Association between experiences of intimate partner sexual violence and cigarette smoking among women in union in Papua New Guinea: evidence from a nationally representative survey

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Study Justification:
– Intimate partner sexual violence (IPSV) is a prevalent public health problem globally, including in Papua New Guinea (PNG).
– Limited empirical evidence exists on the association between IPSV and cigarette smoking among women in union in PNG.
– This study aims to examine the prevalence of IPSV and its association with cigarette smoking among women in union in PNG.
Study Highlights:
– The study used data from the first demographic and health survey of PNG conducted between 2016 and 2018.
– A total of 9,943 women aged 15-49 years in intimate unions were included in the study.
– The rates of IPSV and current cigarette smoking were 25.9% and 26.8%, respectively.
– The study found a significant association between IPSV and an elevated risk for cigarette smoking among women in union in PNG.
– Even after controlling for demographic, social, and economic factors, the association between IPSV and cigarette smoking remained statistically significant.
Recommendations for Lay Reader and Policy Maker:
– The study highlights the high rates of IPSV and cigarette smoking among women in union in PNG.
– The findings call for attention from policy-makers and relevant authorities in PNG to address this important association.
– Urgent actions are needed, including counseling, awareness creation, service provision, and program design to minimize cigarette smoking and IPSV among women in union in PNG.
Key Role Players Needed to Address Recommendations:
– Policy-makers and relevant authorities in PNG.
– Public health professionals and researchers.
– Non-governmental organizations (NGOs) working on gender-based violence and tobacco control.
– Healthcare providers and counselors.
Cost Items to Include in Planning the Recommendations:
– Funding for awareness campaigns and educational programs.
– Resources for counseling services and support for survivors of IPSV.
– Training for healthcare providers on addressing IPSV and smoking cessation.
– Research funding for further studies on IPSV and its impact on health outcomes.
– Monitoring and evaluation of interventions to assess their effectiveness.
Please note that the cost items mentioned are general suggestions and may vary based on the specific context and resources available in PNG.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, but there are some areas for improvement. The study used a nationally representative survey with a large sample size, which enhances the generalizability of the findings. The study also employed a robust statistical analysis, including modified Poisson regression models and controlling for relevant confounding variables. However, the abstract could be improved by providing more details on the methodology, such as the specific demographic and socioeconomic variables included in the analysis. Additionally, it would be helpful to mention any limitations or potential biases in the study, as well as suggestions for future research.

Background: Intimate partner sexual violence (IPSV) is a prevalent public health problem affecting millions of people each year globally, particularly in developing countries like Papua New Guinea (PNG). Although over two-thirds of women in PNG are estimated to experience some form of sexual violence in their lifetime, empirical evidence is limited on the association between IPSV and cigarette smoking. Thus, the present study aims to examine the prevalence of IPSV and its association with cigarette smoking among women in union in PNG. Methods: This cross-sectional study used data from the first demographic and health survey of PNG conducted between 2016 and 2018. A total of 9,943 women aged 15–49 years in intimate unions were included in this study. We estimated the relative risk of smoking cigarette using modified Poisson regression models with a robust variance and 95% confidence intervals. Results: The rates of IPSV and current cigarette smoking were 25.9% and 26.8%, respectively. The modified Poisson regression results showed that IPSV was significantly associated with an elevated risk for cigarette smoking. Women with IPSV history were more likely to smoke cigarette relative to their counterparts with no IPSV history (RR: 1.33, 95% CI: 1.18–1.50) in the absence of covariates. After controlling for demographic, social and economic factors, the association between IPSV and cigarette smoking remained statistically significant (RR: 1.24, 95% CI: 1.08–1.42). Conclusions: The rates of IPSV and cigarette smoking among women in union in PNG in the current study were relatively high. Irrespective of diverse demographic, social and economic factors, IPSV was still significantly associated with cigarette smoking among women in union in PNG. The findings presented call the attention of policy-makers and relevant authorities in PNG to an important association that needs to be addressed. Counseling, awareness creation, service provision and program design on IPSV are urgently required to minimize cigarette smoking and IPSV among women in union in PNG.

