The Japanese Ministry of Health, Labour and Welfare (MHLW) promoted the National Health Promotion Movement in the 21st century (Health Japan 21) in 2000,1 aiming to reduce the number of deaths of people in the prime of their life and prolong healthy years of life. According to the Health Japan 21 middle evaluation report in 2007,1 lifestyle-related diseases should be promoted further as a national campaign in cooperation with industry and through efficient, as well as effective, health check-ups and counselling guidance made by healthcare insurers. Therefore, the MHLW introduced annual health screening and health promotion services in 2008 as part of the national health insurance system. National specific health check-up and specific health guidance systems were implemented to provide population-based primary prevention for cardiovascular disease, cerebrovascular disease and cancer for all subjects aged 40–74 years.2,3 As early detection and intervention for subjects with or at high risk of metabolic syndrome are purposed in specific health check-ups, all subjects are interviewed, a survey is taken of their lifestyle, and they undergo laboratory tests for metabolic diseases, including hypertension, dyslipidaemia and type 2 diabetes mellitus.
Based on the concept of public health, public health nurses in Japan are the principal experts providing specific health guidance and played a core role in this project.3 Subjects meeting the criteria defining metabolic syndrome were targeted for specific health check-ups and specific health guidance by public health nurses who were assigned to each local area. For health check-ups, nurses are not authorised to prescribe medicine, administer treatment covered by insurance, or write a letter of referral, but they may encourage patients to seek consultation at a medical institution if necessary. Based on the health check-ups manualised by the MHLW and standardised training on health guidance, when giving specific health guidance, public health nurses who gained knowledge on lifestyle diseases, behavioural changes, and high-risk and population approaches provide information to people through home visits and health lectures and provide motivational as well as active support.2–4
Although previous studies on the specific health guidance system suggested that the prevalence of metabolic syndrome may have decreased at the population level,5 the extent of the quantitative and qualitative effects of health guidance differed among studies6–8 and whether there are long-term effects has not been clarified.9 Furthermore, as a critical issue in the specific health check-up system, Japanese public health nurses often face and address a small percentage of subjects at high risk of cardiovascular disease (eg systolic blood pressure [SBP] ≥160 mmHg, diastolic blood pressure [DBP] ≥100 mmHg, and fasting plasma glucose [FPG] level ≥ 6.99 mmol/L) who receive specific health guidance and consult a medical institution. In particular, approximately 35% were linked to medical intervention in Tottori City, Japan, in 2012, and the remaining subjects, who may account for a large portion of medical expenses associated with cardiovascular disease events in the future, did not receive adequate health guidance and medical treatment. Thus, it is important to examine the roles of specific health check-ups and specific health guidance in individuals at high risk of these lifestyle diseases, but evaluation based on a stratified analysis of persons undergoing a health check-up has not been adequately performed.
Therefore, in the present study, among people who underwent a specific health check-up, we targeted patients at high risk of a lifestyle disease and examined whether the continuous health guidance provided by public health nurses in the local community is linked to improvement in the health indicators in comparison with the group without the health guidance.
Methods
Study design
We conducted a case-control study examining whether health guidance by public health nurses over a three-year period could lead to improvements in health indicators for subjects at a high risk of multiple lifestyle diseases in comparison to the group without the health guidance. The study population consisted of subjects who received a specific health check-up in Tottori City in 2012.
This study was approved by the institutional review board of the Faculty of Medicine of Tottori University (approval number 1702A191) and was conducted according to the Declaration of Helsinki and the Ethical Guidelines for Medical and Health Research Involving Human Subjects.
Subjects
Among people aged 40–74 years at the start of the study who underwent a specific health check-up in 2012, subjects meeting the criteria defining metabolic syndrome were excluded (central obesity [waist circumference at umbilical level ≥85 cm in men, ≥90 cm in women] plus more than two of following conditions: triglycerides [TG] ≥1.69 mmol/L and/or high-density lipoprotein cholesterol [HDL-C] <1.03 mmol/L, SBP ≥130 mmHg and/or DBP ≥85 mmHg, FPG ≥6.10 mmol/L). Subjects who had already visited or did not require a medical institution for consultation were also excluded.
