Rural–Urban Differences in Common Mental Disorders, Functional Limitation and Social Support among Adults with Cancer: A Population-Based Study in Spain

Citation: Portero de la Cruz, S.; Cebrino, J. Rural–Urban Differences in Common Mental Disorders, Functional Limitation and Social Support among Adults with Cancer: A Population-Based Study in Spain. J. Clin. Med. 2022,11, 2742. https:// doi.org/10.3390/jcm11102742 Academic Editor: Aristeidis H. Katsanos Received: 2 March 2022 Accepted: 10 May 2022 Published: 12 May 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Journal of Clinical Medicine Article Rural–Urban Differences in Common Mental Disorders, Functional Limitation and Social Support among Adults with Cancer: A Population-Based Study in Spain Silvia Portero de la Cruz 1,2 and Jesús Cebrino 3,* 1Department of Nursing, Pharmacology and Physiotherapy, Faculty of Medicine and Nursing, University of Córdoba, Avda. Menéndez Pidal, S/N, 14071 Córdoba, Spain; [email protected] 2Research Group GC12 Clinical and Epidemiological Research in Primary Care, Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Hospital Universitario Reina Sofía, 14071 Córdoba, Spain 3Department of Preventive Medicine and Public Health, Faculty of Medicine, University of Seville, Avda. Doctor Fedriani, S/N, 41009 Seville, Spain *Correspondence: [email protected]; Tel.: +34-954-551-771 Abstract: The psychological, physical and social well-being components may differ for cancer patients living in urban vs. rural zones. This study aimed to examine the common mental disorders (CMDs), functional limitation (FL) and perceived social support (PSS) of rural and urban Spanish cancer patients from 2006 to 2017, to compare sociodemographic variables, health-related determinants and use of healthcare resources and to identify which sociodemographic and health-related factors were related to CMDs, FL and PSS. We performed a cross-sectional study among cancer patients using data from the Spanish National Health Surveys (2006, 2011 and 2017). A total of 698 of the subjects resided in rural areas and 1824 in urban areas. Binary logistic and multiple linear regressions were performed to determine the factors related to CMDs, FL and PSS. Rural residents visited their general practitioners more frequently than the city dwellers (61.03% vs. 56.63%, p = 0.04). A decreased prevalence of CMDs was observed among urban individuals over time (2006: 39.13%, 2011: 38.87%, 2017: 34.30%; pfor trend = 0.04). Among rural residents, FL was associated with age, educational level and self-perceived health status, while among city dwellers, PSS was linked to marital status, nationality, having chronic conditions and self-perceived health status. Keywords: activities of daily living; cancer survivors; mental disorders; psycho-oncology; social support 1. Introduction The number of cancer survivors is rising worldwide, fueled by advances in early detection and treatment and the aging of the world’s population [ 1 ]. In Spain, between 2002–2007 and 2008–2013, the 5-year net survival rate increased by 3.3% (2002–2007: 52.0% and 2008–2013: 55.3%) for all cancers in men and by 2.6% overall for women (2002–2007: 59.1% and 2008–2013: 61.7%) [2]. Individuals with cancer must cope with the side effects of cancer treatment and how it affects their lives, leading to functional and cognitive impairments as well as other psychological and economic issues [ 3 ]. This has resulted in a growing interest in evaluating these aspects, which may vary in rural and urban areas, in cancer patients [4]. Regarding psychological functioning, cancer patients have an increased risk of mental health disorders compared with healthy populations [ 5 ]. Common mental disorders (CMDs), such as depression and anxiety, affect up to 20% and 10% of people with cancer, respectively [ 6 ]. CMDs in individuals with cancer can lead to negative consequences, including low treatment adherence, decreased survival rate and increased healthcare costs [ 7 ]. Although it has been suggested that urban living might be detrimental to the J. Clin. Med. 2022,11, 2742. https://doi.org/10.3390/jcm11102742 https://www.mdpi.com/journal/jcm J. Clin. Med. 2022,11, 2742 2 of 15 mental health of urban residents [ 8 ], current research on cancer patients suggests that living in a rural residence is related with decreased psychological well-being [9]. On the other hand, it is important to consider the influence of cancer on the ability to carry out daily activities. These activities of daily living are those that people perform in order to live independently within a society and can be divided into basic activities of daily life (e.g., washing or dressing) or more complex activities named as instrumental activities of daily living (e.g., shopping or using public transportation) [ 10 ]. Cancer has a significant impact on activities of daily living, as between 37% and 55% of cancer patients report having experienced difficulties or requiring assistance to complete activities of daily living [ 11 ]. Functional limitation (FL) in these activities influences decision making over treatments, as colorectal cancer patients who require assistance to perform at least two or more activities of daily living are 35% to 40% less likely to receive chemotherapy [ 12 , 13 ]. Moreover, higher mortality rates have been found in colorectal cancer individuals with two or more FLs [ 12 ]. Nevertheless, the functional status may be different in rural and urban areas. In this context, urban–rural differences have been reported in social and economic determinants of health, mental health issues and infrastructure and service delivery, with increased issues with transportation and providing healthcare services [ 14 ], all of which can affect the functional status of individuals with cancer. Another essential factor to emphasize is well-being. In the case of cancer patients, a greater level of perceived social support (PSS), defined as the satisfaction gained by receiving assistance from members of a social network [ 15 ], is related with a higher experience of well-being [ 16 ] and plays an important role in coping with the disease and in improving quality of life [ 15 ]. PSS is also beneficial for the immune system in individuals with cancer, and those individuals with social support live approximately twice as long as those without such support [ 17 ]. A previous study has suggested that rural dwellers experience stronger social support than their urban counterparts [18]. Spanish studies have shown some factors affecting psychological, physical and social dimensions in cancer patients. For example, having a low socioeconomic status seems to have a clearly negative influence on physical, mental and social health in people with cancer [ 19 ]. In addition, there is evidence of a high prevalence of comorbid chronic conditions [ 20 ] and risk-promoting behavior, such as smoking, in Spanish cancer patients [ 21 ], all of which also have a negative influence on quality of life [22]. The evaluation of psychological, physical and social dimensions is relevant and should be part of the routine clinical analysis of cancer survivors at critical moments, such as receiving treatment and routine follow-up visits [ 23 ]. Taking this into account, it is important to examine these components according to place of residence, since they may differ in individuals with cancer living in rural and urban areas. Moreover, currently, there is very little research in Spain considering the geographical location. On the other hand, identifying the sociodemographic and health-related predictors involved is crucial, so that prompt, efficient interventions can be adapted or redesigned to take into account both these contributors and the residential location in order to improve quality of life in populations with cancer. This study, which used a large, representative and national dataset of Spanish individuals with cancer, aimed to examine the presence of CMDs, FL and PSS in rural and urban Spanish individuals with cancer aged ≥ 18 years from 2006 to 2017. The objective was to compare sociodemographic variables, health-related determinants and use of healthcare resources in those individuals according to the residential location and to identify which sociodemographic and health-related factors were related to CMDs, FL and PSS among urban and rural individuals with cancer. 