Exploring the link between women’s financial inclusion and child nutrition in Rulindo district, Rwanda

Abstract

Background

Childhood malnutrition remains a public health concern in Rwanda, with stunting rates at 33%, underweight at 8%, and wasting at 1%. These rates are particularly high in rural areas. As primary caregivers, women play a central role in child nutrition, their financial inclusion may significantly influence child health outcomes. This study investigated the relationship between women’s financial inclusion and the nutritional status of children aged under five in Rulindo District, Rwanda.

Methods

A cross-sectional study was conducted in February 2024 among 315 women with children aged under 5 years. Financial inclusion data were collected using structured questionnaire. Children’s nutritional status was assessed using anthropometric tools. WHO Anthro software, and SPSS version 25.0 were used to analyze the collected data. Bivariate and binary logistic regression analyses were conducted to identify associations between financial inclusion variables and child nutrition outcomes.

Results

Among children, 29.5% were stunted, 7.6% underweight, and 4.1% wasted. Bivariate analysis showed significant associations between financial practices (saving for future use and microfinance membership) and child nutritional status. Women who saved for the future were significantly less likely to have stunted children (p = 0.008) or wasted (p = 0.028). Additionally, microfinance membership was associated with a lower prevalence of stunting (p = 0.07), but a higher risk of underweight (p = 0.035).

Logistic regression confirmed the association: women with stable income had children with lower odds of stunting (Adjusted Odds Ratio [AOR] = 4.039, p = 0.022), and those in microfinance groups were less likely to have stunted children (AOR = 2.587, p = 0.009), but more likely to report underweight (Crude Odd Ratio [COR] = 4.711, p = 0.029). Saving behavior was protective in the crude model, though it was not statistically significant in the adjusted model.

Conclusion

Women’s financial inclusion is positively associated with improved child nutritional outcomes, particularly regarding stunting and wasting. However, financial literacy and targeted support are needed to ensure that economic tools translate into measurable health benefits. Integrated strategies addressing both financial capacity and nutrition education are essential for long-term child health improvement

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-025-24643-7.

Background

Despite significant global progress, child undernutrition remains a persistent public health threat, particularly in low- and middle-income countries (LMICs). Undernutrition in children under five years contributes significantly to mortality, impaired physical growth, cognitive delays, and future diminished economic productivity across the life course [1]. This translates into a vicious cycle of stunted growth, perpetuating poverty across generations. According to the World Health Organization (WHO), global estimates from 2020 reported that 149 million children under the age of 5 were stunted, 45 million were wasted, and 38.9 million children were classified as overweight or obese [2]. Alarmingly, nearly 45% of child deaths in Low and Middle Income Countries(LMICs) are attributed to undernutrition [1]. Sub-Saharan Africa bears a disproportionate burden of undernutrition, with East Africa having the highest stunting rates at 37% [3]. In Rwanda, although progress has been made, child undernutrition remains a concern. The 2019–2020 Rwanda Demographic and Health Survey (RDHS) indicated that 33% of children under five are stunted, 8% are underweight, and 1% are wasted. Rural areas exhibit even higher rates, with 36.7% of children under five stunted, 9.7% underweight, and 6.2% wasted [4]. These urban and rural disparities in child nutrition are echoed in East African Countries. For instance, data from the 2022 Tanzania Demographic and Health Survey shows significant rural-urban differentials in meeting the Minimum Dietary Diversity for Children (MDD-C) aged 5 years and less [5], this may point to the underlaying structural and socioeconomic determinants influencing child feeding practices.

The integration of financial inclusion and child nutrition has gained consideration in global literature. Financial inclusion, like the access to and effective use of financial services such as bank accounts, credit facilities, savings, insurance, and mobile money, has been recognized as a vehicle for economic resilience, especially among women [6]. It is associated with improved food security, better health care access and enhanced household decision making, and enhanced household decision-making power, which are essential for child nutrition [7]. Women’s financial empowerment enables timely purchases of food and healthcare and facilitates investments in preventive and curative services for children.

Rwanda has invested in financial inclusion through strategic policy framework such as Vision 2020 and related development plans. These initiatives have narrowed gender gaps in financial access. According to the 2024 Financial Scope report, 63% of women and 74% of men in Rwanda use formal financial services. Still gaps remain in mobile money use, as well as in borrowing from commercial banks and ownership of formal savings products [8]. Only 3% of women access commercial loans compared to 5% of men, and fewer women own bank accounts(24% versus 29%) [9]. Despite these advancements, women’s financial participation in formal financial institutions remains constrained by low financial literacy, cultural norms, and limited economic opportunities, particularly in rural areas [10]. Moreover, informal saving mechanisms like village or community savings and loan associations (VSLAs), are more accessible to rural women, but may lack the robustness of formally financial tools. These dynamics may have downstream effects on household food security and children’s nutritional outcomes.

