EXPLORING THE ASSOCIATION OF LIFE-STYLE FACTORS AND HEALTH RELATED ISSUES WITH THE NON-COMMUNICABLE DISEASES: A GENDER-BASED STUDY ON NFHS-4 (2015-16), INDIA

Abstract

NCDs are one of the major causes of increasing death toll in India. Diabetes, asthma and cardiovascular diseases are taken into consideration in this study as these diseases are highly prevalent among all NCDs. This study aims to assess the association of lifestyle factors and other health issues with the risk of these three diseases for both the genders. Simultaneously, it will examine the differences between the crude odds ratio and adjusted odds ratio based on the selected-factors. Adjusted and Crude Logistic Regression has been used in National Family Health Survey, 2015-16 data (Demographic Health Survey, DHS of India) for the study. Prevalence of diabetes was higher among men, whereas asthma and cardiovascular diseases were found more prevalent among women. Marginalised sections have shown less prevalence of diabetes and more prevalence of asthma and cardiovascular diseases. In conclusion, smoking, tobacco and alcohol consumption, obesity, severe haemoglobin level, very high glucose level were positively correlated with the risk of these three diseases. Also, crude and adjusted odds ratio depicted the clear picture of correlation between specific factors and diseases for men and women.

Full text

EXPLORING THE ASSOCIATION OF LIFE-STYLE FACTORS AND
HEALTH RELATED ISSUES WITH THE NON-COMMUNICABLE
DISEASES: A GENDER-BASED STUDY ON NFHS-4 (2015-16), INDIA
Anuj Singh* and Abhinesh Singh1
DST-Centre for Interdisciplinary Mathematical Sciences, Institute of Science, B.H.U., Varanasi - 221 005, India.
Swabhimaan Project, UNICEF, International Institute for Population Sciences, Mumbai - 400 088, India.
E-mail: anujsingh11185@gmail.com
Abstract: NCDs are one of the major causes of increasing death toll in India. Diabetes, asthma and cardiovascular diseases
are taken into consideration in this study as these diseases are highly prevalent among all NCDs. This study aims to assess
the association of life-style factors and other health issues with the risk of these three diseases for both the genders.
Simultaneously, it will examine the differences between the crude odds ratio and adjusted odds ratio based on the selected-
factors. Adjusted and Crude Logistic Regression has been used in National Family Health Survey, 2015-16 data (Demographic
Health Survey, DHS of India) for the study. Prevalence of diabetes was higher among men, whereas asthma and cardiovascular
diseases were found more prevalent among women. Marginalised sections have shown less prevalence of diabetes and more
prevalence of asthma and cardiovascular diseases. In conclusion, smoking, tobacco and alcohol consumption, obesity,
severe haemoglobin level, very high glucose level were positively correlated with the risk of these three diseases. Also, crude
and adjusted odds ratio depicted the clear picture of correlation between specific factors and diseases for men and women.
Key words:Non-communicable diseases, Cardiovascular diseases, Life-style factors, BMI, Haemoglobin level, Glucose
level.
Cite this article
Anuj Singh and Abhinesh Singh (2022). Exploring the Association of Life-style Factors and Health related issues with the
Non-Communicable Diseases: A Gender-based study on NFHS-4 (2015-16), India. International Journal of Agricultural and
Statistical Sciences. DocID: https://connectjournals.com/03899.2022.18.845
*Author for correspondence Received January 12, 2022 Revised April 27, 2022 Accepted June 29, 2022
Int. J. Agricult. Stat. Sci. Vol. 18, No. 2, pp. 845-854, 2022 www.connectjournals.com/ijass
DocID: https://connectjournals.com/03899.2022.18.845 ISSN: 0973-1903, e-ISSN: 0976-3392
ORIGINAL ARTICLE
1. Introduction
Non-communicable diseases (NCDs)-mainly
cardiovascular diseases, cancers, chronic respiratory
diseases and diabetes are the world’s biggest killers.
