Environmental Stress and Household Well-Being in Agriculture-Dependent Systems

A Comparative Analysis of Vulnerability Pathways in Indonesia

Authors

  • Yustitia Asri Ertaningrum Universitas Airlangga, Indonesia
  • Unggul Heriqbaldi Universitas Airlangga, Indonesia
  • Jaisy Aghniarahim Putritamara Universitas Brawijaya, Indonesia
  • Agus Nugroho Universitas Brawijaya, Indonesia

DOI:

https://doi.org/10.61255/jeemba.v4i5.1803

Keywords:

Agriculture-dependent livelihoods, Environmental stress, Subjective well-being, Multi-hazard risk, Vulnerability pathways

Abstract

Purpose – This study examines how environmental stress is associated with different psychosocial pathway configurations affecting household well-being in climate-sensitive rural systems, addressing limited attention to how stress is transmitted through resource, livelihood, health, economic, and psychological processes in agriculture-dependent households. The comparison is explicitly bounded to two context-specific sets of within-model associations and does not treat hazard regime as a statistically isolated cause of regional differences.

Design/methodology/approach – The study uses comparative survey data from 1,080 households across chronic-drought areas in East Nusa Tenggara and multi-hazard areas in Sumatera. Separate Partial Least Squares Structural Equation Modeling (PLS-SEM) models were estimated for NTT (n = 540) and Sumatera (n = 540), and theory-specified direct paths were evaluated with 5,000 bootstrap subsamples. Because the regional models contain non-equivalent constructs, indicators, paths, and Subjective Well-Being measures, the cross-context comparison is descriptive and conceptual; no formal multi-group coefficient test, measurement-equivalence claim, or cross-regional mediation test is made.

Findings/Results – In drought-prone NTT, significant direct paths form a sequential modeled chain linking perceived drought chronicity, water insecurity, food security, mental health stress, and the NTT well-being profile; the descriptive arithmetic product for the livelihood-resilience/economic-vulnerability chain is smaller within the NTT model. In Sumatera, significant direct paths form pollution-health and supply-chain-economic modeled chains whose descriptive arithmetic products are close in magnitude within that model. These values are descriptive multi-step products, not bootstrapped specific indirect effects, and they do not establish mediation, causal ordering, or a hazard-regime effect.

Originality/Value – The study contributes empirically grounded, context-sensitive archetypes that clarify conditions under which chronic attrition or cascading disruption may become more prominent in agriculture-dependent systems. It also demonstrates a transparent way to compare non-equivalent model architectures descriptively without treating their coefficients or well-being endpoints as directly interchangeable. The archetypes are presented as mechanism-oriented propositions for future longitudinal, measurement-invariant, and objectively validated research.

Abstract views: 13 , PDF downloads: 5

Downloads

Download data is not yet available.

References

Adger, W. N. (2010). Climate change, human well-being and insecurity. New Political Economy, 15(2), 275–292. https://doi.org/10.1080/13563460903290912

Anbumozhi, V., Kimura, F., & Thangavelu, S. M. (2020). Global supply chain resilience: Vulnerability and shifting risk management strategies. In V. Anbumozhi, F. Kimura, & S. M. Thangavelu (Eds.), Supply chain resilience: Reducing vulnerability to economic shocks, financial crises, and natural disasters (pp. 3–14). Springer. https://doi.org/10.1007/978-981-15-2870-5_1

Asiamah, N., Mensah, H. K., Ansah, E. W., Eku, E., Ansah, N. B., Danquah, E., Yarfi, C., Aidoo, I., Opuni, F. F., & Agyemang, S. M. (2025). Association of optimism, self-efficacy, and resilience with life engagement among middle-aged and older adults with severe climate anxiety: Sensitivity of a path model. Journal of Affective Disorders, 380, 607–619. https://doi.org/10.1016/j.jad.2025.03.180

Atkinson, C. L., & Alibašić, H. (2023). Prospects for governance and climate change resilience in peatland management in Indonesia. Sustainability, 15(3), Article 1839. https://doi.org/10.3390/su15031839

Axelrod, L. J. (1994). Balancing personal needs with environmental preservation: Identifying the values that guide decisions in ecological dilemmas. Journal of Social Issues, 50(3), 85–104. https://doi.org/10.1111/j.1540-4560.1994.tb02421.x

Bahta, Y. T., & Myeki, V. A. (2022). The impact of agricultural drought on smallholder livestock farmers: Empirical evidence insights from Northern Cape, South Africa. Agriculture, 12(4), Article 442. https://doi.org/10.3390/agriculture12040442

Beckerman, W. (2015). A poverty of reason: Sustainable development and economic growth. Independent Institute.

