| Literature DB >> 35480592 |
Katrina Ann Obas1,2, Ariana Bytyci-Katanolli1,2, Marek Kwiatkowski1,2, Qamile Ramadani3, Nicu Fota3, Naim Jerliu4,5, Shukrije Statovci6, Jana Gerold2,7, Manfred Zahorka2,7, Nicole Probst-Hensch1,2.
Abstract
Objectives: Kosovo has the lowest life expectancy in the Balkans. Primary healthcare (PHC) plays an essential role in non-communicable disease (NCD) prevention. We described primary, secondary and tertiary prevention indicators in Kosovo and assessed their association with depressive symptoms.Entities:
Keywords: COPD; depressive symptoms; diabetes; hypertension; prevention; public health
Mesh:
Year: 2022 PMID: 35480592 PMCID: PMC9037373 DOI: 10.3389/fpubh.2022.794309
Source DB: PubMed Journal: Front Public Health ISSN: 2296-2565
Figure 1Conceptual framework. Primary care participants exist on a disease continuum, from a healthy person to disease onset, to disease progression. Primary healthcare aims to prevent people from moving forward along the continuum. Primary, secondary and tertiary prevention strategies target people at different stages of the disease continuum. To evaluate gaps in primary, secondary and tertiary prevention in Kosovo's PHC system, our study assesses negative indicators of each stage of prevention. Specifically, it describes the prevalence of lifestyle risk factors (targets if primary prevention), as well as undetected hypertension, diabetes and chronic obstructive pulmonary disease (COPD) (targets of secondary prevention) and uncontrolled hypertension, diabetes and COPD (targets of tertiary prevention) among Kosovo PHC users. It further assesses the association between depressive symptoms and these indicators to evaluate whether depressive symptoms act as a barrier to disease prevention.
Participant characteristics (Kosovo Non-Communicable Disease Cohort, Kosovo, 2019).
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| Age, median (IQR) | 60 (53–67) |
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| Male | 402 (41.2) |
| Female | 575 (58.8) |
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| Primary school or less | 618 (63.3) |
| Secondary school | 300 (30.7) |
| University/College | 59 (6.0) |
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| Currently working | 162 (16.6) |
| House person | 467 (47.8) |
| Retired or disabled | 314 (32.1) |
| Unemployed | 34 (3.5) |
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| Rural | 549 (56.2) |
| Urban | 428 (43.8) |
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| Drenas | 96 (9.8) |
| Fushe Kosova | 109 (11.2) |
| Gjakova | 72 (7.4) |
| Gracanica | 52 (5.3) |
| Junik | 21 (2.2) |
| Lipjan | 171 (17.5) |
| Malisheva | 77 (7.9) |
| Mitrovica | 81 (8.3) |
| Obiliq | 70 (7.2) |
| Rahovec | 77 (7.9) |
| Skenderaj | 93 (9.5) |
| Vushtrri | 58 (5.9) |
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| Albanian | 890 (91.1) |
| Serbian | 48 (4.9) |
| Roma, Ashkali, Egyptian, Other | 39 (4.0) |
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| Blood pressure (mmHg), | |
| Systolic, median (IQR) | 133 (123–146) |
| Diastolic, median (IQR) | 86 (80–93) |
| HbA1c (%), median (IQR) | 6.5 (5.7–7.7) |
| PEF (L/min), median (IQR) | 260 (187–350) |
| BMI, median (IQR) | 30.3 (27.4–34.1) |
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| Diagnosed hypertension, freq (%) | 605 (61.9) |
| Diagnosed Diabetes, freq (%) | 506 (51.8) |
| Diagnosed COPD, freq (%) | 59 (6.0) |
| Depressive symptoms score (median, IQR) | 2 (0–6) |
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| Normal (DASS depression score 0–9) | 792 (81.1) |
| Mild (DASS depression score 10–13) | 66 (6.8) |
| Moderate (DASS depression score 14–20) | 84 (8.6) |
| Severe (DASS depression score 21–27) | 17 (1.7) |
| Very severe (DASS depression score 28–42) | 18 (1.8) |
IQR, Interquartile range; mmHg, millimeters of mercury; HbA1c, glycated hemoglobin; PEF, Peak Expiratory Flow; BMI, body mass index; COPD, chronic obstructive pulmonary disease; DASS, Depression Anxiety Stress Scale.
