Education Level Of Household Head Research Articles

Open defecation among Kenyan households: an analysis of demographic and health survey 2022 and census report of 2019

BackgroundOpen defecation (OD) is the disposal of human excreta in the fields, bushes, water bodies and other open spaces. It poses a public health risk as it can lead to the spread of diarrhoea, cholera, soil-transmitted helminths and trachoma. Kenya aims to achieve 100% open defecation free status by 2030 in line with Sustainable development goal number 6. This study sought to determine factors influencing OD at the household level as well as quantify the number of households practicing OD in each of the 47 Kenyan counties.MethodsData from the household questionnaire of the Kenya Demographic and Health Survey, 2022 was analysed. Bivariate logistic regression was done with open defecation status as the dependent variable. Independent variables were poverty status, place of residence, ownership of farm animals, gender and educational level of household head. The number of households practicing OD per county were determined using the Kenya Census report of 2019.ResultsPoverty was the strongest predictor of a household practicing OD (OR 43.8 95% CI 26.1–73.8) followed by educational status of the household head (OR 3.3 95% CI 2.3–4.6 ) and the household not owning livestock ( OR 0.7 95% CI 0.6–0.9). An estimated 7.4% of households practice OD. These are estimated to be 814,223 households. Out of these, 686,051 households (84.3%) are found in the 15 counties ranked as having a high population practicing OD. Five counties have managed to eliminate OD and another nine have OD rates of less than 0.5%.ConclusionKenya has made commendable progress in eliminating OD. Poverty is a significant predictor of OD at the household level. To eliminate OD, it is advised that more efforts be targeted towards poor households as well as the 15 counties having a high number of OD-practicing households.

Predictors of the willingness to accept a free COVID-19 vaccine among households in Nigeria

BackgroundTo inform vaccination policy and programmatic strategies to increase COVID-19 vaccine uptake, an understanding of the factors associated with the willingness to vaccinate is needed. MethodsWe analyzed data collected from the sixth and tenth round of the Nigerian COVID-19 National Longitudinal Phone Survey conducted by the National Bureau of Statistics and the World Bank in 2020 and 2021, respectively. Exploratory data analysis and feature selection techniques were used to identify important variables. Multivariable logistic regression models were fitted to assess the association between socio-demographic and economic factors and the willingness to receive a free COVID-19 vaccine among Nigerian households at two different time points before vaccines became widely available. ResultsData from 1,733 and 1,651 Nigerian households who completed the sixth and tenth round of the survey, respectively, were included. Most respondents (>85% of households) were willing to receive a free COVID-19 vaccine from both survey rounds. The median household size was 6 (IQR: [4, 8]) with females heading about 18% of the households. Approximately 22% of the household heads had not received any formal education. Compared to households whose head had no education, households whose heads had completed tertiary education or higher had significantly lower odds of willingness to be vaccinated (ORround 6: 0.46, 95% CI: [0.31, 0.68], ORround 10: 0.49, 95% CI: [0.34, 0.71]). An increasing proportion of male household members was associated with greater willingness to receive a free COVID-19 vaccine (ORround 6: 1.84, 95% CI: [1.01, 3.33], ORround 10: 5.25, 95% CI: [2.86, 9.65]). Significant associations with vaccine willingness were also observed across geopolitical zones of residence with households in South-East Nigeria (ORround 6: 0.16, 95% CI: [0.10, 0.24]; ORround 10: 0.29, 95% CI: [0.19, 0.43]) and South-South Nigeria (ORround 6: 0.57, 95% CI: [0.36, 0.90], ORround 10: 0.32, 95% CI: [0.22, 0.48]) less likely to be willing to receive a free vaccine compared to households in North-Central Nigeria. ConclusionThese findings from two different time points before vaccine roll-out suggest that the educational level of household head, proportion of male household members, and the geopolitical zone of residence are important baseline predictors of the willingness to receive a free COVID-19 vaccine in Nigeria. These factors should be carefully considered and specifically targeted when designing public health programs to inform early-stage strategies that address underlying vaccine hesitancy, improve vaccine uptake, promote ongoing COVID-19 vaccination efforts, and potentially enhance other immunization programs in Nigeria.

Factors associated with the rabies vaccination status of dogs in households in Beni City, D.R. Congo.