2. Materials and Methods We conducted a cross-sectional study using individualized data from the Spanish National Health Surveys (SNHS) performed in 2006 [ 24 ], 2011 [ 25 ] and 2017 [ 26 ] and J. Clin. Med. 2022,11, 2742 3 of 15 conducted by the Ministry of Health, Consumer Affairs and Social Welfare and the National Institute of Statistics. 2.1. Data Source The SNHS are conducted on a representative sample of Spanish population. The sample approach used a multistage cluster, with the census as the primary unit, households as the secondary unit and household members as the tertiary unit. An adult from each household was randomly chosen to complete the survey and was mailed the reasons for the questionnaire, as well as the character and anonymity of participation. The interviews were conducted by an approved interviewer. 2.2. Study Participants All people aged ≥ 18 years old were selected. Those who answered “yes” to the query, “Has your doctor told you that you are currently suffering from a malign tumor?” were identified as individuals with cancer. The sample initially comprised 2853 individuals with cancer (SNSH 2006: n= 965; SNSH 2011: n= 741; SNHS 2017: n= 1147), of whom 331 subjects (11.60%) were subsequently excluded due to refusal to answer the questions (SNSH 2006: n= 130; SNSH 2011: n= 109; SNHS 2017: n= 92), although their characteristics were similar to the other cancer subjects included. Finally, the total sample was composed of 2522 individuals: 835 in SNHS 2006; 632 in SNHS 2011; and 1055 in SNHS 2017. The sample was stratified, in terms of the rural/urban nature of their place of residence, by the number of inhabitants, as follows: rural towns (<10,000 inhabitants) and urban towns/cities (≥10,000 inhabitants) [27]. 2.3. Study Variables The variables were based on questions included in the questionnaires which were identical in all the surveys. The outcome variables in this study were the presence of CMDs, FL and PSS, which were assessed as follows. CMDs. The 12-item General Health Questionnaire (GHQ-12) [ 28 ] validated in Spain [ 29 , 30 ] was used to identify them. The GHQ-12 has four possible answers, with the first two responses denoting the non-existence of a specific symptom (“0” points) and the last two revealing the existence of a symptom (“1” point) [ 31 ]. The total score ranges from 0 to 12 points, and the scores obtained for each item are added together. We set the cut-off point at ≥ 3 points, establishing the absence of CMDs by scores <3 points and their existence by scores ≥ 3 points, the latter being used to indicate the risk of psychological distress [31]. FL. This variable was investigated by using questions about different physical tasks in two functional domains [ 32 , 33 ]: (i) basic activities of daily life (e.g., personal hygiene or dressing); (ii) instrumental activities of daily life (e.g., food preparation or housekeeping). The difficulty level for each task was rated as: “I can do it by myself”, “I can do it with someone’s help” or “I am unable to do it at all”. When individuals replied “I can do it with someone’s help” or “I am unable to do it at all” in at least one item for a specific domain of FL, we identified the presence of FL. PSS. This was measured using the Duke-UNC-11 questionnaire [ 34 ], validated in Spain [ 35 , 36 ]. This questionnaire includes 11 statements that assess the areas of social support as confident, emotional and instrumental support. It is scored using a 5-category Likert scale, with 1 being “far less than I would like” and 5 being “as much as I would like”. The larger the score, the greater the PSS. An overall score is calculated by summing all of the replies, which, in our study, ranged from 11 to 55 points. The independent variables were classified into three groups: (i) sociodemographic variables, (ii) health-related determinants and (iii) use of healthcare resources. Sociodemographic variables, including gender (men, women), age group (18–40 years, 41–64 years, ≥ 65 years), educational attainment (without studies, primary, secondary, professional training or university); marital status (single, married, widowed, J. Clin. Med. 2022,11, 2742 4 of 15 separated/divorced), social class (upper: classes I and II, middle: classes III and IV, lower: classes V and VI) [37] and nationality (Spanish, foreign). The health-related determinants consisted of body mass index (BMI) (underweight, normal weight, overweight and obese) [ 38 ], smoking status (yes, no), alcohol intake in the last year (yes, no), number of comorbid chronic conditions (none, one or two, and three or more) and self-perceived health status (very good, good, fair, poor, very poor). Use of healthcare resources was evaluated through visits to the general practitioner in the previous 4 weeks (yes, no), visits to a specialist physician in the previous 4 weeks (yes, no), use of emergency services in the previous year (yes, no) and hospitalizations in the previous year (yes, no). 