Factors associated with stunting among pre-school children in southern highlands of Tanzania

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Study Justification:
– Stunting is a major public health problem in Africa and is associated with poor child survival and development.
– The study aimed to investigate factors associated with child stunting in three Tanzanian regions (Iringa, Njombe, and Mbeya) where stunting prevalence was high.
Study Highlights:
– The study found that in the younger group (6-23 months), stunting was associated with male sex, maternal absence, and household diet diversity.
– Among older children (24-59 months), stunting was associated with male sex, age of 4 and 5, access to improved water source and functioning water station, and mother breastfeeding.
– Interventions that increase household wealth, improve water and sanitation conditions, and support mothers during pregnancy and lactation should be implemented to reduce stunting.
Study Recommendations:
– Implement interventions to increase household wealth and improve water and sanitation conditions.
– Conduct family planning activities and programs supporting mothers during pregnancy and lactation.
– These interventions can positively affect both newborns and older siblings.
Key Role Players:
– Government of Tanzania
– Ministry of Health
– Non-governmental organizations (NGOs) working in the field of nutrition and child health
– Community health workers
– Local leaders and community members
Cost Items for Planning Recommendations:
– Household wealth-building programs
– Water and sanitation infrastructure improvement projects
– Family planning activities and programs
– Training and capacity building for healthcare providers and community health workers
– Information and education campaigns for mothers and caregivers
– Monitoring and evaluation activities to assess the impact of interventions
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.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong, but there are some areas for improvement. The study design is a cross-sectional survey, which limits the ability to establish causality. However, the study includes a large sample size and uses both descriptive statistics and multivariate logistic regression analyses to identify factors associated with stunting. The study also provides specific odds ratios and confidence intervals for each factor. To improve the evidence, future research could consider using a longitudinal design to establish causal relationships and include more detailed information on the methodology, such as the sampling strategy and data collection procedures.

Background: Stunting is a major public health problem in Africa and is associated with poor child survival and development. We investigate factors associated to child stunting in three Tanzanian regions.Methods: A cross-sectional two-stage cluster sampling survey was conducted among children aged 6-59 months. The sample included 1360 children aged 6-23 months and 1904 children aged 24-59 months. Descriptive statistics and binary and multivariate logistic regression analyses were used.Results: Our main results are: in the younger group, stunting was associated with male sex (adjusted odds ratio [AOR]: 2.17; confidence interval [CI]: 1.52-3.09), maternal absence (AOR: 1.93; CI: 1.21-3.07) and household diet diversity (AOR: 0.61; CI: 0.41-0.92). Among older children, stunting was associated with male sex (AOR: 1.28; CI: 1.00-1.64), age of 4 and 5 (AOR: 0.71; CI: 0.54-0.95; AOR: 0.60; CI: 0.44-0.83), access to improved water source (AOR: 0.70; CI: 0.52-0.93) and to a functioning water station (AOR: 0.63; CI: 0.40-0.98) and mother breastfeeding (AOR: 1.97; CI: 1.18-3.29).Conclusions: Interventions that increase household wealth and improve water and sanitation conditions should be implemented to reduce stunting. Family planning activities and programmes supporting mothers during pregnancy and lactation can positively affect both newborns and older siblings.