While Rwanda has implemented various nutrition policies like the National food and nutrition policy and the integrated child Development Program (ICDP), the integration between these policies and household level regarding economic empowerment, particularly women’s financial inclusion, is underexplored. This study examines how women’s financial inclusion may influence children’s nutritional outcomes in Rulindo district. By exploring both formal and informal financial mechanisms and their linkage to child growth indicators, this study offers practical insights that can be used to inform integrated economic and nutrition policy.

Materials and methods

Study design and setting

A cross-sectional study was conducted in February 2024 in Rulindo District, Rwanda, to assess the relationship between women’s financial inclusion and nutritional status of children aged under five years. Rulindo district was purposively selected due to its high levels of poverty and undernutrition [11]. Within the district, Mbogo sector was randomly chosen as the study site by drawing one paper from a set of 17, each presenting a sector in Rulindo.

Study population, sample determination and sampling process

The study population comprised women residing in Mbogo Sector who had at least one child under the age of five. All four cells of the sector were included to ensure geographic and demographic representation. According to the sector’s data management office, 1,482 women met the inclusion criteria.

The sample was calculated using Taro Yamane’s formula:

[12]

Where: n is the sample size, N = 1,482 is the total eligible population of women

E = 0.05, margin error of at a confidence level of 95%

Then the sample 

To ensure an equitable distribution of the 315 households across the four study cells, the Excel RAND function was used to assign random values, ensuring equitable allocation. As a result, three cells were finally allocated 79 participants each, while one cell received 78 participants. Within each selected household, one eligible woman was randomly chosen. Eligibility was based solely on having a child under five years, regardless of the woman’s access to financial services.

Data collection methods

Data collectors explained the study’s objectives and procedures to participants, before obtaining informed consent. A structured questionnaire was used to collect primary quantitative data. The instrument included sections assessing children’s nutritional status, socio-demographic characteristics, and indicators of women’s financial inclusion. The questionnaire, initially developed in English language, was translated into the local language of Kinyarwanda and digitalized using KoBoCollect for efficient and secure data collection. The questionnaire was also pretested with six women from a neighboring sector to ensure clarity, logical flow and estimated completion time. Anthropometric measurements were taken using portable length boards, Seca 876 - Flat scales, and MUAC tapes. Children’s vaccination cards were reviewed to confirm age. Trained nutritionists collected the data using tablets, with support from local Community Health Workers (CHWs). All data were uploaded daily to the study’s data manager for quality assurance.

Data analysis

Following data collection, data were cleaned, coded, and analyzed using IBM SPSS Statistics version 25.0. Children’s height-for-age, weight for height, and weight-for-age z-scores were calculated using the WHO Anthro software. Malnutrition was defined as follows: Stunting was defined as a height-for-age z-score < −2 standard deviations (SD), Wasting as a weight-for-height z-score <−2 SD, and underweight as a weight-for-age z-score <−2 SD. Descriptive statistics, including frequencies and percentages, were used to summarize the characteristics of the children, women, and financial inclusion variables. Associations between financial inclusion and nutritional status were examined using the Chi-square test. However, the Fisher exact test was applied for variables where more than 20% of cells had expected counts less than 5. Variables with P-values deemed statistically significant (P ≤ 0.05) were further analyzed using binary logistic regression to explore adjusted associations.

Results

Participants’ socio-demographic and financial inclusion characteristics

Among 315 participants, 42.2% (133) were between 25 and 31 years. Most participants, 70.8% (223), were married or partnered, and 66% (208) completed primary education. Additionally, a large majority, 84.8% (267), resided in male-headed households. Agriculture was identified as the primary source of income for 92.4% (291) of participants, with property ownership being common. Only 0.6% (2) reported not having community-based health insurance. Over half, 54.6% (172), had a monthly income between 5,000 and 50,000 Rwandan francs. More than half, 54% (172), held personal bank accounts primarily used for savings related to childcare. While 74.8% (235) of participants knew where to obtain loans, and 64.3% (151) had previously borrowed money, 73.6% (231) were unaware of loans specifically for food purchases. Details of these characteristics of the study population are presented in Table 1.

Table 1.