Berry, H. L., Waite, T. D., Dear, K. B. G., Capon, A. G., & Murray, V. (2018). The case for systems thinking about climate change and mental health. Nature Climate Change, 8, 282–290. https://doi.org/10.1038/s41558-018-0102-4

Bradley, G. L., & Reser, J. P. (2017). Adaptation processes in the context of climate change: A social and environmental psychology perspective. Journal of Bioeconomics, 19(1), 29–51. https://doi.org/10.1007/s10818-016-9231-x

Burrows, K., Denckla, C. A., Hahn, J., et al. (2024). A systematic review of the effects of chronic, slow-onset climate change on mental health. Nature Mental Health, 2, 228–243. https://doi.org/10.1038/s44220-023-00170-5

Chin, W. W., & Newsted, P. R. (1999). Structural equation modeling analysis with small samples using partial least squares. In R. H. Hoyle (Ed.), Statistical strategies for small sample research (pp. 307–341). SAGE Publications.

Cianconi, P., Betrò, S., & Janiri, L. (2020). The impact of climate change on mental health: A systematic descriptive review. Frontiers in Psychiatry, 11, Article 74. https://doi.org/10.3389/fpsyt.2020.00074

Clayton, S. (2020). Climate anxiety: Psychological responses to climate change. Journal of Anxiety Disorders, 74, Article 102263. https://doi.org/10.1016/j.janxdis.2020.102263

Cunsolo, A., & Ellis, N. R. (2018). Ecological grief as a mental health response to climate change-related loss. Nature Climate Change, 8(4), 275–281. https://doi.org/10.1038/s41558-018-0092-2

Cutter, S. L., Barnes, L., Berry, M., Burton, C., Evans, E., Tate, E., & Webb, J. (2008). A place-based model for understanding community resilience to natural disasters. Global Environmental Change, 18(4), 598–606. https://doi.org/10.1016/j.gloenvcha.2008.07.013

Dadson, S., Hall, J. W., Garrick, D., Sadoff, C., Grey, D., & Whittington, D. (2017). Water security, risk, and economic growth: Insights from a dynamical systems model. Water Resources Research, 53(8), 6425–6438. https://doi.org/10.1002/2017WR020640

Djalante, R., Garschagen, M., Thomalla, F., & Shaw, R. (2017). Introduction: Disaster risk reduction in Indonesia: Progress, challenges, and issues. In R. Djalante, M. Garschagen, F. Thomalla, & R. Shaw (Eds.), Disaster risk reduction in Indonesia: Progress, challenges, and issues (pp. 1–17). Springer. https://doi.org/10.1007/978-3-319-54466-3_1

Doherty, T. J., & Clayton, S. (2011). The psychological impacts of global climate change. American Psychologist, 66(4), 265–276. https://doi.org/10.1037/a0023141

Düvel, E., & García-Portela, L. (2024). The ethics of climate change loss and damage. WIREs Climate Change, 15(6), Article e910. https://doi.org/10.1002/wcc.910

Food and Agriculture Organization of the United Nations. (2017). The future of food and agriculture: Trends and challenges. https://www.fao.org/3/i6583e/i6583e.pdf

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104

Grosvenor, M. J., Ardiyani, V., Wooster, M. J., Gillott, S., Green, D. C., Lestari, P., & Suri, W. (2024). Catastrophic impact of extreme 2019 Indonesian peatland fires on urban air quality and health. Communications Earth & Environment, 5, Article 649. https://doi.org/10.1038/s43247-024-01813-w

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). SAGE Publications.

Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Springer. https://doi.org/10.1007/978-3-030-80519-7

Hair, J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: Updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107–123. https://doi.org/10.1504/IJMDA.2017.087624

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Planning, 46(1–2), 1–12. https://doi.org/10.1016/j.lrp.2013.01.001

Hair, J. F., Sarstedt, M., Pieper, T. M., & Ringle, C. M. (2012). The use of partial least squares structural equation modeling in strategic management research: A review of past practices and recommendations for future applications. Long Range Planning, 45(5–6), 320–340. https://doi.org/10.1016/j.lrp.2012.09.008