Among the remaining subjects, we enrolled those who were identified as requiring medical consultation or requiring consultation in the immediate or near future for at least two of the following conditions: high blood glucose level, high blood pressure, high lipid levels or decreased renal function. The criteria for a requirement for immediate medical consultation included moderate to severe hypertension (SBP ≥160 mmHg or DBP ≥100 mmHg), dyslipidaemia (TG ≥11.3 mmol/L or low-density lipoprotein cholesterol [LDL-C] ≥4.65 mmol/L), hyperglycaemia (FPG ≥6.99 mmol/L), or nephropathy (proteinuria ≥1+ or estimated glomerular filtration rate [eGFR] <50 mL/min/1.73 m2). The criteria for a requirement for medical consultation in the near future included mild hypertension (160 mmHg > SBP ≥ 140 mmHg or 100 mmHg > DBP ≥ 90 mmHg), dyslipidaemia (11.3 mmol/L > TG ≥ 3.39 mmol/L or 4.65 mmol/L > LDL-C ≥ 3.62 mmol/L), hyperglycaemia (6.99 mmol/L > FPG ≥ 6.10 mmol/L) or nephropathy (proteinuria ≥1+ or eGFR <50 mL/min/1.73 m2).
Subjects who met the following exclusion criteria were not included in the analysis: 1) mortality during the follow-up period or loss to follow-up, for example, owing to moving; 2) not receiving a medical consultation for a specific health check-up or later-stage elderly health check-up (subjects aged ≥75 years) in 2013 or later; and 3) notice of a desire to not participate in the present study after a presentation of the outline of the study in writing at Tottori City Hall.
Examination items and stratification of subjects
We examined age, sex, height, weight, body mass index (BMI), abdominal circumference, smoking habit, drinking habit, and presence of a renal disorder (proteinuria ≥1± and eGFR ≥50 mL min/1.73 m2), serum uric acid, aspartate aminotransferase (AST), alanine aminotransferase (ALT) and γ-glutamyl transpeptidase (γ-GTP) as background factors. In addition, SBP, DBP, TG, LDL-C, HDL-C and FPG were used as items for comparison between the years 2012 and 2015.
Subjects were assigned to a health guidance group that received health guidance performed through home visits and other means from 2013 (before implementation of the specific health check-up in that year) to 2015 or a control group that did not receive health guidance owing to absence, refusal or some other reason. We also calculated the number of times health guidance was performed for each subject as the sum of the number of times of participation in home visits and health classes organised by Tottori City.
The participants who decided to seek a medical institution consultation after their 2012 health visit were determined from a medical questionnaire at their 2013 health check-up (Appendix 1). Moreover, to determine whether a medical institution was consulted in 2015, the diseases being treated on the itemised receipts (National Health Insurance, Latter-Stage Elderly Medical Care; subject name and address anonymised) from January to June 2015 were extracted. Subjects with any of the following conditions listed were determined to have received a consultation: hypertension; dyslipidaemia; abnormal glucose metabolism; any renal disease; or organ complications related to lifestyle disease, including stroke, brain haemorrhage, heart failure, angina pectoris, myocardial infarction, atrial fibrillation, renal failure, diabetic nephropathy, retinopathy, obstructive arteriosclerosis, aortic aneurysm, and fundus haemorrhage.
Comparison of 2012 and 2015 health check-up data
To verify the effects of improvement in risk factors of lifestyle disease due to health guidance, we comparatively examined SBP, DBP, TG, LDL-C, HDL-C and FPG in subjects with health check-up data for both 2012 and 2015 in a health guidance group and a control group. In addition, the health guidance group was classified into two groups according to the number of times guidance was provided from 2013 to 2015, and differences with the control group were similarly examined.
