Household Income Research Articles

Neurofibromatosis Type 1 Patients With Epilepsy: A Comprehensive Analysis of Demographics, Comorbidities and Healthcare Outcomes.

Neurofibromatosis Type 1 (NF1) is the most common neurocutaneous disorder in the United States. Due to a nonfunctional mutation in the NF1 gene, the disorder may initially present with café-au-lait spots and later numerous neurofibromas across the body. Epilepsy is a rare comorbidity of NF1, with an incidence of just 4%-7%. While abnormal electroencephalograms have been seen in up to 25% of NF1 patients, very few studies have investigated the association between epilepsy and the NF1 patient profile. This study was aimed at evaluating the associations between epilepsy and demographics, comorbidities and healthcare outcomes in NF1 patients. The 2017 National Inpatient Sample (NIS) database was retrospectively queried for patients with NF1 using ICD-10 PCS codes. Chi-square tests were used in univariable analysis to compare patients within this cohort with and without epilepsy. Regression analysis was used in multivariable analysis to identify comorbidities that were predictors of epilepsy and the effect of comorbidities on outcomes. 4635 patients with NF1 were identified, of which 655 (14.1%) had epilepsy and 3980 (85.9%) did not. The NF1 patient population with epilepsy was largely comprised of White males of lower household income in larger urban/teaching hospitals and who used Medicare or Medicaid. Multivariable logistic regression revealed that malignant brain neoplasms, paralytic ileus, scoliosis, pregnancy complications, paralysis, other neurological disorders, metastatic cancer, coagulopathy, drug abuse and hypertension were predictors of developing epilepsy in NF1 patients. Additionally, epilepsy in NF1 patients was associated with a shorter length of stay, lower total charges and fewer total procedures.

몽골인의 사회계층이 관광 목적지 숙식 및 체험활동 선택에 미치는 영향 : 홉스골 국립공원 지역 관광자를 대상으로 한 이항 로지스틱 회귀분석

Looking at Mongolian tourists to the Khuvsgul National Park area, this study examines the impacts of tourists’ social stratification on their accommodation, dining, and experiential activity choices. The survey was conducted both online and offline at five different accommodations in the Khuvsgul National Park area between January 2024 and March 2024, and 288 valid questionnaires were used for the binary logistic regression analysis. The results showed that tourists’ occupation, average monthly household income, and subjective social class significantly influenced their choice of either luxury (e.g., hotels and resorts) or inexpensive accommodation (e.g., traditional Mongolian ger camps). Specifically, office workers were about 4.24 times more likely to stay in hotels or resorts than unskilled laborers, and the probability of staying at a hotel or resort increased by 1.45 times with each increment in subjective social stratification. In regard to tourists' dining choices (i.e., eating at hotel or resort restaurants vs. bringing their own food or eating at regular restaurants), average monthly household income and subjective social class had significant effects. However, education level influenced neither accommodation nor dining choices. Finally, tourists’ choices of some experiential activities (e.g., Tsaatan experience and Sukhbaatar ship travels) were influenced by their occupation and other control variables such as gender and age. The study findings and their implications were further discussed at the conclusion of this article.

How do policy measures affect the ability of poverty-stricken households to cope with external shocks? From the perspective of differences in the human capital endowment of households

Human capital plays a vital role in poverty-stricken households' efforts to cope with external shocks. Improving the human capital of poverty-stricken households to help them address external shocks can enhance the sustainability of poverty-stricken household livelihoods and support poverty alleviation. In this study, households with dependent children and older members were selected from questionnaires covering 6,463 poverty-stricken households from 33 poverty alleviation districts and counties in Chongqing municipality, China. Multiple linear regression model and stepwise regression methods were then used to compare the effects of the number of household members supported and the number of those working on the increase in income among poverty-stricken and nonpoverty-stricken households. Finally, the correlations between policy measures, dependent household members and household labor were examined. The results show the following: (1) Policy measures can alleviate the negative impact of a household's dependent population on household income. (2) Poverty-stricken households' access to policy support is closely related to the characteristics of their human capital. The household's dependent members and laborers are effectively protected by safety net and cargo net policies. (3) Policy measures can mitigate the impact of COVID-19 on the income of nonagricultural laborers while increasing the income of agricultural laborers. The findings show that the ability of poverty-stricken households to overcome poverty and deal with external shocks can be increased by revitalizing rural industries, linking the development of rural industries with the income of poverty-stricken households, and rationally using rural labor resources.

