Prevalence and factors associated with complementary feeding practices among children aged 6-23 months in India: A regional analysis

BMC Public Health, Volume 19, No. 1, Year 2019

Interpretation

Background: Inappropriate complementary feeding practices significantly contribute to undernutrition among children under 2 years of age in India. However, there is limited up-to-date evidence on the prevalence and factors associated with complementary feeding practices to guide policy actions at the subnational level in India. We investigated the regional prevalence and factors associated with complementary feeding practices in India. Methods: This study used a sample of 69,464 maternal responses from the 2015-16 National Family Health Survey in India. The prevalence of complementary feeding indicators was estimated using data for each administrative region, namely: North (n = 8469), South (n = 12,828), East (n = 18,141), West (n = 8940), North-East (n = 2422) and Central (n = 18,664). Factors associated with complementary feeding by region in India were investigated using logistic regression Generalized Linear Latent and Mixed Models (GLLAMM) with a logit link and binomial family that adjusted for clustering and sampling weights. Results: The study showed a wide variation in the prevalence of introduction of solid, semi-solid or soft foods (complementary foods) among infants aged 6-8 months in regional India; highest in the South (61%) and lowest in the Central and Northern regions (38%). Similarly, minimum dietary diversity (MDD) was highest in the South (33%) and lowest in the Central region (12%). Both minimum meal frequency (MMF) and minimum acceptable diet (MAD) varied substantially across the regions. The factors associated with complementary feeding practices also differed across Indian regions. Significant modifiable factors associated with complementary feeding practices included higher household wealth index for the introduction of complementary foods in the North and Eastern India; higher maternal education for MMF and MDD in the North and Central regions; and frequent antenatal care visits (≥4 visits) for all indicators but for different regions. Conclusion: Our study indicates that there are wide differences in regional prevalence and factors associated with complementary feeding practices in India. The improvement of complementary feeding practices in India would require national and sub-national efforts that target vulnerable mothers, including those with no education and limited health service contacts. The overall methodology used in this study has been described elsewhere [12]. Briefly, the present study was based on data from the National Family Health Survey 2015–2016 (NFHS-4, also known as the 2015–16 India DHS) which was conducted by the International Institute for Population Sciences, Mumbai, India. A two-stage sampling design was used in both rural and urban areas, where villages and Census Enumeration Blocks were designated as primary sampling units, respectively. Socio-demographic and household characteristics, as well as infant and young child feeding practices data were collected from a sample of women aged between 15 and 49 years. The response rates across the states and territories of India were high, 94.0% in Andhra Pradesh [8] and West Bengal [9], and 99.6% in Bihar [13]. The survey covered 29 states and 7 union territories in India and included approximately 572,000 Indian households. Further information on the sampling procedure used in the NFHS-4 is provided in the respective India DHS state-level reports [8, 9]. A total of 69,464 maternal responses for children aged 6–23 months were selected for the survey and were assessed based on the WHO specified complementary feeding indicators. The children were from six administrative regions, namely: North (n = 8469), South (n = 12,828), East (n = 18,141), West (n = 8940), Central (n = 18,664) and North East (n = 2422) regions. The northern region consists of Jammu and Kashmir, Himachal Pradesh, Haryana, Delhi, Chandigarh, Punjab and Rajasthan. Southern region consists of Andaman and Nicobar Islands, Andhra Pradesh, Karnataka, Kerala, Lakshadweep, Puducherry, Tamil Nadu and Telangana. Eastern region consists of Bihar, Jharkhand, Odisha and West Bengal. The western region consists of Gujarat, Maharashtra, Goa, Daman and Diu as well as Dadra and Nagar Haveli. The central region consists of Chhattisgarh, Madhya Pradesh, Uttar Pradesh and Uttarakhand. The north-eastern region consists of Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim and Tripura. The distribution of states into regions was performed by the Government of India to facilitate allocation of funds for administrative purposes and improvement of inter-state cooperation [14] and this regional strategy guided our analysis. The assessment of the study outcomes (primary variables) followed the WHO definitions for assessing IYCF indicators in a population [15]. The explanatory variables were categorised into child, maternal, household, health service and community level characteristics for each region. The characteristics of the child included sex, age, the perceived size of the baby at birth, preceding birth interval and birth order of the child. For the mother, the characteristics included maternal age, education/literacy level, employment status, power over earnings, power over household purchases, as well as the type of caste or tribe and religion. For the family or household level characteristics, marital status, household wealth index, and access to media sources like newspapers, radio, and television were considered. The household wealth index was derived from a principal component analysis conducted by the IIPS and ICF International and was calculated as a score of ownership of household assets such as transportation device, ownership of durable goods and household facilities. The IIPS and ICF International classified the household wealth index into five categories (quintiles), and each household was assigned to one of these wealth index categories, namely; poorest, poorer, middle, rich and richest [16]. In addition, data on the number of antenatal care (ANC) visits, place of delivery, access to the type of delivery assistance and mode of delivery were considered as health service factors. At the community level, areas of residence (urban or rural) was considered. The analytical strategy was similar to previously published studies [12, 17, 18]. For this study, preliminary analyses involved the assessment of frequencies and cross-tabulations to calculate the prevalence of complementary feeding practices (i.e., introduction of solid, semi-solid or soft foods, MDD, MMF and MAD) and by the study factors for each geographical region in India. This was followed by an estimation of the prevalence and corresponding confidence intervals of complementary feeding practices by region. Univariable and multivariable logistic regression analyses were conducted to investigate the association between the study variables (child, maternal, household, health service and community factors) and complementary feeding practices using Generalized Linear Latent and Mixed Models (GLLAMM) with a logit link and binomial family that adjusted for clustering and sampling weights. Specifically, a five-stage modelling methodology was used in the multivariable analyses. First, in modelling of child factors, adjustment for maternal, household, health service and community factors was conducted in the assessment of child factors associated with complementary feeding practices by region in India. We used a similar approach for maternal, household, health service and community factors in the third, fourth and fifth stages, respectively. Adjusted odds ratios (aORs) and their corresponding 95% confidence intervals were calculated and reported as the measure of association between the study factors and complementary feeding practices for each Indian region. All analyses were performed in Stata version 14.0 (Stata Corp, College Station, Texas, USA).