More than 36 million people die annually from NCDs
(63% of global deaths) [WHO (2018)]. A quite big
percentage of deaths have been increased worldwide
in last few years only because of NCDs. The reason
of deaths is not only NCDs but the lack of awareness
about this hazardous affliction [Nivedita et al. (2021)].
Demographic change, urbanization, behavioral pattern
and lifestyle changes were the factors behind the
increase of NCDs in India. Simultaneously lack of
preparedness and awareness exaggerate the rise of
NCDs. Social insurance, skilled health workers, and
infrastructure is required to combat NCDs [Upadhyay
(2012)]. With the ongoing demographic and
epidemiological transition in India, India is witnessing a
major shift in disease patterns. Unlike in past decades,
non-communicable diseases (NCDs) are now taking a
major toll on the health of the Indian population. Recent
data suggests that every year about 5.8 million Indians
die from cardiovascular and lung diseases, stroke,
cancer and diabetes [WHO (2014)].
NCDs are often associated with modifiable risk
factors. Data obtained from the National Family Health
Survey-4 (2015-16), India, shows that the dietary risk,
household air pollution from solid fuels and tobacco
smoking are three leading risk factors for major disease
burden in India. Given the growing burden of NCDs in
India, there is a need to have timely information on
NCDs and the associated risk factors at the national

846 Anuj Singh and Abhinesh Singh
and state levels. Such information can act as a baseline
for the projection of future trends and for the formulation
of evidence-based targeted interventions [Singh et al.
(2014)]. Prevalence of NCDs is majorly driven by the
socioeconomic patterning of the population; risk factors
are more prevalent among the marginalized section and
lower wealth quintile population [Yadav et al. (2020)].
Diabetes has been growing at a rapid rate
throughout the world. The complications caused by this
disease are very severe and need to be predicted at an
early stage [Faiz et al. (2021)]. Diabetes showed a
positive and independent association with age, BMI,
physical activity and its prevalence in progenitors. Study
highlighted positive correlation between the prevalence
of diabetes or impaired glucose tolerance with age, and
by place of residence prevalence is higher in urban
areas [Daivadanam et al. (2013), Ramachandran et
al. (2001)]. The elderly populations have increased
three times faster than actual population, this leads to
higher prevalence of diabetes [Yadav et al. (2018)].
Various studies have found that the socioeconomic
conditions, lifestyles, and health conditions differ
between men and women, as does the association of
these factors with hypertension [Inamo et al. (2005)].
There are various unobserved factors which affect
obesity and leads to increase in diabetes and
hypertension [Marbaniang et al. (2021)]. Numerous
studies indicated that the overall prevalence of asthma
in India ranged between two percent to ten percent. A
multi-centric conducted a survey using structured
questionnaire reported that the overall prevalence of
respiratory symptoms in different centers vary from
3% to 11%. The study further highlighted that urban
locality; smoking, passive exposures to tobacco smoke
and combustion of domestic cooking fuels to be
significantly associated, however, exposure to biomass
fuels did not emerge as an important associate of asthma
[Aggarwal et al. (2006)].
Cardiovascular diseases caused 2.3 million deaths
in India in the year 1990; this is projected to double by
the year 2020. However, the urbanization and changing
lifestyles the number of people with diabetes, obesity,
dyslipidemia, or high blood pressure may increase,
suggesting that the increase in CVD based purely on
demographic shifts are likely underestimates [Yusuf et
al. (2001), Patel et al. (2020)]. This study tries to fill
the gap by examining the association between the life-
style factors or health-related factors with the diabetes,
asthma and cardiovascular diseases. Simultaneously,
the study examines the difference between crude odds
ratio and adjusted odds ratio. The findings will also be
helpful to gain adequate knowledge about these diseases
and associated risk factors. Moreover, findings can
further be used for various policy making and formation
of various preventive measures to prevent and cure
such diseases. The objectives of the study are 1): To
examine the correlation of life-style factors and health-
related factors, with the prevalence of diabetes, asthma
and cardiovascular diseases, and 2) To explore the
differences between crude and adjusted odds ratio while
examining the correlation of life style factors and health-
related factors with the prevalence of diabetes, asthma
and cardiovascular diseases.