Socioeconomic Status and Physical Fitness Levels among University Students

This study examines the correlation between socioeconomic status (SES) and physical fitness levels among university students in Henan, China. The research considers various SES indicators, including parental education, household income, and access to healthcare, in relation to students' self-assessed physical fitness and activity levels across multiple domains, such as vigorous physical activity, organized sports, and recreational activities. Findings reveal that students from lower SES backgrounds often face barriers, such as limited access to safe recreational spaces and organized sports, which may hinder their ability to participate in physical activities, thereby impacting their fitness levels. In contrast, students from higher SES backgrounds have greater access to fitness resources, leading to more favorable physical fitness outcomes. The study underscores the need for policy interventions and school programs that prioritize equitable access to physical activity opportunities for students of all socioeconomic backgrounds.

Association between Gestational Bisphenol A Exposure and Maternofoetal Outcomes: A Cohort Study in a Single Tertiary Hospital in Klang Valley

A growing body of literature has documented the adverse effects of bisphenol A (BPA) exposure on pregnancy and birth outcomes. Regardless, how gestational BPA exposure affects mother-newborn pairs in Malaysia is yet to be explored. Hence, this study aimed to investigate urinary BPA levels of pregnant women living in Klang Valley and their associations with adverse obstetric and birth outcomes. This cross-sectional study involved pregnant women in their third trimester attending antenatal clinic in Hospital Al Sultan Abdullah (HASA), UiTM Puncak Alam, who planned to have their delivery in HASA. Information on maternal age, parity, education, household income, gestational age, and obstetric complications, such as Gestational Diabetes Mellitus (GDM), preeclampsia, preterm labour, and foetal growth restriction (FGR) were collected. Maternal urine samples were also obtained and evaluated using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Additionally, the neonatal outcomes including mode of delivery, gestational age, birth weight and need for NICU admission were documented. Our LC-MS/MS analysis showed that BPA was present in all the urine samples, with levels varying from 4.42 to 30.86 ng/mL. The median level was 15.96 ng/mL. Urinary BPA level has no significant correlation with gestational hypertension (GHTN), preterm labour and low birth weight babies. Babies who need NICU admission were born to mothers who exhibited significantly different urinary BPA levels compared to those whose babies were not admitted (p=0.049). Finding from this study suggestive of further investigation on level of gestational urinary BPA with NICU admission, ideally with a larger sample size to validate these results.

Association of relative handgrip strength on the development of diabetes mellitus in elderly Koreans.

Diabetes mellitus (DM) is a significant public health concern, particularly in the elderly population. Absolute handgrip strength (HGS) serves to quantify muscle strength. It is recommended that the risk of low muscle strength and increased body mass index be concurrently evaluated using relative HGS. There are currently insufficient evidence regarding the relationship between relative HGS and DM in the elderly Korean population. Therefore, the association between relative HGS and the development of DM in Korean elderly was investigated. Data from the Korean Longitudinal Study of Ageing were used to determine the odds ratio (OR) between relative HGS and DM during the follow-up period from 2006-2020 among Korean men and women aged ≥65 years without DM when they first participated in this survey. Analysis was conducted using the Generalized Estimating Equation method. Trend analysis was performed for DM development based on relative HGS. Among elderly males, higher relative HGS groups had reduced odds of developing DM (Middle tertile: OR 0.87, 95% CI 0.61-1.23, p = 0.419.) (Upper tertile: OR 0.82, 95% CI 0.56-1.18, p = 0.281.) Among elderly females, the reductions were similar. (Middle tertile: OR 0.82, 95% CI 0.66-1.03, p = 0.087.) (Upper tertile: OR 0.79, 95% CI 0.50-1.25, p = 0.306.) However, these differences were not statistically significant. Significant predictors of new-onset DM included age, BMI (overweight/obese), household income, alcohol consumption, hypertension, and chronic liver disease. Trend tests indicated a substantial decrease in the OR as the relative HGS increased for male and total groups (p for trend < 0.05). Relative HGS did not achieve statistical significance. Our findings indicate that BMI, particularly overweight and obesity, significantly predicts new-onset DM. However, trend tests indicated a substantial decrease in the OR as the relative HGS increased for male and total groups (p for trend < 0.05), even after adjusting for BMI categories. Despite the lack of statistical significance in some cases, the trend suggests that promoting resistance exercises to enhance HGS could be beneficial in DM prevention. Comprehensive DM prevention strategies should include managing obesity and chronic conditions for elderly.