AI Digest

Study Justification:

– Inappropriate complementary feeding practices contribute to undernutrition among children under 2 years of age in India.
– Limited up-to-date evidence on the prevalence and factors associated with complementary feeding practices at the subnational level in India.
– Need for policy actions to improve complementary feeding practices in India.

Study Highlights:

– Wide variation in the prevalence of introduction of complementary foods among infants aged 6-8 months in regional India.
– Highest prevalence of introduction of complementary foods in the South region (61%) and lowest in the Central and Northern regions (38%).
– Minimum dietary diversity (MDD) highest in the South (33%) and lowest in the Central region (12%).
– Variation in minimum meal frequency (MMF) and minimum acceptable diet (MAD) across regions.
– Factors associated with complementary feeding practices differ across Indian regions.
– Modifiable factors include household wealth index, maternal education, and antenatal care visits.

Recommendations for Lay Reader and Policy Maker:

– National and sub-national efforts needed to improve complementary feeding practices in India.
– Target vulnerable mothers, including those with no education and limited health service contacts.

Key Role Players:

– Government of India
– Ministry of Health and Family Welfare
– International Institute for Population Sciences
– Indian Council of Medical Research
– Non-governmental organizations (NGOs)
– Community health workers
– Health professionals (doctors, nurses, nutritionists)

Cost Items for Planning Recommendations:

– Training and capacity building for health professionals and community health workers
– Development and dissemination of educational materials for mothers
– Implementation of awareness campaigns
– Monitoring and evaluation systems
– Research and data collection
– Collaboration and coordination between government agencies and NGOs
– Infrastructure and equipment for health facilities
– Support for antenatal care services
Please note that the cost items provided are general categories and not actual cost estimates. The actual cost will depend on the specific interventions and strategies implemented.