Hallegatte, S., Bangalore, M., Bonzanigo, L., Fay, M., Kane, T., Narloch, U., Rozenberg, J., Treguer, D., & Vogt-Schilb, A. (2016). Shock waves: Managing the impacts of climate change on poverty. World Bank. https://doi.org/10.1596/978-1-4648-0673-5

Haluza-DeLay, R. (2014). Religion and climate change: Varieties in viewpoints and practices. WIREs Climate Change, 5(2), 261–279. https://doi.org/10.1002/wcc.268

Hartono, B., Toiba, H., Putritamara, J. A., & Rahman, M. S. (2024). Do dynamic capabilities and entrepreneurial orientation promote farm resilience? Insights from Indonesian beef-cattle farmers facing a foot-and-mouth disease outbreak. Cogent Food & Agriculture, 10(1), Article 2409486. https://doi.org/10.1080/23311932.2024.2409486

Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: Updated guidelines. Industrial Management & Data Systems, 116(1), 2–20. https://doi.org/10.1108/IMDS-09-2015-0382

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8

Heyd, T. (2021). COVID-19 and climate change in the times of the Anthropocene. The Anthropocene Review, 8(1), 21–36. https://doi.org/10.1177/2053019620961799

Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118

Intergovernmental Panel on Climate Change. (2022). Climate change 2022: Mitigation of climate change: Working Group III contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. https://doi.org/10.1017/9781009157926

Kajikawa, Y. (2008). Research core and framework of sustainability science. Sustainability Science, 3(2), 215–239. https://doi.org/10.1007/s11625-008-0053-1

Khatun, M., Sarkar, S., Era, F. M., Islam, A. K. M. M., Anwar, M. P., Fahad, S., Datta, R., & Islam, A. K. M. A. (2021). Drought stress in grain legumes: Effects, tolerance mechanisms and management. Agronomy, 11(12), Article 2374. https://doi.org/10.3390/agronomy11122374

Kimutai, J. J., Lund, C., Moturi, W. N., Shewangizaw, S., Feyasa, M., & Hanlon, C. (2023). Evidence on the links between water insecurity, inadequate sanitation and mental health: A systematic review and meta-analysis. PLOS ONE, 18, e0286146. https://doi.org/10.1371/journal.pone.0286146

Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). Guilford Press.

Kornher, L., & Sakketa, T. G. (2021). Does food security matter to subjective well-being? Evidence from a cross-country panel. Journal of International Development, 33(8), 1270–1289. https://doi.org/10.1002/jid.3575

Lawrance, E. L., Thompson, R., Newberry Le Vay, J., Page, L., & Jennings, N. (2022). The impact of climate change on mental health and emotional wellbeing: A narrative review of current evidence, and its implications. International Review of Psychiatry, 34(5), 443–498. https://doi.org/10.1080/09540261.2022.2128725

Liu, W., Sun, F., Lim, W. H., Zhang, J., Wang, H., Shiogama, H., & Zhang, Y. (2018). Global drought and severe drought-affected populations in 1.5 and 2 °C warmer worlds. Earth System Dynamics, 9(1), 267–283. https://doi.org/10.5194/esd-9-267-2018

Lorem, G., Cook, S., Leon, D. A., Emaus, N., & Schirmer, H. (2020). Self-reported health as a predictor of mortality: A cohort study of its relation to other health measurements and observation time. Scientific Reports, 10(1), Article 4886. https://doi.org/10.1038/s41598-020-61603-0

Marchezini, V. (2015). The biopolitics of disaster: Power, discourses, and practices. Human Organization, 74(4), 362–371. https://doi.org/10.17730/0018-7259-74.4.362

Marchezini, V. (2019). The power of localism during the long-term disaster recovery process. Disaster Prevention and Management: An International Journal, 28(1), 143–152. https://doi.org/10.1108/DPM-05-2018-0150

Martin, S. F., Bergmann, J., Rigaud, K. K., & Yameogo, N. D. (2021). Climate change, human mobility, and development. Migration Studies, 9(1), 142–149. https://doi.org/10.1093/migration/mnaa030

McBean, G., & Rodgers, C. (2010). Climate hazards and disasters: The need for capacity building. WIREs Climate Change, 1(6), 871–884. https://doi.org/10.1002/wcc.77

Mongonia, L. (2022). Climate change and mental health: The counseling professional’s role. Journal of Counselor Leadership and Advocacy, 9(1), 57–70. https://doi.org/10.1080/2326716X.2022.2041505

Natarajan, N., Newsham, A., Rigg, J., & Suhardiman, D. (2022). A sustainable livelihoods framework for the 21st century. World Development, 155, Article 105898. https://doi.org/10.1016/j.worlddev.2022.105898

