Background In case-control studies, population controls can help ensure generalizability; however, the selection of population controls can be challenging in environments that lack population registries. We developed a population enumeration and sampling strategy to facilitate use of population controls in a breast cancer case-control study conducted in Ghana. Methods Household enumeration was conducted in 110 census-defined geographic areas within Ghana’s Ashanti, Central, Eastern, and Greater Accra Regions. A pool of potential controls (women aged 18 to 74 years, never diagnosed with breast cancer) was selected from the enumeration using systematic random sampling and frequency-matched to the anticipated distributions of age and residence among cases. Multiple attempts were made to contact potential controls to assess eligibility and arrange for study participation. To increase participation, we implemented a refusal conversion protocol in which initial non-participants were re-approached after several months. Results 2,528 women were sampled from the enumeration listing, 2,261 (89%) were successfully contacted, and 2,106 were enrolled (overall recruitment of 83%). 170 women were enrolled through refusal conversion. Compared with women enrolled after being first approached, refusal conversion enrollees were younger and less likely to complete the study interview in the study hospital (13% vs. 23%). The most common reasons for non-participation were lack of interest and lack of time. Conclusions Using household enumeration and repeated contacts, we were able to recruit population controls with a high participation rate. Our approach may provide a blue-print for others undertaking epidemiologic studies in populations that lack accessible population registries.
In Sub-Saharan Africa and other developing regions, there has been very little systematic attempt to document the uses and perceived health benefits of urban green spaces in cities and the factors influencing usage. We therefore sought to establish the availability, accessibility and use of urban green spaces, and the perceived health benefits in an African population. We also ascertained the factors influencing use and development of green spaces at home. A population-based survey was conducted in Accra, the capital city of Ghana, spanning 11 Municipal and 3 Sub-Metropolitan areas. Multivariable binary logistic regression adjusting for potential confounders was used to establish the association between green space use and development at home, and socio-demographic, neighbourhood and health factors. Odds ratios and their corresponding 95% confidence intervals were estimated from the models. Several socio-demographic (gender, age, marital status, occupation, ethnicity, religion) and district-level (population density, income level, neighbourhood greenness) factors were associated with use of green spaces and development of green spaces at home in Accra. Residents who were worried about depletion of green spaces in their community were more likely to develop green spaces at home. In neighbourhoods with moderate and high level of greenness, residents were less likely to develop green spaces at home. Five-percent and 47% of green space users in Accra reported witnessing an improvement in their physical and mental health, respectively, from use of green spaces. The study findings can inform policy action for promoting use and development of green spaces in African cities and for mitigating depletion and degradation of the limited urban greenery.
Introduction: Although breast cancer incidence in sub-Saharan African countries, including Ghana, has been historically low, incidence is rising. Evaluating age-specific incidence rates by breast cancer risk factors may provide etiologic insights. Here we present age-specific incidence rates for breast cancer estimated from the Ghana Breast Health Study (GBHS) for key breast cancer risk factors. Methods: GBHS is a population-based case-control study with 1,071 pathologically confirmed incident invasive breast cancer cases (18-74 years old) diagnosed between 2013-2015 in three hospitals in Accra and Kumasi. A total of 2,094 controls were sampled from the population, and frequency matched by site and age to the cases. Sample weights for controls were calculated using data from the 2010 Ghana Census, adjusted for non-response. Data on incident breast cancer cases in Accra (2012-2014) and Kumasi (2013-2015) were obtained from their respective cancer registries and compared to the incidence rates observed in the GBHS. Using data from GBHS adjusted by sampling weights, we estimated 5-year age-specific breast cancer incidence rates and 95% confidence intervals overall and according to breast cancer risk factors. Results: Age-specific breast cancer incidence rates estimated from the GBHS rose quickly until approximately age 50 when the rate plateaued but still rose (Clemmeson's hook), which was consistent with cancer registry data from Kumasi and Accra. The rates from the GBHS are not significantly different from the cancer registry rates under age 50 but are significantly higher after age 50. While the rates from the GBHS and Accra and Kumasi cancer registries were much lower than rates observed in the SEER registries for African American women, the trends were consistent. Analyses of overall rates by breast cancer risk factors showed that age-specific breast cancer risk was elevated among women with a family history of breast cancer across all ages. Data suggested cross-over interactions for other factors, particularly parity, and breastfeeding among parous women. Specifically, incidence rates were higher for parous than nulliparous women aged 20-35 years, while incidence rates were lower for parous and breastfeeding (among parous) women older than 35 years. Conclusions: Age-specific incidence rates of breast cancer that demonstrate cross-over interactions by risk factors may be important in understanding racial disparities in breast cancer incidence, overall as well as for specific breast cancer subtypes. Elevated risk among young parous women may be indicative of the higher risk associated with early-onset (triple-negative) breast cancer. Citation Format: Brittny Davis Lynn, Jonine Figueroa, Richard Biritwum, Beatrice Wiafe Addai, Baffour Awuah, Joe Net Clegg-Lamptey, Robertson Adjei, Lucy Afriyie, Joel Yarney, Naomi Oyoe Ohene Oti, Daniel Ansong, Seth Wiafe, Louise Brinton, Montserrat Garcia-Closas, Barry Graubard. Breast cancer age-specific incidence rates among Ghanaian women by breast cancer risk factors: A study using census and population-based case-control study data [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4636.
Statistical surveys are conducted to estimate population parameters where there are reasons restricting the use of the total population. In practice, there are two different survey strategies (i.e. simple and complex survey designs) to be implemented and the choice of a strategy depends on several factors including the characteristics of the population, the nature of the research questions, etc. However, when the complex survey design is used, standard statistical methods that do not take into account the complex nature of the survey design may lead to inaccurate estimates. In Ghana, living standard surveys are conducted using complex survey design involving stratifications, clustering and estimation of survey weights. In this study, bootstrap resampling methods are used to explore the effect of complex survey design in the analysis of child labour prevalence rate. The relative efficiency of the complex survey design approach was determined by using design effect (deff). Data from the Ghana Living Standard Survey Round 6 (GLSS 6) conducted by the Ghana Statistical Service in 2012 was used for the analysis and the target population was children aged 5-17 years. The results from the simulation study shows that relative efficient estimates are obtained when the complex survey design characteristics are considered in the analysis. Thus, ignoring the characteristics of complex survey design could lead to unrealistic estimates.
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