Strength of Evidence

N/A

Abstract

The overall methodology used in this study has been described elsewhere [12]. Briefly, the present study was based on data from the National Family Health Survey 2015–2016 (NFHS-4, also known as the 2015–16 India DHS) which was conducted by the International Institute for Population Sciences, Mumbai, India. A two-stage sampling design was used in both rural and urban areas, where villages and Census Enumeration Blocks were designated as primary sampling units, respectively. Socio-demographic and household characteristics, as well as infant and young child feeding practices data were collected from a sample of women aged between 15 and 49 years. The response rates across the states and territories of India were high, 94.0% in Andhra Pradesh [8] and West Bengal [9], and 99.6% in Bihar [13]. The survey covered 29 states and 7 union territories in India and included approximately 572,000 Indian households. Further information on the sampling procedure used in the NFHS-4 is provided in the respective India DHS state-level reports [8, 9]. A total of 69,464 maternal responses for children aged 6–23 months were selected for the survey and were assessed based on the WHO specified complementary feeding indicators. The children were from six administrative regions, namely: North (n = 8469), South (n = 12,828), East (n = 18,141), West (n = 8940), Central (n = 18,664) and North East (n = 2422) regions. The northern region consists of Jammu and Kashmir, Himachal Pradesh, Haryana, Delhi, Chandigarh, Punjab and Rajasthan. Southern region consists of Andaman and Nicobar Islands, Andhra Pradesh, Karnataka, Kerala, Lakshadweep, Puducherry, Tamil Nadu and Telangana. Eastern region consists of Bihar, Jharkhand, Odisha and West Bengal. The western region consists of Gujarat, Maharashtra, Goa, Daman and Diu as well as Dadra and Nagar Haveli. The central region consists of Chhattisgarh, Madhya Pradesh, Uttar Pradesh and Uttarakhand. The north-eastern region consists of Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim and Tripura. The distribution of states into regions was performed by the Government of India to facilitate allocation of funds for administrative purposes and improvement of inter-state cooperation [14] and this regional strategy guided our analysis. The assessment of the study outcomes (primary variables) followed the WHO definitions for assessing IYCF indicators in a population [15]. The explanatory variables were categorised into child, maternal, household, health service and community level characteristics for each region. The characteristics of the child included sex, age, the perceived size of the baby at birth, preceding birth interval and birth order of the child. For the mother, the characteristics included maternal age, education/literacy level, employment status, power over earnings, power over household purchases, as well as the type of caste or tribe and religion. For the family or household level characteristics, marital status, household wealth index, and access to media sources like newspapers, radio, and television were considered. The household wealth index was derived from a principal component analysis conducted by the IIPS and ICF International and was calculated as a score of ownership of household assets such as transportation device, ownership of durable goods and household facilities. The IIPS and ICF International classified the household wealth index into five categories (quintiles), and each household was assigned to one of these wealth index categories, namely; poorest, poorer, middle, rich and richest [16]. In addition, data on the number of antenatal care (ANC) visits, place of delivery, access to the type of delivery assistance and mode of delivery were considered as health service factors. At the community level, areas of residence (urban or rural) was considered. The analytical strategy was similar to previously published studies [12, 17, 18]. For this study, preliminary analyses involved the assessment of frequencies and cross-tabulations to calculate the prevalence of complementary feeding practices (i.e., introduction of solid, semi-solid or soft foods, MDD, MMF and MAD) and by the study factors for each geographical region in India. This was followed by an estimation of the prevalence and corresponding confidence intervals of complementary feeding practices by region. Univariable and multivariable logistic regression analyses were conducted to investigate the association between the study variables (child, maternal, household, health service and community factors) and complementary feeding practices using Generalized Linear Latent and Mixed Models (GLLAMM) with a logit link and binomial family that adjusted for clustering and sampling weights. Specifically, a five-stage modelling methodology was used in the multivariable analyses. First, in modelling of child factors, adjustment for maternal, household, health service and community factors was conducted in the assessment of child factors associated with complementary feeding practices by region in India. We used a similar approach for maternal, household, health service and community factors in the third, fourth and fifth stages, respectively. Adjusted odds ratios (aORs) and their corresponding 95% confidence intervals were calculated and reported as the measure of association between the study factors and complementary feeding practices for each Indian region. All analyses were performed in Stata version 14.0 (Stata Corp, College Station, Texas, USA).

Materials

N/A

Innovations

Based on the provided information, here are some potential innovations that could be used to improve access to maternal health:

1. Mobile Health (mHealth) Applications: Develop and implement mobile applications that provide pregnant women and new mothers with access to information, resources, and support related to maternal health. These apps can offer personalized advice, reminders for prenatal care appointments, nutrition guidance, and breastfeeding support.

2. Telemedicine Services: Establish telemedicine services that allow pregnant women in remote or underserved areas to consult with healthcare professionals remotely. This can help overcome geographical barriers and provide access to prenatal care, monitoring, and guidance without the need for in-person visits.

3. Community Health Workers: Train and deploy community health workers who can provide education, counseling, and support to pregnant women and new mothers in their own communities. These workers can help bridge the gap between healthcare facilities and individuals, ensuring that women receive the necessary care and information.

4. Maternal Health Vouchers: Implement voucher programs that provide pregnant women with financial assistance to access essential maternal health services, such as prenatal care, delivery, and postnatal care. These vouchers can be distributed through community health centers or local organizations to ensure affordability and accessibility.