Nef, D. P., Nef, S., & Krütli, P. (2023). Putting people back at the center of livelihood vulnerability analysis. SN Social Sciences, 3(11), Article 184. https://doi.org/10.1007/s43545-023-00775-8

Nguyen, D. L., Nguyen, T. T., & Grote, U. (2023). Shocks, household consumption, and livelihood diversification: A comparative evidence from panel data in rural Thailand and Vietnam. Economic Change and Restructuring, 56(5), 3223–3255. https://doi.org/10.1007/s10644-022-09400-9

Nimo, T. K. O. A., Akoto-Baako, H., Antiri, E. O., & Ansah, E. W. (2025). Coping strategies for climate change anxiety: A perspective on building resilience through psychological capital. BMJ Mental Health, 28(1), Article e301421. https://doi.org/10.1136/bmjment-2024-301421

O’Brien, K. (2012). Global environmental change II: From adaptation to deliberate transformation. Progress in Human Geography, 36(5), 667–676. https://doi.org/10.1177/0309132511425767

Ojala, M., Cunsolo, A., Ogunbode, C. A., & Middleton, J. (2021). Anxiety, worry, and grief in a time of environmental and climate crisis: A narrative review. Annual Review of Environment and Resources, 46, 35–58. https://doi.org/10.1146/annurev-environ-012220-022716

Perrone, D., & Hornberger, G. M. (2014). Water, food, and energy security: Scrambling for resources or solutions? WIREs Water, 1(1), 49–68. https://doi.org/10.1002/wat2.1004

Pescaroli, G., & Alexander, D. (2018). Understanding compound, interconnected, interacting, and cascading risks: A holistic framework. Risk Analysis, 38(11), 2245–2257. https://doi.org/10.1111/risa.13128

Purnomo, E. P., Ramdani, R., Agustiyara, Nurmandi, A., Trisnawati, D. W., & Fathani, A. T. (2021). Bureaucratic inertia in dealing with annual forest fires in Indonesia. International Journal of Wildland Fire, 30(10), 733–744. https://doi.org/10.1071/WF20168

Purnomo, E. P., Ramdani, R., Agustiyara, Tomaro, Q. P. V., & Samidjo, G. S. (2019). Land ownership transformation before and after forest fires in Indonesian palm oil plantation areas. Journal of Land Use Science, 14(1), 37–51. https://doi.org/10.1080/1747423X.2019.1614686

Purwanti, T. S., Syafrial, S., Huang, W.-C., & Saeri, M. (2022). What drives climate change adaptation practices in smallholder farmers? Evidence from potato farmers in Indonesia. Atmosphere, 13(1), Article 113. https://doi.org/10.3390/atmos13010113

Rafa, N., Zabala, A., & Galway, L. P. (2025). Empirical research review on solastalgia: Place, people and policy pathways for addressing environmental distress. People and Nature, 7(8), 1811–1825. https://doi.org/10.1002/pan3.70090

Rahman, M. S., Huang, W.-C., Toiba, H., & Efani, A. (2022). Does adaptation to climate change promote household food security? Insights from Indonesian fishermen. International Journal of Sustainable Development & World Ecology, 29(7), 611–624. https://doi.org/10.1080/13504509.2022.2063433

Rahman, M. S., Huang, W.-C., Toiba, H., Putritamara, J. A., Nugroho, T. W., & Saeri, M. (2023). Climate change adaptation and fishers’ subjective well-being in Indonesia: Is there a link? Regional Studies in Marine Science, 63, Article 103030. https://doi.org/10.1016/j.rsma.2023.103030

Rahman, M. S., Toiba, H., & Huang, W.-C. (2021). The impact of climate change adaptation strategies on income and food security: Empirical evidence from small-scale fishers in Indonesia. Sustainability, 13(14), Article 7905. https://doi.org/10.3390/su13147905

Rasoolimanesh, S. M. (2022). Discriminant validity assessment in PLS-SEM: A comprehensive composite-based approach. Data Analysis Perspectives Journal, 3(2), 1–8.