Human rabies transmitted by dogs still kills thousands of people each year worldwide. Dog bites are common in the city of Beni (Democratic Republic of Congo), which shows low rabies vaccination coverage. This study aimed to determine the factors associated with the rabies vaccination status of dogs. A cross-sectional analytical study was conducted in the town of Beni among dog owners, during a household survey selected using a multistage sampling. The information sought concerned the knowledge and characteristics of the dog owners as well as the vaccination status of these dogs. Logistic regression was used to investigate associations between the vaccination status of the dogs and the main independent factors. Rabies vaccination coverage in Beni was 26% (95% confidence interval [CI]: 22% - 30%). The main factors associated with the rabies vaccination status of the dog were primary education level of household head (adjusted odds ratio [aOR]:4.8; 95% CI: 1.2- 19.8); university education level of household head (aOR: 5.9; 95% CI: 1.6-22); perceived rabies severity (aOR: 44. 4; 95% CI: 10.4-188), having more than one dog in the household (aOR: 2.6; 95% CI: 1.6-4.3); age range 7-12 months (aOR: 0.2; 95% CI: 0.1-0.6) and confined dog breeding (aOR: 3.9; 95% CI: 1.1-14.9). The low vaccination coverage in Beni requires mass vaccination campaigns against canine rabies targeting the dog owners with low education levels, those raising more than one dog, with stray dogs or dogs less than 12 months old.

Market participation as livelihood and safeguarding intangible cultural heritage: A case of Chăm ethnic minority pottery households in Vietnam

This study examines the extent of market participation among Chăm pottery producers in Vietnam and the factors that influence this extent. The research utilized the total market participation index to assess the level of market participation and Tobit regression to examine the factors influencing market participation. Primary data were collected from a sample of 150 pottery households. The study demonstrates that pottery households are involved in the market to varying degrees. Factors such as family size, hired labourers, production space, self-owned transportation, average distance to customers, amount of advertising, and credit accessibility positively affect their participation in the market. Shipping damage, government assistance, non-pottery income, and education level of household head have a negative effect. The findings indicate that government assistance should consider the requirements of pottery households to develop efficient support measures. The research serves as a useful reference for policymakers and managers in devising strategies to promote both the growth of traditional craft production and the sustained well-being of ethnic groups. This, in turn, would contribute to the overall economic advancement of the country.

Household vulnerability to and preparedness for disasters in Haiti

This paper examines the socioeconomic factors correlated with vulnerability to natural hazards using data from the High-Frequency Phone Survey conducted in 2021, 2022, and 2023. The results indicate a high overall exposure to hazards, with a significant number of households facing the threat of multiple hazards. Approximately 76 percent of respondents reside in households facing 3 or more hazards. Furthermore, the analysis finds that disaster preparedness is generally low, with the poorest households experiencing the most significant challenges: households in the two bottom wealth quintiles are less likely to have the necessary supplies to prepare for and respond to disasters sufficiently compared to those in the upper quintiles. Moreover, the household head's education level and internet access are found to be correlated with the likelihood of better disaster preparedness. This suggests that higher levels of education and internet access play a significant role in improving preparedness levels among households. These findings highlight the importance of addressing socioeconomic factors when developing strategies to enhance resilience to natural hazards. Policymakers can mitigate the negative impacts of natural disasters on affected communities by improving disaster preparedness among the most vulnerable households and promoting education and internet access.

The rich-poor divide: Unravelling the spatial complexities and determinants of wealth inequality in India

This study presents the first in-depth analysis of spatial differences and factors influencing wealth distribution among households in India. It uses data from the latest National Family Health Survey, covering 707 districts. Techniques like the Lorenz curve, Gini coefficient, Location Quotient, Morans statistics, and Univariate and Bivariate LISA methods explore inequalities, concentration, and clustering patterns of rich-poor households at the district level. Additionally, spatial regression models such as OLS, GWR, and MGWR help to uncover spatial disparities and variability. Our findings demonstrate significant regional disparities, with the affluent household concentration being notably higher in north-western and southern India, while central, eastern, and northeastern regions exhibit greater inequality. Key factors impacting wealth inequality include rurality, low female literacy rates, educational level of household heads and prevalence of Scheduled Castes/Tribes. This study highlights the spatial dimensions of wealth inequality and provides a nuanced understanding of the factors contributing to these patterns. The GWR and MGWR models prove most effective, explaining more than 90% of the variation in wealth distribution factors. This study sheds light on the spatial dynamics and factors behind wealth disparities in India, offering strategic insights for equitable growth initiatives targeting diverse socio-economic sectors.