5. Maternal Health Hotlines: Establish toll-free hotlines staffed by trained healthcare professionals who can provide information, guidance, and support to pregnant women and new mothers. These hotlines can be available 24/7 and offer a confidential platform for women to ask questions and seek advice.

6. Public-Private Partnerships: Foster collaborations between public and private sectors to improve access to maternal health services. This can involve leveraging private healthcare providers, facilities, and resources to expand the reach and availability of maternal health services in underserved areas.

7. Maternal Health Education Programs: Develop and implement comprehensive maternal health education programs that target women, families, and communities. These programs can focus on promoting healthy behaviors, raising awareness about the importance of prenatal care, and addressing cultural or social barriers to accessing maternal health services.

It is important to note that the specific implementation and effectiveness of these innovations may vary depending on the local context and resources available.

AI Innovations Description

The study titled “Prevalence and factors associated with complementary feeding practices among children aged 6-23 months in India: A regional analysis” provides valuable insights into the current state of complementary feeding practices in India and identifies factors associated with these practices. Based on the findings of the study, the following recommendations can be developed into an innovation to improve access to maternal health:

1. Targeted interventions: Develop targeted interventions that focus on vulnerable mothers, especially those with no education and limited health service contacts. These interventions can provide education and support to improve maternal knowledge and practices related to complementary feeding.

2. Regional-specific strategies: Recognize the wide variation in the prevalence of complementary feeding practices across different regions in India. Tailor interventions and strategies to address the specific needs and challenges of each region. This could involve collaborating with local healthcare providers, community leaders, and organizations to implement region-specific programs.

3. Maternal education: Emphasize the importance of maternal education in improving complementary feeding practices. Implement programs that provide accessible and comprehensive education to mothers on the appropriate timing, types, and quantities of complementary foods to be introduced to their infants.

4. Antenatal care: Promote frequent antenatal care visits (≥4 visits) as a means to improve complementary feeding practices. Encourage healthcare providers to include counseling on complementary feeding during antenatal care visits, providing mothers with the necessary information and support.

5. Health service improvements: Strengthen the overall healthcare system to ensure better access to maternal health services. This could involve improving the availability and quality of antenatal care, delivery assistance, and postnatal care services. Additionally, healthcare providers should be trained to provide accurate and up-to-date information on complementary feeding practices.

6. Community engagement: Engage communities in promoting and supporting appropriate complementary feeding practices. This can be achieved through community-based programs, support groups, and awareness campaigns that involve community members, local leaders, and organizations.

By implementing these recommendations, it is possible to develop innovative approaches that address the regional disparities and factors associated with complementary feeding practices in India. This, in turn, can contribute to improving access to maternal health and reducing undernutrition among children under 2 years of age.

AI Innovations Methodology

The study described in the provided text aimed to investigate the prevalence and factors associated with complementary feeding practices among children aged 6-23 months in different regions of India. The methodology used in the study involved analyzing data from the 2015-16 National Family Health Survey in India, which collected information from a sample of 69,464 maternal responses.

The study utilized a two-stage sampling design, where villages and Census Enumeration Blocks were designated as primary sampling units in rural and urban areas, respectively. Socio-demographic and household characteristics, as well as infant and young child feeding practices data, were collected from women aged between 15 and 49 years. The survey covered 29 states and 7 union territories in India, with a high response rate across the states and territories.

To assess the prevalence and factors associated with complementary feeding practices, the study used logistic regression Generalized Linear Latent and Mixed Models (GLLAMM) with a logit link and binomial family. This statistical approach adjusted for clustering and sampling weights. The study analyzed various factors at the child, maternal, household, health service, and community levels to determine their association with complementary feeding practices.

The study’s findings showed wide variations in the prevalence of complementary feeding indicators across different regions of India. Factors associated with complementary feeding practices also differed across regions. The study identified significant modifiable factors, such as household wealth index, maternal education, and antenatal care visits, that were associated with different aspects of complementary feeding practices in specific regions.

In summary, the methodology used in this study involved analyzing data from a large-scale survey to assess the prevalence and factors associated with complementary feeding practices in different regions of India. The study employed logistic regression models and considered various factors at different levels to understand the determinants of complementary feeding practices.

Author

Dima Health

Statistics:

Citations: 45

Identifiers:

DOI: 10.1186/s12889-019-7360-6

Research Areas:

Community Interventions, Disparities, Food Security, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Social Determinants

Study Design:

Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Female