<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">FNS</journal-id><journal-title-group><journal-title>Food and Nutrition Sciences</journal-title></journal-title-group><issn pub-type="epub">2157-944X</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/fns.2017.81002</article-id><article-id pub-id-type="publisher-id">FNS-72693</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Biomedical&amp;Life Sciences</subject></subj-group></article-categories><title-group><article-title>
 
 
  Prevalence of Non-Communicable Diseases and Number of Comorbidities According to Differences in Household Income Levels in Japan: Analysis from National Health and Nutrition Survey
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Chika</surname><given-names>Horikawa</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Nobuko</surname><given-names>Murayama</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Asami</surname><given-names>Ota</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Megumi</surname><given-names>Tsuruta</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Satoshi</surname><given-names>Matsunaga</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Kazuya</surname><given-names>Fujihara</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Osamu</surname><given-names>Hanyu</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Hirohito</surname><given-names>Sone</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>Department of Health and Nutrition, Faculty of Human Life Studies, University of Niigata Prefecture, Niigata, Japan</addr-line></aff><aff id="aff2"><addr-line>Department of Hematology, Endocrinology, and Metabolism, Faculty of Medicine, Niigata University, Niigata, Japan</addr-line></aff><pub-date pub-type="epub"><day>09</day><month>12</month><year>2016</year></pub-date><volume>08</volume><issue>01</issue><fpage>19</fpage><lpage>30</lpage><history><date date-type="received"><day>October</day>	<month>18,</month>	<year>2016</year></date><date date-type="rev-recd"><day>Accepted:</day>	<month>December</month>	<year>9,</year>	</date><date date-type="accepted"><day>December</day>	<month>12,</month>	<year>2016</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  Though it has been reported that in Western developed countries socioeconomic status is associated with non-communicable diseases (NCD), there are sparse evidence from Japan, midst an income gap that has been pointed out in recent years. Therefore, we examined the presence or absence of NCD and the number of comorbidities according to household income in Japanese, using data from the National Health and Nutrition Survey of 2010. 1287 men and 1659 women aged 20 - 79 years from households at 3 income levels (&lt;2, 2 - 5.9, ≥6 million yen) were analyzed. Participants completed questionnaires regarding whether they had been diagnosed with NCD, as well as undergoing clinical laboratory tests. Logistic regression analyses were used for statistical analysis with adjustment for age, gender, household size, and population of municipalities. The prevalences of participants with high, medium, and low income were 22.3%, 57.6%, and 20.2%, respectively. Participants with the lowest income had the highest odds of hypertension (OR [95% confidence interval (CI)] = 1.71 [1.29 - 2.26], 
  p &lt; 0.001), diabetes (1.50 [1.02 - 2.20], 
  p = 0.041), and stroke (5.07 [2.04 - 12.60] 
  p &lt; 0.001). Additionally, prevalences of participants with 2 or 3 NCD (hypertension, diabetes, and hypercholesterolemia) were 15.0% and 33.0% in high and low income levels, respectively. A low income could contribute to a high prevalence of NCD and large number of comorbidities among Japanese. Establishing a health policy in Japan is needed to enable an optimal health condition and lifestyle regardless of socioeconomic disparities.
 
</p></abstract><kwd-group><kwd>Non-Communicable Diseases</kwd><kwd> Comorbidities</kwd><kwd> Household Income</kwd><kwd> National Health and Nutrition Survey</kwd><kwd> Japan</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Socioeconomic disparities cause health disparities, such as those related to environmental exposures [<xref ref-type="bibr" rid="scirp.72693-ref1">1</xref>] , social environment [<xref ref-type="bibr" rid="scirp.72693-ref2">2</xref>] , psychological characteristics [<xref ref-type="bibr" rid="scirp.72693-ref3">3</xref>] , health care [<xref ref-type="bibr" rid="scirp.72693-ref4">4</xref>] , lifestyle [<xref ref-type="bibr" rid="scirp.72693-ref5">5</xref>] , and behavior [<xref ref-type="bibr" rid="scirp.72693-ref1">1</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref6">6</xref>] and health disparities have become among the most serious problems on a global basis. According to some reports from Western developed countries, there showed that participants with low socioeconomic status have a high risk of obesity, diabetes mellitus, cardiovascular disease [<xref ref-type="bibr" rid="scirp.72693-ref7">7</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref9">9</xref>] , and mortality [<xref ref-type="bibr" rid="scirp.72693-ref10">10</xref>] . Once a disease has developed, the cost of medical care constrains a low- income individual’s financial situation [<xref ref-type="bibr" rid="scirp.72693-ref11">11</xref>] and creates a vicious circle.</p><p>On the other hand, Japan is an Asian developed country that had relatively narrowed the gap between wealth and poverty compared to Western developed countries. About 30 years ago, it was declared that “almost all Japanese are middle-class” [<xref ref-type="bibr" rid="scirp.72693-ref12">12</xref>] , however, the widening of the household income gap in more recent years in Japan is now considered a social problem, and the Gini coefficient of income inequality has increased [<xref ref-type="bibr" rid="scirp.72693-ref13">13</xref>] . Because of the growing interest in the effect of socioeconomic differences on health, a question on household income was added to the questionnaire of the National Health and Nutrition Survey (NHNS) in 2010.