2. Methods
The National Family Health Survey, India 2015-16
(International Institute for Population Sciences and ICF,
2017) provides nationally representative data on fertility,
mortality, morbidity, nutrition and other important aspects
mainly for Indian households. This study has done
gender-based analysis and uses data for men (15-54
years) and women (15-49 years) regarding their life-
style factors, health-related factors, and prevalence of
diabetes, asthma, and cardiovascular diseases. Three
dependent variables were used which are diabetes,
asthma, and cardiovascular diseases for men and
women. Three broad categories of independent
variables were included which are socio-economic
characteristics (region, age, place of residence,
education, wealth-quintile, caste and religion), life-style
factors (smoking, consuming tobacco, and alcohol),
health-related factors (Body Mass Index, glucose level,
hypertension (systolic and diastolic), haemoglobin level).
These health-related factors were used as per WHO
standards.
Bivariate analysis and adjusted logistic regression
are used to see the effect of independent variables on
the dependent variables for objective one. For the
second objective the crude and adjusted odds ratio are
used to see the effect of independent variables on the
dependent variables and simultaneously the differences
between these two is highlighted. Crude logistic
regression is used to see the individual effect of predictor
on dependent variables and adjusted logistic regression
is used to see the adjusted effect of predictor on
dependent variables.
The logistic is usually put into a more compact form
as follows:

Exploring the Association of Life-style Factors and Health related Issues with the Non-Communicable Diseases 847
 








P
P
Yit 1
lnlog +1x1 +2x2 +3x3 .... +
.... kxk + 
where, 1, 2, ...., k are regression coefficients
indicating the relative effect of a particular explanatory
variable on outcome. The coefficients change as per
the context in the analysis.
3. Results
Table 1 shows the gender differences in the
prevalence of diabetes, asthma, and cardiovascular
diseases per 100 populations in India. The prevalence
Table 1: Prevalence (%) of Non-communicable Diseases by sex with background characteristics in India, NFHS-4 (2015-16).
Diabetes Asthma Cardiovascular diseases
Men Women Men Women Men Women
Total 2.15 1.69 1.45 1.94 1.18 1.35
Region
North 1.43 1.57 0.73 1.85 0.84 1.68
Central 1.21 1.24 1.13 1.34 0.87 0.32
East 1.97 1.11 1.80 0.98 1.66 1.44
North-East 1.70 1.95 0.66 1.94 1.22 1.13
West 1.62 1.80 1.28 1.92 0.61 1.32
South 4.05 1.72 2.14 2.21 1.73 1.47
Age
15-24 0.43 0.39 0.81 0.99 0.54 0.53
25-34 0.97 1.03 0.97 1.78 0.81 1.16
35-44 2.84 2.75 1.55 2.74 1.50 2.10
45-54 6.11 5.52 3.20 3.76 2.47 2.89
Place of Residence
Urban 2.72 2.59 1.28 2.06 1.12 1.24
Rural 1.80 1.21 1.56 1.88 1.22 1.42
Education
No education 1.86 1.61 2.28 2.25 1.67 1.83
Primary 2.29 2.14 2.28 2.44 1.63 1.84
Secondary 2.06 1.65 1.21 1.79 1.06 1.11
Higher 2.56 1.57 1.05 1.37 0.92 0.77
Wealth-Index
Poorest 1.12 0.80 1.90 1.74 1.48 1.43
Poorer 1.23 0.95 1.71 1.90 1.21 1.45
Middle 1.83 1.31 1.31 2.00 1.22 1.46
Richer 2.61 2.27 1.62 2.16 1.31 1.35
Richest 3.39 2.91 0.93 1.87 0.83 1.10
Caste
Scheduled Caste 1.93 1.48 1.59 1.83 1.22 1.42
Scheduled Tribes 1.19 1.12 1.96 1.79 1.51 1.11
Other Backward Class 2.21 1.67 1.56 1.93 1.17 1.30
Others 2.53 1.90 1.04 1.97 1.02 1.37
Religion
Hindu 2.09 1.61 1.50 1.96 1.17 1.28
Muslim 2.07 2.04 1.13 1.75 1.06 1.77
Christian 4.94 2.71 2.61 2.91 3.06 1.65
Sikh 2.05 1.71 0.53 1.33 0.52 1.60
Others 1.97 1.53 1.05 2.07 0.96 0.72
Socio-demographic
characteristics

848 Anuj Singh and Abhinesh Singh
of diabetes was higher among women, whereas the
prevalence of asthma, cardiovascular diseases was
higher among men.