Furthermore, in the group that was judged to require health guidance either for hypertension (SBP ≥140 mmHg or DBP ≥90 mmHg), dyslipidaemia (TG ≥3.57 mmol/L or LDL-C ≥3.62 mmol/L) or hyperglycaemia (FPG ≥6.06 mmol/L), we similarly and comparatively examined outcomes with regard to the presence or absence of health guidance.
Data are shown as mean ± standard deviation. Statistical analysis was performed using paired t test or Wilcoxon rank sum test (SPSS version 21). P values <0.05 were considered significant.
Effects of health guidance during a three-year period
To examine the influence of health guidance on medical institution consultation by subjects, a χ2 test was performed using the 2015 medical institution consultation visit as the dependent variable and the presence/absence of health guidance as the explanatory variable.
Differences between 2015 and 2012 of SBP, DBP, LDL-C, TG, HDL-C and FPG values were set as ΔSBP, ΔDBP, ΔLDL-C, ΔTG, ΔHDL-C and ΔFPG, respectively; scores that decreased were regarded as negative and those that increased as positive.
A simple regression analysis and a multiple regression analysis were performed regarding the above-mentioned indicators, age, BMI, sex, and number of visits (SPSS version 21). We then selected items with a significant correlation (P <0.05).
Results
Subjects
In this study, 393 subjects in Tottori City who were enrolled in National Health Insurance and received repeated guidance until 2015 were defined as the health guidance group. By contrast, 109 subjects, excluding those who visited a medical institution for consultation using their own judgement by 2013 from the group that did not receive any health guidance, were defined as the control group (Figure 1).
Various indicators in both groups at the start of the study are shown in Table 1. There were no significant differences at baseline between the groups, except that a few subjects in the health guidance group had renal impairments (P <0.001).
Figure 1. Flow chart for the study
| Table 1. Baseline characteristics |
| |
Health guidance group (n = 393) |
Control group (n = 109) |
| Men:women |
148:245 |
36:73 |
| Age (years) |
67 ± 6 |
65 ± 7 |
| Height (cm) |
158 ± 8 |
157 ± 8 |
| Body weight (kg) |
53.4 ± 7.1 |
53.7 ± 7.6 |
| Body mass index |
21.4 ± 1.9 |
21.7 ± 1.9 |
| Abdominal circumference (cm) |
78.2 ± 6.2 |
78.7 ± 6.6 |
| Systolic blood pressure (mmHg) |
137 ± 20 |
136 ± 19 |
| Diastolic blood pressure (mmHg) |
80 ± 12 |
78 ± 13 |
| Low-density lipoprotein cholesterol (mmol/L) |
3.69 ± 0.83 |
3.65 ± 0.91 |
| Triglycerides (mmol/L) |
1.23 ± 0.65 |
1.25 ± 0.71 |
| High-density lipoprotein cholesterol (mmol/L) |
1.68 ± 0.41 |
1.68 ± 0.47 |
| Fasting plasma glucose (mmol/L) |
5.83 ± 1.50 |
5.77 ± 1.39 |
| Creatinine (μmol/L) |
69.9 ± 28.6 |
71.3 ± 49.7 |
| Estimated glomerular filtration rate (mL/min) |
68 ± 15 |
65 ± 20 |
| Uric acid (μmol/L) |
312 ± 74 |
302 ± 81 |
| Aspartate aminotransferase (IU/L) |
24 ± 9 |
23 ± 7 |
| Alanine aminotransferase (IU/L) |
21 ± 11 |
20 ± 10 |
| Gamma-glutamyltransferase (IU/L) |
21 ± 11 |
20 ± 10 |
| Appropriate entries (%) |
|
|
|
Hypertension
Dyslipidaemia
Hyperglycaemia
Hypertension+dyslipidaemia
Hypertension+hyperglycaemia
Dyslipidaemia+hyperglycaemia
All the above
|
53
62
26
36
5
5
6
|
51
63
27
33
6
6
6
|
| Renal impairment |
17 |
34* |
| Smoking habits (%) |
7 |
13 |
| Drinking habits (%) |
41 |
34 |
| *P <0.05 versus health guidance group |
Weight change and smoking
We examined the changes in body weight in 365 subjects who underwent a health check-up in 2015 as well as 2012; in the health guidance group (n = 301), weight decreased significantly from 53.4 ± 7.2 kg to 52.8 ± 7.5 kg (P <0.001), but no change was noted in the control group (n = 64; 53.6 ± 7.8 kg in 2012 and 54.2 ± 8.3 kg in 2015 [P = 0.058]).