Socio-demographic and financial inclusion characteristics of the participants (n=315)

Variables	Category	Frequency (n)	Percentage (%)
Socio-demographic
Age of Mothers(years)	18-24	52	16.5
	25-31	133	42.2
	32-38	85	27.0
	>39	45	14.3
Marital Status of participants	Without partner	92	29.2
	With partner	223	70.8
Educational Level	No formal Education	29	9.2
	Primary	208	66.0
	Secondary	72	22.9
	Vocational Training	6	1.9
Disability	Yes	9	2.9
	No	306	97.1
Gender of the Household Head	Female	48	15.2
	Male	267	84.8
Household size (Number of members)	Below 4	163	51.7
	Above 4	152	48.3
Number of children Under 5 years	1-2 children	308	97.8
	3-5 children	7	2.2
Medical Insurance	CBHI*	313	99.4
	RSSB**	2	0.6
Financial Inclusion Characteristics
Source of income	Agriculture	291	92.4
	Small Business	57	18.1
	Monthly Salary/Wages	18	5.7
	Renting Houses	4	1.3
	No income	6	1.9
	Others (Tailoring, Casual labor.)	17	5.4
Estimated Monthly Income (RwF)*	<5,000	126	40.0
	5,001-50,000	172	54.6
	50,001-80,000	10	3.2
	>80,000	7	2.2
Owned Properties	Residential building	273	86.7
	Commercial house	33	10.5
	Land	228	72.4
	Motorcycle	10	3.2
	Bicycle	39	12.4
	None	27	8.6
Bank account Ownership	Yes	170	54.0
	No	145	46.0
Type of bank Account	Self	158	92.3
	Business	2	1.2
	Shared	11	6.5
Financial institution membership	Bank	77	45.3
	Microfinance	60	35.3
	Mobile money networks	96	56.5
	Saving and lending group	79	46.5
	NGOs or trust	8	4.7
Saving for future use	Yes	232	73.9
	No	83	26.1
Savings towards Childcare	Yes	194	84.3
	No	36	15.7
Knows where to obtain loans	Yes	235	74.8
	No	80	25.2
Has taken loan	Yes	151	64.3
	No	84	35.7
Aware of loans for food Purchase	Yes	83	26.4
	No	231	73.6
Motivation for a Loan	Association with Fls	114	36.2
	Low interest	223	70.6
	Flexibility repayment	175	55.6
	Simple Application	104	33.0
	Nearby access	55	17.7
Purpose of Taking Loan	Opening small business	189	60.0
	Buy Foods	152	48.3
	Pay school fees	148	47.0
	Other development	142	45.1
	Others	28	8.9
Taken loan to buy food (Last 12 Months)	Yes	155	49.2
	No	160	50.8
Estimated monthly expense on food (Rwf)	< 10,000	181	57.5
	10,001-50,000	125	39.7
	50,001-100,000	9	2.9
Difficult accessing financial services	Easy	173	54.9
	Medium	132	41.9
	Difficult	10	3.2
Received Financial Inclusion Training	Yes	37	11.7
	No	278	88.3

*Community Based Health Insurance

**Rwanda Social Security Board

Child nutritional status

Table 2 shows that 7.6% (24) of the children were underweight, while 29.5% (93) were stunted, and 4.1% (13) were wasted. The prevalence of underweight among boys was 11.4% (18) and girls was 3.8% (6), while the prevalence of stunting among boys was 33.5% (53) and girls was 25.5% (40), while the prevalence of wasting among boys was 6.3% (10) and girls was 1.9% (3). Regarding age, underweight, stunting and wasting were more prominent in children aged under 24 months with prevalence of 8.5% (17), 30.5% (61), and 4.0% (8) respectively.

Table 2.

Children’s nutritional status per sex and age group in months(n = 315)

Nutritional status	Sex		Age(months)
	Male	Female	< 24	24–47	48–59	Total
Underweight n(%)
Yes	18(11.4)	6(3.8)	17(8.5)	4(4.9)	3(8.8)	24(7.6)
No	140(88.6)	151(96.2)	183(91.5)	77(95.1)	31(91.2)	291(92.4)
Stunted n (%)
Yes	53(33.5)	40(25.5)	61(30.5)	22(27.2)	10(29.4)	93(29.5)
No	105(66.5)	117(74.5)	139(69.5)	59(72.8)	24(70.6)	222(70.5)
Wasted n (%)
Yes	10(6.3)	3(1.9)	8(4.0)	2(2.5)	3(8.8)	13(4.1)
No	148(93.7)	154(98.1)	192(96.0)	79(97.5)	31(91.2)	302(95.9)

Association between socio-demographic factors, women’s financial inclusion and children’s nutritional status

To understand how women’s financial situation impacts children’s nutritional status, we examined the relationship between socioeconomic factors, financial inclusion, and child nutritional status. A significant association was found between additional income sources and child stunting (p = 0.012). Additionally, Women’s participation in microfinance institutions was statistically significantly associated with stunting (p = 0.007) and underweight (p = 0.035) and the practice of saving for the future was significantly associated with stunting (p = 0.008) and wasting (p = 0.028) (Table 3).