</p><p>Providing a scientific basis for the income gap in the Japanese population is of immediate importance in order to develop effective health policies relevant to increasing healthy life expectancy and improving ones’ quality of life, considering the number of persons with non-communicable diseases (NCD) and medical expenses in Japan have been rapidly increasing in the last ten years [<xref ref-type="bibr" rid="scirp.72693-ref14">14</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref15">15</xref>] . As shown by previous studies in Japan, a low socioeconomic position and relative income deprivation were significantly correlated with high mortality rates caused by cardiovascular disease and cancer [<xref ref-type="bibr" rid="scirp.72693-ref16">16</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref17">17</xref>] .</p><p>Nevertheless, evidence for the association between household income and the presence or absence of NCD is limited to studies based on household expenditures and relative income deprivation [<xref ref-type="bibr" rid="scirp.72693-ref18">18</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref19">19</xref>] although NCD is a leading cause of death in Japan [<xref ref-type="bibr" rid="scirp.72693-ref20">20</xref>] . Moreover, there has been no evidence from research on the relationship between household income and number of comorbidities in Japan based on a nationwide setting. Therefore, we aimed this study to explore differences in the prevalence of NCD and the number of comorbidities according to household income from data of the NHNS.</p></sec><sec id="s2"><title>2. Methods</title><sec id="s2_1"><title>2.1. Participants</title><p>Study participants were those who completed the NHNS. The NHNS, conducted in November 2010, included a lifestyle questionnaire survey, dietary intake survey, and physical examination. Participants aged from 1 year or older had measurements of height and weight and a dietary assessment and those aged 20 years or older additionally had blood tests and answered the question on household income. Detailed information regarding the NHNS were described elsewhere [<xref ref-type="bibr" rid="scirp.72693-ref21">21</xref>] . The NHNS is a survey conducted by the Japanese government based on the Health Promotion Law. Those administering this survey agreed to following the Declaration of Helsinki and the ethical guidelines for medical and health research involving human subjects stipulated by the Ministry of Education, Culture, Sports, Science and Technology in Japan and the Ministry of Health, Labor and Welfare. Informed consent was obtained for all enrolled participants. The data obtained were published under the Statistics Act by the Japanese government. Our study was permitted to use the unlinkable anonymizing data by the Ministry of Health, Labor and Welfare for the purpose of this study (ID 0813-2 approved on August 13, 2015). Participants in this study were 1287 men and 1659 women aged 20 - 79 years who completed the questionnaire, laboratory tests, and physical examination.</p></sec><sec id="s2_2"><title>2.2. Assessments of Participants</title><p>Participants’ characteristics were surveyed by a physical examination that included measurements of weight, height, body mass index (BMI), systolic blood pressure (SBP), and diastolic blood pressure (DBP) and laboratory tests to determine values for HbA1c, random blood glucose (RBG), serum HDL-cholesterol (HDL-C), serum LDL-choles- terol (LDL-C), and serum triglycerides (TG). Screening status for NCD including hypertension (HT), diabetes mellitus (DM), hypercholesterolemia (HC), stroke, and coronary heart disease (CHD) were obtained by self-reported questionnaires on whether participants had been diagnosed with any of those diseases and/or whether participants had been or were being treated with medication (antihypertensive agents, oral hypoglycemic agents and/or insulin, and cholesterol-lowering agents).</p><p>Household income per year was assessed by a question with four options (High: ≥6 million yen, Middle: 2 - 5.9 million yen, Low: &lt;2 million yen, and “Don’t know”). Households that had non-responders or responders who selected multiple options were excluded from the current analysis. Other assessments included household size and population of municipalities (cities with populations of ≥150,000, ≥50,000, &lt;150,000, or &lt;50,000).</p></sec><sec id="s2_3"><title>2.3. Statistical Analysis</title><p>Participants’ characteristics were described as mean &#177;SD or percentage. The relationship of household income to clinical characteristics and nutritional intake were then examined using one-way ANOVA. Logistic regression analyses were used to estimate the adjusted odds ratios (OR) and 95% confidence interval (CI) for whether participants had HT, diabetes, HC, stroke, or CHD. We also investigated ORs for the number of the following combinations of NCD according to household income level: HT and DM, HT and HC, DM and HC, and HT, DM, and HC. ORs were also investigated for stroke combined with 1 or more among HT, DM, and/or HC and CHD combined with at least 1 or more among HT, DM, and/or HC. Adjusted analyses were conducted with adjustment for age, gender, household size, and population of municipalities. All p values are two-sided, and the significance level is 0.05. All statistical analyses and data management were conducted using SPSS version 23 (IBM Corp., Armonk, NY, USA).