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 Table of Contents  
Year : 2022  |  Volume : 7  |  Issue : 2  |  Page : 294-301

Comparison of demographic, socioeconomic, and lifestyle determinants in infertile and fertile males and females from two big cities of Punjab

1 Department of Genetics, Sri Guru Ram Das University of Health Sciences, Amritsar, India
2 Department of Physiology, Sri Guru Ram Das University of Health Sciences, Amritsar, India
3 Department of Obstetrics & Gynaecology, Sri Guru Ram Das University of Health Sciences, Amritsar, India
4 Department of Human Genetics, Guru Nanak Dev University, Amritsar, India
5 Beri IVF Centre, Amritsar, India
6 Iqbal Nursing Home & IVF Centre, Ludhiana, Punjab, India

Date of Submission27-May-2022
Date of Decision14-Jun-2022
Date of Acceptance16-Jun-2022
Date of Web Publication09-Sep-2022

Correspondence Address:
Richa Ghay Thaman
1- Sant Avenue, The Mall, Amritsar, Punjab
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/bjhs.bjhs_99_22

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BACKGROUND: Infertility is an apparent failure of a couple to conceive. The demographic, socioeconomic, and lifestyle determinants in infertility and its related factors should be seen more realistically. Regional variations in the causes of infertility need a completely comprehensive approach that helps to dive deeper into the root cause of the disease and manage it holistically.
MATERIALS AND METHODS: A study on selected risk factors of infertility among 100 infertile couples and 200 fertile males, females attending tertiary health-care centers and in vitro fertilization centers from two big cities of Punjab was conducted. The data were collected using semi-structured pro forma questionnaire. The data collected included the anthropometric measurements, demographic profile, lifestyle variables impacting infertility, and socioeconomic attributes. Data were analyzed to look out for risk factors and their association using the odds ratio.
RESULTS: The findings of the study revealed that nonvegetarian diet, more tea and alcohol usage, smoking abuse, and duration of mobile phone usage were seen more in infertile couples which was statistically significant in relation to fertile participants. Occupation, physical activity, sleep, socioeconomic variables, and education status did not show any statistical significance when compared between the two groups. Interestingly, statistical significance was seen in the obese class II category only in infertile males in comparison to fertile males.
CONCLUSION: An all-inclusive perspective is needed for the diagnosis, treatment, and management of infertility. Health-care professionals need to dive into aspects of infertility treatment other than medical interventions to provide an integrated treatment regimen for couples facing infertility.

Keywords: Adiposity, infertility, lifestyle variables, sleep, socioeconomic profile

How to cite this article:
Kaur S, Thaman RG, Sood R, Sambyal V, S Sandhu I M, Beri A, Chawla M S. Comparison of demographic, socioeconomic, and lifestyle determinants in infertile and fertile males and females from two big cities of Punjab. BLDE Univ J Health Sci 2022;7:294-301

How to cite this URL:
Kaur S, Thaman RG, Sood R, Sambyal V, S Sandhu I M, Beri A, Chawla M S. Comparison of demographic, socioeconomic, and lifestyle determinants in infertile and fertile males and females from two big cities of Punjab. BLDE Univ J Health Sci [serial online] 2022 [cited 2023 Jun 3];7:294-301. Available from: https://www.bldeujournalhs.in/text.asp?2022/7/2/294/355861

Infertility is estimated to affect as many as 186 million people worldwide. The World Health Organization defines an infertile relationship as a disease of the reproductive system, in which there is a failure to achieve a clinical pregnancy after 12 months or more of being sexually active and noncontracepting.[1],[2] The reported prevalence of infertility is 12.5% among women and 10.1% among men. The two types of infertility are primary and secondary infertility. Primary infertility refers to couples who have not become pregnant after at least 1 year of being sexually active without using birth control methods. Secondary infertility refers to couples who have been able to get pregnant at least once but now is unable to conceive.[3] The major causes of infertility in females are polycystic ovary syndrome (PCOS), endometriosis, uterine fibroids, premature ovarian insufficiency, tubal blockage, and in males, it is related to testicular deficiency or the diseases that can concern either of the sex like systematic diseases, infections, hyperprolactinemia, and hypogonadotropic hypogonadism while many cases of infertility remain unexplained, i.e., idiopathic, but the answer may be in the epigenome.[4]