Prevalence of non-communicable disease risk factors, stratified by sex and highest level of education attained (Kosovo Non-Communicable Disease Cohort, Kosovo, 2019).
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| Current smoker | 201 (20.6) | 110 (27.4) | 91 (15.8) | <0.001*a | 106 (17.2) | 77 (25.7) | 18 (30.5) | 0.002*a |
| Physical inactivity | 687 (70.3) | 250 (62.2) | 437 (76.0) | <0.001*a | 482 (78.0) | 165 (55.0) | 40 (67.8) | <0.001*a |
| Poor nutrition | 831 (85.1) | 340 (84.6) | 491 (85.4) | 0.725 a | 537 (86.9) | 246 (82.0) | 48 (81.4) | 0.106a |
| Alcohol consumption | 44 (4.5) | 43 (10.7) | 1 (0.2) | <0.001*a | 14 (2.3) | 26 (8.7) | 4 (6.8) | <0.001*a |
| Obesity | 515 (52.7) | 151 (37.6) | 364 (63.3) | <0.001*a | 381 (61.7) | 111 (37.0) | 23 (39.0) | <0.001*a |
| Lifestyle index b | <0.001*c | <0.001*c | ||||||
| 0 | 16 (1.6) | 13 (3.2) | 3 (0.5) | 2 (0.3) | 11 (3.7) | 3 (5.1) | ||
| 1 | 155 (15.9) | 81 (20.2) | 74 (12.9) | 69 (11.2) | 77 (25.7) | 9 (15.3) | ||
| 2 | 379 (38.8) | 156 (38.8) | 223 (38.8) | 240 (38.8) | 115 (38.3) | 24 (40.7) | ||
| 3 | 348 (35.6) | 112 (27.9) | 236 (41.0) | 259 (41.9) | 72 (24.0) | 17 (28.8) | ||
| 4 | 74 (7.6) | 35 (8.7) | 39 (6.8) | 46 (7.4) | 23 (7.7) | 5 (8.5) | ||
| 5 | 5 (0.5) | 5 (1.2) | 0 (0.0) | 2 (0.3) | 2 (0.7) | 1 (1.7) | ||
aChi.
Prevalence of undetected and uncontrolled hypertension, diabetes and COPD, also disaggregated by disease severity and stratified by sex and educational level (Kosovo Non-Communicable Disease Cohort, Kosovo, 2019).
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| Undetected hypertension ( | 138 (18.6) | 70 (24.0) | 68 (15.1) | 0.002* | 75 (15.3) | 51 (23.6) | 12 (31.6) | 0.004* |
| Undetected diabetes ( | 95 (15.8) | 36 (14.7) | 59 (16.7) | 0.478 | 62 (16.3) | 27 (14.5) | 6 (17.7) | 0.826 |
| Undetected COPD ( | 49 (45.4) | 13 (36.1) | 36 (50.0) | 0.172 | 35 (46.7) | 13 (43.3) | 1 (33.3) | 0.870 |
| Uncontrolled hypertension ( | 171 (28.3) | 74 (33.3) | 97 (25.3) | 0.350 | 114 (27.5) | 49 (29.7) | 8 (30.8) | 0.837 |
| Uncontrolled diabetes ( | 400 (79.1) | 170 (80.6) | 230 (78.0) | 0.478 | 258 (80.9) | 121 (76.1) | 21 (75.0) | 0.416 |
| Uncontrolled COPD ( | 45 (76.3) | 15 (65.2) | 30 (83.3) | 0.111 | 32 (80.0) | 12 (70.6) | 1 (50.0) | 0.503 |
aChi.
Figure 2Association between depressive symptoms (continuous score) and primary, secondary and tertiary prevention negative indicators. Squares indicate the odds ratio per one-point increase in depressive symptoms. Lines indicate the 95% confidence interval. Depressive symptoms were assessed using the Depression, Anxiety, Stress Scale-21. Mixed ordinal logistic regression models quantified the association between depressive symptoms and lifestyle index. The associations between depressive symptoms and all other outcomes were quantified with mixed logistic regression models. All models included municipality as a random effect and were adjusted for age, sex, work status, education level, living in a rural or urban setting, and ethnicity with exception of alcohol, which was reduced to adjustment for only age, sex and ethnicity.