Diabetes reported highest among higher educated
men and primary level educated women. Asthma and
cardiovascular disease reported highest among
uneducated men and primary level educated/
uneducated women. Marginalised sections of society
have shown less prevalence of diabetes and higher
prevalence of asthma and cardiovascular diseases.
Prevalence of diabetes was highest in richest-wealth
quintile and the prevalence of asthma and
cardiovascular diseases were highest in poorest wealth-
quintile. All these NCDs were more prevalent among
Christian population.
Table 2 shows the sex differences in the prevalence
of NCDs with the associated lifestyle factors and other
prevailing health issues.
Prevalence of smoking, consuming tobacco and
alcohol were found to be higher for these three
diseases. Obesity, very high glucose level, stage II
hypertension, and severe haemoglobin level were more
prevalent in these three diseases. Gender-wise
prevalence of diabetes was more among men and
prevalence of asthma and cardiovascular diseases were
more among women.
Table 3 presents the adjusted odds ratio for both
the sex to highlight the differences of odds of having
Table 2: Prevalence (%) of Non-communicable Diseases by sex with life style factors associated and other selected health
issues in India, NFHS-4 (2015-16).
Diabetes Asthma Cardiovascular diseases
Life style Factors Men Women Men Women Men Women
Smoking
Not smoking 1.98 1.69 1.40 1.93 1.04 1.35
Smoking 3.17 2.41 1.80 3.40 2.03 2.07
Tobacco consumption
Not consuming 2.30 1.67 1.37 1.87 1.10 1.31
Consuming 1.79 2.11 1.66 3.42 1.39 2.34
Alcohol consumption
Not consuming 1.85 1.67 1.18 1.92 0.97 1.34
Consuming 2.87 3.14 2.11 3.92 1.70 2.28
Health-related factors
BMI
Underweight 0.96 0.57 1.94 1.47 1.00 1.04
Normal 1.66 1.25 1.25 1.76 1.16 1.27
Overweight 4.36 3.55 1.75 2.89 1.41 1.86
Obese 7.11 6.10 1.49 3.60 1.96 2.44
Glucose Level
Normal 1.27 1.03 1.43 1.89 1.11 1.30
High 3.63 3.67 1.54 2.72 1.32 1.99
Very high 18.94 22.30 2.61 3.59 2.93 2.89
Blood Pressure
Normal 1.36 1.02 1.30 1.67 0.91 1.12
Pre-Hypertension 2.00 2.12 1.37 2.18 1.19 1.50
HBP-I 3.94 4.09 1.92 2.85 1.86 2.38
HBP- II 5.87 5.22 2.97 3.23 2.24 3.01
Haemoglobin
Normal 2.15 1.90 1.45 2.06 1.10 1.38
Mild 2.06 1.50 1.41 1.87 1.45 1.34
Moderate 2.64 1.62 2.00 1.85 1.76 1.35
Severe 3.15 1.51 4.16 2.30 1.34 1.46

Exploring the Association of Life-style Factors and Health related Issues with the Non-Communicable Diseases 849
Table 3: Adjusted Logistic Regression of selected Non-Communicable Diseases with background characteristics among
men & women in India, NFHS-4 (2015-16).
