Prevalence and predictors of mother and newborn skin-to-skin contact at birth in Papua New Guinea

BMJ Open, Volume 12, No. 9, Year 2022

Interprétation

Objective This study examined the prevalence and predictors of maternal and newborn skin-to-skin contact at birth in Papua New Guinea. Design Data for the study was extracted from the 2016-18 Papua New Guinea Demographic and Health Survey. We included 6,044 women with birth history before the survey in the analysis. Percentages were used to summarise the prevalence of maternal and newborn skin-to-skin contact. A multivariable multilevel binary logistic regression was adopted to examine the predictors of maternal and newborn skin-to-skin contact. The results were presented using adjusted ORs (aORs), with their respective 95% confidence intervals (CIs). Statistical significance was set at p<0.05. Setting The study was conducted in Papua New Guinea. Participant Mothers with children under 5 years. Outcome measures Mother and newborn skin-to-skin contact. Results The prevalence of mother and newborn skin-to-skin contact was 45.2% (95% CI=42.4 to 48.0). The odds of mother and newborn skin-to-skin contact was higher among women with primary education (aOR=1.38; 95% CI=1.03 to 1.83), women with four or more antenatal care attendance (aOR=1.27; 95% CI=1.01 to 1.61), those who delivered at the health facility (aOR=1.27; 95% CI=1.01 to 1.61), and women from communities with high socioeconomic status (aOR=1.45; 95% CI=1.11 to 1.90). Conclusion The study has demonstrated that the prevalence of mother and newborn skin-to-skin contact in Papua New Guinea is low. Factors shown to be associated with mother and newborn skin-to-skin contact were maternal level of education, antenatal care attendance, health facility delivery, and community socioeconomic status. A concerted effort should be placed in improving maternal health service utilisation such as antenatal care attendance and skilled birth delivery, which subsequently lead to the practice of skin-to-skin contact. Also, women should be empowered through education as it has positive impact on their socioeconomic status and health service utilisation. We performed a secondary analysis of data from the 2016–2018 Papua New Guinea Demographic and Health Survey (DHS). The data for the study was extracted from the Kid’s recode file (KR File) of the DHS. The DHS is a nationally representative survey conducted in over 85 countries worldwide.15 The survey captures data on men, women, and child indicators including SSC.15 The DHS employed a cross-sectional design. Standardised structured interviewer-administered questionnaires were used to collect the data from the respondents. A stratified two-stage cluster sampling design was used to recruit the samples for the survey. In the first stage, clusters were selected using a probability proportional to size sampling technique. In the second stage, a predetermined number of households (usually 28–30) were selected using a systematic sampling technique. The detailed study methodology can be found in the DHS report.16 We included 6,044 women with birth history before the survey who had complete data on all variables of interest in the study. The dataset can be assessed freely at https://dhsprogram.com/data/dataset/Papua-New-Guinea_Standard-DHS_2017.cfm?flag=1.17 Mother and newborn SSC was the outcome variable in the present study. This variable was assessed using the question ‘Was child put on mother’s chest and bare skin after birth?’. With this question, the response options were 0=no; 1=put on chest, touching bare skin; 2=put on chest, no touching of bare skin; 3=put on chest, do not know/missing on touching on bare skin and 8=do not know. For this study’s purpose and with reference to literature,18–20 the response options were further recoded into ‘1=practiced SSC’ for women who response category was “put on chest, touching bare skin” whilst the remaining response options were categorised as ‘0=not practiced SSC’. We included 20 explanatory variables in the study. We selected the variables based on their availability in the DHS dataset as well as their significant association with mother and newborn SSC from literature.18–22 The variables were grouped into individual level and community level. The individual level variables consisted of sex of child, birth order, birth weight, caesarean delivery, type of birth, mother’s age, maternal educational level, marital status, current working status, number of antenatal care visits, place of delivery, health insurance coverage, exposure to watching television, exposure to listening to radio, exposure to reading newspaper or magazine and wealth index. We maintained the existing coding as found in the DHS for sex of child, type of birth, mothers age, caesarean delivery, health insurance coverage, and wealth status. The remaining individual-level variables were coded as birth order (first, second, third, fourth, and fifth or more); birth weight (normal and low birth weight); maternal educational level (no education, primary, and secondary or higher), marital status (never married, married, cohabiting, and previously married); number of antenatal care visits (below four visits and four or more visits); place of delivery (home, health facility, and other); exposure to watching television (no and yes); exposure to listening to radio (no and yes) and exposure to reading newspaper or magazine (no and yes). The DHS devised a wealth index as a proxy measure of socioeconomic position. It was calculated using component rankings derived from principal component analysis on family asset ownership, such as access to drinking water, kind of toilet, type of cooking fuel and possession of a television and refrigerator. The community level variables consisted of place of residence (urban and rural), region (Southern, Highlands, Momase, and Islands), community literacy level (low, medium, and high) and community socioeconomic status (low, medium, and high). We performed the statistical analyses using Stata software V.16.0 (Stata, College Station, Texas, USA). The extracted data was cleaned and all the missing observations were dropped while subcategories of variables with small observations were merged. Percentages were used to present the prevalence of mother and newborn SSC. Later, we examined the distribution of mother and newborn SSC across the explanatory variables using a cross-tabulation. We adopted a binary logistic regression to select significant variables for the multivariable multilevel logistic regression. All the variables that had a p value <0.05 were considered statistically significant and included in the multilevel regression model. Four models of the multilevel regression analysis were built to examine the predictors of mother and newborn SSC. Model O (empty model) was built to examine the variation of the outcome variable (maternal and newborn SSC) attributed to the clustering of the primary sample units. Models I and II were fitted to include variables at the individual and community levels, respectively. The last model (model III) was fitted to include all the statistically significant explanatory variables from the binary logistic regression. The result of the multilevel binary logistic regression analysis was presented using the adjusted ORs (aORs), with their corresponding 95% confidence intervals (CIs). We used the Akaike Information Criterion (AIC) to assess the fitness of each model and for comparing the fitness across the models. All the analyses were weighted. The Stata command ‘svyset’ was employed in all the analyses to adjust for over-and-under sampling, non-response and to improve the generalisability of the findings. In writing the manuscript, we followed the guidelines from the Strengthening the Reporting of Observational Studies in Epidemiology statement (online supplemental table S1).23 bmjopen-2022-062422supp001.pdf Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Résumé de l’IA

