Abstract
Aim: This study aimed to investigate whether the impact of body mass index (BMI) on the risk of cardiovascular disease (CVD) has changed among the 1960s, 1970s, 1980s, 1990s, and early 2000s in Japan.
Methods: The study population consisted of residents in Japan aged 40–69 years who had no history of CVD. The baseline surveys have been conducted every year since 1963. We defined the first, second, third, fourth, and fifth cohorts as 1963–1969 (n=4,248), 1970–1979 (n=6,742), 1980–1989 (n=12,789), 1990–1999 (n=12,537), and 2000–2005 (n=9,140) respectively. The participants were followed up for a median of 15 years for each cohort to determine the incidence of CVD. We classified them into four categories (BMI ＜21.0, 21.0–＜23.0, 23.0–＜25.0, and ≥ 25.0 kg/m2).
Results: From 1963–1969 to 2000–2005, the prevalence of BMI ≥ 25.0 increased over time. Compared with BMI 23.0–＜25.0, the age-, sex- and community-adjusted hazard ratios (95% confidence interval [CIs]) of CVD for BMI ≥ 25.0 were 1.10 (0.77–1.57), 0.89 (0.68–1.18), 1.03 (0.85–1.26), 1.28 (1.04–1.58), and 1.36 (1.04–1.78) in the first, second, third, fourth, and fifth cohorts, respectively. The corresponding population attributable fractions were 2.0% (nonsignificant), −2.6% (nonsignificant), 0.9% (nonsignificant), 7.6%, and 10.9%. Further adjustment for systolic blood pressure and antihypertensive medication use in the fourth and fifth cohorts attenuated the associations, which may reflect that blood pressure may mediate the BMI-CVD association.
Conclusion: The proportion of CVD attributable to overweight/obesity has increased during the periods between 1963–1969 and 2000–2005. The significant associations between overweight/obesity and risk of CVD after the 1990s were mediated by blood pressure levels.
See editorial vol. 30: 323-325
Introduction
In Western countries, overweight (body mass index [BMI] ≥ 25 kg/m2) and obesity (BMI ≥ 30 kg/m2) were associated with increased risk of cardiovascular disease (CVD)1-6). In Japan, the age-adjusted prevalence of overweight/obesity was much lower than that in Western countries, i.e., 32.6% among men and 19.9% among women in Japan in 2019 7), whereas that in 2017–2018 was 73.1% in the United States8). The impact of overweight/obesity on CVD was less attributable than hypertension, diabetes, or dyslipidemia in the Japanese population9). The prevalence of overweight and obesity worldwide has been increasing, especially in developing countries10, 11). Urbanization accompanied by rapid economic growth has caused changes in people’s lifestyles, including increased fat intake and reduced physical activity12-14), leading to the increased prevalence of overweight/obesity. The number of people that are overweight/obese worldwide is projected to increase to approximately 3.3 billion by 2030 from approximately 1.3 billion in 2005 15). In East Asian countries, the prevalence of overweight/obesity has increased with economic growth. In Korean men and Chinese men and women, the prevalence of overweight/obesity increased from 10.6%–24.8% in the 1990s to 32.3%–42.4% in the 2010s16, 17). In Japan, rapid economic growth was achieved from the 1960s to the 1980s, and the crude prevalence of overweight/obesity among men increased from 17.8% in 1980 to 33.0% in 2019, whereas among women, the prevalence was not materially changed7, 18).
Aim
In this context, we sought to investigate whether the impact (relative and attributable risks) of BMI on the risk of CVD changed from the 1960s to 2000s in Japan, which experienced rapid economic growth.
Methods
Study Population
The study population included residents aged 40–69 years who lived in four communities of the Circulatory Risk in Communities Study (CIRCS)19): (community 1) Ikawa, Akita Prefecture; (community 2) Minami-Takayasu District of Yao City, Osaka Prefecture; (community 3) Noichi, Kochi Prefecture; and (community 4) Kyowa District of Chikusei City, Ibaraki Prefecture. The CIRCS is an ongoing dynamic community-based cohort study that started since 1963 19). According to the availability of the data, we defined the first cohort (1963–1969 for community 1, 1964–1969 for community 2, and 1969 for community 3), second cohort (1970–1979 for community 1, 1970–1974 and 1976–1979 for community 2, and 1970–1979 for community 3), third cohort (1980–1989 for communities 1–3 and 1981–1989 for community 4); fourth cohort (1990–1999 for communities 1–4); and fifth cohort (2000–2005 for communities 1–4). The numbers of persons who participated in the baseline survey in the first, second, third, fourth, and fifth cohorts were 5,001 (2,223 men and 2,778 women), 7,595 (3,099 men and 4,496 women), 14,158 (5,787 men and 8,371 women), 13,866 (5,409 men and 8,457 women), and 10,092 (3,770 men and 6,322 women), respectively. After excluding the participants with a history of heart disease or stroke, or with missing information on BMI at the baseline survey, we analyzed data from 4,248 (1,909 men and 2,339 women), 6,742 (2,754 men and 3,988 women), 12,789 (5,240 men and 7,549 women), 12,537 (4,867 men and 7,670 women), and 9,140 (3,347 men and 5,793 women) individuals, respectively.
Baseline Survey
The height (with stocking on) and weight (wearing of light clothing) were measured, and the BMI at baseline was calculated as weight (kg) divided by the square of height (m2). Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured on the right arm by trained physicians or nurses using a standard mercury sphygmomanometer employing standard epidemiological methods after the participant has rested for 5 min in the sitting position20). The serum total cholesterol and serum glucose levels were measured using standardized methods at the laboratory of the Osaka Center for Cancer and Cardiovascular Disease Prevention or Ibaraki Health Service Association.
We conducted a face-to-face interview to obtain information on the use of medication. Information on the history of diabetes was obtained from 1975. Diabetes mellitus was defined as a fasting serum glucose level ≥ 126 mg/dL, non-fasting serum glucose level ≥ 200 mg/dL, or the use of glucose-lowering medication.
Follow-up Survey of Incidence of Cardiovascular Disease
CVD follow-up surveys were conducted from the time of baseline survey until the end of 1980 for the first cohort, end of 1988 for the second cohort, end of 1999 for the third cohort, end of 2007 for the fourth cohort, and end of 2019 in Ikawa, 2018 in Minami-Takayasu District, 2009 in Noichi, and 2015 in Kyowa District for the fifth cohort. The median follow-up years were 15.0, 14.7, 15.1, 15.1, and 15.1, respectively. Incident CVD was defined as first-ever stroke and coronary heart disease (CHD). Details of the CVD registration system in CIRCS were described in our previous report19). In brief, we extracted information on the possible cases of incident CVD from the death certificate, national health insurance claim, report by local physicians, public health nurses and community health volunteers, annual cardiovascular risk surveys, and/or household visited surveys. To confirm the epidemiological diagnosis of CVD, all suspected patients or their families were called, visited, or invited to take part in a cardiovascular risk survey to obtain a history of the incidence. In addition, we reviewed medical records at local clinics and hospitals.
Stroke was diagnosed through neurological symptoms with rapid onset and that persisted at least 24 h after onset or until death. CHD (definite myocardial infarction, possible myocardial infarction, definite angina pectoris, and sudden cardiac death) was diagnosed based on the modified World Health Organization criteria21). Definite myocardial infarction was diagnosed through the following two conditions: (1) typical severe chest pain that persisted for 30 min or more and (2) appearance of abnormal Q or QS wave on the electrocardiogram or consistent change in myocardial enzyme value. The patients who had a symptom of (1) but not (2) were diagnosed with possible myocardial infarction. Definite angina pectoris was diagnosed through repeated episodes of chest pain when exerting effort, especially when walking, usually disappearing rapidly after the cessation of effort or the use of sublingual nitroglycerin. Sudden cardiac death was defined as death within 1 h from onset, except for other obvious causes of death. Finally, several physician-epidemiologists determined the incidence of stroke or CHD using the same diagnostic criteria of CVD, blinded to the data from the cardiovascular risk survey.
