What makes advocacy work? Stakeholders’ voices and insights from prioritisation of maternal and child health programme in Nigeria

Background The Nigerian government introduced and implemented a health programme to improve maternal and child health (MCH) called Subsidy Reinvestment and Empowerment programme for MCH (SURE-P/MCH). It ran from 2012 and ended abruptly in 2015 and was followed by increased advocacy for sustaining the MCH (antenatal, delivery, postnatal and immunization) services as a policy priority. Advocacy is important in allowing social voice, facilitating prioritization, and bringing different forces/actors together. Therefore, the study set out to understand how advocacy works - through understanding what effective advocacy implementation processes comprise and what mechanisms are triggered by which contexts to produce the intended outcomes. Methods The study used a Realist Evaluation design through a mixed quantitative and qualitative methods case study approach. The programme theory (PT) was developed from three substantive social theories (power politics, media influence communication theory, and the three-streams theory of agenda-setting), data and programme design documentation, and subsequently tested. We report information from 22 key informant interviews including national and State policy and law makers, policy implementers, CSOs, Development partners, NGOs, health professional groups, and media practitioners and review of relevant documents on advocacy events post-SURE-P. Results Key advocacy organizations and individuals including health professional groups, the media, civil society organizations, powerful individuals, and policymakers were involved in advocacy activities. The nature of their engagement included organizing workshops, symposiums, town hall meetings, individual meetings, press conferences, demonstrations, and engagements with media. Effective advocacy mechanism involved alliance brokering to increase influence, the media supporting and engaging in advocacy, and the use of champions, influencers, and spouses (Leadership and Elite Gendered Power Dynamics). The key contextual influences which determined the effectiveness of advocacy measures for MCH included the political cycle, availability of evidence on the issue, networking with powerful and interested champions, and alliance building in advocacy. All these enhanced the entrenchment of MCH on the political and financial agenda at the State and Federal levels. Conclusions Our result suggest that advocacy can be a useful tool to bring together different forces by allowing expression of voices and ensuring accountability of different actors including policymakers. In the context of poor health outcomes, interest from policymakers and politicians in MCH, combined with advocacy from key policy actors armed with evidence, can improve prioritization and sustained implementation of MCH services

Walking balance is mediated by muscle strength and bone mineral density in postmenopausal women: an observational study

Background: Depletion of ovarian hormone in postmenopausal women has been associated with changes in the locomotor apparatus that may compromise walking function including muscle atrophy/weakness, weight gain, and bone demineralization. Therefore, handgrip strength (HGS), bone mineral density (BMD) and body composition [percentage body fat mass (%BFM), fat mass (FM), Fat-free mass (FFM) and body mass index (BMI)], may significantly vary and predict WB in postmenopausal women. Consequently, the study sought to 1. Explore body composition, BMD and muscle strength differences between premenopausal and postmenopausal women and 2. Explore how these variables [I.e., body composition, BMD and muscle strength] relate to WB in postmenopausal women. Method: Fifty-one pre-menopausal (35.74 + 1.52) and 50 postmenopausal (53.32 + 2.28) women were selected by convenience sampling and studied. Six explanatory variables (HGS, BMD, %BFM, FFM, BMI and FM) were explored to predict WB in postmenopausal women: Data collected were analyzed using multiple linear regression, ANCOVA, independent t-test and Pearson correlation coefficient at p < 0.05. Result: Postmenopausal women had higher BMI(t = + 1.72; p = 0.04), %BFM(t = + 2.77; p = .003), FM(t = + 1.77; p = 0.04) and lower HGS(t = − 3.05; p = 0.001),compared to the premenopausal women. The predicted main effect of age on HGS was not significant, F(1, 197) = 0.03, p = 0.06, likewise the interaction between age and %BFM, F(1, 197) = 0.02, p = 0.89; unlike the predicted main effect of %BFM, F(1, 197) = 10.34, p = .002, on HGS. HGS was the highest predictor of WB (t = 2.203; β=0.3046) in postmenopausal women and combined with T-score right big toe (Tscorert) to produce R2 = 0.11;F (2, 47)=4.11;p = 0.02 as the best fit for the predictive model. The variance (R2) change was significant from HGS model (R2 = 0.09;p = 0.03) to HGS + Tscorert model (R2 = 0.11;p = 0.02). The regression model equation was therefore given as: WB =5.4805 + 0.1578(HGS) + (− 1.3532) Tscorert. Conclusion: There are differences in body composition suggesting re-compartmentalization of the body, which may adversely impact the (HGS) muscle strength in postmenopausal women. Muscle strength and BMD areassociated with WB, although, only contribute to a marginal amount of the variance for WB. Therefore, other factors in addition to musculoskeletal health are necessary to mitigate fall risk in postmenopausal women

Improving rational treatment of malaria: perceptions and influence of RDTs on prescribing behaviour of health workers in southeast Nigeria.

INTRODUCTION: Developments in rapid diagnostic tests (RDTs) have opened new possibilities for improved remote malaria diagnosis that is independent of microscopic diagnosis. Studies in some settings have tried to assess the influence of RDTs on the prescribing behaviour of health workers, but such information is generally lacking in Nigeria and many parts of sub-Saharan Africa. This study analysed health workers' perceptions of RDTs and their potential influence on their prescribing and treatment practices after their introduction. METHODS: The study was conducted in four health centers in the Enugu East local government of Enugu State, Nigeria. All 32 health workers in the health centers where RDTs were deployed were interviewed by field workers. Information was sought on their perception of symptoms-based, RDT-based, and microscopy-based malaria diagnoses. In addition, prescription analysis was carried out on 400 prescriptions before and 12 months after RDT deployment. RESULTS: The majority of the health workers perceived RDTs to be more effective for malaria diagnosis than microscopy and clinical diagnosis. They also felt that the benefits of RDTs included increased use of RDTs in the facilities and the tendency to prescribe more Artemisinin-based combination therapies (ACTs) and less chloroquine and SP. Some of the health workers experienced some difficulties in the process of using RDT kits. ACTs were prescribed in 74% of RDT-negative results. CONCLUSIONS/SIGNIFICANCE: RDT-supported malaria diagnosis may have led to the overprescription of ACTs, with the drug being prescribed to people with RDT-negative results. However, the prescription of other antimalarial drugs that are not first-line drugs has been reduced. Efforts should be made to encourage health workers to trust RDT results and prescribe ACTs only to those with positive RDT results. In-depth studies are needed to determine why health workers continue to prescribe ACTs in RDT-negative results

Prescription practices of health workers before and after RDT introduction.

<p>Prescription practices of health workers before and after RDT introduction.</p

ACT prescription practices of health workers after RDT introduction.

<p>ACT prescription practices of health workers after RDT introduction.</p

Respondents' perception of different diagnostic methods.

<p>Respondents' perception of different diagnostic methods.</p

Socio-demographic characteristics of the respondents.

<p>Socio-demographic characteristics of the respondents.</p

Prescribing of non-antimalarial drugs by RDT test results.

<p>Prescribing of non-antimalarial drugs by RDT test results.</p