</p></sec></sec><sec id="s3"><title>3. Results</title><p><xref ref-type="table" rid="table1">Table 1</xref> shows the characteristics of 2,946 participants according to household income.</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Characteristics of the participants according to household income: National Health and Nutrition Survey, Japan, 2010</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="2"  >Household income (yen/year)</th><th align="center" valign="middle" >Total (N = 2946)</th><th align="center" valign="middle" >High (N = 656)</th><th align="center" valign="middle" >Middle (N = 1696)</th><th align="center" valign="middle" >Low (N = 594)</th><th align="center" valign="middle"  rowspan="2"  >p for trend</th></tr></thead><tr><td align="center" valign="middle" >Mean &#177; SD</td><td align="center" valign="middle" >Mean &#177; SD</td><td align="center" valign="middle" >Mean &#177; SD</td><td align="center" valign="middle" >Mean &#177; SD</td></tr><tr><td align="center" valign="middle" >Age (year)</td><td align="center" valign="middle" >56.9 &#177; 14.5</td><td align="center" valign="middle" >52.0 &#177; 12.7</td><td align="center" valign="middle" >56.6 &#177; 15.0</td><td align="center" valign="middle" >63.3 &#177; 12.7</td><td align="center" valign="middle" >&lt;0.001a</td></tr><tr><td align="center" valign="middle" >Men (%)</td><td align="center" valign="middle" >43.7%</td><td align="center" valign="middle" >40.8%</td><td align="center" valign="middle" >46.3%</td><td align="center" valign="middle" >39.1%</td><td align="center" valign="middle" >0.032b</td></tr><tr><td align="center" valign="middle" >Height (cm)</td><td align="center" valign="middle" >159.3 &#177; 9.2</td><td align="center" valign="middle" >160.9 &#177; 8.8</td><td align="center" valign="middle" >159.8 &#177; 9.1</td><td align="center" valign="middle" >156.1 &#177; 8.9</td><td align="center" valign="middle" >&lt;0.001a</td></tr><tr><td align="center" valign="middle" >Weight (kg)</td><td align="center" valign="middle" >59.1 &#177; 11.6</td><td align="center" valign="middle" >59.3 &#177; 12.1</td><td align="center" valign="middle" >59.7 &#177; 11.7</td><td align="center" valign="middle" >57.3 &#177; 10.8</td><td align="center" valign="middle" >&lt;0.001a</td></tr><tr><td align="center" valign="middle" >Body mass index (kg/m<sup>2</sup>)</td><td align="center" valign="middle" >23.2 &#177; 3.5</td><td align="center" valign="middle" >22.7 &#177; 3.4</td><td align="center" valign="middle" >23.3 &#177; 3.4</td><td align="center" valign="middle" >23.4 &#177; 3.5</td><td align="center" valign="middle" >&lt;0.001a</td></tr><tr><td align="center" valign="middle" >Systolic blood pressure (mmHg)</td><td align="center" valign="middle" >132.9 &#177; 19.9</td><td align="center" valign="middle" >128.0 &#177; 19.0</td><td align="center" valign="middle" >132.6 &#177; 19.4</td><td align="center" valign="middle" >139.3 &#177; 20.3</td><td align="center" valign="middle" >&lt;0.001a</td></tr><tr><td align="center" valign="middle" >Diastolic blood pressure (mmHg)</td><td align="center" valign="middle" >80.3 &#177; 11.4</td><td align="center" valign="middle" >79.6 &#177; 11.4</td><td align="center" valign="middle" >80.3 &#177; 11.3</td><td align="center" valign="middle" >81.1 &#177; 11.8</td><td align="center" valign="middle" >0.05a</td></tr><tr><td align="center" valign="middle" >Random blood glucose (mg/dl)</td><td align="center" valign="middle" >104.2 &#177; 33.8</td><td align="center" valign="middle" >99.6 &#177; 25.7</td><td align="center" valign="middle" >103.7 &#177; 33.9</td><td align="center" valign="middle" >110.5 &#177; 40.2</td><td align="center" valign="middle" >&lt;0.001a</td></tr><tr><td align="center" valign="middle" >HbA1c (%)</td><td align="center" valign="middle" >5.4 &#177; 0.8</td><td align="center" valign="middle" >5.4 &#177; 0.7</td><td align="center" valign="middle" >5.4 &#177; 0.8</td><td align="center" valign="middle" >5.5 &#177; 0.9</td><td align="center" valign="middle" >0.002a</td></tr><tr><td align="center" valign="middle" >Total cholesterol (mg/dl)</td><td align="center" valign="middle" >206.0 &#177; 35.4</td><td align="center" valign="middle" >207.8 &#177; 34.6</td><td align="center" valign="middle" >205.3 &#177; 34.5</td><td align="center" valign="middle" >206.2 &#177; 38.5</td><td align="center" valign="middle" >0.31a</td></tr><tr><td align="center" valign="middle" >LDL-cholesterol (mg/dl)</td><td align="center" valign="middle" >119.1 &#177; 31.2</td><td align="center" valign="middle" >119.9 &#177; 30.7</td><td align="center" valign="middle" >119.1 &#177; 30.3</td><td align="center" valign="middle" >117.9 &#177; 34.0</td><td align="center" valign="middle" >0.52a</td></tr><tr><td align="center" valign="middle" >HDL-cholesterol (mg/dl)</td><td align="center" valign="middle" >62.3 &#177; 16.1</td><td align="center" valign="middle" >64.3 &#177; 16.3</td><td align="center" valign="middle" >62.1 &#177; 15.7</td><td align="center" valign="middle" >60.5 &#177; 16.8</td><td align="center" valign="middle" >&lt;0.001a</td></tr><tr><td align="center" valign="middle" >Triglycerides (mg/dl)</td><td align="center" valign="middle" >136.5 &#177; 99.1</td><td align="center" valign="middle" >133.3 &#177; 96.3</td><td align="center" valign="middle" >132.4 &#177; 90.0</td><td align="center" valign="middle" >151.8 &#177; 122.7</td><td align="center" valign="middle" >&lt;0.001a</td></tr><tr><td align="center" valign="middle" >Household size (person)</td><td align="center" valign="middle" >3.0 &#177; 1.5</td><td