The epigenome is dynamic and can be modified by environmental factors and lifestyle choices. Various lifestyle choices disrupt biological pathways and cause oxidative stress. Oxidative stress, an abnormal oxidation status in human cells has been related to various chronic diseases, such as diabetes, cardiovascular, PCOS, cancer, and neurological diseases.[5]

Genetic and various environmental factors which include infections, parasitic diseases, lifestyle, stress, postponing parenthood, obesity may be considered an essential determinant of infertility. Apart from the genetic, epigenetic or physiological causes of infertility, various lifestyle factors such as unhealthy diet, decreased physical activity, alcohol consumption, and smoking are suggested as potential risk factors for disrupted semen quality in men and ovulatory function in women.[6],[7]

The objective of the present study was to assess the demographic, socioeconomic, and lifestyle determinants of infertility and to compare the determinants assessed with those of fertile males and females.

  Materials and Methods Top

Study design

The study design involves a case–control study.

Study setting

Three study centers were chosen. A tertiary health-care medical institute from Amritsar, An in vitro fertilization (IVF) center in Amritsar and IVF center from Ludhiana city of Punjab.

Fertile participants were included from the general population and from hospital settings.

Study subject


Inclusion criteria

One hundred clinically confirmed infertile couples (100 males, 100 females) having no live births were selected. The inclusion criteria for sampling were the age 20–40 years of the couple. Patients were selected using the criterion sampling technique. Written informed consent was obtained from the cases.

Exclusion criteria

The infertile couples above the age of 40 years were excluded from the study. The cases who denied informed consent were also excluded from the study.


Inclusion criteria

Two hundred controls (100 males, 100 females) were age- and gender-matched healthy individuals having children conceived by natural methods residing in the same geographical area as that of the patients and showing no signs of any malignancy or chronic disease.

Exclusion criteria

The exclusion criteria for controls were individuals suffering from any chronic or malignant disease, or individuals having conceived children out of IVF/IUI/any other ART procedure.


The study was given ethical clearance by the Institutional Ethical Committee of the medical Institute (ref no. Patho 927/2018.dated 03/11/2018). The interviews were conducted between period of January 2019 to May 2021. The semi-structured questionnaire pro forma was designed to record the history details, examination details, and investigation details of participants. The questionnaire was reviewed by faculty members and their suggestions were incorporated. The questionnaire was pilot tested on five couples and thus validated. The written informed consent was taken from all participants in English and vernacular language (Punjabi, Hindi). Data were collected with face-to-face in-depth interviews. The case records of the patients were also referred. The confidentiality of the patients was maintained and a unique patient code was given to all the patients. Participants were encouraged to express their experiences freely and without any restrictions. The length of the interview lasted from 20 min to 35 min per couple. The interviews were conducted in the separate counseling room.

The demographic parameters, habitat, religion, caste/subcaste of patient couples, and matched controls were noted down. The history details also included the dietary habits, caffeine/tea intake, occupation, smoking, physical activity, and mutagenic exposure carried out by patients and age-matched controls. Various parameters of clinical investigations were recorded from case records.

Statistical analysis

Sample size calculation

Sample size was calculated using Epi Info software version (Epi Info is a free to use statistical software for epidemiology developed by Centers for Disease Control and Prevention (CDC) in Atlanta, Georgia (US)) using the previous study.[8] The sample size of 90 couples at 97% confidence interval and alpha error of 5% was estimated with a power of 85. Based on it, the sample size of 100 infertile couples was selected for the present study.

A summary of the data obtained from the pro forma was entered into excel sheets. Data were represented as percentage for categorical data, mean ± standard deviation (SD) for demographic continuous data. A Chi-square test was applied to all the continuous variables of demographic data. A P < 0.05 was considered statistically significant, whereas P < 0.001 was considered highly significant for all the tests. The P values of all the variables have been calculated using Medcal C software (MedCalc is the flagship product of MedCalc Software Ltd- based in Ostend, Belgium).

  Results Top

In the present study, mean duration of marriage among infertile participants was 5.6 years ± SD (1 year and 3 months – 16 years) and the mean duration for trying for conception was 4.36 years ± SD (1 year –16 years). The cause of infertility was unknown/idiopathic for 38 couples, whereas 35 couples were diagnosed with the female cause of infertility and 19 with male cause and 8 couples with male as well as female factors as the cause of infertility.