Diabetes Asthma Cardiovascular diseases
Background characteristics Adjusted OR CI (95%) Adjusted OR CI (95%) Adjusted OR CI (95%)
Men Women Men Women Men Women
Age
15-24®
25-34 1.75** 1.98** 1.35** 1.58** 1.49** 1.85**
(1.41- 2.16) (1.80-2.18) (1.11- 1.65) (1.48-1.68) (1.21- 1.85) (1.72- 1.99)
35-44 3.51** 4.02** 2.22** 2.53** 2.41** 3.21**
(2.88- 4.28) (3.67-4.41) (1.84- 2.69) (2.37-2.70) (1.96- 2.95) (2.99-3.45)
45-49 6.65** 6.66** 3.94** 3.40** 4.16** 4.15**
(5.47- 8.08) (6.04-7.34) (3.26- 4.76) (3.15-3.67) (3.40- 5.10) (3.82- 4.50)
Place of Residence
Urban®
Rural 1.05 0.87** 1.01 1.06** 0.94 1.09**
(0.94- 1.18) (0.83-0.92) (0.87- 1.17) (1.01-1.12) (0.81- 1.10) (1.03-1.16)
Education
No education®
Primary 1.25** 1.27** 1.08 1.09** 1.07 1.13**
(1.02- 1.53) (1.18-1.37) (0.90- 1.30) (1.02-1.16) (0.87- 1.32) (1.05-1.20)
Secondary 1.57** 1.35** 0.93 1.01 1.14 1.03
(1.32-1.86) (1.26-1.44) (0.79- 1.10) (0.96-1.07) (0.95- 1.36) (0.97-1.09)
Higher 1.83** 1.16** 0.84 0.81** 1.19 0.80**
(1.49- 2.25) (1.05-1.27) (0.66- 1.08) (0.74-0.89) (0.93- 1.53) (0.73- 0.89)
Wealth-Index
Poorest®
Poorer 0.94 1.08 0.99 1.11** 0.94 1.12**
(0.76- 1.16) (0.98-1.19) (0.83- 1.19) (1.04- 1.19) (0.77- 1.14) (1.04-1.20)
Middle 0.96 1.23** 0.77** 1.07 0.74** 1.08**
(0.78- 1.18) (1.12-1.36) (0.63- 0.94) (1.00-1.15) (0.60- 0.92) (1.01-1.17)
Richer 1.14 1.58** 0.84 1.11** 0.71** 1.07
(0.92- 1.41) (1.43-1.74) (0.68- 1.05) (1.03-1.20) (0.56- 0.89) (0.98-1.16)
Richest 1.46** 1.77** 0.63 1.02 0.64** 0.93
(1.16- 1.83) (1.59-1.97) (0.49- 0.82) (0.94-1.12) (0.49- 0.84) (0.84-1.02)
Caste
Scheduled Caste®
Scheduled Tribes 0.82 0.68** 1.04 0.83** 0.90 0.84**
(0.67- 1.00) (0.61-0.75) (0.85- 1.27) (0.76- 0.89) (0.72- 1.12) (0.78-0.92)
OBC 0.79** 0.89** 0.92 1.00 0.86 0.85**
(0.69- 0.91) (0.83-0.96) (0.79- 1.08) (0.94-1.06) (0.73- 1.02) (0.80-0.90)
Others 1.01 0.92** 0.80** 0.99 0.93 1.00
(0.87- 1.18) (0.85-0.99) (0.66- 0.98) (0.93- 1.06) (0.76- 1.13) (0.93- 1.07)
Table 3 continued...