Comparative examination of health check-up data for 2012 and 2015
A significant decrease was observed in SBP, DBP, LDL-C and FPG levels in the health guidance group (P = 0.034, P = 0.012, P <0.001 and P = 0.031 versus control group, respectively; Table 2). However, no change in any health check-up data between 2012 and 2015 was observed in the control group. In the health guidance group in 2012, SBP and FPG were significantly higher in the group that received health guidance four or more times than that received less frequently (P = 0.016 and P = 0.016 versus control group, respectively). A significant decrease was observed in SBP and LDL-C (P = 0.003 and P <0.001 versus control group, respectively) and a significant increase in HDL-C (P = 0.009 versus control group) was observed in the group that received health guidance four or more times. Furthermore, a significant decrease in LDL-C was also noted in the group that received health guidance three or fewer times (P = 0.013 versus control group).
In the group requiring health guidance for hypertension, especially if it occurred more frequently, there was a significant decrease in LDL-C in addition to SBP and DBP (P <0.001, P <0.001 and P <0.001 versus control group, respectively). In the control group, there was a significant decrease in LDL-C and DBP (P = 0.017, and P = 0.003 vs control group, respectively).
In the group requiring health guidance for dyslipidaemia, especially if it occurred more frequently, LDL-C, SBP and DBP significantly decreased (P <0.001, P = 0.007 and P = 0.002 versus control group, respectively) and HDL-C significantly increased (P = 0.040 versus control group). In the control group, a significant decrease in LDL-C was observed (P = 0.035 versus control group).
In the group that underwent health guidance for hyperglycaemia, there was a significant decrease in FPG, LDL-C, TG and SBP (P = 0.001, P = 0.014, P = 0.033 and P = 0.032 versus control group, respectively). On the other hand, there were a significant decrease in LDL-C (P = 0.028 versus control group) and a significant increase in SBP (P = 0.014 versus control group).
| Table 2. Comparative examination of health check-up data for 2012 and 2015 in health guidance and control groups |
| Overall |
Year |
Control group
(n = 109) |
Health guidance group (n = 393) |
| All |
Three times or
less (n = 218) |
Four times or
more (n = 175) |
| SBP (mmHg) |
2012 |
133.7 ± 18.2 |
134.2 ± 18.7 |
131.5 ± 18.9 |
137.2 ± 18.2‡ |
| 2015 |
134.8 ± 18.4 |
132.2 ± 19.3* |
131.7 ± 20.2 |
132.9 ± 18.5† |
| DBP (mmHg) |
2012 |
77.0 ± 12.7 |
78.8 ± 11.6 |
78.3 ± 12.2 |
79.3 ± 11 |
| 2015 |