Statistical Analysis
In the present study, we stratified the participants into four categories (＜21.0, 21.0–＜23.0, 23.0–＜25.0, and ≥ 25.0 kg/m2) and used 23.0–＜25.0 as the reference. The person-years for each individual were calculated as the follow-up period from the time at baseline survey until the occurrence of CVD, death, emigration from the community, or end of follow-up. For the CVD subtype analysis, the person-years for the people who developed both stroke and CHD during the follow-up were calculated until the occurrence of stroke if the stroke was the outcome or that of CHD if CHD was the outcome. The absolute risk (age- and sex-adjusted incidence rate/1000 person-years) was adjusted with the direct method using the STDRATE procedure (version 9.4 SAS Institute, Cary, NC, USA). The sum of person-years from cohorts 1 to 5 for each group combining age categories (40–49, 50–59, and 60–69 years) and sex was set as the reference for the direct method. Age- (years), sex-, and community-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated according to the BMI categories using Cox proportional hazards model compared with the reference category. The population attributable fraction (PAF) was calculated using the formula: PAF=pdi×[(HR–1)/HR], where pdi denotes the proportion of the cases of each BMI category to the total cases, and HR indicates age-, sex-, and community-adjusted HR of each BMI category with 95% CI for PAF22, 23). To consider the effect of aging from cohorts 1 to 5 on the results, we conducted stratified analyses by age categories (40–49, 50–59, and 60–69 years).
Two approaches were applied to examine mediation on the association between overweight/obesity and risk of CVD when the association was statistically significant. First, we added serum total cholesterol (quartiles in each cohort), history of diabetes, and blood pressure (continuous SBP and antihypertensive medication use) separately to the age-, sex-, and community-adjusted HR model to determine whether the association between overweight/obesity and risk of CVD was attenuated through mediation. Second, we calculated the magnitude of mediating effect via traditional mediation analysis using the following formula24): the percentage of mediation effect=(HR with the basic model–HR with adjustment model)/(HR with the basic model–1)×100. HR with the basic model indicates the age-, sex-, and community-adjusted HR, and HR with adjustment model added each mediator separately to the basic model.
We conducted all analyses using SAS (version 9.4 SAS Institute, Cary, NC, USA). P values less than 0.05 in a two-sided test were regarded as statistically significant.
The CIRCS protocol was approved by the Ethics Committee of Osaka Center for Cancer and Cardiovascular Disease Prevention, Osaka University, and University of Tsukuba.
Results
After a median of approximately 15 years of follow-up for each cohort, the incident cases for the first, second, third, fourth, and fifth cohorts were 274 CVDs (226 strokes and 52 CHDs), 444 CVDs (351 strokes and 99 CHDs), 752 CVDs (571 strokes and 192 CHDs), 612 CVDs (451 strokes and 181 CHDs), and 338 CVDs (235 strokes and 110 CHDs), respectively.
As presented in Table 1, the proportions of BMI 23.0–＜25.0 and ≥ 25.0 increased from cohorts 1 to 5, whereas those of BMI ＜21.0 and 21.0–＜23.0 decreased in the same period, i.e., from 29.1% to 22.7% for ＜21.0, from 29.1% to 23.9% for 21.0–＜23.0, from 21.0% to 24.4% for 23.0–＜25.0, and from 20.7% to 29.0% for BMI ≥ 25.0. The mean SBP, DBP, serum total cholesterol, and proportion of antihypertensive medication use tended to be higher for the higher BMI categories in all cohorts. The proportion of history of diabetes tended to be higher for the higher BMI categories in cohort 5. In each BMI category, the serum total cholesterol level increased from cohorts 1 to 5.
Table 1.
Mean values (standard deviation) and proportions of cardiovascular risk factors at baseline according to body mass index (BMI) categories for 5 baseline periods from 1963 to 2005
|
BMI (kg/m2)
|
| ＜21.0 |
21.0-＜23.0 |
23.0-＜25.0 |
≥ 25.0 |
| First cohort (1963-1969) |
|
|
|
|
| No. at risk |
1237 |
1238 |
892 |
881 |
| Proportion, % |
29.1 |
29.1 |
21.0 |
20.7 |
| Age, years |
53.2 (8.5) |
51.8 (8.2) |
51.6 (8.2) |
52.4 (7.9) |
| Male, % |
45.6 |
52.7 |
45.5 |
32.6 |
| Systolic blood pressure, mmHg |
132.7 (21.9) |
135.7 (23.3) |
139.7 (23.8) |
142.4 (23.4) |
| Diastolic blood pressure, mmHg |
77.9 (11.6) |
79.6 (12.3) |
82.8 (12.8) |
84.6 (12.2) |
| Anti-hypertensive medication use, % |
2.6 |
2.9 |
5.0 |
7.4 |
| Serum total cholesterol, mg/dl |
169.4 (32.6) |
170.2 (33.4) |
174.7 (35.3) |
188.1 (39.2) |
| History of diabetes, % |
- |
- |
- |
- |
| Second cohort (1970-1979) |
|
|
|
|
| No. at risk |
2023 |
1786 |
1418 |
1515 |
| Proportion, % |
30.0 |
26.5 |
21.0 |
22.5 |
| Age, years |
53.1 (9.0) |
51.7 (8.8) |
51.3 (8.5) |
51.6 (8.5) |
| Male, % |
43.0 |
46.9 |
41.5 |
30.2 |
| Systolic blood pressure, mmHg |
132.2 (20.8) |
135.5 (21.8) |
136.4 (19.7) |
140.9 (20.1) |
| Diastolic blood pressure, mmHg |
77.9 (11.4) |
80.6 (12.1) |
82.2 (11.6) |
85.0 (11.6) |
| Anti-hypertensive medication use, % |
6.6 |
7.3 |
9.9 |
14.5 |
| Serum total cholesterol, mg/dl |
180.3 (31.7) |
183.5 (32.0) |
186.1 (33.2) |
193.0 (34.7) |
| History of diabetes, % |
- |
- |
- |
- |
| Third cohort (1980-1989) |
|
|
|
|
| No. at risk |
3142 |
3365 |
3004 |
3278 |
| Proportion, % |
24.6 |
26.3 |
23.5 |
25.6 |
| Age, years |
52.8 (9.0) |
51.5 (8.7) |
51.7 (8.5) |
52.4 (8.4) |
| Male, % |
42.8 |
43.0 |
41.5 |
36.6 |
| Systolic blood pressure, mmHg |