The study was conducted in the regions of Iringa, Njombe and Mbeya, where 4.4 million people live, 72% of whom live in rural areas [22]. Although these regions receive the highest rainfall and are Tanzania’s bread baskets, stunting prevalence was 51.3%, 51.5% and 36.0%, respectively, in 2014 [20]. These are the second and the third highest values in Tanzania, well above the national prevalence (34.7%). The study population includes children under 5 in rural and urban households in the three regions. One cross-sectional survey was conducted in each region in November 2013, using a two-stage cluster sampling design. Sixty-three clusters were selected in each region by probability proportional to the size using ENA delta software [23]. Twenty households were chosen in each cluster by random sampling, using a random number table. A complete list of households with children under 5 in each cluster was prepared before the survey date. Households were visited for verification if necessary. Sample size was calculated to detect a 10 percentage point reduction in stunting among children 24–47 months by the end of the project in each region. Power was set at 80%, level of confidence at 95% (one-tailed test), design effect at 1.5 and non-response at 10%. A sample of 501 children in the age group 24–47 months per region was required. A total of 1253 households with children under 5 were targeted in each region to achieve the required sample size. Data were collected using a standardized questionnaire on a digital data gathering (DDG) device, via face-to-face interview with the main caregiver of the child. The following data were collected for anthropometric measurements of all children under 5: sex, age, weight, height and presence of bilateral pitting oedema. Length was taken for children under 24 months in horizontal position; height was taken standing for older children; both to the nearest 0.1 cm with a standard 130-cm height/length board. Weight was measured with an electronic scale to the nearest 0.1 kg. Stunting was defined as height-for-age z-score (HAZ) below −2 SD from the median height of the WHO reference population. Additional data were collected to reflect selected immediate, underlying and basic causes of undernutrition as illustrated in the UNICEF Conceptual Framework [24]. These were regrouped in child characteristics: IYCF practices, occurrence of diseases, supplementation and treatments received; maternal characteristic: nutritional status, pregnancy and breastfeeding status, workload, habits and supplementation during pregnancy and nutritional information received; and household characteristics: water source, sanitation facilities, use of iodized salt, household dietary diversity and farm diversity. When more than one child aged 6–23 months was present in a sampled household, only data from the youngest child were collected. Definition and measurements of variables used in the analysis are presented in Table 1. Definitions and measurement of variables used in the analysis The SMART methodology was used to ensure standardized procedures and tools [28]. After a 6-day training, data collectors had to pass a standardization test to assess accuracy and precision of their anthropometric measurements. The questionnaire was piloted and finalized. Team leaders ensured data quality during data collection. Checks, skip functions and acceptable ranges were pre-established in the DDG devices to reduce mistakes. Implausible anthropometric measurements were defined as  ±6 SD, as per WHO criteria [29]. The analysis of factors associated with stunting was divided by age groups: 6–23 and 24–59 months, and conducted for the entire sample and broken down by region. Baseline sociodemographic and clinical characteristics of the sample were described with simple frequency distribution. Crude associations between stunting and sociodemographic and clinical variables were investigated using Pearson’s chi-square test. A multivariate logistic regression model was constructed to identify factors associated with stunting. Odds ratios (OR), 95% confidence intervals (CI) and p-values were obtained. P-values  <0.05 were considered significant. Sampling weights were applied to ensure the representativeness of the sample at the regional level. The analysis was conducted in STATA IC/12.1 for Windows and SPSS 20.0. Anthropometric indicators were calculated with ENA software. Concern Worldwide routinely conducts nutrition surveys within its programmes, which are not subject to research ethical scrutiny. The organization subscribes to the ethical principles outlined in the Humanitarian Charter [30]. Furthermore, the project protocol and questionnaire were reviewed and approved by the Government of Tanzania and UNICEF. Oral informed consent was obtained by the interviewees. Consent to conduct anthropometric measurement was obtained from a parent or guardian in the local language.

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 mobile applications that provide pregnant women and new mothers with access to information, resources, and support related to maternal health. These apps can provide guidance on prenatal care, nutrition, breastfeeding, and postnatal care.

2. Telemedicine: Implement telemedicine services to enable remote consultations between pregnant women and healthcare providers. This can help overcome geographical barriers and provide access to specialized care for high-risk pregnancies.

3. Community health workers: Train and deploy community health workers who can provide education, support, and basic healthcare services to pregnant women and new mothers in rural areas. These workers can help bridge the gap between communities and formal healthcare systems.

4. Maternal health clinics: Establish dedicated maternal health clinics in underserved areas to provide comprehensive prenatal and postnatal care. These clinics can offer services such as antenatal check-ups, vaccinations, family planning, and breastfeeding support.

5. Maternal health vouchers: Introduce voucher programs that provide pregnant women with access to essential maternal health services, including prenatal care, delivery, and postnatal care. These vouchers can be distributed to vulnerable populations to ensure equitable access to care.

6. Mobile clinics: Set up mobile clinics that travel to remote and underserved areas to provide maternal health services. These clinics can offer prenatal check-ups, vaccinations, and health education to pregnant women who may not have easy access to healthcare facilities.

7. Maternal health awareness campaigns: Launch targeted awareness campaigns to educate communities about the importance of maternal health and the available services. These campaigns can address cultural beliefs, myths, and misconceptions surrounding pregnancy and childbirth.