Demographic profile of infertile couples and matched controls

General demographic findings of the participants revealed the mean age of participants as 32 years ± SD (31.61 years).

The mean age of infertile participants was 32 years (31.61 years), whereas the mean age of controls was also 32 years (31.82 years). Majority of the infertile patients (57%) were above 30 years of age [Table 1]. About 74.5% of infertile couples reside in urban areas. The religion and caste/subcaste of cases and controls were calculated to be statistically significant which implies the random sampling for data collection is in accordance with the distribution of population in the region.
Table 1: Demographic profile of Infertile/Fertile Participants

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Anthropometric measurements of cases and controls

Height, weight, waist circumference, and hip circumference of each subject were taken using standard methods.[9] Classification of subjects on the basis of body mass index (BMI) was done by using WHO criteria for the Asian population (WHO, 2004). The assessment of abdominal adiposity was made using a waist circumference cut-off value; 85 cm for men and 80 cm for women and waist–hip ratio as 0.88 for men and 0.81 for women, recommended for the Asian population.[10]

Only 20% of infertile males and 9% of fertile males were of obese class II which was statistically significant [Table 2], while infertile (11%) and fertile females (4%) showed no statistical significance in obese class II for BMI.
Table 2: Body mass index profile of patients and controls

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The adiposity of patients and controls was calculated by waist–hip ratio (waist circumference/hip circumference). Majority of infertile males (93%) and infertile females (94%) were found to be of increased adiposity. In comparison with controls, 91% of fertile males and 92% of females also showed increased adiposity [Table 3].
Table 3: Waist-hip ratio measurements of both groups

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In the present study, 22.5% of infertile males who were adipose with waist–hip ratio of more than 0.89 also suffered from abnormal semen parameters.[11] The infertile females with adiposity approximately 27.6% also showed anovulatory menstrual cycles [Table 3].

Lifestyle variables

[Table 4] shows that 74% of infertile males and 54% of controls had nonvegetarian diet though the frequency of taking meat or eggs was reported as once or twice in a week. The diet pattern of cases and controls was found to be statistically significant. The tea intake in infertile males was statistically significant in relation to controls. Alcohol drinking (63%) and smoking (7%) were reported in male patients with a variability of 1% in females. Alcohol drinking and smoking abuse were found to be statistically significant.
Table 4: Lifestyle variables of infertile Males & fertile controls

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About 14% of male patients were farmers; other 18% ran their own business and approximately 52% were Engineers/IT professional by profession. The occupation of participants was asked to assess any type of occupational mutagenic/teratogenic/radiations the participant is exposed to due to their work profile. There have been pesticide/fertilizer exposures in participants doing farming. About 50% of male patients were doing the light physical activity which was statistically nonsignificant.

The diet pattern and physical activity of infertile females with their fertile controls showed statistical significance [Table 5].
Table 5: Lifestyle variables of infertile Females & fertile controls

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Higher number of patients were exposed to electromagnetic radiations emitted through mobile phone usage for a longer duration (>5 h) in a day [Table 6]. In infertile males (77%), the duration of mobile phone usage was found to be significantly higher as compared to control males (30%). The same pattern has been observed in infertile females (71%) and fertile controls (10%). The longer duration of mobile phone usage and infertility has been found to be statistically significant.
Table 6: Duration of mobile phone usage in infertile/fertile participants

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The sleep history was noted from the patients and controls. The sleep history in infertile male and female and fertile male and female showed statistical significance. It has been observed that females in both groups reported lesser hours of sleep in comparison to males, but no statistical significant difference in sleep hours was reported among both groups, as shown in [Table 7].
Table 7: Details of sleep history in Infertile/fertile participants

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Socioeconomic demographic profile of infertile patients and controls

The income group of patients and controls varied from the economically weaker section (EWS) of society, lower income group (LIG), middle income group I (MIG I), and middle-income group II (MIG II).[12] The family annual income up to 3 lakhs INR is categorized in EWS, LIG comprised annual income up to 6 lakhs INR, MIG I up to 12 lakhs INR, MIG II up to 18 lakhs INR.

A large percentage of infertile couples (46%) belonged to LIG with approximately same percentage of controls (57%) in the same economic group (LIG). Only 14% couples reportedly belonged to middle income group II (MIG II). The case–control comparison for income group was found to be statistically nonsignificant [Table 8].
Table 8: Income group variable of cases and controls

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The educational status of infertile patients and controls ranged from primary level of education to Master's degree.