76.8 ± 11.5 |
77.3 ± 12.2* |
76.8 ± 13.0 |
77.9 ± 11.5 |
| LDL-C (mmol/L) |
2012 |
3.66 ± 0.87 |
3.59 ± 0.80 |
3.56 ± 0.82 |
3.64 ± 0.76 |
| 2015 |
3.50 ± 0.82 |
3.43 ± 0.77† |
3.43 ± 0.7396* |
3.3696 ± 0.81† |
| TG (mmol/L) |
2012 |
1.19 ± 0.66 |
1.20 ± 0.70 |
1.11 ± 0.57 |
1.30 ± 0.80 |
| 2015 |
1.31 ± 0.94 |
1.16 ± 0.68 |
1.13 ± 0.59 |
1.19 ± 0.76 |
| HDL-C (mmol/L) |
2012 |
1.72 ± 0.44 |
1.68 ± 0.43 |
1.66 ± 0.40 |
1.66 ± 0.39 |
| 2015 |
1.67 ± 0.44 |
1.69 ± 0.42 |
1.66 ± 0.39 |
1.72 ± 0.45† |
| FPG (mmol/L) |
2012 |
5.71 ± 1.25 |
5.81 ± 1.61 |
5.60 ± 1.59 |
6.04 ± 1.62‡ |
| 2015 |
5.66 ± 1.05 |
5.66 ± 1.10* |
5.52 ± 0.91 |
5.80 ± 1.25 |
*P <0.05, †P <0.01 versus year 2012; ‡P <0.05 versus the group that underwent health guidance three or fewer times
DBP, diastolic blood pressure; FPG, fasting plasma glucose; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol;
SBP, systolic blood pressure; TG, triglycerides |
| |
| Hypertension |
Year |
Control group
(n = 53) |
Health guidance group (n = 201) |
| All |
Three times or
less (n = 106) |
Four times or
more (n = 95) |
SBP (mmHg)
|
2012 |
149.0 ± 11.0 |
150.2 ± 11.8 |
149.8 ± 12.3 |
150.7 ± 11.2 |
| 2015 |
146.1 ± 17.4 |
142.7 ± 16.3† |
143.8 ± 15.4* |
141.7 ± 17.2† |
DBP (mmHg)
|
2012 |
87.1 ± 9.3 |
85.9 ± 9.5 |
86.4 ± 9.4 |
85.4 ± 9.7 |
| 2015 |
81.0 ± 12.8† |
81.9 ± 11.6† |
82.0 ± 11.8† |
81.8 ± 11.6† |
LDL-C (mmol/L)
|
2012 |
3.87 ± 0.92 |
3.94 ± 0.74 |
3.97 ± 0.79 |
3.89 ± 0.68 |
| 2015 |
3.65 ± 0.78* |
3.65 ± 0.76† |
3.70 ± 0.78* |
3.60 ± 0.75† |
TG (mmol/L)
|
2012 |
1.36 ± 0.78 |
1.32 ± 0.76 |
1.24 ± 0.63 |
1.39 ± 0.87 |
| 2015 |
1.34 ± 1.06 |
1.24 ± 0.74 |
1.14 ± 0.51 |
1.32 ± 0.90 |
HDL-C (mmol/L)
|
2012 |
1.65 ± 0.43 |
1.68 ± 0.42 |
1.70 ± 0.39 |
1.66 ± 0.45 |
| 2015 |
1.58 ± 0.37 |
1.69 ± 0.40 |
1.70 ± 0.34 |
1.68 ± 0.44 |
FPG (mmol/L)
|
2012 |
5.75 ± 1.14 |
5.62 ± 0.98 |
5.67 ± 1.13 |
5.58 ± 1.42 |
| 2015 |
5.43 ± 0.80 |
5.57 ± 1.07 |
5.57 ± 0.89 |
5.56 ± 1.20 |
*P <0.05, †P <0.01 versus year 2012
DBP, diastolic blood pressure; FPG, fasting plasma glucose; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; SBP, systolic blood pressure; TG, triglycerides |
| |
| Dyslipidaemia |
Year |
Control group
(n = 67) |
Health guidance group (n = 236) |
| All |
Three times or
less (n = 126) |
Four times or
more (n = 110) |
SBP (mmHg)
|
2012 |
138.4 ± 19.0 |
141.8 ± 17.7 |
140.4 ± 18.0 |
143.5 ± 17.4 |
| 2015 |
138.8 ± 18.4 |
137.6 ± 18.4† |
138.6 ± 18.2 |
136.6 ± 18.8† |
DBP (mmHg)
|
2012 |
79.7 ± 14.0 |
82.1 ± 11.4 |
81.8 ± 11.5 |
82.5 ± 11.3 |
| 2015 |
77.3 ± 13.0 |
79.0 ± 12.4† |
79.4 ± 12.7 |
79.4 ± 11.9† |
LDL-C (mmol/L)
|
2012 |