Differential impacts of electricity access on educational outcomes: Evidence from Uganda

We investigate the differential impact of electricity access on educational outcomes in Uganda using the Uganda National Panel Survey data and employ instrumental panel probit techniques. The findings indicate that reliable electricity is associated with high school enrolment and completion. Also, the results show that education level of household head, marital status, gender, and good housing conditions are associated with better education outcomes. Our results provide evidence for designing supportive policies for increased access to reliable electricity especially among rural households where there are high disproportionately lower education outcomes. Also, the results suggest that policies to eliminate all barriers to reliable electricity access can greatly enhance educational outcomes in Uganda.

Research on farmers' adoption of additional technology combinations: Practice from Chongqing, China.

Tobacco farmers often adopt additional multiple agricultural technologies (AMATs) in addition to implementing the standardized technical system in China. Based on the cross-sectional micro data of 346 households of Chongqing, China, this paper assesses the determinants and impacts of the adoption of AMATs on income by using a multinomial endogenous treatment effects model to correct for selection bias and endogeneity caused by observed and unobserved heterogeneity. The results show that (1) the adoption of combinations of AMATs is determined by the household head's education level, experience in tobacco growing, the shortest distance to nearby town, the amount of technical training, the ratio of land available for mechanical cultivation to tobacco land, the distance to extension station, and the ratio of leased land. (2) The adoption of combinations of AMATs has heterogeneous effects on farmers' income through yield and quality improvement. (3) The comprehensive combination of AMATs is not necessarily the best option for farmers. Due to the interaction between technologies such as complementary, substitute or supplementary effects, the moderate implementation of fertilizers and soil improvement is the most effective combination. The results of this research provide a scientific basis for improving the adoption efficiency of AMATs in China.

DETERMINANTS OF HOUSEHOLDS’ EDUCATIONAL EXPENDITURE IN THE MEKONG DELTA OF VIETNAM

This study investigates the determinants of households’ educational expenditure in the Mekong Delta through the Viet Nam Living Standard Survey (VHLSS) data in 2022. The Tobit model is used to identify factors that may influence and explain the households’ expenditure on education in the Mekong Delta. The findings found that eight factors have a statistically significant impact of 1% to 10% on the households' educational expenditure. They include 06 factors (age of household head, ethnicity of household head, household’s size, place of residence, households with additional studying members and household’s average income) which positively impact on the households’ educational consumption and the other factors (educational level of household head and participation in local government) which have negative impacts on the educational consumption of the households. Given findings enable us to propose various suggestions to optimize the investment and expenditure for the education of households in the Mekong Delta.

Impact of Agroforestry Adoption among Smallholder Farmers’ Households in Zambia: An Expenditure Approach

The environmental, economic, and social effects of climate change are expected to be profound for smallholder farmers, especially in developing countries like Zambia, whose way of life is largely dependent on the natural world. Many developing countries have realized that climate-smart agricultural practices such as agroforestry are a solution to existing problems caused by climate change. Agroforestry technologies incorporate tree crops in farming systems that benefit farmers with fodder for animals and fruits, reduce erosion, and reclaim soil fertility. This study investigated the impacts of agroforestry adoption on smallholder farmers’ crop productivity and household expenditure in Nyimba district, Zambia. The study further explored the factors influencing the adoption of agroforestry among smallholder farmers in the study area. Data was collected from July to August of 2022 from 325 randomly selected smallholder farmers’ households in four villages in the Nyimba district of Zambia. A binary logistic regression model was used in this study to determine factors influencing the adoption of agroforestry among smallholder farmers. The results revealed that smallholder farmers’ household head education level, access to extension services, household size, access to credit, farming experience, farmland size, and distance to the nearest market had an influence on agroforestry adoption. Propensity score matching was performed to determine the impacts of agroforestry adoption on smallholder farmers’ household expenditure and crop productivity. The results revealed that smallholder farmers’ household adopters had 1,929.040 kilograms of crop yield (Zea mays L.) higher than non-adopters by 817.43 kilograms. Household expenditure for smallholder farmers adopters was ZMW 8,873.47 higher than non-adopters by ZMW 5,617.91 in the study area. The findings imply that smallholder farmers’ households should implement agroforestry in the long term to improve their household welfare. Therefore, the study suggested that efforts should be focused concomitantly on the diffusion of agroforestry options and the lifting of their adoption barriers among smallholder farmers