Religion
Hindu®
Muslim 1.22** 1.31** 1.44** 0.95 1.21 1.51**
(1.03- 1.45) (1.23-1.41) (1.20- 1.74) (0.88-1.01) (0.99- 1.49) (1.41-1.61)
Christian 1.39** 0.97 1.59** 1.15** 1.57** 1.85**
(1.12- 1.72) (0.87-1.09) (1.20- 2.11) (1.05- 1.26) (1.20- 2.06) (1.70-2.02)
Sikh 1.08 0.73** 0.52** 0.68** 0.56 1.23**
(0.78- 1.51) (0.63-0.85) (0.27- 0.99) (0.58-0.79) (0.32- 1.00) (1.06-1.43)
Others 0.97 0.84 0.81 0.83** 0.95 0.80**
(0.69- 1.36) (0.71- 1.00) (0.52- 1.27) (0.72-0.96) (0.62- 1.45) (0.69-0.94)
Region
North®
Central 0.95 0.70** 0.89 0.89 0.74** 0.27**
(0.80- 1.14) (0.61-0.81) (0.73- 1.09) (0.79- 1.01) (0.61- 0.91) (0.21- 0.33)
East 1.57** 0.80** 1.31** 0.75** 1.18 0.92
(1.30- 1.89) (0.73-0.89) (1.06- 1.63) (0.68-0.82) (0.95- 1.45) (0.85- 1.01)
North-East 1.20 0.96 0.41** 1.26** 0.66** 1.13**
(0.95- 1.51) (0.89-1.03) (0.30- 0.57) (1.18- 1.35) (0.50- 0.88) (1.06- 1.20)
West 1.09 1.05 1.28** 1.38** 0.50** 0.90**
(0.89- 1.33) (0.96-1.16) (1.02- 1.61) (1.27- 1.50) (0.37- 0.67) (0.82-0.98)
South 2.28** 0.94 2.02** 1.14** 1.50** 0.92**
(1.93- 2.69) (0.87-1.01) (1.65- 2.46) (1.07-1.21) (1.23- 1.83) (0.86- 0.98)
Note: ® Reference category; **P < 0.05
Table 3 continued...
NCDs with reference to background characteristics.
Odds of having diabetes among women were more
in urban areas. Odds of having diabetes increases as
education level increases, and among men it was more
prevalent than women. Odds of having diabetes were
highest among the richest and among women it was
more prevalent. Odds of having diabetes among men
was 1.39 times higher in Christian among women it
was 1.31 times higher in Muslim. Odds of having asthma
among women were 1.06 times in rural area. Odds of
having asthma decreases as wealth quintile increases.
Odds of having asthma were highest among Christian’s.
Odds of having cardiovascular diseases among women
were 1.09 times higher in rural areas. Odds of having
cardiovascular diseases decreases as wealth quintile
increases. Odds of having cardiovascular diseases were
highest among Christian’s.
Table 4 shows the results of crude and adjusted
logistic regression analyses for the life style factors and
health-related factors with the prevalence of diabetes,
asthma, and cardiovascular diseases for men. The
individual effect of each predictor is more than the
combined effect on dependent variables. Obesity and
very high glucose level show strong positive correlation
with diabetes individually. Stage II hypertension and
consumption of alcohol is positively correlated with
asthma and cardiovascular diseases as it shows the
major effect.
Table 5 shows the results of logistic regression
analyses for the life style factors associated and health-
related issues with diabetes, asthma and cardiovascular
diseases for women. Here, crude odds ratio of obesity,
very high glucose level and stage II hypertension are
positively correlated with diabetes, asthma and
cardiovascular diseases at very large extent compared
to the predictors in the adjusted odds ratio.
4. Discussion
In this study, we tried to find out the association of
life-style factors and health-related factors with the
selected NCDs. Our results indicate that there is
association between these factors and selected NCDs.
Unhealthy lifestyle increases the risk of NCDs and it
has strong positive correlation with smoking, alcohol
intake and obesity [Lohse et al. (2016) and Chakma &
850 Anuj Singh and Abhinesh Singh

Exploring the Association of Life-style Factors and Health related Issues with the Non-Communicable Diseases 851
Table 4: Crude and adjusted Logistic Regression of Non-Communicable Diseases with life style factors & other health
issues among men in India, NFHS-4 (2015-16).