align="center" valign="middle" >3.6 &#177; 1.4</td><td align="center" valign="middle" >3.0 &#177; 1.5</td><td align="center" valign="middle" >2.3 &#177; 1.5</td><td align="center" valign="middle" >&lt;0.001a</td></tr><tr><td align="center" valign="middle"  colspan="2"  >Population size of municipalities</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle"  colspan="2"  >&lt;50,000 (%)</td><td align="center" valign="middle" >19.5%</td><td align="center" valign="middle" >57.9%</td><td align="center" valign="middle" >22.6%</td><td align="center" valign="middle" >0.002b</td></tr><tr><td align="center" valign="middle"  colspan="2"  >≥50,000 - &lt;150,000 (%)</td><td align="center" valign="middle" >20.3%</td><td align="center" valign="middle" >57.8%</td><td align="center" valign="middle" >21.9%</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle"  colspan="2"  >≥150,000 (%)</td><td align="center" valign="middle" >25.1%</td><td align="center" valign="middle" >57.3%</td><td align="center" valign="middle" >17.7%</td><td align="center" valign="middle" ></td></tr></tbody></table></table-wrap><p>a. One-way ANOVA was used. b. Chi-square test was used. Household income (yen): high (≥6 million), middle (≥2 million and &lt;6 million) and low (&lt;2 million).</p><p>Mean age of participants was 56.9 years and percentage of men was 43.7%. Participants in the low household income group were significantly older and had significantly lower BMI, higher SBP, higher RBG and HbA1c, lower HDL-C, and higher TG compared with those with high household income. There was a significant association between low household income and small household size and small population of municipalities.</p><p><xref ref-type="table" rid="table2">Table 2</xref> shows the ORs for NCD of the participants according to household income. In the logistic regression model where adjustments were made for age, gender, household size, and population size of municipalities, the lowest household income was associated with a significantly high prevalence of HT (OR [95% (CI)] = 1.71 [1.29 to 2.26], p &lt; 0.001), DM (1.50 [1.02 to 2.20], p = 0.041), and stroke (5.07 [2.04 to 12.60] p &lt; 0.001). There was no significant difference between household income and prevalence of HC (p for trend = 0.73). When the participants at the middle and low income levels were combined, these participants had a 2.02-fold prevalence of CHD compared with participants at a high income level (p = 0.045).</p><p><xref ref-type="table" rid="table3">Table 3</xref> shows the ORs for the number of prevalent NCD according to household</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Odds ratios for prevalence of non-communicable diseases among participants according to household income: National Health and Nutrition Survey, Japan, 2010</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  colspan="2"  >High (N = 656)</th><th align="center" valign="middle"  colspan="2"  >Middle (N = 1696)</th><th align="center" valign="middle"  colspan="2"  >Low (N = 594)</th><th align="center" valign="middle"  rowspan="2"  >p for trend</th></tr></thead><tr><td align="center" valign="middle"  colspan="2"  >OR</td><td align="center" valign="middle" >OR(95%CI)</td><td align="center" valign="middle" >p value</td><td align="center" valign="middle" >OR(95%CI)</td><td align="center" valign="middle" >p value</td></tr><tr><td align="center" valign="middle"  colspan="7"  >Hypertension</td></tr><tr><td align="center" valign="middle" >No. cases</td><td align="center" valign="middle" >153 (23%)</td><td align="center" valign="middle"  colspan="2"  >577 (34%)</td><td align="center" valign="middle"  colspan="2"  >290 (49%)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Not adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >1.70 (1.38 to 2.09)</td><td align="center" valign="middle" >&lt;0.001</td><td align="center" valign="middle" >3.14 (2.46 to 4.00)</td><td align="center" valign="middle" >&lt;0.001</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" >Adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >1.25 (0.99 to 1.57)</td><td align="center" valign="middle" >0.06</td><td align="center" valign="middle" >1.71 (1.29 to 2.26)</td><td align="center" valign="middle" >&lt;0.001</td><td align="center" valign="middle" >0.001</td></tr><tr><td align="center" valign="middle"  colspan="7"  >Diabetes</td></tr><tr><td align="center" valign="middle" >No. cases</td><td align="center" valign="middle" >53 (8%)</td><td align="center" valign="middle"  colspan="2"  >229 (14%)</td><td align="center" valign="middle"  colspan="2"  >112 (19%)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Not adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >1.78 (1.30 to 2.43)</td><td align="center" valign="middle" >&lt;0.001</td><td align="center" valign="middle" >2.64 (1.87 to 3.74)</td><td align="center" valign="middle" >&lt;0.001</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" >Adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >1.30 (0.93 to 1.81)</td><td align="center" valign="middle" >0.12</td><td align="center" valign="middle" >1.50 (1.02 to 2.20)</td><td align="center" valign="middle" >0.041</td><td align="center" valign="middle" >0.12</td></tr><tr><td align="center" valign="middle"  colspan="7"  >Hypercholesterolemia</td></tr><tr><td align="center" valign="middle" >No. cases</td><td align="center" valign="middle" >227 (35%)</td><td align="center" valign="middle"  colspan="2"  >635 (37%)</td><td align="center" valign="middle"  colspan="2"  >260 (44%)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Not adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >1.13 (0.94 to 1.37)</td><td align="center" valign="middle" >0.20</td><td