4.16 ± 0.63 |
4.15 ± 0.54 |
4.21 ± 0.53 |
4.11 ± 0.54 |
| 2015 |
3.86 ± 0.75* |
3.74 ± 0.75† |
3.78 ± 0.73† |
3.71 ± 0.78† |
TG (mmol/L)
|
2012 |
1.31 ± 0.72 |
1.33 ± 0.71 |
1.24 ± 0.56 |
1.42 ± 0.85‡ |
| 2015 |
1.27 ± 0.79 |
1.24 ± 0.71 |
1.19 ± 0.53 |
1.28 ± 0.85* |
HDL-C (mmol/L)
|
2012 |
1.69 ± 0.42 |
1.66 ± 0.40 |
1.66 ± 0.38 |
1.66 ± 0.43 |
| 2015 |
1.61 ± 0.39 |
1.70 ± 0.40* |
1.67 ± 0.34 |
1.72 ± 0.44* |
FPG (mmol/L)
|
2012 |
5.60 ± 1.00 |
5.63 ± 1.08 |
5.44 ± 0.75 |
5.59 ± 0.82 |
| 2015 |
5.59 ± 0.82 |
5.55 ± 0.93 |
5.43 ± 0.68 |
5.65 ± 1.09 |
|
*P <0.05, †P <0.01 versus year 2012; ‡P <0.05 versus the group that underwent health guidance three or fewer times
DBP, diastolic blood pressure; FPG, fasting plasma glucose; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; SBP, systolic blood pressure; TG, triglycerides
|
| |
| Hyperglycaemia |
Year |
Control group
(n = 32) |
Health guidance group (n = 97) |
| All |
Three times or
less (n = 43) |
Four times or
more (n = 54) |
SBP (mmHg)
|
2012 |
132.0 ± 18.0 |
136.1 ± 18.9 |
138.2 ± 20.4 |
134.4 ± 17.6 |
| 2015 |
135.4 ± 20.6* |
129.2 ± 3.2* |
130.1 ± 20.4 |
128.7 ± 17.2 |
DBP (mmHg)
|
2012 |
77.4 ± 13.4 |
79.9 ± 11.2 |
81.9 ± 11.4 |
78.4 ± 10.9 |
| 2015 |
77.2 ± 11.8 |
77.8 ± 12.4 |
76.7 ± 13.3 |
78.5 ± 11.9 |
LDL-C (mmol/L)
|
2012 |
3.50 ± 0.96 |
3.41 ± 0.80 |
3.47 ± 0.94 |
3.35 ± 0.67 |
| 2015 |
3.39 ± 0.84* |
3.22 ± 0.72* |
3.29 ± 0.75 |
3.18 ± 0.65 |
TG (mmol/L)
|
2012 |
1.14 ± 0.52 |
1.18 ± 0.61 |
1.15 ± 0.59 |
1.19 ± 0.63 |
| 2015 |
1.57 ± 1.09 |
1.03 ± 0.72* |
1.05 ± 0.36 |
1.02 ± 0.86 |
HDL-C (mmol/L)
|
2012 |
1.71 ± 0.47 |
1.72 ± 0.43 |
1.67 ± 0.43 |
1.76 ± 0.42 |
| 2015 |
1.74 ± 0.56 |
1.77 ± 0.41 |
1.63 ± 0.36 |
1.85 ± 0.41 |
FPG (mmol/L)
|
2012 |
7.16 ± 1.65 |
7.50 ± 1.90 |
7.16 ± 1.65 |
7.44 ± 2.21 |
| 2015 |
6.79 ± 1.09 |
6.85 ± 1.24† |
6.79 ± 1.01 |
6.88 ± 1.35† |
*P <0.05, †P <0.01 versus year 2012
DBP, diastolic blood pressure; FPG, fasting plasma glucose; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; SBP, systolic blood pressure; TG, triglycerides |
Effects of health guidance on medical institution consultation and blood pressure, blood lipids and blood glucose levels over three years
Effects of health guidance on medical institution consultation
Using itemised receipts as a reference, we examined the number of subjects who visited a medical institution for consultation in 2015 but had not had a consultation as of 2013. The results confirmed a history of medical institution consultation in 37% (144 of 393 people) of the health guidance group and 24% (26 of 109 people) of the control group (χ2 = 6.23, P = 0.017).