Reid, C. E., Kubzansky, L. D., Li, J., Shmool, J. L., & Clougherty, J. E. (2018). It’s not easy assessing greenness: A comparison of NDVI datasets and neighborhood types and their associations with self-rated health in New York City. Health & Place, 54, 92–101. https://doi.org/10.1016/j.healthplace.2018.09.005

Salmoral, G., Ababio, B., & Holman, I. P. (2020). Drought impacts, coping responses and adaptation in the UK outdoor livestock sector: Insights to increase drought resilience. Land, 9(6), Article 202. https://doi.org/10.3390/land9060202

Sarstedt, M., Hair, J. F., & Ringle, C. M. (2023). PLS-SEM: Indeed a silver bullet—Retrospective observations and recent advances. Journal of Marketing Theory and Practice, 31(3), 261–275. https://doi.org/10.1080/10696679.2022.2056488

Shao, L., & Yu, G. (2023). Media coverage of climate change, eco-anxiety and pro-environmental behavior: Experimental evidence and the resilience paradox. Journal of Environmental Psychology, 91, Article 102130. https://doi.org/10.1016/j.jenvp.2023.102130

Sharma, S., Talchabhadel, R., Nepal, S., Ghimire, G. R., Rakhal, B., Panthi, J., Adhikari, B. R., Pradhanang, S. M., Maskey, S., & Kumar, S. (2023). Increasing risk of cascading hazards in the central Himalayas. Natural Hazards, 119(2), 1117–1126. https://doi.org/10.1007/s11069-022-05462-0

Shiva, V., & Bedi, G. (2002). Sustainable agriculture and food security: The impact of globalisation. SAGE Publications India.

Shmueli, G., Ray, S., Velasquez Estrada, J. M., & Chatla, S. B. (2016). The elephant in the room: Predictive performance of PLS models. Journal of Business Research, 69(10), 4552–4564. https://doi.org/10.1016/j.jbusres.2016.03.049

Siagian, T. H., Purhadi, P., Suhartono, S., & Ritonga, H. (2014). Social vulnerability to natural hazards in Indonesia: Driving factors and policy implications. Natural Hazards, 70(2), 1603–1617. https://doi.org/10.1007/s11069-013-0888-3

Smith, G. S., Anjum, E., Francis, C., Deanes, L., & Acey, C. (2022). Climate change, environmental disasters, and health inequities: The underlying role of structural inequalities. Current Environmental Health Reports, 9(1), 80–89. https://doi.org/10.1007/s40572-022-00336-w

Sovacool, B. K., Bazilian, M., Griffiths, S., Kim, J., Foley, A., & Rooney, D. (2021). Decarbonizing the food and beverages industry: A critical and systematic review of developments, sociotechnical systems and policy options. Renewable and Sustainable Energy Reviews, 143, Article 110856. https://doi.org/10.1016/j.rser.2021.110856

Syaban, A. S. N., & Appiah-Opoku, S. (2025). Perspective chapter: Indonesia’s capital city relocation as a multidimensional national conflicts resolution strategy. In S. Appiah-Opoku (Ed.), Contemporary regional planning issues. IntechOpen. https://doi.org/10.5772/intechopen.1010922

Tan, Y., Dong, Z., Guzman, S. M., Wang, X., & Yan, W. (2021). Identifying the dynamic evolution and feedback process of water resources nexus system considering socioeconomic development, ecological protection, and food security: A practical tool for sustainable water use. Hydrology and Earth System Sciences, 25(12), 6495–6522. https://doi.org/10.5194/hess-25-6495-2021

Thoma, M. V., Rohleder, N., & Rohner, S. L. (2021). Clinical ecopsychology: The mental health impacts and underlying pathways of the climate and environmental crisis. Frontiers in Psychiatry, 12, Article 675936. https://doi.org/10.3389/fpsyt.2021.675936

Thomas, K., Hardy, R. D., Lazrus, H., Mendez, M., Orlove, B., Rivera-Collazo, I., Roberts, J. T., Rockman, M., Warner, B. P., & Winthrop, R. (2019). Explaining differential vulnerability to climate change: A social science review. WIREs Climate Change, 10(2), Article e565. https://doi.org/10.1002/wcc.565

Tsai, W.-L., Silva, R. A., Nash, M. S., Cochran, F. V., Prince, S. E., Rosenbaum, D. J., D’Aloisio, A. A., Jackson, L. E., Mehaffey, M. H., Neale, A. C., Sandler, D. P., & Buckley, T. J. (2020). How do natural features in the residential environment influence women’s self-reported general health? Results from cross-sectional analyses of a U.S. national cohort. Environmental Research, 183, Article 109176. https://doi.org/10.1016/j.envres.2020.109176

