Strengths, Weaknesses, Opportunities and Threats (SWOT) Analysis of Civil Society Organisations for Immunisation in a Nigerian Rural Community.

BACKGROUND AND OBJECTIVE: Immunisation coverage remains sub-optimal, especially in rural hard-to-reach communities in Nigeria. Nigeria's immunisation program suffered set-backs in recent years due to socio-cultural, religious and health system barriers. Grassroots Civil Society Organisations could play a role in addressing some of these barriers with resultant increase in demand for and uptake of immunisation services. The objective of this study was to carry out strengths, weaknesses, opportunities and threats (SWOT) analysis of grassroots civil society organisations regarding engagement for increasing demand for and uptake of immunisation services. SUBJECTS, MATERIALS AND METHODS: This was a qualitative study. A pre-tested SWOT analysis template was used to collect data from 26 grassroots CSOs in Odukpani local government area (LGA) of Cross River State of Nigeria. The data were manually entered into a matrix made up of four quadrants. The results were presented as tables of frequencies and percentages. RESULTS: The CSOs have the numerical strength to carry out immunisation advocacy, communication and social mobilization. There is pool of non-CSO community members who are willing to volunteer. However, some of the CSOs are not good in record keeping. There are also several security threats due to communal clashes. CONCLUSION: There are several strengths and opportunities that the CSOs can leverage on while dealing with identified weaknesses and threats in order to contribute towards increasing the demand for and uptake of immunisation services in this community.

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; ß=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 are associated 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.