Cardiovascular disease prevention capacity in Colombian local health departments

Figures & data

Figure 1. Problems, potential solutions and expected outcomes regarding the cardiovascular disease prevention capacity in Colombia.

Figure 2. Conceptual model of the cardiovascular disease prevention capacity in Colombian local health departments.

Table 1. Cronbach’s α of the final subdimensions of the organisational cardiovascular disease prevention capacity in Colombian local levels.

Dimension (number of items)	Subdimensions (numbers of items)	α-Cronbach
1. Skills (24 items)	Needs assessment of population factors associated with the prevention of cardiovascular disease (4 items)	0.8723
	Identification of relevant practices for the prevention of cardiovascular disease (7 items)	0.6492
	Programme planning (4 items)	0.7984
	Implementation strategies (9 items)	0.7980
2. Knowledge (11 items)	Knowledge generation (5 items)	0.6792
	Dissemination of evidence making decisions (6 items)	0.6972
3. Resources (7 items)	Allocation of resources (4 items)	0.7056
	Technological resources (3 items)	0.9055
4. Willingness to act (21 items)	Behavioural and psychosocial factors (5 items)	0.9519
	Biological factors (5 items)	0.9675
	Social determinants (5 items)	0.7075
	Previous actions for the prevention of cardiovascular disease (3 items)	0.6247
	Motivation for the prevention of cardiovascular disease (3 items)	0.7417
5. Leadership (19 items)	Support from managers (6 items)	0.6595
	Opportunities for learning (3 items)	0.7081
	Organisational learning (4 items)	0.7201
	Workplace climate (3 items)	0.9171
	Professional development policies (3 items)	0.8447
6. Alliances (6 items)	Interdisciplinary and intersectoral approach (6 items)	0.8958

Figure 3. Flow diagram for the development of the quesstionaire for assess the organisational prevention capacity of cardiovascular disease in Colombian local health departments.

Figure 4. Overall score of CVD prevention capacity in 95 municipalities of two Colombian departments.

Table 2. Descriptive statistics of the overall, dimensions and subdimension of cardiovascular capacity prevention in two Colombian departments, 2021*.

Dimension and subdimensions	Departments
	Mideast (n = 55)			West (n = 40)
	Mean	Median	Range	Mean	Median	Range
Overall CVD prevention capacity	5.06	5.11	3.28–6.73	5.14	5.33	3.38–6.20
1. Skills	4.95	5.14	2.88–6.92	4.92	5.17	2.87–6.42
Needs assessment of population factors associated with the prevention of cardiovascular disease	5.20	5.25	3.25–7.00	5.27	5.50	3.00–6.50
Identification of relevant practices for the prevention of cardiovascular disease	4.62	5.00	1.71–7.00	4.62	4.78	2.29–6.43
Programme planning	5.09	5.50	3.00–7.00	4.96	5.25	1.75–7.00
Implementation strategies	5.02	5.22	2.89–6.78	4.98	5.17	2.88–6.89
2. Knowledge	5.12	5.10	2.73–6.91	5.15	5.36	1.91–6.64
Knowledge generation	5.11	5.00	2.40–7.00	5.33	5.55	3.00–6.80
Dissemination of evidence making decisions	5.12	5.17	2.67–7.00	5.01	5.17	1.00–6.50
3. Resources	4.76	4.83	2.28–6.86	4.49	4.57	2.14–6.86
Allocation of resources	4.67	4.75	1.75–7.00	4.39	4.25	1.00–7.00
Technological resources	4.88	5.00	1.33–7.00	4.63	5.00	2.00–7.00
4. Willingness to act	5.78	5.81	3.71–7.00	5.92	6.12	3.38–6.90
Behavioural and psychosocial factors	6.44	6.60	5.00–7.00	6.42	6.80	5.00–7.00
Biological factors	6.25	6.40	3.40–7.00	6.22	6.60	1.60–7.00
Social determinants	5.78	5.80	2.20–7.00	5.98	6.40	2.00–7.00
Previous actions for the prevention of cardiovascular disease	4.85	5.00	1.67–7.00	5.19	5.33	1.00–7.00
Motivation for the prevention of cardiovascular disease	4.85	5.00	1.67–7.00	5.24	5.33	1.00–7.00
5. Leadership	4.60	4.63	2.16–7.00	4.88	4.97	2.37–6.47
Support from managers	4.67	5.00	2.00–7.00	5.01	5.17	1.00–6.83
Opportunities for learning	4.36	4.33	1.00–7.00	4.73	4.67	1.00–6.67
Organisational learning	4.42	4.50	1.25–7.00	4.53	4.50	1.00–7.00
Workplace climate	5.43	5.67	1.67–7.00	6.15	6.33	3.00–7.00
Professional development policies	4.07	4.33	1.00–7.00	3.98	4.17	1.00–7.00
6. Alliances	4.68	5.00	1.67–7.00	4.83	5.33	1.00–6.67
Interdisciplinary and intersectoral approach	4.68	5.00	1.67–7.00	4.83	4.83	1.00–6.67

* T-tests were smaller than the pre-established threshold of 0.05.

Table 3. Univariable and multivariable GEE models for the association between overall CVD prevention capacity with political, population and organisational factors.

Variables	n	Univariable			Multivariable
					Model a*			Model b**
		Coefficient (95% CI)	p-value	Deviance	Coefficient (95% CI)	p-value	Deviance	Coefficient (95% CI)	p-value	Deviance
Resources allocated to public health in 2021	94			57.07			55.99			53.02
First quintile	32	−0.18 (−0.56–0.21)	0.36		−0.13 (−0.52–0.27)	0.53		0.00^¥ (−0.41–0.40)	0.99
Second quintile	31	−0.2 (−0.59–0.19)	0.32		−0.2 (−0.58–0.19)	0.32		−0.23 (−0.61–0.14)	0.23
Third quintile	31	Ref			Ref			Ref
Population size in 2021 (log transformation)	95	0.06 (−0.07–0.20)	0.38	57.67	0.06 (−0.17–0.29)	0.6	56.46	0.07 (−0.16–0.30)	0.54
Number of LHD employees	94	0.01 (−0.00^£−0.02)	0.06	55.64	0.02 (0.00^¥ −0.03)	0.04	54.19	0.02 (0.00^€−0.04)	0.03

*Adjusted for category of the municipality, department, percentage of urban population.

** Fully adjusted model for category of the municipality, department, percentage of urban population.

^¥ Actual estimate was −0.0007.

^£ Actual estimate was −0.0003.

^€ Actual estimate was 0.002.

Data availability statement

The datasets generated and analysed during the current study are available from the corresponding author upon reasonable request.