130.1 (21.2) |
133.0 (20.7) |
135.9 (20.1) |
140.9 (20.6) |
| Diastolic blood pressure, mmHg |
76.6 (11.9) |
79.2 (11.7) |
81.7 (11.5) |
85.1 (11.8) |
| Anti-hypertensive medication use, % |
6.7 |
8.8 |
11.8 |
18.4 |
| Serum total cholesterol, mg/dl |
182.9 (33.2) |
189.2 (34.0) |
194.6 (35.4) |
199.8 (36.3) |
| History of diabetes, % |
3.9 |
3.7 |
4.6 |
5.8 |
| Fourth cohort (1990-1999) |
|
|
|
|
| No. at risk |
2905 |
3220 |
3049 |
3363 |
| Proportion, % |
23.2 |
25.7 |
24.3 |
26.8 |
| Age, years |
52.9 (9.4) |
52.9 (9.0) |
53.3 (8.8) |
53.8 (8.7) |
| Male, % |
35.1 |
38.0 |
42.4 |
39.6 |
| Systolic blood pressure, mmHg |
128.1 (20.3) |
131.0 (20.0) |
135.3 (19.8) |
139.6 (20.3) |
| Diastolic blood pressure, mmHg |
76.5 (11.2) |
78.9 (11.4) |
81.7 (11.6) |
84.9 (11.8) |
| Anti-hypertensive medication use, % |
6.1 |
8.3 |
11.4 |
18.0 |
| Serum total cholesterol, mg/dl |
193.5 (34.7) |
197.4 (35.0) |
202.9 (35.9) |
208.5 (35.8) |
| History of diabetes, % |
3.2 |
2.9 |
4.6 |
6.0 |
| Fifth cohort (2000-2005) |
|
|
|
|
| No. at risk |
2074 |
2185 |
2233 |
2648 |
| Proportion, % |
22.7 |
23.9 |
24.4 |
29.0 |
| Age, years |
53.9 (9.0) |
55.3 (8.4) |
56.2 (8.1) |
56.3 (8.3) |
| Male, % |
25.5 |
35.3 |
41.6 |
42.3 |
| Systolic blood pressure, mmHg |
125.4 (18.3) |
130.2 (18.2) |
134.9 (18.2) |
138.9 (18.6) |
| Diastolic blood pressure, mmHg |
76.4 (10.8) |
79.6 (10.9) |
82.3 (10.9) |
85.1 (11.3) |
| Anti-hypertensive medication use, % |
6.9 |
10.0 |
15.2 |
21.3 |
| Serum total cholesterol, mg/dl |
206.4 (35.8) |
210.9 (36.2) |
215.3 (35.8) |
216.2 (35.1) |
| History of diabetes, % |
3.7 |
4.9 |
5.9 |
7.0 |
Table 2 presents the HRs (95% CIs) and PAFs of CVD according to the BMI categories in five cohorts. Compared with the persons with BMI 23.0–＜25.0, the age-, sex-, and community-adjusted HRs (95% CIs) and PAFs of CVD for BMI ≥ 25.0 increased from cohorts 1 to 5. The age-, sex-, and community-adjusted HRs (95% CIs, PAFs) of CVD for BMI ≥ 25.0 were 1.10 (0.77–1.57, 2.0% [nonsignificant]), 0.89 (0.68–1.18, −2.6% [nonsignificant]), 1.03 (0.85–1.26, 0.9% [nonsignificant]), 1.28 (1.04–1.58, 7.6%), and 1.36 (1.04–1.78, 10.9%) in cohorts 1, 2, 3, 4, and 5, respectively. Regarding the subtypes of CVD, there was an increasing trend for HRs and PAFs of stroke for BMI ≥ 25.0 (Table 3). The corresponding HRs (95% CIs, PAFs) of stroke were 1.23 (0.83–1.83, 4.3% [nonsignificant]), 0.83 (0.61–1.13, −4.5% [nonsignificant]), 1.22 (0.97–1.53, 5.5% [nonsignificant]), 1.25 (0.98–1.60, 6.7% [nonsignificant]), and 1.42 (1.03–1.97, 12.6%). For CHD, the HRs for BMI ≥ 25.0 were higher in cohorts 4 and 5, but those were not statistically significant (HRs: 1.30 [95% CIs: 0.89–1.88] in cohort 4 and 1.35 [0.85–2.15] in cohort 5; Table 4). The HRs and PAFs of BMI ≥ 25.0 for incident CVD and stroke tended to increase from cohorts 1 to 5 in all age categories, especially among individuals aged 40–49 years. We could not calculate the HRs and PAFs of CHD among those aged 40–49 years in cohort 5 because of the small number of CHD cases (Supplemental Tables 1, 2, 3).
Table 2.
Hazard ratios (HRs), 95% confidence intervals (CIs) and population-attributable fractions (PAFs) for cardiovascular disease according to body mass index (BMI) categories for 5 baseline periods from 1963 to 2005
|
BMI (kg/m2)
|
| ＜21.0 |
21.0 - ＜23.0 |
23.0 - ＜25.0 |
≥ 25.0 |
| First cohort (1963-1969) |
|
|
|
|
| Person-years |
17530 |
17362 |
12570 |
12355 |
| No. at risk |
1237 |
1238 |
892 |
881 |
| No. cases |
55 |
97 |
62 |
60 |
| Age- and sex-adjusted incident rate/1000 person-years |
3.0 |
5.8 |
5.7 |
5.5 |
| Age-, sex- and community-adjusted HR |
0.59 (0.41-0.85) |
1.08 (0.79-1.49) |
1.00 |
1.10 (0.77-1.57) |
| PAF (%) |
-13.9 (-24.2 to -4.4) |
2.7 (-8.7 to 12.9) |
- |
2.0 (-5.9 to 9.2) |
| Second cohort (1970-1979) |
|
|
|
|
| Person-years |
28582 |
24856 |
19308 |
20887 |
| No. at risk |
2023 |
1786 |
1418 |
1515 |
| No. cases |
131 |
112 |
105 |
96 |
| Age- and sex-adjusted incident rate/1000 person-years |
4.4 |
4.6 |
6.2 |
5.7 |
| Age-, sex- and community-adjusted HR |
0.69 (0.54-0.90) |
0.75 (0.58-0.98) |
1.00 |
0.89 (0.68-1.18) |
| PAF (%) |
-13.0 (-23.0 to -3.8) |
-8.4 (-16.6 to -0.7) |
- |
-2.6 (-9.2 to 3.5) |
| Third cohort (1980-1989) |
|
|
|
|
| Person-years |
44860 |
48701 |
43843 |
48012 |
| No. at risk |
3142 |
3365 |
3004 |
3278 |
| No. cases |
170 |
178 |
190 |
214 |
| Age- and sex-adjusted incident rate/1000 person-years |
3.7 |
3.9 |
4.6 |
4.7 |
| Age-, sex- and community-adjusted HR |
0.80 (0.65-0.99) |
0.85 (0.69-1.04) |
1.00 |
1.03 (0.85-1.26) |
| PAF (%) |
-5.6 (-11.0 to -0.5) |
-4.3 (-9.8 to 0.8) |
- |
0.9 (-4.7 to 6.2) |
| Fourth cohort (1990-1999) |
|
|
|
|
| Person-years |
39078 |
44269 |
41966 |
45827 |
| No. at risk |
2905 |
3220 |
3049 |
3363 |
| No. cases |
114 |
136 |
151 |
211 |
| Age- and sex-adjusted incident rate/1000 person-years |
2.9 |
3.0 |
3.5 |
4.5 |
| Age-, sex- and community-adjusted HR |
0.83 (0.65-1.06) |
0.88 (0.70-1.11) |
1.00 |
1.28 (1.04-1.58) |
| PAF (%) |
-3.8 (-8.9 to 1.0) |
-3.0 (-8.7 to 2.4) |
- |
7.6 (1.1 to 13.7) |
| Fifth cohort (2000-2005) |
|
|
|
|
| Person-years |
27520 |
29819 |
30431 |
35493 |
| No. at risk |
2074 |
2185 |
2233 |
2648 |
| No. cases |
59 |
53 |
86 |
140 |
| Age- and sex-adjusted incident rate/1000 person-years |
2.2 |
1.6 |
2.2 |
3.3 |
| Age-, sex- and community-adjusted HR |
0.98 (0.70-1.36) |
0.70 (0.50-0.99) |
1.00 |
1.36 (1.04-1.78) |
| PAF (%) |
-0.4 (-6.4 to 5.3) |
-6.7 (-13.2 to -0.5) |
- |
10.9 (1.1 to 19.8) |
PAF was calculated using age-, sex-, and community-adjusted HR.
Table 3.