Table 3.

Bivariate Analysis of socio-demographic and financial inclusion characteristics and nutrition status (n=315)

Variables	Characteristics	Underweight (%)		P Values	Stunting (%)		P Values	Wasting (%)		P values
		Underweight	Normal weight		Stunted	Not Stunted		Wasted	Not Wasted
Socio-demographic characteristics and Nutritional Status
Age of respondent(years)	18-24	0(0.0)	52(100.0)	0.103*	15(28.8)	37(71.2)	0.68	2(3.8)	50(96.2)	0.547*
	25-31	12(9.0)	121(91.0)		40(30.1)	93(69.9)		5(3.8)	128(96.2)
	32-38	9(10.6)	76(89.4)		28(32.9)	57(67.1)		6(7.1)	79(92.9)
	>39	3(8.3)	42(91.7)		10(25.0)	36(75.0)		0(0.0)	45(100.0)
Marital Status	Without partner	5(5.4)	87(94.6)	0.37	24(26.1)	68(73.9)	0.42	2(2.2)	90(97.8)	0.36
	With partner	19(8.5)	204(91.5)		69(30.9)	154(69.1)		11(4.9)	212(95.1)
Educational Level	No formal Education	2(6.9)	27(93.1)	0.4	7(24.1)	22(75.9)	0.25	1(3.4)	28(96.6)	0.250*
	Primary	13(6.3)	195(93.8)		56(26.9)	152(73.1)		6(2.9)	202(97.1)
	Secondary	8(11.1)	64(88.9)		28(38.9)	44(61.1)		6(8.3)	66(91.7)
	Vocational Training	1(16.7)	5(83.3)		2(33.3)	4(66.7)		0(0.0)	6(100.0)
Disability	Yes	1(11.1)	8(88.9)	0.34	12(34.2)	23(65.7)	0.56	0(0.0)	35(100.0)	0.38
	No	23(7.5)	283(92.5)		81(28.9)	199(71.1)		13(4.6)	267(95.4)
Head of Household	Yes	3(6.3)	45(93.8)	0.78	11(24.9)	37(77.1)	0.31	1(2.1)	47(97.9)	0.7
	No	21(7.9)	246(92.1)		82(30.7)	185(69.3)		12(4.5)	255(95.5)
Financial Inclusion characteristics and Nutritional Status
Source of income	Agriculture
	No	4(16.7)	20(83.3)	0.1	10(41.7)	14(58.3)	0.24	1(4.2)	23(95.8)	1
	Yes	20(6.9)	271(93.1)		83(28.5)	208(71.5)		12(4.1)	279(95.9)
	Small Business
	No	17(6.6)	241(93.4)	0.17	71(27.5)	187(72.5)	0.11	10(3.9)	248(96.1)	0.71
	Yes	7(12.3)	50(87.7)		22(38.6)	35(61.4)		3(5.3)	54(94.7)
	Salary/Wages
	No	22(7.4)	275(92.6)	0.64	85(28.6)	212(71.4)	0.18	12(4.0)	285(96.0)	1
	Yes	2(11.1)	16(88.9)		8(44.4)	10(55.6)		1(5.6)	17(94.4)
	Renting Houses
	No	24(7.7)	287(92.3)	1.000*	93(29.9)	218(70.1)	0.324*	13(4.2)	298(95.8)	1.000*
	Yes	0(0.0)	4(100.0)		0(0.0)	4(100.0)		0(0.0)	4(100)
	No income
	No	23(7.4)	286(92.6)	0.38	92(29.8)	217(70.2)	0.674*	12(3.9)	297(96.1)	0.23
	Yes	1(16.7)	5(83.3)		1(16.7)	5(83.3)		1(16.7)	5(83.3)
	Others
	No	22(7.4)	276(92.6)	0.63	83(27.9)	215(72.1)	0.01	13(4.1)	285(95.6)	0.63
	Yes	2(11.8)	15(88.2)		10(58.8)	7(41.2)		0(0.0)	17(100.0)
Monthly Income	<5000 rwf	9(7.1)	117(92.9)	0.604*	39(31.0)	87(69.0)	0.781*	5(4.0)	121(96)	1.000*
	5001-50000 rwf	14(8.1)	158(91.9)		49(28.)	123(71.5)		8(4.7)	164(95.3)
	>50000rwf	1(5.9)	16(94.1)		5(29.4)	12(70.6)		0(0)	17(100)
Owned Properties	Residential building
	No	3(7.1)	39(92.9)	1	11(26.2)	31(73.8)	0.72	1(2.4)	41(97.6)	0.71