Correlation between health guidance and improvements in risk factors of lifestyle diseases
We performed multiple regression analysis with ΔSBP, ΔDBP, ΔLDC-C, ΔTG, ΔHDL-C and ΔFPG as dependent variables to examine the degree to which health guidance in 2012 had an influence. Because there was a bias in the distribution of the number of times health guidance was received, the data are shown as the square root of the number of times health guidance ([health guidance frequency]1/2) was received.
As listed in Table 3, SBP was adopted as a significant explanatory variable as a result of multiple regression analysis with explanatory variables of SBP and (health guidance frequency)1/2. Similarly, TG and (health guidance frequency)1/2, HDL-C and (health guidance frequency)1/2, FPG and age were adopted as meaningful explanatory variables.
| Table 3. Correlation between health guidance and improvement in lifestyle disease risk factors |
| Dependent variable |
Explanatory variables |
Coefficients |
Standard error |
Standardised coefficients |
t value |
P value |
Correlation |R| |
| ΔSBP |
|
47.18 |
5.68 |
|
|
<0.001 |
0.41 |
| SBP |
–0.34 |
0.04 |
–0.40 |
–8.3 |
<0.001 |
| (Health guidance frequency)1/2 |
–1.71 |
0.91 |
–0.09 |
–1.87 |
0.063 |
| ΔLDL-C |
|
79.50 |
14.76 |
|
|
<0.001 |
0.46 |
| LDL-C |
–0.38 |
0.04 |
–0.44 |
–9.48 |
<0.001 |
| Age |
–0.50 |
0.21 |
–0.11 |
–2.44 |
0.015 |
| ΔTG |
|
60.51 |
7.97 |
|
|
<0.001 |
0.46 |
| TG |
–0.47 |
0.04 |
–0.45 |
–9.75 |
<0.001 |
| (Health guidance frequency)1/2 |
–7.09 |
3.48 |
–0.10 |
–2.04 |
0.042 |
| ΔHDL-C |
|
9.51 |
2.10 |
|
|
<0.001 |
0.33 |
| HDL-C |
–0.17 |
0.28 |
–0.30 |
–6.05 |
<0.001 |
| (Health guidance frequency)1/2 |
1.23 |
0.55 |
0.11 |
2.23 |
0.026 |
| ΔFPG |
|
44.80 |
10.60 |
|
|
<0.001 |
0.73 |
| Fasting plasma glucose |
–0.55 |
0.03 |
-0.72 |
–17.52 |
<0.001 |
| Age |
0.16 |
0.15 |
0.04 |
1.06 |
0.289 |
| FPG, fasting plasma glucose; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; SBP, systolic blood pressure; TG, triglycerides |
Discussion
In the present study, among the untreated subjects with lifestyle-related risk factors identified through a specific health check-up, improvements in health indicators in the group that underwent health guidance were more strongly noted compared with those who did not undergo health guidance. In the group that underwent health guidance for a lipid abnormality, lipid levels and blood pressure both decreased, and subjects with hyperglycaemia also showed a decrease in lipid levels and blood pressure.