[Table 9] shows that 66% infertile and 61% of fertile males had graduate and or postgraduate degree whereas 79% of infertile and 79% of fertile females had graduate and or postgraduate degrees. In our study, females were more qualified than their male counterparts.
Table 9: Case-control study of educational status and infertility

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  Discussion Top

Infertility is a worldwide health problem with one in six couples suffering from it and posing a major economic burden on the global health-care industry. Demographic characteristics of the infertile couples are one of the factors influencing infertility. There is an increase in the prevalence of infertility as people's lifestyle evolves with time. An increase in nicotine and alcohol usage, population aging, difficult living standards, and various psychological parameters are all factors that contribute to the rise in infertility.[13] In the present study, the anthropometric variables, demographic characteristics, and lifestyle attributes for all the participants (fertile/infertile) have been measured and compared.

Various epidemiological studies on infertility from almost every region of India show that the age of women and their age at marriage has a significant influence on primary infertility[14] which is depicted in the present study also. Approximately 57% of infertile couples were above the age of 30 years who postponed conception thereby leading to infertility. The present study also showed a higher number of infertile couples from urban areas (74.5%) visiting tertiary health-care hospital/IVF clinics as compared to rural couples (25.5%) suggesting that urban couples are more prone to infertility as compared to rural, indicating the presence of different environmental, lifestyle causes related to infertility.[15],[16] However, the huge difference in urban and rural participants may also be because of the location of the institute and infertility centers in urban areas and more urban people motivated to seek treatment from a registered medical practitioner.

In the present study, approximately 27.6% of infertile females who had anovulatory cycles had higher waist–hip ratios and obesity. Large number of studies also show the correlation of obesity and infertility in males and females. In obese women, there is a higher level of circulating free fatty acids which damage nonadipose cells and increase reactive oxygen species (ROS), thereby increasing mitochondrial stress and resulting in apoptosis of multiple cell types mainly oocytes in females.[17] Fedorcsák et al. highlighted the influence of female obesity on various fertility treatments. The overweight and obese women have been shown to have lower outcomes after fertility treatment than females of normal BMI. Obese women respond poorly to induction of ovulation, require higher doses of gonadotropins and go through longer treatment courses for follicular development and ovulatory cycles.[18]

The present study also showed increased adiposity and abnormal semen parameters in 22.5% of infertile male patients. A cross-sectional study assessed the potential role of central obesity in males by assessing the difference between BMI and WHR and their relationship with selected semen parameters. The findings indicated a possible role of central obesity for progressive motility of sperms in semen sample.[19],[20]

In the present study, 19% of infertile males consuming nonvegetarian diet showed abnormal sperm parameters as compared to this only 4% of infertile males in our study with abnormal semen parameters were on plant-based vegetarian diet. Kljajic et al. did a comparison of sperm parameters and acrosome reaction assessment between vegan and nonvegan diet consumers and provided an additional evidence to the existing literature about the favorable effect of a plant-based diet on sperm parameters.[21]

The evidence from the large number of studies suggests that damage in spermatozoa may be associated with the direct binding of tobacco smoke constituents to sperm deoxyribonucleic acid (DNA) molecule in males. Cigarette smoke contains toxic ROS that develop adducts which are mutagenic in nature.[22],[23] In females, smoking is related to impaired fecundity, increased risk of spontaneous abortion, and ectopic pregnancy. The adverse effect of passive smoking has been well established. The evidence show that excessive exposure to tobacco smoke has reproductive consequences equal to those observed in smokers.[24],[25] In the present study, 7% infertile males reported tobacco smoking which may have passively affected their female counterparts. At the same time, we want to bring forth that Punjab being a Sikh-dominated region, the total number of smokers is much less in the population in relation to the rest of the country.

