reserved
1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”), for small-
scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are maintained. By
accessing, sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of use (“Terms”). For these
purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal
subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription
(to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will
apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within
ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not
otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as
detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that Users may
not:
use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access
control;
use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is
otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association unless explicitly agreed to by Springer Nature in
writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal
content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue,
royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal
content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any
other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not obligated to publish any information or
content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature
may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied
with respect to the Springer nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law,
including merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed
from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not
expressly permitted by these Terms, please contact Springer Nature at
onlineservice@springernature.com
