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Background: A consequence of the widespread uptake of anti-retroviral therapy (ART) is that the older South African population will experience an increase in life expectancy, increasing their risk for cardiometabolic diseases (CMD), and its risk factors. The long-term interactions between HIV infection, treatment, and CMD remain to be elucidated in the African population. The HAALSI cohort was established to investigate the impact of these interactions on CMD morbidity and mortality among middle-aged and older adults.Methods: We recruited randomly selected adults aged 40 or older residing in the rural Agincourt sub-district in Mpumalanga Province. In-person interviews were conducted to collect baseline household and socioeconomic data, self-reported health, anthropometric measures, blood pressure, high-sensitivity C-reactive protein (hsCRP), HbA1c, HIV-status, and point-of-care glucose and lipid levels.Results: Five thousand fifty nine persons (46.4% male) were enrolled with a mean age of 61.7 ± 13.06 years. Waist-to-hip ratio was high for men and women (0.92 ± 0.08 vs. 0.89 ± 0.08), with 70% of women and 44% of men being overweight or obese. Blood pressure was similar for men and women with a combined hypertension prevalence of 58.4% and statistically significant increases were observed with increasing age. High total cholesterol prevalence in women was twice that observed for men (8.5 vs. 4.1%). The prevalence of self-reported CMD conditions was higher among women, except for myocardial infarction, and women had a statistically significantly higher prevalence of angina (10.82 vs. 6.97%) using Rose Criteria. The HIV- persons were significantly more likely to have hypertension, diabetes, or be overweight or obese than HIV+ persons. Approximately 56% of the cohort had at least 2 measured or self-reported clinical co-morbidities, with HIV+ persons having a consistently lower prevalence of co-morbidities compared to those without HIV. Absolute 10-year risk cardiovascular risk scores ranged from 7.7-9.7% for women and from 12.5-15.3% for men, depending on the risk score equations used.Conclusions: This cohort has high CMD risk based on both traditional risk factors and novel markers like hsCRP. Longitudinal follow-up of the cohort will allow us to determine the long-term impact of increased lifespan in a population with both high HIV infection and CMD risk. [ABSTRACT FROM AUTHOR]

The use of Global Positioning Systems (GPS) and Geographical Information Systems (GIS) in disease surveys and reporting is becoming increasingly routine, enabling a better understanding of spatial epidemiology and the improvement of surveillance and control strategies. In turn, the greater availability of spatially referenced epidemiological data is driving the rapid expansion of disease mapping and spatial modeling methods, which are becoming increasingly detailed and sophisticated, with rigorous handling of uncertainties. This expansion has, however, not been matched by advancements in the development of spatial datasets of human population distribution that accompany disease maps or spatial models. Where risks are heterogeneous across population groups or space or dependent on transmission between individuals, spatial data on human population distributions and demographic structures are required to estimate infectious disease risks, burdens, and dynamics. The disease impact in terms of morbidity, mortality, and speed of spread varies substantially with demographic profiles, so that identifying the most exposed or affected populations becomes a key aspect of planning and targeting interventions. Subnational breakdowns of population counts by age and sex are routinely collected during national censuses and maintained in finer detail within microcensus data. Moreover, demographic and health surveys continue to collect representative and contemporary samples from clusters of communities in low-income countries where census data may be less detailed and not collected regularly. Together, these freely available datasets form a rich resource for quantifying and understanding the spatial variations in the sizes and distributions of those most at risk of disease in low income regions, yet at present, they remain unconnected data scattered across national statistical offices and websites. In this paper we discuss the deficiencies of existing spatial population datasets and their limitations on epidemiological analyses. We review sources of detailed, contemporary, freely available and relevant spatial demographic data focusing on low income regions where such data are often sparse and highlight the value of incorporating these through a set of examples of their application in disease studies. Moreover, the importance of acknowledging, measuring, and accounting for uncertainty in spatial demographic datasets is outlined. Finally, a strategy for building an open-access database of spatial demographic data that is tailored to epidemiological applications is put forward. [ABSTRACT FROM AUTHOR]

Background: Almost one in five contraceptive users in India uses a temporary method. It is important to understand user profiles and method use patterns for optimal program targeting. This analysis examines differences in demographic characteristics, discontinuation and use patterns of temporary method users among a representative sample of urban women from four cities in Uttar Pradesh, India. Methods: Individual data from a panel of women aged 15–49 were collected in 2010 in Agra, Aligarh, Allahabad, and Gorakhpur and follow-up data from the same women were collected in 2012. A contraceptive calendar was used to collect month-by-month data on contraceptive use, non-use, discontinuation, reason for discontinuation, and pregnancy and birth, covering the approximately two-year period between the baseline and midterm surveys. The analysis sample is 4,023 non-sterilized women in union at baseline. A descriptive comparison is made of socio-demographic characteristics, fertility desires, discontinuation, method switching, and pregnancy outcomes. Reasons for discontinuation are assessed by the order of discontinuation. Results: There were a number of socio-demographic differences between users of temporary methods during the calendar period; by education, wealth, and caste. Notably, women who used only condoms during this time had the most education, were the least likely to be poor, and the least likely to be from a scheduled caste or tribe as compared to users of other temporary methods. Compared to the full sample of women, users of temporary methods during this period were less likely to reside in slum areas. The group of multiple method users was small in comparison to the groups of women using a single method throughout the calendar period. This indicates that there was little method switching between condoms, traditional methods, and other forms of modern methods reported in the calendar. Conclusions: The calendar may not be well-suited to measure coital-dependent contraceptive use (e.g., condoms and traditional methods), as "continuous" monthly use may be overstated. A coital episode-specific data collection tool may produce more accurate records of contraceptive use in such contexts. Research findings also lead to useful programmatic recommendations for addressing unmet need and unintended pregnancies in urban Uttar Pradesh and beyond.