Driving is important for older people to maintain mobility. In order to reduce age-related functional decline, older drivers may adjust their driving by avoiding difficult situations. One of these situations is driving in adverse weather conditions, such as in the rain, snow, and fog which reduce visual clarity of the road ahead. The upcoming highly automated vehicle (HAV) has the potential supporting older people. However, only limited work has been done to study older drivers' interaction with HAV, especially in adverse weather conditions. This study investigates the effect of age and weather on takeover control performance among drivers from HAV. A driving simulation study with 76 drivers has been implemented. The participants took over the vehicle control from HAV under four weather conditions-clear weather, rain, snow and fog where the time and quality of the takeover control are quantified and measured. Results show age did affect the takeover time and quality. Moreover, adverse weather conditions, especially snow and fog, lead to a longer takeover time and worse takeover quality. The results highlighted that a user-centred design of human-machine interaction would have the potential to facilitate a safe interaction with HAV under the adverse weather for older drivers.

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Chronic obstructive pulmonary disease (COPD) causes substantial burden of disease in developed countries, but there are limited data from Africa. We aimed to estimate the prevalence of COPD in Tanzania and identify the risk factors associated with it.This was a cross-sectional descriptive survey involving adults aged ≥35 years. We collected data on symptoms and risk factors using the Burden of Obstructive Lung Diseases questionnaire. Spirometry was performed and COPD diagnosed based on post-bronchodilator forced expiratory volume in 1 s/forced vital capacity <70%. We also measured indoor and outdoor carbon monoxide (CO) levels.A total of 869 participants (49.1% females) completed the questionnaires. Of these, 57.1% completed post-bronchodilator spirometry. Of the 25.2% ever-smokers, only 5.4% were current smokers. COPD prevalence was estimated at 17.5% (21.7% in males and 12.9% in females). COPD was associated with a history of cough, phlegm production and wheezing. 51.7% of COPD patients reported cough and 85% had mild to moderate airway limitation. Females had a higher rate of exacerbation. Pulmonary tuberculosis (TB) was reported in 10% of patients. Only 1.7% of patients who were diagnosed as COPD had ever received any medication, with only one female COPD patient having received an inhaler. 99.5% of the population used biomass fuels for cooking. The majority of households had CO levels up to 20 ppm.The prevalence of COPD in Tanzania is high, with a peak at a relatively young age and a preponderance in males. A history of TB, cigarette smoking and male sex are important risk factors. Indoor air pollution coupled with use of biomass fuel for cooking and heating may be an important risk factor for developing COPD in rural Tanzania. However, these factors need to be studied further.

Driving is closely linked to older people's mobility and independence. However, age-related functional decline reduces their safe driving abilities and thereby their wellbeing may decline. The rapid development of vehicle automation has the potential to enhance the mobility of older drivers by enabling them to continue driving safer for longer. So far only limited work has been carried out to study older drivers' interaction with highly automated vehicles (HAV). This study investigates the effect of age and level of driving disengagement on the takeover control performance in HAV. A driving simulation study with 76 drivers has been conducted. Results showed that 20 s was sufficient for drivers to take over control from HAV. Older drivers take longer to respond and make decisions than younger drivers. The age effect on some aspects of takeover quality, in terms of operating steering wheel and pedals, is still pronounced. In addition, complete disengagement in driving in HAV leads to a longer takeover time and worse takeover quality, and it affects older drivers more seriously than younger drivers. The results highlight that an age-friendly design of human-machine interaction is important for enhancing the safety and comfort of older drivers when interacting with HAVs.