2.4. Procedure and Ethical Considerations The anonymized data are available to the general public through the National Institute of Statistics and Ministry of Health, Consumer Affairs and Social Welfare sites [ 36 – 38 ]. According to Spanish law, authorization by an Ethics Committee was deemed unnecessary because a de-identified public database was used. The research data are included in the Supplementary File S1. 2.5. Statistical Analysis Descriptive analysis was carried out using counts, percentages and mean and standard deviation. The Chi-squared test was used to compare proportions. Chi-square trend analysis and linear regression model were performed to recognize significant trends in the presence of CMDs, FL and PSS from 2006 to 2017. Subsequently, two multivariate logistic regressions were performed to find the factors associated with the presence of CMDs and FL. The measures of estimated association were the crude and adjusted odds ratio (OR) with confidence intervals set at 95%. The Hosmer–Lemeshow test was used to assess the goodness of fit. For PSS, we fitted a multiple linear regression model. We examined the adjusted coefficient of determination (R 2 ), the F statistic and the normality of the residues to determine the goodness of fit. For the multivariate models, we only included the variables that had a potential association with each dependent variable (p ≤ 0.15), and backward selection was used to eliminate non-significant variables based on the likelihood of the Wald statistic. For purposes of the multivariate analysis, the variables were reorganized as follows: age group (<65 years old, ≥ 65 years old), educational attainment (without/primary studies, secondary/university studies), marital status (married, non-married), BMI (normal weight, non-normal weight), chronic conditions (yes, no), self-perceived health status (very good/good, fair, very poor/poor). Statistical significance was set at α = 0.05. The IBM SPSS Statistical package version 25 (IBM Corp, Armonk, NY, USA) was used for the statistical analysis, which was licensed to the University of Cordoba (Córdoba, Spain). 3. Results 3.1. Sociodemographic Variables, Health-Related Determinants and Use of Healthcare Resources Of the cancer individuals identified, 27.68% (n= 698) resided in areas defined as rural and 72.32% (n= 1824) in urban areas. Statistically significant differences in sociodemographic characteristics, health-related determinants and use of healthcare resources between rural and urban individuals were observed. Rural residents reported a lower prevalence of cancer (p< 0.0001), were older (p= 0.001), had a lower educational level (p< 0.001), belonged to a lower social class (p< 0.001) and reported a less common use of tobacco (p< 0.01) and alcohol (p< 0.001) than urban participants (Table 1). Moreover, we observed an increase in the prevalence of cancer patients between both groups (rural: 2006: 2.81%, 2011: 2.07%, 2017: 4.38%, pfor trend <0.0001; urban: 2006: 2.92%, 2011: 4.45%, 2017: 4.95%, pfor trend < 0.0001). Figure 1shows the use of healthcare resources by the rural and urban populations. Although the rural participants used emergency services and were hospitalized about as frequently as urban residents ( p= 0.09 and p= 0.29 , respectively), rural residents saw their general practitioners more J. Clin. Med. 2022,11, 2742 5 of 15 often than urban participants (p= 0.04). On the other hand, urban participants visited a specialist physician more frequently than rural residents (p< 0.01). Table 1. Sociodemographic characteristics and health-related determinants of rural and urban cancer individuals (n= 2522). Variables