Analysing the Influence of Caste, Gender, Religion, and Household Characteristics on Enrolment Status and Student Dropout in Assam: A Logistic Regression Study

This study investigates the factors contributing to enrolment status and dropout rates in Assam using a binomial logistic regression model. The dependent variable, enrolment status, is categorized into currently enrolled and dropout or no enrolment. Explanatory variables encompass religion, gender, social group, sex of the head of the household, household head's education level, family income, and household size.
 Our objectives include assessing the influence of religion, gender, social group, household leadership, head's education level, family income, and household size on enrolment and dropout likelihood. Dummy variables are used for religious affiliations, social group categories, head's education, and family income groups.
 The results reveal significant associations between gender, education level of the head of the household, and family income with enrolment and dropout likelihood. Muslims exhibit a higher likelihood of dropout or no enrolment compared to Hindus. Female-headed households and individuals in households with higher-educated heads display increased odds of no enrolment or dropout. Lower family income levels are associated with higher odds of dropout.

Patterns and Determinants of Households' Energy Choices for Cooking as Well as Their Implications for Poverty Eradication in Nigeria

ABSTRACT: Adequate access to environmentally-friendly energy sources is crucial for addressing the problems of environmental degradation and adverse climate change as well as other developmental challenges. The literature on the patterns and determinants of households' energy choices for cooking is very scanty. Essentially, the scanty literature, in general, did not adequately cater for household composition and economies of scale in household consumption as well as give adequate consideration to the impact of ownership of education/entertainment appliances and means of communication by households on households' energy choices for cooking. It is very important to utilize adult equivalence scales and estimate of economies of scales in household consumption in the analysis of household consumption in order to make such analysis highly robust. It is also very important to include ownership of education/entertainment appliances and means of communication in the analysis of households' energy choices for cooking because they (the appliances and means of communication) are expected to provide adequate awareness on the harmful effects of dirty energy sources and such awareness can influence households' energy choices. Furthermore, none of the studies in the scanty literature discussed the major implications for poverty eradication of the patterns and determinants of households' energy choices for cooking. This study adequately addressed the highlighted research gaps. The study analyzed the patterns and determinants of households' energy choices for cooking in Nigeria and discussed their implications for poverty eradication in the country using, among other things, descriptive statistics and multinomial logistic regression technique. The study was based on a nationally representative survey data, obtained from the National Bureau of Statistics. The study found that the patterns of households' energy choices for cooking in Nigeria exhibit the operation of energy ladder hypothesis. The study also found that increased educational level of household head, ownership of electric food preservation appliance by household and satisfactory housing condition are among the factors that increase the likelihoods of the uses of transition fuels and very clean energy sources as well as reduce the likelihood of the use of traditional biomass fuels. Adequate measures should therefore be put in place to sufficiently increase households' incomes and guarantee optimal access to environmentally-friendly energy sources for cooking in the country; this will pave the way for poverty eradication in the country.

Determinants of transitions in drinking water service systems in developing economies: a case study of Uganda

Abstract Limited research has been undertaken on significant factors associated with transitions between drinking water supply systems (DWSS) ladders. In this paper, we applied panel ordered logistic multinomial logistic regression models to seven datasets of the Uganda Demographic and Health Survey (1988–2021), with the SDG6 categorical levels of DWSS (unimproved, improved and piped into dwelling) as transition levels, and various socio-economic and demographic characteristics as covariates. Sex and education level of household head, toilet facility, electricity access, size of agricultural land and wealth index are significant factors. The main implication is the need to address socio-economic disparities in developing economies.