align="center" valign="middle" >1.47 (1.17 to 1.85)</td><td align="center" valign="middle" >0.001</td><td align="center" valign="middle" >0.003</td></tr><tr><td align="center" valign="middle" >Adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >0.92 (0.76 to 1.13)</td><td align="center" valign="middle" >0.44</td><td align="center" valign="middle" >0.92 (0.72 to 1.19)</td><td align="center" valign="middle" >0.55</td><td align="center" valign="middle" >0.73</td></tr><tr><td align="center" valign="middle"  colspan="7"  >Stroke</td></tr><tr><td align="center" valign="middle" >No. cases</td><td align="center" valign="middle" >6 (1%)</td><td align="center" valign="middle"  colspan="2"  >57 (3%)</td><td align="center" valign="middle"  colspan="2"  >41 (7%)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Not adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >3.77 (1.62 to 8.78)</td><td align="center" valign="middle" >0.002</td><td align="center" valign="middle" >8.03 (3.38 to 19.06)</td><td align="center" valign="middle" >&lt;0.001</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" >Adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >2.74 (1.15 to 6.50)</td><td align="center" valign="middle" >0.022</td><td align="center" valign="middle" >5.07 (2.04 to 12.60)</td><td align="center" valign="middle" >&lt;0.001</td><td align="center" valign="middle" >0.001</td></tr><tr><td align="center" valign="middle"  colspan="7"  >Coronary heart disease</td></tr><tr><td align="center" valign="middle" >No. cases</td><td align="center" valign="middle" >10 (2%)</td><td align="center" valign="middle"  colspan="2"  >77 (5%)</td><td align="center" valign="middle"  colspan="2"  >28 (5%)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Not adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >3.07 (1.58 to 5.97)</td><td align="center" valign="middle" >0.001</td><td align="center" valign="middle" >3.20 (1.54 to 6.64)</td><td align="center" valign="middle" >0.002</td><td align="center" valign="middle" >0.003</td></tr><tr><td align="center" valign="middle" >Adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >2.08 (1.05 to 4.16)</td><td align="center" valign="middle" >0.037</td><td align="center" valign="middle" >1.77 (0.81 to 3.87)</td><td align="center" valign="middle" >0.15</td><td align="center" valign="middle" >0.10</td></tr></tbody></table></table-wrap><p>Abbreviations: confidence interval, CI; odds ratios, OR. Adjusted analyses were conducted with adjustment for age, gender, household size, and population size of municipalities.</p><table-wrap-group id="3"><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Odds ratios for number of non-communicable diseases among participants according to household income: National Health and Nutrition Survey, Japan, 2010</title></caption><table-wrap id="3_1"><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="2"  ></th><th align="center" valign="middle" >High (N = 656)</th><th align="center" valign="middle"  colspan="2"  >Middle (N = 1696)</th><th align="center" valign="middle"  colspan="2"  >Low (N = 594)</th><th align="center" valign="middle"  rowspan="2"  >p for trend</th></tr></thead><tr><td align="center" valign="middle" >OR (95%CI)</td><td align="center" valign="middle" >OR (95%CI)</td><td align="center" valign="middle" >p value</td><td align="center" valign="middle" >OR (95%CI)</td><td align="center" valign="middle" >p value</td></tr><tr><td align="center" valign="middle"  colspan="7"  >Having HT and DM</td></tr><tr><td align="center" valign="middle" >No. cases</td><td align="center" valign="middle" >25 (4%)</td><td align="center" valign="middle" >140</td><td align="center" valign="middle" >(8%)</td><td align="center" valign="middle" >76</td><td align="center" valign="middle" >(13%)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Not adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >2.27 (1.47 to 3.51)</td><td align="center" valign="middle" >&lt;0.001</td><td align="center" valign="middle" >3.70 (2.32 to 5.90)</td><td align="center" valign="middle" >&lt;0.001</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" >Adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >1.54 (0.98 to 2.44)</td><td align="center" valign="middle" >0.06</td><td align="center" valign="middle" >1.87 (1.12 to 3.11)</td><td align="center" valign="middle" >0.017</td><td align="center" valign="middle" >0.06</td></tr><tr><td align="center" valign="middle"  colspan="7"  >Having HT and HC</td></tr><tr><td align="center" valign="middle" >No. cases</td><td align="center" valign="middle" >80 (12%)</td><td align="center" valign="middle" >294</td><td align="center" valign="middle" >(17%)</td><td align="center" valign="middle" >154</td><td align="center" valign="middle" >(26%)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Not adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >1.51 (1.16 to 1.97)</td><td align="center" valign="middle" >0.002</td><td align="center" valign="middle" >3.14 (2.46 to 3.39)</td><td align="center" valign="middle" >&lt;0.001</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" >Adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >1.14 (0.86 to 1.51)</td><td align="center" valign="middle" >0.36</td><td align="center" valign="middle" >1.46 (1.05 to 2.04)</td><td align="center" valign="middle" >0.025</td><td align="center" valign="middle" >0.05</td></tr></tbody></table></table-wrap><table-wrap id="3_2"><table><tbody><thead><tr><th align="center" valign="middle"  colspan="7"  >Having DM and HC</th></tr></thead><tr><td align="center" valign="middle" >No. cases</td><td align="center" valign="middle" >29 (4%)</td><td align="center" valign="middle" >136</td><td