Total n(%) Rural n= 698 (%) Urban n= 1824 (%) p-Value Gender 0.41 Men 961 (38.10) 275 (39.40) 686 (37.61) Women 1561 (61.90) 423 (60.60) 1138 (62.39) Age group 0.001 18–40 years old 124 (4.92) 33 (4.72) 91 (4.99) 41–64 years old 1023 (40.56) 244 (34.96) 779 (42.71) ≥65 years old 1375 (54.52) 421 (60.32) 954 (52.30) Educational attainment <0.001 Without studies 512 (20.30) 196 (28.08) 316 (17.32) Primary 773 (30.65) 262 (37.54) 511 (28.02) Secondary or PT 922 (36.56) 198 (28.37) 724 (39.69) University 315 (12.49) 42 (6.01) 273 (14.97) Marital status 0.17 Single 298 (11.82) 88 (12.61) 210 (11.51) Married 1524 (60.43) 421 (60.32) 1103 (60.47) Widowed 511 (20.26) 149 (21.35) 362 (19.85) Separated or divorced 189 (7.49) 40 (5.72) 149 (8.17) Social class <0.001 Upper 452 (17.92) 79 (11.32) 373 (20.45) Middle 1084 (42.98) 298 (42.69) 786 (43.09) Lower 986 (39.10) 321 (45.99) 665 (36.46) Nationality 0.37 Spanish 2472 (98.02) 687 (98.42) 1785 (97.86) Foreigner 50 (1.98) 11 (1.58) 39 (2.14) Body Mass Index 0.28 Underweight 45 (1.78) 16 (2.29) 29 (1.59) Normal weight 942 (37.35) 272 (38.97) 670 (36.73) Overweight 990 (39.25) 273 (39.11) 717 (39.31) Obesity 545 (21.62) 137 (19.63) 408 (22.37) Smoking status <0.01 Yes 380 (15.07) 81 (11.60) 299 (16.39) No 2142 (84.93) 617 (88.40) 1525 (83.61) Alcohol intake in the last year <0.001 Yes 931 (36.92) 204 (29.23) 727 (39.86) No 1591 (63.08) 494 (70.77) 1097 (60.14) Number of chronic conditions 0.32 0 379 (15.03) 102 (14.62) 277 (15.19) 1–2 732 (29.02) 218 (31.23) 514 (28.18) ≥3 1411 (55.95) 378 (54.15) 1033 (56.63) Self-perceived health status 0.54 Very good 103 (4.09) 22 (3.16) 81 (4.44) Good 726 (28.79) 194 (27.79) 532 (29.17) Fair 962 (38.14) 273 (39.11) 689 (37.77) Poor 533 (21.13) 150 (21.49) 383 (21.00) Very poor 198 (7.85) 59 (8.45) 139 (7.62) PT: Professional Training. J. Clin. Med. 2022,11, 2742 6 of 15 J. Clin. Med. 2022, 11, x FOR PEER REVIEW 6 of 17 emergency services and were hospitalized about as frequently as urban residents (p = 0.09 and p = 0.29, respectively), rural residents saw their general practitioners more often than urban participants (p = 0.04). On the other hand, urban participants visited a specialist physician more frequently than rural residents (p < 0.01). Figure 1. Use of healthcare resources by cancer patients, according to place of residence. 3.2. CMDs, FL and PSS With regard to CMDs, we found no differences between rural and urban residents (37.11% vs. 36.95%, respectively; p = 0.94). Nevertheless, over the study years, the prevalence of CMDs among urban cancer patients decreased (2006: 39.13%, 2011: 38.87%, 2017: 34.30%; p for trend = 0.04) but not among rural residents (2006: 40.28%, 2011: 35.90%, 2017: 34.36%; p for trend = 0.16). In relation to FL, rural participants reported a significantly higher prevalence compared to urban residents (35.24% vs. 30.15%, respectively; p = 0.01). Moreover, we discovered an increase in the prevalence of FL between both groups (rural: 2006: 30.74%, 2011: 27.56%, 2017: 44.79%, p for trend <0.001; urban: 2006: 15.76%, 2011: 22.06%, 2017: 44.97%, p for trend <0.001). On the other hand, there were no significant associations between PSS and rural–urban place of residence (47.93 ± 8.40 points vs. 47.25 ± 8.31 points; p = 0.07). No significant changes were observed in either rural or urban residents over the study period in relation to PSS (rural: 2006: 47.47 ± 9.29 points, 2011: 48.06 ± 8.52 points, 2017: 48.35 ± 7.22 points, p for trend = 0.40; urban: 2006: 47.42 ± 8.82 points, 2011: 47.29 ± 8.61 points, 2017: 47.11 ± 7.76 points, p for trend = 0.50). 3.3. Associations between Sociodemographic Variables, Health-Related Determinants, CMDs, FL and PSS Table 2 shows the results from logistic regression models of CMDs in rural and urban participants. In rural residents with chronic conditions or a fair or very poor/poor selfperceived health status, the probability of suffering from CMDs was higher. In urban residents, having consumed alcohol in the last year and visiting a specialist physician decreased that probability. Figure 1. Use of healthcare resources by cancer patients, according to place of residence. 