Determinants of household poverty in Arsi Nagelle town, West Arsi Zone, Ethiopia

The struggle to achieve above the poverty line at the household level in the urban areas of Ethiopia dates back an extended period. In this regard, this study was conducted to identify and analyze the determinants of urban household poverty in the case of Arsi Nagele town. The study employed both primary and secondary data. Preliminary data was collected from 337 randomly selected households in two sub-cities by questionnaire. Both descriptive and Logit regression model was used for data analysis. From the three schools of thought, the basic needs approach is employed to identify households as poor and non-poor. Sixteen (14) explanatory variables, four continuous and ten discrete, were included in the logit regression model. Out of these variables, the sex of the household head, age of the household head, marital status of the household head, family size of household head, education level of household head, household head house tenure, household head access to electricity, household head access to the market center, household head access to credit, household head access to clear and sufficient water, the existence of solid institution was among the significant variables affecting the level of household's poverty. The research found that the area's food poverty line and the total poverty line were 13,788 Birr and 14,436 Birr per adult per year, respectively. Accordingly, the incidence of poverty, poverty gap, and severity was found to be 40 percent, 26.5 percent, and 7 percent, respectively. The research found that the area's food poverty line and the total poverty line are 13,788 Birr and 14,436 Birr per adult per year, respectively. Keywords: poverty, Logit, Poverty line, poverty gap, and severity

Factors influencing paddy producers’ profitability and sale to markets: evidence from Battambang Province, Cambodia

While rice farming is essential for livelihoods of smallholder farmers and the economy, there is limited evidence of specific socioeconomic determinants of paddy sale and profitability of Cambodian farmers. The study analyzes factors influencing sale and profitability of paddy production in Battambang Province using primary data collected from randomly selected 242 paddy farmers in the northwest of Cambodia. The data were analyzed using the log-linear ordinary least squares regression. The results show that paddy farming is profitable with the benefit-cost ratio of around 2.0. Besides, smallholders obtained larger profitability than medium- and large-scale farmers due to the diseconomies of scale. Fertilizer, pesticide, harvesting, and seed costs were major cost items for paddy production in the study area. Education level of household heads, household size, land are under paddy, the quantity of paddy consumed at home, the quantity of paddy retained for seed recycling, varieties of rice, and distance to markets significantly influenced paddy sale to markets, while education level of household heads, farming experience, household size, varieties of rice, selling price, cost of seed, and cost of fertilizer were found to influence the profitability of paddy production. Farm policies should aim at increasing paddy fields, expanding irrigation systems, promoting premium rice varieties, and supporting the farm gate price of paddy produce, while reducing the prices of inputs, particularly seed and fertilizer.

Synthetic Minority Over-sampling Technique (SMOTE) for handling imbalanced data in poverty classification

Poverty data in official statistics data is important for development planning. The lower percentage of the poor recorded yearly indicates good development of a country. Moreover, there is always a problem when performing an inferential and classification analysis because of the imbalanced data, thereby leading to biases in the estimation results and prediction errors in the classification. One of the solutions to this problem is using Synthetic Minority Over-sampling Technique (SMOTE). Therefore, this study aims to evaluate the inference and classification quality using the binary logistic regression model without and with SMOTE. The data utilized was the poverty status of households in the rural and urban areas in East Java, Indonesia as contained in the 2019 National Socio-Economic Survey. Furthermore, the variables used are poverty status of the household, the age of the household head (HH), the ratio of household members who are employed, gender of the HH, number of household members, education level of HH, and occupation of the HH. It was concluded that the model with SMOTE approach was better at inference and classifying the results.

Access to inclusive sanitation and participation in sanitation programs for people with disabilities in Indonesia

Access to inclusive sanitation for people with disabilities (PWDs) remains a global challenge, including in Indonesia, where 10–15% of its population is disabled. Inclusive sanitation facilities can be achieved when PWDs are involved in the sanitation-related decision-making process, e.g., designing toilet that meets their needs. This study aims to investigate the situation of the sanitation facility in houses of PWDs and understand knowledge, attitude, and practices related to PWD participation in sanitation programs using a case study in two provinces in Indonesia: Nusa Tenggara Barat and Nusa Tenggara Timur. Quantitative data were taken from 129 PWD households, and qualitative data were from in-depth interviews with relevant stakeholders. The latter was presented in a causal loop diagram. Less than 5% had inclusive sanitation at home, mainly due to no supportive tools and bins. The knowledge levels related to sanitation and PWDs participation in sanitation programs were relatively low. Economic condition was one of the barriers for PWDs to participate in the sanitation program. Statistical analysis found that a higher household head education level was associated with a more positive attitude and higher PWD participation in sanitation programs. Although Indonesian law supports PWD participation, the implementation remains a challenge. This study also underlines the need for capacity building in facilitating PWDs’ involvement in sanitation programs and community meetings. Finally, barriers to PWD participation can come from different levels and actors, e.g., the family, the community, the district level, and the PWD itself, indicating the need to involve actors at all levels to enhance PWD participation in the sanitation program that leads to inclusive sanitation facilities for all groups.