This cross-sectional study used data from the Papua New Guinea Demography and Health Survey (PNGDHS) conducted from October 2016 to December 2018. This is the first demographic and survey conducted in PNG. The PNGDHS aimed to generate comprehensive data on demographic, maternal and reproductive issues such as fertility, family planning awareness and practices, breastfeeding practices, health behaviors, immunizations, domestic and intimate partner violence, among others. Through the Demographic and Health Survey (DHS) programme, technical support for the execution of the survey was provided by Inner City Fund (ICF), with the financial support of Papua New Guinea Government, Australian Government Department of Foreign Affairs and Trade, the United Nations Population Fund (UNFPA) and UNICEF [13]. The sample for the 2016–18 PNGDHS was nationally representative and covered the entire population that lived in private dwelling units in the country. The survey used the list of census units (CUs) from the 2011 Papua New Guinea National Population and Housing Census as the sampling frame and adopted a probability-based sampling approach. Specifically, a two-stage stratified cluster sampling procedure was followed. The methodology and selection procedure details have been reported in the PNGDHS final report. In summary, each province in the country was stratified into urban and rural areas, yielding 43 sampling strata, except the National Capital District, which has no rural areas. The division paid particular attention to urban–rural variations. Samples of census units were selected independently in each stratum in two stages. In the first stage, sorting the sampling frame within each sampling stratum to achieve implicit stratification and proportional allocation using a probability proportional-to-size selection was done. In the second stage of sampling, a fixed number of 24 households per cluster were selected with an equal probability systematic selection from the newly created household listing, resulting in a total sample size of approximately 19,200 households. To prevent bias, no replacements and no changes of the pre-selected households were allowed in the implementing stages. In cases where a census unit had fewer than 24 households, all households were included in the sample. A total of 17,505 households were selected for the sample, of which 16,754 were occupied. Of the occupied households, 16,021 were successfully interviewed, yielding a response rate of 96%. In the interviewed households, 18,175 women age 15–49 were identified for individual interviews; interviews were completed with 15,198 women, yielding a response rate of 84%. In this present study, the sample comprised 9,943 women who were in union (either married or cohabiting) during the survey. Thus, our analysis used data only on women who were in union during the survey. The data have been archived in the public repository of DHS. The access to the data requires registration which is granted specifically for legitimate research purposes. Consent forms were administered at household and individual levels, in accordance with the Human Subject Protection. The dataset can be accessed at https://dhsprogram.com/data/dataset/Papua-New-Guinea_Standard-DHS_2017.cfm?flag = 0. Current cigarette smoking was the outcome variable in this study. This was measured as having smoked cigarette in the last 24 h before the survey. Women in union were asked the question: Smoked cigarette in the last 24 h? Women in union current smoking status were classified as “No” (0): no current smoking in the last 24 h or “Yes” (1): smoking in the last 24 h. The key explanatory variable in this study was IPSV. This variable was derived from the optional domestic violence module, where questions are based on a modified version of the conflict tactics scale [14, 15]. Questions asked are in relation to physical, sexual or emotional violence experiences. In this study, the focus was on the experience of sexual violence. Three standard items including whether the partner ever physically forced the respondent into unwanted sex; whether the partner ever forced respondent into other unwanted sexual acts and; whether the respondent has been physically forced to perform sexual acts she did not want to were used to generate the experience of intimate partner sexual violence. For each of these items, the responses were ‘never’ ‘often’ ‘sometimes’ and ‘yes, but not in the last 12 months. However, for our analysis purpose, we created a dichotomous variable to represent whether a respondent had experienced sexual violence in the past 12 months. This was done by recoding the following responses: ‘never’ and ‘yes, but not in the last 12 months’ as “No” (0) and ‘yes’, ‘often’ and ‘sometimes’ as “Yes” (1). Theoretically and empirically relevant demographic and socioeconomic variables were included as confounders. In all, we included twenty socioeconomic and demographic variables to adjust for in the modelling. These variables included age, region, religion, place of residence, highest educational level, literacy, marital status, residing with a partner, number of partner’s wives, partner’s age, partner’s education, health insurance cover, internet access, mobile phone ownership, watch television, listen to radio, read newspaper/magazine, occupation and wealth index. The selection of these variables was informed by their statistically significant associations with sexual violence and cigarette smoking in previous studies [1, 2, 4, 16, 17]. (See Table ​Table11 for the details on the coding of the covariates). Background characteristics of respondents Before the analysis, all missing data were removed. Both descriptive (frequencies, percentages, mean and standard deviation) and inferential (chi-square and modified Poisson regression) analytical frameworks embedded in STATA software version 13.0 (StataCorp LP, College Station, Texas, USA) were used. The statistical analysis followed some essential steps. We performed descriptive statistics such as frequencies and percentages to describe the sample. The Pearson’s Chi-square test was done to examine the differences in smoking cigarette by socio-demographic characteristics and IPSV. A modified Poisson regression, adjusting for demographic, social and economic variables, was also performed to model the association between IPSV and cigarette smoking, to estimate the relative risk (RR) of cigarette smoking [18, 19]. The study used the modified Poisson regression that incorporates the robust error variance procedure to optimize the accuracy of the estimates [18], as direct estimates of relative risk produce from modified Poisson regression modelling may be a preferred method for estimating population-level risk [19]. We fitted four regression models. Model 1 included dependent and independent variables only; thus, was the base model. While adjusting for the theoretically relevant confounding variables, Models 2, 3 and 4, respectively introduced demographic and socioeconomic factors to investigate whether these variables play any role and might tamper the effects of IPSV on cigarette smoking. Before the regression analysis, diagnostics checks for multicollinearity were conducted using the variance inflation factor (VIF). In this analysis, none of the VIF scores exceeded the value of 2.38, suggesting no multicollinearity. The results of the regression analyses were presented as crude relative risk (CRR) and adjusted relative risk (ARR) at 95% confidence intervals (CIs). All the estimates provided in this study are derived by applying appropriate sampling weights supplied by PNGDHS, 2016–18. A statistical significance threshold of p ≤ 0.05 was selected.