The Awareness of Antimicrobial Resistance Among Adult Population in an Urban Setting of Rawalpindi

O Objective: To determine the association of various aspects of antimicrobial resistance awareness and socio-demographic determinants among residents of Rawalpindi. Study Design: Cross-sectional analytical study. Place and Duration of Study: Rawalpindi Cantonment, Pakistan, from Jan to Dec 2021. Methodology: A validated (World Health Organization) multi-country questionnaire was completed by a total of 400 participants, aged 16 years and older, by using two-stage sampling technique. The relationship between social and dependent variables was analyzed using chi-square test of significance. Results: Study results showed that 53.8% of participants were aware of the term ‘antibiotic resistance’ whereas only 29.5% understood what antimicrobial resistance meant. In comparison to males, more females (65.3%) knew the term antibiotic resistance. Antibiotic resistance awareness was higher among young adults aged 16-24 years (67.8%) than among older age groups (p=0.001). Antibiotic resistance awareness in relation to gender (p&lt;0.001), education level (p&lt;0.001), occupation (p&lt;0.001) and monthly household income (p&lt;0.001) was found statistically significant. Antibiotic resistance, according to nearly one-third of respondents (31.8%), was a problem in other countries but not in Pakistan. Conclusion: Awareness and level of understanding regarding spread of antimicrobial resistance and antibiotic resistance itself were found to be low. The study findings revealed that older adults, those with lower education and lower socioeconomic status had the least knowledge and attitudes regarding antibiotic resistance and antimicrobial resistance as compared to other groups.

Machine Learning Analysis of Factors Influencing Pediatric Telehealth Visits During COVID-19: A State-Level Comparison Using 2021–22 National Survey of Children’s Health Data

Background/Objectives: The COVID-19 pandemic reduced in-person pediatric visits in the United States by over 50%, while telehealth visits increased significantly. The national use of telehealth for children and the factors influencing their use have been rarely studied. This study aimed to investigate the prevalence of telehealth use during the COVID-19 pandemic and explore the potential factors linked to its use at the state level. Methods: A cross-sectional study of the National Survey of Children’s Health (2021–22) sponsored by the federal Maternal and Child Health Bureau was performed. We used the least absolute shrinkage and selection operator (LASSO) regression to predict telehealth use during the pandemic. A bar map showing the significant factors from the multivariable regression was created. Results: Of the 101,136 children, 15.25% reported using telehealth visits due to COVID-19, and 3.67% reported using telehealth visits due to other health reasons. The Northeast states showed the highest telehealth use due to COVID-19. In the Midwest and Southern states, children had a lower prevalence of telehealth visits due to other health reasons. The LASSO regressions demonstrated that telehealth visits were associated with age, insurance type, household income, usual source of pediatric preventive care, perceived child health, blood disorders, allergy, brain injury, seizure, ADHD, anxiety, depression, and special needs. Conclusions: This study demonstrated significant variability in the use of telehealth among states during the COVID-19 pandemic. Understanding who uses telehealth and why, as well as identifying access barriers, helps maximize telehealth potential and improve healthcare outcomes for all.

Dynamics of living income for coffee farming households in agricultural area development policy: Socio-spatial integration

A decent income is an important part of overcoming economic disparities in agricultural development, especially in developing countries where most of the population are small farmers. As a developing country, Indonesia has also established a decent standard of living by setting a minimum wage as a reference for a decent income at the national and regional levels. However, this benchmark is not relevant to be applied uniformly at all levels of workers. This research determines the national coffee development area as the study center. We developed the Anker living wage methodology as a simple concept for determining living income for certain worker communities, especially for small farmers in rural areas who dominate the type of work in Indonesia. a socio-spatial approach is used to visualize the distribution of the dynamics of a decent life in various conditions of farming households. We found that 96.6% of coffee farming households in the national coffee development area had an inadequate living income, and only 3.4% were at an adequate level. We conclude that the current state of agricultural land management does not guarantee a decent income, even though efforts have been made to maximize agricultural crop productivity. The spatial description also shows that this condition is evenly distributed throughout residential areas. It is hoped that this approach can become an essential reference in implementing agricultural development programs that focus on welfare and equitable development as benchmarks for sustainable development goals in the future.