Hazard ratios (HRs), 95% confidence intervals (CIs) and population-attributable fractions (PAFs) for stroke according to body mass index (BMI) categories for 5 baseline periods from 1963 to 2005
|
BMI (kg/m2)
|
| ＜21.0 |
21.0 - ＜23.0 |
23.0 - ＜25.0 |
≥ 25.0 |
| First cohort (1963-1969) |
|
|
|
|
| Person-years |
17567 |
17406 |
12622 |
12372 |
| No. at risk |
1237 |
1238 |
892 |
881 |
| No. cases |
46 |
80 |
48 |
52 |
| Age- and sex-adjusted incident rate/1000 person-years |
2.6 |
4.9 |
4.4 |
4.7 |
| Age-, sex- and community-adjusted HR |
0.64 (0.43-0.96) |
1.15 (0.81-1.65) |
1.00 |
1.23 (0.83-1.83) |
| PAF (%) |
-11.4 (-22.6 to -1.2) |
4.7 (-7.7 to 15.6) |
- |
4.3 (-4.3 to 12.2) |
| Second cohort (1970-1979) |
|
|
|
|
| Person-years |
28699 |
24951 |
19394 |
20993 |
| No. at risk |
2023 |
1786 |
1418 |
1515 |
| No. cases |
101 |
88 |
87 |
75 |
| Age- and sex-adjusted incident rate/1000 person-years |
3.4 |
3.7 |
5.1 |
4.2 |
| Age-, sex- and community-adjusted HR |
0.65 (0.49-0.87) |
0.72 (0.53-0.96) |
1.00 |
0.83 (0.61-1.13) |
| PAF (%) |
-15.6 (-27.1 to -5.2) |
-10.0 (-19.4 to -1.4) |
- |
-4.5 (-12.0 to 2.6) |
| Third cohort (1980-1989) |
|
|
|
|
| Person-years |
45044 |
48941 |
44131 |
48197 |
| No. at risk |
3142 |
3365 |
3004 |
3278 |
| No. cases |
127 |
134 |
133 |
177 |
| Age- and sex-adjusted incident rate/1000 person-years |
2.8 |
3.0 |
3.2 |
3.9 |
| Age-, sex- and community-adjusted HR |
0.86 (0.68-1.10) |
0.91 (0.72-1.16) |
1.00 |
1.22 (0.97-1.53) |
| PAF (%) |
-3.6 (-9.6 to 2.1) |
-2.3 (-8.4 to 3.5) |
- |
5.5 (-1.0 to 11.6) |
| Fourth cohort (1990-1999) |
|
|
|
|
| Person-years |
39193 |
44444 |
42175 |
46156 |
| No. at risk |
2905 |
3220 |
3049 |
3363 |
| No. cases |
92 |
101 |
108 |
150 |
| Age- and sex-adjusted incident rate/1000 person-years |
2.3 |
2.2 |
2.5 |
3.1 |
| Age-, sex- and community-adjusted HR |
0.92 (0.70-1.22) |
0.91 (0.69-1.19) |
1.00 |
1.25 (0.98-1.60) |
| PAF (%) |
-1.7 (-7.8 to 4.0) |
-2.3 (-8.9 to 3.9) |
- |
6.7 (-0.9 to 13.7) |
| Fifth cohort (2000-2005) |
|
|
|
|
| Person-years |
27642 |
29919 |
30580 |
35791 |
| No. at risk |
2074 |
2185 |
2233 |
2648 |
| No. cases |
45 |
33 |
57 |
100 |
| Age- and sex-adjusted incident rate/1000 person-years |
1.7 |
0.9 |
1.5 |
2.4 |
| Age-, sex- and community-adjusted HR |
1.12 (0.76-1.66) |
0.66 (0.43-1.02) |
1.00 |
1.42 (1.03-1.97) |
| PAF (%) |
2.1 (-5.3 to 9.0) |
-7.1 (-14.6 to -0.1) |
- |
12.6 (0.5 to 23.2) |
PAF was calculated using age-, sex-, and community-adjusted HR.
Table 4.
Hazard ratio (HRs), 95% confidence intervals (CIs) and population-attributable fractions (PAFs) for coronary heart disease according to body mass index (BMI) categories for 5 baseline periods from 1963 to 2005
|
BMI (kg/m2)
|
| ＜21.0 |
21.0 - ＜23.0 |
23.0 - ＜25.0 |
≥ 25.0 |
| First cohort (1963-1969) |
|
|
|
|
| Person-years |
17623 |
17649 |
12747 |
12519 |
| No. at risk |
1237 |
1238 |
892 |
881 |
| No. cases |
11 |
18 |
14 |
9 |
| Age- and sex-adjusted incident rate/1000 person-years |
0.6 |
1.0 |
1.2 |
0.9 |
| Age-, sex- and community-adjusted HR |
0.51 (0.23-1.14) |
0.88 (0.44-1.76) |
1.00 |
0.75 (0.32-1.74) |
| PAF (%) |
-20.0 (-47.1 to 2.1) |
-4.9 (-34.7 to 18.3) |
- |
-5.9 (-24.0 to 9.6) |
| Second cohort (1970-1979) |
|
|
|
|
| Person-years |
28938 |
25234 |
19724 |
21184 |
| No. at risk |
2023 |
1786 |
1418 |
1515 |
| No. cases |
31 |
25 |
20 |
23 |
| Age- and sex-adjusted incident rate/1000 person-years |
1.0 |
0.9 |
1.1 |
1.5 |
| Age-, sex- and community-adjusted HR |
0.88 (0.50-1.55) |
0.88 (0.49-1.59) |
1.00 |
1.21 (0.66-2.21) |
| PAF (%) |
-4.4 (-25.5 to 13.2) |
-3.4 (-20.7 to 11.4) |
- |
4.0 (-9.6 to 15.9) |
| Third cohort (1980-1989) |
|
|
|
|
| Person-years |
45491 |
49446 |
44503 |
48978 |
| No. at risk |
3142 |
3365 |
3004 |
3278 |
| No. cases |
47 |
47 |
59 |
39 |
| Age- and sex-adjusted incident rate/1000 person-years |
1.0 |
1.0 |
1.4 |
0.9 |
| Age-, sex- and community-adjusted HR |
0.70 (0.48-1.04) |
0.72 (0.49-1.05) |
1.00 |
0.62 (0.41-0.93) |
| PAF (%) |
-10.3 (-22.2 to 0.4) |
-9.8 (-21.5 to 0.8) |
- |
-12.6 (-23.5 to -2.6) |
| Fourth cohort (1990-1999) |
|
|
|
|
| Person-years |
39498 |
44805 |
42569 |
46671 |
| No. at risk |
2905 |
3220 |
3049 |
3363 |
| No. cases |
28 |
39 |
48 |
66 |
| Age- and sex-adjusted incident rate/1000 person-years |
0.7 |
0.9 |
1.1 |
1.4 |
| Age-, sex- and community-adjusted HR |
0.68 (0.43-1.08) |
0.82 (0.54-1.25) |
1.00 |
1.30 (0.89-1.88) |
| PAF (%) |
-7.3 (-16.3 to 1.0) |
-4.8 (-15.3 to 4.8) |
- |
8.3 (-4.3 to 19.4) |
| Fifth cohort (2000-2005) |
|
|
|
|
| Person-years |
27706 |
30033 |
30752 |
36075 |
| No. at risk |
2074 |
2185 |
2233 |
2648 |
| No. cases |
15 |
21 |
29 |
45 |
| Age- and sex-adjusted incident rate/1000 person-years |
0.6 |
0.6 |
0.7 |
1.0 |
| Age-, sex- and community-adjusted HR |
0.77 (0.41-1.44) |
0.84 (0.48-1.47) |
1.00 |
1.35 (0.85-2.15) |
| PAF (%) |
-4.1 (-14.0 to 5.0) |
-3.7 (-16.0 to 7.3) |
- |
10.6 (-7.2 to 25.3) |
PAF was calculated using age-, sex-, and community-adjusted HR.
Supplemental Table 1.