The study mentioned focuses on the association between experiences of intimate partner sexual violence (IPSV) and cigarette smoking among women in union in Papua New Guinea (PNG). The study used data from the first demographic and health survey of PNG conducted between 2016 and 2018. The key findings of the study include:

1. Rates of IPSV and current cigarette smoking among women in union in PNG were relatively high, with IPSV prevalence at 25.9% and cigarette smoking prevalence at 26.8%.

2. The study found a significant association between IPSV and an elevated risk for cigarette smoking. Women with a history of IPSV were more likely to smoke cigarettes compared to those without a history of IPSV.

3. Even after controlling for demographic, social, and economic factors, the association between IPSV and cigarette smoking remained statistically significant.

Based on these findings, potential recommendations to improve access to maternal health and address the association between IPSV and cigarette smoking among women in union in PNG could include:

1. Strengthening counseling services: Providing comprehensive counseling services that address the psychological and emotional impact of IPSV can help women cope with trauma and reduce the likelihood of engaging in harmful behaviors such as smoking.

2. Increasing awareness: Conducting awareness campaigns to educate women, their partners, and the community about the negative consequences of IPSV and the link between IPSV and cigarette smoking can help raise awareness and promote behavior change.

3. Enhancing service provision: Ensuring that healthcare facilities have the necessary resources and trained staff to provide support and assistance to women who have experienced IPSV. This includes offering specialized services for survivors of IPSV, such as trauma-informed care and access to mental health support.

4. Developing targeted programs: Designing programs specifically tailored to address the needs of women in union who have experienced IPSV. These programs can include interventions aimed at reducing smoking rates, promoting healthy coping mechanisms, and empowering women to seek help and support.

It is important to note that these recommendations are based on the findings of the study and should be implemented in conjunction with existing efforts to improve maternal health and address gender-based violence in PNG.
AI Innovations Description
The study mentioned in the description aims to examine the association between intimate partner sexual violence (IPSV) and cigarette smoking among women in union in Papua New Guinea (PNG). The study found that both IPSV and cigarette smoking rates were relatively high among women in union in PNG. The results showed a significant association between IPSV and an elevated risk for cigarette smoking. Women with a history of IPSV were more likely to smoke cigarettes compared to those without a history of IPSV. This association remained statistically significant even after controlling for demographic, social, and economic factors.