3.2. CMDs, FL and PSS With regard to CMDs, we found no differences between rural and urban residents (37.11% vs. 36.95%, respectively; p= 0.94). Nevertheless, over the study years, the prevalence of CMDs among urban cancer patients decreased (2006: 39.13%, 2011: 38.87%, 2017: 34.30%; pfor trend = 0.04) but not among rural residents (2006: 40.28%, 2011: 35.90%, 2017: 34.36%; pfor trend = 0.16). In relation to FL, rural participants reported a significantly higher prevalence compared to urban residents (35.24% vs. 30.15%, respectively; p= 0.01). Moreover, we discovered an increase in the prevalence of FL between both groups (rural: 2006: 30.74%, 2011: 27.56%, 2017: 44.79%, pfor trend <0.001; urban: 2006: 15.76%, 2011: 22.06%, 2017: 44.97%, pfor trend <0.001). On the other hand, there were no significant associations between PSS and rural–urban place of residence ( 47.93 ±8.40 points vs. 47.25 ±8.31 points ;p= 0.07). No significant changes were observed in either rural or urban residents over the study period in relation to PSS (rural: 2006: 47.47 ±9.29 points , 2011: 48.06 ± 8.52 points, 2017: 48.35 ± 7.22 points, pfor trend = 0.40; urban: 2006: 47.42 ±8.82 points , 2011: 47.29 ± 8.61 points, 2017: 47.11 ± 7.76 points, pfor trend = 0.50). 3.3. Associations between Sociodemographic Variables, Health-Related Determinants, CMDs, FL and PSS Table 2shows the results from logistic regression models of CMDs in rural and urban participants. In rural residents with chronic conditions or a fair or very poor/poor selfperceived health status, the probability of suffering from CMDs was higher. In urban residents, having consumed alcohol in the last year and visiting a specialist physician decreased that probability. Table 2. Association between CMDs, sociodemographic factors and health-related determinants in rural and urban cancer patients (n= 2522). Variables Rural Residents Urban Residents OR (IC 95%) ORa (IC 95%) p-Value OR (IC 95%) ORa (IC95%) p-Value Gender Men Reference Reference Reference Women 1.17 (0.85–1.60) 1.40 (1.14–1.70) 1.37 (1.09–1.71) 0.01 Age group <65 years old Reference Reference ≥65 years old 1.05 (0.77–1.43) 0.87 (0.72–1.06) Educational attainment Without/Primary studies 1.36 (0.98–1.89) 1.31 (1.08–1.58) 1.17 (1.11–1.28) 0.001 Secondary/University studies Reference Reference Reference Marital status Married 1.02 (0.75–1.40) 0.83 (0.68–1.12) Non-married Reference Reference J. Clin. Med. 2022,11, 2742 7 of 15 Table 2. Cont. Variables Rural Residents Urban Residents OR (IC 95%) ORa (IC 95%) p-Value OR (IC 95%) ORa (IC95%) p-Value Social class Upper Reference Reference Reference Middle 1.47 (0.86–2.51) 1.85 (1.40–2.44) 1.65 (1.21–2.26) 0.001 Lower 1.53 (0.90–2.62) 2.38 (1.80–3.16) 1.98 (1.44–2.76) <0.001 Nationality Spanish 1.03 (0.30–3.56) 1.50 (0.74–3.04) Foreigner Reference Reference Body Mass Index Normal weight Reference Reference Non-normal weight 0.98 (0.73–1.37) 1.14 (0.93–1.39) Hospitalization during the previous year Yes 0.87 (0.76–1.53) 0.44 (0.35–0.54) No Reference Reference Use of emergency services during the previous year Yes 0.65 (0.55–1.14) 0.42 (0.35–0.51) No Reference Reference Visits to specialist physician during the previous 4 weeks Yes 0.49 (0.36–0.68) 0.43 (0.36–0.53) 0.62 (0.50–0.77) <0.001 No Reference Reference Reference Visits to general practitioner during the previous 4 weeks Yes 0.47 (0.34–0.66) 0.74 (0.51–0.91) 0.03 0.53 (0.43–0.64) No Reference Reference Reference Smoking status Yes 1.06 (0.66–1.70) 1.18 (0.91–1.51) No Reference Reference Alcohol intake in the last year Yes 0.58 (0.41–0.82) 0.67 (0.46–0.97) 0.04 0.53 (0.44–0.65) 0.69 (0.55–0.87) <0.001 No Reference Reference Reference Reference Chronic conditions Yes 1.99 (1.23–3.22) 1.52 (1.10–2.61) 0.01 1.31 (0.99–1.72) No Reference Reference Reference Self-perceived health status Very good/good Reference Reference Reference Reference Fair 2.30 (1.48–3.56) 1.98 (1.26–3.11) 0.001 2.88 (2.21–3.76) 2.57 (1.95–3.37) <0.001 Very poor/poor 3.51 (2.02–4.03) 5.85 (3.82–6.15) <0.001 4.94 (3.02–5.91) 4.43 (4.31–5.10) <0.001 OR: odds ratio; ORa: odds ratio adjusted for all sociodemographic and health-related variables; CI 95%: 95% confidence interval; Rural residents: Hosmer–Lemeshow test for CMDs χ2 = 3.74, p= 0.61; Nagelkerke’s R 2 Square for CMDs = 0.19; p-value < 0.001; Urban residents: Hosmer–Lemeshow test