Hazard ratios (HRs), 95% confidence intervals (CIs), and population-attributable fractions (PAFs) of body mass index (BMI) ≥ 25.0 kg/m
2 versus BMI 23.0-＜25.0 kg/m
2 for cardiovascular disease, stratified by age categories
|
40-49 years |
50-59 years |
60-69 years |
| Total |
BMI (kg/m2)
|
Total |
BMI (kg/m2)
|
Total |
BMI (kg/m2)
|
|
23.0 -
＜25.0
|
≥ 25.0 |
23.0 -
＜25.0
|
≥ 25.0 |
23.0 -
＜25.0
|
≥ 25.0 |
| First cohort (1963-1969) |
|
|
|
|
|
|
|
|
|
| Person-years |
25672 |
5924 |
4921 |
20973 |
4120 |
4943 |
13173 |
2526 |
2491 |
| No. at risk |
1788 |
413 |
348 |
1474 |
291 |
346 |
986 |
188 |
187 |
| No. of cases |
57 |
12 |
16 |
93 |
20 |
22 |
124 |
30 |
22 |
| Age-, sex- and area-adjusted HR |
- |
1.00 |
1.94 (0.91-4.13) |
- |
1.00 |
1.09 (0.59-2.01) |
- |
1.00 |
0.80 (0.46-1.40) |
| PAF |
- |
- |
13.6 (-3.5 to 28.0) |
- |
- |
1.9 (-12.9 to 14.8) |
- |
- |
-4.4 (-16.1 to 6.1) |
| Second cohort (1970-1979) |
|
|
|
|
|
|
|
|
|
| Person-years |
41477 |
8962 |
9507 |
30237 |
6602 |
7078 |
21918 |
3744 |
4302 |
| No. at risk |
3004 |
661 |
694 |
2100 |
465 |
491 |
1638 |
292 |
330 |
| No. of cases |
79 |
24 |
12 |
143 |
33 |
33 |
222 |
48 |
51 |
| Age-, sex- and area-adjusted HR |
- |
1.00 |
0.51 (0.25-1.01) |
- |
1.00 |
0.98 (0.60-1.59) |
- |
1.00 |
0.99 (0.67-1.47) |
| PAF |
- |
- |
-14.8 (-30.3 to -1.2) |
- |
- |
-0.5 (-12.5 to 10.2) |
- |
- |
-0.2 (-9.8 to 8.6) |
| Third cohort (1980-1989) |
|
|
|
|
|
|
|
|
|
| Person-years |
80455 |
19633 |
20146 |
61934 |
14849 |
16810 |
43027 |
9361 |
11055 |
| No. at risk |
5519 |
1355 |
1354 |
4160 |
994 |
1134 |
3110 |
655 |
790 |
| No. of cases |
144 |
44 |
42 |
281 |
72 |
90 |
327 |
74 |
82 |
| Age-, sex- and area-adjusted HR |
- |
1.00 |
0.89 (0.59-1.37) |
- |
1.00 |
1.15 (0.84-1.57) |
- |
1.00 |
0.98 (0.71-1.34) |
| PAF |
- |
- |
-3.5 (-17.4 to 8.8) |
- |
- |
4.1 (-5.7 to 12.9) |
- |
- |
-0.6 (-8.9 to 7.1) |
| Fourth cohort (1990-1999) |
|
|
|
|
|
|
|
|
|
| Person-years |
65991 |
15989 |
15807 |
53850 |
13487 |
15721 |
51299 |
12490 |
14299 |
| No. at risk |
4841 |
1154 |
1169 |
3825 |
951 |
1132 |
3871 |
944 |
1062 |
| No. of cases |
82 |
19 |
38 |
195 |
50 |
75 |
335 |
82 |
98 |
| Age-, sex- and area-adjusted HR |
- |
1.00 |
2.00 (1.15-3.47) |
- |
1.00 |
1.35 (0.94-1.93) |
- |
1.00 |
1.07 (0.80-1.44) |
| PAF |
- |
- |
23.2 (3.7 to 38.7) |
- |
- |
10.0 (-2.6 to 20.9) |
- |
- |
1.9 (-6.7 to 9.9) |
| Fifth cohort (2000-2005) |
|
|
|
|
|
|
|
|
|
| Person-years |
33860 |
7062 |
8484 |
44668 |
11563 |
12733 |
44735 |
11806 |
14276 |
| No. at risk |
2430 |
502 |
621 |
3192 |
820 |
909 |
3518 |
911 |
1118 |
| No. of cases |
26 |
3 |
15 |
82 |
22 |
33 |
230 |
61 |
92 |
| Age-, sex- and area-adjusted HR |
- |
1.00 |
4.01 (1.16-13.85) |
- |
1.00 |
1.35 (0.78-2.31) |
- |
1.00 |
1.23 (0.89-1.71) |
| PAF |
- |
- |
43.3 (5.4 to 66.0) |
- |
- |
10.3 (-10.2 to 27.0) |
- |
- |
7.6 (-4.7 to 18.4) |
PAF was calculated using age-, sex-, and community-adjusted HR.
Supplemental Table 2.
Hazard ratios (HRs), 95% confidence intervals (CIs), and population-attributable fractions (PAFs) of body mass index (BMI) ≥ 25.0 kg/m
2 versus BMI 23.0-＜25.0 kg/m
2 for stroke, stratified by age categories
|
40-49 years |
50-59 years |
60-69 years |
| Total |
BMI (kg/m2)
|
Total |
BMI (kg/m2)
|
Total |
BMI (kg/m2)
|
|
23.0 -
＜25.0
|
≥ 25.0 |
23.0 -
＜25.0
|
≥ 25.0 |
23.0 -
＜25.0
|
≥ 25.0 |
| First cohort (1963-1969) |
|
|
|
|
|
|
|
|
|
| Person-years |
25701 |
5932 |
4929 |
21007 |
4123 |
4952 |
13259 |
2567 |
2491 |
| No. at risk |
1788 |
413 |
348 |
1474 |
291 |
346 |
986 |
188 |
187 |
| No. of cases |
42 |
9 |
12 |
82 |
16 |
20 |
102 |
23 |
20 |
| Age-, sex- and area-adjusted HR |
- |
1.00 |
2.04 (0.86-4.89) |
- |
1.00 |
1.26 (0.65-2.44) |
- |
1.00 |
0.94 (0.51-1.73) |
| PAF |
- |
- |
14.6 (-5.6 to 30.9) |
- |
- |
5.0 (-10.6 to 18.3) |
- |
- |
-1.3 (-14.5 to 10.3) |
| Second cohort (1970-1979) |
|
|
|
|
|
|
|
|
|
| Person-years |
41572 |
8981 |
9507 |
30395 |
6648 |
7134 |
22070 |
3765 |
4352 |
| No. at risk |
3004 |
661 |
694 |
2100 |
465 |
491 |
1638 |
292 |
330 |
| No. of cases |
61 |
21 |
10 |
105 |
23 |
26 |
185 |
43 |
39 |
| Age-, sex- and area-adjusted HR |
- |
1.00 |
0.48 (0.22-1.02) |
- |
1.00 |
1.10 (0.63-1.94) |
- |
1.00 |
0.83 (0.53-1.28) |
| PAF |
- |
- |
-18.0 (-36.7 to -1.8) |
- |
- |
2.3 (-11.9 to 14.7) |
- |
- |
-4.5 (-15.2 to 5.2) |
| Third cohort (1980-1989) |
|
|
|
|
|
|
|
|
|
| Person-years |
80711 |
19746 |
20206 |
62236 |
14929 |
16854 |
43367 |
9457 |
11137 |
| No. at risk |
5519 |
1355 |
1354 |
4160 |
994 |
1134 |
3110 |
655 |
790 |
| No. of cases |
103 |
28 |
31 |
220 |
53 |
80 |
248 |
52 |
66 |
| Age-, sex- and area-adjusted HR |
- |
1.00 |
1.02 (0.61-1.70) |
- |
1.00 |
1.39 (0.98-1.97) |
- |
1.00 |
1.12 (0.78-1.61) |
| PAF |
- |
- |
0.5 (-16.1 to 14.7) |
- |
- |
10.3 (-1.0 to 20.2) |
- |
- |
2.8 (-6.8 to 11.5) |
| Fourth cohort (1990-1999) |
|
|
|
|
|
|
|
|
|
| Person-years |
66121 |
16015 |
15878 |
54148 |
13570 |
15836 |
51699 |
12589 |
14441 |
| No. at risk |
4841 |
1154 |
1169 |
3825 |
951 |
1132 |
3871 |
944 |
1062 |
| No. of cases |
54 |
13 |
25 |
140 |
35 |
55 |
257 |
60 |
70 |
| Age-, sex- and area-adjusted HR |
- |
1.00 |
1.89 (0.97-3.71) |
- |
1.00 |
1.36 (0.89-2.08) |
- |
1.00 |
1.04(0.73-1.46) |
| PAF |
- |
- |
21.8 (-3.3 to 40.8) |
- |
- |
10.4 (-4.8 to 23.4) |
- |
- |
0.9 (-8.8 to 9.8) |
| Fifth cohort (2000-2005) |
|
|
|
|
|
|
|
|
|
| Person-years |
33908 |
7062 |
8514 |
44908 |
11633 |
12834 |
45117 |
11885 |
14444 |
| No. at risk |
2430 |
502 |
621 |
3192 |
820 |
909 |
3518 |
911 |
1118 |
| No. of cases |
19 |
3 |
11 |
47 |
11 |
20 |
169 |
43 |
69 |
| Age-, sex- and area-adjusted HR |
- |
1.00 |
2.94 (0.82-10.54) |
- |
1.00 |
1.62 (0.77-3.37) |
- |
1.00 |
1.26 (0.86-1.85) |
| PAF |
- |
- |
38.2 (-12.6 to 66.1) |
- |
- |
16.2 (-11.4 to 37.0) |
- |
- |
8.5 (-6.1 to 21.2) |
PAF was calculated using age-, sex-, and community-adjusted HR.