Competitive or crowding‐out? Estimating spillover effects from large‐scale farms on smallholders in China

AbstractDrawing on data from the Chinese Family Database for 2015, 2017, and 2019, this study employed the difference‐in‐differences method to examine the spillover effects of large‐scale farms (LSFs) on smallholders. The findings confirmed that LSFs positively affect smallholder household income and nonfarm income. The mechanisms verified that LSFs increase the nonfarm income of smallholders, primarily through the transfer out of their land. Additionally, we found that vulnerable groups—such as households with a lower proportion of the labor force, a lower proportion of members in good health, and lower total education years of the labor force—are more likely to be crowded out. Additionally, the study confirmed that LSFs steal the market from smallholders, precipitating a slightly negative competitive effect. These findings have important policy implications for developing countries implementing the LSF policy and for countries where smallholders suffer from livelihood issues.

Two birds, one stone: minimum wage and child labor

PurposeThis paper investigates the impact of quasi-exogenous and substantial increases in the minimum wage on child labor outcomes in Türkiye. The study aims to provide empirical evidence on how minimum wage policies affect child labor outcomes in a developing country context, with a focus on gender and age differences. It seeks to understand whether minimum wage increases lead to a reduction in child labor and whether the impact is different for various demographic groups.Design/methodology/approachThe research employs a difference-in-differences methodology using data from the 2012 and 2019 Child Labor Force Survey in Türkiye. The treatment group consists of children from households with minimum wage earners, while the control group comprises children from other households. Various labor market outcomes are analyzed, and robustness checks are performed.FindingsOur findings indicate that while the overall effect of minimum wage increases on child labor is statistically insignificant, there are notable heterogeneous impacts across different demographic groups and employment sectors. Specifically, we observe a significant reduction in the employment probability of girls under the age of 15 and unpaid family workers. Additionally, the likelihood of younger children being wage earners decreases, and the minimum wage increase reduces employment in the agriculture and services sectors for certain subgroups. The impact is also more limited for children in single-adult-worker households.Social implicationsThese results underscore the varying effects of minimum wage policies on child labor and highlight the importance of considering demographic and sectoral differences in policy formulation. Policymakers should complement such policies with income-generating programs and targeted education initiatives to address child labor issues more comprehensively and sustainably.Originality/valueThis study fills a critical gap in the limited international literature on the causal effects of minimum wage policies on child labor incidence. One notable exception, Menon and van der Meulen Rodgers (2018) have explored the impact of minimum wage on child labor in India using regional variation, our study uniquely analyzes the effects at the household level in Türkiye. This approach provides valuable insights into how minimum wage changes affect child labor outcomes in a developing economy context with a high prevalence of minimum wage earners. It also contributes to the broader economic understanding of child labor and household income dynamics.

The Beehives of Stingless Bees in Manipur, India and Their Ecological and Economic Impact to Farmers

Stingless bees (Trigona spp.) are important pollinators in tropical and subtropical ecosystems, playing a vital role in maintaining biodiversity and agricultural productivity. In Manipur, traditional bamboo beehives are used to house these bees, reflecting a culturally significant and sustainable approach to beekeeping. This study examines the ecological and economic impacts of stingless bee beekeeping with bamboo hives in Manipur, using data from field surveys, interviews, and honey production analysis. The results show that stingless bees contribute to a 25-30% increase in crop yield through enhanced pollination. Bamboo beekeeping also generates an average household income increase of 20-35% from the sale of honey and other products. The demand of stingless bee honey is becoming high due to its unique medicinal properties. Despite these benefits, challenges such as habitat loss, climate change, and technical limitations persist. The findings suggest that integrating traditional knowledge with modern beekeeping practices could address these challenges and optimize the ecological and economic potential of stingless bee conservation in the region. This paper emphasizes for supportive policies and further research to fully realize the potential of bamboo beekeeping in Manipur.

A study of oral health and quality of life in patients with dyslipidemia

Objectives: This study analyzed factors influencing oral health and quality of life in patients with dyslipidemia using raw data from the first year (2019) and third year (2021), where the quality of life was assessed using the HINT-8 tool from the 8th National Health and Nutrition Survey data. Methods: Frequency analysis, descriptive statistics, general linear model analysis, and linear regression analysis were performed on the collected data using SPSS program 26.0, and the data of 1,926 participants were analyzed. Results: The mean quality of life (HINT-8) score was 0.78 out of 1.00. Quality of life according to general characteristics, showed significant differences according to gender, age, household income, education level, lifetime smoking status, and lifetime alcohol consumption. In terms of oral health, it significantly differed according to chewing discomfort, speaking discomfort, oral examination history, toothbrushing frequency, toothache history, untreated dental care needs, subjective oral health status and use of oral care products. The predictors of quality of life were gender, household income, education level, lifetime alcohol consumption, chewing discomfort, speaking discomfort, toothache history, and untreated dental care needs. Conclusions: These results confirm that oral health influences the quality of life of patients with dyslipidemia and are expected to provide basic data for research on improving oral health and quality of life in these patients.