Valenzuela-Mahecha, M. A., Pulido-Velazquez, M., & Macian-Sorribes, H. (2022). Hydrological drought-indexed insurance for irrigated agriculture in a highly regulated system. Agronomy, 12(9), Article 2170. https://doi.org/10.3390/agronomy12092170

Watts, N., Amann, M., Arnell, N., Ayeb-Karlsson, S., Belesova, K., Boykoff, M., Byass, P., Cai, W., Campbell-Lendrum, D., Capstick, S., Chambers, J., Dalin, C., Daly, M., Dasandi, N., Davies, M., Drummond, P., Dubrow, R., Ebi, K. L., Eckelman, M., … Montgomery, H. (2019). The 2019 report of The Lancet Countdown on health and climate change: Ensuring that the health of a child born today is not defined by a changing climate. The Lancet, 394(10211), 1836–1878. https://doi.org/10.1016/S0140-6736(19)32596-6

Werners, S. E., Wise, R. M., Butler, J. R. A., Totin, E., & Vincent, K. (2021). Adaptation pathways: A review of approaches and a learning framework. Environmental Science & Policy, 116, 266–275. https://doi.org/10.1016/j.envsci.2020.11.003

Weston, P., Hong, R., Kaboré, C., & Kull, C. A. (2015). Farmer-managed natural regeneration enhances rural livelihoods in dryland West Africa. Environmental Management, 55(6), 1402–1417. https://doi.org/10.1007/s00267-015-0469-1

Wisner, B., Blaikie, P., Cannon, T., & Davis, I. (2004). At risk: Natural hazards, people's vulnerability and disasters (2nd ed.). Routledge.

Wolf, T., Lyne, K., Sanchez Martinez, G., & Kendrovski, V. (2015). The health effects of climate change in the WHO European Region. Climate, 3(4), 901–936. https://doi.org/10.3390/cli3040901

Woodhall-Melnik, J., Dunn, J. R., Svenson, S., Hamilton-Wright, S., Patterson, C., Waterfield, D., Kirst, M., & Matheson, F. I. (2017). Finding a place to start: Exploring meanings of housing stability in Hamilton’s male Housing First participants. Housing, Theory and Society, 34(3), 359–375. https://doi.org/10.1080/14036096.2016.1266382

World Bank. (2016). World development report 2016: Digital dividends. https://doi.org/10.1596/978-1-4648-0671-1

Yana, A. A. G. A., Rusdhi, H. A., & Wibowo, M. A. (2015). Analysis of factors affecting design changes in construction project with Partial Least Square (PLS). Procedia Engineering, 125, 40–45. https://doi.org/10.1016/j.proeng.2015.11.007

Yang, M., & Zou, Y. (2025). Assessing environmental determinants of subjective well-being via machine learning approaches: A systematic review. Humanities and Social Sciences Communications, 12(1), Article 828. https://doi.org/10.1057/s41599-025-05234-8

Yuan, M., Cao, Y.-Q., Wang, H., & Xiang, H. (2022). Does social capital promote health? Social Indicators Research, 162(2), 501–524. https://doi.org/10.1007/s11205-021-02810-8

Zhang, Q., Jiang, X., Tong, D., Davis, S. J., Zhao, H., Geng, G., Feng, T., Zheng, B., Lu, Z., Streets, D. G., Ni, R., Brauer, M., van Donkelaar, A., Martin, R. V., Huo, H., Liu, Z., Pan, D., Kan, H., Yan, Y., … Guan, D. (2017). Transboundary health impacts of transported global air pollution and international trade. Nature, 543(7647), 705–709. https://doi.org/10.1038/nature21712

Zscheischler, J., Martius, O., Westra, S., Bevacqua, E., Raymond, C., Horton, R. M., van den Hurk, B., AghaKouchak, A., Jézéquel, A., Mahecha, M. D., Maraun, D., Ramos, A. M., Ridder, N. N., Thiery, W., & Vignotto, E. (2020). A typology of compound weather and climate events. Nature Reviews Earth & Environment, 1(7), 333–347. https://doi.org/10.1038/s43017-020-0060-z

Downloads

Published

2026-08-31

How to Cite

Ertaningrum, Y. A., Heriqbaldi, U., Putritamara, J. A., & Nugroho, A. (2026). Environmental Stress and Household Well-Being in Agriculture-Dependent Systems: A Comparative Analysis of Vulnerability Pathways in Indonesia. Journal of Economics, Entrepreneurship, Management Business and Accounting, 4(5), 1523–1552. https://doi.org/10.61255/jeemba.v4i5.1803