align="center" valign="middle" >(8%)</td><td align="center" valign="middle" >74</td><td align="center" valign="middle" >(12%)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Not adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >1.88 (1.25 to 2.84)</td><td align="center" valign="middle" >0.003</td><td align="center" valign="middle" >3.08 (1.97 to 4.80)</td><td align="center" valign="middle" >&lt;0.001</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" >Adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >1.44 (0.94 to 2.21)</td><td align="center" valign="middle" >0.09</td><td align="center" valign="middle" >1.86 (1.15 to 3.02)</td><td align="center" valign="middle" >0.012</td><td align="center" valign="middle" >0.040</td></tr><tr><td align="center" valign="middle"  colspan="7"  >Having HT, DM and HC</td></tr><tr><td align="center" valign="middle" >No. cases</td><td align="center" valign="middle" >18 (3%)</td><td align="center" valign="middle" >85</td><td align="center" valign="middle" >(5%)</td><td align="center" valign="middle" >54</td><td align="center" valign="middle" >(9%)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Not adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >1.87 (1.12 to 3.14)</td><td align="center" valign="middle" >0.018</td><td align="center" valign="middle" >3.54 (2.05 to 6.12)</td><td align="center" valign="middle" >&lt;0.001</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" >Adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >1.35 (0.79 to 2.31)</td><td align="center" valign="middle" >0.27</td><td align="center" valign="middle" >1.99 (1.10 to 3.61</td><td align="center" valign="middle" >0.024</td><td align="center" valign="middle" >0.044</td></tr><tr><td align="center" valign="middle"  colspan="7"  >Having stroke and at least 1 of HT, DM and HC</td></tr><tr><td align="center" valign="middle" >No. cases</td><td align="center" valign="middle" >5 (1%)</td><td align="center" valign="middle" >55</td><td align="center" valign="middle" >(3%)</td><td align="center" valign="middle" >37</td><td align="center" valign="middle" >(6%)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Not adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >4.36 (1.74 to 10.95)</td><td align="center" valign="middle" >0.002</td><td align="center" valign="middle" >8.65 (3.38 to 22.16)</td><td align="center" valign="middle" >&lt;0.001</td><td align="center" valign="middle" >&lt;0.001</td></tr><tr><td align="center" valign="middle" >Adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >3.21 (1.25 to 8.20)</td><td align="center" valign="middle" >0.015</td><td align="center" valign="middle" >5.58 (2.08 to 15.0)</td><td align="center" valign="middle" >0.001</td><td align="center" valign="middle" >0.001</td></tr><tr><td align="center" valign="middle"  colspan="7"  >Having CHD and at least 1 of HT, DM and HC</td></tr><tr><td align="center" valign="middle" >No. cases</td><td align="center" valign="middle" >10 (2%)</td><td align="center" valign="middle" >67</td><td align="center" valign="middle" >(4%)</td><td align="center" valign="middle" >26</td><td align="center" valign="middle" >(4%)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Not adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >2.66 (1.36 to 5.20)</td><td align="center" valign="middle" >0.004</td><td align="center" valign="middle" >2.96 (1.41 to 6.19)</td><td align="center" valign="middle" >0.004</td><td align="center" valign="middle" >0.010</td></tr><tr><td align="center" valign="middle" >Adjusted</td><td align="center" valign="middle" >1.00 (Ref)</td><td align="center" valign="middle" >1.79 (0.89 to 3.60)</td><td align="center" valign="middle" >0.10</td><td align="center" valign="middle" >1.66 (0.75 to 3.68)</td><td align="center" valign="middle" >0.21</td><td align="center" valign="middle" >0.26</td></tr></tbody></table></table-wrap></table-wrap-group><p>Abbreviations: confidence interval, CI; coronary heart disease, CHD; diabetes mellitus, DM; hypercholesterolemia, HC; hypertension, HT; odds ratios, OR. Adjusted analyses were conducted with adjustment for age, gender, household size, and population size of municipalities.</p><p>income level. The adjusted ORs for having HT and DM, HT and HC, and DM and HC among participants with a high income level compared with those with a low income level was 1.87 [1.12 to 3.11] (p = 0.017), 1.46 [1.05 to 2.04] (p = 0.025), and 1.86 [1.15 o 3.02] (p = 0.012), respectively. According to the presence of HT, DM, and HC, there was a significantly higher prevalence among participants at the low income level than at the high income level (HR [95%CI] = 1.99 [1.10 to 3.61], p = 0.024). The prevalence of having stroke and at least 1 among HT, DM, and HC in participants with a low income level was also significantly higher compared with those with a high income level (HR [95%CI] = 5.88 [2.08 to 15.0], p = 0.001). There was no significant difference between household income and prevalence of having CHD and at least 1 condition among HT, DM, and HC (p = 0.21).</p><p><xref ref-type="fig" rid="fig1">Figure 1</xref> shows the prevalences of HT, DM, and HC in participants according to household income level. The prevalences of participants with neither HT, DM, nor HC were 51.7%, 43.6%, and 30.6% in the high, middle, and low income level, respectively. As to having 1 disease among HT, DM, and HC, prevalences of participants at high, middle, and low income levels were 33.4%, 32.7%, and 36.4%, respectively. The prevalences of participants with 2 diseases among HT, DM, and HC were 12.3%, 18.5%, and 23.9%, and those with having all 3 diseases, HT, DM, and HC, were 2.7%, 5.0%, and 9.1% in the high, middle, and low income level, respectively.]