Statistically significant alcohol consumption is seen in infertile males in comparison to fertile males in our study. Sabarre et al. reported reduced sperm count, with reduced motility and number of normal morphology sperm in men with alcohol consumption.[26] Alcohol is one of the most used recreational substances. It has effect on ovarian reserve, steroid hormone production, sperm quality, and fecundability and also effect fertility treatments. In our studies, only 3% of women reported alcohol consumption in the infertility group, while none in the fertility group, this was statistically insignificant.[27]

Mirzaei et al. found the prevalence of infertility to be higher in women with low frequency or intensity of physical activity. They found that the chance of infertility is 3.5 times higher in women with lower physical activity (Light).[28] Recent studies also showed that moderate physical activity improves ovarian function curbing insulin insensitivity in females, thereby improving the reproductive ovarian potential of the women. In the present study, only 41% of obese infertile participants reported light physical activity. Physical activity in men in our study in both groups shows no statistical significance. However, interestingly, physical activity is higher in infertile women in comparison to the control group and it is statistically significant, unlike other studies. It appears that physical activity is not really contributing to infertility in our study. In fact, infertile women may have more time at hand to carry on with some exercise regime.

Interestingly, in our study, 88% of infertile males and 80% of fertile males were overweight/obese. Only in the obese class II category, there had been more infertile males than fertile controls which was statistically significant. Further in our study, 65% of infertile females were overweight/obese in comparison to 69% of fertile females which was statistically insignificant. It is engrossing to note that according to the national family health survey of overweight/obese males/females in the general demographic distribution of Punjab, only 35.2% of males and 44.3% of females were overweight/obese.[29]

Sleep dysregulation may alter successful conception through the suppression or augmentation of reproductive hormones. Much data to date exists and provides support for the concept that sleep, sleep disturbances, sleep deprivation, and/or circadian factors are associated with reproductive capacity in general and fertility in specific.[30] Sleep continuity disturbance/insomnia disorder disproportionately affects women more compared to men. In our study, 60% of Infertile women reported <6 h of sleep at night. Approximately 3% of infertile women reported irregular sleep patterns suggesting of Insomnia disorder. However, interestingly, males were sleeping more than women in both groups which were statistically significant. A survey reported that 71% of women sleepless in India even though they require 20 min more sleep then men due to household chores and unequal division of work. Similar results came forward in our study.[31]

In the present study, approximately 64% of infertile males and females had a longer duration of mobile phone usage, i.e., >5 h in a day as compared to controls. Most of the patients reported a longer duration of mobile phone usage as an excuse to deal with their anxieties and to pass their time. We have found evidence to this effect for male infertility studies.

Radiofrequency electromagnetic radiation (RF-EMR) from the frequency range and power density of cell phones has been studied to increase mitochondrial ROS production in human spermatozoa and sperm DNA disintegration. A long-term exposure to EMR affects the male germ cells in humans.[32] The constant exposure to EMR in another study altered pituitary function, thereby affecting Leydig and Sertoli cells in the male rats profoundly impacting male fertility. The scrotal hyperthermia with increased oxidative stress is possibly the key mechanisms by which EMR affects male fertility and these negative consequences are in alliance with the duration of mobile phone (cell phone) usage.[33] Zhang et al. examined an association between mobile phone internet use and poor sperm quality. The findings of the cohort study encapsulated that EMR from mobile phones negatively impacts sperm quality by lowering the semen volume, count, and concentration of sperm, thus affecting male fertility.[34],[35]

In our study, educational status and income, group variables showed an insignificant correlation to infertility. It revealed that women were better educated than their male counterparts in both groups. Educational attainment and standard of living are other significant factors influencing infertility, and its prevalence decreases with an increase in educational attainment and standard of living because of better awareness. In our study, we found 50% of infertile couples from the good economic background and good educational background coming forward to seek treatment.[36]

  Conclusion Top

Infertility has been the universal barrier affecting people all over the world. It is a difficult process to overcome but dealing with infertility is conducive to pursue a positive family-building journey in the future. Modification of lifestyle apart from various clinical parameters, evaluation of lifestyle factors, and optimizing weight and adiposity may benefit infertile couples. The present study highlights that having a healthy lifestyle, which includes a holistic approach to healthy living with healthy nutrition, following a circadian rhythm of sleep, no substance abuse, maintaining optimum body weight, less duration of exposure to EMR from mobile phones, cutting down on mental stress, with no holding up to the time to conceive can improve the chances of conception in couples. A comprehensive approach is required for the diagnosis, treatment, and management of infertility, analyzing the demographic, socioeconomic, and lifestyle determinants of infertility, thereby significantly helping to reduce the number of idiopathic infertility diagnoses.

Limitation of our study

The study will hold more significance if we increase the sample size. Our study had a small sample size.


The author would like to acknowledge all the participants of the study for giving me time and sharing their experience with me.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

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  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8], [Table 9]


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