Cost-related medication nonadherence in US adults with asthma: The National Health Interview Survey, 2013-2020.

BACKGROUND: Asthma is a chronic disease that needs long-term control for secondary prevention. Health-related expenditures resulting from asthma are rising in the United States, and medication nonadherence is associated with adverse health outcomes in patients with asthma. OBJECTIVE: To estimate the prevalence and risk factors of cost-related medication nonadherence (CRN) in individuals with asthma in the United States. METHODS: We identified patients aged above or equal to 18 years with a history of asthma in nationally representative cross-sectional data, the National Health Interview Survey 2013 to 2020. Participants were considered to have experienced CRN if at any time in the 12 months they reported skipping doses, taking less medication, or delaying filling a prescription to save money. The weighted prevalence of CRN was estimated overall and by subgroups. Logistic regression was used to identify CRN-related characteristics. RESULTS: Of the 26,539 National Health Interview Survey participants with a history of asthma, 4360 (15.77%; representing 3.92 million of the US population) reported CRN, with 10.12% (weighted 2.51 million) of patients skipping doses to save money, 10.82% (weighted 2.69 million) taking less medication to save money, and 13.35% (weighted 3.31 million) delaying filling a prescription to save money. The subgroups young, women, low income, no health insurance, currently smoking, and with comorbidities had a higher prevalence of CRN. The results of this sensitivity analysis did not differ from the overall results. CONCLUSION: In the United States, 1 in 6 adults with a history of asthma is nonadherence with medications due to costs. Removing financial barriers to accessing medication can improve medication adherence in patients with asthma.

Green-Light Responsive Perylene Bisimides for Atom-Economic Thiol Generation and Click-Ligation.

Novel methylthiophene/benzo[b]thiophene perylene bisimide thiol-precursors that would generate thiols via a green-light-induced (λexc = 530 nm, φre = 0.33) photorearrangement are presented herein. The "no-wash", photoreleased thiols thus enabled a subsequent thiol-ene click ligation with electron-deficient substrates. Moreover, by virtue of the intrinsic fluorescence evolution from the rearrangement of perylene bisimide scaffolds, the whole process of thiol formation could be self-reported, further potentiating themselves with application versatilities.

[Spatial-temporal differentiation and influencing mechanism of green development efficiency in three major urban agglomerations in Zhejiang Province, China.] / 浙江三大城市群绿色发展效率时空分异及影响机理.

Improving the green development efficiency of the three major urban agglomerations in Zhejiang is an important way to faster build the pilot demonstration area of beautiful China. Based on county panel data from 2000 to 2019 of 41 counties (cities) included in the three major urban agglomerations, we combined the super-efficiency SBM model with window analysis to evaluate the efficiency, and used spatial econometric analysis method to study the spatial distribution and the differences in regional difference. Furthermore, the fixed panel fixed effect model was used to explore the differential influencing mechanism. The results showed that green development efficiency of the three major urban agglomerations increased gradually with fluctuations during the study period. The distribution of efficiency values gradually shifted from a situation of 'high in the north and low in the south' to a 'relatively common and coordinated' development in the various regions. There was a significant spatial agglomeration effect in green development efficiency of the three major urban agglomerations, but it presented fluctuating phenomenon among cities which were at the similar level. The average green development efficiency of central Zhejiang urban agglomeration was the highest. The development within the three major urban agglomerations was relatively stable. The annulus Hangzhou Bay urban agglomeration came next, with stable development. The Wenzhou-Taizhou coastal urban agglomeration was the lowest, but the efficiency enhancement was the largest. The increases in population density, along with the proportion of added value of tertiary industry in GDP, per capita industrial added value, local fiscal expenditures, education expenditures and per capita actual use of foreign capital could improve the efficiency of green development. However, the increases in industrial electricity consumption and fixed asset investment in kennels would inhibit the improvement of green development efficiency. The impacts of per capita industrial added value, local fiscal expenditure, education expenditure and per capita actual use of foreign capital on urban agglomerations were heterogeneous among different cities.

Predicting socio-economic levels of urban regions via offline and online indicators.

Predicting the socio-economic level of an urban region is of great significance for governments and city managers when allocating resources and making decisions. However, the current approaches for estimating regional socio-economic levels heavily rely on census data, which demands significant effort in terms of time and money. With the ubiquitous usage of smart phones and the prevalence of mobile applications, massive amounts of data are generated by mobile networks that record people's behaviors. In this paper, we propose a low-cost approach of using humans' online and offline indicators to predict the socio-economic levels of urban regions. The results show that the socio-economic prediction model that is trained using online and offline features extracted from these data achieves a high accuracy over 85%. Notably, online features are showed to be tightly linked with socio-economic development. In environments where censuses are rarely held, our method provides an option for timely and accurate prediction of the economic status of urban regions.