</p></sec><sec id="s4"><title>4. Discussion</title><p>In this current study, we determined that there were differences in the prevalence of</p><fig id="fig1"  position="float"><label><xref ref-type="fig" rid="fig1">Figure 1</xref></label><caption><title> Summary of prevalence of hypertension, diabetes, and hypercholesterolemia of participants according to household income level: National Health and Nutrition Survey, Japan, 2010. Household income (yen): high (≥6 million), middle (≥2 million and &lt;6 million) and low (&lt;2 million). Abbreviations: coronary heart disease, CHD; diabetes mellitus, DM; hypercholesterolemia, HC; hypertension, HT</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/2-2702035x2.png"/></fig><p>NCD and the number of comorbidities according to household income in Japanese participants in the NHNS. High prevalence of NCD were observed in participants with a low household income, which supports previous reports from Western developed countries [<xref ref-type="bibr" rid="scirp.72693-ref7">7</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref9">9</xref>] . Of concern is that only 30.6% of participants with a low income was free from HT, DM, and HC, but more than half at the high income level was free from these diseases. Participants with multiple risk factors have a greater risk of cardiovascular disease and mortality [<xref ref-type="bibr" rid="scirp.72693-ref22">22</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref23">23</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref24">24</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref25">25</xref>] . Cardiovascular disease is the most common cause of death after cancer [<xref ref-type="bibr" rid="scirp.72693-ref20">20</xref>] , therefore, proactive screening and control of NCD would be especially important for participants having a low income.</p><p>Although the current observational study could not reveal cause-effect relationships, plausible findings have been reported, suggesting reasons that a low household income is associated with NCD and a greater number of comorbidities. As for the association between income level and food intake in Japanese, we recently reported that household members with low and middle incomes had a significantly higher intake of cereals and a lower intake of vegetables, fruit, and fish compared with those with high incomes [<xref ref-type="bibr" rid="scirp.72693-ref26">26</xref>] . The price of grains and grain products is lower for supplying energy than foods such as fish, vegetables, and fruit according to market prices in Japan [<xref ref-type="bibr" rid="scirp.72693-ref27">27</xref>] . It is well known that vegetables and fruit are good sources of vitamins, minerals, and fiber, which are vital for maintaining health. For example, micronutrients, including vitamins and minerals, enable the optimal transformation of dietary energy sources such as carbohydrate, fat, and protein [<xref ref-type="bibr" rid="scirp.72693-ref28">28</xref>] . Vitamins, predominantly vitamins C and E, and carotenoids prevent organ damage by reactive oxygen species [<xref ref-type="bibr" rid="scirp.72693-ref29">29</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref30">30</xref>] . Fibers slow gastric emptying and small bowel transit, interfere with the mixing of foodstuffs and digestive enzymes, and disrupt micelle formation [<xref ref-type="bibr" rid="scirp.72693-ref31">31</xref>] , and have been associated with improved glucose metabolism [<xref ref-type="bibr" rid="scirp.72693-ref32">32</xref>] . As to fish, it is rich in omega-3 fatty acids, including eicosapentaenoic acid and docosahexaenoic acid, and these essential fats significantly decrease blood pressure and reduce inflammatory processes, vasoconstriction, and platelet aggregation, all known to be antiatherogenic [<xref ref-type="bibr" rid="scirp.72693-ref33">33</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref34">34</xref>] . On the other hand, high consumption of foods such as grains that contain a high percentage of carbohydrates promotes high serum glucose [<xref ref-type="bibr" rid="scirp.72693-ref35">35</xref>] and TG levels but also promotes low HDL-C and LDL-C levels [<xref ref-type="bibr" rid="scirp.72693-ref36">36</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref37">37</xref>] because of the relative reduction of fat intake relevant to cholesterogenesis. Considering the features of nutrients relevant to each food group and our current study that showed those with a low income level had high cereal intake and low vegetable, fruit, and fish intakes, it can be speculated that the characteristics of the dietary intake of Japanese with a low income level were related to their blood pressure and blood test values and were responsible for the high prevalence of HT, DM, and stroke.</p><p>Additionally, previous reports showed an association with a low income level and fewer occasions of regular physical activity and chronic stress than among those with higher incomes [<xref ref-type="bibr" rid="scirp.72693-ref38">38</xref>] . It is well recognized that an increment in physical activity improves blood pressure, blood glucose, blood lipids, and lipoproteins [<xref ref-type="bibr" rid="scirp.72693-ref39">39</xref>] , and that chronic stress has an impact on neurotransmission and metabolism, resulting in elevations in blood pressure and blood glucose and enhanced lipoprotein synthesis [<xref ref-type="bibr" rid="scirp.72693-ref40">40</xref>] . Factors other than dietary habits need consideration in order to decrease NCD in persons with low incomes.