Study Justification:

This study aimed to investigate the prevalence and predictors of mother and newborn skin-to-skin contact at birth in Papua New Guinea. The justification for this study is to understand the current status of skin-to-skin contact practices in the country and identify factors that influence its occurrence. This information is crucial for policymakers and healthcare providers to develop targeted interventions and improve maternal and newborn health outcomes.

Study Highlights:

– The prevalence of mother and newborn skin-to-skin contact in Papua New Guinea was found to be 45.2%.
– Factors associated with higher odds of skin-to-skin contact included maternal education, antenatal care attendance, health facility delivery, and community socioeconomic status.
– The study highlights the need to improve maternal health service utilization, such as antenatal care attendance and skilled birth delivery, to promote the practice of skin-to-skin contact.
– Education plays a significant role in empowering women and positively impacting their socioeconomic status and health service utilization.

Recommendations for Lay Readers:

– Efforts should be made to increase the prevalence of mother and newborn skin-to-skin contact in Papua New Guinea.
– Women should be encouraged to attend antenatal care visits and deliver at health facilities to improve the chances of skin-to-skin contact.
– Education plays a crucial role in improving maternal and newborn health outcomes, and efforts should be made to empower women through education.
– Policies and interventions should focus on improving access to and utilization of maternal health services, which can positively impact skin-to-skin contact practices.

Recommendations for Policy Makers:

– Develop and implement policies that promote and support skin-to-skin contact at birth.
– Improve access to and utilization of antenatal care services to ensure that more women receive the necessary information and support for skin-to-skin contact.
– Strengthen the healthcare system to ensure that health facilities are equipped to facilitate skin-to-skin contact and provide appropriate training to healthcare providers.
– Invest in education programs to empower women and improve their socioeconomic status, which can positively impact skin-to-skin contact practices.
– Collaborate with community leaders and stakeholders to raise awareness about the benefits of skin-to-skin contact and promote its practice.