Supplemental Table 3.
Hazard ratios (HRs), 95% confidence intervals (CIs), and population-attributable fractions (PAFs) of body mass index (BMI) ≥ 25.0 kg/m
2 versus BMI 23.0-＜25.0 kg/m
2 for coronary heart disease, stratified by age categories
|
40-49 years |
50-59 years |
60-69 years |
| Total |
BMI (kg/m2)
|
Total |
BMI (kg/m2)
|
Total |
BMI (kg/m2)
|
|
23.0 -
＜25.0
|
≥25.0 |
23.0 -
＜25.0
|
≥25.0 |
23.0 -
＜25.0
|
≥25.0 |
| First cohort (1963-1969) |
|
|
|
|
|
|
|
|
|
| Person-years |
25804 |
5960 |
4963 |
21276 |
4184 |
5019 |
13458 |
2603 |
2537 |
| No. at risk |
1788 |
413 |
348 |
1474 |
291 |
346 |
986 |
188 |
187 |
| No. of cases |
16 |
3 |
5 |
11 |
4 |
2 |
25 |
7 |
2 |
| Age-, sex- and area-adjusted HR |
- |
1.00 |
2.15 (0.51-9.11) |
- |
1.00 |
0.48 (0.09-2.61) |
- |
1.00 |
0.35 (0.07-1.73) |
| PAF |
- |
- |
16.7 (-20.8 to 42.6) |
- |
- |
-20.0 (-72.8 to 16.7) |
- |
- |
-14.6 (-36.0 to 3.5) |
| Second cohort (1970-1979) |
|
|
|
|
|
|
|
|
|
| Person-years |
41747 |
9069 |
9558 |
30707 |
6714 |
7193 |
22627 |
3941 |
4434 |
| No. at risk |
3004 |
661 |
694 |
2100 |
465 |
491 |
1638 |
292 |
330 |
| No. of cases |
19 |
3 |
2 |
41 |
11 |
9 |
39 |
6 |
12 |
| Age-, sex- and area-adjusted HR |
- |
1.00 |
0.72 (0.12-4.32) |
- |
1.00 |
0.82 (0.34-1.98) |
- |
1.00 |
2.14 (0.80-5.73) |
| PAF |
- |
- |
-4.1 (-28.7 to 15.8) |
- |
- |
-4.9 (-28.8 to 14.5) |
- |
- |
16.4 (-6.6 to 34.4) |
| Third cohort (1980-1989) |
|
|
|
|
|
|
|
|
|
| Person-years |
80981 |
19775 |
20287 |
63069 |
15126 |
17246 |
44368 |
9601 |
11445 |
| No. at risk |
5519 |
1355 |
1354 |
4160 |
994 |
1134 |
3110 |
655 |
790 |
| No. of cases |
42 |
17 |
11 |
66 |
20 |
11 |
84 |
22 |
17 |
| Age-, sex- and area-adjusted HR |
- |
1.00 |
0.65 (0.30-1.38) |
- |
1.00 |
0.49 (0.24-1.03) |
- |
1.00 |
0.70 (0.37-1.32) |
| PAF |
- |
- |
-14.4 (-41.6 to 7.7) |
- |
- |
-17.2 (-36.0 to -1.0) |
- |
- |
-8.7 (-25.3 to 5.8) |
| Fourth cohort (1990-1999) |
|
|
|
|
|
|
|
|
|
| Person-years |
66269 |
16066 |
15937 |
54610 |
13649 |
16051 |
52664 |
12854 |
14683 |
| No. at risk |
4841 |
1154 |
1169 |
3825 |
951 |
1132 |
3871 |
944 |
1062 |
| No. of cases |
29 |
6 |
14 |
59 |
18 |
21 |
93 |
24 |
31 |
| Age-, sex- and area-adjusted HR |
- |
1.00 |
2.33 (0.89-6.07) |
- |
1.00 |
1.10 (0.59-2.07) |
- |
1.00 |
1.18 (0.69-2.02) |
| PAF |
- |
- |
27.6 (-7.4 to 51.1) |
- |
- |
3.3 (-20.6 to 22.5) |
- |
- |
5.2 (-12.6 to 20.1) |
| Fifth cohort (2000-2005) |
|
|
|
|
|
|
|
|
|
| Person-years |
34013 |
7077 |
8570 |
44980 |
11649 |
12860 |
45572 |
12026 |
14646 |
| No. at risk |
2430 |
502 |
621 |
3192 |
820 |
909 |
3518 |
911 |
1118 |
| No. of cases |
7 |
0 |
4 |
36 |
11 |
14 |
67 |
18 |
27 |
| Age-, sex- and area-adjusted HR |
- |
1.00 |
- |
- |
1.00 |
1.13 (0.51-2.50) |
- |
1.00 |
1.31 (0.72-2.38) |
| PAF |
- |
- |
- |
- |
- |
4.6 (-29.0 to 29.4) |
- |
- |
9.5 (-13.8 to 28.0) |
PAF was calculated using age-, sex-, and community-adjusted HR.
Table 5 presents the mediation effects of the selected risk factors on the associations between overweight/obesity and risks of CVD and stroke. The HRs of CVD and stroke for BMI ≥ 25.0 compared with BMI 23.0–＜25.0 were almost unchanged after further adjustment for serum total cholesterol or history of diabetes. When we adjusted further for blood pressure levels (SBP and antihypertensive medication use), those associations were attenuated and no longer statistically significant. The percentage of the mediation effect of blood pressure level on overweight/obesity-CVD risk was 37% in cohort 4 and 21% in cohort 5, whereas that on overweight/obesity-stroke risk was 32% in cohort 5.
Table 5.
Mediation effects of selected risk factors on the associations between overweight/obesity and risks of cardiovascular disease and stroke
|
CVD |
Stroke |
| BMI (kg/m2)
|
Percentage of mediation effect (%) |
BMI (kg/m2)
|
Percentage of mediation effect (%) |
|
23.0 -
＜25.0
|
≥ 25.0 |
23.0 -
＜25.0
|
≥ 25.0 |
| Fourth cohort (1990-1999) |
|
|
|
|
|
|
| Age-, sex- and area-adjusted HR |
1.00 |
1.28 (1.04-1.58) |
- |
- |
- |
- |
| + Total cholesterol |
1.00 |
1.27 (1.03-1.56) |
5 |
- |
- |
- |
| + History of diabetes |
1.00 |
1.26 (1.03-1.56) |
6 |
- |
- |
- |
| + Systolic blood pressure and antihypertensive medication use |
1.00 |
1.18 (0.95-1.45) |
37 |
- |
- |
- |
| Fifth cohort (2000-2005) |
|
|
|
|
|
|
| Age-, sex- and area-adjusted HR |
1.00 |
1.36 (1.04-1.78) |
- |
1.00 |
1.42 (1.03-1.97) |
- |
| + Total cholesterol |
1.00 |
1.37 (1.05-1.79) |
-3 |
1.00 |
1.44 (1.04-1.99) |
-4 |
| + History of diabetes |
1.00 |
1.36 (1.04-1.78) |
-1 |
1.00 |
1.43 (1.03-1.97) |
-1 |
| + Systolic blood pressure and antihypertensive medication use |
1.00 |
1.29 (0.98-1.69) |
21 |
1.00 |
1.28 (0.92-1.79) |
32 |
CVD; cardiovascular disease, BMI; body mass index, CI; confidence interval, HR; hazard ratio.
