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The purpose of this study was to determine the factors associated with functionality, a clinical criterion that could predict frailty in the elderly people in a rural context.

This project is a cross-sectional descriptive analysis of 342 adults of age >60 years who are residents of Putumayo province in Colombia. Information regarding demographic characteristics, medical history, health perception and current illness was collected. The Mini-Mental State Examination (MMSE) protocol was used to perform cognitive evaluation; the Yesavage Geriatric Depression Scale was used to establish depressive symptoms; and the Hamilton Rating Scale was used to assess anxiety level. Questionnaire was used to evaluate performance on instrumental activities of daily living that lead to functional independence [daily life questionnaire (DLQ)]. The medical outcomes study scale was used to assess social parameters.

A moderate and negative correlation was found between the DLQ score and age (r = −0.49; 95% CI: −0.57 to −0.47), whereas a positive correlation was found with education (r = 0.17; 95% CI: 0.07–0.27). Older adults with economic independence achieved a higher score in functional performance than those with economic dependence (standardized mean difference = 0.55; 95% CI: 0.33–0.77). This study observed a moderate correlation a moderate correlation between the MMSE cognitive performance (r = 0.56; 95% CI: 0.48−0.63) and the depressive symptomatology of Yesavage Scale (r = −0.36, 95% CI: −0.44 to −0.26). Finally, the structural model determined that age (r = −0.37), economic dependence (r = −0.383) and cognitive state (r = 0.309) determine the functional component.

This study provides empirical support about older adults living in rural contexts, around the functionality variable from a multidimensional approach, highlighting the sociodemographic and cognitive variables. Consequently, the policy of social support in older adults must be oriented toward the development of a range of divergent intervention strategies.

The study deals with the assessment of functionality in the elderly people from an interdisciplinary approach in the rural setting which presents a greater risk of physical and socioeconomic vulnerability. Therefore, the community, the health professionals and the government entities should help implement active aging programs for this population.

Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to improve the prediction accuracy of port cargo throughput and realize the coordinated development of FTZ policymaking and port construction.

Considering the effects of data randomization, this paper proposes a novel self-adaptive grey multivariate prediction model, namely FDCGM(1,N). First, fractional-order accumulative generation operation (AGO) is introduced, which integrates the policy impact effect. Second, the heuristic grey wolf optimization (GWO) algorithm is used to determine the optimal nonlinear parameters. Finally, the novel model is then applied to port scale simulation and forecasting in Tianjin and Fujian where FTZs are situated and compared with three other grey models and two machine learning models.

In the Tianjin and Fujian cases, the new model outperforms the other comparison models, with the least mean absolute percentage error (MAPE) values of 6.07% and 4.16% in the simulation phase, and 6.70% and 1.63% in the forecasting phase, respectively. The results of the comparative analysis find that after the constitution of the FTZs, Tianjin’s port cargo throughput has shown a slow growth trend, and Fujian’s port cargo throughput has exhibited rapid growth. Further, the port cargo throughput of Tianjin and Fujian will maintain a growing trend in the next four years.

The new multivariable grey model can effectively reduce the impact of data randomness on forecasting. Meanwhile, FTZ policy has regional heterogeneity in port development, and the government can take different measures to improve the development of ports.

Under the background of FTZ policy, the new multivariable model can be used to achieve accurate prediction, which is conducive to determining the direction of port development and planning the port layout.