Higher blood pressure, higher LDL-C levels, impaired glucose tolerance and lower HDL-C levels additively correlate with the risk of arteriosclerotic disease,10 and moreover, hypertriglyceridemia independent of LDL-C11 and non-HDL-C lipids is associated with the risk of coronary artery disease.12,13 In type 2 diabetes mellitus, high TG and LDL-C levels are correlated with the risk of coronary artery disease.14 Although it is speculated that multiple risk factors were ameliorated simultaneously in the health guidance group, suggesting that health guidance plays a part in ameliorating the risk of atherosclerotic disease, a long-term observational study is needed to prove this hypothesis.
Previous studies on type 2 diabetes have evaluated the long-term effects of health guidance provided by specialised public health nurses worldwide on health promotion,15,16 but it cannot be said that the topic has been sufficiently examined. According to the MetS ACTION-J study,16 subjects with multiple abnormalities such as mildly elevated blood pressure or lipid or glucose abnormalities showed long-term improvement in those health indicators as a result of health guidance. The subjects had mild risk owing to visceral fat accumulation, and it appears that comprehensive risk amelioration was obtained by supporting the subjects in accordance with the prescribed health promotion program. On the other hand, the present study targeted a population with little obesity but which showed abnormally high values for blood pressure or lipid or glucose levels. Such high-risk individuals live in diverse environments, and public health nurses, who do not conduct clinical activities, repeatedly go out into the local community to perform home visit activities and conduct health lectures. To the extent that public health nurses interviewed subjects with respect to health promotion in the present study, there was a wide gap among the subjects regarding their understanding of the need to manage lifestyle diseases, their behavioural change stage, and their intention to seek a consultation at a medical institution. In addition, by listening to each background in detail, public health nurses are able to understand problem points (eg being busy with work, having little consideration for eating and exercise owing to nursing care for an elderly person at home, or having difficulty ensuring a dietary balance and caloric intake owing to living with a young person). Thus, the fact that Japanese public health nurses can carefully interact with the subjects in their home environment and collaborate to make a decision on treatment intention appears to be a unique characteristic.
In the present study, we examined the impact of visiting medical institutions as a factor with respect to the effects of health guidance. Our results showed that the group that underwent health guidance visited a medical institution for consultation more frequently than the control group. There was no significant improvement in any of the health indicators in subjects who did not undergo health guidance, and when limited to subjects with hypertension and lipid abnormalities, improvement in factors other than those indicators was minimal. The results revealed that the health guidance group had consultations with a doctor more frequently than the control group, suggesting that receiving appropriate medication such as antihypertensive medicine greatly contributed to the improvements in test values. Even if the influence of medical examination at a medical institution is excluded (subgroups divided according to medical institution visits of both groups were compared), there are differences that occurred in the health guidance group, but in the control group, health indicators did not improve even for those who had a consultation at a medical institution. Dietary guidance (salt intake restriction and adjustment of food balance), exercise habits and treatment effects of pharmacotherapy were more likely to be prominent. Furthermore, by reviewing a subject’s previous or ongoing treatment with a public health nurse, it appeared to be possible to encourage continuation of further treatment while giving advice from the perspective of the patient to more strongly realise the effect of improving lifestyle diseases using medical treatment.
The present study had some limitations. First, selection of the health guidance group and control group was based on whether or not the subject accepted the visit of public health nurses, leading to the possibility of selection bias. Second, approximately 30% of the subjects in both groups did not receive a health check-up in 2015 and were excluded from the analysis. Third, what kind of lifestyle improvement (eg salt/caloric intake and exercise) or behavioural change contributed specifically to the risk of a lifestyle disease in each subject was not sufficiently examined. Although the above points affect the interpretation of the study results, none appear to be a serious problem.
Conclusion
In the present study, we examined the effects of providing specific health guidance to individuals considered at high risk for a lifestyle disease after specific health check-ups. Continued support by Japanese public health nurses through health guidance closely related to the subject’s lifestyle over three years and may lead to a comprehensive reduction in the risk of lifestyle diseases.
Appendix 1