Factors influencing the social acceptance of brain-computer interface technology among Chinese general public: an exploratory study

This study investigates the impact of social factors on public acceptance of brain-computer interface (BCI) technology within China's general population. As BCI emerges as a pivotal advancement in artificial intelligence and a cornerstone of Industry 5.0, understanding its societal reception is crucial. Utilizing data from the Psychological and Behavioral Study of Chinese Residents (N = 1,923), this research examines the roles of learning ability, age, health, social support, and socioeconomic status in BCI acceptance, alongside considerations of gender and the level of monthly household income. Multiple regression analysis via STATA-MP18 reveals that while health, socioeconomic status, social support, and learning ability significantly positively correlate with acceptance, and age presents an inverse relationship, gender and household income do not demonstrate a significant effect. Notably, the prominence of learning ability and social support as principal factors suggests targeted avenues for increasing BCI technology adoption. These findings refine the current understanding of technology acceptance and offer actionable insights for BCI policy and practical applications.

Social-Economic Factors and Secondary School Dropout among Girls in Mariani Ward, Tharaka-Nithi County, Kenya

This study investigated the high dropout rates among girls in secondary schools in Mariani Ward, a critical issue observed in many developing regions. The specific objectives of the study were to assess how household income, parental education, and family structure influence girls’ dropout rates. The study was grounded in the Relative Deprivation theory and utilized a descriptive survey design, involving a sample of 385 respondents selected from a larger population of 10,202 through cluster sampling method to ensure representation of various groups within the population. Within the target population, five clusters or sub-locations were identified based on their diverse characteristics. The sample included female dropouts as well as key informants such as head teachers, household heads, and local leaders. Data collection was achieved through questionnaires and interviews, and quantitative analysis was performed using SPSS version 25. The study employed inferential statistical methods, including correlation analysis, chi-square tests, and binomial logistic regression, to assess the impact of socio-economic factors on dropout rates. The results revealed significant positive correlations between dropout rates and household income (0.684), parental education status (0.547), and family structure (0.761). Binomial logistic regression analysis further confirmed the substantial influence of these factors on dropout rates. In addition to these factors, the study also indicated the presence of other unidentified variables affecting dropout rates. This highlights the necessity for further research to explore these additional influences. Based on these findings, the study recommends implementing targeted interventions to address the identified socio-economic challenges. These recommendations include developing financial support programs for low-income families, enhancing parental education and involvement, and fostering supportive family environments. Such measures are essential for reducing dropout rates and promoting sustained educational participation among girls in Mariani Ward. The study provides actionable insights for educators, policymakers, and stakeholders to effectively improve girls' access to education and support their academic persistence.

Chinese Household Carbon Footprint: Structural Differences, Influencing Factors, and Emission Reduction Strategies Analysis

The wide variation in household characteristics, such as household size, income, and age, can lead to significant differences in carbon footprints. Based on data from 1132 Chinese households in 2021, this study examines the structural differences, multiple influencing factors, and mitigation strategies of household carbon footprints (HCFs) in China. The results indicate that indirect emissions, primarily from energy and food consumption, account for the largest share of household carbon footprints, making up over 65% of total emissions. Households with lower carbon footprints are characterized by a per capita living area of less than 20 square meters, rural residences, and shared living arrangements. Carbon footprints for the elderly and minors are lower than adults, while households with higher monthly incomes have the highest carbon footprints. The Multivariate Analysis of Variance (MANOVA) reveals that the main factors influencing HCF include household size, income, and single status, with a more pronounced impact on affluent households than on average households. High-income households have the potential to reduce their carbon footprints through investments in energy-efficient technologies, whereas low-income households are more susceptible to the effects of household size and geographic location. It is recommended that policymakers adopt differentiated measures, such as setting higher reduction targets for larger and wealthier households while providing incentives and technical support to low-income households to achieve meaningful carbon reductions. More effective and equitable low-carbon policies can be formulated by addressing these structural disparities and leveraging the unique characteristics of different household types.