	Yes	21(7.7)	252(92.3)		82(30.0)	191(70.0)		12(4.4)	261(95.6)
	commercial house
	No	20(7.1)	262(92.9)	0.49	80(28.4)	202(71.6)	0.23	11(3.9)	271(96.1)	0.63
	Yes	4(12.1)	29(87.9)		13(39.4)	20(60.6)		2(6.1)	31(93.9)
	Land
	No	10(11.5)	77(88.5)	0.15	22(25.3)	65(74.7)	0.34	4(4.6)	83(95.4)	1
	Yes	14(6.1)	214(93.9)		71(31.1)	157(68.9)		9(3.9)	219(96.1)
	Moto
	No	24(7.9)	281(92.1)	0.62	90(29.5)	215(70.5)	1	13(4.3)	292(95.7)	1
	Yes	0(0)	10(100)		3(30.0)	7(70.0)		0(0)	10(100)
	bicycle
	No	23(8.3)	253(91.7)	0.33	84(30.4)	192(69.6)	0.36	13(4.7)	263(95.3)	0.24
	Yes	1(2.6)	38(97.4)		9(23.1)	30(76.9)		0(0)	39(100)
	none
	No	22(7.6)	266(92.4)	1	86(29.9)	202(70.1)	0.83	12(4.2)	276(95.8)	1
	Yes	2(7.4)	25(92.6)		7(25.9)	20(74.1)		1(3.7)	26(96.3)
Household size	Below 4	15(9.2)	148(90.8)	0.3	45(27.6)	118(72.4)	0.46	8(4.9)	155(95.1)	0.58
	Above 4	19(8.4)	208(91.6)		48(31.6)	104(68.4)		5(3.3)	147(96.7)
Number of children Under 5years	1_2 children	24(7.8)	284(92.2)	0.66	92(29.9)	216(70.1)	0.678*	13(4.2)	295(95.8)	1
	3-5 children	0(0)	7(100)		1(14.3)	6(85.7)		0(0)	7(100)
Medical Insurance	CBHI**	24(7.7)	289(92.3)	1.000*	92(29.4)	221(70.6)	0.504*	13(4.2)	300(95.8)	1.000*
	RSSB***	0(0)	2(100)		1(50.0)	1(50.0)		0(0)	2(100)
Holding Bank account	Yes	11(6.4)	160(93.6)	0.4	47(27.5)	124(72.5)	0.46	5(2.9)	166(97.1)	0.27
	No	13(9.9)	131(91.0)		46(31.9	98(68.1)		8(5.6)	136(94.4)
Type of Account	Self-Account
	Yes	9(5.7)	150(94.3)	1	41(25.8)	118(74.2)	0.17	5(3.1)	154(96.9)	1.000*
	No	1(9.1)	10(90.9)		5(45.5)	6(54.5)		0(0)	11(100)
	Business Account
	Yes	1(50)	1(50)	0.115*	1(50)	1(50)	0.469*	0(0)	2(100)	1
	No	9(5.4)	159(94.6)		45(26.8)	123(73.2)		5(3.0)	163(97.0)
	Shared Account
	Yes	0(0)	11(100)	0.63	4(36.4)	7(63.6)	0.49	0(0)	11(100)	1.000*
	No	10(6.3)	149(93.7)		42(26.4)	117(73.6)		5(3.1)	154(96.9)
Financial institution membership	Bank
	Yes	4(5.2)	73(94.8)	0.76	19(24.7)	58(75.3)	0.6	3(3.9)	74(96.1)	0.659*
	No	6(6.5)	87(93.5)		27(29.0)	66(71.0)		2(2.20	91(97.8)
	Microfinance
	Yes	7(11.7)	53(88.3)	0.04	24(40)	36(60)	0.01	4(6.7)	56(93.3)	0.053*
	No	3(2.7)	107(97.3)		22(20)	88(80)		1(0.9)	109(99.1)
	Mobile money Networks
	Yes	8(8.3)	88(91.7)	0.19	29(30.2)	67(69.8)	0.3	2(2.1)	94(97.9)	0.654*
	No	2(2.7)	72(97.3)		17(23.0)	57(77.0)		3(4.1)	71(95.9)
	saving and lending group
	Yes	4(5.1)	75(94.9)	0.75	20(25.3)	59(74.7)	0.73	0(0)	79(100)	0.062*
	No	6(6.6)	85(93.4)		26(28.6)	65(71.4)		5(5.5)	86(94.5)
	NGOs/trust
	Yes	0(0)	8(100)	1	4(50)	4(50)	0.21	0(0)	8(100)	1.000*
	No	10(6.2)	152(93.8)		42(25.9)	120(74.1)		5(3.1)	157(96.9)
Saving for future use	Yes	17(7.3)	215(92.7)	0.81	59(25.4)	173(74.6)	0.01	6(2.6)	226(97.4)	0.03
	No	7(8.5)	75(91.5)		34(41.5)	48(58.5)		7(8.5)	75(91.5)