</p><p>Once blood pressure control or the metabolic balance worsens caused by inappropriate intake of carbohydrate, fat, or protein and micronutrients resulting from the factors noted above, compensatory regulation occurs in metabolism for other nutritional and/or neurotransmitter activities caused by hormonal secretion [<xref ref-type="bibr" rid="scirp.72693-ref41">41</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref42">42</xref>] . Therefore, the above-mentioned suggest reasons for the elevated prevalence of participants having multiple NCD in those with low income levels compared with high income levels.</p><p>Previous studies reported that persons with multiple chronic diseases have fair or poor general health and high psychological distress and feel dissatisfied, unhappy, or terrible about their lives [<xref ref-type="bibr" rid="scirp.72693-ref43">43</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref44">44</xref>] . Furthermore, participants with multiple diseases incurred higher medical costs over a long duration than those without or having only 1 disease [<xref ref-type="bibr" rid="scirp.72693-ref45">45</xref>] . Therefore, the financial situations of low-income individuals would go from bad to worse in the presence of illness. Support for good control of NCD and for preventing onset of other diseases should be developed for low income Japanese.</p><p>In an effort to improve nutritional intake and metabolic characteristics related to NCD for people with low household income, Western developed countries are already using various approaches such as teaching skills for coping with stress and improving relationship skills [<xref ref-type="bibr" rid="scirp.72693-ref46">46</xref>] , food aids such as food programs [<xref ref-type="bibr" rid="scirp.72693-ref47">47</xref>] , and health coaching for lifestyle-style habits and preventing chronic disease [<xref ref-type="bibr" rid="scirp.72693-ref48">48</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref49">49</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref50">50</xref>] . These strategies were reported to be effective for participants to acquire appropriate knowledge and motivation and improve metabolic characteristics [<xref ref-type="bibr" rid="scirp.72693-ref46">46</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref48">48</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref49">49</xref>] [<xref ref-type="bibr" rid="scirp.72693-ref50">50</xref>] . However, practical research regarding health and nutrition policies for low-income Japanese is sparse. Moreover, we clarified that Japanese with a low income tended to have high carbohydrate and low animal fat and protein intake unlike low-income Western people. These results would be caused by differences between Asian and Western people in racial and ethnic-specific lifestyles and culture including dietary habits. Further studies are needed considering racial and ethnic-specific dietary patterns and lifestyle characteristics to explore effective health and nutrition policies, including those in Japan.</p><p>The present study had several limitations. First, as a cross-sectional study rather than a longitudinal or intervention study, we could not conclude cause-effect relationships as to how household income differences would affect NCD. Second, the potential for bias, such as response to a questionnaire on household income and whether having diseases or not, cannot be ruled out entirely although those who created the NHNS were public health experts. Another limitation is that the NHNS that included the questionnaire about household income and prevalence of NCD was first performed in 2010; therefore, we could not compare responses to the NHNS of previous years. The same survey should be routinely performed to monitor domestic situations.</p></sec><sec id="s5"><title>5. Conclusion</title><p>In conclusion, we determined from responses to the NHNS that differences in income level would contribute to a high prevalence of NCD and a number of comorbidities in Japanese. Based on preliminary findings, further study is required to establish health policies that would enable an optimal health condition and lifestyle regardless of socioeconomic disparities.</p></sec><sec id="s6"><title>Acknowledgements</title><p>This work was supported by a Health and Labour Sciences Research Grant, Japan (Comprehensive Research on Life Style-Related Diseases Including Cardiovascular Diseases and Diabetes Mellitus [H24-Jyunkankitou-Seisyu-Ippan-006]).</p><p>The research organizations that provided funding for this research did not have any role in the design and conduct of the study; correction, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. The authors declare that there is no conflict of interest associated with this manuscript.</p></sec><sec id="s7"><title>Cite this paper</title><p>Horikawa, C., et al. (2017) Prevalence of Non-Communicable Diseases and Number of Comorbidities According to Differences in Household Income Levels in Japan: Analysis from National Health and Nutrition Survey. Food and Nutrition Sciences, 8, 19-30. http://dx.doi.org/10.4236/fns.2017.81002</p></sec></body><back><ref-list><title>References</title><ref id="scirp.72693-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Pamuk, E., Makuc, D., Heck, K., et al. (1998) Socioeconomic Status and Health Chartbook. US Department of Health and Human Services, Washington DC.</mixed-citation></ref><ref id="scirp.72693-ref2"><label>2</label><mixed-citation publication-type="other" xlink:type="simple">Sampson, R.J., Raudenbush, S.W. and Earls, F. (1997) Neighborhoods and Violent Crime: A Multilevel Study of Collective Efficacy. 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