Key Role Players:

– Ministry of Health: Responsible for developing and implementing policies related to maternal and newborn health.
– Healthcare Providers: Involved in providing antenatal care, delivery services, and postnatal care, and play a crucial role in promoting and facilitating skin-to-skin contact.
– Community Leaders: Engage with the community to raise awareness about the importance of skin-to-skin contact and promote its practice.
– Non-Governmental Organizations (NGOs): Collaborate with the government and healthcare providers to implement interventions and programs aimed at improving maternal and newborn health outcomes.

Cost Items for Planning Recommendations:

– Training Programs: Budget for training healthcare providers on the importance of skin-to-skin contact and the proper techniques for facilitating it.
– Equipment and Supplies: Allocate funds for providing necessary equipment and supplies in health facilities to support skin-to-skin contact, such as comfortable chairs or beds for mothers and newborns.
– Education Programs: Invest in educational initiatives targeting women to improve their knowledge and understanding of the benefits of skin-to-skin contact.
– Awareness Campaigns: Allocate funds for community-level awareness campaigns to promote the practice of skin-to-skin contact and raise awareness about its importance.
– Monitoring and Evaluation: Set aside resources for monitoring and evaluating the implementation and impact of interventions aimed at improving skin-to-skin contact practices.

Force de la preuve

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is rated 7 because it is based on a secondary analysis of data from a nationally representative survey. The study methodology is described, including the sample size and statistical analysis. However, the abstract does not provide information on the limitations of the study or potential biases. To improve the evidence, the abstract could include a discussion of the limitations and potential biases, as well as recommendations for future research to address these limitations.