Diabetes Asthma Cardiovascular diseases
Model-1 Model-2 Model-1 Model-2 Model-1 Model-2
COR AOR9 COR AOR COR AOR
95% CI 5% CI 95% CI 95% CI 95% CI 95% CI
Smoking
Not Using®
Using 1.37** 1.23** 1.17** 1.15 1.75** 1.48**
(1.23- 1.52) (1.08- 1.40) (1.02- 1.34) (0.98- 1.35) (1.54- 1.98) (1.27-1.71)
Tobacco Use
Not Using®
Using 0.77** 0.81** 1.16** 1.02 1.20** 1.11
(0.70- 0.85) (0.72-0.92) (1.04- 1.29) (0.90- 1.17) (1.08- 1.35) (0.97-1.27)
Alcohol Use
Not Using®
Using 1.30** 1.08 1.45** 1.19** 1.46** 1.14**
(1.19- 1.42) (0.97-1.21) (1.30- 1.61) (1.05- 1.36) (1.31- 1.63) (1.00- 1.31)
BMI
Underweight®
Normal 1.78** 1.09 0.72** 0.63** 1.05 0.87
(1.52- 2.08) (0.91-1.29) (0.63- 0.82) (0.54- 0.72) (0.90- 1.22) (0.73-1.03)
Overweight 4.28** 1.46** 0.90 0.67** 1.47** 1.04
(3.63- 5.05) (1.20-1.77) (0.75- 1.06) (0.54- 0.82) (1.23- 1.76) (0.83-1.29)
Obese 7.44** 1.81** 1.10 0.87 1.73** 1.17
(6.05- 9.15) (1.41-2.32) (0.81- 1.48) (0.62- 1.21) (1.28- 2.34) (0.82-1.65)
Glucose Level
Normal®
High 2.34** 1.68** 1.18 0.98 1.28** 0.93
(1.95- 2.82) (1.37-2.05) (0.92- 1.52) (0.75- 1.28) (1.00- 1.64) (0.70-1.23)
Very high 16.49** 9.33** 1.64** 1.06 2.33** 1.55**
(14.96-18.17) (8.34- 10.44) (1.32- 2.04) (0.83- 1.35) (1.92- 2.83) (1.25-1.92)
Blood Pressure
Normal®
Pre-Hypertension 1.37** 0.93 0.99 0.96 1.07 0.92
(1.23- 1.54) (0.82-1.05) (0.87- 1.13) (0.84- 1.10) (0.93- 1.22) (0.80-1.07)
HBP-I 2.46** 1.00 1.33** 1.09 1.59** 1.11
(2.16- 2.81) (0.86-1.16) (1.13- 1.58) (0.91- 1.31) (1.34- 1.88) (0.92- 1.33)
HBP-II 3.63** 1.07 1.66** 1.22 2.06** 1.17
(3.03- 4.34) (0.87-1.31) (1.29- 2.15) (0.93- 1.60) (1.60- 2.63) (0.88-1.53)
Haemoglobin
Normal®
Mild 0.98 1.06 0.99 0.85 1.09 1.08
(0.87- 1.10) (0.93-1.21) (0.86- 1.15) (0.73- 1.00) (0.95- 1.26) (0.93-1.27)
Moderate 1.10** 1.31** 1.19 0.93 1.32** 1.13
(1.10- 1.61) (1.05- 1.63) (0.93- 1.53) (0.71- 1.22) (1.03- 1.68) (0.87- 1.49)
Severe 1.54 1.27 1.50 1.09 1.32 0.92
(0.95- 2.51) (0.73- 2.21) (0.82- 2.74) (0.56- 2.13) (0.68- 2.57) (0.41- 2.09)
Note: ® Reference category; **P<0.05
Life Style Factors & other
Health Issues

Table 5: Crude and Adjusted Logistic Regression of Non-Communicable Diseases with life style factors & other health
issues among women in India, NFHS-4 (2015-16).