for CMDs χ2 = 5.21, p= 0.76; Nagelkerke’s R2Square for CMDs = 0.21; p-value < 0.001. The results from the logistic regression models of FL in rural and urban participants are shown in Table 3. Three variables were found to be related with a greater probability of FL in rural residents: being ≥ 65 years old, having no studies or primary studies and having a fair or very poor/poor self-perceived health status. In urban participants, the probability of FL was higher in those who were ≥ 65 years old, had no studies or primary studies, were Spanish, had non-normal weight and had a fair or very poor/poor self-perceived health status. Table 3. Association between FL, sociodemographic factors and health-related determinants in rural and urban cancer patients (n= 2522). Variables Rural Residents Urban Residents OR (IC 95%) ORa (IC 95%) p-Value OR (IC 95%) ORa (IC 95%) p-Value Gender Men Reference Reference Women 0.81 (0.59–1.11) 1.02 (0.83–1.26) Age group <65 years old Reference Reference Reference Reference ≥65 years old 9.10 (5.92–9.98) 8.41 (5.21–9.40) <0.001 9.60 (7.37–9.96) 9.04 (6.75–9.49) <0.001 Educational attainment Without/Primary studies 3.65 (2.50–5.32) 1.60 (1.03–2.50) 0.04 2.31 (2.25–3.39) 1.43 (1.11–1.84) <0.01 Secondary/University studies Reference Reference Reference Reference J. Clin. Med. 2022,11, 2742 8 of 15 Table 3. Cont. Variables Rural Residents Urban Residents OR (IC 95%) ORa (IC 95%) p-Value OR (IC 95%) ORa (IC 95%) p-Value Marital status Married 0.97 (0.70–1.33) 0.59 (0.48–0.73) 0.67 (0.52–0.85) 0.001 Non-married Reference Reference Reference Social class Upper Reference Reference Middle 1.55 (0.88–2.74) 1.32 (0.99–1.76) Lower 2.12 (1.21–3.72) 1.98 (1.48–2.64) Nationality Spanish 1.46 (0.38–5.55) 5.30 (1.63–5.29) 3.87 (1.07–4.02) 0.04 Foreigner Reference Reference Reference Body Mass Index Normal weight Reference Reference Reference Non-normal weight 1.02 (0.74–1.41) 1.93 (1.55–2.41) 1.49 (1.14–1.94) <0.01 Hospitalization during the previous year Yes 0.63 (0.44–0.90) 0.68 (0.54–0.85) No Reference Reference Use of emergency services during the previous year Yes 0.41 (0.29–0.56) 0.47 (0.39–0.58) 0.60 (0.47–0.77) <0.001 No Reference Reference Reference Visits to specialist physician during the previous 4 weeks Yes 0.75 (0.54–1.06) 0.82 (0.67–1.10) No Reference Reference Visits to general practitioner during the previous 4 weeks Yes 0.62 (0.45–0.86) 0.80 (0.66–0.98) No Reference Reference Smoking status Yes 0.26 (0.13–0.49) 0.43 (0.32–0.60) No Reference Reference Alcohol intake in the last year Yes 0.57 (0.40–0.81) 0.90 (0.74–1.11) No Reference Reference Chronic conditions Yes 2.50 (1.50–4.20) 5.18 (0.79–7.91) No Reference Reference Self-perceived health status Very good/good Reference Reference Reference Reference Fair 2.80 (1.82–4.30) 2.42 (1.52–3.84) <0.001 2.90 (2.19–3.84) 2.43 (1.77–3.32) <0.001 Very poor/poor 5.27 (3.38–8.24) 5.92 (3.59–9.75) <0.001 5.96 (4.47–7.95) 5.82 (4.16–8.14) <0.001 OR: odds ratio; ORa: odds ratio adjusted for all sociodemographic and health-related variables; CI 95%: 95% confidence interval; Rural residents: Hosmer–Lemeshow test for FL χ2 = 2.36, p= 0.94; Nagelkerke’s R 2 Square for FL = 0.34; p-value < 0.001; Urban residents: Hosmer–Lemeshow test for FL χ2 = 11.41, p= 0.11; Nagelkerke’s R 2 Square for FL = 0.34; p-value < 0.001. Table 4shows the multiple linear regression models considering social support as a dependent variable and sociodemographic and health-related factors as independent variables, according to the place of residence. Among the participants who lived in rural areas, PSS was positively related with being married and negatively with smoking and having a fair or very poor/poor self-perceived health status. In urban residents, being married, being Spanish and having chronic conditions were positively associated with the PSS. Table 4. Association between PSS, sociodemographic factors and health-related determinants in rural and urban cancer patients (n= 2522). Variables Rural Residents Urban Residents Univariate Analysis Multivariate Analysis Univariate Analysis Multivariate Analysis Bβp-Value B βp-Value B βp-Value B βp-Value Gender Men Reference Reference Reference Reference Women 0.71 0.65 0.28 0.20 0.01 0.62 Age group <65 years old Reference