Savings towards Childcare	Yes	16(8.2)	178(91.8)	0.32	53(27.3)	141(72.7)	0.22	4(2.1)	190(97.9)	0.24
	NO	1(2.8)	35(97.2)		6(16.7)	30(83.13)		2(5.9)	34(94.4)
Knowing where to get loan	Yes	19(8.10)	216(91.9)	0.64	70(29.8)	165(70.2)	1	11(4.7)	224(95.3)	0.53
	No	5(6.30	74(93.7)		23(29.1)	56(70.9)		2(2.5)	77(97.5)
Taken loan	Yes	13(8.6)	138(91.4)	0.81	42(27.8)	109(72.2)	0.46	5(3.3)	146(96.7)	0.21
	No	6(7.1)	78(92.9)		28(33.3)	56(66.7)		6(7.1)	78(92.9)
Financial institution offering loan to buy food	Yes	8(9.6)	75(90.4)	0.47	24(28.9)	59(71.1)	0.89	4(4.8)	79(95.2)	0.75
	No	16(6.9)	215(93.1)		69(29.9)	162(70.1)		9(3.9)	222(96.1)
Motivation to Loan	Association with FIS
	Yes	8(7.0)	106(93.0)	0.83	35(30.7)	79(69.3)	0.8	4(3.5)	110(95.5)	0.78
	No	16(8.0)	185(92.0)		58(28.9)	143(71.1)		9(4.5)	192(95.5)
	low interest
	Yes	20(9.0)	203(91.0)	0.17	68(30.5)	155(69.5)	0.59	8(3.6)	215(96.4)	0.53
	No	4(4.3)	88(95.7)		25(27.2)	67(72.8)		5(5.4)	87(94.6)
	Flexibility in Payment
	Yes	14(8.0)	161(92.0)	0.83	54(30.9)	121(69.1)	0.62	10(5.7)	165(94.3)	0.16
	No	10(7.1)	130(92.9)		39(27.9)	109(72.1)		3(2.1)	137(97.9)
	Simple loan Application
	Yes	6(5.8)	98(94.2)	0.5	30(28.8)	74(71.2)	0.9	3(2.9)	101(97.1)	0.56
	No	18(8.5)	193(91.5)		63(29.9)	148(70.1)		10(4.7)	201(95.3)
	Nearby FIS
	Yes	5(9.1)	50(90.9)	0.78	16(29.1)	39(70.9)	1	3(5.5)	52(94.5)	0.71
	No	19(7.3)	241(92.7)		77(29.6)	183(70.4)		10(3.8)	250(96.2)
Purpose of Taking Loan	Opening small business
	Yes	17(9.0)	172(91.0)	0.29	60(31.7)	129(68.3)	0.32	9(4.8)	180(95.2)	0.57
	No	7(5.6)	119(94.4)		33(26.2)	93(73.8)		4(3.2)	122(96.0
	Buying Foods
	Yes	14(9.2)	138(90.8)	0.4	44(28.9)	108(71.1)	0.9	8(5.3)	144(94.7)	0.4
	No	10(6.1)	153(93.9)		49(30.1)	114(69.9)		5(3.1)	158(96.9)
	Paying school fees
	Yes	11(7.4)	137(92.6)	1	45(30.4)	103(69.6)	0.81	6(4.1)	142(95.9)	1
	No	13(7.8)	154(92.2)		48(28.7)	119(71.3)		7(4.2)	160(95.8)
	Other Development Purposes
	Yes	13(9.2)	129(90.8)	0.4	46(32.4)	96(67.6)	0.32	4(2.8)	138(97.2)	0.4
	No	11(6.4)	162(93.6)		47(27.2)	126(72.8)		9(5.2)	164(94.8)
	others
	Yes	2(7.1)	26(92.9)	1	7(25.0)	21(75.0)	0.67	0(0)	28(100)	0.39
	No	22(7.7)	265(92.3)		86(30.0)	201(70.0)		13(4.5)	274(95.5)
Taken Loan Specific to buying food	Yes	12(7.7)	143(92.3)	1	49(31.6)	106(68.4)	0.46	9(5.8)	146(94.2)	0.17
	No	12(7.5)	1448(92.5)		44(27.5)	116(72.5)		4(2.5)	156(97.5)
Information on Accessing Financial	Easy	12(6.9)	161(93.1)	0.51	53(30.6)	120(69.4)	0.76	8(4.6)	165(95.4)	0.86
	Medium	12(9.1)	120(90.9)		38(28.8)	94(71.2)		5(3.8)	127(96.2)
	Difficult	0(0)	10(100)		2(20.0)	8(80)		0(0)	10(100)
Training on Financial Inclusion	Yes	4(10.8)	33(89.2)	0.5	13(35.1)	24(64.9)	0.45	3(8.1)	34(91.9)	0.38
	No	20(7.2)	258(92.8)		80(28.8)	198(71.2)		10(3.6)	268(96.4)