Abstrait

We performed a secondary analysis of data from the 2016–2018 Papua New Guinea Demographic and Health Survey (DHS). The data for the study was extracted from the Kid’s recode file (KR File) of the DHS. The DHS is a nationally representative survey conducted in over 85 countries worldwide.15 The survey captures data on men, women, and child indicators including SSC.15 The DHS employed a cross-sectional design. Standardised structured interviewer-administered questionnaires were used to collect the data from the respondents. A stratified two-stage cluster sampling design was used to recruit the samples for the survey. In the first stage, clusters were selected using a probability proportional to size sampling technique. In the second stage, a predetermined number of households (usually 28–30) were selected using a systematic sampling technique. The detailed study methodology can be found in the DHS report.16 We included 6,044 women with birth history before the survey who had complete data on all variables of interest in the study. The dataset can be assessed freely at https://dhsprogram.com/data/dataset/Papua-New-Guinea_Standard-DHS_2017.cfm?flag=1.17 Mother and newborn SSC was the outcome variable in the present study. This variable was assessed using the question ‘Was child put on mother’s chest and bare skin after birth?’. With this question, the response options were 0=no; 1=put on chest, touching bare skin; 2=put on chest, no touching of bare skin; 3=put on chest, do not know/missing on touching on bare skin and 8=do not know. For this study’s purpose and with reference to literature,18–20 the response options were further recoded into ‘1=practiced SSC’ for women who response category was “put on chest, touching bare skin” whilst the remaining response options were categorised as ‘0=not practiced SSC’. We included 20 explanatory variables in the study. We selected the variables based on their availability in the DHS dataset as well as their significant association with mother and newborn SSC from literature.18–22 The variables were grouped into individual level and community level. The individual level variables consisted of sex of child, birth order, birth weight, caesarean delivery, type of birth, mother’s age, maternal educational level, marital status, current working status, number of antenatal care visits, place of delivery, health insurance coverage, exposure to watching television, exposure to listening to radio, exposure to reading newspaper or magazine and wealth index. We maintained the existing coding as found in the DHS for sex of child, type of birth, mothers age, caesarean delivery, health insurance coverage, and wealth status. The remaining individual-level variables were coded as birth order (first, second, third, fourth, and fifth or more); birth weight (normal and low birth weight); maternal educational level (no education, primary, and secondary or higher), marital status (never married, married, cohabiting, and previously married); number of antenatal care visits (below four visits and four or more visits); place of delivery (home, health facility, and other); exposure to watching television (no and yes); exposure to listening to radio (no and yes) and exposure to reading newspaper or magazine (no and yes). The DHS devised a wealth index as a proxy measure of socioeconomic position. It was calculated using component rankings derived from principal component analysis on family asset ownership, such as access to drinking water, kind of toilet, type of cooking fuel and possession of a television and refrigerator. The community level variables consisted of place of residence (urban and rural), region (Southern, Highlands, Momase, and Islands), community literacy level (low, medium, and high) and community socioeconomic status (low, medium, and high). We performed the statistical analyses using Stata software V.16.0 (Stata, College Station, Texas, USA). The extracted data was cleaned and all the missing observations were dropped while subcategories of variables with small observations were merged. Percentages were used to present the prevalence of mother and newborn SSC. Later, we examined the distribution of mother and newborn SSC across the explanatory variables using a cross-tabulation. We adopted a binary logistic regression to select significant variables for the multivariable multilevel logistic regression. All the variables that had a p value <0.05 were considered statistically significant and included in the multilevel regression model. Four models of the multilevel regression analysis were built to examine the predictors of mother and newborn SSC. Model O (empty model) was built to examine the variation of the outcome variable (maternal and newborn SSC) attributed to the clustering of the primary sample units. Models I and II were fitted to include variables at the individual and community levels, respectively. The last model (model III) was fitted to include all the statistically significant explanatory variables from the binary logistic regression. The result of the multilevel binary logistic regression analysis was presented using the adjusted ORs (aORs), with their corresponding 95% confidence intervals (CIs). We used the Akaike Information Criterion (AIC) to assess the fitness of each model and for comparing the fitness across the models. All the analyses were weighted. The Stata command ‘svyset’ was employed in all the analyses to adjust for over-and-under sampling, non-response and to improve the generalisability of the findings. In writing the manuscript, we followed the guidelines from the Strengthening the Reporting of Observational Studies in Epidemiology statement (online supplemental table S1).23 bmjopen-2022-062422supp001.pdf Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Matériaux

Innovations

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

1. Education and awareness campaigns: Implementing targeted educational programs to raise awareness about the importance of maternal and newborn skin-to-skin contact. This can be done through community health workers, antenatal care clinics, and media channels.

2. Strengthening antenatal care services: Enhancing antenatal care services to ensure that pregnant women receive adequate information and support regarding skin-to-skin contact. This can include training healthcare providers, improving the availability of resources, and promoting early and regular antenatal care visits.

3. Facility-based delivery support: Encouraging and facilitating facility-based deliveries, as they have been associated with higher rates of skin-to-skin contact. This can involve improving the quality of healthcare facilities, ensuring skilled birth attendants are available, and addressing barriers to accessing healthcare facilities.

4. Empowering women through education: Promoting women’s education as it has been shown to positively impact their socioeconomic status and health service utilization. This can be achieved through initiatives that focus on improving access to education, especially for girls and women in marginalized communities.

5. Community engagement and support: Engaging communities in promoting and supporting skin-to-skin contact practices. This can involve community-based interventions, such as peer support groups, community health volunteers, and cultural sensitization programs.

It is important to note that these recommendations are based on the specific context of Papua New Guinea and the findings of the study mentioned. Implementing these innovations would require collaboration between healthcare providers, policymakers, community leaders, and other stakeholders to ensure their effectiveness and sustainability.

AI Innovations Description

Based on the study titled “Prevalence and predictors of mother and newborn skin-to-skin contact at birth in Papua New Guinea,” the following recommendation can be developed into an innovation to improve access to maternal health:

1. Increase awareness and education: Implement educational campaigns to raise awareness among pregnant women and their families about the benefits of skin-to-skin contact at birth. This can be done through community health programs, antenatal care visits, and media platforms.