Discussion
We found that the prevalence of overweight/obesity increased and that the HRs and PAFs of BMI ≥ 25.0 kg/m2 for total CVD, more specifically stroke, increased between the 1960s and early 2000s in the Japanese populations. Similar but nonsignificant trends were observed for CHD, particularly due to the small number of cases. The excessive risks of CVD for BMI ≥ 25.0 kg/m2 in cohorts 4 and 5 were attenuated and no longer statistically significant after adjustment for blood pressure levels, which may reflect that blood pressure may mediate the BMI-CVD association.
We noted two reasons for the increase in the PAF of CVD for BMI ≥ 25.0 kg/m2. First, the absolute risk of stroke in the reference group (BMI 23.0–＜25.0 kg/m2) dramatically decreased from 4.4/1000 person-years in cohort 1 to 1.5/1000 person-years in cohort 5. Our previous observation revealed that the major contributors to the reduced risk of stroke were decreased blood pressure levels, followed by increased serum cholesterol levels from very low levels, partly reflecting improved nutritional status25, 26). The prevalence of hypertension without overweight/obesity was much higher than that of hypertension with overweight/obesity in both men and women aged 40–69 in the 1960s27). Economic development contributed to a reduction in sodium intake and in extremely strenuous labor as farm work due to the use of farming machines26). The community-wide health screening system was established in 1982, and residents aged ≥ 40 years could receive health check-ups to prevent CVD along with universal health insurance25). Community-based health education also contributed to the decline in sodium intake and increased proportion of antihypertensive medication use25, 26). The increased saturated fat intakes caused the rise in serum total cholesterol from the very low levels (mean, 157 mg/dL in men and 163 mg/dL in women) to the moderate levels (179 mg/dL in men and 192 mg/dL in women), which might contribute in part to the decline in intraparenchymal hemorrhage occurrence26). On the other hand, the reduction of stroke incidence rate for BMI ≥ 25.0 kg/m2 from cohorts 1 to 5 was smaller (from 4.7/1000 person-years to 2.4/1000 person-years) than that of the reference category. A possible reason for this finding is that an adverse impact of overweight/obesity on hypertension remained, while other factors associated with overweight/obesity such as elevated systemic inflammation28) might increase overtime.
According to a pooled analysis of the population in East Asia (Japan, Korea, China, Taiwan, and Singapore), high BMI was a risk factor for mortality from CVD, CHD, and stroke29). In the Japan Public Health Center-based Prospective Study (JPHC), compared with BMI 23.0–＜25.0 kg/m2, men with BMI ≥ 30.0 kg/m2 had 1.8 times higher risk of CHD, and women with BMI ≥ 30.0 kg/m2 had 2.2 to 2.5 times higher risks of total, intraparenchymal hemorrhagic, and ischemic strokes after adjustment for history of hypertension and diabetes30, 31). In the Japan Arteriosclerosis Longitudinal Study (JALS) that consolidated 16 Japanese cohorts in Japan, including CIRCS, compared with BMI ＜21.0 kg/m2, men with BMI ≥ 27.5 kg/m2 had 1.5 to 2.1 times higher risks of total CVD, total stroke, ischemic CVD, and myocardial infarction independent of SBP and serum total cholesterol32). In women, BMI was positively associated with the risk of total stroke after adjustment for SBP and serum total cholesterol (P for trend=0.021).
The HRs of CVD and stroke associated with high BMI were attenuated after adjustment for blood pressure, but not serum total cholesterol or history of diabetes. In the Women’s Health Study, the multivariable HR of stroke for BMI ≥ 35.0 kg/m2 compared with BMI ＜20.0 kg/m2 was attenuated and no longer statistically significant after adjustment for history of hypertension3). In JALS, the excessive risks of total CVD and stroke for BMI ≥ 27.5 kg/m2 compared with BMI ＜21.0 kg/m2 were substantially attenuated after adjustment for SBP32).
The strengths of this study are as follows: (1) sufficient follow-up period to consider the trend in BMI and the HR and PAF of incident CVD, (2) an almost-complete CVD surveillance, and (3) the use of standardized methods for physical examinations, including measurements of weight, height, and blood pressure level.
This study has several limitations. First, we used data of weight only at the baseline for each cohort, which may have caused regression dilution bias, because of temporal changes and random errors in the measurement of weight. We calculated the regression dilution rate33) among persons who participated at both baseline and 1–5 years after the baseline surveys. The differences in the mean values of BMI between the top and bottom categories reduced from baseline to 1–5 years after baseline in all cohorts, i.e., from 7.7 to 7.2 kg/m2 in cohort 1 (n=2,285), from 7.8 to 7.4 kg/m2 in cohort 2 (n =4,681), from 7.8 to 7.3 kg/m2 in cohort 3 (n =9,554), from 7.7 to 7.4 kg/m2 in cohort 4 (n =10,281), and from 7.8 to 7.5 kg/m2 in cohort 5 (n =7,538). Based on this, we estimated that the regression dilution rates were 0.93, 0.95, 0.94, 0.96, and 0.96, respectively. Therefore, the regression dilution effect-adjusted HRs should have been 4% to 8% higher than our study result. Second, we did not conduct sex-specific analyses due to the small sample size. Although the interaction of sex and BMI categories in relation to the incident CVD was not significant in this study, previous studies demonstrated that the association between overweight/obesity and risk of CVD was different between men and women30-32). In the JPHC study, the BMI–stroke association was observed only in women, and the BMI–CHD association was only noted in men. In JALS, the BMI–stroke association was observed in both men and women, and the BMI–myocardial infarction association was noted only in men.
Conclusion
In conclusion, the proportion of cardiovascular disease attributable to overweight/obesity has slightly increased between 1963–1969 and 2000–2005. The significant associations between overweight/obesity and risk of CVD after the 1990s were mediated by blood pressure levels.
Acknowledgements
The authors thank the healthcare staffs of surveyed communities, and the Osaka Center for Cancer and Cardiovascular Disease Prevention. The full list of the CIRCS Investigators are listed in Ref. 19.
Sources of Funding
This research was partly supported, by a Grant-in-Aid from the Ministry of Health, Labour and Welfare, Health and Labour Sciences Research Grants, Japan (19-FA1-008 and 20-FA1-002), and the Japan Society for the Promotion of Science (Scientific Research B [19H03901]).
Conflict of Interest
None.