Fis Financial institutions

1450rwf= 1$

*Fisher’s exact test p-value, bolded P value indicates significance level at 5% and below

**Indicated Community Based Health Insurance

***Indicated Rwanda Social Security Board

Multivariate analysis of factors associated with child nutritional status

The factors that were significantly associated with child underweight, stunting, and wasting, such as saving for future use, microfinance and other sources of income as variables, were analyzed in a multivariate analysis. Results of those factors showed that mothers with diverse income sources were more likely to have stunted children (COR: 3.701, p = 0.010), while those saving for the future had a lower risk of stunting (COR: 0.481, p = 0.007). Additionally, not belonging to a microfinance institution increased the risk of stunting (COR: 2.667, p = 0.006); however, it also increased the risk of being underweight (COR: 4.711, p = 0.029). After adjusting for other factors, the positive association between diverse income sources and stunting persisted (AOR: 4.039, p = 0.022). Additionally, microfinance membership on stunting remained significant (AOR: 2.587, p = 0.009). However, the relationship between saving for the future and stunting was no longer significant (AOR: 0.501, p = 0.179) (Table 4).

Table 4.

The results of the binary logistic regression include the crude odds ratio (COR), adjusted odds ratio (AOR), and corresponding 95% confidence intervals

Nutritional status
Variable	Number	NO (%)	No (%)	COR	95%CI		P value	AOR	95%CI		P Value
		stunted	Not stunted		Lower	Upper			Lower	Upper
Others source of income
Yes	93	10(58.8)	7(41.2)	3.701	1.363	10.44	0.01	4.039	1.226	13.311	0.022
No	222	83(27.9)	215(72.1)	1				1
Microfinance membership
Yes	46	22(20)	88(80)	1	1.329	5.351	0.006	1	1.265	5.289	0.009
No	124	24(40)	36(60)	2.667				2.587
Saving for future use
Yes	93	1(2.8)	35(97.2)	0.481	0.284	0.818	0.007	0.501	0.183	1.373	0.179
No	221	16(8.2)	178(91.8)	1				1
		wasted	Not wasted
Saving for future use
Yes	93	1(2.8)	35(97.2)	0.284	0.93	0.873	0.028
No	221	16(8.2)	178(91.8)	1
		Underweight	Normal weight
Microfinance membership
Yes	46	22(20)	88(80)	4.711	1.171	18.95	0.029
No	46	24(40)	36(60)	1

COR crude odds ration, AOR adjusted odds ratio, CI confidence interval

P value indicates a significant level at 5% and below

Discussion

The study demonstrates notable advancements in women’s financial inclusion in Mbogo sector, Rulindo district with 54% of women reporting ownership of bank accounts. A figure that is more than double the national average of 24% [13]. Additionally, 56.5% of participants reported using mobile money platforms, reflecting growing penetration and adoption of digital financial services among women in this rural setting. These findings are consistent with broader trends across Sub-Saharan Africa, where the expansion of mobile money services has played a transformative role in enhancing women’s financial autonomy and access to economic resources [14].

However, despite increased access, the study highlights a persistent gap in financial literacy. Only 11.7% of participants have received training in financial management. This limitation may hinder women’s ability to make informed financial decisions and fully utilize available resources. Recent studies suggest that financial literacy is a crucial enabler of economic empowerment and improved health and nutrition outcomes among households in resource limited settings [10, 15]. Therefore, targeted educational programs are needed to ensure that financial inclusion translates into meaningful improvements in household wellbeing.

The study findings align with previous research emphasizing that access alone is insufficient, financial literacy must accompany financial inclusion to achieve lasting impact [16]. While this study confirms enhanced savings behaviors among financially included women 9735 reported saving), it also raises questions about the causal direction, women with stable income sources maybe more likely to save, rather than savings alone directly improving child nutrition outcomes.

In terms of nutrition, this study found a stunting prevalence of 29.5%, underweight of 7.6%, and wasting of 4.1%. While stunting and underweight figures were slightly below national averages reported in the RDHS 2019–2020, wasting was found to be above the national average [4]. Contrary to national levels, boys were more affected than girls, which align with several recent regional studies suggesting sex-based differences in nutritional vulnerability. Children under 24 months exhibited the highest levels of stunting and underweight, reinforcing the importance of early childhood nutrition interventions. These findings correspond with evaluations of Rwanda’s community nutrition-oriented interventions and programs, including growth monitoring, supplementary feeding and multisectoral programs such as GIKURIRO program, and World Vision’s integrated efforts [17, 18]. While progress is evident, the persistence of malnutrition in vulnerable subgroups calls for the need for strengthened implementation and monitoring, particularly in rural settings like Rulindo.