2. Strengthen antenatal care services: Improve access to and utilization of antenatal care services by providing comprehensive and culturally sensitive care. This includes promoting regular antenatal care visits, providing information on the importance of skin-to-skin contact, and addressing any barriers to accessing care.

3. Enhance facility-based deliveries: Encourage and support women to deliver their babies at health facilities where skilled birth attendants can facilitate immediate skin-to-skin contact. This can be achieved by improving the quality of maternity services, ensuring availability of trained healthcare providers, and addressing any financial or logistical barriers to facility-based deliveries.

4. Empower women through education: Promote women’s education as it has been shown to positively impact their socioeconomic status and health service utilization. This can be done by providing scholarships, vocational training, and adult education programs to empower women and improve their access to maternal health services.

5. Address socioeconomic disparities: Implement strategies to reduce socioeconomic disparities that affect access to maternal health services. This can include targeted interventions to improve access for women from low socioeconomic backgrounds, such as providing financial support for transportation or reducing out-of-pocket expenses for maternal health services.

By implementing these recommendations, it is expected that access to maternal health services, including skin-to-skin contact at birth, can be improved in Papua New Guinea.

AI Innovations Methodology

Based on the provided description, here are some potential recommendations to improve access to maternal health:

1. Increase awareness and education: Implement comprehensive public health campaigns to raise awareness about the importance of maternal health and the benefits of practices such as skin-to-skin contact. This can be done through various channels, including mass media, community outreach programs, and educational materials.

2. Strengthen antenatal care services: Enhance the quality and accessibility of antenatal care services, ensuring that pregnant women receive regular check-ups, counseling, and education on maternal health practices. This can include promoting the benefits of skin-to-skin contact during antenatal visits.

3. Improve access to skilled birth attendants: Increase the availability and utilization of skilled birth attendants, particularly in rural and remote areas. This can be achieved by training and deploying more midwives and other healthcare professionals to provide safe and supportive delivery care.

4. Enhance facility-based deliveries: Encourage and support women to deliver in healthcare facilities rather than at home. This can be done by improving the infrastructure and resources of health facilities, addressing cultural and social barriers, and providing financial incentives or subsidies for facility-based deliveries.

5. Address socioeconomic disparities: Implement strategies to reduce socioeconomic disparities that affect access to maternal health services. This can include initiatives to improve education, income, and employment opportunities for women, as well as targeted interventions to support disadvantaged communities.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could involve the following steps:

1. Define the indicators: Identify specific indicators that reflect access to maternal health, such as the percentage of women receiving antenatal care, the percentage of facility-based deliveries, or the prevalence of skin-to-skin contact.

2. Collect baseline data: Gather existing data on the selected indicators to establish a baseline measurement of access to maternal health. This can be obtained from surveys, health records, or other relevant sources.

3. Define the intervention scenarios: Develop different scenarios that represent the potential impact of the recommendations. For example, one scenario could assume an increase in antenatal care attendance by a certain percentage, while another scenario could assume improved facility infrastructure and resources.

4. Apply the scenarios: Use statistical modeling or simulation techniques to apply the intervention scenarios to the baseline data. This can involve adjusting the relevant indicators based on the assumed changes in the recommendations.

5. Analyze the results: Compare the simulated outcomes of each scenario to the baseline data to assess the potential impact of the recommendations on improving access to maternal health. This can include quantifying changes in the selected indicators and evaluating the statistical significance of the results.

6. Interpret and communicate the findings: Interpret the results of the simulation analysis and communicate the potential benefits of implementing the recommendations. This can involve presenting the findings in a clear and concise manner, highlighting the expected improvements in access to maternal health and the potential implications for maternal and newborn outcomes.

It is important to note that the methodology for simulating the impact of recommendations may vary depending on the available data, resources, and specific context. Therefore, it is recommended to adapt the methodology to suit the specific needs and constraints of the study or program.

Auteurs et co-auteurs

Statistics:

Authors: 7

Identifiers:

DOI: 10.1136/bmjopen-2022-062422

Research Areas:

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

Study Countries:

Guinea

Study Design:

Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Male & Female

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