8. Public-private partnerships: Foster collaborations between public and private sectors to improve access to maternal health services. This can involve leveraging private healthcare providers, pharmaceutical companies, and technology companies to expand access and improve the quality of care.

It is important to note that the specific context and needs of the target population should be considered when implementing these innovations.
AI Innovations Description
Based on the study titled “Factors associated with stunting among pre-school children in southern highlands of Tanzania,” the following recommendation can be developed into an innovation to improve access to maternal health:

1. Implement interventions to increase household wealth: Since household wealth was found to be associated with stunting in younger children, implementing interventions that aim to improve household income and economic opportunities can indirectly improve access to maternal health. These interventions can include income-generating activities, vocational training, and microfinance programs targeted at women.

2. Improve water and sanitation conditions: The study found that access to improved water sources and functioning water stations was associated with reduced stunting in older children. Therefore, investing in infrastructure and programs that improve water and sanitation conditions in communities can contribute to better maternal health outcomes. This can include initiatives such as building water supply systems, promoting hygiene practices, and providing education on safe water handling.

3. Strengthen family planning activities: The study highlighted the importance of family planning in positively affecting both newborns and older siblings. To improve access to maternal health, it is crucial to provide comprehensive family planning services, including access to contraceptives, counseling, and education on reproductive health. This can help women plan their pregnancies and ensure adequate spacing between children, which can have a positive impact on maternal and child health outcomes.

4. Support mothers during pregnancy and lactation: Programs that provide support to mothers during pregnancy and lactation can contribute to improved maternal health and child nutrition. This can include antenatal care services, nutrition counseling, breastfeeding support, and access to prenatal and postnatal healthcare. By prioritizing the well-being of mothers, the overall health of both mothers and children can be improved.

In summary, to improve access to maternal health, it is recommended to implement interventions that increase household wealth, improve water and sanitation conditions, strengthen family planning activities, and support mothers during pregnancy and lactation. These recommendations are based on the findings of the study conducted in the southern highlands of Tanzania.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Increase household wealth: Implement interventions that focus on poverty reduction and income generation to improve the economic status of households. This can help ensure that families have the financial resources to access maternal health services.

2. Improve water and sanitation conditions: Implement initiatives to provide access to improved water sources and functioning water stations. This can help reduce the risk of waterborne diseases and improve overall hygiene, which is crucial for maternal health.

3. Implement family planning activities: Promote and provide access to family planning services to support women in making informed decisions about their reproductive health. This can help reduce unintended pregnancies and improve maternal health outcomes.

4. Support mothers during pregnancy and lactation: Implement programs that provide comprehensive support to pregnant women and lactating mothers, including access to prenatal care, nutrition education, and breastfeeding support. This can positively impact both newborns and older siblings.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Define the indicators: Identify key indicators that reflect access to maternal health, such as the percentage of pregnant women receiving prenatal care, the percentage of births attended by skilled health personnel, and the maternal mortality rate.

2. Collect baseline data: Gather data on the current status of these indicators in the target population. This can be done through surveys, interviews, or existing data sources.

3. Develop a simulation model: Create a mathematical or statistical model that incorporates the identified recommendations and their potential impact on the selected indicators. This model should consider the specific context and characteristics of the population.

4. Input data and run simulations: Input the baseline data into the simulation model and run multiple simulations to estimate the potential impact of the recommendations on the selected indicators. This can be done by varying the parameters related to the recommendations, such as the coverage of interventions or the level of improvement in water and sanitation conditions.

5. Analyze results: Analyze the simulation results to assess the potential impact of the recommendations on improving access to maternal health. This can include comparing the simulated outcomes with the baseline data and identifying the magnitude of change that can be expected.

6. Refine and validate the model: Refine the simulation model based on the analysis of results and feedback from experts in the field. Validate the model by comparing the simulated outcomes with real-world data, if available.

7. Communicate findings: Present the findings of the simulation study in a clear and concise manner, highlighting the potential benefits of implementing the recommended interventions to improve access to maternal health. This can help inform decision-making and resource allocation for maternal health programs and policies.

It is important to note that the methodology described above is a general framework and can be adapted based on the specific context and available data.

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