Based on these findings, the study recommends several actions to improve access to maternal health and address the association between IPSV and cigarette smoking among women in union in PNG. These recommendations include:

1. Counseling: Providing counseling services to women who have experienced IPSV can help them cope with the trauma and reduce the likelihood of engaging in harmful behaviors such as smoking.

2. Awareness creation: Raising awareness about the link between IPSV and cigarette smoking is crucial. Educational campaigns can help women understand the potential health risks associated with smoking and the importance of seeking support to address IPSV.

3. Service provision: Ensuring access to comprehensive healthcare services, including reproductive and maternal health services, can contribute to the overall well-being of women in union. This includes providing support for smoking cessation and addressing the underlying factors contributing to IPSV.

4. Program design: Developing targeted programs that address IPSV and smoking cessation specifically for women in union can be effective. These programs should consider the unique needs and challenges faced by this population and provide tailored support.

By implementing these recommendations, policymakers and relevant authorities in PNG can work towards minimizing cigarette smoking and IPSV among women in union, ultimately improving access to maternal health and overall well-being.
AI Innovations Methodology
The study you provided focuses on the association between intimate partner sexual violence (IPSV) and cigarette smoking among women in union in Papua New Guinea (PNG). To improve access to maternal health in PNG, here are some potential recommendations:

1. Strengthening healthcare infrastructure: Invest in improving healthcare facilities, including maternal health clinics and hospitals, especially in rural and remote areas. This will ensure that women have access to quality maternal healthcare services.

2. Enhancing healthcare workforce: Increase the number of skilled healthcare professionals, such as doctors, nurses, midwives, and community health workers, to provide comprehensive maternal health services. This can be achieved through training programs, incentives, and recruitment drives.

3. Promoting community-based interventions: Implement community-based programs that focus on raising awareness about maternal health, providing education on pregnancy and childbirth, and promoting healthy behaviors. These interventions can be delivered through community health workers, local leaders, and community organizations.

4. Improving transportation and logistics: Address transportation barriers by improving road infrastructure, providing ambulances or other means of transportation for pregnant women, and ensuring the availability of emergency obstetric care facilities within a reasonable distance.

5. Strengthening health information systems: Develop and implement robust health information systems to collect, analyze, and disseminate data on maternal health indicators. This will enable policymakers and healthcare providers to make evidence-based decisions and monitor progress.

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

1. Baseline data collection: Gather data on key maternal health indicators, such as maternal mortality rate, antenatal care coverage, skilled birth attendance, and access to emergency obstetric care. This data will serve as a baseline for comparison.

2. Define simulation parameters: Determine the specific parameters to be simulated, such as the increase in healthcare infrastructure, the number of additional healthcare professionals, the coverage of community-based interventions, and improvements in transportation and logistics.

3. Model development: Develop a simulation model that incorporates the baseline data and the defined parameters. This model should consider the interdependencies between different factors and their impact on maternal health outcomes.

4. Data input and scenario testing: Input the defined parameters into the simulation model and test different scenarios to assess their potential impact on improving access to maternal health. This could involve adjusting the parameters individually or in combination to evaluate their cumulative effect.

5. Analysis and interpretation: Analyze the simulation results to understand the potential impact of the recommended interventions on maternal health outcomes. This could include assessing changes in maternal mortality rate, antenatal care coverage, skilled birth attendance, and access to emergency obstetric care.

6. Sensitivity analysis: Conduct sensitivity analysis to assess the robustness of the simulation results by varying the input parameters within a certain range. This will help identify the most influential factors and potential limitations of the simulation model.

7. Policy recommendations: Based on the simulation results, provide evidence-based policy recommendations to stakeholders, policymakers, and healthcare providers. These recommendations should prioritize the interventions that have the greatest potential for improving access to maternal health in PNG.

It is important to note that the methodology for simulating the impact of recommendations on improving access to maternal health may vary depending on the specific context and available data. The steps outlined above provide a general framework for conducting such simulations.

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