Influence of maternal and infant technology use and other family factors on infant development

BackgroundDigital technology is ubiquitous in the lives of many children and parents. To better understand any influence of technology use by infants, and mothers, on child development, technology use should be considered within the broader family system context in which children develop. This study aimed to investigate associations between infant and maternal technology use and infant 12-month development, taking into consideration other family factors.MethodsThis cross-sectional study used data from ORIGINS participants, collected at 12-months of age: maternal and child technology use (TechU-Q), sociodemographic factors (e.g. child sex, household income), parental mental health (DASS-21), and child development (Ages and Stages Questionnaire). Linear regression was used for analyses.ResultsWhen family factors were considered, higher infant mobile touchscreen device (MTSD) use was associated with poorer infant development for gross motor, problem-solving, and total ASQ-3 scores. In contrast there were no associations between infant television (TV) watching or maternal technology use and total ASQ-3 scores. Higher maternal technology use was associated with higher infant technology use. Poorer maternal and paternal mental health were associated with poorer infant development. Poorer maternal mental health was also associated with higher infant TV watching and higher maternal MTSD use.ConclusionThere is a complex relationship between technology use, parental mental health and other family factors that together influence infant development. To improve infant development outcomes, less focus should be on infant or maternal technology use, and more on supporting the family as a whole, and parental mental health in particular.

Bridging digital divides in Wisconsin: an examination of policy efforts and effectiveness over the past five years

ABSTRACT The digital divide, generally characterized by unequal Internet access, represents the gap between individuals who benefit from the use of digital technologies and those who do not. Many social inequalities are associated with the prevalence of the digital divide, particularly across the rural-urban divide. This research seeks to characterize the status of the digital divide, and related sociodemographic variables, within the context of the US state of Wisconsin. In addition, this research investigates the effectiveness of broadband expansion grants, within the state of Wisconsin, on bridging the digital divide. The findings indicate that, at the county level, variations in education, household income, age, and location on a rural-urban continuum are all associated with variations in county broadband adoption rates. Also, despite increasing broadband funding, the amount of money sent to a county is not associated with the need of that county or the change in county level broadband adoption rates from the year 2017–2021. The findings of this study have theoretical implications as they add to our understanding of how broadband adoption is related to social aspects of life. In addition, there are political implications in terms of how grant funding allocation is determined.

Application of The Blinder-Oaxaca Decomposition Method to Analyze The Unemployment Gap Between Gender in Riau Province in 2022

Gender equality is one of the goals of SDG, so every country needs to make efforts so that gender equality can be realized. Gender inequality is calculated using the Gender Inequality Index (GII). One of the components in preparing the Gender Inequality Index is labor force participation rate. Within the population included in the labor force, some people are employed and unemployed. In this study, gender inequality in terms of unemployment will be calculated using Blinder-Oaxaca decomposition with three calculation stages. The first is probit regression analysis, the second is marginal effects and the third is Oaxaca blinder decomposition. The results of the probit regression analysis show that all observed independent variables significantly effect on unemployment for both men and women. Meanwhile, the marginal effect results show that this variable’s influence is quite small, only 0.1 - 2 percent. The results of Oaxaca blinder decomposition show that the inequality between male and female unemployment is 1.42%, of which 29.88% is influenced by, observed factors and unobserved factors influence the remaining. There are only three variables that influence the gender gap, namely marital status, number of household members and household income 70.12%.

An Analysis of the Impact of Self-Help Group Bank Linkage Program on Sustainable Development

India's banking system has advanced its reach to the poorest people in urban and rural areas. It is recognized that their credit requirements are frequent, unpredictable and very small. However, these are crucial for the development of the rural regions. Therefore, the country's banking system has emphasized this area to promote savings and insurance financial products in this target population. Hence, alternative policies, procedures, and systems have been developed to fulfil these people's credit requirements. One such program is Self-help Group Bank Linkage, which is implemented to provide easy microfinance to members of these groups. This paper adopts a qualitative research methodology to discuss the impact of self-help bank linkage programs on sustainable development. This is assessed through a framework of UN’s 17 sustainable development goals. A systematic review has been conducted to determine the effectiveness of this program in attaining these goals in India. The study's results pointed out this program's impact on sustainable development. It has been found to directly and indirectly impact the attainment of many UN sustainable development goals. The study aims to analyze the effectiveness of microfinancing programs in rural India in achieving UN sustainable development goals. Entire rural India is considered for this paper. A qualitative research methodology has been adopted for this paper. Past research work and governmental data have been used to find the impact of self-help bank linkage programs on poverty alleviation. Household incomes have increased, and people have become financially empowered. There is a broader contribution to sustainable development practice and theory with the implementation of this program. People have gained access to better housing, education, clean drinking water, energy and health.