Factors Affecting Maize Productivity: In Case of Bedele District of Buno Bedele Zone, Oromia Regional State, Ethiopia

Though agriculture remains to be the most important sector of the Ethiopian economy, its performance has been disappointing and food production has been lagging behind population growth. This gap between demand for and supply of food can be reduced by improving crop production and productivity. As maize is a significant contributor to the Ethiopian economy, increasing production and productivity in maize production could be taken as an important step in attaining food security. This study was conducted in Bedele district of Buno Bedele zone of Oromia National Regional State with the aim of identifying factors affecting the productivity of maize production. This study used cross sectional data which was collected from a total of 174 farm households which were randomly and proportionally selected from 4kebeles of the Woreda using two stage sampling technique. The primary data were collected through individual interviews of respondents using semi-structure questionnaire. Secondary data was collected from different relevant literatures such as district reports, publications, journals and other documents relevant for the study. Descriptive statistics and Econometric model were used to assess the collected data. The result of Descriptive statistics indicated that the mean amount of maize produced by households in quintal per hectare is about 19.76 quintal. Results of Cobb- Douglas production function revealed that Variability of weather condition, Extension Contact, Land allocated for maize, Mode of sowing, Amount of fertilizer used, Farm Income, labor cost, Number of Oxen, and educational level of household head positively and significantly affected the productivity of maize production. Whereas Soil fertility, occurrence of pests and diseases, over cultivation are negatively and significantly affected the productivity of maize production. Therefore, attention should be given to major factors that affect the productivity of maize production to increase production and productivity of maize.

Fuel adoption in rural heating: a field study on northern China

PurposePromoting clean heating in rural areas is crucial for achieving a low-carbon transition of energy consumption and China's dual-carbon target. The study aims to consider the energy stacking behavior in heating energy use, reveals the determinants that affect household cleaner heating choices under the winter clean heating plan (WCHP), and proposes policy recommendations for the sustainable promotion of clean heating.Design/methodology/approachWith unique rural household survey data covering the clean heating pilot regions in northern China in 2020, this study estimates the relationship between driving factors and heating energy choices through binary and multivariate probit models.FindingsThe regression estimates show that the main drivers of heating energy choices include household income per capita, education level of household head, knowledge of the WCHP, access to heating subsidies and perception of indoor air pollution. There is energy stacking behavior in rural household heating energy use. Household decisions to adopt electricity or clean coal heating are correlated with firewood or soft coal use.Originality/valueThis study is one of the few to investigate the heating energy use of rural households by allowing for the adoption of multiple energy types. Combined with a unique microsurvey dataset, it could provide rich information for formulating proper energy transition planning. The findings also shed light on the importance of heating subsidies, households' knowledge of WCHP and awareness of environmental health in choosing clean heating energy, which has not been fully valued in related research.

Smallholders' resilience-building adaptation and its influencing factors in rainfed agricultural areas in China: based on random forest model.

In recent years, extreme events and risks have increased under the background of global warming, which influenced agricultural production significantly. Adaptation has been considered as a key pathway to enhancing smallholders' climate resilience. We selected a total of 903 smallholders using the multi-stage random sampling technique in rainfed areas in China, and then collected the survey data through the structured questionnaire and focus group discussion. Three resilience-building adaptation indices (RBAS-A, RBAS-D and RBAS-I) were constructed by the entropy method, whose mean values were 0.378, 0.336, and 0.602, respectively. Furtherly, the random forest model was used to explore influencing factors of climate-resilient adaptation strategies. The results revealed that education level of household head, family size, farmland size, access to information by mass media and kith and kin, perception of temperature change in summer and winter, and perception of crop yield change were the significant factors influencing smallholders' alteration strategies. Meanwhile, age and education level of household heads, off-farm income, farmland size, mass media, and perception of winter temperature changes had significant effects on the diversification strategies. Moreover, demographic characteristics, socioeconomic characteristics, information access and climate change perceptions, and impacts had significant impacts on intensification strategies. Importantly, we found that there was a certain threshold for the impact of several factors on the constructed composite indices. And the impacts of the perceptions of temperature on alteration and intensification strategies showed a V-shape. Finally, we proposed targeted suggestions for improving smallholders' climate-resilient adaptation in the rainfed agricultural areas in China.