Reference Reference Reference ≥65 years old 0.09 0.005 0.89 −0.11 −0.07 0.78 Educational attainment Without/Primary studies −0.67 −0.04 0.32 −0.06 −0.01 0.98 Secondary/University studies Reference Reference Reference Reference J. Clin. Med. 2022,11, 2742 9 of 15 Table 4. Cont. Variables Rural Residents Urban Residents Univariate Analysis Multivariate Analysis Univariate Analysis Multivariate Analysis Bβp-Value B βp-Value B βp-Value B βp-Value Marital status Married 2.47 0.14 <0.001 2.48 0.15 <0.001 2.48 0.15 <0.001 2.38 0.14 <0.001 Non-married Reference Reference Reference Reference Reference Reference Reference Reference Social class Upper Reference Reference Reference Reference Middle 0.13 0.008 0.90 −0.38 −0.02 0.47 Lower −0.28 −0.02 0.79 −1.02 −0.06 0.06 Nationality Spanish 0.48 0.007 0.85 2.82 0.05 0.04 2.71 0.05 0.04 Foreigner Reference Reference Reference Reference Reference Reference Body Mass Index 0.19 0.01 0.64 Normal weight Reference Reference Reference Reference Non-normal weight −0.32 −0.02 0.62 Hospitalization during the previous year Yes 0.71 0.76 <0.001 0.18 0.23 <0.001 No Reference Reference Reference Use of emergency services during the previous year Yes 0.18 0.67 <0.001 0.65 0.40 <0.001 No Reference Reference Reference Visits to specialist physician during the previous 4 weeks Yes 0.21 0.69 <0.001 0.18 0.25 <0.001 No Reference Reference Reference Visits to general practitioner during the previous 4 weeks Yes 0.14 0.65 <0001 0.17 0.39 <0.001 No Reference Reference Reference Smoking status Yes −2.14 −0.08 0.03 −1.95 −0.07 0.04 −1.03 −0.05 0.05 No Reference Reference Reference Reference Reference Reference Alcohol intake in the last year Yes 1.63 0.09 0.02 −0.20 −0.01 0.61 No Reference Reference Reference Reference Chronic conditions Yes 0.63 0.03 0.48 1.54 0.07 <0.01 1.09 0.05 0.04 No Reference Reference Reference Reference Reference Reference Self-perceived health status Very good/good Reference Reference Reference Reference Reference Reference Reference Reference Fair −1.21 −0.07 0.04 −1.22 −0.07 0.03 −0.98 −0.06 0.04 −0.88 −0.05 0.04 Very poor/poor −2.91 −0.16 0.000 −3.07 −0.17 <0.001 −2.42 −0.13 <0.001 −2.28 −0.12 <0.001 B: Unstandardized coefficient; β : Standardized coefficient; Rural: Adjusted coefficient of determination (R2) = 21.33% , F = 8.44, p< 0.001; Urban: Adjusted coefficient of determination (R 2 ) = 26.50%, F =14.48, p< 0.001. 4. Discussion 4.1. Sociodemographic Characteristics, Health-Related Determinants and Use of Healthcare Resources: Differences across Places of Residence The findings of the current study show that rural participants were older, had a lower educational level, belonged to a lower social class and reported a less common use of tobacco and alcohol than their urban counterparts. On the other hand, cancer diagnosis was more prevalent among urban participants, which could be due to the fact that urban dwellers are subjected to higher levels of industrial pollution than rural residents, and they are more vulnerable to important cancer risk factors, such as overweight and obesity, cigarette smoking, alcohol use and physical inactivity and are more likely to participate in cancer screening [ 39 ]. Although universal health coverage has eliminated many barriers to receiving suitable, high-quality health care, in the present study, geographic location seems to influence the type of healthcare services used by cancer patients. In our case, the participants from rural areas reported a higher use of primary care and a lower use of specialist care than urban residents. Specialists and subspecialists generally tend to be concentrated in urban areas, resulting in a greater reliance on primary care providers in rural areas [ 40 ]. Moreover, the greater use of primary care by people residing in rural areas may be due to a lack of willingness or because of transportation issues [ 41 ]. Taking this into account, general practitioners should be trained to care for cancer patients, and communication with oncologists should be encouraged early on in the training [42]. 4.2. CMDs, FL and PSS The fact that mental health is affected systematically according to the characteristics of the place of residence or the neighborhood has been reported [ 43 ]. Living in cities is