References
- 1) Wilson PW, D’Agostino RB, Sullivan L, Parise H, Kannel WB. Overweight and obesity as determinants of cardiovascular risk: the Framingham experience. Arch Intern Med, 2002; 162: 1867-1872
- 2) Jood K, Jern C, Wilhelmsen L, Rosengren A. Body mass index in mid-life is associated with a first stroke in men: a prospective population study over 28 years. Stroke, 2004; 35: 2764-2769
- 3) Kurth T, Gaziano JM, Rexrode KM, Kase CS, Cook NR, Manson JE, Buring JE. Prospective study of body mass index and risk of stroke in apparently healthy women. Circulation, 2005; 111: 1992-1998
- 4) Wannamethee SG, Shaper AG, Walker M. Overweight and obesity and weight change in middle aged men: impact on cardiovascular disease and diabetes. J Epidemiol Community Health, 2005; 59: 134-139
- 5) Hu G, Tuomilehto J, Silventoinen K, Sarti C, Männistö S, Jousilahti P. Body mass index, waist circumference, and waist-hip ratio on the risk of total and type-specific stroke. Arch Intern Med, 2007; 167: 1420-1427
- 6) Flint AJ, Rexrode KM, Hu FB, Glynn RJ, Caspard H, Manson JE, Willett WC, Rimm EB. Body mass index, waist circumference, and risk of coronary heart disease: a prospective study among men and women. Obes Res Clin Pract, 2010; 4: e171-e181
- 7) Ministry of Health, Labour and Welfare. The National Health and Nutrition Survey in Japan, 2019 [in Japanese]. Ministry of Health, Labour and Welfare, Tokyo. Available from: https: //www.mhlw.go.jp/content/000710991.pdf [Accessed April 30, 2022]
- 8) Fryar CD, Carroll MD, Afful J. Prevalence of overweight, obesity, and severe obesity among adults aged 20 and over: United States, 1960–1962 through 2017–2018. NCHS Health E-Stats. 2020
- 9) Ikeda N, Inoue M, Iso H, Ikeda S, Satoh T, Noda M, Mizoue T, Imano H, Saito E, Katanoda K, Sobue T, Tsugane S, Naghavi M, Ezzati M, Shibuya K. Adult mortality attributable to preventable risk factors for non-communicable diseases and injuries in Japan: a comparative risk assessment. PLoS Med, 2012; 9: e1001160
- 10) Luhar S, Mallinson PAC, Clarke L, Kinra S. Trends in the socioeconomic patterning of overweight/obesity in India: a repeated cross-sectional study using nationally representative data. BMJ Open, 2018; 8: e023935
- 11) Flores-Ortiz R, Malta DC, Velasquez-Melendez G. Adult body weight trends in 27 urban populations of Brazil from 2006 to 2016: A population-based study. PLoS One, 2019; 14: e0213254
- 12) Popkin BM. Urbanization, lifestyle changes and the nutrition transition. World Dev, 1999; 27: 1905-1916
- 13) Yamauchi T, Umezaki M, Ohtsuka R. Influence of urbanisation on physical activity and dietary changes in Huli-speaking population: a comparative study of village dwellers and migrants in urban settlements. Br J Nutr, 2001; 85: 65-73
- 14) Fong TCT, Ho RTH, Yip PSF. Effects of urbanization on metabolic syndrome via dietary intake and physical activity in Chinese adults: Multilevel mediation analysis with latent centering. Soc Sci Med, 2019; 234: 112372
- 15) Kelly T, Yang W, Chen CS, Reynolds K, He J. Global burden of obesity in 2005 and projections to 2030. Int J Obes (Lond), 2008; 32: 1431-1437
- 16) Jang HJ, Oh H. Trends and Inequalities in Overall and Abdominal Obesity by Sociodemographic Factors in Korean Adults, 1998-2018. Int J Environ Res Public Health, 2021; 18: 4162
- 17) Bai R, Wu W, Dong W, Liu J, Yang L, Lyu J. Forecasting the Populations of Overweight and Obese Chinese Adults. Diabetes Metab Syndr Obes, 2020; 13: 4849-4857
- 18) Ministry of Health, Labour and Welfare. The National Health and Nutrition Survey in Japan, 2017 [in Japanese]. Ministry of Health, Labour and Welfare, Tokyo. Available from: https: //www.mhlw.go.jp/content/000681194.pdf [Accessed April 30, 2022]
- 19) Yamagishi K, Muraki I, Kubota Y, Hayama-Terada M, Imano H, Cui R, Umesawa M, Shimizu Y, Sankai T, Okada T, Sato S, Kitamura A, Kiyama M, Iso H. The Circulatory Risk in Communities Study (CIRCS): A Long-Term Epidemiological Study for Lifestyle-Related Disease Among Japanese Men and Women Living in Communities. J Epidemiol, 2019; 29: 83-91
- 20) Kirkendall WM, Feinleib M, Freis ED, Mark AL. Recommendations for human blood pressure determination by sphygmomanometers. Subcommittee of the AHA Postgraduate Education Committee. Circulation, 1980; 62: 1146A-1155A
- 21) Arterial Hypertension and Ischaemic Heart Disease-Preventive Aspects-Report of an Expert Committee; 1962
- 22) Rockhill B, Newman B, Weinberg C. Use and misuse of population attributable fractions. Am J Public Health, 1998; 88: 15-19
- 23) Greenland S. Re: “Confidence limits made easy: interval estimation using a substitution method”. Am J Epidemiol, 1999; 149: 884; author reply 885-886
- 24) Kaufman JS, Maclehose RF, Kaufman S. A further critique of the analytic strategy of adjusting for covariates to identify biologic mediation. Epidemiol Perspect Innov, 2004; 1: 4
- 25) Shimamoto T, Iso H, Iida M, Komachi Y. Epidemiology of cerebrovascular disease: stroke epidemic in Japan. J Epidemiol, 1996; 6: S43-47
- 26) Shimamoto T, Komachi Y, Inada H, Doi M, Iso H, Sato S, Kitamura A, Iida M, Konishi M, Nakanishi N. Trends for coronary heart disease and stroke and their risk factors in Japan. Circulation, 1989; 79: 503-515
- 27) Hori M, Kitamura A, Kiyama M, Imano H, Yamagishi K, Cui R, Umesawa M, Muraki I, Okada T, Sankai T, Ohira T, Saito I, Tanigawa T, Iso H; CIRCS Investigators. Fifty-year Time Trends in Blood Pressures, Body Mass Index and their Relations in a Japanese Community: The Circulatory Risk in Communities Study (CIRCS). J Atheroscler Thromb, 2017; 24: 518-529
- 28) Cercato C, Fonseca FA. Cardiovascular risk and obesity. Diabetol Metab Syndr, 2019; 11: 74.
- 29) Chen Y, Copeland WK, Vedanthan R, Grant E, Lee JE, Gu D, Gupta PC, Ramadas K, Inoue M, Tsugane S, Tamakoshi A, Gao YT, Yuan JM, Shu XO, Ozasa K, Tsuji I, Kakizaki M, Tanaka H, Nishino Y, Chen CJ, Wang R, Yoo KY, Ahn YO, Ahsan H, Pan WH, Chen CS, Pednekar MS, Sauvaget C, Sasazuki S, Yang G, Koh WP, Xiang YB, Ohishi W, Watanabe T, Sugawara Y, Matsuo K, You SL, Park SK, Kim DH, Parvez F, Chuang SY, Ge W, Rolland B, McLerran D, Sinha R, Thornquist M, Kang D, Feng Z, Boffetta P, Zheng W, He J, Potter JD. Association between body mass index and cardiovascular disease mortality in east Asians and south Asians: pooled analysis of prospective data from the Asia Cohort Consortium. BMJ, 2013; 347: f5446
- 30) Chei CL, Iso H, Yamagishi K, Inoue M, Tsugane S. Body mass index and weight change since 20 years of age and risk of coronary heart disease among Japanese: the Japan Public Health Center-Based Study. Int J Obes (Lond), 2008; 32: 144-151
- 31) Saito I, Iso H, Kokubo Y, Inoue M, Tsugane S. Body mass index, weight change and risk of stroke and stroke subtypes: the Japan Public Health Center-based prospective (JPHC) study. Int J Obes (Lond), 2011; 35: 283-291
- 32) Yatsuya H, Toyoshima H, Yamagishi K, Tamakoshi K, Taguri M, Harada A, Ohashi Y, Kita Y, Naito Y, Yamada M, Tanabe N, Iso H, Ueshima H; Japan Arteriosclerosis Longitudinal Study (JALS) group. Body mass index and risk of stroke and myocardial infarction in a relatively lean population: meta-analysis of 16 Japanese cohorts using individual data. Circ Cardiovasc Qual Outcomes, 2010; 3: 498-505
- 33) Clarke R, Shipley M, Lewington S, Youngman L, Collins R, Marmot M, Peto R. Underestimation of risk associations due to regression dilution in long-term follow-up of prospective studies. Am J Epidemiol, 1999; 150: 341-353