Importantly, this study revealed a significant association between women’s financial inclusion and children’s nutritional status. Women with diverse and stable income sources were significantly less likely to have stunted children. These findings are consistent with studies in other LMICs, such as Ethiopia and Kenya, where women s economic empowerment has been linked to improved dietary diversity and child growth outcomes [19, 20]. Membership in microfinance institutions was associated with positive and complex outcomes. On the one hand, it was linked to reducing stunting risk, likely due to improved access to capital and income-generating opportunities. On the other hand, it showed an unexpected association with increased risk of being underweight, suggesting that microfinance alone may not guarantee better child nutrition. These mixed findings are met in studies from Ghana and Bangladesh, which suggest that microfinance outcomes depend heavily on how funds are used and whether they are complemented by health and nutrition education [21, 22].

These findings imply that financial inclusion, particularly when coupled with financial literacy and stable income, can serve as a pathway to improving child nutrition. However, interventions should be context specific and integrated with nutrition sensitive approaches. Finally, the sounds an echo of creating or strengthening bonds between economic and public health sectors as they are very essential to translating financial empowerment into measurable nutritional gains.

Limitations

This study relied on self-reported data from 315 women regarding financial inclusion, which may be subject to recall or social desirability bias, potentially limiting the accuracy of reported financial behaviours. In addition, the correctional design restricts the ability to establish causal relationships between women’s financial inclusion and children’s nutritional status. Future research shall address these limitations by using longitudinal or mixed methods designs on increased sample size. Despite the limitations, the study addresses an under-researched but policy-relevant issue. The use of objective anthropometric measurements alongside structured data on financial inclusion provides robust and multidimensional insights. Moreover, the study applied rigorous sampling methods to ensure representativeness and used validated tools which enhanced data quality and reliability.

Conclusion

This study confirms a significant association between women’s financial inclusion and the nutritional status of children under five years in Mbogo sector, Rulindo district, Rwanda. Key indicators of financial inclusion, including income diversity, savings behavior, and microfinance membership, were significantly linked to child nutrition outcomes, particularly stunting. Mothers with stable income sources were significantly less likely to have stunted children, while those participating in microfinance programs were more likely to report both positive (lower stunting) and negative (higher underweight) nutritional outcomes. These findings show a complexity of financial mechanisms and their multifaceted influence on child health. However, financial literacy levels remain low, limiting the full potential of financial services. The study further highlights the importance of early childhood nutrition interventions, especially for children under 24 months, who showed the highest prevalence of stunting and underweight. The broader implication of these findings is the need for integrated strategies that combine financial inclusion with targeted health and nutrition programs. Policies should prioritize financial literacy education, support for income-generating activities, and gender-responsive financial services.

Authors’ contributions

PN was responsible for study design, ethics submissions, and contributed significantly to manuscript writing. ARM assisted with tool adaptation, data collection, analysis, and manuscript preparation. PI organized and led the manuscript writing process, adapted tools, and contributed to the discussion. PNw contributed to writing and the presentation of findings in figures and tables. AN provided writing insights and reviewed the manuscript. DNI supervised data collection and analysis and reviewed the manuscript. FXS provided overall guidance, supervising and reviewing the manuscript for rigor and quality.

Funding

This study did not receive any specific funding from public, commercial, or not-for-profit agencies.

Data availability

The data used for writing this paper is available to whoever needs it for research purposes, it can be accessed by direct contact to authors for promoting transparency, collaboration and advancement of knowledge.

Declarations

Ethics approval and consent to participate

Ethical approval for this study was granted by the University of Rwanda, College of Medicine and Health Sciences Institutional Review Board (IRB) (CMHS/IRB/489/2023). The research was conducted following the ethical principles of the Declaration of Helsinki of October 2013 and the Rwanda National Ethics Committee (RNEC) Standard Operating Procedures of August 2021. Authorization for data collection was obtained from relevant local administrative authorities. Participants received information about the study objectives, significance and procedures. Participation was fully voluntary, and participants were informed of their rights to withdraw at any stage without penalty. Informed consent was obtained from all participants prior to data collection. For individuals who could not read or write, the consent process was verbally explained, and consent was documented using thumbprints, in the presence of a witness chosen by the participant. For children involved in anthropometric assessments, parental consent was obtained.

Consent for publication

All participants provided permission for the anonymous publication of study findings. No identifying personal data were collected.

Competing interests

The authors declare no competing interests.