Model-1 Model-2 Model-1 Model-2 Model-1 Model-2
COR AOR COR AOR COR AOR
95% CI 95% CI 95% CI 95% CI 95% CI 95% CI
Smoking
Not Using®
Using 1.08 0.98 1.44** 1.12 1.81** 1.20**
(0.91- 1.29) (0.80-1.19) (1.25- 1.65) (0.96-1.30) (1.59- 2.07) (1.04-1.38)
Tobacco Use
Not Using®
Using 1.17** 0.95 1.64** 1.24** 1.99** 1.37**
(1.08- 1.26) (0.87-1.04) (1.55- 1.74) (1.16- 1.33) (1.88- 2.11) (1.28-1.46)
Alcohol Use
Not Using®
Using 1.00 1.22** 1.51** 1.49** 1.48** 1.27**
(0.88- 1.15) (1.04-1.43) (1.37- 1.67) (1.33-1.67) (1.33- 1.64) (1.12-1.42)
BMI
Underweight®
Normal 1.95** 1.30** 1.13** 1.00 1.27** 1.02
(1.81- 2.11) (1.19- 1.42) (1.07- 1.19) (0.94-1.06) (1.20- 1.34) (0.96-1.09)
Overweight 6.05** 1.85** 1.91** 1.39** 1.96** 1.23**
(5.59- 6.55) (1.68-2.04) (1.79- 2.03) (1.29-1.49) (1.83- 2.09) (1.14-1.33)
Obese 11.16** 2.23** 2.63** 1.82** 2.57** 1.57**
(10.23-12.17) (2.00- 2.49) (2.43- 2.85) (1.66- 1.99) (2.36- 2.80) (1.42-1.74)
Glucose Level
Normal®
High 3.52** 2.31** 1.52** 1.14** 1.50** 1.07
(3.23- 3.83) (2.10-2.53) (1.39- 1.67) (1.03-1.25) (1.36- 1.65) (0.96-1.19)
Very high 28.47** 14.45** 1.98** 1.17** 2.15** 1.34**
(27.17-29.82) (13.69-15.25) (1.81- 2.17) (1.06-1.30) (1.97- 2.35) (1.22- 1.48)
Blood Pressure
Normal®
Pre-Hypertension 2.07** 1.20** 1.27** 0.98 1.26** 0.94**
(1.97- 2.17) (1.14-1.27) (1.22- 1.33) (0.94-1.03) (1.21- 1.32) (0.89-0.98)
HBP-I 4.07** 1.37** 1.78** 1.08** 1.97** 1.10**
(3.83- 4.33) (1.27- 1.47) (1.67- 1.90) (1.01-1.16) (1.85- 2.10) (1.03-1.19)
HBP-II 5.54** 1.48** 2.01** 1.11 2.78 ** 1.44**
(5.06- 6.06) (1.33-1.65) (1.81- 2.24) (0.99-1.24) (2.52- 3.06) (1.29-1.60)
Haemoglobin
Normal®
Mild 0.80** 0.94** 0.89** 0.95 0.88** 0.98
(0.76- 0.84) (0.88-0.99) (0.85- 0.94) (0.91- 1.00) (0.83- 0.92) (0.92-1.03)
Moderate 0.79** 0.97 0.89** 0.96 0.86** 0.95
(0.75- 0.83) (0.92-1.03) (0.85- 0.93) (0.92-1.01) (0.82- 0.90) (0.90-1.00)
Severe 0.84** 1.02 1.10 1.18** 0.97 1.03
(0.73- 0.97) (0.87-1.20) (0.98- 1.24) (1.04-1.34) (0.85- 1.10) (0.89- 1.19)
Note: ® Reference category; **P<0.05
Life Style Factors & other
Health Issues
852 Anuj Singh and Abhinesh Singh

Gupta (2017)]. These associations led to mortality and
morbidity in India due to chronic NCDs and shortage
of health-care services in coming decades [Rufi and
Khan (2021)]. Various studies have highlighted the
physical activity as prevention against NCDs. Physical
activity reduces fat, blood pressure and controls blood
glucose level [Booth et al. (2012), Ranasinghe et al.
(2013)].
5. Conclusion
In this study, we found that age, obesity, glucose
level, hypertension, smoking, consuming tobacco and
alcohol are mostly increases the risk of diabetes, asthma,
and cardiovascular diseases. Study also found out that
the prevalence of diabetes were found to be more in
educated class whereas asthma and hypertension were
found to be more prevalent in uneducated or low
educated people for both the sexes. Crude and adjusted
odds ratio depicted the clear picture of each predictor’s
effect on the dependent variable individually or in
combined form for three diseases and for both the sexes.
This individual effect will let all know the major causes
of diseases and will help in creating public awareness
and providing health-care.
Acknowledgement
Authors are thankful to the anonymous reviewers
for their insightful comments and providing directions
for additional work which has resulted in this paper.
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